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": 0.178615,
"end_time": "2025-07-16T07:44:23.958277",
"message_sent": true,
"start_time": "2025-07-16T07:44:23.779662",
"timestamp": "2025-07-16T07:44:23.958277",
"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": 0.432652,
"end_time": "2025-07-16T07:40:57.523571",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.090919",
"timestamp": "2025-07-16T07:40:57.523571",
"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": 0.226847,
"end_time": "2025-07-16T07:44:08.361160",
"message_sent": true,
"start_time": "2025-07-16T07:44:08.134313",
"timestamp": "2025-07-16T07:44:08.361160",
"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": 0.373858,
"end_time": "2025-07-16T07:40:57.387888",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.014030",
"timestamp": "2025-07-16T07:40:57.387888",
"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": "Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\n\nHere\u2019s a detailed quality assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\n\n2. **Consistency of Information**:\n - Without access to the customer information, it is not possible to check for consistency within the application data.\n\n3. **Red Flags or Inconsistencies**:\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\n\n4. **Overall Application Quality Score**:\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\n\nBased on the above assessment, here is the JSON response:\n\n```json\n{\n \"data_completeness\": \"Incomplete - customer information not accessible\",\n \"data_accuracy\": \"Cannot assess - data retrieval failed\",\n \"information_consistency\": \"Cannot assess - data retrieval failed\",\n \"red_flags\": [\n \"Unresolved reference to customer information\",\n \"Potential issues with application submission or data handling\"\n ],\n \"overall_quality_score\": 10\n}\n```\n\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 506,
"model": "gpt-4o-mini",
"output_length": 1917,
"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": "Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\n\nHere\u2019s a detailed quality assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\n\n2. **Consistency of Information**:\n - Without access to the customer information, it is not possible to check for consistency within the application data.\n\n3. **Red Flags or Inconsistencies**:\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\n\n4. **Overall Application Quality Score**:\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\n\nBased on the above assessment, here is the JSON response:\n\n```json\n{\n \"data_completeness\": \"Incomplete - customer information not accessible\",\n \"data_accuracy\": \"Cannot assess - data retrieval failed\",\n \"information_consistency\": \"Cannot assess - data retrieval failed\",\n \"red_flags\": [\n \"Unresolved reference to customer information\",\n \"Potential issues with application submission or data handling\"\n ],\n \"overall_quality_score\": 10\n}\n```\n\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\\n\\nHere\\u2019s a detailed quality assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\\n\\n2. **Consistency of Information**:\\n - Without access to the customer information, it is not possible to check for consistency within the application data.\\n\\n3. **Red Flags or Inconsistencies**:\\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\\n\\n4. **Overall Application Quality Score**:\\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\\n\\nBased on the above assessment, here is the JSON response:\\n\\n```json\\n{\\n \\\"data_completeness\\\": \\\"Incomplete - customer information not accessible\\\",\\n \\\"data_accuracy\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"information_consistency\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"red_flags\\\": [\\n \\\"Unresolved reference to customer information\\\",\\n \\\"Potential issues with application submission or data handling\\\"\\n ],\\n \\\"overall_quality_score\\\": 10\\n}\\n```\\n\\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 370, \"total_tokens\": 556, \"estimated_cost\": {\"amount\": 0.00025, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": "",
"token_usage": {
"completion_tokens": 370,
"estimated_cost": {
"amount": 0.00025,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 186,
"provider": "openai",
"total_tokens": 556
}
},
"duration_seconds": 6.697684,
"end_time": "2025-07-16T07:40:48.556783",
"message_sent": true,
"start_time": "2025-07-16T07:40:41.859099",
"timestamp": "2025-07-16T07:40:48.556783",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\n\nHere\u2019s a detailed quality assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\n\n2. **Consistency of Information**:\n - Without access to the customer information, it is not possible to check for consistency within the application data.\n\n3. **Red Flags or Inconsistencies**:\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\n\n4. **Overall Application Quality Score**:\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\n\nBased on the above assessment, here is the JSON response:\n\n```json\n{\n \"data_completeness\": \"Incomplete - customer information not accessible\",\n \"data_accuracy\": \"Cannot assess - data retrieval failed\",\n \"information_consistency\": \"Cannot assess - data retrieval failed\",\n \"red_flags\": [\n \"Unresolved reference to customer information\",\n \"Potential issues with application submission or data handling\"\n ],\n \"overall_quality_score\": 10\n}\n```\n\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\\n\\nHere\\u2019s a detailed quality assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\\n\\n2. **Consistency of Information**:\\n - Without access to the customer information, it is not possible to check for consistency within the application data.\\n\\n3. **Red Flags or Inconsistencies**:\\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\\n\\n4. **Overall Application Quality Score**:\\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\\n\\nBased on the above assessment, here is the JSON response:\\n\\n```json\\n{\\n \\\"data_completeness\\\": \\\"Incomplete - customer information not accessible\\\",\\n \\\"data_accuracy\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"information_consistency\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"red_flags\\\": [\\n \\\"Unresolved reference to customer information\\\",\\n \\\"Potential issues with application submission or data handling\\\"\\n ],\\n \\\"overall_quality_score\\\": 10\\n}\\n```\\n\\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 370, \"total_tokens\": 556, \"estimated_cost\": {\"amount\": 0.00025, \"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": 370,
"estimated_cost": {
"amount": 0.00025,
"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 186,
"provider": "openai",
"total_tokens": 556
}
},
"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": 0.267759,
"end_time": "2025-07-16T07:44:08.657189",
"message_sent": true,
"start_time": "2025-07-16T07:44:08.389430",
"timestamp": "2025-07-16T07:44:08.657189",
"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": 0.188743,
"end_time": "2025-07-16T07:44:23.528568",
"message_sent": true,
"start_time": "2025-07-16T07:44:23.339825",
"timestamp": "2025-07-16T07:44:23.528568",
"worker_executed": true,
"workers_notified": true
},
"internal_credit_score": 337.9,
"min_required_score": 650,
"output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
"return_code": 0,
"risk_category": "high",
"score_acceptable": false,
"scoring_factors": {
"cibil_contribution": 288.0,
"loan_burden_contribution": 7.2,
"payment_history_contribution": 29.7,
"utilization_contribution": 12.96
},
"status": "completed",
"stderr": "",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpt4_7jqhj.py\", line 13, in \u003cmodule\u003e\n loan_amount = UNRESOLVED_loan_amount\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpt4_7jqhj.py\", line 13, in \u003cmodule\u003e\n loan_amount = UNRESOLVED_loan_amount\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_debt_to_income"
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.22863,
"end_time": "2025-07-16T07:44:08.102407",
"message_sent": true,
"start_time": "2025-07-16T07:44:07.873777",
"timestamp": "2025-07-16T07:44:08.102407",
"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 a comprehensive 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 Compliance\": {\n \"regulatory_risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"policy_version\": \"2024.1\",\n \"policy_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\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1347,
"model": "gpt-4o-mini",
"output_length": 1659,
"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",
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"output": "Based on the provided compliance check results, here is a comprehensive 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 Compliance\": {\n \"regulatory_risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"policy_version\": \"2024.1\",\n \"policy_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\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive 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 Compliance\\\": {\\n \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"policy_version\\\": \\\"2024.1\\\",\\n \\\"policy_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\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2599, \"completion_tokens\": 378, \"total_tokens\": 2977, \"estimated_cost\": {\"amount\": 0.000617, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided compliance check results, here is a comprehensive 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 Compliance\": {\n \"regulatory_risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"policy_version\": \"2024.1\",\n \"policy_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\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive 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 Compliance\\\": {\\n \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"policy_version\\\": \\\"2024.1\\\",\\n \\\"policy_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\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2599, \"completion_tokens\": 378, \"total_tokens\": 2977, \"estimated_cost\": {\"amount\": 0.000617, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\n\n3. **Risk Factors Identified**:\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\n\n4. **Recommendation for Proceeding**:\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n \"overall_verification_success_rate\": \"0%\",\n \"consistency_across_documents\": \"All documents failed verification due to absence\",\n \"risk_factors_identified\": [\n \"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\",\n \"Potential issues with document submission process\"\n ],\n \"recommendation_for_proceeding\": [\n \"Request the applicant to re-upload all required documents\",\n \"Provide clear instructions for document submission\",\n \"Implement a checklist for applicants to ensure all documents are submitted\"\n ]\n}\n```",
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"output": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\n\n3. **Risk Factors Identified**:\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\n\n4. **Recommendation for Proceeding**:\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n \"overall_verification_success_rate\": \"0%\",\n \"consistency_across_documents\": \"All documents failed verification due to absence\",\n \"risk_factors_identified\": [\n \"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\",\n \"Potential issues with document submission process\"\n ],\n \"recommendation_for_proceeding\": [\n \"Request the applicant to re-upload all required documents\",\n \"Provide clear instructions for document submission\",\n \"Implement a checklist for applicants to ensure all documents are submitted\"\n ]\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\\n\\n3. **Risk Factors Identified**:\\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\\n\\n4. **Recommendation for Proceeding**:\\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n \\\"consistency_across_documents\\\": \\\"All documents failed verification due to absence\\\",\\n \\\"risk_factors_identified\\\": [\\n \\\"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\\\",\\n \\\"Potential issues with document submission process\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": [\\n \\\"Request the applicant to re-upload all required documents\\\",\\n \\\"Provide clear instructions for document submission\\\",\\n \\\"Implement a checklist for applicants to ensure all documents are submitted\\\"\\n ]\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 888, \"completion_tokens\": 385, \"total_tokens\": 1273, \"estimated_cost\": {\"amount\": 0.000364, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\n\n3. **Risk Factors Identified**:\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\n\n4. **Recommendation for Proceeding**:\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n \"overall_verification_success_rate\": \"0%\",\n \"consistency_across_documents\": \"All documents failed verification due to absence\",\n \"risk_factors_identified\": [\n \"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\",\n \"Potential issues with document submission process\"\n ],\n \"recommendation_for_proceeding\": [\n \"Request the applicant to re-upload all required documents\",\n \"Provide clear instructions for document submission\",\n \"Implement a checklist for applicants to ensure all documents are submitted\"\n ]\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\\n\\n3. **Risk Factors Identified**:\\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\\n\\n4. **Recommendation for Proceeding**:\\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n \\\"consistency_across_documents\\\": \\\"All documents failed verification due to absence\\\",\\n \\\"risk_factors_identified\\\": [\\n \\\"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\\\",\\n \\\"Potential issues with document submission process\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": [\\n \\\"Request the applicant to re-upload all required documents\\\",\\n \\\"Provide clear instructions for document submission\\\",\\n \\\"Implement a checklist for applicants to ensure all documents are submitted\\\"\\n ]\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 888, \"completion_tokens\": 385, \"total_tokens\": 1273, \"estimated_cost\": {\"amount\": 0.000364, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n- **Recent Inquiries**: 2\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- **Repayment Track Record**: Excellent\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Total Outstanding**: 125000\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\n\n### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n### Risk Score Calculation\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \n\n1. **Credit Score**: 720 (weight: 30%) \u2192 30 * 0.8 = 24\n2. **Payment History**: 99% on-time (weight: 30%) \u2192 30 * 0.99 = 29.7\n3. **Credit Utilization**: 35.5% (weight: 15%) \u2192 15 * (1 - 0.355) = 9.15\n4. **Loan Burden Ratio**: 28% (weight: 15%) \u2192 15 * (1 - 0.28) = 10.2\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \u2192 10 * 0.85 = 8.5\n\n### Total Risk Score Calculation\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\n\n### Final Risk Score\n- **Risk Score**: 82 (rounded to nearest whole number)\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\n\n### Conclusion\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.",
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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 various factors contributing to the default risk and calculate a risk score.\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n- **Recent Inquiries**: 2\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- **Repayment Track Record**: Excellent\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Total Outstanding**: 125000\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\n\n### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n### Risk Score Calculation\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \n\n1. **Credit Score**: 720 (weight: 30%) \u2192 30 * 0.8 = 24\n2. **Payment History**: 99% on-time (weight: 30%) \u2192 30 * 0.99 = 29.7\n3. **Credit Utilization**: 35.5% (weight: 15%) \u2192 15 * (1 - 0.355) = 9.15\n4. **Loan Burden Ratio**: 28% (weight: 15%) \u2192 15 * (1 - 0.28) = 10.2\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \u2192 10 * 0.85 = 8.5\n\n### Total Risk Score Calculation\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\n\n### Final Risk Score\n- **Risk Score**: 82 (rounded to nearest whole number)\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\n\n### Conclusion\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n- **Recent Inquiries**: 2\\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- **Repayment Track Record**: Excellent\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding**: 125000\\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\\n\\n### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n### Risk Score Calculation\\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \\n\\n1. **Credit Score**: 720 (weight: 30%) \\u2192 30 * 0.8 = 24\\n2. **Payment History**: 99% on-time (weight: 30%) \\u2192 30 * 0.99 = 29.7\\n3. **Credit Utilization**: 35.5% (weight: 15%) \\u2192 15 * (1 - 0.355) = 9.15\\n4. **Loan Burden Ratio**: 28% (weight: 15%) \\u2192 15 * (1 - 0.28) = 10.2\\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \\u2192 10 * 0.85 = 8.5\\n\\n### Total Risk Score Calculation\\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\\n\\n### Final Risk Score\\n- **Risk Score**: 82 (rounded to nearest whole number)\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\\n\\n### Conclusion\\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1877, \"completion_tokens\": 745, \"total_tokens\": 2622, \"estimated_cost\": {\"amount\": 0.000729, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n- **Recent Inquiries**: 2\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- **Repayment Track Record**: Excellent\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Total Outstanding**: 125000\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\n\n### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n### Risk Score Calculation\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \n\n1. **Credit Score**: 720 (weight: 30%) \u2192 30 * 0.8 = 24\n2. **Payment History**: 99% on-time (weight: 30%) \u2192 30 * 0.99 = 29.7\n3. **Credit Utilization**: 35.5% (weight: 15%) \u2192 15 * (1 - 0.355) = 9.15\n4. **Loan Burden Ratio**: 28% (weight: 15%) \u2192 15 * (1 - 0.28) = 10.2\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \u2192 10 * 0.85 = 8.5\n\n### Total Risk Score Calculation\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\n\n### Final Risk Score\n- **Risk Score**: 82 (rounded to nearest whole number)\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\n\n### Conclusion\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n- **Recent Inquiries**: 2\\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- **Repayment Track Record**: Excellent\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding**: 125000\\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\\n\\n### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n### Risk Score Calculation\\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \\n\\n1. **Credit Score**: 720 (weight: 30%) \\u2192 30 * 0.8 = 24\\n2. **Payment History**: 99% on-time (weight: 30%) \\u2192 30 * 0.99 = 29.7\\n3. **Credit Utilization**: 35.5% (weight: 15%) \\u2192 15 * (1 - 0.355) = 9.15\\n4. **Loan Burden Ratio**: 28% (weight: 15%) \\u2192 15 * (1 - 0.28) = 10.2\\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \\u2192 10 * 0.85 = 8.5\\n\\n### Total Risk Score Calculation\\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\\n\\n### Final Risk Score\\n- **Risk Score**: 82 (rounded to nearest whole number)\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\\n\\n### Conclusion\\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1877, \"completion_tokens\": 745, \"total_tokens\": 2622, \"estimated_cost\": {\"amount\": 0.000729, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpfflt2smf.py\", line 18, in \u003cmodule\u003e\n \"requested_amount\": UNRESOLVED_loan_amount\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
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"ai_response": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable.\n- **Loan Term**: Not applicable.\n- **Repayment Schedule**: Not applicable.\n\n#### Risk Mitigation Measures:\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\n\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\n\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\n\n#### Confidence Level: 85\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.",
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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: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable.\n- **Loan Term**: Not applicable.\n- **Repayment Schedule**: Not applicable.\n\n#### Risk Mitigation Measures:\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\n\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\n\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\n\n#### Confidence Level: 85\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable.\\n- **Loan Term**: Not applicable.\\n- **Repayment Schedule**: Not applicable.\\n\\n#### Risk Mitigation Measures:\\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\\n\\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\\n\\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\\n\\n#### Confidence Level: 85\\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. 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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable.\n- **Loan Term**: Not applicable.\n- **Repayment Schedule**: Not applicable.\n\n#### Risk Mitigation Measures:\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\n\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\n\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\n\n#### Confidence Level: 85\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable.\\n- **Loan Term**: Not applicable.\\n- **Repayment Schedule**: Not applicable.\\n\\n#### Risk Mitigation Measures:\\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\\n\\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\\n\\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\\n\\n#### Confidence Level: 85\\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. 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"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmp9oirvh3q.py\", line 11, in \u003cmodule\u003e\n \"loan_amount\": UNRESOLVED_loan_amount,\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
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"ai_response": "Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true,\n \"stability_score\": 90,\n \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\"\n },\n \"debt_servicing_capability\": {\n \"monthly_debts\": 5800,\n \"monthly_net_income\": 6800,\n \"debt_to_income_ratio\": 85.29,\n \"loan_emis_detected\": 2,\n \"bounced_transactions\": 0,\n \"comments\": \"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\"\n },\n \"financial_discipline_evaluation\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"salary_credits_consistent\": true,\n \"irregular_transactions\": false,\n \"comments\": \"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"High debt-to-income ratio may limit future borrowing capacity.\",\n \"Dependence on salary for debt servicing could be risky if employment status changes.\"\n ],\n \"recommendations\": [\n \"Consider reducing existing debt to improve the debt-to-income ratio.\",\n \"Maintain an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore additional income sources to diversify income streams.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"comments\": \"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.",
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"output": "Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true,\n \"stability_score\": 90,\n \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\"\n },\n \"debt_servicing_capability\": {\n \"monthly_debts\": 5800,\n \"monthly_net_income\": 6800,\n \"debt_to_income_ratio\": 85.29,\n \"loan_emis_detected\": 2,\n \"bounced_transactions\": 0,\n \"comments\": \"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\"\n },\n \"financial_discipline_evaluation\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"salary_credits_consistent\": true,\n \"irregular_transactions\": false,\n \"comments\": \"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"High debt-to-income ratio may limit future borrowing capacity.\",\n \"Dependence on salary for debt servicing could be risky if employment status changes.\"\n ],\n \"recommendations\": [\n \"Consider reducing existing debt to improve the debt-to-income ratio.\",\n \"Maintain an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore additional income sources to diversify income streams.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"comments\": \"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true,\\n \\\"stability_score\\\": 90,\\n \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_debts\\\": 5800,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"debt_to_income_ratio\\\": 85.29,\\n \\\"loan_emis_detected\\\": 2,\\n \\\"bounced_transactions\\\": 0,\\n \\\"comments\\\": \\\"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"salary_credits_consistent\\\": true,\\n \\\"irregular_transactions\\\": false,\\n \\\"comments\\\": \\\"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"High debt-to-income ratio may limit future borrowing capacity.\\\",\\n \\\"Dependence on salary for debt servicing could be risky if employment status changes.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Consider reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Maintain an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore additional income sources to diversify income streams.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"comments\\\": \\\"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1299, \"completion_tokens\": 627, \"total_tokens\": 1926, \"estimated_cost\": {\"amount\": 0.000571, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true,\n \"stability_score\": 90,\n \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\"\n },\n \"debt_servicing_capability\": {\n \"monthly_debts\": 5800,\n \"monthly_net_income\": 6800,\n \"debt_to_income_ratio\": 85.29,\n \"loan_emis_detected\": 2,\n \"bounced_transactions\": 0,\n \"comments\": \"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\"\n },\n \"financial_discipline_evaluation\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"salary_credits_consistent\": true,\n \"irregular_transactions\": false,\n \"comments\": \"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"High debt-to-income ratio may limit future borrowing capacity.\",\n \"Dependence on salary for debt servicing could be risky if employment status changes.\"\n ],\n \"recommendations\": [\n \"Consider reducing existing debt to improve the debt-to-income ratio.\",\n \"Maintain an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore additional income sources to diversify income streams.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"comments\": \"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true,\\n \\\"stability_score\\\": 90,\\n \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_debts\\\": 5800,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"debt_to_income_ratio\\\": 85.29,\\n \\\"loan_emis_detected\\\": 2,\\n \\\"bounced_transactions\\\": 0,\\n \\\"comments\\\": \\\"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"salary_credits_consistent\\\": true,\\n \\\"irregular_transactions\\\": false,\\n \\\"comments\\\": \\\"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"High debt-to-income ratio may limit future borrowing capacity.\\\",\\n \\\"Dependence on salary for debt servicing could be risky if employment status changes.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Consider reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Maintain an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore additional income sources to diversify income streams.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"comments\\\": \\\"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1299, \"completion_tokens\": 627, \"total_tokens\": 1926, \"estimated_cost\": {\"amount\": 0.000571, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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},
"oldest_account_age": "60 months",
"output": "__OUTPUTS__ {\"oldest_account_age\": \"60 months\", \"average_account_age\": \"32 months\", \"credit_mix\": {\"credit_cards\": 3, \"personal_loans\": 1, \"auto_loans\": 1, \"home_loans\": 0, \"other\": 1}, \"repayment_behavior\": {\"never_missed\": 85.0, \"30_days_late\": 12.0, \"60_days_late\": 2.5, \"90_days_late\": 0.5, \"defaults\": 0.0}, \"credit_limit_utilization\": 35.2, \"recent_credit_behavior\": \"stable\"}\n",
"recent_credit_behavior": "stable",
"repayment_behavior": {
"30_days_late": 12.0,
"60_days_late": 2.5,
"90_days_late": 0.5,
"defaults": 0.0,
"never_missed": 85.0
},
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "analyze_credit_history"
},
"analyze_salary_slips": {
"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": 0.373858,
"end_time": "2025-07-16T07:40:57.387888",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.014030",
"timestamp": "2025-07-16T07:40:57.387888",
"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": "Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\n\nHere\u2019s a detailed quality assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\n\n2. **Consistency of Information**:\n - Without access to the customer information, it is not possible to check for consistency within the application data.\n\n3. **Red Flags or Inconsistencies**:\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\n\n4. **Overall Application Quality Score**:\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\n\nBased on the above assessment, here is the JSON response:\n\n```json\n{\n \"data_completeness\": \"Incomplete - customer information not accessible\",\n \"data_accuracy\": \"Cannot assess - data retrieval failed\",\n \"information_consistency\": \"Cannot assess - data retrieval failed\",\n \"red_flags\": [\n \"Unresolved reference to customer information\",\n \"Potential issues with application submission or data handling\"\n ],\n \"overall_quality_score\": 10\n}\n```\n\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"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"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\n\nHere\u2019s a detailed quality assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\n\n2. **Consistency of Information**:\n - Without access to the customer information, it is not possible to check for consistency within the application data.\n\n3. **Red Flags or Inconsistencies**:\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\n\n4. **Overall Application Quality Score**:\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\n\nBased on the above assessment, here is the JSON response:\n\n```json\n{\n \"data_completeness\": \"Incomplete - customer information not accessible\",\n \"data_accuracy\": \"Cannot assess - data retrieval failed\",\n \"information_consistency\": \"Cannot assess - data retrieval failed\",\n \"red_flags\": [\n \"Unresolved reference to customer information\",\n \"Potential issues with application submission or data handling\"\n ],\n \"overall_quality_score\": 10\n}\n```\n\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\\n\\nHere\\u2019s a detailed quality assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\\n\\n2. **Consistency of Information**:\\n - Without access to the customer information, it is not possible to check for consistency within the application data.\\n\\n3. **Red Flags or Inconsistencies**:\\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\\n\\n4. **Overall Application Quality Score**:\\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\\n\\nBased on the above assessment, here is the JSON response:\\n\\n```json\\n{\\n \\\"data_completeness\\\": \\\"Incomplete - customer information not accessible\\\",\\n \\\"data_accuracy\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"information_consistency\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"red_flags\\\": [\\n \\\"Unresolved reference to customer information\\\",\\n \\\"Potential issues with application submission or data handling\\\"\\n ],\\n \\\"overall_quality_score\\\": 10\\n}\\n```\\n\\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 370, \"total_tokens\": 556, \"estimated_cost\": {\"amount\": 0.00025, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
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"status": "completed",
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"estimated_cost": {
"amount": 0.00025,
"currency": "USD"
},
"model": "gpt-4o-mini",
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"provider": "openai",
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}
},
"duration_seconds": 6.697684,
"end_time": "2025-07-16T07:40:48.556783",
"message_sent": true,
"start_time": "2025-07-16T07:40:41.859099",
"timestamp": "2025-07-16T07:40:48.556783",
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"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\n\nHere\u2019s a detailed quality assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\n\n2. **Consistency of Information**:\n - Without access to the customer information, it is not possible to check for consistency within the application data.\n\n3. **Red Flags or Inconsistencies**:\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\n\n4. **Overall Application Quality Score**:\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\n\nBased on the above assessment, here is the JSON response:\n\n```json\n{\n \"data_completeness\": \"Incomplete - customer information not accessible\",\n \"data_accuracy\": \"Cannot assess - data retrieval failed\",\n \"information_consistency\": \"Cannot assess - data retrieval failed\",\n \"red_flags\": [\n \"Unresolved reference to customer information\",\n \"Potential issues with application submission or data handling\"\n ],\n \"overall_quality_score\": 10\n}\n```\n\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there is an issue with the extraction of customer information from the loan application. The error message indicates that the script failed due to an unresolved reference to `UNRESOLVED_extract_application_info.customer_info`. This suggests that the application data is either not available or not properly formatted for analysis.\\n\\nHere\\u2019s a detailed quality assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n - **Completeness**: The customer information is not accessible due to the unresolved reference. Therefore, it is impossible to assess the completeness of the data.\\n - **Accuracy**: Since the data cannot be retrieved, accuracy cannot be evaluated.\\n\\n2. **Consistency of Information**:\\n - Without access to the customer information, it is not possible to check for consistency within the application data.\\n\\n3. **Red Flags or Inconsistencies**:\\n - The primary red flag is the failure to extract customer information, which indicates a potential issue with the application process or data handling. This could suggest that the application is incomplete or improperly submitted.\\n\\n4. **Overall Application Quality Score**:\\n - Given that the application data is not retrievable and no information can be assessed, the overall quality score would be very low.\\n\\nBased on the above assessment, here is the JSON response:\\n\\n```json\\n{\\n \\\"data_completeness\\\": \\\"Incomplete - customer information not accessible\\\",\\n \\\"data_accuracy\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"information_consistency\\\": \\\"Cannot assess - data retrieval failed\\\",\\n \\\"red_flags\\\": [\\n \\\"Unresolved reference to customer information\\\",\\n \\\"Potential issues with application submission or data handling\\\"\\n ],\\n \\\"overall_quality_score\\\": 10\\n}\\n```\\n\\nThis score reflects the inability to analyze the application due to the unresolved data extraction issue.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 370, \"total_tokens\": 556, \"estimated_cost\": {\"amount\": 0.00025, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "application_quality_check",
"token_usage": {
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"currency": "USD"
},
"model": "gpt-4o-mini",
"prompt_tokens": 186,
"provider": "openai",
"total_tokens": 556
}
},
"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": 0.267759,
"end_time": "2025-07-16T07:44:08.657189",
"message_sent": true,
"start_time": "2025-07-16T07:44:08.389430",
"timestamp": "2025-07-16T07:44:08.657189",
"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": 0.188743,
"end_time": "2025-07-16T07:44:23.528568",
"message_sent": true,
"start_time": "2025-07-16T07:44:23.339825",
"timestamp": "2025-07-16T07:44:23.528568",
"worker_executed": true,
"workers_notified": true
},
"internal_credit_score": 337.9,
"min_required_score": 650,
"output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
"return_code": 0,
"risk_category": "high",
"score_acceptable": false,
"scoring_factors": {
"cibil_contribution": 288.0,
"loan_burden_contribution": 7.2,
"payment_history_contribution": 29.7,
"utilization_contribution": 12.96
},
"status": "completed",
"stderr": "",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpt4_7jqhj.py\", line 13, in \u003cmodule\u003e\n loan_amount = UNRESOLVED_loan_amount\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpt4_7jqhj.py\", line 13, in \u003cmodule\u003e\n loan_amount = UNRESOLVED_loan_amount\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_debt_to_income"
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.22863,
"end_time": "2025-07-16T07:44:08.102407",
"message_sent": true,
"start_time": "2025-07-16T07:44:07.873777",
"timestamp": "2025-07-16T07:44:08.102407",
"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 a comprehensive 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 Compliance\": {\n \"regulatory_risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"policy_version\": \"2024.1\",\n \"policy_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\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.",
"execution_details": {
"actual_result": {
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"agent_type": "assistant",
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"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
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"model_client_id": "compliance_reviewer",
"output": "Based on the provided compliance check results, here is a comprehensive 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 Compliance\": {\n \"regulatory_risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"policy_version\": \"2024.1\",\n \"policy_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\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive 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 Compliance\\\": {\\n \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"policy_version\\\": \\\"2024.1\\\",\\n \\\"policy_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\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2599, \"completion_tokens\": 378, \"total_tokens\": 2977, \"estimated_cost\": {\"amount\": 0.000617, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
"output_format": "json",
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"output": "Based on the provided compliance check results, here is a comprehensive 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 Compliance\": {\n \"regulatory_risk\": \"Minimal\",\n \"compliance_score\": 97.2\n },\n \"Internal Policy\": {\n \"policy_version\": \"2024.1\",\n \"policy_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\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive 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 Compliance\\\": {\\n \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n \\\"compliance_score\\\": 97.2\\n },\\n \\\"Internal Policy\\\": {\\n \\\"policy_version\\\": \\\"2024.1\\\",\\n \\\"policy_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\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The organization is compliant with all relevant regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Regular monitoring and updates to compliance practices are recommended to maintain high standards.\\n5. **Compliance Confidence Score**: A score of 97 reflects a strong confidence in the organization\u0027s compliance posture.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2599, \"completion_tokens\": 378, \"total_tokens\": 2977, \"estimated_cost\": {\"amount\": 0.000617, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\n\n3. **Risk Factors Identified**:\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\n\n4. **Recommendation for Proceeding**:\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n \"overall_verification_success_rate\": \"0%\",\n \"consistency_across_documents\": \"All documents failed verification due to absence\",\n \"risk_factors_identified\": [\n \"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\",\n \"Potential issues with document submission process\"\n ],\n \"recommendation_for_proceeding\": [\n \"Request the applicant to re-upload all required documents\",\n \"Provide clear instructions for document submission\",\n \"Implement a checklist for applicants to ensure all documents are submitted\"\n ]\n}\n```",
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"output": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\n\n3. **Risk Factors Identified**:\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\n\n4. **Recommendation for Proceeding**:\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n \"overall_verification_success_rate\": \"0%\",\n \"consistency_across_documents\": \"All documents failed verification due to absence\",\n \"risk_factors_identified\": [\n \"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\",\n \"Potential issues with document submission process\"\n ],\n \"recommendation_for_proceeding\": [\n \"Request the applicant to re-upload all required documents\",\n \"Provide clear instructions for document submission\",\n \"Implement a checklist for applicants to ensure all documents are submitted\"\n ]\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\\n\\n3. **Risk Factors Identified**:\\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\\n\\n4. **Recommendation for Proceeding**:\\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n \\\"consistency_across_documents\\\": \\\"All documents failed verification due to absence\\\",\\n \\\"risk_factors_identified\\\": [\\n \\\"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\\\",\\n \\\"Potential issues with document submission process\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": [\\n \\\"Request the applicant to re-upload all required documents\\\",\\n \\\"Provide clear instructions for document submission\\\",\\n \\\"Implement a checklist for applicants to ensure all documents are submitted\\\"\\n ]\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 888, \"completion_tokens\": 385, \"total_tokens\": 1273, \"estimated_cost\": {\"amount\": 0.000364, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\n\n3. **Risk Factors Identified**:\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\n\n4. **Recommendation for Proceeding**:\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n \"overall_verification_success_rate\": \"0%\",\n \"consistency_across_documents\": \"All documents failed verification due to absence\",\n \"risk_factors_identified\": [\n \"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\",\n \"Potential issues with document submission process\"\n ],\n \"recommendation_for_proceeding\": [\n \"Request the applicant to re-upload all required documents\",\n \"Provide clear instructions for document submission\",\n \"Implement a checklist for applicants to ensure all documents are submitted\"\n ]\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n - All document verifications have failed, resulting in a 0% success rate. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n - There is a consistent failure across all document types. Each verification indicates that the respective document was not found in the uploaded documents, leading to a uniform lack of data for assessment.\\n\\n3. **Risk Factors Identified**:\\n - The primary risk factor is the absence of all critical identification documents (PAN, Aadhaar, Passport, and Address Proof). This raises concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n - The lack of any extracted data or OCR confidence (0.0) suggests that the documents may not have been uploaded correctly or are missing entirely.\\n\\n4. **Recommendation for Proceeding**:\\n - It is recommended to request the applicant to re-upload the required documents. Clear instructions should be provided to ensure that all necessary identification and address proof documents are included.\\n - Consider implementing a checklist for applicants to verify that all required documents are submitted before processing their application further.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n \\\"consistency_across_documents\\\": \\\"All documents failed verification due to absence\\\",\\n \\\"risk_factors_identified\\\": [\\n \\\"Absence of critical identification documents (PAN, Aadhaar, Passport, Address Proof)\\\",\\n \\\"Potential issues with document submission process\\\"\\n ],\\n \\\"recommendation_for_proceeding\\\": [\\n \\\"Request the applicant to re-upload all required documents\\\",\\n \\\"Provide clear instructions for document submission\\\",\\n \\\"Implement a checklist for applicants to ensure all documents are submitted\\\"\\n ]\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 888, \"completion_tokens\": 385, \"total_tokens\": 1273, \"estimated_cost\": {\"amount\": 0.000364, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"ai_response": "Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n- **Recent Inquiries**: 2\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- **Repayment Track Record**: Excellent\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Total Outstanding**: 125000\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\n\n### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n### Risk Score Calculation\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \n\n1. **Credit Score**: 720 (weight: 30%) \u2192 30 * 0.8 = 24\n2. **Payment History**: 99% on-time (weight: 30%) \u2192 30 * 0.99 = 29.7\n3. **Credit Utilization**: 35.5% (weight: 15%) \u2192 15 * (1 - 0.355) = 9.15\n4. **Loan Burden Ratio**: 28% (weight: 15%) \u2192 15 * (1 - 0.28) = 10.2\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \u2192 10 * 0.85 = 8.5\n\n### Total Risk Score Calculation\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\n\n### Final Risk Score\n- **Risk Score**: 82 (rounded to nearest whole number)\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\n\n### Conclusion\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.",
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"output": "Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n- **Recent Inquiries**: 2\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- **Repayment Track Record**: Excellent\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Total Outstanding**: 125000\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\n\n### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n### Risk Score Calculation\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \n\n1. **Credit Score**: 720 (weight: 30%) \u2192 30 * 0.8 = 24\n2. **Payment History**: 99% on-time (weight: 30%) \u2192 30 * 0.99 = 29.7\n3. **Credit Utilization**: 35.5% (weight: 15%) \u2192 15 * (1 - 0.355) = 9.15\n4. **Loan Burden Ratio**: 28% (weight: 15%) \u2192 15 * (1 - 0.28) = 10.2\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \u2192 10 * 0.85 = 8.5\n\n### Total Risk Score Calculation\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\n\n### Final Risk Score\n- **Risk Score**: 82 (rounded to nearest whole number)\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\n\n### Conclusion\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n- **Recent Inquiries**: 2\\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- **Repayment Track Record**: Excellent\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding**: 125000\\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\\n\\n### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n### Risk Score Calculation\\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \\n\\n1. **Credit Score**: 720 (weight: 30%) \\u2192 30 * 0.8 = 24\\n2. **Payment History**: 99% on-time (weight: 30%) \\u2192 30 * 0.99 = 29.7\\n3. **Credit Utilization**: 35.5% (weight: 15%) \\u2192 15 * (1 - 0.355) = 9.15\\n4. **Loan Burden Ratio**: 28% (weight: 15%) \\u2192 15 * (1 - 0.28) = 10.2\\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \\u2192 10 * 0.85 = 8.5\\n\\n### Total Risk Score Calculation\\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\\n\\n### Final Risk Score\\n- **Risk Score**: 82 (rounded to nearest whole number)\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\\n\\n### Conclusion\\nThe overall risk score of 82 indicates a moderate risk of default. 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"output": "Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\n\n### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Credit Utilization**: 35.5%\n- **Credit History Length**: 5 years\n- **Recent Inquiries**: 2\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- **Repayment Track Record**: Excellent\n\n### 3. Credit Utilization\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\n\n### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Total Outstanding**: 125000\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\n\n### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n### Risk Score Calculation\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \n\n1. **Credit Score**: 720 (weight: 30%) \u2192 30 * 0.8 = 24\n2. **Payment History**: 99% on-time (weight: 30%) \u2192 30 * 0.99 = 29.7\n3. **Credit Utilization**: 35.5% (weight: 15%) \u2192 15 * (1 - 0.355) = 9.15\n4. **Loan Burden Ratio**: 28% (weight: 15%) \u2192 15 * (1 - 0.28) = 10.2\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \u2192 10 * 0.85 = 8.5\n\n### Total Risk Score Calculation\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\n\n### Final Risk Score\n- **Risk Score**: 82 (rounded to nearest whole number)\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\n\n### Conclusion\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, we will analyze the various factors contributing to the default risk and calculate a risk score.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Credit Utilization**: 35.5%\\n- **Credit History Length**: 5 years\\n- **Recent Inquiries**: 2\\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- **Repayment Track Record**: Excellent\\n\\n### 3. Credit Utilization\\n- **Credit Limit Utilization**: 35.2% (within the acceptable range, typically below 30% is ideal)\\n\\n### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding**: 125000\\n- **Loan Burden Ratio**: 0.28 (28% of income allocated to loan repayments)\\n\\n### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n### Risk Score Calculation\\nBased on the analysis of the above factors, we can assign weights to each component to calculate an overall risk score. \\n\\n1. **Credit Score**: 720 (weight: 30%) \\u2192 30 * 0.8 = 24\\n2. **Payment History**: 99% on-time (weight: 30%) \\u2192 30 * 0.99 = 29.7\\n3. **Credit Utilization**: 35.5% (weight: 15%) \\u2192 15 * (1 - 0.355) = 9.15\\n4. **Loan Burden Ratio**: 28% (weight: 15%) \\u2192 15 * (1 - 0.28) = 10.2\\n5. **Repayment Patterns**: Excellent track record (weight: 10%) \\u2192 10 * 0.85 = 8.5\\n\\n### Total Risk Score Calculation\\nTotal Risk Score = 24 + 29.7 + 9.15 + 10.2 + 8.5 = **81.55**\\n\\n### Final Risk Score\\n- **Risk Score**: 82 (rounded to nearest whole number)\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue to ensure timely payments to maintain the high payment history percentage.\\n2. **Reduce Credit Utilization**: Aim to lower credit utilization below 30% to improve credit score further.\\n3. **Monitor Loan Burden**: Keep an eye on the loan burden ratio; consider paying down existing loans to reduce monthly EMI obligations.\\n4. **Diversify Credit Mix**: Continue to maintain a diverse mix of credit types to enhance credit profile.\\n5. **Avoid New Inquiries**: Limit new credit inquiries to prevent potential negative impacts on the credit score.\\n\\n### Conclusion\\nThe overall risk score of 82 indicates a moderate risk of default. While the applicant has a good credit score and repayment history, the existing loan burden and credit utilization should be managed carefully to mitigate any potential risks in the future.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1877, \"completion_tokens\": 745, \"total_tokens\": 2622, \"estimated_cost\": {\"amount\": 0.000729, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpfflt2smf.py\", line 18, in \u003cmodule\u003e\n \"requested_amount\": UNRESOLVED_loan_amount\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
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"ai_response": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable.\n- **Loan Term**: Not applicable.\n- **Repayment Schedule**: Not applicable.\n\n#### Risk Mitigation Measures:\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\n\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\n\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\n\n#### Confidence Level: 85\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.",
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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable.\n- **Loan Term**: Not applicable.\n- **Repayment Schedule**: Not applicable.\n\n#### Risk Mitigation Measures:\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\n\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\n\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\n\n#### Confidence Level: 85\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable.\\n- **Loan Term**: Not applicable.\\n- **Repayment Schedule**: Not applicable.\\n\\n#### Risk Mitigation Measures:\\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\\n\\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\\n\\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\\n\\n#### Confidence Level: 85\\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6131, \"completion_tokens\": 471, \"total_tokens\": 6602, \"estimated_cost\": {\"amount\": 0.001202, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable.\n- **Loan Term**: Not applicable.\n- **Repayment Schedule**: Not applicable.\n\n#### Risk Mitigation Measures:\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\n\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\n\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\n\n#### Confidence Level: 85\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. Therefore, the decision to decline the application is made with a reasonable level of confidence based on the available information.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable.\\n- **Loan Term**: Not applicable.\\n- **Repayment Schedule**: Not applicable.\\n\\n#### Risk Mitigation Measures:\\n- **Request for Re-Submission**: If the applicant wishes to proceed in the future, they should be advised to re-submit the application with all required documentation and ensure that the application is complete and properly formatted.\\n- **Clear Guidelines**: Provide clear instructions and a checklist for document submission to avoid similar issues in the future.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low (10), indicating significant issues with data extraction and completeness. The unresolved reference to customer information suggests that the application is either incomplete or improperly submitted, making it impossible to assess the applicant\u0027s qualifications accurately.\\n\\n2. **Document Verification**: All required documents (PAN, Aadhaar, Passport, Address Proof) failed verification, resulting in a 0% success rate. The absence of critical identification documents raises serious concerns about the authenticity of the application and the applicant\u0027s identity verification process.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates good financial discipline, the high debt-to-income ratio (85.29%) poses a significant risk. This indicates that a large portion of the applicant\u0027s income is already allocated to debt servicing, which could limit their ability to manage additional loan obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score (720) and an excellent repayment track record. However, the overall risk profile is still concerning due to the high debt burden and the unresolved issues with the application and documentation.\\n\\n5. **Compliance Status**: Although the compliance checks indicate that the organization is compliant with regulations, the lack of proper documentation and verification from the applicant undermines the ability to proceed with the loan.\\n\\n#### Confidence Level: 85\\nWhile there are positive aspects to the applicant\u0027s financial profile, the overwhelming issues with application quality, document verification, and high debt-to-income ratio lead to a high level of uncertainty regarding the applicant\u0027s ability to repay the loan. 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"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmp9oirvh3q.py\", line 11, in \u003cmodule\u003e\n \"loan_amount\": UNRESOLVED_loan_amount,\n ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
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"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpd14uod6l.py\", line 16, in \u003cmodule\u003e\n \"debt_to_income_ratio\": UNRESOLVED_calculate_debt_to_income.debt_to_income_ratio,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_debt_to_income\u0027 is not defined\n",
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"ai_response": "Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true,\n \"stability_score\": 90,\n \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\"\n },\n \"debt_servicing_capability\": {\n \"monthly_debts\": 5800,\n \"monthly_net_income\": 6800,\n \"debt_to_income_ratio\": 85.29,\n \"loan_emis_detected\": 2,\n \"bounced_transactions\": 0,\n \"comments\": \"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\"\n },\n \"financial_discipline_evaluation\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"salary_credits_consistent\": true,\n \"irregular_transactions\": false,\n \"comments\": \"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"High debt-to-income ratio may limit future borrowing capacity.\",\n \"Dependence on salary for debt servicing could be risky if employment status changes.\"\n ],\n \"recommendations\": [\n \"Consider reducing existing debt to improve the debt-to-income ratio.\",\n \"Maintain an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore additional income sources to diversify income streams.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"comments\": \"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true,\n \"stability_score\": 90,\n \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\"\n },\n \"debt_servicing_capability\": {\n \"monthly_debts\": 5800,\n \"monthly_net_income\": 6800,\n \"debt_to_income_ratio\": 85.29,\n \"loan_emis_detected\": 2,\n \"bounced_transactions\": 0,\n \"comments\": \"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\"\n },\n \"financial_discipline_evaluation\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"salary_credits_consistent\": true,\n \"irregular_transactions\": false,\n \"comments\": \"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"High debt-to-income ratio may limit future borrowing capacity.\",\n \"Dependence on salary for debt servicing could be risky if employment status changes.\"\n ],\n \"recommendations\": [\n \"Consider reducing existing debt to improve the debt-to-income ratio.\",\n \"Maintain an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore additional income sources to diversify income streams.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"comments\": \"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true,\\n \\\"stability_score\\\": 90,\\n \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_debts\\\": 5800,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"debt_to_income_ratio\\\": 85.29,\\n \\\"loan_emis_detected\\\": 2,\\n \\\"bounced_transactions\\\": 0,\\n \\\"comments\\\": \\\"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"salary_credits_consistent\\\": true,\\n \\\"irregular_transactions\\\": false,\\n \\\"comments\\\": \\\"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"High debt-to-income ratio may limit future borrowing capacity.\\\",\\n \\\"Dependence on salary for debt servicing could be risky if employment status changes.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Consider reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Maintain an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore additional income sources to diversify income streams.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"comments\\\": \\\"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1299, \"completion_tokens\": 627, \"total_tokens\": 1926, \"estimated_cost\": {\"amount\": 0.000571, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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"output": "Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true,\n \"stability_score\": 90,\n \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\"\n },\n \"debt_servicing_capability\": {\n \"monthly_debts\": 5800,\n \"monthly_net_income\": 6800,\n \"debt_to_income_ratio\": 85.29,\n \"loan_emis_detected\": 2,\n \"bounced_transactions\": 0,\n \"comments\": \"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\"\n },\n \"financial_discipline_evaluation\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"salary_credits_consistent\": true,\n \"irregular_transactions\": false,\n \"comments\": \"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"High debt-to-income ratio may limit future borrowing capacity.\",\n \"Dependence on salary for debt servicing could be risky if employment status changes.\"\n ],\n \"recommendations\": [\n \"Consider reducing existing debt to improve the debt-to-income ratio.\",\n \"Maintain an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore additional income sources to diversify income streams.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"comments\": \"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment of the applicant\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true,\\n \\\"stability_score\\\": 90,\\n \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive trend in income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_debts\\\": 5800,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"debt_to_income_ratio\\\": 85.29,\\n \\\"loan_emis_detected\\\": 2,\\n \\\"bounced_transactions\\\": 0,\\n \\\"comments\\\": \\\"The debt-to-income ratio is high, indicating that a significant portion of the income is allocated to debt servicing. However, there are no bounced transactions, which suggests timely payments.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"salary_credits_consistent\\\": true,\\n \\\"irregular_transactions\\\": false,\\n \\\"comments\\\": \\\"The applicant demonstrates good financial discipline with a high financial discipline score, consistent salary credits, and no irregular transactions.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"High debt-to-income ratio may limit future borrowing capacity.\\\",\\n \\\"Dependence on salary for debt servicing could be risky if employment status changes.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Consider reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Maintain an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore additional income sources to diversify income streams.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"comments\\\": \\\"The applicant has a stable income and demonstrates good financial discipline, but the high debt-to-income ratio poses a risk. Overall, the income is adequate for current obligations but requires careful management to ensure future financial stability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable job with a consistent salary and a recent increment, indicating a positive income trend.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio suggests that a significant portion of income is used for debt servicing, which could be a concern for future borrowing.\\n3. **Financial Discipline Evaluation**: The applicant shows good financial discipline with stable account balances and no irregular transactions.\\n4. **Risk Factors and Recommendations**: The high debt-to-income ratio is a risk factor, and recommendations include reducing debt and maintaining an emergency fund.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally adequate income situation, but with caution advised due to the debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1299, \"completion_tokens\": 627, \"total_tokens\": 1926, \"estimated_cost\": {\"amount\": 0.000571, \"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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"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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},
"geographic_restrictions_met": true,
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"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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"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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},
"identity_verified": true,
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"kyc_status": "compliant",
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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",
"regulatory_requirements_met": true,
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"data_privacy_compliant": true,
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"execution_details": {
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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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"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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"all_conditions_checked": [
{
"condition": "${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50",
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{
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"name": "conditional_approval_path",
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{
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"ocr_extraction_successful": false,
"requested_amount": 0,
"risk_category": "unknown",
"total_processed_documents": 0,
"total_uploaded_documents": 0
},
"execution_details": {
"actual_result": {
"output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\", \"upload_timestamp\": \"2025-07-16T07:50:46.595715\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.684416,
"end_time": "2025-07-16T07:50:46.882828",
"message_sent": true,
"start_time": "2025-07-16T07:50:44.198412",
"timestamp": "2025-07-16T07:50:46.882828",
"worker_executed": true,
"workers_notified": true
},
"file_size_bytes": 2803,
"filename": "loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv",
"output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\", \"upload_timestamp\": \"2025-07-16T07:50:46.595715\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
"public_url": "https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?",
"records_uploaded": 1,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "upload_to_supabase",
"upload_status": "success",
"upload_timestamp": "2025-07-16T07:50:46.595715"
},
"validate_application_fields": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpfjx3sroq.py\", line 8, in \u003cmodule\u003e\n customer_info = UNRESOLVED_extract_application_info.customer_info\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpfjx3sroq.py\", line 8, in \u003cmodule\u003e\n customer_info = UNRESOLVED_extract_application_info.customer_info\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\n",
"status": "FAILED",
"task_id": "validate_application_fields"
},
"verify_aadhaar": {
"aadhaar_masked": "N/A",
"address_match": false,
"address_on_aadhaar": "N/A",
"biometric_verified": false,
"date_of_birth": "N/A",
"document_found": false,
"error": "Aadhaar card not found in uploaded documents",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.505155,
"end_time": "2025-07-16T07:40:49.338406",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.833251",
"timestamp": "2025-07-16T07:40:49.338406",
"worker_executed": true,
"workers_notified": true
},
"extracted_from_ocr": false,
"is_valid": false,
"last_updated": "N/A",
"name_on_aadhaar": "N/A",
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"verification_score": 0.0
},
"verify_address_proof": {
"address_confirmed": "N/A",
"address_match": false,
"document_date": "N/A",
"document_found": false,
"document_type": "N/A",
"error": "Address proof document not found in uploaded documents",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.524456,
"end_time": "2025-07-16T07:40:49.474696",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.950240",
"timestamp": "2025-07-16T07:40:49.474696",
"worker_executed": true,
"workers_notified": true
},
"extracted_from_ocr": false,
"is_valid": false,
"name_on_document": "N/A",
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"total_address_documents": 0,
"verification_score": 0.0
},
"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": 0.246036,
"end_time": "2025-07-16T07:40:57.669843",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.423807",
"timestamp": "2025-07-16T07:40:57.669843",
"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": {
"document_found": false,
"error": "PAN card not found in uploaded documents",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.427276,
"end_time": "2025-07-16T07:40:49.207418",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.780142",
"timestamp": "2025-07-16T07:40:49.207418",
"worker_executed": true,
"workers_notified": true
},
"extracted_from_ocr": false,
"father_name": "N/A",
"is_valid": false,
"name_match": false,
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
"pan_number": "N/A",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"verification_score": 0.0,
"verified_name": "N/A"
},
"verify_passport": {
"document_found": false,
"document_provided": false,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.282198,
"end_time": "2025-07-16T07:40:49.168129",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.885931",
"timestamp": "2025-07-16T07:40:49.168129",
"worker_executed": true,
"workers_notified": true
},
"expiry_date": "N/A",
"extracted_from_ocr": false,
"is_valid": false,
"issuing_authority": "N/A",
"name_on_passport": "N/A",
"note": "Passport not provided - optional document",
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
"passport_number": "N/A",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"verification_score": 0.0
},
"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": 0.315935,
"end_time": "2025-07-16T07:40:57.484536",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.168601",
"timestamp": "2025-07-16T07:40:57.484536",
"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": 0.001109,
"ended_at": "2025-07-16T07:44:33.513588",
"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\": 0.001109, \"started_at\": \"2025-07-16T07:44:33.512479\", \"ended_at\": \"2025-07-16T07:44:33.513588\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.156511,
"end_time": "2025-07-16T07:44:33.577334",
"message_sent": true,
"start_time": "2025-07-16T07:44:33.420823",
"timestamp": "2025-07-16T07:44:33.577334",
"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\": 0.001109, \"started_at\": \"2025-07-16T07:44:33.512479\", \"ended_at\": \"2025-07-16T07:44:33.513588\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-16T07:44:33.512479",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"upload_to_supabase": {
"bucket_name": "loan-approval",
"columns_count": 110,
"csv_structure": {
"column_count": 110,
"columns": [
"processing_timestamp",
"workflow_id",
"workflow_version",
"application_id",
"requested_amount",
"processing_date",
"workflow_status",
"customer_id",
"applicant_name",
"email",
"phone",
"address",
"employment_status",
"annual_income",
"loan_purpose",
"pan_number",
"pan_verified",
"pan_verification_score",
"pan_name_match",
"aadhaar_masked",
"aadhaar_verified",
"aadhaar_verification_score",
"aadhaar_address_match",
"passport_number",
"passport_verified",
"passport_verification_score",
"address_proof_type",
"address_proof_verified",
"address_proof_verification_score",
"total_uploaded_documents",
"total_processed_documents",
"documents_successfully_processed",
"average_ocr_confidence",
"document_types_found",
"ocr_extraction_successful",
"high_confidence_documents",
"low_confidence_documents",
"pan_card_ocr_extracted",
"pan_card_ocr_confidence",
"aadhaar_ocr_extracted",
"aadhaar_ocr_confidence",
"passport_ocr_extracted",
"passport_ocr_confidence",
"address_proof_ocr_extracted",
"address_proof_ocr_confidence",
"monthly_gross_salary",
"monthly_net_salary",
"annual_gross_income",
"annual_net_income",
"employer_name",
"employment_duration",
"salary_consistency",
"recent_increment",
"employment_confirmed",
"designation",
"employment_type",
"job_stability_score",
"average_monthly_credits",
"account_balance_trend",
"minimum_balance",
"maximum_balance",
"bounced_transactions",
"loan_emis_detected",
"financial_discipline_score",
"declared_tax_income",
"tax_paid",
"tax_compliance_score",
"debt_to_income_ratio",
"existing_debt_payments",
"proposed_emi",
"total_debt_payments",
"ratio_acceptable",
"cibil_score",
"credit_score_range",
"credit_history_length",
"total_accounts",
"active_accounts",
"credit_utilization",
"payment_history",
"recent_inquiries",
"internal_credit_score",
"score_acceptable",
"risk_category",
"total_outstanding_loans",
"number_of_existing_loans",
"total_monthly_emi",
"loan_burden_ratio",
"repayment_track_record",
"kyc_status",
"kyc_compliance_score",
"identity_verified",
"address_verified",
"income_verified",
"documents_complete",
"aml_status",
"aml_compliance_score",
"watchlist_check",
"pep_screening",
"sanctions_check",
"manual_review_required",
"rbi_guidelines_met",
"lending_norms_compliant",
"regulatory_compliance_score",
"internal_policy_compliance_score",
"final_decision",
"decision_confidence",
"overall_processing_status",
"processing_time_minutes",
"processed_by",
"processing_node"
],
"key_metrics": {
"aml_cleared": false,
"avg_ocr_confidence": 0.0,
"cibil_score": 0,
"credit_score": 0,
"documents_processed": 0,
"documents_uploaded": 0,
"kyc_compliant": false,
"ocr_successful": false,
"ratio_acceptable": false,
"risk_category": "unknown"
},
"row_count": 1
},
"data_summary": {
"applicant_name": "Unknown Applicant",
"application_id": "UNRESOLVED_application_id",
"average_ocr_confidence": 0.0,
"cibil_score": 0,
"debt_to_income_ratio": 0,
"final_decision": "PENDING",
"internal_credit_score": 0,
"ocr_extraction_successful": false,
"requested_amount": 0,
"risk_category": "unknown",
"total_processed_documents": 0,
"total_uploaded_documents": 0
},
"execution_details": {
"actual_result": {
"output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\", \"upload_timestamp\": \"2025-07-16T07:50:46.595715\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.684416,
"end_time": "2025-07-16T07:50:46.882828",
"message_sent": true,
"start_time": "2025-07-16T07:50:44.198412",
"timestamp": "2025-07-16T07:50:46.882828",
"worker_executed": true,
"workers_notified": true
},
"file_size_bytes": 2803,
"filename": "loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv",
"output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?\", \"upload_timestamp\": \"2025-07-16T07:50:46.595715\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
"public_url": "https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_075045.csv?",
"records_uploaded": 1,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "upload_to_supabase",
"upload_status": "success",
"upload_timestamp": "2025-07-16T07:50:46.595715"
},
"validate_application_fields": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpfjx3sroq.py\", line 8, in \u003cmodule\u003e\n customer_info = UNRESOLVED_extract_application_info.customer_info\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\n",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpfjx3sroq.py\", line 8, in \u003cmodule\u003e\n customer_info = UNRESOLVED_extract_application_info.customer_info\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\n",
"status": "FAILED",
"task_id": "validate_application_fields"
},
"verify_aadhaar": {
"aadhaar_masked": "N/A",
"address_match": false,
"address_on_aadhaar": "N/A",
"biometric_verified": false,
"date_of_birth": "N/A",
"document_found": false,
"error": "Aadhaar card not found in uploaded documents",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.505155,
"end_time": "2025-07-16T07:40:49.338406",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.833251",
"timestamp": "2025-07-16T07:40:49.338406",
"worker_executed": true,
"workers_notified": true
},
"extracted_from_ocr": false,
"is_valid": false,
"last_updated": "N/A",
"name_on_aadhaar": "N/A",
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"verification_score": 0.0
},
"verify_address_proof": {
"address_confirmed": "N/A",
"address_match": false,
"document_date": "N/A",
"document_found": false,
"document_type": "N/A",
"error": "Address proof document not found in uploaded documents",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.524456,
"end_time": "2025-07-16T07:40:49.474696",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.950240",
"timestamp": "2025-07-16T07:40:49.474696",
"worker_executed": true,
"workers_notified": true
},
"extracted_from_ocr": false,
"is_valid": false,
"name_on_document": "N/A",
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"total_address_documents": 0,
"verification_score": 0.0
},
"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": 0.246036,
"end_time": "2025-07-16T07:40:57.669843",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.423807",
"timestamp": "2025-07-16T07:40:57.669843",
"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": {
"document_found": false,
"error": "PAN card not found in uploaded documents",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.427276,
"end_time": "2025-07-16T07:40:49.207418",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.780142",
"timestamp": "2025-07-16T07:40:49.207418",
"worker_executed": true,
"workers_notified": true
},
"extracted_from_ocr": false,
"father_name": "N/A",
"is_valid": false,
"name_match": false,
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
"pan_number": "N/A",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"verification_score": 0.0,
"verified_name": "N/A"
},
"verify_passport": {
"document_found": false,
"document_provided": false,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.282198,
"end_time": "2025-07-16T07:40:49.168129",
"message_sent": true,
"start_time": "2025-07-16T07:40:48.885931",
"timestamp": "2025-07-16T07:40:49.168129",
"worker_executed": true,
"workers_notified": true
},
"expiry_date": "N/A",
"extracted_from_ocr": false,
"is_valid": false,
"issuing_authority": "N/A",
"name_on_passport": "N/A",
"note": "Passport not provided - optional document",
"ocr_confidence": 0.0,
"output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
"passport_number": "N/A",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"verification_score": 0.0
},
"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": 0.315935,
"end_time": "2025-07-16T07:40:57.484536",
"message_sent": true,
"start_time": "2025-07-16T07:40:57.168601",
"timestamp": "2025-07-16T07:40:57.484536",
"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
}
}