Complete Execution Output (JSON):
{
"aml_screening": {
"adverse_media": "no_hits",
"aml_status": "cleared",
"compliance_score": 96.8,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aml_status\": \"cleared\", \"watchlist_check\": \"no_matches\", \"pep_screening\": \"not_identified\", \"sanctions_check\": \"cleared\", \"adverse_media\": \"no_hits\", \"risk_rating\": \"low\", \"compliance_score\": 96.8, \"screening_date\": \"2024-07-15\", \"manual_review_required\": false}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
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"end_time": "2025-07-16T06:58:42.730487",
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"start_time": "2025-07-16T06:58:42.534006",
"timestamp": "2025-07-16T06:58:42.730487",
"worker_executed": true,
"workers_notified": true
},
"manual_review_required": false,
"output": "__OUTPUTS__ {\"aml_status\": \"cleared\", \"watchlist_check\": \"no_matches\", \"pep_screening\": \"not_identified\", \"sanctions_check\": \"cleared\", \"adverse_media\": \"no_hits\", \"risk_rating\": \"low\", \"compliance_score\": 96.8, \"screening_date\": \"2024-07-15\", \"manual_review_required\": false}\n",
"pep_screening": "not_identified",
"return_code": 0,
"risk_rating": "low",
"sanctions_check": "cleared",
"screening_date": "2024-07-15",
"status": "completed",
"stderr": "",
"task_id": "aml_screening",
"watchlist_check": "no_matches"
},
"analyze_bank_statements": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"account_details\": {\n \"account_holder_name\": \"N/A\",\n \"account_number\": \"N/A\",\n \"bank_name\": \"N/A\",\n \"branch_name\": \"N/A\",\n \"ifsc_code\": \"N/A\"\n },\n \"monthly_inflow_outflow_patterns\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"net_flow\": 0,\n \"inflow_trends\": [],\n \"outflow_trends\": []\n },\n \"salary_credits\": {\n \"salary_credit_amount\": 0,\n \"salary_credit_frequency\": \"N/A\",\n \"consistency\": \"N/A\"\n },\n \"transaction_patterns\": {\n \"total_transactions\": 0,\n \"transaction_types\": [],\n \"average_transaction_amount\": 0\n },\n \"balance_behavior\": {\n \"average_balance\": 0,\n \"minimum_balance\": 0,\n \"maximum_balance\": 0,\n \"balance_trends\": []\n },\n \"loan_emis\": {\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": []\n },\n \"compliance_indicators\": {\n \"suspicious_activities\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_ratios\": {\n \"debt_to_income_ratio\": 0,\n \"current_ratio\": 0,\n \"liquidity_ratio\": 0\n },\n \"verification_score\": {\n \"ocr_quality\": 0,\n \"data_completeness\": 0,\n \"overall_verification_score\": 0\n },\n \"analysis_summary\": {\n \"status\": \"incomplete\",\n \"reason\": \"OCR extraction failed with an error, and no application data is available for cross-verification.\"\n }\n}\n```",
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"actual_result": {
"agent_type": "assistant",
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"agent_type": "assistant",
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"model": "gpt-4o-mini",
"output_length": 1325,
"provider": "openai",
"system_message": "You are an expert financial analyst. Analyze the OCR extracted text from a bank statement and cross-verify with application data.\n\nExtract and analyze:\n1. Account details and account holder information\n2. Monthly inflow and outflow patterns\n3. Salary credits and their consistency\n4. Transaction patterns and financial behavior\n5. Balance behavior and trends\n6. Loan EMIs and existing financial obligations\n7. Compliance indicators and suspicious activities\n8. Financial ratios and stability metrics\n\nReturn the data in the exact same JSON structure format with all required bank analysis fields.\nCalculate verification scores based on OCR quality and financial patterns.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"account_details\": {\n \"account_holder_name\": \"N/A\",\n \"account_number\": \"N/A\",\n \"bank_name\": \"N/A\",\n \"branch_name\": \"N/A\",\n \"ifsc_code\": \"N/A\"\n },\n \"monthly_inflow_outflow_patterns\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"net_flow\": 0,\n \"inflow_trends\": [],\n \"outflow_trends\": []\n },\n \"salary_credits\": {\n \"salary_credit_amount\": 0,\n \"salary_credit_frequency\": \"N/A\",\n \"consistency\": \"N/A\"\n },\n \"transaction_patterns\": {\n \"total_transactions\": 0,\n \"transaction_types\": [],\n \"average_transaction_amount\": 0\n },\n \"balance_behavior\": {\n \"average_balance\": 0,\n \"minimum_balance\": 0,\n \"maximum_balance\": 0,\n \"balance_trends\": []\n },\n \"loan_emis\": {\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": []\n },\n \"compliance_indicators\": {\n \"suspicious_activities\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_ratios\": {\n \"debt_to_income_ratio\": 0,\n \"current_ratio\": 0,\n \"liquidity_ratio\": 0\n },\n \"verification_score\": {\n \"ocr_quality\": 0,\n \"data_completeness\": 0,\n \"overall_verification_score\": 0\n },\n \"analysis_summary\": {\n \"status\": \"incomplete\",\n \"reason\": \"OCR extraction failed with an error, and no application data is available for cross-verification.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"account_details\\\": {\\n \\\"account_holder_name\\\": \\\"N/A\\\",\\n \\\"account_number\\\": \\\"N/A\\\",\\n \\\"bank_name\\\": \\\"N/A\\\",\\n \\\"branch_name\\\": \\\"N/A\\\",\\n \\\"ifsc_code\\\": \\\"N/A\\\"\\n },\\n \\\"monthly_inflow_outflow_patterns\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"net_flow\\\": 0,\\n \\\"inflow_trends\\\": [],\\n \\\"outflow_trends\\\": []\\n },\\n \\\"salary_credits\\\": {\\n \\\"salary_credit_amount\\\": 0,\\n \\\"salary_credit_frequency\\\": \\\"N/A\\\",\\n \\\"consistency\\\": \\\"N/A\\\"\\n },\\n \\\"transaction_patterns\\\": {\\n \\\"total_transactions\\\": 0,\\n \\\"transaction_types\\\": [],\\n \\\"average_transaction_amount\\\": 0\\n },\\n \\\"balance_behavior\\\": {\\n \\\"average_balance\\\": 0,\\n \\\"minimum_balance\\\": 0,\\n \\\"maximum_balance\\\": 0,\\n \\\"balance_trends\\\": []\\n },\\n \\\"loan_emis\\\": {\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": []\\n },\\n \\\"compliance_indicators\\\": {\\n \\\"suspicious_activities\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_ratios\\\": {\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"current_ratio\\\": 0,\\n \\\"liquidity_ratio\\\": 0\\n },\\n \\\"verification_score\\\": {\\n \\\"ocr_quality\\\": 0,\\n \\\"data_completeness\\\": 0,\\n \\\"overall_verification_score\\\": 0\\n },\\n \\\"analysis_summary\\\": {\\n \\\"status\\\": \\\"incomplete\\\",\\n \\\"reason\\\": \\\"OCR extraction failed with an error, and no application data is available for cross-verification.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1952, \"completion_tokens\": 399, \"total_tokens\": 2351, \"estimated_cost\": {\"amount\": 0.000532, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
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"currency": "USD"
},
"model": "gpt-4o-mini",
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"provider": "openai",
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}
},
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"end_time": "2025-07-16T06:52:17.626723",
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"start_time": "2025-07-16T06:52:05.957681",
"timestamp": "2025-07-16T06:52:17.626723",
"worker_executed": true,
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},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"account_details\": {\n \"account_holder_name\": \"N/A\",\n \"account_number\": \"N/A\",\n \"bank_name\": \"N/A\",\n \"branch_name\": \"N/A\",\n \"ifsc_code\": \"N/A\"\n },\n \"monthly_inflow_outflow_patterns\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"net_flow\": 0,\n \"inflow_trends\": [],\n \"outflow_trends\": []\n },\n \"salary_credits\": {\n \"salary_credit_amount\": 0,\n \"salary_credit_frequency\": \"N/A\",\n \"consistency\": \"N/A\"\n },\n \"transaction_patterns\": {\n \"total_transactions\": 0,\n \"transaction_types\": [],\n \"average_transaction_amount\": 0\n },\n \"balance_behavior\": {\n \"average_balance\": 0,\n \"minimum_balance\": 0,\n \"maximum_balance\": 0,\n \"balance_trends\": []\n },\n \"loan_emis\": {\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": []\n },\n \"compliance_indicators\": {\n \"suspicious_activities\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_ratios\": {\n \"debt_to_income_ratio\": 0,\n \"current_ratio\": 0,\n \"liquidity_ratio\": 0\n },\n \"verification_score\": {\n \"ocr_quality\": 0,\n \"data_completeness\": 0,\n \"overall_verification_score\": 0\n },\n \"analysis_summary\": {\n \"status\": \"incomplete\",\n \"reason\": \"OCR extraction failed with an error, and no application data is available for cross-verification.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"account_details\\\": {\\n \\\"account_holder_name\\\": \\\"N/A\\\",\\n \\\"account_number\\\": \\\"N/A\\\",\\n \\\"bank_name\\\": \\\"N/A\\\",\\n \\\"branch_name\\\": \\\"N/A\\\",\\n \\\"ifsc_code\\\": \\\"N/A\\\"\\n },\\n \\\"monthly_inflow_outflow_patterns\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"net_flow\\\": 0,\\n \\\"inflow_trends\\\": [],\\n \\\"outflow_trends\\\": []\\n },\\n \\\"salary_credits\\\": {\\n \\\"salary_credit_amount\\\": 0,\\n \\\"salary_credit_frequency\\\": \\\"N/A\\\",\\n \\\"consistency\\\": \\\"N/A\\\"\\n },\\n \\\"transaction_patterns\\\": {\\n \\\"total_transactions\\\": 0,\\n \\\"transaction_types\\\": [],\\n \\\"average_transaction_amount\\\": 0\\n },\\n \\\"balance_behavior\\\": {\\n \\\"average_balance\\\": 0,\\n \\\"minimum_balance\\\": 0,\\n \\\"maximum_balance\\\": 0,\\n \\\"balance_trends\\\": []\\n },\\n \\\"loan_emis\\\": {\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": []\\n },\\n \\\"compliance_indicators\\\": {\\n \\\"suspicious_activities\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_ratios\\\": {\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"current_ratio\\\": 0,\\n \\\"liquidity_ratio\\\": 0\\n },\\n \\\"verification_score\\\": {\\n \\\"ocr_quality\\\": 0,\\n \\\"data_completeness\\\": 0,\\n \\\"overall_verification_score\\\": 0\\n },\\n \\\"analysis_summary\\\": {\\n \\\"status\\\": \\\"incomplete\\\",\\n \\\"reason\\\": \\\"OCR extraction failed with an error, and no application data is available for cross-verification.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1952, \"completion_tokens\": 399, \"total_tokens\": 2351, \"estimated_cost\": {\"amount\": 0.000532, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "analyze_bank_statements",
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"estimated_cost": {
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"currency": "USD"
},
"model": "gpt-4o-mini",
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"provider": "openai",
"total_tokens": 2351
}
},
"analyze_credit_history": {
"average_account_age": "32 months",
"credit_limit_utilization": 35.2,
"credit_mix": {
"auto_loans": 1,
"credit_cards": 3,
"home_loans": 0,
"other": 1,
"personal_loans": 1
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"oldest_account_age\": \"60 months\", \"average_account_age\": \"32 months\", \"credit_mix\": {\"credit_cards\": 3, \"personal_loans\": 1, \"auto_loans\": 1, \"home_loans\": 0, \"other\": 1}, \"repayment_behavior\": {\"never_missed\": 85.0, \"30_days_late\": 12.0, \"60_days_late\": 2.5, \"90_days_late\": 0.5, \"defaults\": 0.0}, \"credit_limit_utilization\": 35.2, \"recent_credit_behavior\": \"stable\"}\n",
"return_code": 0,
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},
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"end_time": "2025-07-16T06:58:28.691969",
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"timestamp": "2025-07-16T06:58:28.691969",
"worker_executed": true,
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},
"oldest_account_age": "60 months",
"output": "__OUTPUTS__ {\"oldest_account_age\": \"60 months\", \"average_account_age\": \"32 months\", \"credit_mix\": {\"credit_cards\": 3, \"personal_loans\": 1, \"auto_loans\": 1, \"home_loans\": 0, \"other\": 1}, \"repayment_behavior\": {\"never_missed\": 85.0, \"30_days_late\": 12.0, \"60_days_late\": 2.5, \"90_days_late\": 0.5, \"defaults\": 0.0}, \"credit_limit_utilization\": 35.2, \"recent_credit_behavior\": \"stable\"}\n",
"recent_credit_behavior": "stable",
"repayment_behavior": {
"30_days_late": 12.0,
"60_days_late": 2.5,
"90_days_late": 0.5,
"defaults": 0.0,
"never_missed": 85.0
},
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "analyze_credit_history"
},
"analyze_salary_slips": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"employer\": \"\",\n \"employment_duration\": \"\",\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"employee_details\": {\n \"employee_id\": \"\",\n \"full_name\": \"\",\n \"designation\": \"\",\n \"department\": \"\",\n \"grade\": \"\",\n \"location\": \"\",\n \"joining_date\": \"\",\n \"pan_number\": \"\",\n \"uan_number\": \"\",\n \"bank_account\": \"\"\n },\n \"employer_details\": {\n \"company_name\": \"\",\n \"company_address\": \"\",\n \"employer_pan\": \"\",\n \"employer_tan\": \"\",\n \"pf_registration\": \"\",\n \"esi_registration\": \"\"\n },\n \"earnings_breakdown\": {\n \"basic_salary\": 0,\n \"hra\": 0,\n \"transport_allowance\": 0,\n \"special_allowance\": 0,\n \"performance_bonus\": 0,\n \"overtime\": 0,\n \"arrears\": 0\n },\n \"deductions\": {\n \"income_tax\": 0,\n \"provident_fund\": 0,\n \"professional_tax\": 0,\n \"health_insurance\": 0,\n \"life_insurance\": 0,\n \"loan_deduction\": 0,\n \"other_deductions\": 0\n },\n \"leave_details\": {\n \"total_days\": 0,\n \"present_days\": 0,\n \"paid_leave\": 0,\n \"loss_of_pay\": 0,\n \"public_holidays\": 0\n },\n \"salary_trends\": {\n \"last_6_months\": [],\n \"average_monthly\": 0,\n \"increment_percentage\": 0,\n \"last_increment_date\": \"\",\n \"bonus_history\": []\n },\n \"compliance_details\": {\n \"pf_contribution\": 0,\n \"esi_contribution\": 0,\n \"tds_deducted\": 0,\n \"form16_available\": false,\n \"salary_certificate\": false\n },\n \"verification_status\": {\n \"employer_verification\": \"unverified\",\n \"bank_credit_confirmation\": false,\n \"tax_compliance\": \"non-compliant\",\n \"document_authenticity\": \"suspicious\"\n }\n}\n```",
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"system_message": "You are an expert financial document analyst. Analyze the OCR extracted text from a salary slip and cross-verify with application data.\n\nExtract and analyze:\n1. Monthly gross and net salary amounts\n2. Employee and employer details\n3. Earnings breakdown (basic, HRA, allowances, bonuses)\n4. Deductions (tax, PF, insurance, etc.)\n5. Leave details and attendance\n6. Compliance information (PF, ESI, TDS)\n7. Cross-match with application data for consistency\n\nReturn the data in the exact same JSON structure format with all required salary analysis fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"employer\": \"\",\n \"employment_duration\": \"\",\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"employee_details\": {\n \"employee_id\": \"\",\n \"full_name\": \"\",\n \"designation\": \"\",\n \"department\": \"\",\n \"grade\": \"\",\n \"location\": \"\",\n \"joining_date\": \"\",\n \"pan_number\": \"\",\n \"uan_number\": \"\",\n \"bank_account\": \"\"\n },\n \"employer_details\": {\n \"company_name\": \"\",\n \"company_address\": \"\",\n \"employer_pan\": \"\",\n \"employer_tan\": \"\",\n \"pf_registration\": \"\",\n \"esi_registration\": \"\"\n },\n \"earnings_breakdown\": {\n \"basic_salary\": 0,\n \"hra\": 0,\n \"transport_allowance\": 0,\n \"special_allowance\": 0,\n \"performance_bonus\": 0,\n \"overtime\": 0,\n \"arrears\": 0\n },\n \"deductions\": {\n \"income_tax\": 0,\n \"provident_fund\": 0,\n \"professional_tax\": 0,\n \"health_insurance\": 0,\n \"life_insurance\": 0,\n \"loan_deduction\": 0,\n \"other_deductions\": 0\n },\n \"leave_details\": {\n \"total_days\": 0,\n \"present_days\": 0,\n \"paid_leave\": 0,\n \"loss_of_pay\": 0,\n \"public_holidays\": 0\n },\n \"salary_trends\": {\n \"last_6_months\": [],\n \"average_monthly\": 0,\n \"increment_percentage\": 0,\n \"last_increment_date\": \"\",\n \"bonus_history\": []\n },\n \"compliance_details\": {\n \"pf_contribution\": 0,\n \"esi_contribution\": 0,\n \"tds_deducted\": 0,\n \"form16_available\": false,\n \"salary_certificate\": false\n },\n \"verification_status\": {\n \"employer_verification\": \"unverified\",\n \"bank_credit_confirmation\": false,\n \"tax_compliance\": \"non-compliant\",\n \"document_authenticity\": \"suspicious\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"employer\\\": \\\"\\\",\\n \\\"employment_duration\\\": \\\"\\\",\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"employee_details\\\": {\\n \\\"employee_id\\\": \\\"\\\",\\n \\\"full_name\\\": \\\"\\\",\\n \\\"designation\\\": \\\"\\\",\\n \\\"department\\\": \\\"\\\",\\n \\\"grade\\\": \\\"\\\",\\n \\\"location\\\": \\\"\\\",\\n \\\"joining_date\\\": \\\"\\\",\\n \\\"pan_number\\\": \\\"\\\",\\n \\\"uan_number\\\": \\\"\\\",\\n \\\"bank_account\\\": \\\"\\\"\\n },\\n \\\"employer_details\\\": {\\n \\\"company_name\\\": \\\"\\\",\\n \\\"company_address\\\": \\\"\\\",\\n \\\"employer_pan\\\": \\\"\\\",\\n \\\"employer_tan\\\": \\\"\\\",\\n \\\"pf_registration\\\": \\\"\\\",\\n \\\"esi_registration\\\": \\\"\\\"\\n },\\n \\\"earnings_breakdown\\\": {\\n \\\"basic_salary\\\": 0,\\n \\\"hra\\\": 0,\\n \\\"transport_allowance\\\": 0,\\n \\\"special_allowance\\\": 0,\\n \\\"performance_bonus\\\": 0,\\n \\\"overtime\\\": 0,\\n \\\"arrears\\\": 0\\n },\\n \\\"deductions\\\": {\\n \\\"income_tax\\\": 0,\\n \\\"provident_fund\\\": 0,\\n \\\"professional_tax\\\": 0,\\n \\\"health_insurance\\\": 0,\\n \\\"life_insurance\\\": 0,\\n \\\"loan_deduction\\\": 0,\\n \\\"other_deductions\\\": 0\\n },\\n \\\"leave_details\\\": {\\n \\\"total_days\\\": 0,\\n \\\"present_days\\\": 0,\\n \\\"paid_leave\\\": 0,\\n \\\"loss_of_pay\\\": 0,\\n \\\"public_holidays\\\": 0\\n },\\n \\\"salary_trends\\\": {\\n \\\"last_6_months\\\": [],\\n \\\"average_monthly\\\": 0,\\n \\\"increment_percentage\\\": 0,\\n \\\"last_increment_date\\\": \\\"\\\",\\n \\\"bonus_history\\\": []\\n },\\n \\\"compliance_details\\\": {\\n \\\"pf_contribution\\\": 0,\\n \\\"esi_contribution\\\": 0,\\n \\\"tds_deducted\\\": 0,\\n \\\"form16_available\\\": false,\\n \\\"salary_certificate\\\": false\\n },\\n \\\"verification_status\\\": {\\n \\\"employer_verification\\\": \\\"unverified\\\",\\n \\\"bank_credit_confirmation\\\": false,\\n \\\"tax_compliance\\\": \\\"non-compliant\\\",\\n \\\"document_authenticity\\\": \\\"suspicious\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2893, \"completion_tokens\": 519, \"total_tokens\": 3412, \"estimated_cost\": {\"amount\": 0.000745, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"employer\": \"\",\n \"employment_duration\": \"\",\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"employee_details\": {\n \"employee_id\": \"\",\n \"full_name\": \"\",\n \"designation\": \"\",\n \"department\": \"\",\n \"grade\": \"\",\n \"location\": \"\",\n \"joining_date\": \"\",\n \"pan_number\": \"\",\n \"uan_number\": \"\",\n \"bank_account\": \"\"\n },\n \"employer_details\": {\n \"company_name\": \"\",\n \"company_address\": \"\",\n \"employer_pan\": \"\",\n \"employer_tan\": \"\",\n \"pf_registration\": \"\",\n \"esi_registration\": \"\"\n },\n \"earnings_breakdown\": {\n \"basic_salary\": 0,\n \"hra\": 0,\n \"transport_allowance\": 0,\n \"special_allowance\": 0,\n \"performance_bonus\": 0,\n \"overtime\": 0,\n \"arrears\": 0\n },\n \"deductions\": {\n \"income_tax\": 0,\n \"provident_fund\": 0,\n \"professional_tax\": 0,\n \"health_insurance\": 0,\n \"life_insurance\": 0,\n \"loan_deduction\": 0,\n \"other_deductions\": 0\n },\n \"leave_details\": {\n \"total_days\": 0,\n \"present_days\": 0,\n \"paid_leave\": 0,\n \"loss_of_pay\": 0,\n \"public_holidays\": 0\n },\n \"salary_trends\": {\n \"last_6_months\": [],\n \"average_monthly\": 0,\n \"increment_percentage\": 0,\n \"last_increment_date\": \"\",\n \"bonus_history\": []\n },\n \"compliance_details\": {\n \"pf_contribution\": 0,\n \"esi_contribution\": 0,\n \"tds_deducted\": 0,\n \"form16_available\": false,\n \"salary_certificate\": false\n },\n \"verification_status\": {\n \"employer_verification\": \"unverified\",\n \"bank_credit_confirmation\": false,\n \"tax_compliance\": \"non-compliant\",\n \"document_authenticity\": \"suspicious\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"employer\\\": \\\"\\\",\\n \\\"employment_duration\\\": \\\"\\\",\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"employee_details\\\": {\\n \\\"employee_id\\\": \\\"\\\",\\n \\\"full_name\\\": \\\"\\\",\\n \\\"designation\\\": \\\"\\\",\\n \\\"department\\\": \\\"\\\",\\n \\\"grade\\\": \\\"\\\",\\n \\\"location\\\": \\\"\\\",\\n \\\"joining_date\\\": \\\"\\\",\\n \\\"pan_number\\\": \\\"\\\",\\n \\\"uan_number\\\": \\\"\\\",\\n \\\"bank_account\\\": \\\"\\\"\\n },\\n \\\"employer_details\\\": {\\n \\\"company_name\\\": \\\"\\\",\\n \\\"company_address\\\": \\\"\\\",\\n \\\"employer_pan\\\": \\\"\\\",\\n \\\"employer_tan\\\": \\\"\\\",\\n \\\"pf_registration\\\": \\\"\\\",\\n \\\"esi_registration\\\": \\\"\\\"\\n },\\n \\\"earnings_breakdown\\\": {\\n \\\"basic_salary\\\": 0,\\n \\\"hra\\\": 0,\\n \\\"transport_allowance\\\": 0,\\n \\\"special_allowance\\\": 0,\\n \\\"performance_bonus\\\": 0,\\n \\\"overtime\\\": 0,\\n \\\"arrears\\\": 0\\n },\\n \\\"deductions\\\": {\\n \\\"income_tax\\\": 0,\\n \\\"provident_fund\\\": 0,\\n \\\"professional_tax\\\": 0,\\n \\\"health_insurance\\\": 0,\\n \\\"life_insurance\\\": 0,\\n \\\"loan_deduction\\\": 0,\\n \\\"other_deductions\\\": 0\\n },\\n \\\"leave_details\\\": {\\n \\\"total_days\\\": 0,\\n \\\"present_days\\\": 0,\\n \\\"paid_leave\\\": 0,\\n \\\"loss_of_pay\\\": 0,\\n \\\"public_holidays\\\": 0\\n },\\n \\\"salary_trends\\\": {\\n \\\"last_6_months\\\": [],\\n \\\"average_monthly\\\": 0,\\n \\\"increment_percentage\\\": 0,\\n \\\"last_increment_date\\\": \\\"\\\",\\n \\\"bonus_history\\\": []\\n },\\n \\\"compliance_details\\\": {\\n \\\"pf_contribution\\\": 0,\\n \\\"esi_contribution\\\": 0,\\n \\\"tds_deducted\\\": 0,\\n \\\"form16_available\\\": false,\\n \\\"salary_certificate\\\": false\\n },\\n \\\"verification_status\\\": {\\n \\\"employer_verification\\\": \\\"unverified\\\",\\n \\\"bank_credit_confirmation\\\": false,\\n \\\"tax_compliance\\\": \\\"non-compliant\\\",\\n \\\"document_authenticity\\\": \\\"suspicious\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2893, \"completion_tokens\": 519, \"total_tokens\": 3412, \"estimated_cost\": {\"amount\": 0.000745, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [\n \"full_name\",\n \"email\",\n \"phone\",\n \"address\",\n \"employment_status\",\n \"annual_income\"\n ],\n \"validation_passed\": false,\n \"completion_percentage\": 0.0\n },\n \"consistency_of_information\": {\n \"status\": \"inconsistent\",\n \"reason\": \"No information provided to assess consistency.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"red_flags\": [\n \"All required fields are missing, indicating a lack of effort or potential issues with the application process.\"\n ]\n },\n \"overall_application_quality_score\": 5\n}\n```",
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"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
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"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [\n \"full_name\",\n \"email\",\n \"phone\",\n \"address\",\n \"employment_status\",\n \"annual_income\"\n ],\n \"validation_passed\": false,\n \"completion_percentage\": 0.0\n },\n \"consistency_of_information\": {\n \"status\": \"inconsistent\",\n \"reason\": \"No information provided to assess consistency.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"red_flags\": [\n \"All required fields are missing, indicating a lack of effort or potential issues with the application process.\"\n ]\n },\n \"overall_application_quality_score\": 5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [\\n \\\"full_name\\\",\\n \\\"email\\\",\\n \\\"phone\\\",\\n \\\"address\\\",\\n \\\"employment_status\\\",\\n \\\"annual_income\\\"\\n ],\\n \\\"validation_passed\\\": false,\\n \\\"completion_percentage\\\": 0.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"No information provided to assess consistency.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"red_flags\\\": [\\n \\\"All required fields are missing, indicating a lack of effort or potential issues with the application process.\\\"\\n ]\\n },\\n \\\"overall_application_quality_score\\\": 5\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 132, \"completion_tokens\": 153, \"total_tokens\": 285, \"estimated_cost\": {\"amount\": 0.000112, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [\n \"full_name\",\n \"email\",\n \"phone\",\n \"address\",\n \"employment_status\",\n \"annual_income\"\n ],\n \"validation_passed\": false,\n \"completion_percentage\": 0.0\n },\n \"consistency_of_information\": {\n \"status\": \"inconsistent\",\n \"reason\": \"No information provided to assess consistency.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"red_flags\": [\n \"All required fields are missing, indicating a lack of effort or potential issues with the application process.\"\n ]\n },\n \"overall_application_quality_score\": 5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [\\n \\\"full_name\\\",\\n \\\"email\\\",\\n \\\"phone\\\",\\n \\\"address\\\",\\n \\\"employment_status\\\",\\n \\\"annual_income\\\"\\n ],\\n \\\"validation_passed\\\": false,\\n \\\"completion_percentage\\\": 0.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"No information provided to assess consistency.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"red_flags\\\": [\\n \\\"All required fields are missing, indicating a lack of effort or potential issues with the application process.\\\"\\n ]\\n },\\n \\\"overall_application_quality_score\\\": 5\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 132, \"completion_tokens\": 153, \"total_tokens\": 285, \"estimated_cost\": {\"amount\": 0.000112, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
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"task_id": "application_quality_check",
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},
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"prompt_tokens": 132,
"provider": "openai",
"total_tokens": 285
}
},
"assess_existing_loans": {
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.196845,
"end_time": "2025-07-16T06:58:28.920345",
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"timestamp": "2025-07-16T06:58:28.920345",
"worker_executed": true,
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},
"loan_burden_ratio": 0.28,
"loan_details": [
{
"emi": 3500,
"outstanding": 45000,
"remaining_tenure": "18 months",
"type": "personal_loan"
},
{
"emi": 4200,
"outstanding": 80000,
"remaining_tenure": "24 months",
"type": "auto_loan"
}
],
"number_of_loans": 2,
"output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
"repayment_track_record": "excellent",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "assess_existing_loans",
"total_monthly_emi": 7700,
"total_outstanding": 125000
},
"calculate_credit_score": {
"cibil_score": 720,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
"return_code": 0,
"status": "completed",
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},
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"start_time": "2025-07-16T06:58:42.070145",
"timestamp": "2025-07-16T06:58:42.261429",
"worker_executed": true,
"workers_notified": true
},
"internal_credit_score": 337.9,
"min_required_score": 650,
"output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
"return_code": 0,
"risk_category": "high",
"score_acceptable": false,
"scoring_factors": {
"cibil_contribution": 288.0,
"loan_burden_contribution": 7.2,
"payment_history_contribution": 29.7,
"utilization_contribution": 12.96
},
"status": "completed",
"stderr": "",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpb9qcqooh.py\", line 9, in \u003cmodule\u003e\n monthly_net = UNRESOLVED_analyze_salary_slips.monthly_net\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_analyze_salary_slips\u0027 is not defined\n",
"execution_details": {
"failed": true,
"message_sent": true,
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},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpb9qcqooh.py\", line 9, in \u003cmodule\u003e\n monthly_net = UNRESOLVED_analyze_salary_slips.monthly_net\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_analyze_salary_slips\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_debt_to_income"
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
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},
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"end_time": "2025-07-16T06:58:28.454936",
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"timestamp": "2025-07-16T06:58:28.454936",
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},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\n\n```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk_category\": \"low\",\n \"individual_risk_categories\": {\n \"kyc_risk\": \"low\",\n \"aml_risk\": \"low\",\n \"regulatory_risk\": \"minimal\",\n \"internal_policy_risk\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue monitoring compliance with KYC, AML, and regulatory requirements.\",\n \"Maintain documentation and audit trails to ensure ongoing compliance.\",\n \"Regularly review internal policies to align with any changes in regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Overall Compliance Status**: The overall compliance status is rated as \"compliant,\" indicating that all checks have been met satisfactorily.\n\n2. **Risk Assessment**:\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\n\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\n\n4. **Recommendations for Proceeding**:\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\n - Documentation and audit trails should be kept up to date to ensure compliance.\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\n\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.",
"execution_details": {
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"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\n\n```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk_category\": \"low\",\n \"individual_risk_categories\": {\n \"kyc_risk\": \"low\",\n \"aml_risk\": \"low\",\n \"regulatory_risk\": \"minimal\",\n \"internal_policy_risk\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue monitoring compliance with KYC, AML, and regulatory requirements.\",\n \"Maintain documentation and audit trails to ensure ongoing compliance.\",\n \"Regularly review internal policies to align with any changes in regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Overall Compliance Status**: The overall compliance status is rated as \"compliant,\" indicating that all checks have been met satisfactorily.\n\n2. **Risk Assessment**:\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\n\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\n\n4. **Recommendations for Proceeding**:\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\n - Documentation and audit trails should be kept up to date to ensure compliance.\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\n\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk_category\\\": \\\"low\\\",\\n \\\"individual_risk_categories\\\": {\\n \\\"kyc_risk\\\": \\\"low\\\",\\n \\\"aml_risk\\\": \\\"low\\\",\\n \\\"regulatory_risk\\\": \\\"minimal\\\",\\n \\\"internal_policy_risk\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue monitoring compliance with KYC, AML, and regulatory requirements.\\\",\\n \\\"Maintain documentation and audit trails to ensure ongoing compliance.\\\",\\n \\\"Regularly review internal policies to align with any changes in regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Overall Compliance Status**: The overall compliance status is rated as \\\"compliant,\\\" indicating that all checks have been met satisfactorily.\\n\\n2. **Risk Assessment**:\\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\\n\\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\\n\\n4. **Recommendations for Proceeding**:\\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\\n - Documentation and audit trails should be kept up to date to ensure compliance.\\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\\n\\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5859, \"completion_tokens\": 1084, \"total_tokens\": 6943, \"estimated_cost\": {\"amount\": 0.001529, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\n\n```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk_category\": \"low\",\n \"individual_risk_categories\": {\n \"kyc_risk\": \"low\",\n \"aml_risk\": \"low\",\n \"regulatory_risk\": \"minimal\",\n \"internal_policy_risk\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue monitoring compliance with KYC, AML, and regulatory requirements.\",\n \"Maintain documentation and audit trails to ensure ongoing compliance.\",\n \"Regularly review internal policies to align with any changes in regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Overall Compliance Status**: The overall compliance status is rated as \"compliant,\" indicating that all checks have been met satisfactorily.\n\n2. **Risk Assessment**:\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\n\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\n\n4. **Recommendations for Proceeding**:\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\n - Documentation and audit trails should be kept up to date to ensure compliance.\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\n\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk_category\\\": \\\"low\\\",\\n \\\"individual_risk_categories\\\": {\\n \\\"kyc_risk\\\": \\\"low\\\",\\n \\\"aml_risk\\\": \\\"low\\\",\\n \\\"regulatory_risk\\\": \\\"minimal\\\",\\n \\\"internal_policy_risk\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue monitoring compliance with KYC, AML, and regulatory requirements.\\\",\\n \\\"Maintain documentation and audit trails to ensure ongoing compliance.\\\",\\n \\\"Regularly review internal policies to align with any changes in regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Overall Compliance Status**: The overall compliance status is rated as \\\"compliant,\\\" indicating that all checks have been met satisfactorily.\\n\\n2. **Risk Assessment**:\\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\\n\\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\\n\\n4. **Recommendations for Proceeding**:\\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\\n - Documentation and audit trails should be kept up to date to ensure compliance.\\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\\n\\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5859, \"completion_tokens\": 1084, \"total_tokens\": 6943, \"estimated_cost\": {\"amount\": 0.001529, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "```json\n{\n \"overall_verification_success_rate\": 0.0,\n \"consistency_across_documents\": {\n \"status\": \"inconsistent\",\n \"reason\": \"All documents returned invalid results with missing or non-matching information.\"\n },\n \"risk_factors_identified\": [\n \"All documents are invalid, indicating potential fraud or identity issues.\",\n \"Missing critical information such as names, addresses, and identification numbers.\",\n \"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\",\n \"Suspicious security features noted in the passport and address proof documents.\"\n ],\n \"recommendation_for_proceeding\": {\n \"action\": \"Do not proceed with the application.\",\n \"justification\": \"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\"\n }\n}\n```",
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"output": "```json\n{\n \"overall_verification_success_rate\": 0.0,\n \"consistency_across_documents\": {\n \"status\": \"inconsistent\",\n \"reason\": \"All documents returned invalid results with missing or non-matching information.\"\n },\n \"risk_factors_identified\": [\n \"All documents are invalid, indicating potential fraud or identity issues.\",\n \"Missing critical information such as names, addresses, and identification numbers.\",\n \"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\",\n \"Suspicious security features noted in the passport and address proof documents.\"\n ],\n \"recommendation_for_proceeding\": {\n \"action\": \"Do not proceed with the application.\",\n \"justification\": \"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 0.0,\\n \\\"consistency_across_documents\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"All documents returned invalid results with missing or non-matching information.\\\"\\n },\\n \\\"risk_factors_identified\\\": [\\n \\\"All documents are invalid, indicating potential fraud or identity issues.\\\",\\n \\\"Missing critical information such as names, addresses, and identification numbers.\\\",\\n \\\"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\\\",\\n \\\"Suspicious security features noted in the passport and address proof documents.\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Do not proceed with the application.\\\",\\n \\\"justification\\\": \\\"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 3587, \"completion_tokens\": 192, \"total_tokens\": 3779, \"estimated_cost\": {\"amount\": 0.000653, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "```json\n{\n \"overall_verification_success_rate\": 0.0,\n \"consistency_across_documents\": {\n \"status\": \"inconsistent\",\n \"reason\": \"All documents returned invalid results with missing or non-matching information.\"\n },\n \"risk_factors_identified\": [\n \"All documents are invalid, indicating potential fraud or identity issues.\",\n \"Missing critical information such as names, addresses, and identification numbers.\",\n \"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\",\n \"Suspicious security features noted in the passport and address proof documents.\"\n ],\n \"recommendation_for_proceeding\": {\n \"action\": \"Do not proceed with the application.\",\n \"justification\": \"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 0.0,\\n \\\"consistency_across_documents\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"All documents returned invalid results with missing or non-matching information.\\\"\\n },\\n \\\"risk_factors_identified\\\": [\\n \\\"All documents are invalid, indicating potential fraud or identity issues.\\\",\\n \\\"Missing critical information such as names, addresses, and identification numbers.\\\",\\n \\\"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\\\",\\n \\\"Suspicious security features noted in the passport and address proof documents.\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Do not proceed with the application.\\\",\\n \\\"justification\\\": \\\"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 3587, \"completion_tokens\": 192, \"total_tokens\": 3779, \"estimated_cost\": {\"amount\": 0.000653, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "Based on the provided credit data, we can analyze the default risk using the following criteria:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n- **Average Account Age**: 32 months\n- **Recent Credit Behavior**: Stable\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Outstanding**: \u20b9125,000\n- **Total Monthly EMI**: \u20b97,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\n- **Repayment Track Record**: Excellent\n\n### 5. Overall Risk Profile\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\n\n### Risk Score Calculation\nConsidering the above factors, we can assign a risk score based on the following criteria:\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 10 points (Excellent)\n- **Credit Utilization**: 10 points (Moderate)\n- **Repayment Patterns**: 10 points (Excellent)\n- **Loan Burden Ratio**: 10 points (Low)\n- **Overall Risk Profile**: 10 points (Stable)\n\n### Total Risk Score\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\n\n### Conclusion\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.",
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"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
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"output": "Based on the provided credit data, we can analyze the default risk using the following criteria:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n- **Average Account Age**: 32 months\n- **Recent Credit Behavior**: Stable\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Outstanding**: \u20b9125,000\n- **Total Monthly EMI**: \u20b97,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\n- **Repayment Track Record**: Excellent\n\n### 5. Overall Risk Profile\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\n\n### Risk Score Calculation\nConsidering the above factors, we can assign a risk score based on the following criteria:\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 10 points (Excellent)\n- **Credit Utilization**: 10 points (Moderate)\n- **Repayment Patterns**: 10 points (Excellent)\n- **Loan Burden Ratio**: 10 points (Low)\n- **Overall Risk Profile**: 10 points (Stable)\n\n### Total Risk Score\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\n\n### Conclusion\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we can analyze the default risk using the following criteria:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n- **Average Account Age**: 32 months\\n- **Recent Credit Behavior**: Stable\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Outstanding**: \\u20b9125,000\\n- **Total Monthly EMI**: \\u20b97,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\\n- **Repayment Track Record**: Excellent\\n\\n### 5. Overall Risk Profile\\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\\n\\n### Risk Score Calculation\\nConsidering the above factors, we can assign a risk score based on the following criteria:\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 10 points (Excellent)\\n- **Credit Utilization**: 10 points (Moderate)\\n- **Repayment Patterns**: 10 points (Excellent)\\n- **Loan Burden Ratio**: 10 points (Low)\\n- **Overall Risk Profile**: 10 points (Stable)\\n\\n### Total Risk Score\\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\\n\\n### Conclusion\\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 4788, \"completion_tokens\": 1144, \"total_tokens\": 5932, \"estimated_cost\": {\"amount\": 0.001405, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided credit data, we can analyze the default risk using the following criteria:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n- **Average Account Age**: 32 months\n- **Recent Credit Behavior**: Stable\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Outstanding**: \u20b9125,000\n- **Total Monthly EMI**: \u20b97,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\n- **Repayment Track Record**: Excellent\n\n### 5. Overall Risk Profile\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\n\n### Risk Score Calculation\nConsidering the above factors, we can assign a risk score based on the following criteria:\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 10 points (Excellent)\n- **Credit Utilization**: 10 points (Moderate)\n- **Repayment Patterns**: 10 points (Excellent)\n- **Loan Burden Ratio**: 10 points (Low)\n- **Overall Risk Profile**: 10 points (Stable)\n\n### Total Risk Score\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\n\n### Conclusion\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we can analyze the default risk using the following criteria:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n- **Average Account Age**: 32 months\\n- **Recent Credit Behavior**: Stable\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Outstanding**: \\u20b9125,000\\n- **Total Monthly EMI**: \\u20b97,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\\n- **Repayment Track Record**: Excellent\\n\\n### 5. Overall Risk Profile\\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\\n\\n### Risk Score Calculation\\nConsidering the above factors, we can assign a risk score based on the following criteria:\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 10 points (Excellent)\\n- **Credit Utilization**: 10 points (Moderate)\\n- **Repayment Patterns**: 10 points (Excellent)\\n- **Loan Burden Ratio**: 10 points (Low)\\n- **Overall Risk Profile**: 10 points (Stable)\\n\\n### Total Risk Score\\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\\n\\n### Conclusion\\nThe individual presents a moderate default risk (70 out of 100), which is manageable. 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"ai_response": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: N/A (not applicable due to decline)\n- **Interest Rate**: N/A\n- **Loan Tenure**: N/A\n- **Repayment Schedule**: N/A\n\n#### Risk Mitigation Measures:\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\n- Recommend the applicant to gather and provide complete documentation before reapplying.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\n\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\n\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\n\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\n\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\n\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\n\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. The applicant is encouraged to rectify these issues and consider reapplying in the future once they have provided complete and verifiable information.\n\n#### Confidence Level: 95\nThis confidence level reflects the strong basis for the decision due to the overwhelming evidence of risk factors and the lack of necessary documentation.",
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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: N/A (not applicable due to decline)\n- **Interest Rate**: N/A\n- **Loan Tenure**: N/A\n- **Repayment Schedule**: N/A\n\n#### Risk Mitigation Measures:\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\n- Recommend the applicant to gather and provide complete documentation before reapplying.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\n\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\n\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\n\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\n\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\n\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\n\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. 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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: N/A (not applicable due to decline)\n- **Interest Rate**: N/A\n- **Loan Tenure**: N/A\n- **Repayment Schedule**: N/A\n\n#### Risk Mitigation Measures:\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\n- Recommend the applicant to gather and provide complete documentation before reapplying.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\n\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\n\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\n\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\n\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\n\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\n\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. The applicant is encouraged to rectify these issues and consider reapplying in the future once they have provided complete and verifiable information.\n\n#### Confidence Level: 95\nThis confidence level reflects the strong basis for the decision due to the overwhelming evidence of risk factors and the lack of necessary documentation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: N/A (not applicable due to decline)\\n- **Interest Rate**: N/A\\n- **Loan Tenure**: N/A\\n- **Repayment Schedule**: N/A\\n\\n#### Risk Mitigation Measures:\\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\\n- Recommend the applicant to gather and provide complete documentation before reapplying.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\\n\\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\\n\\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\\n\\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\\n\\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\\n\\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\\n\\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. 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"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpb779tfei.py\", line 11, in \u003cmodule\u003e\n \"loan_amount\": UNRESOLVED_loan_amount,\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
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"ai_response": "Based on the provided income data, here is a detailed assessment in JSON format:\n\n```json\n{\n \"income_stability_assessment\": {\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"job_stability_score\": 88.5,\n \"employment_status\": \"permanent\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"tax_compliance_score\": 92.0,\n \"income_growth_trend\": \"positive\"\n },\n \"debt_servicing_capability\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"debt_to_income_ratio\": 0,\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_discipline_evaluation\": {\n \"tax_paid\": 12000,\n \"declared_income\": 98000,\n \"discrepancies_found\": false,\n \"returns_filed_consistently\": true,\n \"verification_with_govt\": true\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"No income data available from salary analysis.\",\n \"Bank statement shows no inflow or outflow patterns.\",\n \"Verification status of employer is unverified.\",\n \"Suspicious document authenticity noted.\"\n ],\n \"recommendations\": [\n \"Obtain complete salary slips and bank statements for verification.\",\n \"Conduct a thorough background check on employment.\",\n \"Request additional documentation to confirm income sources.\"\n ]\n },\n \"overall_income_adequacy_score\": 25\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Income Stability Assessment**:\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\n\n2. **Debt Servicing Capability**:\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\n\n3. **Financial Discipline Evaluation**:\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\n\n4. **Risk Factors and Recommendations**:\n - The lack of income data and unverified employment status are significant risk factors.\n - Recommendations include obtaining further documentation and conducting a thorough background check.\n\n5. **Overall Income Adequacy Score**:\n - Given the lack of income data and potential risks, the overall score is low (25 out of 100), indicating that the individual may not be a suitable candidate for loan underwriting without further verification.",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "Based on the provided income data, here is a detailed assessment in JSON format:\n\n```json\n{\n \"income_stability_assessment\": {\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"job_stability_score\": 88.5,\n \"employment_status\": \"permanent\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"tax_compliance_score\": 92.0,\n \"income_growth_trend\": \"positive\"\n },\n \"debt_servicing_capability\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"debt_to_income_ratio\": 0,\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_discipline_evaluation\": {\n \"tax_paid\": 12000,\n \"declared_income\": 98000,\n \"discrepancies_found\": false,\n \"returns_filed_consistently\": true,\n \"verification_with_govt\": true\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"No income data available from salary analysis.\",\n \"Bank statement shows no inflow or outflow patterns.\",\n \"Verification status of employer is unverified.\",\n \"Suspicious document authenticity noted.\"\n ],\n \"recommendations\": [\n \"Obtain complete salary slips and bank statements for verification.\",\n \"Conduct a thorough background check on employment.\",\n \"Request additional documentation to confirm income sources.\"\n ]\n },\n \"overall_income_adequacy_score\": 25\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Income Stability Assessment**:\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\n\n2. **Debt Servicing Capability**:\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\n\n3. **Financial Discipline Evaluation**:\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\n\n4. **Risk Factors and Recommendations**:\n - The lack of income data and unverified employment status are significant risk factors.\n - Recommendations include obtaining further documentation and conducting a thorough background check.\n\n5. **Overall Income Adequacy Score**:\n - Given the lack of income data and potential risks, the overall score is low (25 out of 100), indicating that the individual may not be a suitable candidate for loan underwriting without further verification.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data, here is a detailed assessment in JSON format:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_status\\\": \\\"permanent\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"income_growth_trend\\\": \\\"positive\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"tax_paid\\\": 12000,\\n \\\"declared_income\\\": 98000,\\n \\\"discrepancies_found\\\": false,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"verification_with_govt\\\": true\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"No income data available from salary analysis.\\\",\\n \\\"Bank statement shows no inflow or outflow patterns.\\\",\\n \\\"Verification status of employer is unverified.\\\",\\n \\\"Suspicious document authenticity noted.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Obtain complete salary slips and bank statements for verification.\\\",\\n \\\"Conduct a thorough background check on employment.\\\",\\n \\\"Request additional documentation to confirm income sources.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 25\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Income Stability Assessment**:\\n - 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"output": "Based on the provided income data, here is a detailed assessment in JSON format:\n\n```json\n{\n \"income_stability_assessment\": {\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"job_stability_score\": 88.5,\n \"employment_status\": \"permanent\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"tax_compliance_score\": 92.0,\n \"income_growth_trend\": \"positive\"\n },\n \"debt_servicing_capability\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"debt_to_income_ratio\": 0,\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_discipline_evaluation\": {\n \"tax_paid\": 12000,\n \"declared_income\": 98000,\n \"discrepancies_found\": false,\n \"returns_filed_consistently\": true,\n \"verification_with_govt\": true\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"No income data available from salary analysis.\",\n \"Bank statement shows no inflow or outflow patterns.\",\n \"Verification status of employer is unverified.\",\n \"Suspicious document authenticity noted.\"\n ],\n \"recommendations\": [\n \"Obtain complete salary slips and bank statements for verification.\",\n \"Conduct a thorough background check on employment.\",\n \"Request additional documentation to confirm income sources.\"\n ]\n },\n \"overall_income_adequacy_score\": 25\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Income Stability Assessment**:\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\n\n2. **Debt Servicing Capability**:\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\n\n3. **Financial Discipline Evaluation**:\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\n\n4. **Risk Factors and Recommendations**:\n - The lack of income data and unverified employment status are significant risk factors.\n - Recommendations include obtaining further documentation and conducting a thorough background check.\n\n5. **Overall Income Adequacy Score**:\n - Given the lack of income data and potential risks, the overall score is low (25 out of 100), indicating that the individual may not be a suitable candidate for loan underwriting without further verification.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data, here is a detailed assessment in JSON format:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_status\\\": \\\"permanent\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"income_growth_trend\\\": \\\"positive\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"tax_paid\\\": 12000,\\n \\\"declared_income\\\": 98000,\\n \\\"discrepancies_found\\\": false,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"verification_with_govt\\\": true\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"No income data available from salary analysis.\\\",\\n \\\"Bank statement shows no inflow or outflow patterns.\\\",\\n \\\"Verification status of employer is unverified.\\\",\\n \\\"Suspicious document authenticity noted.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Obtain complete salary slips and bank statements for verification.\\\",\\n \\\"Conduct a thorough background check on employment.\\\",\\n \\\"Request additional documentation to confirm income sources.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 25\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Income Stability Assessment**:\\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\\n\\n2. **Debt Servicing Capability**:\\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\\n\\n3. **Financial Discipline Evaluation**:\\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\\n\\n4. **Risk Factors and Recommendations**:\\n - The lack of income data and unverified employment status are significant risk factors.\\n - Recommendations include obtaining further documentation and conducting a thorough background check.\\n\\n5. **Overall Income Adequacy Score**:\\n - 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{
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}
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"output": "__OUTPUTS__ {\"aml_status\": \"cleared\", \"watchlist_check\": \"no_matches\", \"pep_screening\": \"not_identified\", \"sanctions_check\": \"cleared\", \"adverse_media\": \"no_hits\", \"risk_rating\": \"low\", \"compliance_score\": 96.8, \"screening_date\": \"2024-07-15\", \"manual_review_required\": false}\n",
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"ai_response": "```json\n{\n \"account_details\": {\n \"account_holder_name\": \"N/A\",\n \"account_number\": \"N/A\",\n \"bank_name\": \"N/A\",\n \"branch_name\": \"N/A\",\n \"ifsc_code\": \"N/A\"\n },\n \"monthly_inflow_outflow_patterns\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"net_flow\": 0,\n \"inflow_trends\": [],\n \"outflow_trends\": []\n },\n \"salary_credits\": {\n \"salary_credit_amount\": 0,\n \"salary_credit_frequency\": \"N/A\",\n \"consistency\": \"N/A\"\n },\n \"transaction_patterns\": {\n \"total_transactions\": 0,\n \"transaction_types\": [],\n \"average_transaction_amount\": 0\n },\n \"balance_behavior\": {\n \"average_balance\": 0,\n \"minimum_balance\": 0,\n \"maximum_balance\": 0,\n \"balance_trends\": []\n },\n \"loan_emis\": {\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": []\n },\n \"compliance_indicators\": {\n \"suspicious_activities\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_ratios\": {\n \"debt_to_income_ratio\": 0,\n \"current_ratio\": 0,\n \"liquidity_ratio\": 0\n },\n \"verification_score\": {\n \"ocr_quality\": 0,\n \"data_completeness\": 0,\n \"overall_verification_score\": 0\n },\n \"analysis_summary\": {\n \"status\": \"incomplete\",\n \"reason\": \"OCR extraction failed with an error, and no application data is available for cross-verification.\"\n }\n}\n```",
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"provider": "openai",
"system_message": "You are an expert financial analyst. Analyze the OCR extracted text from a bank statement and cross-verify with application data.\n\nExtract and analyze:\n1. Account details and account holder information\n2. Monthly inflow and outflow patterns\n3. Salary credits and their consistency\n4. Transaction patterns and financial behavior\n5. Balance behavior and trends\n6. Loan EMIs and existing financial obligations\n7. Compliance indicators and suspicious activities\n8. Financial ratios and stability metrics\n\nReturn the data in the exact same JSON structure format with all required bank analysis fields.\nCalculate verification scores based on OCR quality and financial patterns.\n"
},
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"output": "```json\n{\n \"account_details\": {\n \"account_holder_name\": \"N/A\",\n \"account_number\": \"N/A\",\n \"bank_name\": \"N/A\",\n \"branch_name\": \"N/A\",\n \"ifsc_code\": \"N/A\"\n },\n \"monthly_inflow_outflow_patterns\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"net_flow\": 0,\n \"inflow_trends\": [],\n \"outflow_trends\": []\n },\n \"salary_credits\": {\n \"salary_credit_amount\": 0,\n \"salary_credit_frequency\": \"N/A\",\n \"consistency\": \"N/A\"\n },\n \"transaction_patterns\": {\n \"total_transactions\": 0,\n \"transaction_types\": [],\n \"average_transaction_amount\": 0\n },\n \"balance_behavior\": {\n \"average_balance\": 0,\n \"minimum_balance\": 0,\n \"maximum_balance\": 0,\n \"balance_trends\": []\n },\n \"loan_emis\": {\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": []\n },\n \"compliance_indicators\": {\n \"suspicious_activities\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_ratios\": {\n \"debt_to_income_ratio\": 0,\n \"current_ratio\": 0,\n \"liquidity_ratio\": 0\n },\n \"verification_score\": {\n \"ocr_quality\": 0,\n \"data_completeness\": 0,\n \"overall_verification_score\": 0\n },\n \"analysis_summary\": {\n \"status\": \"incomplete\",\n \"reason\": \"OCR extraction failed with an error, and no application data is available for cross-verification.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"account_details\\\": {\\n \\\"account_holder_name\\\": \\\"N/A\\\",\\n \\\"account_number\\\": \\\"N/A\\\",\\n \\\"bank_name\\\": \\\"N/A\\\",\\n \\\"branch_name\\\": \\\"N/A\\\",\\n \\\"ifsc_code\\\": \\\"N/A\\\"\\n },\\n \\\"monthly_inflow_outflow_patterns\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"net_flow\\\": 0,\\n \\\"inflow_trends\\\": [],\\n \\\"outflow_trends\\\": []\\n },\\n \\\"salary_credits\\\": {\\n \\\"salary_credit_amount\\\": 0,\\n \\\"salary_credit_frequency\\\": \\\"N/A\\\",\\n \\\"consistency\\\": \\\"N/A\\\"\\n },\\n \\\"transaction_patterns\\\": {\\n \\\"total_transactions\\\": 0,\\n \\\"transaction_types\\\": [],\\n \\\"average_transaction_amount\\\": 0\\n },\\n \\\"balance_behavior\\\": {\\n \\\"average_balance\\\": 0,\\n \\\"minimum_balance\\\": 0,\\n \\\"maximum_balance\\\": 0,\\n \\\"balance_trends\\\": []\\n },\\n \\\"loan_emis\\\": {\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": []\\n },\\n \\\"compliance_indicators\\\": {\\n \\\"suspicious_activities\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_ratios\\\": {\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"current_ratio\\\": 0,\\n \\\"liquidity_ratio\\\": 0\\n },\\n \\\"verification_score\\\": {\\n \\\"ocr_quality\\\": 0,\\n \\\"data_completeness\\\": 0,\\n \\\"overall_verification_score\\\": 0\\n },\\n \\\"analysis_summary\\\": {\\n \\\"status\\\": \\\"incomplete\\\",\\n \\\"reason\\\": \\\"OCR extraction failed with an error, and no application data is available for cross-verification.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1952, \"completion_tokens\": 399, \"total_tokens\": 2351, \"estimated_cost\": {\"amount\": 0.000532, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"account_details\": {\n \"account_holder_name\": \"N/A\",\n \"account_number\": \"N/A\",\n \"bank_name\": \"N/A\",\n \"branch_name\": \"N/A\",\n \"ifsc_code\": \"N/A\"\n },\n \"monthly_inflow_outflow_patterns\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"net_flow\": 0,\n \"inflow_trends\": [],\n \"outflow_trends\": []\n },\n \"salary_credits\": {\n \"salary_credit_amount\": 0,\n \"salary_credit_frequency\": \"N/A\",\n \"consistency\": \"N/A\"\n },\n \"transaction_patterns\": {\n \"total_transactions\": 0,\n \"transaction_types\": [],\n \"average_transaction_amount\": 0\n },\n \"balance_behavior\": {\n \"average_balance\": 0,\n \"minimum_balance\": 0,\n \"maximum_balance\": 0,\n \"balance_trends\": []\n },\n \"loan_emis\": {\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": []\n },\n \"compliance_indicators\": {\n \"suspicious_activities\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_ratios\": {\n \"debt_to_income_ratio\": 0,\n \"current_ratio\": 0,\n \"liquidity_ratio\": 0\n },\n \"verification_score\": {\n \"ocr_quality\": 0,\n \"data_completeness\": 0,\n \"overall_verification_score\": 0\n },\n \"analysis_summary\": {\n \"status\": \"incomplete\",\n \"reason\": \"OCR extraction failed with an error, and no application data is available for cross-verification.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"account_details\\\": {\\n \\\"account_holder_name\\\": \\\"N/A\\\",\\n \\\"account_number\\\": \\\"N/A\\\",\\n \\\"bank_name\\\": \\\"N/A\\\",\\n \\\"branch_name\\\": \\\"N/A\\\",\\n \\\"ifsc_code\\\": \\\"N/A\\\"\\n },\\n \\\"monthly_inflow_outflow_patterns\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"net_flow\\\": 0,\\n \\\"inflow_trends\\\": [],\\n \\\"outflow_trends\\\": []\\n },\\n \\\"salary_credits\\\": {\\n \\\"salary_credit_amount\\\": 0,\\n \\\"salary_credit_frequency\\\": \\\"N/A\\\",\\n \\\"consistency\\\": \\\"N/A\\\"\\n },\\n \\\"transaction_patterns\\\": {\\n \\\"total_transactions\\\": 0,\\n \\\"transaction_types\\\": [],\\n \\\"average_transaction_amount\\\": 0\\n },\\n \\\"balance_behavior\\\": {\\n \\\"average_balance\\\": 0,\\n \\\"minimum_balance\\\": 0,\\n \\\"maximum_balance\\\": 0,\\n \\\"balance_trends\\\": []\\n },\\n \\\"loan_emis\\\": {\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": []\\n },\\n \\\"compliance_indicators\\\": {\\n \\\"suspicious_activities\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_ratios\\\": {\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"current_ratio\\\": 0,\\n \\\"liquidity_ratio\\\": 0\\n },\\n \\\"verification_score\\\": {\\n \\\"ocr_quality\\\": 0,\\n \\\"data_completeness\\\": 0,\\n \\\"overall_verification_score\\\": 0\\n },\\n \\\"analysis_summary\\\": {\\n \\\"status\\\": \\\"incomplete\\\",\\n \\\"reason\\\": \\\"OCR extraction failed with an error, and no application data is available for cross-verification.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1952, \"completion_tokens\": 399, \"total_tokens\": 2351, \"estimated_cost\": {\"amount\": 0.000532, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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},
"analyze_credit_history": {
"average_account_age": "32 months",
"credit_limit_utilization": 35.2,
"credit_mix": {
"auto_loans": 1,
"credit_cards": 3,
"home_loans": 0,
"other": 1,
"personal_loans": 1
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"oldest_account_age\": \"60 months\", \"average_account_age\": \"32 months\", \"credit_mix\": {\"credit_cards\": 3, \"personal_loans\": 1, \"auto_loans\": 1, \"home_loans\": 0, \"other\": 1}, \"repayment_behavior\": {\"never_missed\": 85.0, \"30_days_late\": 12.0, \"60_days_late\": 2.5, \"90_days_late\": 0.5, \"defaults\": 0.0}, \"credit_limit_utilization\": 35.2, \"recent_credit_behavior\": \"stable\"}\n",
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},
"oldest_account_age": "60 months",
"output": "__OUTPUTS__ {\"oldest_account_age\": \"60 months\", \"average_account_age\": \"32 months\", \"credit_mix\": {\"credit_cards\": 3, \"personal_loans\": 1, \"auto_loans\": 1, \"home_loans\": 0, \"other\": 1}, \"repayment_behavior\": {\"never_missed\": 85.0, \"30_days_late\": 12.0, \"60_days_late\": 2.5, \"90_days_late\": 0.5, \"defaults\": 0.0}, \"credit_limit_utilization\": 35.2, \"recent_credit_behavior\": \"stable\"}\n",
"recent_credit_behavior": "stable",
"repayment_behavior": {
"30_days_late": 12.0,
"60_days_late": 2.5,
"90_days_late": 0.5,
"defaults": 0.0,
"never_missed": 85.0
},
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"task_id": "analyze_credit_history"
},
"analyze_salary_slips": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"employer\": \"\",\n \"employment_duration\": \"\",\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"employee_details\": {\n \"employee_id\": \"\",\n \"full_name\": \"\",\n \"designation\": \"\",\n \"department\": \"\",\n \"grade\": \"\",\n \"location\": \"\",\n \"joining_date\": \"\",\n \"pan_number\": \"\",\n \"uan_number\": \"\",\n \"bank_account\": \"\"\n },\n \"employer_details\": {\n \"company_name\": \"\",\n \"company_address\": \"\",\n \"employer_pan\": \"\",\n \"employer_tan\": \"\",\n \"pf_registration\": \"\",\n \"esi_registration\": \"\"\n },\n \"earnings_breakdown\": {\n \"basic_salary\": 0,\n \"hra\": 0,\n \"transport_allowance\": 0,\n \"special_allowance\": 0,\n \"performance_bonus\": 0,\n \"overtime\": 0,\n \"arrears\": 0\n },\n \"deductions\": {\n \"income_tax\": 0,\n \"provident_fund\": 0,\n \"professional_tax\": 0,\n \"health_insurance\": 0,\n \"life_insurance\": 0,\n \"loan_deduction\": 0,\n \"other_deductions\": 0\n },\n \"leave_details\": {\n \"total_days\": 0,\n \"present_days\": 0,\n \"paid_leave\": 0,\n \"loss_of_pay\": 0,\n \"public_holidays\": 0\n },\n \"salary_trends\": {\n \"last_6_months\": [],\n \"average_monthly\": 0,\n \"increment_percentage\": 0,\n \"last_increment_date\": \"\",\n \"bonus_history\": []\n },\n \"compliance_details\": {\n \"pf_contribution\": 0,\n \"esi_contribution\": 0,\n \"tds_deducted\": 0,\n \"form16_available\": false,\n \"salary_certificate\": false\n },\n \"verification_status\": {\n \"employer_verification\": \"unverified\",\n \"bank_credit_confirmation\": false,\n \"tax_compliance\": \"non-compliant\",\n \"document_authenticity\": \"suspicious\"\n }\n}\n```",
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"system_message": "You are an expert financial document analyst. Analyze the OCR extracted text from a salary slip and cross-verify with application data.\n\nExtract and analyze:\n1. Monthly gross and net salary amounts\n2. Employee and employer details\n3. Earnings breakdown (basic, HRA, allowances, bonuses)\n4. Deductions (tax, PF, insurance, etc.)\n5. Leave details and attendance\n6. Compliance information (PF, ESI, TDS)\n7. Cross-match with application data for consistency\n\nReturn the data in the exact same JSON structure format with all required salary analysis fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"employer\": \"\",\n \"employment_duration\": \"\",\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"employee_details\": {\n \"employee_id\": \"\",\n \"full_name\": \"\",\n \"designation\": \"\",\n \"department\": \"\",\n \"grade\": \"\",\n \"location\": \"\",\n \"joining_date\": \"\",\n \"pan_number\": \"\",\n \"uan_number\": \"\",\n \"bank_account\": \"\"\n },\n \"employer_details\": {\n \"company_name\": \"\",\n \"company_address\": \"\",\n \"employer_pan\": \"\",\n \"employer_tan\": \"\",\n \"pf_registration\": \"\",\n \"esi_registration\": \"\"\n },\n \"earnings_breakdown\": {\n \"basic_salary\": 0,\n \"hra\": 0,\n \"transport_allowance\": 0,\n \"special_allowance\": 0,\n \"performance_bonus\": 0,\n \"overtime\": 0,\n \"arrears\": 0\n },\n \"deductions\": {\n \"income_tax\": 0,\n \"provident_fund\": 0,\n \"professional_tax\": 0,\n \"health_insurance\": 0,\n \"life_insurance\": 0,\n \"loan_deduction\": 0,\n \"other_deductions\": 0\n },\n \"leave_details\": {\n \"total_days\": 0,\n \"present_days\": 0,\n \"paid_leave\": 0,\n \"loss_of_pay\": 0,\n \"public_holidays\": 0\n },\n \"salary_trends\": {\n \"last_6_months\": [],\n \"average_monthly\": 0,\n \"increment_percentage\": 0,\n \"last_increment_date\": \"\",\n \"bonus_history\": []\n },\n \"compliance_details\": {\n \"pf_contribution\": 0,\n \"esi_contribution\": 0,\n \"tds_deducted\": 0,\n \"form16_available\": false,\n \"salary_certificate\": false\n },\n \"verification_status\": {\n \"employer_verification\": \"unverified\",\n \"bank_credit_confirmation\": false,\n \"tax_compliance\": \"non-compliant\",\n \"document_authenticity\": \"suspicious\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"employer\\\": \\\"\\\",\\n \\\"employment_duration\\\": \\\"\\\",\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"employee_details\\\": {\\n \\\"employee_id\\\": \\\"\\\",\\n \\\"full_name\\\": \\\"\\\",\\n \\\"designation\\\": \\\"\\\",\\n \\\"department\\\": \\\"\\\",\\n \\\"grade\\\": \\\"\\\",\\n \\\"location\\\": \\\"\\\",\\n \\\"joining_date\\\": \\\"\\\",\\n \\\"pan_number\\\": \\\"\\\",\\n \\\"uan_number\\\": \\\"\\\",\\n \\\"bank_account\\\": \\\"\\\"\\n },\\n \\\"employer_details\\\": {\\n \\\"company_name\\\": \\\"\\\",\\n \\\"company_address\\\": \\\"\\\",\\n \\\"employer_pan\\\": \\\"\\\",\\n \\\"employer_tan\\\": \\\"\\\",\\n \\\"pf_registration\\\": \\\"\\\",\\n \\\"esi_registration\\\": \\\"\\\"\\n },\\n \\\"earnings_breakdown\\\": {\\n \\\"basic_salary\\\": 0,\\n \\\"hra\\\": 0,\\n \\\"transport_allowance\\\": 0,\\n \\\"special_allowance\\\": 0,\\n \\\"performance_bonus\\\": 0,\\n \\\"overtime\\\": 0,\\n \\\"arrears\\\": 0\\n },\\n \\\"deductions\\\": {\\n \\\"income_tax\\\": 0,\\n \\\"provident_fund\\\": 0,\\n \\\"professional_tax\\\": 0,\\n \\\"health_insurance\\\": 0,\\n \\\"life_insurance\\\": 0,\\n \\\"loan_deduction\\\": 0,\\n \\\"other_deductions\\\": 0\\n },\\n \\\"leave_details\\\": {\\n \\\"total_days\\\": 0,\\n \\\"present_days\\\": 0,\\n \\\"paid_leave\\\": 0,\\n \\\"loss_of_pay\\\": 0,\\n \\\"public_holidays\\\": 0\\n },\\n \\\"salary_trends\\\": {\\n \\\"last_6_months\\\": [],\\n \\\"average_monthly\\\": 0,\\n \\\"increment_percentage\\\": 0,\\n \\\"last_increment_date\\\": \\\"\\\",\\n \\\"bonus_history\\\": []\\n },\\n \\\"compliance_details\\\": {\\n \\\"pf_contribution\\\": 0,\\n \\\"esi_contribution\\\": 0,\\n \\\"tds_deducted\\\": 0,\\n \\\"form16_available\\\": false,\\n \\\"salary_certificate\\\": false\\n },\\n \\\"verification_status\\\": {\\n \\\"employer_verification\\\": \\\"unverified\\\",\\n \\\"bank_credit_confirmation\\\": false,\\n \\\"tax_compliance\\\": \\\"non-compliant\\\",\\n \\\"document_authenticity\\\": \\\"suspicious\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2893, \"completion_tokens\": 519, \"total_tokens\": 3412, \"estimated_cost\": {\"amount\": 0.000745, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"employer\": \"\",\n \"employment_duration\": \"\",\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"employee_details\": {\n \"employee_id\": \"\",\n \"full_name\": \"\",\n \"designation\": \"\",\n \"department\": \"\",\n \"grade\": \"\",\n \"location\": \"\",\n \"joining_date\": \"\",\n \"pan_number\": \"\",\n \"uan_number\": \"\",\n \"bank_account\": \"\"\n },\n \"employer_details\": {\n \"company_name\": \"\",\n \"company_address\": \"\",\n \"employer_pan\": \"\",\n \"employer_tan\": \"\",\n \"pf_registration\": \"\",\n \"esi_registration\": \"\"\n },\n \"earnings_breakdown\": {\n \"basic_salary\": 0,\n \"hra\": 0,\n \"transport_allowance\": 0,\n \"special_allowance\": 0,\n \"performance_bonus\": 0,\n \"overtime\": 0,\n \"arrears\": 0\n },\n \"deductions\": {\n \"income_tax\": 0,\n \"provident_fund\": 0,\n \"professional_tax\": 0,\n \"health_insurance\": 0,\n \"life_insurance\": 0,\n \"loan_deduction\": 0,\n \"other_deductions\": 0\n },\n \"leave_details\": {\n \"total_days\": 0,\n \"present_days\": 0,\n \"paid_leave\": 0,\n \"loss_of_pay\": 0,\n \"public_holidays\": 0\n },\n \"salary_trends\": {\n \"last_6_months\": [],\n \"average_monthly\": 0,\n \"increment_percentage\": 0,\n \"last_increment_date\": \"\",\n \"bonus_history\": []\n },\n \"compliance_details\": {\n \"pf_contribution\": 0,\n \"esi_contribution\": 0,\n \"tds_deducted\": 0,\n \"form16_available\": false,\n \"salary_certificate\": false\n },\n \"verification_status\": {\n \"employer_verification\": \"unverified\",\n \"bank_credit_confirmation\": false,\n \"tax_compliance\": \"non-compliant\",\n \"document_authenticity\": \"suspicious\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"employer\\\": \\\"\\\",\\n \\\"employment_duration\\\": \\\"\\\",\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"employee_details\\\": {\\n \\\"employee_id\\\": \\\"\\\",\\n \\\"full_name\\\": \\\"\\\",\\n \\\"designation\\\": \\\"\\\",\\n \\\"department\\\": \\\"\\\",\\n \\\"grade\\\": \\\"\\\",\\n \\\"location\\\": \\\"\\\",\\n \\\"joining_date\\\": \\\"\\\",\\n \\\"pan_number\\\": \\\"\\\",\\n \\\"uan_number\\\": \\\"\\\",\\n \\\"bank_account\\\": \\\"\\\"\\n },\\n \\\"employer_details\\\": {\\n \\\"company_name\\\": \\\"\\\",\\n \\\"company_address\\\": \\\"\\\",\\n \\\"employer_pan\\\": \\\"\\\",\\n \\\"employer_tan\\\": \\\"\\\",\\n \\\"pf_registration\\\": \\\"\\\",\\n \\\"esi_registration\\\": \\\"\\\"\\n },\\n \\\"earnings_breakdown\\\": {\\n \\\"basic_salary\\\": 0,\\n \\\"hra\\\": 0,\\n \\\"transport_allowance\\\": 0,\\n \\\"special_allowance\\\": 0,\\n \\\"performance_bonus\\\": 0,\\n \\\"overtime\\\": 0,\\n \\\"arrears\\\": 0\\n },\\n \\\"deductions\\\": {\\n \\\"income_tax\\\": 0,\\n \\\"provident_fund\\\": 0,\\n \\\"professional_tax\\\": 0,\\n \\\"health_insurance\\\": 0,\\n \\\"life_insurance\\\": 0,\\n \\\"loan_deduction\\\": 0,\\n \\\"other_deductions\\\": 0\\n },\\n \\\"leave_details\\\": {\\n \\\"total_days\\\": 0,\\n \\\"present_days\\\": 0,\\n \\\"paid_leave\\\": 0,\\n \\\"loss_of_pay\\\": 0,\\n \\\"public_holidays\\\": 0\\n },\\n \\\"salary_trends\\\": {\\n \\\"last_6_months\\\": [],\\n \\\"average_monthly\\\": 0,\\n \\\"increment_percentage\\\": 0,\\n \\\"last_increment_date\\\": \\\"\\\",\\n \\\"bonus_history\\\": []\\n },\\n \\\"compliance_details\\\": {\\n \\\"pf_contribution\\\": 0,\\n \\\"esi_contribution\\\": 0,\\n \\\"tds_deducted\\\": 0,\\n \\\"form16_available\\\": false,\\n \\\"salary_certificate\\\": false\\n },\\n \\\"verification_status\\\": {\\n \\\"employer_verification\\\": \\\"unverified\\\",\\n \\\"bank_credit_confirmation\\\": false,\\n \\\"tax_compliance\\\": \\\"non-compliant\\\",\\n \\\"document_authenticity\\\": \\\"suspicious\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2893, \"completion_tokens\": 519, \"total_tokens\": 3412, \"estimated_cost\": {\"amount\": 0.000745, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [\n \"full_name\",\n \"email\",\n \"phone\",\n \"address\",\n \"employment_status\",\n \"annual_income\"\n ],\n \"validation_passed\": false,\n \"completion_percentage\": 0.0\n },\n \"consistency_of_information\": {\n \"status\": \"inconsistent\",\n \"reason\": \"No information provided to assess consistency.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"red_flags\": [\n \"All required fields are missing, indicating a lack of effort or potential issues with the application process.\"\n ]\n },\n \"overall_application_quality_score\": 5\n}\n```",
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"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
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"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [\n \"full_name\",\n \"email\",\n \"phone\",\n \"address\",\n \"employment_status\",\n \"annual_income\"\n ],\n \"validation_passed\": false,\n \"completion_percentage\": 0.0\n },\n \"consistency_of_information\": {\n \"status\": \"inconsistent\",\n \"reason\": \"No information provided to assess consistency.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"red_flags\": [\n \"All required fields are missing, indicating a lack of effort or potential issues with the application process.\"\n ]\n },\n \"overall_application_quality_score\": 5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [\\n \\\"full_name\\\",\\n \\\"email\\\",\\n \\\"phone\\\",\\n \\\"address\\\",\\n \\\"employment_status\\\",\\n \\\"annual_income\\\"\\n ],\\n \\\"validation_passed\\\": false,\\n \\\"completion_percentage\\\": 0.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"No information provided to assess consistency.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"red_flags\\\": [\\n \\\"All required fields are missing, indicating a lack of effort or potential issues with the application process.\\\"\\n ]\\n },\\n \\\"overall_application_quality_score\\\": 5\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 132, \"completion_tokens\": 153, \"total_tokens\": 285, \"estimated_cost\": {\"amount\": 0.000112, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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{
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}
],
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"output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
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},
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"output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
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"output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
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"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpb9qcqooh.py\", line 9, in \u003cmodule\u003e\n monthly_net = UNRESOLVED_analyze_salary_slips.monthly_net\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_analyze_salary_slips\u0027 is not defined\n",
"status": "FAILED",
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"ai_response": "Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\n\n```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk_category\": \"low\",\n \"individual_risk_categories\": {\n \"kyc_risk\": \"low\",\n \"aml_risk\": \"low\",\n \"regulatory_risk\": \"minimal\",\n \"internal_policy_risk\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue monitoring compliance with KYC, AML, and regulatory requirements.\",\n \"Maintain documentation and audit trails to ensure ongoing compliance.\",\n \"Regularly review internal policies to align with any changes in regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Overall Compliance Status**: The overall compliance status is rated as \"compliant,\" indicating that all checks have been met satisfactorily.\n\n2. **Risk Assessment**:\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\n\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\n\n4. **Recommendations for Proceeding**:\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\n - Documentation and audit trails should be kept up to date to ensure compliance.\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\n\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.",
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"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
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"output": "Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\n\n```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk_category\": \"low\",\n \"individual_risk_categories\": {\n \"kyc_risk\": \"low\",\n \"aml_risk\": \"low\",\n \"regulatory_risk\": \"minimal\",\n \"internal_policy_risk\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue monitoring compliance with KYC, AML, and regulatory requirements.\",\n \"Maintain documentation and audit trails to ensure ongoing compliance.\",\n \"Regularly review internal policies to align with any changes in regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Overall Compliance Status**: The overall compliance status is rated as \"compliant,\" indicating that all checks have been met satisfactorily.\n\n2. **Risk Assessment**:\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\n\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\n\n4. **Recommendations for Proceeding**:\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\n - Documentation and audit trails should be kept up to date to ensure compliance.\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\n\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk_category\\\": \\\"low\\\",\\n \\\"individual_risk_categories\\\": {\\n \\\"kyc_risk\\\": \\\"low\\\",\\n \\\"aml_risk\\\": \\\"low\\\",\\n \\\"regulatory_risk\\\": \\\"minimal\\\",\\n \\\"internal_policy_risk\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue monitoring compliance with KYC, AML, and regulatory requirements.\\\",\\n \\\"Maintain documentation and audit trails to ensure ongoing compliance.\\\",\\n \\\"Regularly review internal policies to align with any changes in regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Overall Compliance Status**: The overall compliance status is rated as \\\"compliant,\\\" indicating that all checks have been met satisfactorily.\\n\\n2. **Risk Assessment**:\\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\\n\\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\\n\\n4. **Recommendations for Proceeding**:\\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\\n - Documentation and audit trails should be kept up to date to ensure compliance.\\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\\n\\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5859, \"completion_tokens\": 1084, \"total_tokens\": 6943, \"estimated_cost\": {\"amount\": 0.001529, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\n\n```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk_category\": \"low\",\n \"individual_risk_categories\": {\n \"kyc_risk\": \"low\",\n \"aml_risk\": \"low\",\n \"regulatory_risk\": \"minimal\",\n \"internal_policy_risk\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue monitoring compliance with KYC, AML, and regulatory requirements.\",\n \"Maintain documentation and audit trails to ensure ongoing compliance.\",\n \"Regularly review internal policies to align with any changes in regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Overall Compliance Status**: The overall compliance status is rated as \"compliant,\" indicating that all checks have been met satisfactorily.\n\n2. **Risk Assessment**:\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\n\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\n\n4. **Recommendations for Proceeding**:\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\n - Documentation and audit trails should be kept up to date to ensure compliance.\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\n\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a consolidated compliance assessment in JSON format:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk_category\\\": \\\"low\\\",\\n \\\"individual_risk_categories\\\": {\\n \\\"kyc_risk\\\": \\\"low\\\",\\n \\\"aml_risk\\\": \\\"low\\\",\\n \\\"regulatory_risk\\\": \\\"minimal\\\",\\n \\\"internal_policy_risk\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue monitoring compliance with KYC, AML, and regulatory requirements.\\\",\\n \\\"Maintain documentation and audit trails to ensure ongoing compliance.\\\",\\n \\\"Regularly review internal policies to align with any changes in regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Overall Compliance Status**: The overall compliance status is rated as \\\"compliant,\\\" indicating that all checks have been met satisfactorily.\\n\\n2. **Risk Assessment**:\\n - **Overall Risk Category**: Low, indicating a strong compliance posture.\\n - **Individual Risk Categories**: Each area (KYC, AML, Regulatory, Internal Policy) is assessed as low or minimal risk.\\n\\n3. **Compliance Gaps or Concerns**: There are no identified gaps or concerns in the compliance checks, indicating that all requirements have been met.\\n\\n4. **Recommendations for Proceeding**:\\n - Ongoing monitoring of compliance requirements is essential to maintain the current status.\\n - Documentation and audit trails should be kept up to date to ensure compliance.\\n - Regular reviews of internal policies are recommended to adapt to any regulatory changes.\\n\\n5. **Compliance Confidence Score**: A score of 97.5 reflects a high level of confidence in the compliance status, based on the scores from KYC, AML, Regulatory, and Internal Policy checks.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5859, \"completion_tokens\": 1084, \"total_tokens\": 6943, \"estimated_cost\": {\"amount\": 0.001529, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "```json\n{\n \"overall_verification_success_rate\": 0.0,\n \"consistency_across_documents\": {\n \"status\": \"inconsistent\",\n \"reason\": \"All documents returned invalid results with missing or non-matching information.\"\n },\n \"risk_factors_identified\": [\n \"All documents are invalid, indicating potential fraud or identity issues.\",\n \"Missing critical information such as names, addresses, and identification numbers.\",\n \"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\",\n \"Suspicious security features noted in the passport and address proof documents.\"\n ],\n \"recommendation_for_proceeding\": {\n \"action\": \"Do not proceed with the application.\",\n \"justification\": \"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\"\n }\n}\n```",
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"output": "```json\n{\n \"overall_verification_success_rate\": 0.0,\n \"consistency_across_documents\": {\n \"status\": \"inconsistent\",\n \"reason\": \"All documents returned invalid results with missing or non-matching information.\"\n },\n \"risk_factors_identified\": [\n \"All documents are invalid, indicating potential fraud or identity issues.\",\n \"Missing critical information such as names, addresses, and identification numbers.\",\n \"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\",\n \"Suspicious security features noted in the passport and address proof documents.\"\n ],\n \"recommendation_for_proceeding\": {\n \"action\": \"Do not proceed with the application.\",\n \"justification\": \"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 0.0,\\n \\\"consistency_across_documents\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"All documents returned invalid results with missing or non-matching information.\\\"\\n },\\n \\\"risk_factors_identified\\\": [\\n \\\"All documents are invalid, indicating potential fraud or identity issues.\\\",\\n \\\"Missing critical information such as names, addresses, and identification numbers.\\\",\\n \\\"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\\\",\\n \\\"Suspicious security features noted in the passport and address proof documents.\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Do not proceed with the application.\\\",\\n \\\"justification\\\": \\\"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 3587, \"completion_tokens\": 192, \"total_tokens\": 3779, \"estimated_cost\": {\"amount\": 0.000653, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "```json\n{\n \"overall_verification_success_rate\": 0.0,\n \"consistency_across_documents\": {\n \"status\": \"inconsistent\",\n \"reason\": \"All documents returned invalid results with missing or non-matching information.\"\n },\n \"risk_factors_identified\": [\n \"All documents are invalid, indicating potential fraud or identity issues.\",\n \"Missing critical information such as names, addresses, and identification numbers.\",\n \"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\",\n \"Suspicious security features noted in the passport and address proof documents.\"\n ],\n \"recommendation_for_proceeding\": {\n \"action\": \"Do not proceed with the application.\",\n \"justification\": \"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 0.0,\\n \\\"consistency_across_documents\\\": {\\n \\\"status\\\": \\\"inconsistent\\\",\\n \\\"reason\\\": \\\"All documents returned invalid results with missing or non-matching information.\\\"\\n },\\n \\\"risk_factors_identified\\\": [\\n \\\"All documents are invalid, indicating potential fraud or identity issues.\\\",\\n \\\"Missing critical information such as names, addresses, and identification numbers.\\\",\\n \\\"Inactive status for Aadhaar and PAN, suggesting they may not be usable for verification.\\\",\\n \\\"Suspicious security features noted in the passport and address proof documents.\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Do not proceed with the application.\\\",\\n \\\"justification\\\": \\\"The complete lack of valid documentation and the presence of multiple red flags indicate a high risk of fraud or misrepresentation. Further investigation is required before considering any approval.\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 3587, \"completion_tokens\": 192, \"total_tokens\": 3779, \"estimated_cost\": {\"amount\": 0.000653, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "Based on the provided credit data, we can analyze the default risk using the following criteria:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n- **Average Account Age**: 32 months\n- **Recent Credit Behavior**: Stable\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Outstanding**: \u20b9125,000\n- **Total Monthly EMI**: \u20b97,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\n- **Repayment Track Record**: Excellent\n\n### 5. Overall Risk Profile\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\n\n### Risk Score Calculation\nConsidering the above factors, we can assign a risk score based on the following criteria:\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 10 points (Excellent)\n- **Credit Utilization**: 10 points (Moderate)\n- **Repayment Patterns**: 10 points (Excellent)\n- **Loan Burden Ratio**: 10 points (Low)\n- **Overall Risk Profile**: 10 points (Stable)\n\n### Total Risk Score\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\n\n### Conclusion\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.",
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"output": "Based on the provided credit data, we can analyze the default risk using the following criteria:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n- **Average Account Age**: 32 months\n- **Recent Credit Behavior**: Stable\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Outstanding**: \u20b9125,000\n- **Total Monthly EMI**: \u20b97,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\n- **Repayment Track Record**: Excellent\n\n### 5. Overall Risk Profile\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\n\n### Risk Score Calculation\nConsidering the above factors, we can assign a risk score based on the following criteria:\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 10 points (Excellent)\n- **Credit Utilization**: 10 points (Moderate)\n- **Repayment Patterns**: 10 points (Excellent)\n- **Loan Burden Ratio**: 10 points (Low)\n- **Overall Risk Profile**: 10 points (Stable)\n\n### Total Risk Score\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\n\n### Conclusion\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we can analyze the default risk using the following criteria:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n- **Average Account Age**: 32 months\\n- **Recent Credit Behavior**: Stable\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Outstanding**: \\u20b9125,000\\n- **Total Monthly EMI**: \\u20b97,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\\n- **Repayment Track Record**: Excellent\\n\\n### 5. Overall Risk Profile\\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\\n\\n### Risk Score Calculation\\nConsidering the above factors, we can assign a risk score based on the following criteria:\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 10 points (Excellent)\\n- **Credit Utilization**: 10 points (Moderate)\\n- **Repayment Patterns**: 10 points (Excellent)\\n- **Loan Burden Ratio**: 10 points (Low)\\n- **Overall Risk Profile**: 10 points (Stable)\\n\\n### Total Risk Score\\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\\n\\n### Conclusion\\nThe individual presents a moderate default risk (70 out of 100), which is manageable. 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"output": "Based on the provided credit data, we can analyze the default risk using the following criteria:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n- **Average Account Age**: 32 months\n- **Recent Credit Behavior**: Stable\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Outstanding**: \u20b9125,000\n- **Total Monthly EMI**: \u20b97,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\n- **Repayment Track Record**: Excellent\n\n### 5. Overall Risk Profile\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\n\n### Risk Score Calculation\nConsidering the above factors, we can assign a risk score based on the following criteria:\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 10 points (Excellent)\n- **Credit Utilization**: 10 points (Moderate)\n- **Repayment Patterns**: 10 points (Excellent)\n- **Loan Burden Ratio**: 10 points (Low)\n- **Overall Risk Profile**: 10 points (Stable)\n\n### Total Risk Score\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\n\n### Conclusion\nThe individual presents a moderate default risk (70 out of 100), which is manageable. With continued good financial habits, they can further improve their credit profile and reduce risk.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we can analyze the default risk using the following criteria:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n- **Average Account Age**: 32 months\\n- **Recent Credit Behavior**: Stable\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within acceptable limits, typically below 30% is ideal but 35% is still manageable)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Outstanding**: \\u20b9125,000\\n- **Total Monthly EMI**: \\u20b97,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income, which is reasonable)\\n- **Repayment Track Record**: Excellent\\n\\n### 5. Overall Risk Profile\\n- The individual has a good credit score and a strong repayment history with no defaults. The credit utilization is slightly above the ideal threshold but still within a manageable range. The loan burden ratio indicates that the individual is not over-leveraged, and the repayment track record is excellent.\\n\\n### Risk Score Calculation\\nConsidering the above factors, we can assign a risk score based on the following criteria:\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 10 points (Excellent)\\n- **Credit Utilization**: 10 points (Moderate)\\n- **Repayment Patterns**: 10 points (Excellent)\\n- **Loan Burden Ratio**: 10 points (Low)\\n- **Overall Risk Profile**: 10 points (Stable)\\n\\n### Total Risk Score\\n- **Risk Score**: 20 + 10 + 10 + 10 + 10 + 10 = **70 out of 100**\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to make payments on time to maintain the excellent repayment history.\\n2. **Monitor Credit Utilization**: Aim to reduce credit utilization below 30% to improve creditworthiness further.\\n3. **Avoid New Credit Inquiries**: Limit new credit inquiries to avoid potential negative impacts on the credit score.\\n4. **Consider Debt Repayment Strategies**: If possible, consider paying down the outstanding loans to further reduce the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on the credit report for any discrepancies and ensure all information is accurate.\\n\\n### Conclusion\\nThe individual presents a moderate default risk (70 out of 100), which is manageable. 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"ai_response": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: N/A (not applicable due to decline)\n- **Interest Rate**: N/A\n- **Loan Tenure**: N/A\n- **Repayment Schedule**: N/A\n\n#### Risk Mitigation Measures:\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\n- Recommend the applicant to gather and provide complete documentation before reapplying.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\n\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\n\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\n\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\n\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\n\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\n\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. The applicant is encouraged to rectify these issues and consider reapplying in the future once they have provided complete and verifiable information.\n\n#### Confidence Level: 95\nThis confidence level reflects the strong basis for the decision due to the overwhelming evidence of risk factors and the lack of necessary documentation.",
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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: N/A (not applicable due to decline)\n- **Interest Rate**: N/A\n- **Loan Tenure**: N/A\n- **Repayment Schedule**: N/A\n\n#### Risk Mitigation Measures:\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\n- Recommend the applicant to gather and provide complete documentation before reapplying.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\n\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\n\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\n\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\n\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\n\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\n\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. The applicant is encouraged to rectify these issues and consider reapplying in the future once they have provided complete and verifiable information.\n\n#### Confidence Level: 95\nThis confidence level reflects the strong basis for the decision due to the overwhelming evidence of risk factors and the lack of necessary documentation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: N/A (not applicable due to decline)\\n- **Interest Rate**: N/A\\n- **Loan Tenure**: N/A\\n- **Repayment Schedule**: N/A\\n\\n#### Risk Mitigation Measures:\\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\\n- Recommend the applicant to gather and provide complete documentation before reapplying.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\\n\\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\\n\\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\\n\\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\\n\\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\\n\\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\\n\\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. 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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: N/A (not applicable due to decline)\n- **Interest Rate**: N/A\n- **Loan Tenure**: N/A\n- **Repayment Schedule**: N/A\n\n#### Risk Mitigation Measures:\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\n- Recommend the applicant to gather and provide complete documentation before reapplying.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. This lack of information indicates a significant risk in processing the application.\n\n2. **Document Verification**: All submitted documents returned invalid results, with multiple red flags indicating potential fraud or identity issues. The verification success rate is 0%, and the recommendation is to not proceed with the application due to the high risk of misrepresentation.\n\n3. **Income Assessment**: The income assessment shows zero reported income, with no inflow or outflow patterns in the bank statements. The overall income adequacy score is very low (25 out of 100), indicating that the applicant may not be a suitable candidate for loan underwriting without further verification.\n\n4. **Credit Score**: Although the CIBIL score is 720, which is considered good, the overall risk profile is still high due to the lack of verifiable income and documentation. The applicant has a moderate default risk score of 70 out of 100, which is manageable but not sufficient to offset the other significant risks identified.\n\n5. **Compliance Status**: While the compliance checks indicate a compliant status with low risk in KYC and AML categories, the overall application quality and document verification issues overshadow this positive aspect.\n\n6. **Debt-to-Income Ratio**: The debt-to-income analysis could not be completed due to unresolved issues with income data, further complicating the risk assessment.\n\nGiven the combination of these factors, particularly the lack of valid documentation and critical information, the decision is to decline the loan application. The applicant is encouraged to rectify these issues and consider reapplying in the future once they have provided complete and verifiable information.\n\n#### Confidence Level: 95\nThis confidence level reflects the strong basis for the decision due to the overwhelming evidence of risk factors and the lack of necessary documentation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: N/A (not applicable due to decline)\\n- **Interest Rate**: N/A\\n- **Loan Tenure**: N/A\\n- **Repayment Schedule**: N/A\\n\\n#### Risk Mitigation Measures:\\n- No loan will be issued due to the high risk of fraud and lack of verifiable information.\\n- Recommend the applicant to gather and provide complete documentation before reapplying.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application has a very low quality score (5 out of 100) due to missing critical fields such as full name, email, phone number, address, employment status, and annual income. 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"ai_response": "Based on the provided income data, here is a detailed assessment in JSON format:\n\n```json\n{\n \"income_stability_assessment\": {\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"job_stability_score\": 88.5,\n \"employment_status\": \"permanent\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"tax_compliance_score\": 92.0,\n \"income_growth_trend\": \"positive\"\n },\n \"debt_servicing_capability\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"debt_to_income_ratio\": 0,\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_discipline_evaluation\": {\n \"tax_paid\": 12000,\n \"declared_income\": 98000,\n \"discrepancies_found\": false,\n \"returns_filed_consistently\": true,\n \"verification_with_govt\": true\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"No income data available from salary analysis.\",\n \"Bank statement shows no inflow or outflow patterns.\",\n \"Verification status of employer is unverified.\",\n \"Suspicious document authenticity noted.\"\n ],\n \"recommendations\": [\n \"Obtain complete salary slips and bank statements for verification.\",\n \"Conduct a thorough background check on employment.\",\n \"Request additional documentation to confirm income sources.\"\n ]\n },\n \"overall_income_adequacy_score\": 25\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Income Stability Assessment**:\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\n\n2. **Debt Servicing Capability**:\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\n\n3. **Financial Discipline Evaluation**:\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\n\n4. **Risk Factors and Recommendations**:\n - The lack of income data and unverified employment status are significant risk factors.\n - Recommendations include obtaining further documentation and conducting a thorough background check.\n\n5. **Overall Income Adequacy Score**:\n - Given the lack of income data and potential risks, the overall score is low (25 out of 100), indicating that the individual may not be a suitable candidate for loan underwriting without further verification.",
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"output": "Based on the provided income data, here is a detailed assessment in JSON format:\n\n```json\n{\n \"income_stability_assessment\": {\n \"monthly_gross\": 0,\n \"monthly_net\": 0,\n \"annual_gross\": 0,\n \"annual_net\": 0,\n \"salary_consistency\": false,\n \"recent_increment\": false,\n \"job_stability_score\": 88.5,\n \"employment_status\": \"permanent\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"tax_compliance_score\": 92.0,\n \"income_growth_trend\": \"positive\"\n },\n \"debt_servicing_capability\": {\n \"monthly_inflow\": 0,\n \"monthly_outflow\": 0,\n \"debt_to_income_ratio\": 0,\n \"total_loans\": 0,\n \"emi_amounts\": [],\n \"existing_financial_obligations\": [],\n \"compliance_status\": \"N/A\"\n },\n \"financial_discipline_evaluation\": {\n \"tax_paid\": 12000,\n \"declared_income\": 98000,\n \"discrepancies_found\": false,\n \"returns_filed_consistently\": true,\n \"verification_with_govt\": true\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"No income data available from salary analysis.\",\n \"Bank statement shows no inflow or outflow patterns.\",\n \"Verification status of employer is unverified.\",\n \"Suspicious document authenticity noted.\"\n ],\n \"recommendations\": [\n \"Obtain complete salary slips and bank statements for verification.\",\n \"Conduct a thorough background check on employment.\",\n \"Request additional documentation to confirm income sources.\"\n ]\n },\n \"overall_income_adequacy_score\": 25\n}\n```\n\n### Explanation of the Assessment:\n\n1. **Income Stability Assessment**:\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\n\n2. **Debt Servicing Capability**:\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\n\n3. **Financial Discipline Evaluation**:\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\n\n4. **Risk Factors and Recommendations**:\n - The lack of income data and unverified employment status are significant risk factors.\n - Recommendations include obtaining further documentation and conducting a thorough background check.\n\n5. **Overall Income Adequacy Score**:\n - Given the lack of income data and potential risks, the overall score is low (25 out of 100), indicating that the individual may not be a suitable candidate for loan underwriting without further verification.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data, here is a detailed assessment in JSON format:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_status\\\": \\\"permanent\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"income_growth_trend\\\": \\\"positive\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"tax_paid\\\": 12000,\\n \\\"declared_income\\\": 98000,\\n \\\"discrepancies_found\\\": false,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"verification_with_govt\\\": true\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"No income data available from salary analysis.\\\",\\n \\\"Bank statement shows no inflow or outflow patterns.\\\",\\n \\\"Verification status of employer is unverified.\\\",\\n \\\"Suspicious document authenticity noted.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Obtain complete salary slips and bank statements for verification.\\\",\\n \\\"Conduct a thorough background check on employment.\\\",\\n \\\"Request additional documentation to confirm income sources.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 25\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Income Stability Assessment**:\\n - The monthly and annual income figures are zero, indicating no reported income from salary analysis.\\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\\n\\n2. **Debt Servicing Capability**:\\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\\n\\n3. **Financial Discipline Evaluation**:\\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\\n\\n4. **Risk Factors and Recommendations**:\\n - The lack of income data and unverified employment status are significant risk factors.\\n - Recommendations include obtaining further documentation and conducting a thorough background check.\\n\\n5. **Overall Income Adequacy Score**:\\n - 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The monthly and annual income figures are zero, indicating no reported income from salary analysis.\n - Job stability is rated high (88.5), and the employment is confirmed as permanent, which is a positive sign.\n - Tax compliance is strong, with a score of 92.0 and consistent filing of returns.\n\n2. **Debt Servicing Capability**:\n - There are no inflows or outflows reported, leading to a debt-to-income ratio of zero.\n - No existing loans or EMIs are noted, which may indicate a lack of financial obligations but also raises concerns about income sources.\n\n3. **Financial Discipline Evaluation**:\n - The individual has paid taxes and filed returns consistently, with no discrepancies found, indicating good financial discipline.\n\n4. **Risk Factors and Recommendations**:\n - The lack of income data and unverified employment status are significant risk factors.\n - Recommendations include obtaining further documentation and conducting a thorough background check.\n\n5. **Overall Income Adequacy Score**:\n - Given the lack of income data and potential risks, the overall score is low (25 out of 100), indicating that the individual may not be a suitable candidate for loan underwriting without further verification.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data, here is a detailed assessment in JSON format:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"monthly_gross\\\": 0,\\n \\\"monthly_net\\\": 0,\\n \\\"annual_gross\\\": 0,\\n \\\"annual_net\\\": 0,\\n \\\"salary_consistency\\\": false,\\n \\\"recent_increment\\\": false,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_status\\\": \\\"permanent\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"income_growth_trend\\\": \\\"positive\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_inflow\\\": 0,\\n \\\"monthly_outflow\\\": 0,\\n \\\"debt_to_income_ratio\\\": 0,\\n \\\"total_loans\\\": 0,\\n \\\"emi_amounts\\\": [],\\n \\\"existing_financial_obligations\\\": [],\\n \\\"compliance_status\\\": \\\"N/A\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"tax_paid\\\": 12000,\\n \\\"declared_income\\\": 98000,\\n \\\"discrepancies_found\\\": false,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"verification_with_govt\\\": true\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"No income data available from salary analysis.\\\",\\n \\\"Bank statement shows no inflow or outflow patterns.\\\",\\n \\\"Verification status of employer is unverified.\\\",\\n \\\"Suspicious document authenticity noted.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Obtain complete salary slips and bank statements for verification.\\\",\\n \\\"Conduct a thorough background check on employment.\\\",\\n \\\"Request additional documentation to confirm income sources.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 25\\n}\\n```\\n\\n### Explanation of the Assessment:\\n\\n1. **Income Stability Assessment**:\\n - 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"actual_result": {
"error": null,
"result": [
{
"annotations": null,
"text": "Error performing OCR: Invalid URL format. URL must start with \u0027http://\u0027 or \u0027https://\u0027",
"type": "text"
}
],
"status": "success",
"tool_name": "ocr_image_url"
},
"duration_seconds": 0.564908,
"end_time": "2025-07-16T06:48:46.800035",
"message_sent": true,
"start_time": "2025-07-16T06:48:46.235127",
"timestamp": "2025-07-16T06:48:46.800035",
"worker_executed": true,
"workers_notified": true
},
"output": "Task completed successfully",
"result": [
{
"annotations": null,
"text": "Error performing OCR: Invalid URL format. URL must start with \u0027http://\u0027 or \u0027https://\u0027",
"type": "text"
}
],
"return_code": 0,
"status": "success",
"stderr": "",
"task_id": "ocr_address_proof",
"tool_name": "ocr_image_url"
},
"ocr_bank_statement": {
"error": null,
"execution_details": {
"actual_result": {
"error": null,
"result": [
{
"annotations": null,
"text": "Error performing OCR: Invalid URL format. URL must start with \u0027http://\u0027 or \u0027https://\u0027",
"type": "text"
}
],
"status": "success",
"tool_name": "ocr_image_url"
},
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"start_time": "2025-07-16T06:52:05.547372",
"timestamp": "2025-07-16T06:52:05.900766",
"worker_executed": true,
"workers_notified": true
},
"output": "Task completed successfully",
"result": [
{
"annotations": null,
"text": "Error performing OCR: Invalid URL format. URL must start with \u0027http://\u0027 or \u0027https://\u0027",
"type": "text"
}
],
"return_code": 0,
"status": "success",
"stderr": "",
"task_id": "ocr_bank_statement",
"tool_name": "ocr_image_url"
},
"ocr_pan_card": {
"error": "MCP tool execution failed: Tool execution failed: \u0027NoneType\u0027 object has no attribute \u0027post\u0027",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: MCP tool execution failed: Tool execution failed: \u0027NoneType\u0027 object has no attribute \u0027post\u0027",
"status": "FAILED",
"task_id": "ocr_pan_card"
},
"ocr_passport": {
"error": "MCP tool execution failed: Tool execution failed: \u0027NoneType\u0027 object has no attribute \u0027post\u0027",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: MCP tool execution failed: Tool execution failed: \u0027NoneType\u0027 object has no attribute \u0027post\u0027",
"status": "FAILED",
"task_id": "ocr_passport"
},
"ocr_salary_slip": {
"error": "Python script failed with return code 1: File \"/tmp/tmpfs4ek_sk.py\", line 12\n first_salary_slip_url = \"\n ^\nSyntaxError: unterminated string literal (detected at line 12)\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: File \"/tmp/tmpfs4ek_sk.py\", line 12\n first_salary_slip_url = \"\n ^\nSyntaxError: unterminated string literal (detected at line 12)\n",
"status": "FAILED",
"task_id": "ocr_salary_slip"
},
"ocr_salary_slip_processing": {
"error": null,
"execution_details": {
"actual_result": {
"error": null,
"result": [
{
"annotations": null,
"text": "Error performing OCR: Invalid URL format. URL must start with \u0027http://\u0027 or \u0027https://\u0027",
"type": "text"
}
],
"status": "success",
"tool_name": "ocr_image_url"
},
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},
"output": "Task completed successfully",
"result": [
{
"annotations": null,
"text": "Error performing OCR: Invalid URL format. URL must start with \u0027http://\u0027 or \u0027https://\u0027",
"type": "text"
}
],
"return_code": 0,
"status": "success",
"stderr": "",
"task_id": "ocr_salary_slip_processing",
"tool_name": "ocr_image_url"
},
"regulatory_compliance": {
"audit_trail_complete": true,
"compliance_score": 97.2,
"consumer_protection_compliant": true,
"data_privacy_compliant": true,
"disclosure_requirements_met": true,
"documentation_complete": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.195992,
"end_time": "2025-07-16T06:58:42.961939",
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"timestamp": "2025-07-16T06:58:42.961939",
"worker_executed": true,
"workers_notified": true
},
"lending_norms_compliant": true,
"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"rbi_guidelines_met": true,
"regulatory_risk": "minimal",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "regulatory_compliance"
},
"underwriting_decision_router": {
"all_conditions_checked": [
{
"condition": "${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50",
"name": "high_risk_path",
"result": false,
"route": "decline_path"
},
{
"condition": "${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700",
"name": "conditional_approval_path",
"result": false,
"route": "conditional_path"
},
{
"condition": "${calculate_credit_score.internal_credit_score} \u003e= 700",
"name": "standard_approval_path",
"result": false,
"route": "approval_path"
}
],
"duration_seconds": 0.001415,
"ended_at": "2025-07-16T06:58:52.495959",
"evaluation_details": {},
"execution_details": {
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"output": "Route selected: manual_review_path\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"manual_review_path\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"high_risk_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50\", \"result\": false, \"route\": \"decline_path\"}, {\"name\": \"conditional_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700\", \"result\": false, \"route\": \"conditional_path\"}, {\"name\": \"standard_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 700\", \"result\": false, \"route\": \"approval_path\"}], \"duration_seconds\": 0.001415, \"started_at\": \"2025-07-16T06:58:52.494544\", \"ended_at\": \"2025-07-16T06:58:52.495959\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.196349,
"end_time": "2025-07-16T06:58:52.572995",
"message_sent": true,
"start_time": "2025-07-16T06:58:52.376646",
"timestamp": "2025-07-16T06:58:52.572995",
"worker_executed": true,
"workers_notified": true
},
"output": "Route selected: manual_review_path\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"manual_review_path\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"high_risk_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50\", \"result\": false, \"route\": \"decline_path\"}, {\"name\": \"conditional_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700\", \"result\": false, \"route\": \"conditional_path\"}, {\"name\": \"standard_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 700\", \"result\": false, \"route\": \"approval_path\"}], \"duration_seconds\": 0.001415, \"started_at\": \"2025-07-16T06:58:52.494544\", \"ended_at\": \"2025-07-16T06:58:52.495959\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
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"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"upload_to_supabase": {
"attempted_upload_timestamp": "2025-07-16T07:05:03.784163",
"bucket_name": "loan-approval",
"data_summary": {
"applicant_name": "UNRESOLVED_verify_pan_card.verified_name",
"application_id": "${application_id",
"final_decision": "APPROVED",
"requested_amount": 0
},
"error_message": "{\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}",
"execution_details": {
"actual_result": {
"output": "Generated CSV file: loan_approval_${application_id_20250716_070502.csv\nCSV content size: 2968 characters\nData rows: 1\nColumns: 85\nError uploading to Supabase: {\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\n__OUTPUTS__ {\"upload_status\": \"failed\", \"error_message\": \"{\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_approval_${application_id_20250716_070502.csv\", \"attempted_upload_timestamp\": \"2025-07-16T07:05:03.784163\", \"records_prepared\": 1, \"data_summary\": {\"application_id\": \"${application_id\", \"applicant_name\": \"UNRESOLVED_verify_pan_card.verified_name\", \"requested_amount\": 0, \"final_decision\": \"APPROVED\"}}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.63386,
"end_time": "2025-07-16T07:05:04.077793",
"message_sent": true,
"start_time": "2025-07-16T07:05:01.443933",
"timestamp": "2025-07-16T07:05:04.077793",
"worker_executed": true,
"workers_notified": true
},
"filename": "loan_approval_${application_id_20250716_070502.csv",
"output": "Generated CSV file: loan_approval_${application_id_20250716_070502.csv\nCSV content size: 2968 characters\nData rows: 1\nColumns: 85\nError uploading to Supabase: {\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\n__OUTPUTS__ {\"upload_status\": \"failed\", \"error_message\": \"{\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_approval_${application_id_20250716_070502.csv\", \"attempted_upload_timestamp\": \"2025-07-16T07:05:03.784163\", \"records_prepared\": 1, \"data_summary\": {\"application_id\": \"${application_id\", \"applicant_name\": \"UNRESOLVED_verify_pan_card.verified_name\", \"requested_amount\": 0, \"final_decision\": \"APPROVED\"}}\n",
"records_prepared": 1,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "upload_to_supabase",
"upload_status": "failed"
},
"validate_application_fields": {
"completion_percentage": 0.0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"validation_passed\": false, \"missing_fields\": [\"full_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\"], \"completion_percentage\": 0.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.211558,
"end_time": "2025-07-16T06:48:41.984646",
"message_sent": true,
"start_time": "2025-07-16T06:48:41.773088",
"timestamp": "2025-07-16T06:48:41.984646",
"worker_executed": true,
"workers_notified": true
},
"missing_fields": [
"full_name",
"email",
"phone",
"address",
"employment_status",
"annual_income"
],
"output": "__OUTPUTS__ {\"validation_passed\": false, \"missing_fields\": [\"full_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\"], \"completion_percentage\": 0.0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "validate_application_fields",
"validation_passed": false
},
"verify_aadhaar": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"aadhaar_masked\": \"XXXX-XXXX-1234\",\n \"is_valid\": false,\n \"address_match\": false,\n \"biometric_verified\": false,\n \"verification_score\": 0,\n \"last_updated\": \"2023-10-01\",\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"mobile_verified\": false,\n \"email_verified\": false,\n \"registered_address\": {\n \"care_of\": \"\",\n \"building\": \"\",\n \"street\": \"\",\n \"area\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"aadhaar_generation_date\": \"N/A\",\n \"aadhaar_update_history\": [],\n \"linked_services\": {},\n \"biometric_details\": {},\n \"demographic_verification\": {\n \"name_similarity\": 0,\n \"address_similarity\": 0,\n \"date_birth_match\": false,\n \"gender_match\": false\n },\n \"aadhaar_status\": \"Inactive\",\n \"verification_timestamp\": \"2023-10-01T12:00:00Z\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1528,
"model": "gpt-4o-mini",
"output_length": 891,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from an Aadhaar card and cross-verify with application data.\n\nExtract and verify:\n1. Aadhaar number (mask it for privacy as XXXX-XXXX-1234)\n2. Personal details (name, father\u0027s name, DOB, gender)\n3. Address information\n4. Cross-match with application data for consistency\n5. Document authenticity indicators\n6. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"aadhaar_masked\": \"XXXX-XXXX-1234\",\n \"is_valid\": false,\n \"address_match\": false,\n \"biometric_verified\": false,\n \"verification_score\": 0,\n \"last_updated\": \"2023-10-01\",\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"mobile_verified\": false,\n \"email_verified\": false,\n \"registered_address\": {\n \"care_of\": \"\",\n \"building\": \"\",\n \"street\": \"\",\n \"area\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"aadhaar_generation_date\": \"N/A\",\n \"aadhaar_update_history\": [],\n \"linked_services\": {},\n \"biometric_details\": {},\n \"demographic_verification\": {\n \"name_similarity\": 0,\n \"address_similarity\": 0,\n \"date_birth_match\": false,\n \"gender_match\": false\n },\n \"aadhaar_status\": \"Inactive\",\n \"verification_timestamp\": \"2023-10-01T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"aadhaar_masked\\\": \\\"XXXX-XXXX-1234\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"biometric_verified\\\": false,\\n \\\"verification_score\\\": 0,\\n \\\"last_updated\\\": \\\"2023-10-01\\\",\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"mobile_verified\\\": false,\\n \\\"email_verified\\\": false,\\n \\\"registered_address\\\": {\\n \\\"care_of\\\": \\\"\\\",\\n \\\"building\\\": \\\"\\\",\\n \\\"street\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"aadhaar_generation_date\\\": \\\"N/A\\\",\\n \\\"aadhaar_update_history\\\": [],\\n \\\"linked_services\\\": {},\\n \\\"biometric_details\\\": {},\\n \\\"demographic_verification\\\": {\\n \\\"name_similarity\\\": 0,\\n \\\"address_similarity\\\": 0,\\n \\\"date_birth_match\\\": false,\\n \\\"gender_match\\\": false\\n },\\n \\\"aadhaar_status\\\": \\\"Inactive\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-01T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 699, \"completion_tokens\": 273, \"total_tokens\": 972, \"estimated_cost\": {\"amount\": 0.000269, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 273,
"estimated_cost": {
"amount": 0.000269,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 699,
"provider": "openai",
"total_tokens": 972
}
},
"duration_seconds": 5.764202,
"end_time": "2025-07-16T06:48:52.499739",
"message_sent": true,
"start_time": "2025-07-16T06:48:46.735537",
"timestamp": "2025-07-16T06:48:52.499739",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"aadhaar_masked\": \"XXXX-XXXX-1234\",\n \"is_valid\": false,\n \"address_match\": false,\n \"biometric_verified\": false,\n \"verification_score\": 0,\n \"last_updated\": \"2023-10-01\",\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"mobile_verified\": false,\n \"email_verified\": false,\n \"registered_address\": {\n \"care_of\": \"\",\n \"building\": \"\",\n \"street\": \"\",\n \"area\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"aadhaar_generation_date\": \"N/A\",\n \"aadhaar_update_history\": [],\n \"linked_services\": {},\n \"biometric_details\": {},\n \"demographic_verification\": {\n \"name_similarity\": 0,\n \"address_similarity\": 0,\n \"date_birth_match\": false,\n \"gender_match\": false\n },\n \"aadhaar_status\": \"Inactive\",\n \"verification_timestamp\": \"2023-10-01T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"aadhaar_masked\\\": \\\"XXXX-XXXX-1234\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"biometric_verified\\\": false,\\n \\\"verification_score\\\": 0,\\n \\\"last_updated\\\": \\\"2023-10-01\\\",\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"mobile_verified\\\": false,\\n \\\"email_verified\\\": false,\\n \\\"registered_address\\\": {\\n \\\"care_of\\\": \\\"\\\",\\n \\\"building\\\": \\\"\\\",\\n \\\"street\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"aadhaar_generation_date\\\": \\\"N/A\\\",\\n \\\"aadhaar_update_history\\\": [],\\n \\\"linked_services\\\": {},\\n \\\"biometric_details\\\": {},\\n \\\"demographic_verification\\\": {\\n \\\"name_similarity\\\": 0,\\n \\\"address_similarity\\\": 0,\\n \\\"date_birth_match\\\": false,\\n \\\"gender_match\\\": false\\n },\\n \\\"aadhaar_status\\\": \\\"Inactive\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-01T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 699, \"completion_tokens\": 273, \"total_tokens\": 972, \"estimated_cost\": {\"amount\": 0.000269, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"token_usage": {
"completion_tokens": 273,
"estimated_cost": {
"amount": 0.000269,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 699,
"provider": "openai",
"total_tokens": 972
}
},
"verify_address_proof": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"document_type\": \"unknown\",\n \"is_valid\": false,\n \"address_match\": false,\n \"document_date\": null,\n \"verification_score\": 0,\n \"address_confirmed\": null,\n \"document_issuer\": null,\n \"consumer_name\": null,\n \"consumer_number\": null,\n \"billing_period\": null,\n \"detailed_address\": {\n \"house_number\": \"\",\n \"street_name\": \"\",\n \"area\": \"\",\n \"locality\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"service_details\": {\n \"service_type\": \"\",\n \"connection_type\": \"\",\n \"load_sanctioned\": \"\",\n \"meter_number\": \"\",\n \"account_status\": \"\"\n },\n \"billing_information\": {\n \"current_reading\": 0,\n \"previous_reading\": 0,\n \"units_consumed\": 0,\n \"bill_amount\": 0.0,\n \"payment_status\": \"\",\n \"payment_date\": \"\"\n },\n \"document_verification\": {\n \"watermark_verified\": false,\n \"official_seal\": false,\n \"barcode_verified\": false,\n \"digital_signature\": \"failed\"\n },\n \"address_validation\": {\n \"geographic_coordinates\": {\n \"latitude\": 0.0,\n \"longitude\": 0.0\n },\n \"postal_verification\": \"failed\",\n \"google_maps_verified\": false,\n \"delivery_confirmation\": \"failed\"\n },\n \"usage_pattern\": {\n \"average_monthly_consumption\": 0,\n \"seasonal_variation\": \"\",\n \"payment_history\": \"\",\n \"account_age\": \"\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 2111,
"model": "gpt-4o-mini",
"output_length": 1403,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from an address proof document and cross-verify with application data.\n\nExtract and verify:\n1. Document type (utility_bill, bank_statement, rental_agreement, etc.)\n2. Address details and match with application address\n3. Document issuer and consumer information\n4. Document date and validity\n5. Cross-match with application data for consistency\n6. Document authenticity indicators\n7. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required address proof verification fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"document_type\": \"unknown\",\n \"is_valid\": false,\n \"address_match\": false,\n \"document_date\": null,\n \"verification_score\": 0,\n \"address_confirmed\": null,\n \"document_issuer\": null,\n \"consumer_name\": null,\n \"consumer_number\": null,\n \"billing_period\": null,\n \"detailed_address\": {\n \"house_number\": \"\",\n \"street_name\": \"\",\n \"area\": \"\",\n \"locality\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"service_details\": {\n \"service_type\": \"\",\n \"connection_type\": \"\",\n \"load_sanctioned\": \"\",\n \"meter_number\": \"\",\n \"account_status\": \"\"\n },\n \"billing_information\": {\n \"current_reading\": 0,\n \"previous_reading\": 0,\n \"units_consumed\": 0,\n \"bill_amount\": 0.0,\n \"payment_status\": \"\",\n \"payment_date\": \"\"\n },\n \"document_verification\": {\n \"watermark_verified\": false,\n \"official_seal\": false,\n \"barcode_verified\": false,\n \"digital_signature\": \"failed\"\n },\n \"address_validation\": {\n \"geographic_coordinates\": {\n \"latitude\": 0.0,\n \"longitude\": 0.0\n },\n \"postal_verification\": \"failed\",\n \"google_maps_verified\": false,\n \"delivery_confirmation\": \"failed\"\n },\n \"usage_pattern\": {\n \"average_monthly_consumption\": 0,\n \"seasonal_variation\": \"\",\n \"payment_history\": \"\",\n \"account_age\": \"\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"document_type\\\": \\\"unknown\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"document_date\\\": null,\\n \\\"verification_score\\\": 0,\\n \\\"address_confirmed\\\": null,\\n \\\"document_issuer\\\": null,\\n \\\"consumer_name\\\": null,\\n \\\"consumer_number\\\": null,\\n \\\"billing_period\\\": null,\\n \\\"detailed_address\\\": {\\n \\\"house_number\\\": \\\"\\\",\\n \\\"street_name\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"locality\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"service_details\\\": {\\n \\\"service_type\\\": \\\"\\\",\\n \\\"connection_type\\\": \\\"\\\",\\n \\\"load_sanctioned\\\": \\\"\\\",\\n \\\"meter_number\\\": \\\"\\\",\\n \\\"account_status\\\": \\\"\\\"\\n },\\n \\\"billing_information\\\": {\\n \\\"current_reading\\\": 0,\\n \\\"previous_reading\\\": 0,\\n \\\"units_consumed\\\": 0,\\n \\\"bill_amount\\\": 0.0,\\n \\\"payment_status\\\": \\\"\\\",\\n \\\"payment_date\\\": \\\"\\\"\\n },\\n \\\"document_verification\\\": {\\n \\\"watermark_verified\\\": false,\\n \\\"official_seal\\\": false,\\n \\\"barcode_verified\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"address_validation\\\": {\\n \\\"geographic_coordinates\\\": {\\n \\\"latitude\\\": 0.0,\\n \\\"longitude\\\": 0.0\\n },\\n \\\"postal_verification\\\": \\\"failed\\\",\\n \\\"google_maps_verified\\\": false,\\n \\\"delivery_confirmation\\\": \\\"failed\\\"\\n },\\n \\\"usage_pattern\\\": {\\n \\\"average_monthly_consumption\\\": 0,\\n \\\"seasonal_variation\\\": \\\"\\\",\\n \\\"payment_history\\\": \\\"\\\",\\n \\\"account_age\\\": \\\"\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1549, \"completion_tokens\": 670, \"total_tokens\": 2219, \"estimated_cost\": {\"amount\": 0.000634, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 670,
"estimated_cost": {
"amount": 0.000634,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1549,
"provider": "openai",
"total_tokens": 2219
}
},
"duration_seconds": 9.29969,
"end_time": "2025-07-16T06:48:56.148206",
"message_sent": true,
"start_time": "2025-07-16T06:48:46.848516",
"timestamp": "2025-07-16T06:48:56.148206",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"document_type\": \"unknown\",\n \"is_valid\": false,\n \"address_match\": false,\n \"document_date\": null,\n \"verification_score\": 0,\n \"address_confirmed\": null,\n \"document_issuer\": null,\n \"consumer_name\": null,\n \"consumer_number\": null,\n \"billing_period\": null,\n \"detailed_address\": {\n \"house_number\": \"\",\n \"street_name\": \"\",\n \"area\": \"\",\n \"locality\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"service_details\": {\n \"service_type\": \"\",\n \"connection_type\": \"\",\n \"load_sanctioned\": \"\",\n \"meter_number\": \"\",\n \"account_status\": \"\"\n },\n \"billing_information\": {\n \"current_reading\": 0,\n \"previous_reading\": 0,\n \"units_consumed\": 0,\n \"bill_amount\": 0.0,\n \"payment_status\": \"\",\n \"payment_date\": \"\"\n },\n \"document_verification\": {\n \"watermark_verified\": false,\n \"official_seal\": false,\n \"barcode_verified\": false,\n \"digital_signature\": \"failed\"\n },\n \"address_validation\": {\n \"geographic_coordinates\": {\n \"latitude\": 0.0,\n \"longitude\": 0.0\n },\n \"postal_verification\": \"failed\",\n \"google_maps_verified\": false,\n \"delivery_confirmation\": \"failed\"\n },\n \"usage_pattern\": {\n \"average_monthly_consumption\": 0,\n \"seasonal_variation\": \"\",\n \"payment_history\": \"\",\n \"account_age\": \"\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"document_type\\\": \\\"unknown\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"document_date\\\": null,\\n \\\"verification_score\\\": 0,\\n \\\"address_confirmed\\\": null,\\n \\\"document_issuer\\\": null,\\n \\\"consumer_name\\\": null,\\n \\\"consumer_number\\\": null,\\n \\\"billing_period\\\": null,\\n \\\"detailed_address\\\": {\\n \\\"house_number\\\": \\\"\\\",\\n \\\"street_name\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"locality\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"service_details\\\": {\\n \\\"service_type\\\": \\\"\\\",\\n \\\"connection_type\\\": \\\"\\\",\\n \\\"load_sanctioned\\\": \\\"\\\",\\n \\\"meter_number\\\": \\\"\\\",\\n \\\"account_status\\\": \\\"\\\"\\n },\\n \\\"billing_information\\\": {\\n \\\"current_reading\\\": 0,\\n \\\"previous_reading\\\": 0,\\n \\\"units_consumed\\\": 0,\\n \\\"bill_amount\\\": 0.0,\\n \\\"payment_status\\\": \\\"\\\",\\n \\\"payment_date\\\": \\\"\\\"\\n },\\n \\\"document_verification\\\": {\\n \\\"watermark_verified\\\": false,\\n \\\"official_seal\\\": false,\\n \\\"barcode_verified\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"address_validation\\\": {\\n \\\"geographic_coordinates\\\": {\\n \\\"latitude\\\": 0.0,\\n \\\"longitude\\\": 0.0\\n },\\n \\\"postal_verification\\\": \\\"failed\\\",\\n \\\"google_maps_verified\\\": false,\\n \\\"delivery_confirmation\\\": \\\"failed\\\"\\n },\\n \\\"usage_pattern\\\": {\\n \\\"average_monthly_consumption\\\": 0,\\n \\\"seasonal_variation\\\": \\\"\\\",\\n \\\"payment_history\\\": \\\"\\\",\\n \\\"account_age\\\": \\\"\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1549, \"completion_tokens\": 670, \"total_tokens\": 2219, \"estimated_cost\": {\"amount\": 0.000634, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"token_usage": {
"completion_tokens": 670,
"estimated_cost": {
"amount": 0.000634,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1549,
"provider": "openai",
"total_tokens": 2219
}
},
"verify_employment": {
"designation": "Senior Software Engineer",
"employer_rating": "A+",
"employment_confirmed": true,
"employment_type": "permanent",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.349873,
"end_time": "2025-07-16T06:55:16.195339",
"message_sent": true,
"start_time": "2025-07-16T06:55:15.845466",
"timestamp": "2025-07-16T06:55:16.195339",
"worker_executed": true,
"workers_notified": true
},
"hr_contact_verified": true,
"job_stability_score": 88.5,
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"probation_status": "confirmed",
"reference_check_passed": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_employment"
},
"verify_pan_card": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"pan_number\": \"N/A\",\n \"is_valid\": false,\n \"name_match\": false,\n \"status\": \"inactive\",\n \"verification_score\": 0,\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"registered_address\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"pan_issue_date\": \"N/A\",\n \"pan_category\": \"Individual\",\n \"aadhaar_linked\": false,\n \"mobile_linked\": false,\n \"email_linked\": false,\n \"jurisdiction\": \"N/A\",\n \"assessing_officer\": \"N/A\",\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\",\n \"document_quality\": {\n \"image_clarity\": 0,\n \"tamper_detection\": \"no_tampering\",\n \"security_features\": \"suspicious\",\n \"ocr_confidence\": 0\n },\n \"tax_compliance\": {\n \"returns_filed\": false,\n \"last_return_year\": \"N/A\",\n \"compliance_rating\": \"Poor\"\n }\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1402,
"model": "gpt-4o-mini",
"output_length": 866,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from a PAN card and cross-verify with application data.\n\nExtract and verify:\n1. PAN number (10 character alphanumeric)\n2. Personal details (name, father\u0027s name, DOB)\n3. Address information\n4. Cross-match with application data for consistency\n5. Document authenticity indicators\n6. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required PAN verification fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"pan_number\": \"N/A\",\n \"is_valid\": false,\n \"name_match\": false,\n \"status\": \"inactive\",\n \"verification_score\": 0,\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"registered_address\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"pan_issue_date\": \"N/A\",\n \"pan_category\": \"Individual\",\n \"aadhaar_linked\": false,\n \"mobile_linked\": false,\n \"email_linked\": false,\n \"jurisdiction\": \"N/A\",\n \"assessing_officer\": \"N/A\",\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\",\n \"document_quality\": {\n \"image_clarity\": 0,\n \"tamper_detection\": \"no_tampering\",\n \"security_features\": \"suspicious\",\n \"ocr_confidence\": 0\n },\n \"tax_compliance\": {\n \"returns_filed\": false,\n \"last_return_year\": \"N/A\",\n \"compliance_rating\": \"Poor\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"pan_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"name_match\\\": false,\\n \\\"status\\\": \\\"inactive\\\",\\n \\\"verification_score\\\": 0,\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"registered_address\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"pan_issue_date\\\": \\\"N/A\\\",\\n \\\"pan_category\\\": \\\"Individual\\\",\\n \\\"aadhaar_linked\\\": false,\\n \\\"mobile_linked\\\": false,\\n \\\"email_linked\\\": false,\\n \\\"jurisdiction\\\": \\\"N/A\\\",\\n \\\"assessing_officer\\\": \\\"N/A\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\",\\n \\\"document_quality\\\": {\\n \\\"image_clarity\\\": 0,\\n \\\"tamper_detection\\\": \\\"no_tampering\\\",\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"ocr_confidence\\\": 0\\n },\\n \\\"tax_compliance\\\": {\\n \\\"returns_filed\\\": false,\\n \\\"last_return_year\\\": \\\"N/A\\\",\\n \\\"compliance_rating\\\": \\\"Poor\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1353, \"completion_tokens\": 282, \"total_tokens\": 1635, \"estimated_cost\": {\"amount\": 0.000372, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 282,
"estimated_cost": {
"amount": 0.000372,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1353,
"provider": "openai",
"total_tokens": 1635
}
},
"duration_seconds": 6.698721,
"end_time": "2025-07-16T06:51:52.790157",
"message_sent": true,
"start_time": "2025-07-16T06:51:46.091436",
"timestamp": "2025-07-16T06:51:52.790157",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"pan_number\": \"N/A\",\n \"is_valid\": false,\n \"name_match\": false,\n \"status\": \"inactive\",\n \"verification_score\": 0,\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"registered_address\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"pan_issue_date\": \"N/A\",\n \"pan_category\": \"Individual\",\n \"aadhaar_linked\": false,\n \"mobile_linked\": false,\n \"email_linked\": false,\n \"jurisdiction\": \"N/A\",\n \"assessing_officer\": \"N/A\",\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\",\n \"document_quality\": {\n \"image_clarity\": 0,\n \"tamper_detection\": \"no_tampering\",\n \"security_features\": \"suspicious\",\n \"ocr_confidence\": 0\n },\n \"tax_compliance\": {\n \"returns_filed\": false,\n \"last_return_year\": \"N/A\",\n \"compliance_rating\": \"Poor\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"pan_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"name_match\\\": false,\\n \\\"status\\\": \\\"inactive\\\",\\n \\\"verification_score\\\": 0,\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"registered_address\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"pan_issue_date\\\": \\\"N/A\\\",\\n \\\"pan_category\\\": \\\"Individual\\\",\\n \\\"aadhaar_linked\\\": false,\\n \\\"mobile_linked\\\": false,\\n \\\"email_linked\\\": false,\\n \\\"jurisdiction\\\": \\\"N/A\\\",\\n \\\"assessing_officer\\\": \\\"N/A\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\",\\n \\\"document_quality\\\": {\\n \\\"image_clarity\\\": 0,\\n \\\"tamper_detection\\\": \\\"no_tampering\\\",\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"ocr_confidence\\\": 0\\n },\\n \\\"tax_compliance\\\": {\\n \\\"returns_filed\\\": false,\\n \\\"last_return_year\\\": \\\"N/A\\\",\\n \\\"compliance_rating\\\": \\\"Poor\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1353, \"completion_tokens\": 282, \"total_tokens\": 1635, \"estimated_cost\": {\"amount\": 0.000372, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"token_usage": {
"completion_tokens": 282,
"estimated_cost": {
"amount": 0.000372,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1353,
"provider": "openai",
"total_tokens": 1635
}
},
"verify_passport": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"passport_number\": \"N/A\",\n \"is_valid\": false,\n \"expiry_date\": \"N/A\",\n \"issuing_authority\": \"Government of India\",\n \"verification_score\": 0,\n \"document_provided\": false,\n \"holder_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"mother_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"place_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"nationality\": \"Indian\",\n \"passport_type\": \"P\",\n \"issue_date\": \"N/A\",\n \"issuing_office\": \"N/A\",\n \"file_number\": \"N/A\",\n \"personal_details\": {\n \"height\": \"\",\n \"identification_marks\": \"\",\n \"blood_group\": \"\",\n \"marital_status\": \"\"\n },\n \"address_in_passport\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"travel_history\": [],\n \"current_visas\": [],\n \"passport_renewals\": 0,\n \"previous_passport_number\": \"\",\n \"emergency_contact\": {\n \"name\": \"\",\n \"relationship\": \"\",\n \"phone\": \"\"\n },\n \"document_security\": {\n \"chip_verified\": false,\n \"security_features\": \"suspicious\",\n \"machine_readable\": false,\n \"digital_signature\": \"failed\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1730,
"model": "gpt-4o-mini",
"output_length": 1134,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from a passport and cross-verify with application data.\n\nExtract and verify:\n1. Passport number, expiry date, issuing authority\n2. Personal details (name, father\u0027s name, mother\u0027s name, DOB, gender)\n3. Address information and travel history\n4. Cross-match with application data for consistency\n5. Document authenticity indicators\n6. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required passport verification fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"passport_number\": \"N/A\",\n \"is_valid\": false,\n \"expiry_date\": \"N/A\",\n \"issuing_authority\": \"Government of India\",\n \"verification_score\": 0,\n \"document_provided\": false,\n \"holder_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"mother_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"place_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"nationality\": \"Indian\",\n \"passport_type\": \"P\",\n \"issue_date\": \"N/A\",\n \"issuing_office\": \"N/A\",\n \"file_number\": \"N/A\",\n \"personal_details\": {\n \"height\": \"\",\n \"identification_marks\": \"\",\n \"blood_group\": \"\",\n \"marital_status\": \"\"\n },\n \"address_in_passport\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"travel_history\": [],\n \"current_visas\": [],\n \"passport_renewals\": 0,\n \"previous_passport_number\": \"\",\n \"emergency_contact\": {\n \"name\": \"\",\n \"relationship\": \"\",\n \"phone\": \"\"\n },\n \"document_security\": {\n \"chip_verified\": false,\n \"security_features\": \"suspicious\",\n \"machine_readable\": false,\n \"digital_signature\": \"failed\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"passport_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"expiry_date\\\": \\\"N/A\\\",\\n \\\"issuing_authority\\\": \\\"Government of India\\\",\\n \\\"verification_score\\\": 0,\\n \\\"document_provided\\\": false,\\n \\\"holder_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"mother_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"place_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"nationality\\\": \\\"Indian\\\",\\n \\\"passport_type\\\": \\\"P\\\",\\n \\\"issue_date\\\": \\\"N/A\\\",\\n \\\"issuing_office\\\": \\\"N/A\\\",\\n \\\"file_number\\\": \\\"N/A\\\",\\n \\\"personal_details\\\": {\\n \\\"height\\\": \\\"\\\",\\n \\\"identification_marks\\\": \\\"\\\",\\n \\\"blood_group\\\": \\\"\\\",\\n \\\"marital_status\\\": \\\"\\\"\\n },\\n \\\"address_in_passport\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"travel_history\\\": [],\\n \\\"current_visas\\\": [],\\n \\\"passport_renewals\\\": 0,\\n \\\"previous_passport_number\\\": \\\"\\\",\\n \\\"emergency_contact\\\": {\\n \\\"name\\\": \\\"\\\",\\n \\\"relationship\\\": \\\"\\\",\\n \\\"phone\\\": \\\"\\\"\\n },\\n \\\"document_security\\\": {\\n \\\"chip_verified\\\": false,\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"machine_readable\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1434, \"completion_tokens\": 353, \"total_tokens\": 1787, \"estimated_cost\": {\"amount\": 0.000427, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 353,
"estimated_cost": {
"amount": 0.000427,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1434,
"provider": "openai",
"total_tokens": 1787
}
},
"duration_seconds": 12.012135,
"end_time": "2025-07-16T06:51:58.256764",
"message_sent": true,
"start_time": "2025-07-16T06:51:46.244629",
"timestamp": "2025-07-16T06:51:58.256764",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"passport_number\": \"N/A\",\n \"is_valid\": false,\n \"expiry_date\": \"N/A\",\n \"issuing_authority\": \"Government of India\",\n \"verification_score\": 0,\n \"document_provided\": false,\n \"holder_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"mother_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"place_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"nationality\": \"Indian\",\n \"passport_type\": \"P\",\n \"issue_date\": \"N/A\",\n \"issuing_office\": \"N/A\",\n \"file_number\": \"N/A\",\n \"personal_details\": {\n \"height\": \"\",\n \"identification_marks\": \"\",\n \"blood_group\": \"\",\n \"marital_status\": \"\"\n },\n \"address_in_passport\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"travel_history\": [],\n \"current_visas\": [],\n \"passport_renewals\": 0,\n \"previous_passport_number\": \"\",\n \"emergency_contact\": {\n \"name\": \"\",\n \"relationship\": \"\",\n \"phone\": \"\"\n },\n \"document_security\": {\n \"chip_verified\": false,\n \"security_features\": \"suspicious\",\n \"machine_readable\": false,\n \"digital_signature\": \"failed\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"passport_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"expiry_date\\\": \\\"N/A\\\",\\n \\\"issuing_authority\\\": \\\"Government of India\\\",\\n \\\"verification_score\\\": 0,\\n \\\"document_provided\\\": false,\\n \\\"holder_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"mother_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"place_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"nationality\\\": \\\"Indian\\\",\\n \\\"passport_type\\\": \\\"P\\\",\\n \\\"issue_date\\\": \\\"N/A\\\",\\n \\\"issuing_office\\\": \\\"N/A\\\",\\n \\\"file_number\\\": \\\"N/A\\\",\\n \\\"personal_details\\\": {\\n \\\"height\\\": \\\"\\\",\\n \\\"identification_marks\\\": \\\"\\\",\\n \\\"blood_group\\\": \\\"\\\",\\n \\\"marital_status\\\": \\\"\\\"\\n },\\n \\\"address_in_passport\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"travel_history\\\": [],\\n \\\"current_visas\\\": [],\\n \\\"passport_renewals\\\": 0,\\n \\\"previous_passport_number\\\": \\\"\\\",\\n \\\"emergency_contact\\\": {\\n \\\"name\\\": \\\"\\\",\\n \\\"relationship\\\": \\\"\\\",\\n \\\"phone\\\": \\\"\\\"\\n },\\n \\\"document_security\\\": {\\n \\\"chip_verified\\\": false,\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"machine_readable\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1434, \"completion_tokens\": 353, \"total_tokens\": 1787, \"estimated_cost\": {\"amount\": 0.000427, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"token_usage": {
"completion_tokens": 353,
"estimated_cost": {
"amount": 0.000427,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1434,
"provider": "openai",
"total_tokens": 1787
}
},
"verify_tax_returns": {
"declared_income": 98000,
"discrepancies_found": false,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.426719,
"end_time": "2025-07-16T06:52:06.040967",
"message_sent": true,
"start_time": "2025-07-16T06:52:05.614248",
"timestamp": "2025-07-16T06:52:06.040967",
"worker_executed": true,
"workers_notified": true
},
"income_growth_trend": "positive",
"output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
"return_code": 0,
"returns_filed_consistently": true,
"status": "completed",
"stderr": "",
"task_id": "verify_tax_returns",
"tax_compliance_score": 92.0,
"tax_paid": 12000,
"verification_with_govt": true
}
},
"underwriting_decision_router": {
"all_conditions_checked": [
{
"condition": "${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50",
"name": "high_risk_path",
"result": false,
"route": "decline_path"
},
{
"condition": "${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700",
"name": "conditional_approval_path",
"result": false,
"route": "conditional_path"
},
{
"condition": "${calculate_credit_score.internal_credit_score} \u003e= 700",
"name": "standard_approval_path",
"result": false,
"route": "approval_path"
}
],
"duration_seconds": 0.001415,
"ended_at": "2025-07-16T06:58:52.495959",
"evaluation_details": {},
"execution_details": {
"actual_result": {
"output": "Route selected: manual_review_path\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"manual_review_path\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"high_risk_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50\", \"result\": false, \"route\": \"decline_path\"}, {\"name\": \"conditional_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700\", \"result\": false, \"route\": \"conditional_path\"}, {\"name\": \"standard_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 700\", \"result\": false, \"route\": \"approval_path\"}], \"duration_seconds\": 0.001415, \"started_at\": \"2025-07-16T06:58:52.494544\", \"ended_at\": \"2025-07-16T06:58:52.495959\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.196349,
"end_time": "2025-07-16T06:58:52.572995",
"message_sent": true,
"start_time": "2025-07-16T06:58:52.376646",
"timestamp": "2025-07-16T06:58:52.572995",
"worker_executed": true,
"workers_notified": true
},
"output": "Route selected: manual_review_path\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"manual_review_path\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"high_risk_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50\", \"result\": false, \"route\": \"decline_path\"}, {\"name\": \"conditional_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700\", \"result\": false, \"route\": \"conditional_path\"}, {\"name\": \"standard_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 700\", \"result\": false, \"route\": \"approval_path\"}], \"duration_seconds\": 0.001415, \"started_at\": \"2025-07-16T06:58:52.494544\", \"ended_at\": \"2025-07-16T06:58:52.495959\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-16T06:58:52.494544",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"upload_to_supabase": {
"attempted_upload_timestamp": "2025-07-16T07:05:03.784163",
"bucket_name": "loan-approval",
"data_summary": {
"applicant_name": "UNRESOLVED_verify_pan_card.verified_name",
"application_id": "${application_id",
"final_decision": "APPROVED",
"requested_amount": 0
},
"error_message": "{\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}",
"execution_details": {
"actual_result": {
"output": "Generated CSV file: loan_approval_${application_id_20250716_070502.csv\nCSV content size: 2968 characters\nData rows: 1\nColumns: 85\nError uploading to Supabase: {\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\n__OUTPUTS__ {\"upload_status\": \"failed\", \"error_message\": \"{\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_approval_${application_id_20250716_070502.csv\", \"attempted_upload_timestamp\": \"2025-07-16T07:05:03.784163\", \"records_prepared\": 1, \"data_summary\": {\"application_id\": \"${application_id\", \"applicant_name\": \"UNRESOLVED_verify_pan_card.verified_name\", \"requested_amount\": 0, \"final_decision\": \"APPROVED\"}}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.63386,
"end_time": "2025-07-16T07:05:04.077793",
"message_sent": true,
"start_time": "2025-07-16T07:05:01.443933",
"timestamp": "2025-07-16T07:05:04.077793",
"worker_executed": true,
"workers_notified": true
},
"filename": "loan_approval_${application_id_20250716_070502.csv",
"output": "Generated CSV file: loan_approval_${application_id_20250716_070502.csv\nCSV content size: 2968 characters\nData rows: 1\nColumns: 85\nError uploading to Supabase: {\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\n__OUTPUTS__ {\"upload_status\": \"failed\", \"error_message\": \"{\u0027statusCode\u0027: 400, \u0027error\u0027: InvalidKey, \u0027message\u0027: Invalid key: loan_approval_${application_id_20250716_070502.csv}\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_approval_${application_id_20250716_070502.csv\", \"attempted_upload_timestamp\": \"2025-07-16T07:05:03.784163\", \"records_prepared\": 1, \"data_summary\": {\"application_id\": \"${application_id\", \"applicant_name\": \"UNRESOLVED_verify_pan_card.verified_name\", \"requested_amount\": 0, \"final_decision\": \"APPROVED\"}}\n",
"records_prepared": 1,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "upload_to_supabase",
"upload_status": "failed"
},
"validate_application_fields": {
"completion_percentage": 0.0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"validation_passed\": false, \"missing_fields\": [\"full_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\"], \"completion_percentage\": 0.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.211558,
"end_time": "2025-07-16T06:48:41.984646",
"message_sent": true,
"start_time": "2025-07-16T06:48:41.773088",
"timestamp": "2025-07-16T06:48:41.984646",
"worker_executed": true,
"workers_notified": true
},
"missing_fields": [
"full_name",
"email",
"phone",
"address",
"employment_status",
"annual_income"
],
"output": "__OUTPUTS__ {\"validation_passed\": false, \"missing_fields\": [\"full_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\"], \"completion_percentage\": 0.0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "validate_application_fields",
"validation_passed": false
},
"verify_aadhaar": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"aadhaar_masked\": \"XXXX-XXXX-1234\",\n \"is_valid\": false,\n \"address_match\": false,\n \"biometric_verified\": false,\n \"verification_score\": 0,\n \"last_updated\": \"2023-10-01\",\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"mobile_verified\": false,\n \"email_verified\": false,\n \"registered_address\": {\n \"care_of\": \"\",\n \"building\": \"\",\n \"street\": \"\",\n \"area\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"aadhaar_generation_date\": \"N/A\",\n \"aadhaar_update_history\": [],\n \"linked_services\": {},\n \"biometric_details\": {},\n \"demographic_verification\": {\n \"name_similarity\": 0,\n \"address_similarity\": 0,\n \"date_birth_match\": false,\n \"gender_match\": false\n },\n \"aadhaar_status\": \"Inactive\",\n \"verification_timestamp\": \"2023-10-01T12:00:00Z\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1528,
"model": "gpt-4o-mini",
"output_length": 891,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from an Aadhaar card and cross-verify with application data.\n\nExtract and verify:\n1. Aadhaar number (mask it for privacy as XXXX-XXXX-1234)\n2. Personal details (name, father\u0027s name, DOB, gender)\n3. Address information\n4. Cross-match with application data for consistency\n5. Document authenticity indicators\n6. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"aadhaar_masked\": \"XXXX-XXXX-1234\",\n \"is_valid\": false,\n \"address_match\": false,\n \"biometric_verified\": false,\n \"verification_score\": 0,\n \"last_updated\": \"2023-10-01\",\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"mobile_verified\": false,\n \"email_verified\": false,\n \"registered_address\": {\n \"care_of\": \"\",\n \"building\": \"\",\n \"street\": \"\",\n \"area\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"aadhaar_generation_date\": \"N/A\",\n \"aadhaar_update_history\": [],\n \"linked_services\": {},\n \"biometric_details\": {},\n \"demographic_verification\": {\n \"name_similarity\": 0,\n \"address_similarity\": 0,\n \"date_birth_match\": false,\n \"gender_match\": false\n },\n \"aadhaar_status\": \"Inactive\",\n \"verification_timestamp\": \"2023-10-01T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"aadhaar_masked\\\": \\\"XXXX-XXXX-1234\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"biometric_verified\\\": false,\\n \\\"verification_score\\\": 0,\\n \\\"last_updated\\\": \\\"2023-10-01\\\",\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"mobile_verified\\\": false,\\n \\\"email_verified\\\": false,\\n \\\"registered_address\\\": {\\n \\\"care_of\\\": \\\"\\\",\\n \\\"building\\\": \\\"\\\",\\n \\\"street\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"aadhaar_generation_date\\\": \\\"N/A\\\",\\n \\\"aadhaar_update_history\\\": [],\\n \\\"linked_services\\\": {},\\n \\\"biometric_details\\\": {},\\n \\\"demographic_verification\\\": {\\n \\\"name_similarity\\\": 0,\\n \\\"address_similarity\\\": 0,\\n \\\"date_birth_match\\\": false,\\n \\\"gender_match\\\": false\\n },\\n \\\"aadhaar_status\\\": \\\"Inactive\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-01T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 699, \"completion_tokens\": 273, \"total_tokens\": 972, \"estimated_cost\": {\"amount\": 0.000269, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 273,
"estimated_cost": {
"amount": 0.000269,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 699,
"provider": "openai",
"total_tokens": 972
}
},
"duration_seconds": 5.764202,
"end_time": "2025-07-16T06:48:52.499739",
"message_sent": true,
"start_time": "2025-07-16T06:48:46.735537",
"timestamp": "2025-07-16T06:48:52.499739",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"aadhaar_masked\": \"XXXX-XXXX-1234\",\n \"is_valid\": false,\n \"address_match\": false,\n \"biometric_verified\": false,\n \"verification_score\": 0,\n \"last_updated\": \"2023-10-01\",\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"mobile_verified\": false,\n \"email_verified\": false,\n \"registered_address\": {\n \"care_of\": \"\",\n \"building\": \"\",\n \"street\": \"\",\n \"area\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"aadhaar_generation_date\": \"N/A\",\n \"aadhaar_update_history\": [],\n \"linked_services\": {},\n \"biometric_details\": {},\n \"demographic_verification\": {\n \"name_similarity\": 0,\n \"address_similarity\": 0,\n \"date_birth_match\": false,\n \"gender_match\": false\n },\n \"aadhaar_status\": \"Inactive\",\n \"verification_timestamp\": \"2023-10-01T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"aadhaar_masked\\\": \\\"XXXX-XXXX-1234\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"biometric_verified\\\": false,\\n \\\"verification_score\\\": 0,\\n \\\"last_updated\\\": \\\"2023-10-01\\\",\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"mobile_verified\\\": false,\\n \\\"email_verified\\\": false,\\n \\\"registered_address\\\": {\\n \\\"care_of\\\": \\\"\\\",\\n \\\"building\\\": \\\"\\\",\\n \\\"street\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"aadhaar_generation_date\\\": \\\"N/A\\\",\\n \\\"aadhaar_update_history\\\": [],\\n \\\"linked_services\\\": {},\\n \\\"biometric_details\\\": {},\\n \\\"demographic_verification\\\": {\\n \\\"name_similarity\\\": 0,\\n \\\"address_similarity\\\": 0,\\n \\\"date_birth_match\\\": false,\\n \\\"gender_match\\\": false\\n },\\n \\\"aadhaar_status\\\": \\\"Inactive\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-01T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 699, \"completion_tokens\": 273, \"total_tokens\": 972, \"estimated_cost\": {\"amount\": 0.000269, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"token_usage": {
"completion_tokens": 273,
"estimated_cost": {
"amount": 0.000269,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 699,
"provider": "openai",
"total_tokens": 972
}
},
"verify_address_proof": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"document_type\": \"unknown\",\n \"is_valid\": false,\n \"address_match\": false,\n \"document_date\": null,\n \"verification_score\": 0,\n \"address_confirmed\": null,\n \"document_issuer\": null,\n \"consumer_name\": null,\n \"consumer_number\": null,\n \"billing_period\": null,\n \"detailed_address\": {\n \"house_number\": \"\",\n \"street_name\": \"\",\n \"area\": \"\",\n \"locality\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"service_details\": {\n \"service_type\": \"\",\n \"connection_type\": \"\",\n \"load_sanctioned\": \"\",\n \"meter_number\": \"\",\n \"account_status\": \"\"\n },\n \"billing_information\": {\n \"current_reading\": 0,\n \"previous_reading\": 0,\n \"units_consumed\": 0,\n \"bill_amount\": 0.0,\n \"payment_status\": \"\",\n \"payment_date\": \"\"\n },\n \"document_verification\": {\n \"watermark_verified\": false,\n \"official_seal\": false,\n \"barcode_verified\": false,\n \"digital_signature\": \"failed\"\n },\n \"address_validation\": {\n \"geographic_coordinates\": {\n \"latitude\": 0.0,\n \"longitude\": 0.0\n },\n \"postal_verification\": \"failed\",\n \"google_maps_verified\": false,\n \"delivery_confirmation\": \"failed\"\n },\n \"usage_pattern\": {\n \"average_monthly_consumption\": 0,\n \"seasonal_variation\": \"\",\n \"payment_history\": \"\",\n \"account_age\": \"\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 2111,
"model": "gpt-4o-mini",
"output_length": 1403,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from an address proof document and cross-verify with application data.\n\nExtract and verify:\n1. Document type (utility_bill, bank_statement, rental_agreement, etc.)\n2. Address details and match with application address\n3. Document issuer and consumer information\n4. Document date and validity\n5. Cross-match with application data for consistency\n6. Document authenticity indicators\n7. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required address proof verification fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"document_type\": \"unknown\",\n \"is_valid\": false,\n \"address_match\": false,\n \"document_date\": null,\n \"verification_score\": 0,\n \"address_confirmed\": null,\n \"document_issuer\": null,\n \"consumer_name\": null,\n \"consumer_number\": null,\n \"billing_period\": null,\n \"detailed_address\": {\n \"house_number\": \"\",\n \"street_name\": \"\",\n \"area\": \"\",\n \"locality\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"service_details\": {\n \"service_type\": \"\",\n \"connection_type\": \"\",\n \"load_sanctioned\": \"\",\n \"meter_number\": \"\",\n \"account_status\": \"\"\n },\n \"billing_information\": {\n \"current_reading\": 0,\n \"previous_reading\": 0,\n \"units_consumed\": 0,\n \"bill_amount\": 0.0,\n \"payment_status\": \"\",\n \"payment_date\": \"\"\n },\n \"document_verification\": {\n \"watermark_verified\": false,\n \"official_seal\": false,\n \"barcode_verified\": false,\n \"digital_signature\": \"failed\"\n },\n \"address_validation\": {\n \"geographic_coordinates\": {\n \"latitude\": 0.0,\n \"longitude\": 0.0\n },\n \"postal_verification\": \"failed\",\n \"google_maps_verified\": false,\n \"delivery_confirmation\": \"failed\"\n },\n \"usage_pattern\": {\n \"average_monthly_consumption\": 0,\n \"seasonal_variation\": \"\",\n \"payment_history\": \"\",\n \"account_age\": \"\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"document_type\\\": \\\"unknown\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"document_date\\\": null,\\n \\\"verification_score\\\": 0,\\n \\\"address_confirmed\\\": null,\\n \\\"document_issuer\\\": null,\\n \\\"consumer_name\\\": null,\\n \\\"consumer_number\\\": null,\\n \\\"billing_period\\\": null,\\n \\\"detailed_address\\\": {\\n \\\"house_number\\\": \\\"\\\",\\n \\\"street_name\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"locality\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"service_details\\\": {\\n \\\"service_type\\\": \\\"\\\",\\n \\\"connection_type\\\": \\\"\\\",\\n \\\"load_sanctioned\\\": \\\"\\\",\\n \\\"meter_number\\\": \\\"\\\",\\n \\\"account_status\\\": \\\"\\\"\\n },\\n \\\"billing_information\\\": {\\n \\\"current_reading\\\": 0,\\n \\\"previous_reading\\\": 0,\\n \\\"units_consumed\\\": 0,\\n \\\"bill_amount\\\": 0.0,\\n \\\"payment_status\\\": \\\"\\\",\\n \\\"payment_date\\\": \\\"\\\"\\n },\\n \\\"document_verification\\\": {\\n \\\"watermark_verified\\\": false,\\n \\\"official_seal\\\": false,\\n \\\"barcode_verified\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"address_validation\\\": {\\n \\\"geographic_coordinates\\\": {\\n \\\"latitude\\\": 0.0,\\n \\\"longitude\\\": 0.0\\n },\\n \\\"postal_verification\\\": \\\"failed\\\",\\n \\\"google_maps_verified\\\": false,\\n \\\"delivery_confirmation\\\": \\\"failed\\\"\\n },\\n \\\"usage_pattern\\\": {\\n \\\"average_monthly_consumption\\\": 0,\\n \\\"seasonal_variation\\\": \\\"\\\",\\n \\\"payment_history\\\": \\\"\\\",\\n \\\"account_age\\\": \\\"\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1549, \"completion_tokens\": 670, \"total_tokens\": 2219, \"estimated_cost\": {\"amount\": 0.000634, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 670,
"estimated_cost": {
"amount": 0.000634,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1549,
"provider": "openai",
"total_tokens": 2219
}
},
"duration_seconds": 9.29969,
"end_time": "2025-07-16T06:48:56.148206",
"message_sent": true,
"start_time": "2025-07-16T06:48:46.848516",
"timestamp": "2025-07-16T06:48:56.148206",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"document_type\": \"unknown\",\n \"is_valid\": false,\n \"address_match\": false,\n \"document_date\": null,\n \"verification_score\": 0,\n \"address_confirmed\": null,\n \"document_issuer\": null,\n \"consumer_name\": null,\n \"consumer_number\": null,\n \"billing_period\": null,\n \"detailed_address\": {\n \"house_number\": \"\",\n \"street_name\": \"\",\n \"area\": \"\",\n \"locality\": \"\",\n \"city\": \"\",\n \"district\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"service_details\": {\n \"service_type\": \"\",\n \"connection_type\": \"\",\n \"load_sanctioned\": \"\",\n \"meter_number\": \"\",\n \"account_status\": \"\"\n },\n \"billing_information\": {\n \"current_reading\": 0,\n \"previous_reading\": 0,\n \"units_consumed\": 0,\n \"bill_amount\": 0.0,\n \"payment_status\": \"\",\n \"payment_date\": \"\"\n },\n \"document_verification\": {\n \"watermark_verified\": false,\n \"official_seal\": false,\n \"barcode_verified\": false,\n \"digital_signature\": \"failed\"\n },\n \"address_validation\": {\n \"geographic_coordinates\": {\n \"latitude\": 0.0,\n \"longitude\": 0.0\n },\n \"postal_verification\": \"failed\",\n \"google_maps_verified\": false,\n \"delivery_confirmation\": \"failed\"\n },\n \"usage_pattern\": {\n \"average_monthly_consumption\": 0,\n \"seasonal_variation\": \"\",\n \"payment_history\": \"\",\n \"account_age\": \"\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"document_type\\\": \\\"unknown\\\",\\n \\\"is_valid\\\": false,\\n \\\"address_match\\\": false,\\n \\\"document_date\\\": null,\\n \\\"verification_score\\\": 0,\\n \\\"address_confirmed\\\": null,\\n \\\"document_issuer\\\": null,\\n \\\"consumer_name\\\": null,\\n \\\"consumer_number\\\": null,\\n \\\"billing_period\\\": null,\\n \\\"detailed_address\\\": {\\n \\\"house_number\\\": \\\"\\\",\\n \\\"street_name\\\": \\\"\\\",\\n \\\"area\\\": \\\"\\\",\\n \\\"locality\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"district\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"service_details\\\": {\\n \\\"service_type\\\": \\\"\\\",\\n \\\"connection_type\\\": \\\"\\\",\\n \\\"load_sanctioned\\\": \\\"\\\",\\n \\\"meter_number\\\": \\\"\\\",\\n \\\"account_status\\\": \\\"\\\"\\n },\\n \\\"billing_information\\\": {\\n \\\"current_reading\\\": 0,\\n \\\"previous_reading\\\": 0,\\n \\\"units_consumed\\\": 0,\\n \\\"bill_amount\\\": 0.0,\\n \\\"payment_status\\\": \\\"\\\",\\n \\\"payment_date\\\": \\\"\\\"\\n },\\n \\\"document_verification\\\": {\\n \\\"watermark_verified\\\": false,\\n \\\"official_seal\\\": false,\\n \\\"barcode_verified\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"address_validation\\\": {\\n \\\"geographic_coordinates\\\": {\\n \\\"latitude\\\": 0.0,\\n \\\"longitude\\\": 0.0\\n },\\n \\\"postal_verification\\\": \\\"failed\\\",\\n \\\"google_maps_verified\\\": false,\\n \\\"delivery_confirmation\\\": \\\"failed\\\"\\n },\\n \\\"usage_pattern\\\": {\\n \\\"average_monthly_consumption\\\": 0,\\n \\\"seasonal_variation\\\": \\\"\\\",\\n \\\"payment_history\\\": \\\"\\\",\\n \\\"account_age\\\": \\\"\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1549, \"completion_tokens\": 670, \"total_tokens\": 2219, \"estimated_cost\": {\"amount\": 0.000634, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"token_usage": {
"completion_tokens": 670,
"estimated_cost": {
"amount": 0.000634,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1549,
"provider": "openai",
"total_tokens": 2219
}
},
"verify_employment": {
"designation": "Senior Software Engineer",
"employer_rating": "A+",
"employment_confirmed": true,
"employment_type": "permanent",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.349873,
"end_time": "2025-07-16T06:55:16.195339",
"message_sent": true,
"start_time": "2025-07-16T06:55:15.845466",
"timestamp": "2025-07-16T06:55:16.195339",
"worker_executed": true,
"workers_notified": true
},
"hr_contact_verified": true,
"job_stability_score": 88.5,
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"probation_status": "confirmed",
"reference_check_passed": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_employment"
},
"verify_pan_card": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"pan_number\": \"N/A\",\n \"is_valid\": false,\n \"name_match\": false,\n \"status\": \"inactive\",\n \"verification_score\": 0,\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"registered_address\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"pan_issue_date\": \"N/A\",\n \"pan_category\": \"Individual\",\n \"aadhaar_linked\": false,\n \"mobile_linked\": false,\n \"email_linked\": false,\n \"jurisdiction\": \"N/A\",\n \"assessing_officer\": \"N/A\",\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\",\n \"document_quality\": {\n \"image_clarity\": 0,\n \"tamper_detection\": \"no_tampering\",\n \"security_features\": \"suspicious\",\n \"ocr_confidence\": 0\n },\n \"tax_compliance\": {\n \"returns_filed\": false,\n \"last_return_year\": \"N/A\",\n \"compliance_rating\": \"Poor\"\n }\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1402,
"model": "gpt-4o-mini",
"output_length": 866,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from a PAN card and cross-verify with application data.\n\nExtract and verify:\n1. PAN number (10 character alphanumeric)\n2. Personal details (name, father\u0027s name, DOB)\n3. Address information\n4. Cross-match with application data for consistency\n5. Document authenticity indicators\n6. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required PAN verification fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"pan_number\": \"N/A\",\n \"is_valid\": false,\n \"name_match\": false,\n \"status\": \"inactive\",\n \"verification_score\": 0,\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"registered_address\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"pan_issue_date\": \"N/A\",\n \"pan_category\": \"Individual\",\n \"aadhaar_linked\": false,\n \"mobile_linked\": false,\n \"email_linked\": false,\n \"jurisdiction\": \"N/A\",\n \"assessing_officer\": \"N/A\",\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\",\n \"document_quality\": {\n \"image_clarity\": 0,\n \"tamper_detection\": \"no_tampering\",\n \"security_features\": \"suspicious\",\n \"ocr_confidence\": 0\n },\n \"tax_compliance\": {\n \"returns_filed\": false,\n \"last_return_year\": \"N/A\",\n \"compliance_rating\": \"Poor\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"pan_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"name_match\\\": false,\\n \\\"status\\\": \\\"inactive\\\",\\n \\\"verification_score\\\": 0,\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"registered_address\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"pan_issue_date\\\": \\\"N/A\\\",\\n \\\"pan_category\\\": \\\"Individual\\\",\\n \\\"aadhaar_linked\\\": false,\\n \\\"mobile_linked\\\": false,\\n \\\"email_linked\\\": false,\\n \\\"jurisdiction\\\": \\\"N/A\\\",\\n \\\"assessing_officer\\\": \\\"N/A\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\",\\n \\\"document_quality\\\": {\\n \\\"image_clarity\\\": 0,\\n \\\"tamper_detection\\\": \\\"no_tampering\\\",\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"ocr_confidence\\\": 0\\n },\\n \\\"tax_compliance\\\": {\\n \\\"returns_filed\\\": false,\\n \\\"last_return_year\\\": \\\"N/A\\\",\\n \\\"compliance_rating\\\": \\\"Poor\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1353, \"completion_tokens\": 282, \"total_tokens\": 1635, \"estimated_cost\": {\"amount\": 0.000372, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
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"status": "completed",
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},
"model": "gpt-4o-mini",
"prompt_tokens": 1353,
"provider": "openai",
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}
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"end_time": "2025-07-16T06:51:52.790157",
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"start_time": "2025-07-16T06:51:46.091436",
"timestamp": "2025-07-16T06:51:52.790157",
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"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"pan_number\": \"N/A\",\n \"is_valid\": false,\n \"name_match\": false,\n \"status\": \"inactive\",\n \"verification_score\": 0,\n \"verified_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"registered_address\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"pan_issue_date\": \"N/A\",\n \"pan_category\": \"Individual\",\n \"aadhaar_linked\": false,\n \"mobile_linked\": false,\n \"email_linked\": false,\n \"jurisdiction\": \"N/A\",\n \"assessing_officer\": \"N/A\",\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\",\n \"document_quality\": {\n \"image_clarity\": 0,\n \"tamper_detection\": \"no_tampering\",\n \"security_features\": \"suspicious\",\n \"ocr_confidence\": 0\n },\n \"tax_compliance\": {\n \"returns_filed\": false,\n \"last_return_year\": \"N/A\",\n \"compliance_rating\": \"Poor\"\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"pan_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"name_match\\\": false,\\n \\\"status\\\": \\\"inactive\\\",\\n \\\"verification_score\\\": 0,\\n \\\"verified_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"registered_address\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"pan_issue_date\\\": \\\"N/A\\\",\\n \\\"pan_category\\\": \\\"Individual\\\",\\n \\\"aadhaar_linked\\\": false,\\n \\\"mobile_linked\\\": false,\\n \\\"email_linked\\\": false,\\n \\\"jurisdiction\\\": \\\"N/A\\\",\\n \\\"assessing_officer\\\": \\\"N/A\\\",\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\",\\n \\\"document_quality\\\": {\\n \\\"image_clarity\\\": 0,\\n \\\"tamper_detection\\\": \\\"no_tampering\\\",\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"ocr_confidence\\\": 0\\n },\\n \\\"tax_compliance\\\": {\\n \\\"returns_filed\\\": false,\\n \\\"last_return_year\\\": \\\"N/A\\\",\\n \\\"compliance_rating\\\": \\\"Poor\\\"\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1353, \"completion_tokens\": 282, \"total_tokens\": 1635, \"estimated_cost\": {\"amount\": 0.000372, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"token_usage": {
"completion_tokens": 282,
"estimated_cost": {
"amount": 0.000372,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1353,
"provider": "openai",
"total_tokens": 1635
}
},
"verify_passport": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"passport_number\": \"N/A\",\n \"is_valid\": false,\n \"expiry_date\": \"N/A\",\n \"issuing_authority\": \"Government of India\",\n \"verification_score\": 0,\n \"document_provided\": false,\n \"holder_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"mother_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"place_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"nationality\": \"Indian\",\n \"passport_type\": \"P\",\n \"issue_date\": \"N/A\",\n \"issuing_office\": \"N/A\",\n \"file_number\": \"N/A\",\n \"personal_details\": {\n \"height\": \"\",\n \"identification_marks\": \"\",\n \"blood_group\": \"\",\n \"marital_status\": \"\"\n },\n \"address_in_passport\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"travel_history\": [],\n \"current_visas\": [],\n \"passport_renewals\": 0,\n \"previous_passport_number\": \"\",\n \"emergency_contact\": {\n \"name\": \"\",\n \"relationship\": \"\",\n \"phone\": \"\"\n },\n \"document_security\": {\n \"chip_verified\": false,\n \"security_features\": \"suspicious\",\n \"machine_readable\": false,\n \"digital_signature\": \"failed\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1730,
"model": "gpt-4o-mini",
"output_length": 1134,
"provider": "openai",
"system_message": "You are an expert document verification specialist. Analyze the OCR extracted text from a passport and cross-verify with application data.\n\nExtract and verify:\n1. Passport number, expiry date, issuing authority\n2. Personal details (name, father\u0027s name, mother\u0027s name, DOB, gender)\n3. Address information and travel history\n4. Cross-match with application data for consistency\n5. Document authenticity indicators\n6. Quality and verification scores\n\nReturn the data in the exact same JSON structure format with all required passport verification fields.\nCalculate verification scores based on OCR quality and data consistency.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"passport_number\": \"N/A\",\n \"is_valid\": false,\n \"expiry_date\": \"N/A\",\n \"issuing_authority\": \"Government of India\",\n \"verification_score\": 0,\n \"document_provided\": false,\n \"holder_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"mother_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"place_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"nationality\": \"Indian\",\n \"passport_type\": \"P\",\n \"issue_date\": \"N/A\",\n \"issuing_office\": \"N/A\",\n \"file_number\": \"N/A\",\n \"personal_details\": {\n \"height\": \"\",\n \"identification_marks\": \"\",\n \"blood_group\": \"\",\n \"marital_status\": \"\"\n },\n \"address_in_passport\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"travel_history\": [],\n \"current_visas\": [],\n \"passport_renewals\": 0,\n \"previous_passport_number\": \"\",\n \"emergency_contact\": {\n \"name\": \"\",\n \"relationship\": \"\",\n \"phone\": \"\"\n },\n \"document_security\": {\n \"chip_verified\": false,\n \"security_features\": \"suspicious\",\n \"machine_readable\": false,\n \"digital_signature\": \"failed\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"passport_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"expiry_date\\\": \\\"N/A\\\",\\n \\\"issuing_authority\\\": \\\"Government of India\\\",\\n \\\"verification_score\\\": 0,\\n \\\"document_provided\\\": false,\\n \\\"holder_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"mother_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"place_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"nationality\\\": \\\"Indian\\\",\\n \\\"passport_type\\\": \\\"P\\\",\\n \\\"issue_date\\\": \\\"N/A\\\",\\n \\\"issuing_office\\\": \\\"N/A\\\",\\n \\\"file_number\\\": \\\"N/A\\\",\\n \\\"personal_details\\\": {\\n \\\"height\\\": \\\"\\\",\\n \\\"identification_marks\\\": \\\"\\\",\\n \\\"blood_group\\\": \\\"\\\",\\n \\\"marital_status\\\": \\\"\\\"\\n },\\n \\\"address_in_passport\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"travel_history\\\": [],\\n \\\"current_visas\\\": [],\\n \\\"passport_renewals\\\": 0,\\n \\\"previous_passport_number\\\": \\\"\\\",\\n \\\"emergency_contact\\\": {\\n \\\"name\\\": \\\"\\\",\\n \\\"relationship\\\": \\\"\\\",\\n \\\"phone\\\": \\\"\\\"\\n },\\n \\\"document_security\\\": {\\n \\\"chip_verified\\\": false,\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"machine_readable\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1434, \"completion_tokens\": 353, \"total_tokens\": 1787, \"estimated_cost\": {\"amount\": 0.000427, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 353,
"estimated_cost": {
"amount": 0.000427,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1434,
"provider": "openai",
"total_tokens": 1787
}
},
"duration_seconds": 12.012135,
"end_time": "2025-07-16T06:51:58.256764",
"message_sent": true,
"start_time": "2025-07-16T06:51:46.244629",
"timestamp": "2025-07-16T06:51:58.256764",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"passport_number\": \"N/A\",\n \"is_valid\": false,\n \"expiry_date\": \"N/A\",\n \"issuing_authority\": \"Government of India\",\n \"verification_score\": 0,\n \"document_provided\": false,\n \"holder_name\": \"N/A\",\n \"father_name\": \"N/A\",\n \"mother_name\": \"N/A\",\n \"date_of_birth\": \"N/A\",\n \"place_of_birth\": \"N/A\",\n \"gender\": \"N/A\",\n \"nationality\": \"Indian\",\n \"passport_type\": \"P\",\n \"issue_date\": \"N/A\",\n \"issuing_office\": \"N/A\",\n \"file_number\": \"N/A\",\n \"personal_details\": {\n \"height\": \"\",\n \"identification_marks\": \"\",\n \"blood_group\": \"\",\n \"marital_status\": \"\"\n },\n \"address_in_passport\": {\n \"line1\": \"\",\n \"line2\": \"\",\n \"city\": \"\",\n \"state\": \"\",\n \"pincode\": \"\",\n \"country\": \"India\"\n },\n \"travel_history\": [],\n \"current_visas\": [],\n \"passport_renewals\": 0,\n \"previous_passport_number\": \"\",\n \"emergency_contact\": {\n \"name\": \"\",\n \"relationship\": \"\",\n \"phone\": \"\"\n },\n \"document_security\": {\n \"chip_verified\": false,\n \"security_features\": \"suspicious\",\n \"machine_readable\": false,\n \"digital_signature\": \"failed\"\n },\n \"verification_timestamp\": \"2023-10-05T12:00:00Z\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"passport_number\\\": \\\"N/A\\\",\\n \\\"is_valid\\\": false,\\n \\\"expiry_date\\\": \\\"N/A\\\",\\n \\\"issuing_authority\\\": \\\"Government of India\\\",\\n \\\"verification_score\\\": 0,\\n \\\"document_provided\\\": false,\\n \\\"holder_name\\\": \\\"N/A\\\",\\n \\\"father_name\\\": \\\"N/A\\\",\\n \\\"mother_name\\\": \\\"N/A\\\",\\n \\\"date_of_birth\\\": \\\"N/A\\\",\\n \\\"place_of_birth\\\": \\\"N/A\\\",\\n \\\"gender\\\": \\\"N/A\\\",\\n \\\"nationality\\\": \\\"Indian\\\",\\n \\\"passport_type\\\": \\\"P\\\",\\n \\\"issue_date\\\": \\\"N/A\\\",\\n \\\"issuing_office\\\": \\\"N/A\\\",\\n \\\"file_number\\\": \\\"N/A\\\",\\n \\\"personal_details\\\": {\\n \\\"height\\\": \\\"\\\",\\n \\\"identification_marks\\\": \\\"\\\",\\n \\\"blood_group\\\": \\\"\\\",\\n \\\"marital_status\\\": \\\"\\\"\\n },\\n \\\"address_in_passport\\\": {\\n \\\"line1\\\": \\\"\\\",\\n \\\"line2\\\": \\\"\\\",\\n \\\"city\\\": \\\"\\\",\\n \\\"state\\\": \\\"\\\",\\n \\\"pincode\\\": \\\"\\\",\\n \\\"country\\\": \\\"India\\\"\\n },\\n \\\"travel_history\\\": [],\\n \\\"current_visas\\\": [],\\n \\\"passport_renewals\\\": 0,\\n \\\"previous_passport_number\\\": \\\"\\\",\\n \\\"emergency_contact\\\": {\\n \\\"name\\\": \\\"\\\",\\n \\\"relationship\\\": \\\"\\\",\\n \\\"phone\\\": \\\"\\\"\\n },\\n \\\"document_security\\\": {\\n \\\"chip_verified\\\": false,\\n \\\"security_features\\\": \\\"suspicious\\\",\\n \\\"machine_readable\\\": false,\\n \\\"digital_signature\\\": \\\"failed\\\"\\n },\\n \\\"verification_timestamp\\\": \\\"2023-10-05T12:00:00Z\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1434, \"completion_tokens\": 353, \"total_tokens\": 1787, \"estimated_cost\": {\"amount\": 0.000427, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"token_usage": {
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"estimated_cost": {
"amount": 0.000427,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 1434,
"provider": "openai",
"total_tokens": 1787
}
},
"verify_tax_returns": {
"declared_income": 98000,
"discrepancies_found": false,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.426719,
"end_time": "2025-07-16T06:52:06.040967",
"message_sent": true,
"start_time": "2025-07-16T06:52:05.614248",
"timestamp": "2025-07-16T06:52:06.040967",
"worker_executed": true,
"workers_notified": true
},
"income_growth_trend": "positive",
"output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
"return_code": 0,
"returns_filed_consistently": true,
"status": "completed",
"stderr": "",
"task_id": "verify_tax_returns",
"tax_compliance_score": 92.0,
"tax_paid": 12000,
"verification_with_govt": true
}
}