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": 0.329191,
"end_time": "2025-07-15T11:38:42.381741",
"message_sent": true,
"start_time": "2025-07-15T11:38:42.052550",
"timestamp": "2025-07-15T11:38:42.381741",
"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": 0.383728,
"end_time": "2025-07-15T11:35:22.476068",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.092340",
"timestamp": "2025-07-15T11:35:22.476068",
"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": 0.239626,
"end_time": "2025-07-15T11:35:29.095393",
"message_sent": true,
"start_time": "2025-07-15T11:35:28.855767",
"timestamp": "2025-07-15T11:35:29.095393",
"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": 0.331802,
"end_time": "2025-07-15T11:35:22.383312",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.051510",
"timestamp": "2025-07-15T11:35:22.383312",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1030,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.28417,
"end_time": "2025-07-15T11:35:19.597430",
"message_sent": true,
"start_time": "2025-07-15T11:35:15.313260",
"timestamp": "2025-07-15T11:35:19.597430",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "application_quality_check"
},
"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": 0.266684,
"end_time": "2025-07-15T11:35:29.321376",
"message_sent": true,
"start_time": "2025-07-15T11:35:29.054692",
"timestamp": "2025-07-15T11:35:29.321376",
"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": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpsjqeb70n.py\", line 9, in \u003cmodule\u003e\n cibil_score = UNRESOLVED_check_cibil_score.credit_score\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\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/tmpsjqeb70n.py\", line 9, in \u003cmodule\u003e\n cibil_score = UNRESOLVED_check_cibil_score.credit_score\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"debt_to_income_ratio": 0.3590686274509804,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.426728,
"end_time": "2025-07-15T11:35:23.089271",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.662543",
"timestamp": "2025-07-15T11:35:23.089271",
"worker_executed": true,
"workers_notified": true
},
"existing_debt_payments": 2400,
"max_allowed_ratio": 0.4,
"monthly_net_income": 6800,
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 41.666666666666664,
"ratio_acceptable": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2441.6666666666665
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.188109,
"end_time": "2025-07-15T11:35:28.826383",
"message_sent": true,
"start_time": "2025-07-15T11:35:28.638274",
"timestamp": "2025-07-15T11:35:28.826383",
"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": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\",\n \"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1161,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\",\n \"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\\\",\\n \\\"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 3.890347,
"end_time": "2025-07-15T11:38:46.838342",
"message_sent": true,
"start_time": "2025-07-15T11:38:42.947995",
"timestamp": "2025-07-15T11:38:46.838342",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\",\n \"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\\\",\\n \\\"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 309,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.435097,
"end_time": "2025-07-15T11:35:22.737431",
"message_sent": true,
"start_time": "2025-07-15T11:35:20.302334",
"timestamp": "2025-07-15T11:35:22.737431",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\n\n### 4. Existing Loan Burden\n- **Outstanding Loans**: The borrower has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n \n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\n\n### Risk Score Calculation\nBased on the available information:\n- **Credit Score**: Unknown (assumed neutral for calculation)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering these factors, we can assign a risk score:\n- Excellent repayment track record: -10 points\n- Manageable loan burden ratio: -10 points\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\n\n### Final Risk Score\n- **Risk Score**: 50/100\n\n### Recommendations\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\n\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
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"agent_type": "assistant",
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"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are 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"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\n\n### 4. Existing Loan Burden\n- **Outstanding Loans**: The borrower has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n \n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\n\n### Risk Score Calculation\nBased on the available information:\n- **Credit Score**: Unknown (assumed neutral for calculation)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering these factors, we can assign a risk score:\n- Excellent repayment track record: -10 points\n- Manageable loan burden ratio: -10 points\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\n\n### Final Risk Score\n- **Risk Score**: 50/100\n\n### Recommendations\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\n\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\\n\\n### 4. Existing Loan Burden\\n- **Outstanding Loans**: The borrower has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n \\n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\\n\\n### Risk Score Calculation\\nBased on the available information:\\n- **Credit Score**: Unknown (assumed neutral for calculation)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering these factors, we can assign a risk score:\\n- Excellent repayment track record: -10 points\\n- Manageable loan burden ratio: -10 points\\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\\n\\n### Final Risk Score\\n- **Risk Score**: 50/100\\n\\n### Recommendations\\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\\n\\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 14.295309,
"end_time": "2025-07-15T11:35:43.577940",
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"start_time": "2025-07-15T11:35:29.282631",
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"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\n\n### 4. Existing Loan Burden\n- **Outstanding Loans**: The borrower has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n \n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\n\n### Risk Score Calculation\nBased on the available information:\n- **Credit Score**: Unknown (assumed neutral for calculation)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering these factors, we can assign a risk score:\n- Excellent repayment track record: -10 points\n- Manageable loan burden ratio: -10 points\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\n\n### Final Risk Score\n- **Risk Score**: 50/100\n\n### Recommendations\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\n\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\\n\\n### 4. Existing Loan Burden\\n- **Outstanding Loans**: The borrower has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n \\n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\\n\\n### Risk Score Calculation\\nBased on the available information:\\n- **Credit Score**: Unknown (assumed neutral for calculation)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering these factors, we can assign a risk score:\\n- Excellent repayment track record: -10 points\\n- Manageable loan burden ratio: -10 points\\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\\n\\n### Final Risk Score\\n- **Risk Score**: 50/100\\n\\n### Recommendations\\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\\n\\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
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"stderr": "",
"task_id": "evaluate_default_risk"
},
"execution_summary": {
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},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.269278,
"end_time": "2025-07-15T11:35:15.065262",
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"timestamp": "2025-07-15T11:35:15.065262",
"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "extract_application_info"
},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\n \n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\n \n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\n \n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\n \n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\n \n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.",
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"provider": "openai",
"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"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\n \n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\n \n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\n \n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\n \n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\n \n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\\n \\n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\\n \\n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\\n \\n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\\n \\n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\\n \\n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\\n \\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\n \n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\n \n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\n \n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\n \n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\n \n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\\n \\n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\\n \\n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\\n \\n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\\n \\n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\\n \\n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\\n \\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"max_allowed_ratio\": 0.4,\n \"proposed_emi\": 41.67,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but implied stability suggests good financial management.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"job stability\": \"High\",\n \"debt servicing capability\": \"Strong\",\n \"potential risks\": [\n \"Economic downturn affecting job security\",\n \"Unexpected expenses not accounted for in current debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Continue monitoring debt levels and aim to reduce existing debt.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```",
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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": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"max_allowed_ratio\": 0.4,\n \"proposed_emi\": 41.67,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but implied stability suggests good financial management.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"job stability\": \"High\",\n \"debt servicing capability\": \"Strong\",\n \"potential risks\": [\n \"Economic downturn affecting job security\",\n \"Unexpected expenses not accounted for in current debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Continue monitoring debt levels and aim to reduce existing debt.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but implied stability suggests good financial management.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"job stability\\\": \\\"High\\\",\\n \\\"debt servicing capability\\\": \\\"Strong\\\",\\n \\\"potential risks\\\": [\\n \\\"Economic downturn affecting job security\\\",\\n \\\"Unexpected expenses not accounted for in current debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Continue monitoring debt levels and aim to reduce existing debt.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"max_allowed_ratio\": 0.4,\n \"proposed_emi\": 41.67,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but implied stability suggests good financial management.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"job stability\": \"High\",\n \"debt servicing capability\": \"Strong\",\n \"potential risks\": [\n \"Economic downturn affecting job security\",\n \"Unexpected expenses not accounted for in current debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Continue monitoring debt levels and aim to reduce existing debt.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but implied stability suggests good financial management.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"job stability\\\": \\\"High\\\",\\n \\\"debt servicing capability\\\": \\\"Strong\\\",\\n \\\"potential risks\\\": [\\n \\\"Economic downturn affecting job security\\\",\\n \\\"Unexpected expenses not accounted for in current debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Continue monitoring debt levels and aim to reduce existing debt.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "__OUTPUTS__ {\"average_monthly_credits\": 7200, \"salary_credits_consistent\": true, \"account_balance_trend\": \"stable\", \"minimum_balance\": 15000, \"maximum_balance\": 45000, \"bounced_transactions\": 0, \"loan_emis_detected\": 2, \"total_monthly_debits\": 5800, \"financial_discipline_score\": 85.5, \"irregular_transactions\": false}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.383728,
"end_time": "2025-07-15T11:35:22.476068",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.092340",
"timestamp": "2025-07-15T11:35:22.476068",
"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": 0.239626,
"end_time": "2025-07-15T11:35:29.095393",
"message_sent": true,
"start_time": "2025-07-15T11:35:28.855767",
"timestamp": "2025-07-15T11:35:29.095393",
"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": 0.331802,
"end_time": "2025-07-15T11:35:22.383312",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.051510",
"timestamp": "2025-07-15T11:35:22.383312",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1030,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.28417,
"end_time": "2025-07-15T11:35:19.597430",
"message_sent": true,
"start_time": "2025-07-15T11:35:15.313260",
"timestamp": "2025-07-15T11:35:19.597430",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application is complete with no missing fields, indicating a high level of accuracy in the provided information.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details about the specific data points would be needed to assess consistency thoroughly.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. The application seems to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be awarded. A score of 95 reflects the high quality of the application.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "application_quality_check"
},
"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": 0.266684,
"end_time": "2025-07-15T11:35:29.321376",
"message_sent": true,
"start_time": "2025-07-15T11:35:29.054692",
"timestamp": "2025-07-15T11:35:29.321376",
"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": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpsjqeb70n.py\", line 9, in \u003cmodule\u003e\n cibil_score = UNRESOLVED_check_cibil_score.credit_score\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\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/tmpsjqeb70n.py\", line 9, in \u003cmodule\u003e\n cibil_score = UNRESOLVED_check_cibil_score.credit_score\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"debt_to_income_ratio": 0.3590686274509804,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.426728,
"end_time": "2025-07-15T11:35:23.089271",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.662543",
"timestamp": "2025-07-15T11:35:23.089271",
"worker_executed": true,
"workers_notified": true
},
"existing_debt_payments": 2400,
"max_allowed_ratio": 0.4,
"monthly_net_income": 6800,
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 41.666666666666664,
"ratio_acceptable": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2441.6666666666665
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.188109,
"end_time": "2025-07-15T11:35:28.826383",
"message_sent": true,
"start_time": "2025-07-15T11:35:28.638274",
"timestamp": "2025-07-15T11:35:28.826383",
"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": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\",\n \"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1161,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\",\n \"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\\\",\\n \\\"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 3.890347,
"end_time": "2025-07-15T11:38:46.838342",
"message_sent": true,
"start_time": "2025-07-15T11:38:42.947995",
"timestamp": "2025-07-15T11:38:46.838342",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\",\n \"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Immediately address and resolve the KYC compliance check to mitigate identity fraud risk.\\\",\\n \\\"Conduct a thorough review and resolution of the AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve any outstanding regulatory compliance issues to avoid potential legal repercussions.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 309,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.435097,
"end_time": "2025-07-15T11:35:22.737431",
"message_sent": true,
"start_time": "2025-07-15T11:35:20.302334",
"timestamp": "2025-07-15T11:35:22.737431",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\n\n### 4. Existing Loan Burden\n- **Outstanding Loans**: The borrower has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n \n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\n\n### Risk Score Calculation\nBased on the available information:\n- **Credit Score**: Unknown (assumed neutral for calculation)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering these factors, we can assign a risk score:\n- Excellent repayment track record: -10 points\n- Manageable loan burden ratio: -10 points\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\n\n### Final Risk Score\n- **Risk Score**: 50/100\n\n### Recommendations\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\n\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 561,
"model": "gpt-4o-mini",
"output_length": 3346,
"provider": "openai",
"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"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\n\n### 4. Existing Loan Burden\n- **Outstanding Loans**: The borrower has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n \n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\n\n### Risk Score Calculation\nBased on the available information:\n- **Credit Score**: Unknown (assumed neutral for calculation)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering these factors, we can assign a risk score:\n- Excellent repayment track record: -10 points\n- Manageable loan burden ratio: -10 points\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\n\n### Final Risk Score\n- **Risk Score**: 50/100\n\n### Recommendations\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\n\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\\n\\n### 4. Existing Loan Burden\\n- **Outstanding Loans**: The borrower has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n \\n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\\n\\n### Risk Score Calculation\\nBased on the available information:\\n- **Credit Score**: Unknown (assumed neutral for calculation)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering these factors, we can assign a risk score:\\n- Excellent repayment track record: -10 points\\n- Manageable loan burden ratio: -10 points\\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\\n\\n### Final Risk Score\\n- **Risk Score**: 50/100\\n\\n### Recommendations\\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\\n\\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 14.295309,
"end_time": "2025-07-15T11:35:43.577940",
"message_sent": true,
"start_time": "2025-07-15T11:35:29.282631",
"timestamp": "2025-07-15T11:35:43.577940",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\n\n### 4. Existing Loan Burden\n- **Outstanding Loans**: The borrower has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n \n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\n\n### Risk Score Calculation\nBased on the available information:\n- **Credit Score**: Unknown (assumed neutral for calculation)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering these factors, we can assign a risk score:\n- Excellent repayment track record: -10 points\n- Manageable loan burden ratio: -10 points\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\n\n### Final Risk Score\n- **Risk Score**: 50/100\n\n### Recommendations\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\n\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key factors mentioned and assign a risk score based on the information provided.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this critical factor. A low score would typically indicate higher risk, while a high score would indicate lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the borrower\u0027s past behavior regarding credit usage and repayment.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This suggests that the borrower has consistently made timely payments on their loans, which is a positive indicator of creditworthiness.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which indicates that 28% of the borrower\u0027s income is going towards loan repayments. This is generally considered a manageable level, as a ratio below 30% is often viewed as acceptable.\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is a significant amount but manageable given the loan burden ratio.\\n\\n### 4. Existing Loan Burden\\n- **Outstanding Loans**: The borrower has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n \\n The total outstanding amount is 125000, which is a considerable sum, but the borrower has an excellent repayment track record.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be favorable. However, the lack of information on the CIBIL score and credit history limits our ability to fully assess the risk.\\n\\n### Risk Score Calculation\\nBased on the available information:\\n- **Credit Score**: Unknown (assumed neutral for calculation)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering these factors, we can assign a risk score:\\n- Excellent repayment track record: -10 points\\n- Manageable loan burden ratio: -10 points\\n- Unknown credit score and history: +30 points (assumed higher risk due to lack of information)\\n\\n### Final Risk Score\\n- **Risk Score**: 50/100\\n\\n### Recommendations\\n1. **Resolve Credit Score and History**: The borrower should check their CIBIL score and credit history to understand their creditworthiness better. This information is crucial for a complete risk assessment.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments on existing loans to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure continued creditworthiness.\\n4. **Consider Future Borrowing**: If the borrower plans to take on additional loans, they should ensure that their total EMIs remain manageable relative to their income.\\n\\nOverall, while the current risk score is moderate, resolving the unknowns related to the credit score and history will provide a clearer picture of the borrower\u0027s credit risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "evaluate_default_risk"
},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.269278,
"end_time": "2025-07-15T11:35:15.065262",
"message_sent": true,
"start_time": "2025-07-15T11:35:14.795984",
"timestamp": "2025-07-15T11:35:15.065262",
"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "extract_application_info"
},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\n \n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\n \n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\n \n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\n \n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\n \n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.",
"execution_details": {
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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"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\n \n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\n \n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\n \n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\n \n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\n \n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\\n \\n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\\n \\n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\\n \\n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\\n \\n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\\n \\n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\\n \\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"status": "completed",
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},
"duration_seconds": 7.017579,
"end_time": "2025-07-15T11:38:53.771963",
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"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\n \n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\n \n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\n \n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\n \n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\n \n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\\n \\n - **Document Verification**: The unresolved document verification suggests that the necessary documentation has not been adequately verified. This lack of verification prevents us from confirming the applicant\u0027s financial standing and identity, which is crucial for making an informed lending decision.\\n \\n - **Income Assessment**: An unresolved income assessment means we cannot ascertain the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in evaluating loan eligibility.\\n \\n - **Credit Score**: Without a calculated credit score, we cannot assess the applicant\u0027s creditworthiness. A strong credit score is typically a key indicator of an applicant\u0027s likelihood to repay their debts.\\n \\n - **Default Risk**: The unresolved evaluation of default risk means we lack a clear understanding of the potential risk associated with lending to this applicant. This uncertainty is unacceptable in the underwriting process.\\n \\n - **Compliance**: Unresolved compliance issues indicate that there may be regulatory or legal concerns that have not been addressed, which could expose the lending institution to potential liabilities.\\n \\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of this application is too high to proceed with approval. The lack of clarity and verification across all critical areas makes it impossible to justify lending to this applicant at this time.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and significant concerns raised by the unresolved assessments, which collectively indicate a high risk of default and compliance issues.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmponi0lbjh.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
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"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmponi0lbjh.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "generate_final_output"
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"income_assessment": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"max_allowed_ratio\": 0.4,\n \"proposed_emi\": 41.67,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but implied stability suggests good financial management.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"job stability\": \"High\",\n \"debt servicing capability\": \"Strong\",\n \"potential risks\": [\n \"Economic downturn affecting job security\",\n \"Unexpected expenses not accounted for in current debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Continue monitoring debt levels and aim to reduce existing debt.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```",
"execution_details": {
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"agent_type": "assistant",
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"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are 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"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"max_allowed_ratio\": 0.4,\n \"proposed_emi\": 41.67,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but implied stability suggests good financial management.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"job stability\": \"High\",\n \"debt servicing capability\": \"Strong\",\n \"potential risks\": [\n \"Economic downturn affecting job security\",\n \"Unexpected expenses not accounted for in current debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Continue monitoring debt levels and aim to reduce existing debt.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but implied stability suggests good financial management.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"job stability\\\": \\\"High\\\",\\n \\\"debt servicing capability\\\": \\\"Strong\\\",\\n \\\"potential risks\\\": [\\n \\\"Economic downturn affecting job security\\\",\\n \\\"Unexpected expenses not accounted for in current debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Continue monitoring debt levels and aim to reduce existing debt.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
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"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"max_allowed_ratio\": 0.4,\n \"proposed_emi\": 41.67,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but implied stability suggests good financial management.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"job stability\": \"High\",\n \"debt servicing capability\": \"Strong\",\n \"potential risks\": [\n \"Economic downturn affecting job security\",\n \"Unexpected expenses not accounted for in current debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Continue monitoring debt levels and aim to reduce existing debt.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but implied stability suggests good financial management.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"job stability\\\": \\\"High\\\",\\n \\\"debt servicing capability\\\": \\\"Strong\\\",\\n \\\"potential risks\\\": [\\n \\\"Economic downturn affecting job security\\\",\\n \\\"Unexpected expenses not accounted for in current debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Continue monitoring debt levels and aim to reduce existing debt.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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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,
"income_criteria_met": true,
"loan_amount_within_limits": true,
"ltv_ratio_acceptable": true,
"output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
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"compliance_score": 98.5,
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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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"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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{
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{
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{
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"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"verification_score": 98.2
},
"verify_address_proof": {
"address_confirmed": "123 Main St, City, State 12345",
"address_match": true,
"document_date": "2024-06-15",
"document_type": "utility_bill",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.862857,
"end_time": "2025-07-15T11:35:20.419559",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.556702",
"timestamp": "2025-07-15T11:35:20.419559",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"verification_score": 92.3
},
"verify_employment": {
"designation": "Senior Software Engineer",
"employer_rating": "A+",
"employment_confirmed": true,
"employment_type": "permanent",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.494969,
"end_time": "2025-07-15T11:35:22.822098",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.327129",
"timestamp": "2025-07-15T11:35:22.822098",
"worker_executed": true,
"workers_notified": true
},
"hr_contact_verified": true,
"job_stability_score": 88.5,
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"probation_status": "confirmed",
"reference_check_passed": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_employment"
},
"verify_pan_card": {
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.345983,
"end_time": "2025-07-15T11:35:19.780878",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.434895",
"timestamp": "2025-07-15T11:35:19.780878",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"name_match": true,
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"pan_number": "ABCDE1234F",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"verification_score": 95.5,
"verified_name": "JOHN DOE"
},
"verify_passport": {
"document_provided": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.853221,
"end_time": "2025-07-15T11:35:20.367685",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.514464",
"timestamp": "2025-07-15T11:35:20.367685",
"worker_executed": true,
"workers_notified": true
},
"expiry_date": "2030-12-31",
"is_valid": true,
"issuing_authority": "Government of India",
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"passport_number": "A1234567",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"verification_score": 96.8
},
"verify_tax_returns": {
"declared_income": 98000,
"discrepancies_found": false,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.657797,
"end_time": "2025-07-15T11:35:22.789965",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.132168",
"timestamp": "2025-07-15T11:35:22.789965",
"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": 0.000986,
"ended_at": "2025-07-15T11:38:46.653958",
"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\": 0.000986, \"started_at\": \"2025-07-15T11:38:46.652972\", \"ended_at\": \"2025-07-15T11:38:46.653958\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.246825,
"end_time": "2025-07-15T11:38:46.800141",
"message_sent": true,
"start_time": "2025-07-15T11:38:46.553316",
"timestamp": "2025-07-15T11:38:46.800141",
"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\": 0.000986, \"started_at\": \"2025-07-15T11:38:46.652972\", \"ended_at\": \"2025-07-15T11:38:46.653958\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T11:38:46.652972",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"validate_application_fields": {
"completion_percentage": 100.0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.198066,
"end_time": "2025-07-15T11:35:15.290665",
"message_sent": true,
"start_time": "2025-07-15T11:35:15.092599",
"timestamp": "2025-07-15T11:35:15.290665",
"worker_executed": true,
"workers_notified": true
},
"missing_fields": [],
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "validate_application_fields",
"validation_passed": true
},
"verify_aadhaar": {
"aadhaar_masked": "1234-5678-9012",
"address_match": true,
"biometric_verified": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.469658,
"end_time": "2025-07-15T11:35:19.944449",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.474791",
"timestamp": "2025-07-15T11:35:19.944449",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"last_updated": "2024-01-15",
"output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_aadhaar",
"verification_score": 98.2
},
"verify_address_proof": {
"address_confirmed": "123 Main St, City, State 12345",
"address_match": true,
"document_date": "2024-06-15",
"document_type": "utility_bill",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.862857,
"end_time": "2025-07-15T11:35:20.419559",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.556702",
"timestamp": "2025-07-15T11:35:20.419559",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_address_proof",
"verification_score": 92.3
},
"verify_employment": {
"designation": "Senior Software Engineer",
"employer_rating": "A+",
"employment_confirmed": true,
"employment_type": "permanent",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.494969,
"end_time": "2025-07-15T11:35:22.822098",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.327129",
"timestamp": "2025-07-15T11:35:22.822098",
"worker_executed": true,
"workers_notified": true
},
"hr_contact_verified": true,
"job_stability_score": 88.5,
"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"probation_status": "confirmed",
"reference_check_passed": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_employment"
},
"verify_pan_card": {
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.345983,
"end_time": "2025-07-15T11:35:19.780878",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.434895",
"timestamp": "2025-07-15T11:35:19.780878",
"worker_executed": true,
"workers_notified": true
},
"is_valid": true,
"name_match": true,
"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"pan_number": "ABCDE1234F",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_pan_card",
"verification_score": 95.5,
"verified_name": "JOHN DOE"
},
"verify_passport": {
"document_provided": true,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.853221,
"end_time": "2025-07-15T11:35:20.367685",
"message_sent": true,
"start_time": "2025-07-15T11:35:19.514464",
"timestamp": "2025-07-15T11:35:20.367685",
"worker_executed": true,
"workers_notified": true
},
"expiry_date": "2030-12-31",
"is_valid": true,
"issuing_authority": "Government of India",
"output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
"passport_number": "A1234567",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "verify_passport",
"verification_score": 96.8
},
"verify_tax_returns": {
"declared_income": 98000,
"discrepancies_found": false,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.657797,
"end_time": "2025-07-15T11:35:22.789965",
"message_sent": true,
"start_time": "2025-07-15T11:35:22.132168",
"timestamp": "2025-07-15T11:35:22.789965",
"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
}
}