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": ""
},
"duration_seconds": 0.226382,
"end_time": "2025-07-15T14:16:54.761901",
"message_sent": true,
"start_time": "2025-07-15T14:16:54.535519",
"timestamp": "2025-07-15T14:16:54.761901",
"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": {
"account_balance_trend": "stable",
"average_monthly_credits": 7200,
"bounced_transactions": 0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"average_monthly_credits\": 7200, \"salary_credits_consistent\": true, \"account_balance_trend\": \"stable\", \"minimum_balance\": 15000, \"maximum_balance\": 45000, \"bounced_transactions\": 0, \"loan_emis_detected\": 2, \"total_monthly_debits\": 5800, \"financial_discipline_score\": 85.5, \"irregular_transactions\": false}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.498809,
"end_time": "2025-07-15T14:16:27.192642",
"message_sent": true,
"start_time": "2025-07-15T14:16:26.693833",
"timestamp": "2025-07-15T14:16:27.192642",
"worker_executed": true,
"workers_notified": true
},
"financial_discipline_score": 85.5,
"irregular_transactions": false,
"loan_emis_detected": 2,
"maximum_balance": 45000,
"minimum_balance": 15000,
"output": "__OUTPUTS__ {\"average_monthly_credits\": 7200, \"salary_credits_consistent\": true, \"account_balance_trend\": \"stable\", \"minimum_balance\": 15000, \"maximum_balance\": 45000, \"bounced_transactions\": 0, \"loan_emis_detected\": 2, \"total_monthly_debits\": 5800, \"financial_discipline_score\": 85.5, \"irregular_transactions\": false}\n",
"return_code": 0,
"salary_credits_consistent": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_bank_statements",
"total_monthly_debits": 5800
},
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.203366,
"end_time": "2025-07-15T14:16:35.822382",
"message_sent": true,
"start_time": "2025-07-15T14:16:35.619016",
"timestamp": "2025-07-15T14:16:35.822382",
"worker_executed": true,
"workers_notified": true
},
"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": {
"annual_gross": 102000,
"annual_net": 81600,
"deductions": {
"insurance": 300,
"pf": 500,
"tax": 1200
},
"employer": "Tech Corp Ltd",
"employment_duration": "2.5 years",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.408108,
"end_time": "2025-07-15T14:16:27.035193",
"message_sent": true,
"start_time": "2025-07-15T14:16:26.627085",
"timestamp": "2025-07-15T14:16:27.035193",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or inconsistencies\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 468,
"model": "gpt-4o-mini",
"output_length": 822,
"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"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or inconsistencies\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 199, \"completion_tokens\": 224, \"total_tokens\": 423, \"estimated_cost\": {\"amount\": 0.000164, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 224,
"estimated_cost": {
"amount": 0.000164,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 199,
"provider": "openai",
"total_tokens": 423
}
},
"duration_seconds": 5.577941,
"end_time": "2025-07-15T14:16:18.270663",
"message_sent": true,
"start_time": "2025-07-15T14:16:12.692722",
"timestamp": "2025-07-15T14:16:18.270663",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or inconsistencies\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 199, \"completion_tokens\": 224, \"total_tokens\": 423, \"estimated_cost\": {\"amount\": 0.000164, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "application_quality_check",
"token_usage": {
"completion_tokens": 224,
"estimated_cost": {
"amount": 0.000164,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 199,
"provider": "openai",
"total_tokens": 423
}
},
"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": 0.215298,
"end_time": "2025-07-15T14:16:36.067416",
"message_sent": true,
"start_time": "2025-07-15T14:16:35.852118",
"timestamp": "2025-07-15T14:16:36.067416",
"worker_executed": true,
"workers_notified": true
},
"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",
"stderr": ""
},
"duration_seconds": 0.238207,
"end_time": "2025-07-15T14:16:54.243774",
"message_sent": true,
"start_time": "2025-07-15T14:16:54.005567",
"timestamp": "2025-07-15T14:16:54.243774",
"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": {
"debt_to_income_ratio": 0.3590686274509804,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.227948,
"end_time": "2025-07-15T14:16:27.502799",
"message_sent": true,
"start_time": "2025-07-15T14:16:27.274851",
"timestamp": "2025-07-15T14:16:27.502799",
"worker_executed": true,
"workers_notified": true
},
"existing_debt_payments": 2400,
"max_allowed_ratio": 0.4,
"monthly_net_income": 6800,
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 41.666666666666664,
"ratio_acceptable": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2441.6666666666665
},
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.215404,
"end_time": "2025-07-15T14:16:35.588661",
"message_sent": true,
"start_time": "2025-07-15T14:16:35.373257",
"timestamp": "2025-07-15T14:16:35.588661",
"worker_executed": true,
"workers_notified": true
},
"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 the consolidated compliance assessment:\n\n```json\n{\n \"overall_compliance_status\": \"Compliant\",\n \"risk_assessment\": {\n \"KYC\": {\n \"status\": \"Compliant\",\n \"risk_category\": \"Low\",\n \"compliance_score\": 98.5\n },\n \"AML\": {\n \"status\": \"Cleared\",\n \"risk_rating\": \"Low\",\n \"compliance_score\": 96.8\n },\n \"Regulatory\": {\n \"risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"compliance_score\": 95.5\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue to monitor compliance with KYC and AML regulations regularly.\",\n \"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\",\n \"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\"\n ],\n \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1347,
"model": "gpt-4o-mini",
"output_length": 1508,
"provider": "openai",
"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 the consolidated compliance assessment:\n\n```json\n{\n \"overall_compliance_status\": \"Compliant\",\n \"risk_assessment\": {\n \"KYC\": {\n \"status\": \"Compliant\",\n \"risk_category\": \"Low\",\n \"compliance_score\": 98.5\n },\n \"AML\": {\n \"status\": \"Cleared\",\n \"risk_rating\": \"Low\",\n \"compliance_score\": 96.8\n },\n \"Regulatory\": {\n \"risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"compliance_score\": 95.5\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue to monitor compliance with KYC and AML regulations regularly.\",\n \"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\",\n \"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\"\n ],\n \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is the consolidated compliance assessment:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": {\\n \\\"status\\\": \\\"Compliant\\\",\\n \\\"risk_category\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 98.5\\n },\\n \\\"AML\\\": {\\n \\\"status\\\": \\\"Cleared\\\",\\n \\\"risk_rating\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 96.8\\n },\\n \\\"Regulatory\\\": {\\n \\\"risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"compliance_score\\\": 95.5\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue to monitor compliance with KYC and AML regulations regularly.\\\",\\n \\\"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\\\",\\n \\\"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2087, \"completion_tokens\": 354, \"total_tokens\": 2441, \"estimated_cost\": {\"amount\": 0.000525, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided compliance check results, here is the consolidated compliance assessment:\n\n```json\n{\n \"overall_compliance_status\": \"Compliant\",\n \"risk_assessment\": {\n \"KYC\": {\n \"status\": \"Compliant\",\n \"risk_category\": \"Low\",\n \"compliance_score\": 98.5\n },\n \"AML\": {\n \"status\": \"Cleared\",\n \"risk_rating\": \"Low\",\n \"compliance_score\": 96.8\n },\n \"Regulatory\": {\n \"risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"compliance_score\": 95.5\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue to monitor compliance with KYC and AML regulations regularly.\",\n \"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\",\n \"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\"\n ],\n \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is the consolidated compliance assessment:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": {\\n \\\"status\\\": \\\"Compliant\\\",\\n \\\"risk_category\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 98.5\\n },\\n \\\"AML\\\": {\\n \\\"status\\\": \\\"Cleared\\\",\\n \\\"risk_rating\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 96.8\\n },\\n \\\"Regulatory\\\": {\\n \\\"risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"compliance_score\\\": 95.5\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue to monitor compliance with KYC and AML regulations regularly.\\\",\\n \\\"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\\\",\\n \\\"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2087, \"completion_tokens\": 354, \"total_tokens\": 2441, \"estimated_cost\": {\"amount\": 0.000525, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name\": {\n \"applicant_name\": \"John Doe\",\n \"verified_name\": \"JOHN DOE\"\n },\n \"address\": {\n \"application_address\": \"123 Main St, City, State 12345\",\n \"address_proof\": \"123 Main St, City, State 12345\"\n },\n \"pan_number\": \"ABCDE1234F\",\n \"aadhaar_masked\": \"1234-5678-9012\",\n \"passport_number\": \"A1234567\"\n },\n \"risk_factors_identified\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"recommendation_for_proceeding\": {\n \"action\": \"Proceed with caution\",\n \"steps\": [\n \"Verify the applicant\u0027s understanding of home purchase costs.\",\n \"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\",\n \"Continue monitoring for any additional inconsistencies in future documentation.\"\n ]\n }\n}\n```",
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"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name\": {\n \"applicant_name\": \"John Doe\",\n \"verified_name\": \"JOHN DOE\"\n },\n \"address\": {\n \"application_address\": \"123 Main St, City, State 12345\",\n \"address_proof\": \"123 Main St, City, State 12345\"\n },\n \"pan_number\": \"ABCDE1234F\",\n \"aadhaar_masked\": \"1234-5678-9012\",\n \"passport_number\": \"A1234567\"\n },\n \"risk_factors_identified\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"recommendation_for_proceeding\": {\n \"action\": \"Proceed with caution\",\n \"steps\": [\n \"Verify the applicant\u0027s understanding of home purchase costs.\",\n \"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\",\n \"Continue monitoring for any additional inconsistencies in future documentation.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name\\\": {\\n \\\"applicant_name\\\": \\\"John Doe\\\",\\n \\\"verified_name\\\": \\\"JOHN DOE\\\"\\n },\\n \\\"address\\\": {\\n \\\"application_address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"address_proof\\\": \\\"123 Main St, City, State 12345\\\"\\n },\\n \\\"pan_number\\\": \\\"ABCDE1234F\\\",\\n \\\"aadhaar_masked\\\": \\\"1234-5678-9012\\\",\\n \\\"passport_number\\\": \\\"A1234567\\\"\\n },\\n \\\"risk_factors_identified\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Proceed with caution\\\",\\n \\\"steps\\\": [\\n \\\"Verify the applicant\u0027s understanding of home purchase costs.\\\",\\n \\\"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\\\",\\n \\\"Continue monitoring for any additional inconsistencies in future documentation.\\\"\\n ]\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 559, \"completion_tokens\": 271, \"total_tokens\": 830, \"estimated_cost\": {\"amount\": 0.000246, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name\": {\n \"applicant_name\": \"John Doe\",\n \"verified_name\": \"JOHN DOE\"\n },\n \"address\": {\n \"application_address\": \"123 Main St, City, State 12345\",\n \"address_proof\": \"123 Main St, City, State 12345\"\n },\n \"pan_number\": \"ABCDE1234F\",\n \"aadhaar_masked\": \"1234-5678-9012\",\n \"passport_number\": \"A1234567\"\n },\n \"risk_factors_identified\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"recommendation_for_proceeding\": {\n \"action\": \"Proceed with caution\",\n \"steps\": [\n \"Verify the applicant\u0027s understanding of home purchase costs.\",\n \"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\",\n \"Continue monitoring for any additional inconsistencies in future documentation.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name\\\": {\\n \\\"applicant_name\\\": \\\"John Doe\\\",\\n \\\"verified_name\\\": \\\"JOHN DOE\\\"\\n },\\n \\\"address\\\": {\\n \\\"application_address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"address_proof\\\": \\\"123 Main St, City, State 12345\\\"\\n },\\n \\\"pan_number\\\": \\\"ABCDE1234F\\\",\\n \\\"aadhaar_masked\\\": \\\"1234-5678-9012\\\",\\n \\\"passport_number\\\": \\\"A1234567\\\"\\n },\\n \\\"risk_factors_identified\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Proceed with caution\\\",\\n \\\"steps\\\": [\\n \\\"Verify the applicant\u0027s understanding of home purchase costs.\\\",\\n \\\"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\\\",\\n \\\"Continue monitoring for any additional inconsistencies in future documentation.\\\"\\n ]\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 559, \"completion_tokens\": 271, \"total_tokens\": 830, \"estimated_cost\": {\"amount\": 0.000246, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"agent_type": "assistant",
"ai_response": "Based on the provided credit data, we will analyze the default risk using the following factors:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\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\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: $7,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\n- **Total Outstanding Loans**: $125,000\n\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\n\n### 5. Overall Risk Profile\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\n\n### Risk Score Calculation\nConsidering all the factors above, we can assign a risk score based on the analysis:\n- **Credit Score**: 15 (Good)\n- **Repayment Patterns**: 10 (Excellent)\n- **Credit Utilization**: 10 (Good)\n- **Existing Loan Burden**: 10 (Acceptable)\n- **Overall Risk Profile**: 10 (Stable)\n\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\n\n### Recommendations\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\n\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.",
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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 will analyze the default risk using the following factors:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\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\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: $7,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\n- **Total Outstanding Loans**: $125,000\n\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\n\n### 5. Overall Risk Profile\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\n\n### Risk Score Calculation\nConsidering all the factors above, we can assign a risk score based on the analysis:\n- **Credit Score**: 15 (Good)\n- **Repayment Patterns**: 10 (Excellent)\n- **Credit Utilization**: 10 (Good)\n- **Existing Loan Burden**: 10 (Acceptable)\n- **Overall Risk Profile**: 10 (Stable)\n\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\n\n### Recommendations\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\n\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the default risk using the following factors:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\\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\\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: $7,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\\n- **Total Outstanding Loans**: $125,000\\n\\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\\n\\n### 5. Overall Risk Profile\\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\\n\\n### Risk Score Calculation\\nConsidering all the factors above, we can assign a risk score based on the analysis:\\n- **Credit Score**: 15 (Good)\\n- **Repayment Patterns**: 10 (Excellent)\\n- **Credit Utilization**: 10 (Good)\\n- **Existing Loan Burden**: 10 (Acceptable)\\n- **Overall Risk Profile**: 10 (Stable)\\n\\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\\n\\n### Recommendations\\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\\n\\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1380, \"completion_tokens\": 730, \"total_tokens\": 2110, \"estimated_cost\": {\"amount\": 0.000645, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided credit data, we will analyze the default risk using the following factors:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\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\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: $7,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\n- **Total Outstanding Loans**: $125,000\n\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\n\n### 5. Overall Risk Profile\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\n\n### Risk Score Calculation\nConsidering all the factors above, we can assign a risk score based on the analysis:\n- **Credit Score**: 15 (Good)\n- **Repayment Patterns**: 10 (Excellent)\n- **Credit Utilization**: 10 (Good)\n- **Existing Loan Burden**: 10 (Acceptable)\n- **Overall Risk Profile**: 10 (Stable)\n\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\n\n### Recommendations\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\n\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the default risk using the following factors:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\\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\\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: $7,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\\n- **Total Outstanding Loans**: $125,000\\n\\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\\n\\n### 5. Overall Risk Profile\\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\\n\\n### Risk Score Calculation\\nConsidering all the factors above, we can assign a risk score based on the analysis:\\n- **Credit Score**: 15 (Good)\\n- **Repayment Patterns**: 10 (Excellent)\\n- **Credit Utilization**: 10 (Good)\\n- **Existing Loan Burden**: 10 (Acceptable)\\n- **Overall Risk Profile**: 10 (Stable)\\n\\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\\n\\n### Recommendations\\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\\n\\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1380, \"completion_tokens\": 730, \"total_tokens\": 2110, \"estimated_cost\": {\"amount\": 0.000645, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"annual_income": 75000,
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"ai_response": "### Final Recommendation: **CONDITIONAL APPROVAL**\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $41.67\n- **Conditions**: \n - Verification of the applicant\u0027s understanding of home purchase costs.\n - Follow-up interview to clarify the loan purpose and requested amount.\n - Continuous monitoring of financial behavior for any changes.\n\n#### Risk Mitigation Measures:\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\n\n#### Reasoning for Decision:\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\n\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\n\n#### Confidence Level: **85**\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.",
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"output": "### Final Recommendation: **CONDITIONAL APPROVAL**\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $41.67\n- **Conditions**: \n - Verification of the applicant\u0027s understanding of home purchase costs.\n - Follow-up interview to clarify the loan purpose and requested amount.\n - Continuous monitoring of financial behavior for any changes.\n\n#### Risk Mitigation Measures:\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\n\n#### Reasoning for Decision:\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\n\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\n\n#### Confidence Level: **85**\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: **CONDITIONAL APPROVAL**\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $41.67\\n- **Conditions**: \\n - Verification of the applicant\u0027s understanding of home purchase costs.\\n - Follow-up interview to clarify the loan purpose and requested amount.\\n - Continuous monitoring of financial behavior for any changes.\\n\\n#### Risk Mitigation Measures:\\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\\n\\n#### Reasoning for Decision:\\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\\n\\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\\n\\n#### Confidence Level: **85**\\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 5041, \"completion_tokens\": 513, \"total_tokens\": 5554, \"estimated_cost\": {\"amount\": 0.001064, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "### Final Recommendation: **CONDITIONAL APPROVAL**\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $41.67\n- **Conditions**: \n - Verification of the applicant\u0027s understanding of home purchase costs.\n - Follow-up interview to clarify the loan purpose and requested amount.\n - Continuous monitoring of financial behavior for any changes.\n\n#### Risk Mitigation Measures:\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\n\n#### Reasoning for Decision:\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\n\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\n\n#### Confidence Level: **85**\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: **CONDITIONAL APPROVAL**\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $41.67\\n- **Conditions**: \\n - Verification of the applicant\u0027s understanding of home purchase costs.\\n - Follow-up interview to clarify the loan purpose and requested amount.\\n - Continuous monitoring of financial behavior for any changes.\\n\\n#### Risk Mitigation Measures:\\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\\n\\n#### Reasoning for Decision:\\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. 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"ai_response": "```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"salary_consistency\": true,\n \"employment_duration\": \"2.5 years\",\n \"recent_increment\": true,\n \"income_growth_trend\": \"positive\",\n \"overall_stability_score\": 90\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"debt_servicing_score\": 85\n },\n \"financial_discipline_evaluation\": {\n \"maximum_balance\": 45000,\n \"minimum_balance\": 15000,\n \"total_monthly_debits\": 5800,\n \"average_monthly_credits\": 7200,\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"financial_discipline_score\": 85.5,\n \"overall_discipline_score\": 88\n },\n \"risk_factors_and_recommendations\": {\n \"identified_risks\": {\n \"loan_emis_detected\": 2,\n \"debt_to_income_ratio\": 0.359,\n \"financial_discipline\": \"stable\"\n },\n \"recommendations\": [\n \"Continue monitoring the applicant\u0027s financial behavior for any changes.\",\n \"Ensure that the applicant maintains a consistent income and does not take on additional debt.\",\n \"Consider a follow-up review of bank statements in the next quarter.\"\n ]\n },\n \"overall_income_adequacy_score\": 88\n}\n```",
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"output": "```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"salary_consistency\": true,\n \"employment_duration\": \"2.5 years\",\n \"recent_increment\": true,\n \"income_growth_trend\": \"positive\",\n \"overall_stability_score\": 90\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"debt_servicing_score\": 85\n },\n \"financial_discipline_evaluation\": {\n \"maximum_balance\": 45000,\n \"minimum_balance\": 15000,\n \"total_monthly_debits\": 5800,\n \"average_monthly_credits\": 7200,\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"financial_discipline_score\": 85.5,\n \"overall_discipline_score\": 88\n },\n \"risk_factors_and_recommendations\": {\n \"identified_risks\": {\n \"loan_emis_detected\": 2,\n \"debt_to_income_ratio\": 0.359,\n \"financial_discipline\": \"stable\"\n },\n \"recommendations\": [\n \"Continue monitoring the applicant\u0027s financial behavior for any changes.\",\n \"Ensure that the applicant maintains a consistent income and does not take on additional debt.\",\n \"Consider a follow-up review of bank statements in the next quarter.\"\n ]\n },\n \"overall_income_adequacy_score\": 88\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"salary_consistency\\\": true,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"recent_increment\\\": true,\\n \\\"income_growth_trend\\\": \\\"positive\\\",\\n \\\"overall_stability_score\\\": 90\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"debt_servicing_score\\\": 85\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"maximum_balance\\\": 45000,\\n \\\"minimum_balance\\\": 15000,\\n \\\"total_monthly_debits\\\": 5800,\\n \\\"average_monthly_credits\\\": 7200,\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"overall_discipline_score\\\": 88\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"identified_risks\\\": {\\n \\\"loan_emis_detected\\\": 2,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"financial_discipline\\\": \\\"stable\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue monitoring the applicant\u0027s financial behavior for any changes.\\\",\\n \\\"Ensure that the applicant maintains a consistent income and does not take on additional debt.\\\",\\n \\\"Consider a follow-up review of bank statements in the next quarter.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 88\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1042, \"completion_tokens\": 388, \"total_tokens\": 1430, \"estimated_cost\": {\"amount\": 0.000389, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"duration_seconds": 7.727679,
"end_time": "2025-07-15T14:16:35.341994",
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"timestamp": "2025-07-15T14:16:35.341994",
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},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"salary_consistency\": true,\n \"employment_duration\": \"2.5 years\",\n \"recent_increment\": true,\n \"income_growth_trend\": \"positive\",\n \"overall_stability_score\": 90\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"debt_servicing_score\": 85\n },\n \"financial_discipline_evaluation\": {\n \"maximum_balance\": 45000,\n \"minimum_balance\": 15000,\n \"total_monthly_debits\": 5800,\n \"average_monthly_credits\": 7200,\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"financial_discipline_score\": 85.5,\n \"overall_discipline_score\": 88\n },\n \"risk_factors_and_recommendations\": {\n \"identified_risks\": {\n \"loan_emis_detected\": 2,\n \"debt_to_income_ratio\": 0.359,\n \"financial_discipline\": \"stable\"\n },\n \"recommendations\": [\n \"Continue monitoring the applicant\u0027s financial behavior for any changes.\",\n \"Ensure that the applicant maintains a consistent income and does not take on additional debt.\",\n \"Consider a follow-up review of bank statements in the next quarter.\"\n ]\n },\n \"overall_income_adequacy_score\": 88\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"salary_consistency\\\": true,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"recent_increment\\\": true,\\n \\\"income_growth_trend\\\": \\\"positive\\\",\\n \\\"overall_stability_score\\\": 90\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"debt_servicing_score\\\": 85\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"maximum_balance\\\": 45000,\\n \\\"minimum_balance\\\": 15000,\\n \\\"total_monthly_debits\\\": 5800,\\n \\\"average_monthly_credits\\\": 7200,\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"overall_discipline_score\\\": 88\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"identified_risks\\\": {\\n \\\"loan_emis_detected\\\": 2,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"financial_discipline\\\": \\\"stable\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue monitoring the applicant\u0027s financial behavior for any changes.\\\",\\n \\\"Ensure that the applicant maintains a consistent income and does not take on additional debt.\\\",\\n \\\"Consider a follow-up review of bank statements in the next quarter.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 88\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1042, \"completion_tokens\": 388, \"total_tokens\": 1430, \"estimated_cost\": {\"amount\": 0.000389, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
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"internal_policy_check": {
"age_criteria_met": true,
"credit_score_threshold_met": true,
"employment_criteria_met": true,
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"execution_details": {
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"output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
"return_code": 0,
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},
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"end_time": "2025-07-15T14:16:55.226624",
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},
"geographic_restrictions_met": true,
"income_criteria_met": true,
"loan_amount_within_limits": true,
"ltv_ratio_acceptable": true,
"output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
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"kyc_compliance_check": {
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"documents_complete": true,
"execution_details": {
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"output": "__OUTPUTS__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
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},
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},
"identity_verified": true,
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"output": "__OUTPUTS__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
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"consumer_protection_compliant": true,
"data_privacy_compliant": true,
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"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",
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},
"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"
},
"status": "FAILED",
"task_outputs": {
"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,
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},
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"timestamp": "2025-07-15T14:16:54.761901",
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},
"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": {
"account_balance_trend": "stable",
"average_monthly_credits": 7200,
"bounced_transactions": 0,
"execution_details": {
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"output": "__OUTPUTS__ {\"average_monthly_credits\": 7200, \"salary_credits_consistent\": true, \"account_balance_trend\": \"stable\", \"minimum_balance\": 15000, \"maximum_balance\": 45000, \"bounced_transactions\": 0, \"loan_emis_detected\": 2, \"total_monthly_debits\": 5800, \"financial_discipline_score\": 85.5, \"irregular_transactions\": false}\n",
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},
"financial_discipline_score": 85.5,
"irregular_transactions": false,
"loan_emis_detected": 2,
"maximum_balance": 45000,
"minimum_balance": 15000,
"output": "__OUTPUTS__ {\"average_monthly_credits\": 7200, \"salary_credits_consistent\": true, \"account_balance_trend\": \"stable\", \"minimum_balance\": 15000, \"maximum_balance\": 45000, \"bounced_transactions\": 0, \"loan_emis_detected\": 2, \"total_monthly_debits\": 5800, \"financial_discipline_score\": 85.5, \"irregular_transactions\": false}\n",
"return_code": 0,
"salary_credits_consistent": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_bank_statements",
"total_monthly_debits": 5800
},
"analyze_credit_history": {
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"credit_limit_utilization": 35.2,
"credit_mix": {
"auto_loans": 1,
"credit_cards": 3,
"home_loans": 0,
"other": 1,
"personal_loans": 1
},
"execution_details": {
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"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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"timestamp": "2025-07-15T14:16:35.822382",
"worker_executed": true,
"workers_notified": true
},
"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": {
"annual_gross": 102000,
"annual_net": 81600,
"deductions": {
"insurance": 300,
"pf": 500,
"tax": 1200
},
"employer": "Tech Corp Ltd",
"employment_duration": "2.5 years",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"return_code": 0,
"status": "completed",
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},
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"end_time": "2025-07-15T14:16:27.035193",
"message_sent": true,
"start_time": "2025-07-15T14:16:26.627085",
"timestamp": "2025-07-15T14:16:27.035193",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
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"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or inconsistencies\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```",
"execution_details": {
"actual_result": {
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"agent_type": "assistant",
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"model": "gpt-4o-mini",
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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 \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or inconsistencies\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 199, \"completion_tokens\": 224, \"total_tokens\": 423, \"estimated_cost\": {\"amount\": 0.000164, \"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 \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or inconsistencies\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 199, \"completion_tokens\": 224, \"total_tokens\": 423, \"estimated_cost\": {\"amount\": 0.000164, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
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},
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"provider": "openai",
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}
},
"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",
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},
"duration_seconds": 0.215298,
"end_time": "2025-07-15T14:16:36.067416",
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"timestamp": "2025-07-15T14:16:36.067416",
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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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"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": {
"debt_to_income_ratio": 0.3590686274509804,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
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},
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"end_time": "2025-07-15T14:16:27.502799",
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"worker_executed": true,
"workers_notified": true
},
"existing_debt_payments": 2400,
"max_allowed_ratio": 0.4,
"monthly_net_income": 6800,
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 41.666666666666664,
"ratio_acceptable": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2441.6666666666665
},
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.215404,
"end_time": "2025-07-15T14:16:35.588661",
"message_sent": true,
"start_time": "2025-07-15T14:16:35.373257",
"timestamp": "2025-07-15T14:16:35.588661",
"worker_executed": true,
"workers_notified": true
},
"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 the consolidated compliance assessment:\n\n```json\n{\n \"overall_compliance_status\": \"Compliant\",\n \"risk_assessment\": {\n \"KYC\": {\n \"status\": \"Compliant\",\n \"risk_category\": \"Low\",\n \"compliance_score\": 98.5\n },\n \"AML\": {\n \"status\": \"Cleared\",\n \"risk_rating\": \"Low\",\n \"compliance_score\": 96.8\n },\n \"Regulatory\": {\n \"risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"compliance_score\": 95.5\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue to monitor compliance with KYC and AML regulations regularly.\",\n \"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\",\n \"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\"\n ],\n \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.",
"execution_details": {
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"provider": "openai",
"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 the consolidated compliance assessment:\n\n```json\n{\n \"overall_compliance_status\": \"Compliant\",\n \"risk_assessment\": {\n \"KYC\": {\n \"status\": \"Compliant\",\n \"risk_category\": \"Low\",\n \"compliance_score\": 98.5\n },\n \"AML\": {\n \"status\": \"Cleared\",\n \"risk_rating\": \"Low\",\n \"compliance_score\": 96.8\n },\n \"Regulatory\": {\n \"risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"compliance_score\": 95.5\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue to monitor compliance with KYC and AML regulations regularly.\",\n \"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\",\n \"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\"\n ],\n \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is the consolidated compliance assessment:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": {\\n \\\"status\\\": \\\"Compliant\\\",\\n \\\"risk_category\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 98.5\\n },\\n \\\"AML\\\": {\\n \\\"status\\\": \\\"Cleared\\\",\\n \\\"risk_rating\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 96.8\\n },\\n \\\"Regulatory\\\": {\\n \\\"risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"compliance_score\\\": 95.5\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue to monitor compliance with KYC and AML regulations regularly.\\\",\\n \\\"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\\\",\\n \\\"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2087, \"completion_tokens\": 354, \"total_tokens\": 2441, \"estimated_cost\": {\"amount\": 0.000525, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "Based on the provided compliance check results, here is the consolidated compliance assessment:\n\n```json\n{\n \"overall_compliance_status\": \"Compliant\",\n \"risk_assessment\": {\n \"KYC\": {\n \"status\": \"Compliant\",\n \"risk_category\": \"Low\",\n \"compliance_score\": 98.5\n },\n \"AML\": {\n \"status\": \"Cleared\",\n \"risk_rating\": \"Low\",\n \"compliance_score\": 96.8\n },\n \"Regulatory\": {\n \"risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"compliance_score\": 95.5\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations_for_proceeding\": [\n \"Continue to monitor compliance with KYC and AML regulations regularly.\",\n \"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\",\n \"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\"\n ],\n \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is the consolidated compliance assessment:\\n\\n```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": {\\n \\\"status\\\": \\\"Compliant\\\",\\n \\\"risk_category\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 98.5\\n },\\n \\\"AML\\\": {\\n \\\"status\\\": \\\"Cleared\\\",\\n \\\"risk_rating\\\": \\\"Low\\\",\\n \\\"compliance_score\\\": 96.8\\n },\\n \\\"Regulatory\\\": {\\n \\\"risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"compliance_score\\\": 95.5\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Continue to monitor compliance with KYC and AML regulations regularly.\\\",\\n \\\"Maintain up-to-date documentation and ensure all regulatory requirements are consistently met.\\\",\\n \\\"Conduct periodic reviews of internal policies to ensure they remain compliant with evolving regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns identified.\\n4. **Recommendations for Proceeding**: Emphasize ongoing monitoring and periodic reviews to maintain compliance.\\n5. **Compliance Confidence Score**: A high score of 97.0 indicates strong confidence in the compliance framework.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2087, \"completion_tokens\": 354, \"total_tokens\": 2441, \"estimated_cost\": {\"amount\": 0.000525, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name\": {\n \"applicant_name\": \"John Doe\",\n \"verified_name\": \"JOHN DOE\"\n },\n \"address\": {\n \"application_address\": \"123 Main St, City, State 12345\",\n \"address_proof\": \"123 Main St, City, State 12345\"\n },\n \"pan_number\": \"ABCDE1234F\",\n \"aadhaar_masked\": \"1234-5678-9012\",\n \"passport_number\": \"A1234567\"\n },\n \"risk_factors_identified\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"recommendation_for_proceeding\": {\n \"action\": \"Proceed with caution\",\n \"steps\": [\n \"Verify the applicant\u0027s understanding of home purchase costs.\",\n \"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\",\n \"Continue monitoring for any additional inconsistencies in future documentation.\"\n ]\n }\n}\n```",
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"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name\": {\n \"applicant_name\": \"John Doe\",\n \"verified_name\": \"JOHN DOE\"\n },\n \"address\": {\n \"application_address\": \"123 Main St, City, State 12345\",\n \"address_proof\": \"123 Main St, City, State 12345\"\n },\n \"pan_number\": \"ABCDE1234F\",\n \"aadhaar_masked\": \"1234-5678-9012\",\n \"passport_number\": \"A1234567\"\n },\n \"risk_factors_identified\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"recommendation_for_proceeding\": {\n \"action\": \"Proceed with caution\",\n \"steps\": [\n \"Verify the applicant\u0027s understanding of home purchase costs.\",\n \"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\",\n \"Continue monitoring for any additional inconsistencies in future documentation.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name\\\": {\\n \\\"applicant_name\\\": \\\"John Doe\\\",\\n \\\"verified_name\\\": \\\"JOHN DOE\\\"\\n },\\n \\\"address\\\": {\\n \\\"application_address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"address_proof\\\": \\\"123 Main St, City, State 12345\\\"\\n },\\n \\\"pan_number\\\": \\\"ABCDE1234F\\\",\\n \\\"aadhaar_masked\\\": \\\"1234-5678-9012\\\",\\n \\\"passport_number\\\": \\\"A1234567\\\"\\n },\\n \\\"risk_factors_identified\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Proceed with caution\\\",\\n \\\"steps\\\": [\\n \\\"Verify the applicant\u0027s understanding of home purchase costs.\\\",\\n \\\"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\\\",\\n \\\"Continue monitoring for any additional inconsistencies in future documentation.\\\"\\n ]\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 559, \"completion_tokens\": 271, \"total_tokens\": 830, \"estimated_cost\": {\"amount\": 0.000246, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name\": {\n \"applicant_name\": \"John Doe\",\n \"verified_name\": \"JOHN DOE\"\n },\n \"address\": {\n \"application_address\": \"123 Main St, City, State 12345\",\n \"address_proof\": \"123 Main St, City, State 12345\"\n },\n \"pan_number\": \"ABCDE1234F\",\n \"aadhaar_masked\": \"1234-5678-9012\",\n \"passport_number\": \"A1234567\"\n },\n \"risk_factors_identified\": {\n \"loan_purpose_vs_requested_amount\": {\n \"issue\": \"The requested amount of $10,000 is unusually low for a home purchase.\",\n \"suggestion\": \"Verify if the applicant is aware of the typical costs associated with home purchases.\"\n }\n },\n \"recommendation_for_proceeding\": {\n \"action\": \"Proceed with caution\",\n \"steps\": [\n \"Verify the applicant\u0027s understanding of home purchase costs.\",\n \"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\",\n \"Continue monitoring for any additional inconsistencies in future documentation.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name\\\": {\\n \\\"applicant_name\\\": \\\"John Doe\\\",\\n \\\"verified_name\\\": \\\"JOHN DOE\\\"\\n },\\n \\\"address\\\": {\\n \\\"application_address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"address_proof\\\": \\\"123 Main St, City, State 12345\\\"\\n },\\n \\\"pan_number\\\": \\\"ABCDE1234F\\\",\\n \\\"aadhaar_masked\\\": \\\"1234-5678-9012\\\",\\n \\\"passport_number\\\": \\\"A1234567\\\"\\n },\\n \\\"risk_factors_identified\\\": {\\n \\\"loan_purpose_vs_requested_amount\\\": {\\n \\\"issue\\\": \\\"The requested amount of $10,000 is unusually low for a home purchase.\\\",\\n \\\"suggestion\\\": \\\"Verify if the applicant is aware of the typical costs associated with home purchases.\\\"\\n }\\n },\\n \\\"recommendation_for_proceeding\\\": {\\n \\\"action\\\": \\\"Proceed with caution\\\",\\n \\\"steps\\\": [\\n \\\"Verify the applicant\u0027s understanding of home purchase costs.\\\",\\n \\\"Consider conducting a follow-up interview to clarify the loan purpose and requested amount.\\\",\\n \\\"Continue monitoring for any additional inconsistencies in future documentation.\\\"\\n ]\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 559, \"completion_tokens\": 271, \"total_tokens\": 830, \"estimated_cost\": {\"amount\": 0.000246, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "Based on the provided credit data, we will analyze the default risk using the following factors:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\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\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: $7,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\n- **Total Outstanding Loans**: $125,000\n\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\n\n### 5. Overall Risk Profile\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\n\n### Risk Score Calculation\nConsidering all the factors above, we can assign a risk score based on the analysis:\n- **Credit Score**: 15 (Good)\n- **Repayment Patterns**: 10 (Excellent)\n- **Credit Utilization**: 10 (Good)\n- **Existing Loan Burden**: 10 (Acceptable)\n- **Overall Risk Profile**: 10 (Stable)\n\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\n\n### Recommendations\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\n\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.",
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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 will analyze the default risk using the following factors:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\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\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: $7,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\n- **Total Outstanding Loans**: $125,000\n\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\n\n### 5. Overall Risk Profile\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\n\n### Risk Score Calculation\nConsidering all the factors above, we can assign a risk score based on the analysis:\n- **Credit Score**: 15 (Good)\n- **Repayment Patterns**: 10 (Excellent)\n- **Credit Utilization**: 10 (Good)\n- **Existing Loan Burden**: 10 (Acceptable)\n- **Overall Risk Profile**: 10 (Stable)\n\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\n\n### Recommendations\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\n\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the default risk using the following factors:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\\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\\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: $7,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\\n- **Total Outstanding Loans**: $125,000\\n\\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\\n\\n### 5. Overall Risk Profile\\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\\n\\n### Risk Score Calculation\\nConsidering all the factors above, we can assign a risk score based on the analysis:\\n- **Credit Score**: 15 (Good)\\n- **Repayment Patterns**: 10 (Excellent)\\n- **Credit Utilization**: 10 (Good)\\n- **Existing Loan Burden**: 10 (Acceptable)\\n- **Overall Risk Profile**: 10 (Stable)\\n\\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\\n\\n### Recommendations\\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\\n\\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1380, \"completion_tokens\": 730, \"total_tokens\": 2110, \"estimated_cost\": {\"amount\": 0.000645, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"model": "gpt-4o-mini",
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"output": "Based on the provided credit data, we will analyze the default risk using the following factors:\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\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\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: $7,700\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\n- **Total Outstanding Loans**: $125,000\n\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\n\n### 5. Overall Risk Profile\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\n\n### Risk Score Calculation\nConsidering all the factors above, we can assign a risk score based on the analysis:\n- **Credit Score**: 15 (Good)\n- **Repayment Patterns**: 10 (Excellent)\n- **Credit Utilization**: 10 (Good)\n- **Existing Loan Burden**: 10 (Acceptable)\n- **Overall Risk Profile**: 10 (Stable)\n\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\n\n### Recommendations\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\n\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the default risk using the following factors:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n\\n**Analysis**: A credit score of 720 is considered good, indicating a lower risk of default. The payment history is excellent, with a high percentage of on-time payments. The credit utilization of 35.5% is within acceptable limits (generally below 40% is considered good).\\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\\n**Analysis**: The repayment behavior shows a strong track record, with no defaults and a high percentage of timely payments. The minor instances of being late (30, 60, and 90 days) are relatively low and do not indicate a significant risk.\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: The credit utilization is healthy, suggesting that the applicant is not overly reliant on credit and is managing their credit responsibly.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: $7,700\\n- **Loan Burden Ratio**: 0.28 (28% of monthly income)\\n- **Total Outstanding Loans**: $125,000\\n\\n**Analysis**: The loan burden ratio of 28% is below the typical threshold of 40%, indicating that the applicant can manage their debt obligations comfortably. The repayment track record for existing loans is excellent.\\n\\n### 5. Overall Risk Profile\\n- **Income Stability**: The applicant has a stable income, which supports their ability to meet existing and new debt obligations.\\n- **Financial Discipline**: The applicant has demonstrated good financial discipline with a low number of late payments and a good mix of credit types.\\n\\n### Risk Score Calculation\\nConsidering all the factors above, we can assign a risk score based on the analysis:\\n- **Credit Score**: 15 (Good)\\n- **Repayment Patterns**: 10 (Excellent)\\n- **Credit Utilization**: 10 (Good)\\n- **Existing Loan Burden**: 10 (Acceptable)\\n- **Overall Risk Profile**: 10 (Stable)\\n\\n**Total Risk Score**: 15 + 10 + 10 + 10 + 10 = **55/100**\\n\\n### Recommendations\\n1. **Proceed with Caution**: The applicant shows a good credit profile, but verify the stability of income and any potential changes in financial circumstances.\\n2. **Monitor Financial Behavior**: Continue to monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Consider Additional Loans**: If the applicant applies for additional loans, ensure that their debt-to-income ratio remains healthy and does not exceed 40%.\\n4. **Follow-up on Credit Mix**: Encourage the applicant to maintain a diverse credit mix to further strengthen their credit profile.\\n\\nIn conclusion, the overall risk of default is moderate, and the applicant is likely to meet their financial obligations based on the current data.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1380, \"completion_tokens\": 730, \"total_tokens\": 2110, \"estimated_cost\": {\"amount\": 0.000645, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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"extraction_success": true,
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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"final_underwriting_analysis": {
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"ai_response": "### Final Recommendation: **CONDITIONAL APPROVAL**\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $41.67\n- **Conditions**: \n - Verification of the applicant\u0027s understanding of home purchase costs.\n - Follow-up interview to clarify the loan purpose and requested amount.\n - Continuous monitoring of financial behavior for any changes.\n\n#### Risk Mitigation Measures:\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\n\n#### Reasoning for Decision:\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\n\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\n\n#### Confidence Level: **85**\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
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"output": "### Final Recommendation: **CONDITIONAL APPROVAL**\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $41.67\n- **Conditions**: \n - Verification of the applicant\u0027s understanding of home purchase costs.\n - Follow-up interview to clarify the loan purpose and requested amount.\n - Continuous monitoring of financial behavior for any changes.\n\n#### Risk Mitigation Measures:\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\n\n#### Reasoning for Decision:\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\n\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\n\n#### Confidence Level: **85**\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: **CONDITIONAL APPROVAL**\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $41.67\\n- **Conditions**: \\n - Verification of the applicant\u0027s understanding of home purchase costs.\\n - Follow-up interview to clarify the loan purpose and requested amount.\\n - Continuous monitoring of financial behavior for any changes.\\n\\n#### Risk Mitigation Measures:\\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\\n\\n#### Reasoning for Decision:\\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. 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"output": "### Final Recommendation: **CONDITIONAL APPROVAL**\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $41.67\n- **Conditions**: \n - Verification of the applicant\u0027s understanding of home purchase costs.\n - Follow-up interview to clarify the loan purpose and requested amount.\n - Continuous monitoring of financial behavior for any changes.\n\n#### Risk Mitigation Measures:\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\n\n#### Reasoning for Decision:\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\n\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. Therefore, a conditional approval is recommended, contingent upon further verification and clarification.\n\n#### Confidence Level: **85**\nThis confidence level reflects the strong financial profile of the applicant, balanced by the need for additional verification regarding the loan purpose and requested amount.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: **CONDITIONAL APPROVAL**\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: To be determined based on market rates and applicant\u0027s profile.\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $41.67\\n- **Conditions**: \\n - Verification of the applicant\u0027s understanding of home purchase costs.\\n - Follow-up interview to clarify the loan purpose and requested amount.\\n - Continuous monitoring of financial behavior for any changes.\\n\\n#### Risk Mitigation Measures:\\n1. **Follow-Up Verification**: Conduct a follow-up interview to ensure the applicant is aware of the typical costs associated with home purchases and confirm the purpose of the loan.\\n2. **Monitoring**: Regularly monitor the applicant\u0027s financial behavior, especially regarding any new credit inquiries or changes in repayment patterns.\\n3. **Documentation Review**: Review bank statements and financial documents in the next quarter to ensure continued compliance with income stability and debt management.\\n4. **Debt Management**: Advise the applicant to maintain a healthy debt-to-income ratio and avoid taking on additional debt during the loan term.\\n\\n#### Reasoning for Decision:\\n- **Application Quality**: The application is complete and accurate, with no missing fields and a high overall quality score of 85. However, there is a red flag regarding the requested loan amount being unusually low for a home purchase, which necessitates further verification.\\n- **Document Verification**: All documents have been verified successfully with a 100% verification success rate, indicating strong consistency across documents.\\n- **Income Assessment**: The applicant has a stable income with a positive growth trend, a debt-to-income ratio of 35.9%, and a good financial discipline score of 88. This indicates that the applicant can manage the proposed EMI comfortably.\\n- **Credit Profile**: The applicant has a good credit score of 720, with a strong payment history and low credit utilization. This suggests a lower risk of default.\\n- **Compliance Status**: The applicant is compliant with KYC and AML regulations, with no significant gaps or concerns identified.\\n\\nDespite the positive aspects of the application, the unusual loan amount relative to the home purchase purpose raises concerns that need to be addressed before final approval. 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"output": "```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"salary_consistency\": true,\n \"employment_duration\": \"2.5 years\",\n \"recent_increment\": true,\n \"income_growth_trend\": \"positive\",\n \"overall_stability_score\": 90\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"debt_servicing_score\": 85\n },\n \"financial_discipline_evaluation\": {\n \"maximum_balance\": 45000,\n \"minimum_balance\": 15000,\n \"total_monthly_debits\": 5800,\n \"average_monthly_credits\": 7200,\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"financial_discipline_score\": 85.5,\n \"overall_discipline_score\": 88\n },\n \"risk_factors_and_recommendations\": {\n \"identified_risks\": {\n \"loan_emis_detected\": 2,\n \"debt_to_income_ratio\": 0.359,\n \"financial_discipline\": \"stable\"\n },\n \"recommendations\": [\n \"Continue monitoring the applicant\u0027s financial behavior for any changes.\",\n \"Ensure that the applicant maintains a consistent income and does not take on additional debt.\",\n \"Consider a follow-up review of bank statements in the next quarter.\"\n ]\n },\n \"overall_income_adequacy_score\": 88\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"salary_consistency\\\": true,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"recent_increment\\\": true,\\n \\\"income_growth_trend\\\": \\\"positive\\\",\\n \\\"overall_stability_score\\\": 90\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"debt_servicing_score\\\": 85\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"maximum_balance\\\": 45000,\\n \\\"minimum_balance\\\": 15000,\\n \\\"total_monthly_debits\\\": 5800,\\n \\\"average_monthly_credits\\\": 7200,\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"overall_discipline_score\\\": 88\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"identified_risks\\\": {\\n \\\"loan_emis_detected\\\": 2,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"financial_discipline\\\": \\\"stable\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue monitoring the applicant\u0027s financial behavior for any changes.\\\",\\n \\\"Ensure that the applicant maintains a consistent income and does not take on additional debt.\\\",\\n \\\"Consider a follow-up review of bank statements in the next quarter.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 88\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1042, \"completion_tokens\": 388, \"total_tokens\": 1430, \"estimated_cost\": {\"amount\": 0.000389, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"salary_consistency\": true,\n \"employment_duration\": \"2.5 years\",\n \"recent_increment\": true,\n \"income_growth_trend\": \"positive\",\n \"overall_stability_score\": 90\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"debt_servicing_score\": 85\n },\n \"financial_discipline_evaluation\": {\n \"maximum_balance\": 45000,\n \"minimum_balance\": 15000,\n \"total_monthly_debits\": 5800,\n \"average_monthly_credits\": 7200,\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"financial_discipline_score\": 85.5,\n \"overall_discipline_score\": 88\n },\n \"risk_factors_and_recommendations\": {\n \"identified_risks\": {\n \"loan_emis_detected\": 2,\n \"debt_to_income_ratio\": 0.359,\n \"financial_discipline\": \"stable\"\n },\n \"recommendations\": [\n \"Continue monitoring the applicant\u0027s financial behavior for any changes.\",\n \"Ensure that the applicant maintains a consistent income and does not take on additional debt.\",\n \"Consider a follow-up review of bank statements in the next quarter.\"\n ]\n },\n \"overall_income_adequacy_score\": 88\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"salary_consistency\\\": true,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"recent_increment\\\": true,\\n \\\"income_growth_trend\\\": \\\"positive\\\",\\n \\\"overall_stability_score\\\": 90\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"debt_servicing_score\\\": 85\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"maximum_balance\\\": 45000,\\n \\\"minimum_balance\\\": 15000,\\n \\\"total_monthly_debits\\\": 5800,\\n \\\"average_monthly_credits\\\": 7200,\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"overall_discipline_score\\\": 88\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"identified_risks\\\": {\\n \\\"loan_emis_detected\\\": 2,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"financial_discipline\\\": \\\"stable\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue monitoring the applicant\u0027s financial behavior for any changes.\\\",\\n \\\"Ensure that the applicant maintains a consistent income and does not take on additional debt.\\\",\\n \\\"Consider a follow-up review of bank statements in the next quarter.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 88\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1042, \"completion_tokens\": 388, \"total_tokens\": 1430, \"estimated_cost\": {\"amount\": 0.000389, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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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\": 0.00126, \"started_at\": \"2025-07-15T14:17:02.972939\", \"ended_at\": \"2025-07-15T14:17:02.974199\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.17266,
"end_time": "2025-07-15T14:17:03.041609",
"message_sent": true,
"start_time": "2025-07-15T14:17:02.868949",
"timestamp": "2025-07-15T14:17:03.041609",
"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\": 0.00126, \"started_at\": \"2025-07-15T14:17:02.972939\", \"ended_at\": \"2025-07-15T14:17:02.974199\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T14:17:02.972939",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"validate_application_fields": {
"completion_percentage": 100.0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.226642,
"end_time": "2025-07-15T14:16:12.642874",
"message_sent": true,
"start_time": "2025-07-15T14:16:12.416232",
"timestamp": "2025-07-15T14:16:12.642874",
"worker_executed": true,
"workers_notified": true
},
"missing_fields": [],
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "validate_application_fields",
"validation_passed": true
},
"verify_aadhaar": {
"aadhaar_masked": "1234-5678-9012",
"address_match": true,
"biometric_verified": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.522727,
"end_time": "2025-07-15T14:16:18.919468",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.396741",
"timestamp": "2025-07-15T14:16:18.919468",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"last_updated": "2024-01-15",
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"verification_score": 98.2
},
"verify_address_proof": {
"address_confirmed": "123 Main St, City, State 12345",
"address_match": true,
"document_date": "2024-06-15",
"document_type": "utility_bill",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.54238,
"end_time": "2025-07-15T14:16:19.062567",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.520187",
"timestamp": "2025-07-15T14:16:19.062567",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"verification_score": 92.3
},
"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": 0.27129,
"end_time": "2025-07-15T14:16:27.346241",
"message_sent": true,
"start_time": "2025-07-15T14:16:27.074951",
"timestamp": "2025-07-15T14:16:27.346241",
"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": {
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.470949,
"end_time": "2025-07-15T14:16:18.773550",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.302601",
"timestamp": "2025-07-15T14:16:18.773550",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"name_match": true,
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"pan_number": "ABCDE1234F",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"verification_score": 95.5,
"verified_name": "JOHN DOE"
},
"verify_passport": {
"document_provided": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.289357,
"end_time": "2025-07-15T14:16:18.746112",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.456755",
"timestamp": "2025-07-15T14:16:18.746112",
"worker_executed": true,
"workers_notified": true
},
"expiry_date": "2030-12-31",
"is_valid": true,
"issuing_authority": "Government of India",
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"passport_number": "A1234567",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"verification_score": 96.8
},
"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": 0.235093,
"end_time": "2025-07-15T14:16:26.995536",
"message_sent": true,
"start_time": "2025-07-15T14:16:26.760443",
"timestamp": "2025-07-15T14:16:26.995536",
"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": 0.00126,
"ended_at": "2025-07-15T14:17:02.974199",
"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\": 0.00126, \"started_at\": \"2025-07-15T14:17:02.972939\", \"ended_at\": \"2025-07-15T14:17:02.974199\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.17266,
"end_time": "2025-07-15T14:17:03.041609",
"message_sent": true,
"start_time": "2025-07-15T14:17:02.868949",
"timestamp": "2025-07-15T14:17:03.041609",
"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\": 0.00126, \"started_at\": \"2025-07-15T14:17:02.972939\", \"ended_at\": \"2025-07-15T14:17:02.974199\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T14:17:02.972939",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"validate_application_fields": {
"completion_percentage": 100.0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.226642,
"end_time": "2025-07-15T14:16:12.642874",
"message_sent": true,
"start_time": "2025-07-15T14:16:12.416232",
"timestamp": "2025-07-15T14:16:12.642874",
"worker_executed": true,
"workers_notified": true
},
"missing_fields": [],
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "validate_application_fields",
"validation_passed": true
},
"verify_aadhaar": {
"aadhaar_masked": "1234-5678-9012",
"address_match": true,
"biometric_verified": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.522727,
"end_time": "2025-07-15T14:16:18.919468",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.396741",
"timestamp": "2025-07-15T14:16:18.919468",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"last_updated": "2024-01-15",
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"verification_score": 98.2
},
"verify_address_proof": {
"address_confirmed": "123 Main St, City, State 12345",
"address_match": true,
"document_date": "2024-06-15",
"document_type": "utility_bill",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.54238,
"end_time": "2025-07-15T14:16:19.062567",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.520187",
"timestamp": "2025-07-15T14:16:19.062567",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"verification_score": 92.3
},
"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": 0.27129,
"end_time": "2025-07-15T14:16:27.346241",
"message_sent": true,
"start_time": "2025-07-15T14:16:27.074951",
"timestamp": "2025-07-15T14:16:27.346241",
"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": {
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.470949,
"end_time": "2025-07-15T14:16:18.773550",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.302601",
"timestamp": "2025-07-15T14:16:18.773550",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"name_match": true,
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"pan_number": "ABCDE1234F",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"verification_score": 95.5,
"verified_name": "JOHN DOE"
},
"verify_passport": {
"document_provided": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.289357,
"end_time": "2025-07-15T14:16:18.746112",
"message_sent": true,
"start_time": "2025-07-15T14:16:18.456755",
"timestamp": "2025-07-15T14:16:18.746112",
"worker_executed": true,
"workers_notified": true
},
"expiry_date": "2030-12-31",
"is_valid": true,
"issuing_authority": "Government of India",
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"passport_number": "A1234567",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"verification_score": 96.8
},
"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": 0.235093,
"end_time": "2025-07-15T14:16:26.995536",
"message_sent": true,
"start_time": "2025-07-15T14:16:26.760443",
"timestamp": "2025-07-15T14:16:26.995536",
"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
}
}