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": 0.319562,
"end_time": "2025-07-15T11:14:41.998238",
"message_sent": true,
"start_time": "2025-07-15T11:14:41.678676",
"timestamp": "2025-07-15T11:14:41.998238",
"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": 0.959722,
"end_time": "2025-07-15T11:11:21.944444",
"message_sent": true,
"start_time": "2025-07-15T11:11:20.984722",
"timestamp": "2025-07-15T11:11:21.944444",
"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": 0.277135,
"end_time": "2025-07-15T11:11:28.446335",
"message_sent": true,
"start_time": "2025-07-15T11:11:28.169200",
"timestamp": "2025-07-15T11:11:28.446335",
"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": 0.516462,
"end_time": "2025-07-15T11:11:21.457794",
"message_sent": true,
"start_time": "2025-07-15T11:11:20.941332",
"timestamp": "2025-07-15T11:11:21.457794",
"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\": \"All required fields are present and validated successfully. The application is complete and accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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": 1009,
"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\": \"All required fields are present and validated successfully. The application is complete and accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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\\\": \\\"All required fields are present and validated successfully. The application is complete and accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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": 5.045226,
"end_time": "2025-07-15T11:11:19.261675",
"message_sent": true,
"start_time": "2025-07-15T11:11:14.216449",
"timestamp": "2025-07-15T11:11:19.261675",
"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\": \"All required fields are present and validated successfully. The application is complete and accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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\\\": \\\"All required fields are present and validated successfully. The application is complete and accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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": 0.347074,
"end_time": "2025-07-15T11:11:28.745806",
"message_sent": true,
"start_time": "2025-07-15T11:11:28.398732",
"timestamp": "2025-07-15T11:11:28.745806",
"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/tmppa708vgv.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/tmppa708vgv.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": 0.4142156862745098,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.40155,
"end_time": "2025-07-15T11:11:22.227144",
"message_sent": true,
"start_time": "2025-07-15T11:11:21.825594",
"timestamp": "2025-07-15T11:11:22.227144",
"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\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 416.6666666666667,
"ratio_acceptable": false,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2816.6666666666665
},
"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": 0.265386,
"end_time": "2025-07-15T11:11:28.140661",
"message_sent": true,
"start_time": "2025-07-15T11:11:27.875275",
"timestamp": "2025-07-15T11:11:28.140661",
"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 \"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\",\n \"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve the 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": 1125,
"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 \"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\",\n \"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve the 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 \\\"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\\\",\\n \\\"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve the 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": 4.592061,
"end_time": "2025-07-15T11:14:47.123147",
"message_sent": true,
"start_time": "2025-07-15T11:14:42.531086",
"timestamp": "2025-07-15T11:14:47.123147",
"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 \"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\",\n \"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve the 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 \\\"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\\\",\\n \\\"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve the 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 and consistent information. 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": 336,
"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 and consistent information. 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 and consistent information. 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": 1.989276,
"end_time": "2025-07-15T11:11:21.152256",
"message_sent": true,
"start_time": "2025-07-15T11:11:19.162980",
"timestamp": "2025-07-15T11:11:21.152256",
"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 and consistent information. 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 and consistent information. 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 various factors mentioned and assign a risk score based on the overall assessment.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score.\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\n- **Credit History**: Excellent - 10 points\n- **Repayment Patterns**: Excellent - 5 points\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\n- **Existing Loan Burden**: Manageable - 10 points\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\n\n### Total Risk Score\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\n\n### Risk Score\n- **Risk Score**: 65 out of 100\n\n### Recommendations\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\n\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.",
"execution_details": {
"actual_result": {
"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 various factors mentioned and assign a risk score based on the overall assessment.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score.\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\n- **Credit History**: Excellent - 10 points\n- **Repayment Patterns**: Excellent - 5 points\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\n- **Existing Loan Burden**: Manageable - 10 points\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\n\n### Total Risk Score\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\n\n### Risk Score\n- **Risk Score**: 65 out of 100\n\n### Recommendations\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\n\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the overall assessment.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score.\\\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\\n- **Credit History**: Excellent - 10 points\\n- **Repayment Patterns**: Excellent - 5 points\\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\\n- **Existing Loan Burden**: Manageable - 10 points\\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\\n\\n### Total Risk Score\\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\\n\\n### Risk Score\\n- **Risk Score**: 65 out of 100\\n\\n### Recommendations\\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\\n\\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this 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": 13.724898,
"end_time": "2025-07-15T11:11:42.416706",
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"start_time": "2025-07-15T11:11:28.691808",
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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 various factors mentioned and assign a risk score based on the overall assessment.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score.\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\n- **Credit History**: Excellent - 10 points\n- **Repayment Patterns**: Excellent - 5 points\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\n- **Existing Loan Burden**: Manageable - 10 points\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\n\n### Total Risk Score\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\n\n### Risk Score\n- **Risk Score**: 65 out of 100\n\n### Recommendations\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\n\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the overall assessment.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score.\\\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\\n- **Credit History**: Excellent - 10 points\\n- **Repayment Patterns**: Excellent - 5 points\\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\\n- **Existing Loan Burden**: Manageable - 10 points\\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\\n\\n### Total Risk Score\\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\\n\\n### Risk Score\\n- **Risk Score**: 65 out of 100\\n\\n### Recommendations\\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\\n\\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
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},
"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": 100000
},
"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\": 100000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.274911,
"end_time": "2025-07-15T11:11:14.000762",
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"start_time": "2025-07-15T11:11:13.725851",
"timestamp": "2025-07-15T11:11:14.000762",
"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\": 100000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
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},
"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:**\n - The application has multiple unresolved issues, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. \n - Each of these unresolved areas represents a significant risk factor that could lead to potential losses for the lending institution. Without clear and verified information in these critical areas, it is impossible to assess the borrower\u0027s ability to repay the loan or their overall creditworthiness.\n - The lack of resolution in these areas indicates that the application does not meet the necessary standards for approval, as it fails to provide a comprehensive and reliable picture of the applicant\u0027s financial situation.\n\n5. **Confidence Level:** 95\n - Given the high number of unresolved issues, there is a strong confidence level in the decision to decline the application. The absence of verified information creates a substantial risk that cannot be overlooked.",
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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"
},
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"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employment_verified\": true\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2816.67,\n \"proposed_emi\": 416.67,\n \"debt_to_income_ratio\": 0.4142,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": false,\n \"assessment\": \"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\"\n },\n \"risk_factors\": {\n \"over_leverage\": {\n \"description\": \"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\",\n \"recommendation\": \"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\"\n },\n \"income_sources\": {\n \"description\": \"Reliance on a single income source may pose a risk if employment status changes.\",\n \"recommendation\": \"Explore additional income streams or savings to mitigate risks associated with job loss.\"\n }\n },\n \"overall_income_adequacy_score\": 65,\n \"recommendations\": [\n \"Focus on reducing existing debt to improve the debt-to-income ratio.\",\n \"Consider building an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore opportunities for salary increases or additional income sources to enhance financial stability.\"\n ]\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\": \"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employment_verified\": true\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2816.67,\n \"proposed_emi\": 416.67,\n \"debt_to_income_ratio\": 0.4142,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": false,\n \"assessment\": \"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\"\n },\n \"risk_factors\": {\n \"over_leverage\": {\n \"description\": \"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\",\n \"recommendation\": \"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\"\n },\n \"income_sources\": {\n \"description\": \"Reliance on a single income source may pose a risk if employment status changes.\",\n \"recommendation\": \"Explore additional income streams or savings to mitigate risks associated with job loss.\"\n }\n },\n \"overall_income_adequacy_score\": 65,\n \"recommendations\": [\n \"Focus on reducing existing debt to improve the debt-to-income ratio.\",\n \"Consider building an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore opportunities for salary increases or additional income sources to enhance financial stability.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_verified\\\": true\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2816.67,\\n \\\"proposed_emi\\\": 416.67,\\n \\\"debt_to_income_ratio\\\": 0.4142,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": false,\\n \\\"assessment\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"over_leverage\\\": {\\n \\\"description\\\": \\\"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\\\",\\n \\\"recommendation\\\": \\\"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\\\"\\n },\\n \\\"income_sources\\\": {\\n \\\"description\\\": \\\"Reliance on a single income source may pose a risk if employment status changes.\\\",\\n \\\"recommendation\\\": \\\"Explore additional income streams or savings to mitigate risks associated with job loss.\\\"\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 65,\\n \\\"recommendations\\\": [\\n \\\"Focus on reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Consider building an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore opportunities for salary increases or additional income sources to enhance financial stability.\\\"\\n ]\\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\": \"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employment_verified\": true\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2816.67,\n \"proposed_emi\": 416.67,\n \"debt_to_income_ratio\": 0.4142,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": false,\n \"assessment\": \"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\"\n },\n \"risk_factors\": {\n \"over_leverage\": {\n \"description\": \"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\",\n \"recommendation\": \"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\"\n },\n \"income_sources\": {\n \"description\": \"Reliance on a single income source may pose a risk if employment status changes.\",\n \"recommendation\": \"Explore additional income streams or savings to mitigate risks associated with job loss.\"\n }\n },\n \"overall_income_adequacy_score\": 65,\n \"recommendations\": [\n \"Focus on reducing existing debt to improve the debt-to-income ratio.\",\n \"Consider building an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore opportunities for salary increases or additional income sources to enhance financial stability.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_verified\\\": true\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2816.67,\\n \\\"proposed_emi\\\": 416.67,\\n \\\"debt_to_income_ratio\\\": 0.4142,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": false,\\n \\\"assessment\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"over_leverage\\\": {\\n \\\"description\\\": \\\"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\\\",\\n \\\"recommendation\\\": \\\"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\\\"\\n },\\n \\\"income_sources\\\": {\\n \\\"description\\\": \\\"Reliance on a single income source may pose a risk if employment status changes.\\\",\\n \\\"recommendation\\\": \\\"Explore additional income streams or savings to mitigate risks associated with job loss.\\\"\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 65,\\n \\\"recommendations\\\": [\\n \\\"Focus on reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Consider building an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore opportunities for salary increases or additional income sources to enhance financial stability.\\\"\\n ]\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
"oldest_account_age": "60 months",
"output": "__OUTPUTS__ {\"oldest_account_age\": \"60 months\", \"average_account_age\": \"32 months\", \"credit_mix\": {\"credit_cards\": 3, \"personal_loans\": 1, \"auto_loans\": 1, \"home_loans\": 0, \"other\": 1}, \"repayment_behavior\": {\"never_missed\": 85.0, \"30_days_late\": 12.0, \"60_days_late\": 2.5, \"90_days_late\": 0.5, \"defaults\": 0.0}, \"credit_limit_utilization\": 35.2, \"recent_credit_behavior\": \"stable\"}\n",
"recent_credit_behavior": "stable",
"repayment_behavior": {
"30_days_late": 12.0,
"60_days_late": 2.5,
"90_days_late": 0.5,
"defaults": 0.0,
"never_missed": 85.0
},
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "analyze_credit_history"
},
"analyze_salary_slips": {
"annual_gross": 102000,
"annual_net": 81600,
"deductions": {
"insurance": 300,
"pf": 500,
"tax": 1200
},
"employer": "Tech Corp Ltd",
"employment_duration": "2.5 years",
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.516462,
"end_time": "2025-07-15T11:11:21.457794",
"message_sent": true,
"start_time": "2025-07-15T11:11:20.941332",
"timestamp": "2025-07-15T11:11:21.457794",
"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\": \"All required fields are present and validated successfully. The application is complete and accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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": 1009,
"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\": \"All required fields are present and validated successfully. The application is complete and accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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\\\": \\\"All required fields are present and validated successfully. The application is complete and accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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": 5.045226,
"end_time": "2025-07-15T11:11:19.261675",
"message_sent": true,
"start_time": "2025-07-15T11:11:14.216449",
"timestamp": "2025-07-15T11:11:19.261675",
"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\": \"All required fields are present and validated successfully. The application is complete and accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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\\\": \\\"All required fields are present and validated successfully. The application is complete and accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided customer information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and aligns with typical loan application criteria.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is well-prepared with complete and accurate information. While there are no red flags, a slight deduction in the score is due to the lack of additional context or supporting documentation that could further strengthen 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": 0.347074,
"end_time": "2025-07-15T11:11:28.745806",
"message_sent": true,
"start_time": "2025-07-15T11:11:28.398732",
"timestamp": "2025-07-15T11:11:28.745806",
"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/tmppa708vgv.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/tmppa708vgv.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": 0.4142156862745098,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.40155,
"end_time": "2025-07-15T11:11:22.227144",
"message_sent": true,
"start_time": "2025-07-15T11:11:21.825594",
"timestamp": "2025-07-15T11:11:22.227144",
"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\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 416.6666666666667,
"ratio_acceptable": false,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2816.6666666666665
},
"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": 0.265386,
"end_time": "2025-07-15T11:11:28.140661",
"message_sent": true,
"start_time": "2025-07-15T11:11:27.875275",
"timestamp": "2025-07-15T11:11:28.140661",
"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 \"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\",\n \"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve the 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": 1125,
"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 \"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\",\n \"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve the 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 \\\"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\\\",\\n \\\"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve the 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": 4.592061,
"end_time": "2025-07-15T11:14:47.123147",
"message_sent": true,
"start_time": "2025-07-15T11:14:42.531086",
"timestamp": "2025-07-15T11:14:47.123147",
"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 \"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\",\n \"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\",\n \"Resolve the 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 \\\"Prioritize resolving the KYC compliance check immediately to mitigate identity fraud risk.\\\",\\n \\\"Address the unresolved AML screening to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Resolve the 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 and consistent information. 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": 336,
"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 and consistent information. 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 and consistent information. 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": 1.989276,
"end_time": "2025-07-15T11:11:21.152256",
"message_sent": true,
"start_time": "2025-07-15T11:11:19.162980",
"timestamp": "2025-07-15T11:11:21.152256",
"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 and consistent information. 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 and consistent information. 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 various factors mentioned and assign a risk score based on the overall assessment.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score.\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\n- **Credit History**: Excellent - 10 points\n- **Repayment Patterns**: Excellent - 5 points\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\n- **Existing Loan Burden**: Manageable - 10 points\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\n\n### Total Risk Score\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\n\n### Risk Score\n- **Risk Score**: 65 out of 100\n\n### Recommendations\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\n\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.",
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"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
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"output": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the overall assessment.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score.\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\n- **Credit History**: Excellent - 10 points\n- **Repayment Patterns**: Excellent - 5 points\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\n- **Existing Loan Burden**: Manageable - 10 points\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\n\n### Total Risk Score\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\n\n### Risk Score\n- **Risk Score**: 65 out of 100\n\n### Recommendations\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\n\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the overall assessment.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score.\\\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\\n- **Credit History**: Excellent - 10 points\\n- **Repayment Patterns**: Excellent - 5 points\\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\\n- **Existing Loan Burden**: Manageable - 10 points\\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\\n\\n### Total Risk Score\\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\\n\\n### Risk Score\\n- **Risk Score**: 65 out of 100\\n\\n### Recommendations\\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\\n\\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"model": "gpt-4o-mini",
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"output": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the overall assessment.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score.\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\n- **Credit History**: Excellent - 10 points\n- **Repayment Patterns**: Excellent - 5 points\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\n- **Existing Loan Burden**: Manageable - 10 points\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\n\n### Total Risk Score\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\n\n### Risk Score\n- **Risk Score**: 65 out of 100\n\n### Recommendations\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\n\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the overall assessment.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score.\\\" Without a specific score, we cannot accurately assess this factor. However, if we assume that the score is average (around 650-700), it would indicate moderate risk. A higher score would reduce risk, while a lower score would increase it.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" If the history is excellent, it would significantly lower the risk. Conversely, a poor history would increase the risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt-to-income ratio, suggesting that the individual is managing their debt well. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700. This is a significant amount, but given the loan burden ratio, it appears manageable.\\n- **Outstanding Loans**: The total outstanding amount is 125,000, which includes a personal loan of 45,000 and an auto loan of 80,000. The remaining tenures of 18 and 24 months respectively indicate that these loans will be paid off relatively soon.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The individual has two loans, which is manageable. However, having multiple loans can increase risk if not managed properly.\\n- **Repayment Patterns**: The excellent repayment track record is a strong positive indicator.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- **CIBIL Score**: Unknown (assumed average for calculation) - 20 points\\n- **Credit History**: Excellent - 10 points\\n- **Repayment Patterns**: Excellent - 5 points\\n- **Credit Utilization (Loan Burden Ratio)**: 28% - 15 points\\n- **Existing Loan Burden**: Manageable - 10 points\\n- **Overall Risk Profile**: Two loans, good repayment history - 5 points\\n\\n### Total Risk Score\\n- **Total Points**: 20 (CIBIL) + 10 (History) + 5 (Repayment) + 15 (Utilization) + 10 (Existing Burden) + 5 (Overall Profile) = 65 points\\n\\n### Risk Score\\n- **Risk Score**: 65 out of 100\\n\\n### Recommendations\\n1. **Improve CIBIL Score**: If the CIBIL score is below average, work on improving it by ensuring timely payments and reducing credit utilization.\\n2. **Maintain Excellent Repayment Patterns**: Continue the trend of timely payments to maintain a good credit history.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Consider Debt Consolidation**: If the individual finds it challenging to manage multiple loans, consider consolidating them into a single loan with a lower interest rate.\\n5. **Financial Planning**: Engage in financial planning to ensure that future expenses do not lead to increased debt levels.\\n\\nIn summary, while the risk score of 65 indicates a moderate risk of default, the individual has several positive factors that can help mitigate this risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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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": 100000
},
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 100000}, \"missing_fields\": []}\n",
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"extraction_success": true,
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 100000}, \"missing_fields\": []}\n",
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"final_underwriting_analysis": {
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"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:**\n - The application has multiple unresolved issues, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. \n - Each of these unresolved areas represents a significant risk factor that could lead to potential losses for the lending institution. Without clear and verified information in these critical areas, it is impossible to assess the borrower\u0027s ability to repay the loan or their overall creditworthiness.\n - The lack of resolution in these areas indicates that the application does not meet the necessary standards for approval, as it fails to provide a comprehensive and reliable picture of the applicant\u0027s financial situation.\n\n5. **Confidence Level:** 95\n - Given the high number of unresolved issues, there is a strong confidence level in the decision to decline the application. The absence of verified information creates a substantial risk that cannot be overlooked.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
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"output": "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:**\n - The application has multiple unresolved issues, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. \n - Each of these unresolved areas represents a significant risk factor that could lead to potential losses for the lending institution. Without clear and verified information in these critical areas, it is impossible to assess the borrower\u0027s ability to repay the loan or their overall creditworthiness.\n - The lack of resolution in these areas indicates that the application does not meet the necessary standards for approval, as it fails to provide a comprehensive and reliable picture of the applicant\u0027s financial situation.\n\n5. **Confidence Level:** 95\n - Given the high number of unresolved issues, there is a strong confidence level in the decision to decline the application. The absence of verified information creates a substantial risk that cannot be overlooked.\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:**\\n - The application has multiple unresolved issues, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. \\n - Each of these unresolved areas represents a significant risk factor that could lead to potential losses for the lending institution. Without clear and verified information in these critical areas, it is impossible to assess the borrower\u0027s ability to repay the loan or their overall creditworthiness.\\n - The lack of resolution in these areas indicates that the application does not meet the necessary standards for approval, as it fails to provide a comprehensive and reliable picture of the applicant\u0027s financial situation.\\n\\n5. **Confidence Level:** 95\\n - Given the high number of unresolved issues, there is a strong confidence level in the decision to decline the application. The absence of verified information creates a substantial risk that cannot be overlooked.\", \"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:**\n - The application has multiple unresolved issues, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. \n - Each of these unresolved areas represents a significant risk factor that could lead to potential losses for the lending institution. Without clear and verified information in these critical areas, it is impossible to assess the borrower\u0027s ability to repay the loan or their overall creditworthiness.\n - The lack of resolution in these areas indicates that the application does not meet the necessary standards for approval, as it fails to provide a comprehensive and reliable picture of the applicant\u0027s financial situation.\n\n5. **Confidence Level:** 95\n - Given the high number of unresolved issues, there is a strong confidence level in the decision to decline the application. The absence of verified information creates a substantial risk that cannot be overlooked.\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:**\\n - The application has multiple unresolved issues, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. \\n - Each of these unresolved areas represents a significant risk factor that could lead to potential losses for the lending institution. Without clear and verified information in these critical areas, it is impossible to assess the borrower\u0027s ability to repay the loan or their overall creditworthiness.\\n - The lack of resolution in these areas indicates that the application does not meet the necessary standards for approval, as it fails to provide a comprehensive and reliable picture of the applicant\u0027s financial situation.\\n\\n5. **Confidence Level:** 95\\n - Given the high number of unresolved issues, there is a strong confidence level in the decision to decline the application. The absence of verified information creates a substantial risk that cannot be overlooked.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"flag_for_manual_review": {
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"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpoeql9e4q.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/tmpoeql9e4q.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\": \"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employment_verified\": true\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2816.67,\n \"proposed_emi\": 416.67,\n \"debt_to_income_ratio\": 0.4142,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": false,\n \"assessment\": \"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\"\n },\n \"risk_factors\": {\n \"over_leverage\": {\n \"description\": \"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\",\n \"recommendation\": \"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\"\n },\n \"income_sources\": {\n \"description\": \"Reliance on a single income source may pose a risk if employment status changes.\",\n \"recommendation\": \"Explore additional income streams or savings to mitigate risks associated with job loss.\"\n }\n },\n \"overall_income_adequacy_score\": 65,\n \"recommendations\": [\n \"Focus on reducing existing debt to improve the debt-to-income ratio.\",\n \"Consider building an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore opportunities for salary increases or additional income sources to enhance financial stability.\"\n ]\n }\n}\n```",
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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\": \"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employment_verified\": true\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2816.67,\n \"proposed_emi\": 416.67,\n \"debt_to_income_ratio\": 0.4142,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": false,\n \"assessment\": \"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\"\n },\n \"risk_factors\": {\n \"over_leverage\": {\n \"description\": \"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\",\n \"recommendation\": \"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\"\n },\n \"income_sources\": {\n \"description\": \"Reliance on a single income source may pose a risk if employment status changes.\",\n \"recommendation\": \"Explore additional income streams or savings to mitigate risks associated with job loss.\"\n }\n },\n \"overall_income_adequacy_score\": 65,\n \"recommendations\": [\n \"Focus on reducing existing debt to improve the debt-to-income ratio.\",\n \"Consider building an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore opportunities for salary increases or additional income sources to enhance financial stability.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_verified\\\": true\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2816.67,\\n \\\"proposed_emi\\\": 416.67,\\n \\\"debt_to_income_ratio\\\": 0.4142,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": false,\\n \\\"assessment\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"over_leverage\\\": {\\n \\\"description\\\": \\\"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\\\",\\n \\\"recommendation\\\": \\\"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\\\"\\n },\\n \\\"income_sources\\\": {\\n \\\"description\\\": \\\"Reliance on a single income source may pose a risk if employment status changes.\\\",\\n \\\"recommendation\\\": \\\"Explore additional income streams or savings to mitigate risks associated with job loss.\\\"\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 65,\\n \\\"recommendations\\\": [\\n \\\"Focus on reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Consider building an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore opportunities for salary increases or additional income sources to enhance financial stability.\\\"\\n ]\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"model": "gpt-4o-mini",
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employment_verified\": true\n },\n \"debt_servicing_capability\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2816.67,\n \"proposed_emi\": 416.67,\n \"debt_to_income_ratio\": 0.4142,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": false,\n \"assessment\": \"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\"\n },\n \"risk_factors\": {\n \"over_leverage\": {\n \"description\": \"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\",\n \"recommendation\": \"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\"\n },\n \"income_sources\": {\n \"description\": \"Reliance on a single income source may pose a risk if employment status changes.\",\n \"recommendation\": \"Explore additional income streams or savings to mitigate risks associated with job loss.\"\n }\n },\n \"overall_income_adequacy_score\": 65,\n \"recommendations\": [\n \"Focus on reducing existing debt to improve the debt-to-income ratio.\",\n \"Consider building an emergency fund to cover at least 3-6 months of expenses.\",\n \"Explore opportunities for salary increases or additional income sources to enhance financial stability.\"\n ]\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High stability due to permanent employment with a reputable employer (A+ rating) and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_verified\\\": true\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2816.67,\\n \\\"proposed_emi\\\": 416.67,\\n \\\"debt_to_income_ratio\\\": 0.4142,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": false,\\n \\\"assessment\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold of 0.4, indicating potential challenges in servicing additional debt.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"The individual has a stable income but is currently over-leveraged based on the debt-to-income ratio. This suggests a need for improved financial discipline in managing existing debts.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"over_leverage\\\": {\\n \\\"description\\\": \\\"The debt-to-income ratio is above the acceptable limit, indicating a risk of financial strain.\\\",\\n \\\"recommendation\\\": \\\"Consider reducing existing debt or increasing income to improve the debt-to-income ratio.\\\"\\n },\\n \\\"income_sources\\\": {\\n \\\"description\\\": \\\"Reliance on a single income source may pose a risk if employment status changes.\\\",\\n \\\"recommendation\\\": \\\"Explore additional income streams or savings to mitigate risks associated with job loss.\\\"\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 65,\\n \\\"recommendations\\\": [\\n \\\"Focus on reducing existing debt to improve the debt-to-income ratio.\\\",\\n \\\"Consider building an emergency fund to cover at least 3-6 months of expenses.\\\",\\n \\\"Explore opportunities for salary increases or additional income sources to enhance financial stability.\\\"\\n ]\\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__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
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{
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{
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"message_sent": true,
"start_time": "2025-07-15T11:11:18.334699",
"timestamp": "2025-07-15T11:11:19.056717",
"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": 0.999215,
"end_time": "2025-07-15T11:11:22.033823",
"message_sent": true,
"start_time": "2025-07-15T11:11:21.034608",
"timestamp": "2025-07-15T11:11:22.033823",
"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": 0.000641,
"ended_at": "2025-07-15T11:14:46.761110",
"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\": 0.000641, \"started_at\": \"2025-07-15T11:14:46.760469\", \"ended_at\": \"2025-07-15T11:14:46.761110\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.250804,
"end_time": "2025-07-15T11:14:46.921029",
"message_sent": true,
"start_time": "2025-07-15T11:14:46.670225",
"timestamp": "2025-07-15T11:14:46.921029",
"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\": 0.000641, \"started_at\": \"2025-07-15T11:14:46.760469\", \"ended_at\": \"2025-07-15T11:14:46.761110\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T11:14:46.760469",
"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": 0.307803,
"end_time": "2025-07-15T11:11:14.259549",
"message_sent": true,
"start_time": "2025-07-15T11:11:13.951746",
"timestamp": "2025-07-15T11:11:14.259549",
"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": 0.52355,
"end_time": "2025-07-15T11:11:18.814268",
"message_sent": true,
"start_time": "2025-07-15T11:11:18.290718",
"timestamp": "2025-07-15T11:11:18.814268",
"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": 0.851806,
"end_time": "2025-07-15T11:11:19.225986",
"message_sent": true,
"start_time": "2025-07-15T11:11:18.374180",
"timestamp": "2025-07-15T11:11:19.225986",
"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": 0.714675,
"end_time": "2025-07-15T11:11:22.079165",
"message_sent": true,
"start_time": "2025-07-15T11:11:21.364490",
"timestamp": "2025-07-15T11:11:22.079165",
"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": 0.37907,
"end_time": "2025-07-15T11:11:18.632555",
"message_sent": true,
"start_time": "2025-07-15T11:11:18.253485",
"timestamp": "2025-07-15T11:11:18.632555",
"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": 0.722018,
"end_time": "2025-07-15T11:11:19.056717",
"message_sent": true,
"start_time": "2025-07-15T11:11:18.334699",
"timestamp": "2025-07-15T11:11:19.056717",
"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": 0.999215,
"end_time": "2025-07-15T11:11:22.033823",
"message_sent": true,
"start_time": "2025-07-15T11:11:21.034608",
"timestamp": "2025-07-15T11:11:22.033823",
"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
}
}