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": 0.253058,
"end_time": "2025-07-15T12:54:16.472975",
"message_sent": true,
"start_time": "2025-07-15T12:54:16.219917",
"timestamp": "2025-07-15T12:54:16.472975",
"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": 0.433978,
"end_time": "2025-07-15T12:50:41.722952",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.288974",
"timestamp": "2025-07-15T12:50:41.722952",
"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": 0.330535,
"end_time": "2025-07-15T12:50:52.583308",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.252773",
"timestamp": "2025-07-15T12:50:52.583308",
"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": 0.288089,
"end_time": "2025-07-15T12:50:41.540061",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.251972",
"timestamp": "2025-07-15T12:50:41.540061",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or_inconsistencies\": {\n \"requested_amount\": {\n \"value\": 10000,\n \"context\": \"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 468,
"model": "gpt-4o-mini",
"output_length": 783,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or_inconsistencies\": {\n \"requested_amount\": {\n \"value\": 10000,\n \"context\": \"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"requested_amount\\\": {\\n \\\"value\\\": 10000,\\n \\\"context\\\": \\\"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.915001,
"end_time": "2025-07-15T12:50:38.942551",
"message_sent": true,
"start_time": "2025-07-15T12:50:34.027550",
"timestamp": "2025-07-15T12:50:38.942551",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or_inconsistencies\": {\n \"requested_amount\": {\n \"value\": 10000,\n \"context\": \"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"requested_amount\\\": {\\n \\\"value\\\": 10000,\\n \\\"context\\\": \\\"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"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": 0.380925,
"end_time": "2025-07-15T12:50:52.911663",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.530738",
"timestamp": "2025-07-15T12:50:52.911663",
"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/tmph9imvt26.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/tmph9imvt26.py\", line 9, in \u003cmodule\u003e\n cibil_score = UNRESOLVED_check_cibil_score.credit_score\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"debt_to_income_ratio": 0.3590686274509804,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.418619,
"end_time": "2025-07-15T12:50:42.334207",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.915588",
"timestamp": "2025-07-15T12:50:42.334207",
"worker_executed": true,
"workers_notified": true
},
"existing_debt_payments": 2400,
"max_allowed_ratio": 0.4,
"monthly_net_income": 6800,
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 41.666666666666664,
"ratio_acceptable": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2441.6666666666665
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.298212,
"end_time": "2025-07-15T12:50:52.308872",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.010660",
"timestamp": "2025-07-15T12:50:52.308872",
"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\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk\": \"low\",\n \"individual_risks\": {\n \"KYC\": \"low\",\n \"AML\": \"low\",\n \"Regulatory\": \"minimal\",\n \"Internal Policy\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations\": [\n \"Continue to monitor compliance checks regularly to maintain low risk status.\",\n \"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\",\n \"Conduct periodic training for staff on compliance policies and updates to regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1285,
"model": "gpt-4o-mini",
"output_length": 623,
"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\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk\": \"low\",\n \"individual_risks\": {\n \"KYC\": \"low\",\n \"AML\": \"low\",\n \"Regulatory\": \"minimal\",\n \"Internal Policy\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations\": [\n \"Continue to monitor compliance checks regularly to maintain low risk status.\",\n \"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\",\n \"Conduct periodic training for staff on compliance policies and updates to regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk\\\": \\\"low\\\",\\n \\\"individual_risks\\\": {\\n \\\"KYC\\\": \\\"low\\\",\\n \\\"AML\\\": \\\"low\\\",\\n \\\"Regulatory\\\": \\\"minimal\\\",\\n \\\"Internal Policy\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations\\\": [\\n \\\"Continue to monitor compliance checks regularly to maintain low risk status.\\\",\\n \\\"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\\\",\\n \\\"Conduct periodic training for staff on compliance policies and updates to regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 3.444743,
"end_time": "2025-07-15T12:54:20.530477",
"message_sent": true,
"start_time": "2025-07-15T12:54:17.085734",
"timestamp": "2025-07-15T12:54:20.530477",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk\": \"low\",\n \"individual_risks\": {\n \"KYC\": \"low\",\n \"AML\": \"low\",\n \"Regulatory\": \"minimal\",\n \"Internal Policy\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations\": [\n \"Continue to monitor compliance checks regularly to maintain low risk status.\",\n \"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\",\n \"Conduct periodic training for staff on compliance policies and updates to regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk\\\": \\\"low\\\",\\n \\\"individual_risks\\\": {\\n \\\"KYC\\\": \\\"low\\\",\\n \\\"AML\\\": \\\"low\\\",\\n \\\"Regulatory\\\": \\\"minimal\\\",\\n \\\"Internal Policy\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations\\\": [\\n \\\"Continue to monitor compliance checks regularly to maintain low risk status.\\\",\\n \\\"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\\\",\\n \\\"Conduct periodic training for staff on compliance policies and updates to regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 309,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 3.191733,
"end_time": "2025-07-15T12:50:42.056744",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.865011",
"timestamp": "2025-07-15T12:50:42.056744",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "### Credit Risk Assessment\n\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\n\n#### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\n\n#### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\n\n#### 3. Credit Utilization\n- **Credit Utilization**: 35.5%\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\n\n#### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Loan Burden Ratio**: 0.28 (28%)\n- **Total Outstanding**: 125000\n\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\n\n#### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\n\n### Risk Score Calculation\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\n\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 15 points (Excellent)\n- **Repayment Patterns**: 10 points (Good, but some late payments)\n- **Credit Utilization**: 10 points (Acceptable)\n- **Existing Loan Burden**: 10 points (Manageable)\n- **Overall Risk Profile**: 5 points (Stable)\n\n**Total Risk Score**: \n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\n\n### Default Risk Assessment\n- **Risk Score**: **70/100**\n- **Risk Level**: Moderate Risk\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\n\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.",
"execution_details": {
"actual_result": {
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"agent_type": "assistant",
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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": "### Credit Risk Assessment\n\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\n\n#### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\n\n#### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\n\n#### 3. Credit Utilization\n- **Credit Utilization**: 35.5%\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\n\n#### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Loan Burden Ratio**: 0.28 (28%)\n- **Total Outstanding**: 125000\n\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\n\n#### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\n\n### Risk Score Calculation\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\n\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 15 points (Excellent)\n- **Repayment Patterns**: 10 points (Good, but some late payments)\n- **Credit Utilization**: 10 points (Acceptable)\n- **Existing Loan Burden**: 10 points (Manageable)\n- **Overall Risk Profile**: 5 points (Stable)\n\n**Total Risk Score**: \n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\n\n### Default Risk Assessment\n- **Risk Score**: **70/100**\n- **Risk Level**: Moderate Risk\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\n\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\n__OUTPUTS__ {\"ai_response\": \"### Credit Risk Assessment\\n\\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\\n\\n#### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n\\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\\n\\n#### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n\\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\\n\\n#### 3. Credit Utilization\\n- **Credit Utilization**: 35.5%\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\\n\\n#### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Loan Burden Ratio**: 0.28 (28%)\\n- **Total Outstanding**: 125000\\n\\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\\n\\n#### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\\n\\n### Risk Score Calculation\\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\\n\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 15 points (Excellent)\\n- **Repayment Patterns**: 10 points (Good, but some late payments)\\n- **Credit Utilization**: 10 points (Acceptable)\\n- **Existing Loan Burden**: 10 points (Manageable)\\n- **Overall Risk Profile**: 5 points (Stable)\\n\\n**Total Risk Score**: \\n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\\n\\n### Default Risk Assessment\\n- **Risk Score**: **70/100**\\n- **Risk Level**: Moderate Risk\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\\n\\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\", \"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": 24.024823,
"end_time": "2025-07-15T12:51:16.881488",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.856665",
"timestamp": "2025-07-15T12:51:16.881488",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "### Credit Risk Assessment\n\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\n\n#### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\n\n#### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\n\n#### 3. Credit Utilization\n- **Credit Utilization**: 35.5%\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\n\n#### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Loan Burden Ratio**: 0.28 (28%)\n- **Total Outstanding**: 125000\n\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\n\n#### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\n\n### Risk Score Calculation\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\n\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 15 points (Excellent)\n- **Repayment Patterns**: 10 points (Good, but some late payments)\n- **Credit Utilization**: 10 points (Acceptable)\n- **Existing Loan Burden**: 10 points (Manageable)\n- **Overall Risk Profile**: 5 points (Stable)\n\n**Total Risk Score**: \n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\n\n### Default Risk Assessment\n- **Risk Score**: **70/100**\n- **Risk Level**: Moderate Risk\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\n\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\n__OUTPUTS__ {\"ai_response\": \"### Credit Risk Assessment\\n\\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\\n\\n#### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n\\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\\n\\n#### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n\\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\\n\\n#### 3. Credit Utilization\\n- **Credit Utilization**: 35.5%\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\\n\\n#### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Loan Burden Ratio**: 0.28 (28%)\\n- **Total Outstanding**: 125000\\n\\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\\n\\n#### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\\n\\n### Risk Score Calculation\\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\\n\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 15 points (Excellent)\\n- **Repayment Patterns**: 10 points (Good, but some late payments)\\n- **Credit Utilization**: 10 points (Acceptable)\\n- **Existing Loan Burden**: 10 points (Manageable)\\n- **Overall Risk Profile**: 5 points (Stable)\\n\\n**Total Risk Score**: \\n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\\n\\n### Default Risk Assessment\\n- **Risk Score**: **70/100**\\n- **Risk Level**: Moderate Risk\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\\n\\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
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"task_id": "evaluate_default_risk"
},
"execution_summary": {
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"execution_mode": "distributed",
"start_time": "2025-07-15T12:50:31.691437",
"total_tasks": 28
},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.275202,
"end_time": "2025-07-15T12:50:33.819336",
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"timestamp": "2025-07-15T12:50:33.819336",
"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
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},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "### Final Recommendation: APPROVE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: 6.5% (fixed)\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $198.66\n- **Prepayment Penalty**: None\n- **Repayment Schedule**: Monthly payments\n\n#### Risk Mitigation Measures:\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\n\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\n\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\n\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\n\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\n\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\n\n#### Confidence Level: 85\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
"input_format": "json",
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"output": "### Final Recommendation: APPROVE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: 6.5% (fixed)\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $198.66\n- **Prepayment Penalty**: None\n- **Repayment Schedule**: Monthly payments\n\n#### Risk Mitigation Measures:\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\n\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\n\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\n\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\n\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\n\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\n\n#### Confidence Level: 85\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: APPROVE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: 6.5% (fixed)\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $198.66\\n- **Prepayment Penalty**: None\\n- **Repayment Schedule**: Monthly payments\\n\\n#### Risk Mitigation Measures:\\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\\n\\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\\n\\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\\n\\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\\n\\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\\n\\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\\n\\n#### Confidence Level: 85\\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "### Final Recommendation: APPROVE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: 6.5% (fixed)\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $198.66\n- **Prepayment Penalty**: None\n- **Repayment Schedule**: Monthly payments\n\n#### Risk Mitigation Measures:\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\n\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\n\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\n\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\n\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\n\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\n\n#### Confidence Level: 85\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: APPROVE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: 6.5% (fixed)\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $198.66\\n- **Prepayment Penalty**: None\\n- **Repayment Schedule**: Monthly payments\\n\\n#### Risk Mitigation Measures:\\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\\n\\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\\n\\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\\n\\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\\n\\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\\n\\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\\n\\n#### Confidence Level: 85\\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"proposed_emi\": 41.67\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Strong\",\n \"details\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"salary_credits_consistent\": true\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"discrepancies_found\": false,\n \"tax_compliance_score\": 92.0,\n \"returns_filed_consistently\": true,\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\"\n }\n },\n \"recommendations\": [\n \"Continue maintaining current employment and financial discipline.\",\n \"Consider increasing savings to further improve financial stability.\",\n \"Monitor any changes in income or expenses that could affect debt servicing.\"\n ],\n \"overall_income_adequacy_score\": 88\n }\n}\n```",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"proposed_emi\": 41.67\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Strong\",\n \"details\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"salary_credits_consistent\": true\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"discrepancies_found\": false,\n \"tax_compliance_score\": 92.0,\n \"returns_filed_consistently\": true,\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\"\n }\n },\n \"recommendations\": [\n \"Continue maintaining current employment and financial discipline.\",\n \"Consider increasing savings to further improve financial stability.\",\n \"Monitor any changes in income or expenses that could affect debt servicing.\"\n ],\n \"overall_income_adequacy_score\": 88\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"proposed_emi\\\": 41.67\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Strong\\\",\\n \\\"details\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"salary_credits_consistent\\\": true\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"discrepancies_found\\\": false,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\"\\n }\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue maintaining current employment and financial discipline.\\\",\\n \\\"Consider increasing savings to further improve financial stability.\\\",\\n \\\"Monitor any changes in income or expenses that could affect debt servicing.\\\"\\n ],\\n \\\"overall_income_adequacy_score\\\": 88\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"proposed_emi\": 41.67\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Strong\",\n \"details\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"salary_credits_consistent\": true\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"discrepancies_found\": false,\n \"tax_compliance_score\": 92.0,\n \"returns_filed_consistently\": true,\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\"\n }\n },\n \"recommendations\": [\n \"Continue maintaining current employment and financial discipline.\",\n \"Consider increasing savings to further improve financial stability.\",\n \"Monitor any changes in income or expenses that could affect debt servicing.\"\n ],\n \"overall_income_adequacy_score\": 88\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"proposed_emi\\\": 41.67\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Strong\\\",\\n \\\"details\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"salary_credits_consistent\\\": true\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"discrepancies_found\\\": false,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\"\\n }\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue maintaining current employment and financial discipline.\\\",\\n \\\"Consider increasing savings to further improve financial stability.\\\",\\n \\\"Monitor any changes in income or expenses that could affect debt servicing.\\\"\\n ],\\n \\\"overall_income_adequacy_score\\\": 88\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"timestamp": "2025-07-15T12:54:16.472975",
"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": 0.433978,
"end_time": "2025-07-15T12:50:41.722952",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.288974",
"timestamp": "2025-07-15T12:50:41.722952",
"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": 0.330535,
"end_time": "2025-07-15T12:50:52.583308",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.252773",
"timestamp": "2025-07-15T12:50:52.583308",
"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": 0.288089,
"end_time": "2025-07-15T12:50:41.540061",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.251972",
"timestamp": "2025-07-15T12:50:41.540061",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or_inconsistencies\": {\n \"requested_amount\": {\n \"value\": 10000,\n \"context\": \"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 468,
"model": "gpt-4o-mini",
"output_length": 783,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or_inconsistencies\": {\n \"requested_amount\": {\n \"value\": 10000,\n \"context\": \"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"requested_amount\\\": {\\n \\\"value\\\": 10000,\\n \\\"context\\\": \\\"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.915001,
"end_time": "2025-07-15T12:50:38.942551",
"message_sent": true,
"start_time": "2025-07-15T12:50:34.027550",
"timestamp": "2025-07-15T12:50:38.942551",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0\n },\n \"consistency_of_information\": {\n \"email\": \"john.doe@email.com\",\n \"phone\": \"+1-555-0123\",\n \"address\": \"123 Main St, City, State 12345\",\n \"full_name\": \"John Doe\",\n \"customer_id\": \"CUST_12345\",\n \"loan_purpose\": \"home_purchase\",\n \"annual_income\": 75000,\n \"requested_amount\": 10000,\n \"employment_status\": \"employed\"\n },\n \"red_flags_or_inconsistencies\": {\n \"requested_amount\": {\n \"value\": 10000,\n \"context\": \"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\"\n }\n },\n \"overall_application_quality_score\": 85\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"email\\\": \\\"john.doe@email.com\\\",\\n \\\"phone\\\": \\\"+1-555-0123\\\",\\n \\\"address\\\": \\\"123 Main St, City, State 12345\\\",\\n \\\"full_name\\\": \\\"John Doe\\\",\\n \\\"customer_id\\\": \\\"CUST_12345\\\",\\n \\\"loan_purpose\\\": \\\"home_purchase\\\",\\n \\\"annual_income\\\": 75000,\\n \\\"requested_amount\\\": 10000,\\n \\\"employment_status\\\": \\\"employed\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"requested_amount\\\": {\\n \\\"value\\\": 10000,\\n \\\"context\\\": \\\"The requested amount of $10,000 is relatively low for a home purchase, which typically requires a significantly higher loan amount.\\\"\\n }\\n },\\n \\\"overall_application_quality_score\\\": 85\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"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": 0.380925,
"end_time": "2025-07-15T12:50:52.911663",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.530738",
"timestamp": "2025-07-15T12:50:52.911663",
"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/tmph9imvt26.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/tmph9imvt26.py\", line 9, in \u003cmodule\u003e\n cibil_score = UNRESOLVED_check_cibil_score.credit_score\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_credit_score"
},
"calculate_debt_to_income": {
"debt_to_income_ratio": 0.3590686274509804,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.418619,
"end_time": "2025-07-15T12:50:42.334207",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.915588",
"timestamp": "2025-07-15T12:50:42.334207",
"worker_executed": true,
"workers_notified": true
},
"existing_debt_payments": 2400,
"max_allowed_ratio": 0.4,
"monthly_net_income": 6800,
"output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 41.666666666666664, \"total_debt_payments\": 2441.6666666666665, \"debt_to_income_ratio\": 0.3590686274509804, \"ratio_acceptable\": true, \"max_allowed_ratio\": 0.4}\n",
"proposed_emi": 41.666666666666664,
"ratio_acceptable": true,
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "calculate_debt_to_income",
"total_debt_payments": 2441.6666666666665
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.298212,
"end_time": "2025-07-15T12:50:52.308872",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.010660",
"timestamp": "2025-07-15T12:50:52.308872",
"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\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk\": \"low\",\n \"individual_risks\": {\n \"KYC\": \"low\",\n \"AML\": \"low\",\n \"Regulatory\": \"minimal\",\n \"Internal Policy\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations\": [\n \"Continue to monitor compliance checks regularly to maintain low risk status.\",\n \"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\",\n \"Conduct periodic training for staff on compliance policies and updates to regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1285,
"model": "gpt-4o-mini",
"output_length": 623,
"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\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk\": \"low\",\n \"individual_risks\": {\n \"KYC\": \"low\",\n \"AML\": \"low\",\n \"Regulatory\": \"minimal\",\n \"Internal Policy\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations\": [\n \"Continue to monitor compliance checks regularly to maintain low risk status.\",\n \"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\",\n \"Conduct periodic training for staff on compliance policies and updates to regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk\\\": \\\"low\\\",\\n \\\"individual_risks\\\": {\\n \\\"KYC\\\": \\\"low\\\",\\n \\\"AML\\\": \\\"low\\\",\\n \\\"Regulatory\\\": \\\"minimal\\\",\\n \\\"Internal Policy\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations\\\": [\\n \\\"Continue to monitor compliance checks regularly to maintain low risk status.\\\",\\n \\\"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\\\",\\n \\\"Conduct periodic training for staff on compliance policies and updates to regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 3.444743,
"end_time": "2025-07-15T12:54:20.530477",
"message_sent": true,
"start_time": "2025-07-15T12:54:17.085734",
"timestamp": "2025-07-15T12:54:20.530477",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"compliant\",\n \"risk_assessment\": {\n \"overall_risk\": \"low\",\n \"individual_risks\": {\n \"KYC\": \"low\",\n \"AML\": \"low\",\n \"Regulatory\": \"minimal\",\n \"Internal Policy\": \"low\"\n }\n },\n \"compliance_gaps_or_concerns\": [],\n \"recommendations\": [\n \"Continue to monitor compliance checks regularly to maintain low risk status.\",\n \"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\",\n \"Conduct periodic training for staff on compliance policies and updates to regulations.\"\n ],\n \"compliance_confidence_score\": 97.5\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"overall_risk\\\": \\\"low\\\",\\n \\\"individual_risks\\\": {\\n \\\"KYC\\\": \\\"low\\\",\\n \\\"AML\\\": \\\"low\\\",\\n \\\"Regulatory\\\": \\\"minimal\\\",\\n \\\"Internal Policy\\\": \\\"low\\\"\\n }\\n },\\n \\\"compliance_gaps_or_concerns\\\": [],\\n \\\"recommendations\\\": [\\n \\\"Continue to monitor compliance checks regularly to maintain low risk status.\\\",\\n \\\"Ensure that all documentation is kept up to date, especially for KYC and AML processes.\\\",\\n \\\"Conduct periodic training for staff on compliance policies and updates to regulations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 97.5\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 309,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 3.191733,
"end_time": "2025-07-15T12:50:42.056744",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.865011",
"timestamp": "2025-07-15T12:50:42.056744",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "### Credit Risk Assessment\n\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\n\n#### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\n\n#### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\n\n#### 3. Credit Utilization\n- **Credit Utilization**: 35.5%\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\n\n#### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Loan Burden Ratio**: 0.28 (28%)\n- **Total Outstanding**: 125000\n\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\n\n#### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\n\n### Risk Score Calculation\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\n\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 15 points (Excellent)\n- **Repayment Patterns**: 10 points (Good, but some late payments)\n- **Credit Utilization**: 10 points (Acceptable)\n- **Existing Loan Burden**: 10 points (Manageable)\n- **Overall Risk Profile**: 5 points (Stable)\n\n**Total Risk Score**: \n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\n\n### Default Risk Assessment\n- **Risk Score**: **70/100**\n- **Risk Level**: Moderate Risk\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\n\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 1130,
"model": "gpt-4o-mini",
"output_length": 3737,
"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": "### Credit Risk Assessment\n\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\n\n#### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\n\n#### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\n\n#### 3. Credit Utilization\n- **Credit Utilization**: 35.5%\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\n\n#### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Loan Burden Ratio**: 0.28 (28%)\n- **Total Outstanding**: 125000\n\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\n\n#### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\n\n### Risk Score Calculation\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\n\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 15 points (Excellent)\n- **Repayment Patterns**: 10 points (Good, but some late payments)\n- **Credit Utilization**: 10 points (Acceptable)\n- **Existing Loan Burden**: 10 points (Manageable)\n- **Overall Risk Profile**: 5 points (Stable)\n\n**Total Risk Score**: \n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\n\n### Default Risk Assessment\n- **Risk Score**: **70/100**\n- **Risk Level**: Moderate Risk\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\n\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\n__OUTPUTS__ {\"ai_response\": \"### Credit Risk Assessment\\n\\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\\n\\n#### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n\\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\\n\\n#### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n\\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\\n\\n#### 3. Credit Utilization\\n- **Credit Utilization**: 35.5%\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\\n\\n#### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Loan Burden Ratio**: 0.28 (28%)\\n- **Total Outstanding**: 125000\\n\\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\\n\\n#### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\\n\\n### Risk Score Calculation\\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\\n\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 15 points (Excellent)\\n- **Repayment Patterns**: 10 points (Good, but some late payments)\\n- **Credit Utilization**: 10 points (Acceptable)\\n- **Existing Loan Burden**: 10 points (Manageable)\\n- **Overall Risk Profile**: 5 points (Stable)\\n\\n**Total Risk Score**: \\n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\\n\\n### Default Risk Assessment\\n- **Risk Score**: **70/100**\\n- **Risk Level**: Moderate Risk\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\\n\\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\", \"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": 24.024823,
"end_time": "2025-07-15T12:51:16.881488",
"message_sent": true,
"start_time": "2025-07-15T12:50:52.856665",
"timestamp": "2025-07-15T12:51:16.881488",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "### Credit Risk Assessment\n\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\n\n#### 1. Credit Score and History\n- **CIBIL Score**: 720 (Good)\n- **Payment History**: 99% on-time payments\n- **Total Accounts**: 8 (6 active, 2 closed)\n- **Recent Inquiries**: 2\n\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\n\n#### 2. Repayment Patterns\n- **Defaults**: 0.0%\n- **30 Days Late**: 12.0%\n- **60 Days Late**: 2.5%\n- **90 Days Late**: 0.5%\n- **Never Missed Payments**: 85.0%\n\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\n\n#### 3. Credit Utilization\n- **Credit Utilization**: 35.5%\n- **Credit Limit Utilization**: 35.2%\n\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\n\n#### 4. Existing Loan Burden\n- **Number of Loans**: 2\n- **Total Monthly EMI**: 7700\n- **Loan Burden Ratio**: 0.28 (28%)\n- **Total Outstanding**: 125000\n\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\n\n#### 5. Overall Risk Profile\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\n- **Average Account Age**: 32 months\n- **Oldest Account Age**: 60 months\n- **Recent Credit Behavior**: Stable\n\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\n\n### Risk Score Calculation\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\n\n- **Credit Score**: 20 points (Good)\n- **Payment History**: 15 points (Excellent)\n- **Repayment Patterns**: 10 points (Good, but some late payments)\n- **Credit Utilization**: 10 points (Acceptable)\n- **Existing Loan Burden**: 10 points (Manageable)\n- **Overall Risk Profile**: 5 points (Stable)\n\n**Total Risk Score**: \n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\n\n### Default Risk Assessment\n- **Risk Score**: **70/100**\n- **Risk Level**: Moderate Risk\n\n### Recommendations\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\n\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\n__OUTPUTS__ {\"ai_response\": \"### Credit Risk Assessment\\n\\nBased on the provided credit data, we will analyze the various components that contribute to the overall default risk and calculate a risk score.\\n\\n#### 1. Credit Score and History\\n- **CIBIL Score**: 720 (Good)\\n- **Payment History**: 99% on-time payments\\n- **Total Accounts**: 8 (6 active, 2 closed)\\n- **Recent Inquiries**: 2\\n\\n**Analysis**: A CIBIL score of 720 is considered good, indicating a low likelihood of default. The payment history of 99% on-time payments further strengthens this assessment. The number of recent inquiries (2) is moderate and does not raise immediate concerns.\\n\\n#### 2. Repayment Patterns\\n- **Defaults**: 0.0%\\n- **30 Days Late**: 12.0%\\n- **60 Days Late**: 2.5%\\n- **90 Days Late**: 0.5%\\n- **Never Missed Payments**: 85.0%\\n\\n**Analysis**: The repayment behavior shows a very low default rate (0.0%), which is excellent. However, the 30 days late percentage (12.0%) is somewhat concerning, indicating that while the individual generally pays on time, there are instances of late payments. The 60 and 90 days late percentages are low, which is positive.\\n\\n#### 3. Credit Utilization\\n- **Credit Utilization**: 35.5%\\n- **Credit Limit Utilization**: 35.2%\\n\\n**Analysis**: A credit utilization rate of 35.5% is acceptable, as it is below the 40% threshold that typically raises red flags. This suggests that the individual is managing their credit well without overextending themselves.\\n\\n#### 4. Existing Loan Burden\\n- **Number of Loans**: 2\\n- **Total Monthly EMI**: 7700\\n- **Loan Burden Ratio**: 0.28 (28%)\\n- **Total Outstanding**: 125000\\n\\n**Analysis**: The loan burden ratio of 28% indicates that the individual is using a reasonable portion of their income for debt repayment. This is generally considered manageable, especially given the excellent repayment track record.\\n\\n#### 5. Overall Risk Profile\\n- **Credit Mix**: Diverse (credit cards, personal loans, auto loans)\\n- **Average Account Age**: 32 months\\n- **Oldest Account Age**: 60 months\\n- **Recent Credit Behavior**: Stable\\n\\n**Analysis**: The individual has a diverse credit mix, which is beneficial for credit scoring. The average account age is reasonable, and the oldest account indicates a long-standing credit history. The stable recent credit behavior suggests that there are no significant changes in financial circumstances.\\n\\n### Risk Score Calculation\\nTaking into account all the factors analyzed, we can assign a risk score based on the following criteria:\\n\\n- **Credit Score**: 20 points (Good)\\n- **Payment History**: 15 points (Excellent)\\n- **Repayment Patterns**: 10 points (Good, but some late payments)\\n- **Credit Utilization**: 10 points (Acceptable)\\n- **Existing Loan Burden**: 10 points (Manageable)\\n- **Overall Risk Profile**: 5 points (Stable)\\n\\n**Total Risk Score**: \\n- 20 + 15 + 10 + 10 + 10 + 5 = **70**\\n\\n### Default Risk Assessment\\n- **Risk Score**: **70/100**\\n- **Risk Level**: Moderate Risk\\n\\n### Recommendations\\n1. **Maintain Payment Discipline**: Continue to ensure timely payments to maintain the high payment history percentage and avoid late payments.\\n2. **Monitor Credit Utilization**: Aim to keep credit utilization below 30% to further improve the credit score.\\n3. **Limit New Credit Inquiries**: Avoid taking on new credit unless necessary, as this can impact the credit score.\\n4. **Consider Debt Reduction**: If possible, focus on paying down existing loans to reduce the overall outstanding balance and improve the loan burden ratio.\\n5. **Regular Credit Monitoring**: Keep an eye on credit reports for any discrepancies and ensure that all accounts are reported accurately.\\n\\nBy following these recommendations, the individual can improve their credit profile and reduce the risk of default further.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "evaluate_default_risk"
},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.275202,
"end_time": "2025-07-15T12:50:33.819336",
"message_sent": true,
"start_time": "2025-07-15T12:50:33.544134",
"timestamp": "2025-07-15T12:50:33.819336",
"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "extract_application_info"
},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "### Final Recommendation: APPROVE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: 6.5% (fixed)\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $198.66\n- **Prepayment Penalty**: None\n- **Repayment Schedule**: Monthly payments\n\n#### Risk Mitigation Measures:\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\n\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\n\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\n\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\n\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\n\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\n\n#### Confidence Level: 85\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.",
"execution_details": {
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"agent_type": "assistant",
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"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "### Final Recommendation: APPROVE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: 6.5% (fixed)\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $198.66\n- **Prepayment Penalty**: None\n- **Repayment Schedule**: Monthly payments\n\n#### Risk Mitigation Measures:\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\n\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\n\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\n\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\n\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\n\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\n\n#### Confidence Level: 85\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: APPROVE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: 6.5% (fixed)\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $198.66\\n- **Prepayment Penalty**: None\\n- **Repayment Schedule**: Monthly payments\\n\\n#### Risk Mitigation Measures:\\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\\n\\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\\n\\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\\n\\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\\n\\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\\n\\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\\n\\n#### Confidence Level: 85\\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "### Final Recommendation: APPROVE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: $10,000\n- **Interest Rate**: 6.5% (fixed)\n- **Loan Term**: 5 years\n- **Monthly EMI**: Approximately $198.66\n- **Prepayment Penalty**: None\n- **Repayment Schedule**: Monthly payments\n\n#### Risk Mitigation Measures:\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\n\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\n\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\n\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\n\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\n\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\n\n#### Confidence Level: 85\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: APPROVE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: $10,000\\n- **Interest Rate**: 6.5% (fixed)\\n- **Loan Term**: 5 years\\n- **Monthly EMI**: Approximately $198.66\\n- **Prepayment Penalty**: None\\n- **Repayment Schedule**: Monthly payments\\n\\n#### Risk Mitigation Measures:\\n1. **Monitoring**: Regular monitoring of the borrower\u0027s financial status and credit behavior for the duration of the loan.\\n2. **Financial Counseling**: Offer financial counseling to help the borrower manage their finances effectively and maintain a good credit score.\\n3. **Emergency Fund Requirement**: Encourage the borrower to maintain an emergency fund equivalent to at least 3 months of loan payments.\\n4. **Periodic Reviews**: Conduct periodic reviews of the borrower\u0027s income and debt situation to ensure continued ability to service the loan.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application is complete and accurate, with no missing fields and a high overall application quality score of 85. The only red flag is the low requested amount for a home purchase, but this does not significantly impact the decision as the borrower has a stable income and good credit history.\\n\\n2. **Document Verification**: All documents have been verified successfully with a 100% success rate, indicating that the information provided is consistent and reliable.\\n\\n3. **Income Assessment**: The borrower has a stable income of $75,000 annually, with a debt-to-income ratio of 35.9%, which is below the acceptable threshold of 40%. This indicates that the borrower has adequate capacity to service the loan.\\n\\n4. **Credit Risk**: The borrower has a good credit score of 720, with a 99% on-time payment history. The repayment patterns show a very low default rate, and the credit utilization is acceptable. Although there are some instances of late payments, the overall credit behavior is stable.\\n\\n5. **Compliance**: The borrower is compliant with KYC and AML regulations, with a low overall risk assessment. This adds an additional layer of confidence in the borrower\u0027s reliability.\\n\\n6. **Overall Risk Profile**: The overall risk profile is moderate, but the combination of stable income, good credit history, and compliance status supports the decision to approve the loan.\\n\\n#### Confidence Level: 85\\nThe confidence level in this decision is high, given the thorough assessment of the borrower\u0027s financial situation, credit history, and compliance status. The borrower demonstrates the ability to repay the loan, and the risk mitigation measures will help ensure continued financial stability.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"proposed_emi\": 41.67\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Strong\",\n \"details\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"salary_credits_consistent\": true\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"discrepancies_found\": false,\n \"tax_compliance_score\": 92.0,\n \"returns_filed_consistently\": true,\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\"\n }\n },\n \"recommendations\": [\n \"Continue maintaining current employment and financial discipline.\",\n \"Consider increasing savings to further improve financial stability.\",\n \"Monitor any changes in income or expenses that could affect debt servicing.\"\n ],\n \"overall_income_adequacy_score\": 88\n }\n}\n```",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"proposed_emi\": 41.67\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Strong\",\n \"details\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"salary_credits_consistent\": true\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"discrepancies_found\": false,\n \"tax_compliance_score\": 92.0,\n \"returns_filed_consistently\": true,\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\"\n }\n },\n \"recommendations\": [\n \"Continue maintaining current employment and financial discipline.\",\n \"Consider increasing savings to further improve financial stability.\",\n \"Monitor any changes in income or expenses that could affect debt servicing.\"\n ],\n \"overall_income_adequacy_score\": 88\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"proposed_emi\\\": 41.67\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Strong\\\",\\n \\\"details\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"salary_credits_consistent\\\": true\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"discrepancies_found\\\": false,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\"\\n }\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue maintaining current employment and financial discipline.\\\",\\n \\\"Consider increasing savings to further improve financial stability.\\\",\\n \\\"Monitor any changes in income or expenses that could affect debt servicing.\\\"\\n ],\\n \\\"overall_income_adequacy_score\\\": 88\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"annual_net_income\": 81600,\n \"monthly_net_income\": 6800,\n \"employment_duration\": \"2.5 years\",\n \"salary_consistency\": true,\n \"recent_increment\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.359,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true,\n \"proposed_emi\": 41.67\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Strong\",\n \"details\": {\n \"financial_discipline_score\": 85.5,\n \"account_balance_trend\": \"stable\",\n \"bounced_transactions\": 0,\n \"irregular_transactions\": false,\n \"salary_credits_consistent\": true\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"discrepancies_found\": false,\n \"tax_compliance_score\": 92.0,\n \"returns_filed_consistently\": true,\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\"\n }\n },\n \"recommendations\": [\n \"Continue maintaining current employment and financial discipline.\",\n \"Consider increasing savings to further improve financial stability.\",\n \"Monitor any changes in income or expenses that could affect debt servicing.\"\n ],\n \"overall_income_adequacy_score\": 88\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"annual_net_income\\\": 81600,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"employment_duration\\\": \\\"2.5 years\\\",\\n \\\"salary_consistency\\\": true,\\n \\\"recent_increment\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.359,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true,\\n \\\"proposed_emi\\\": 41.67\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Strong\\\",\\n \\\"details\\\": {\\n \\\"financial_discipline_score\\\": 85.5,\\n \\\"account_balance_trend\\\": \\\"stable\\\",\\n \\\"bounced_transactions\\\": 0,\\n \\\"irregular_transactions\\\": false,\\n \\\"salary_credits_consistent\\\": true\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"discrepancies_found\\\": false,\\n \\\"tax_compliance_score\\\": 92.0,\\n \\\"returns_filed_consistently\\\": true,\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\"\\n }\\n },\\n \\\"recommendations\\\": [\\n \\\"Continue maintaining current employment and financial discipline.\\\",\\n \\\"Consider increasing savings to further improve financial stability.\\\",\\n \\\"Monitor any changes in income or expenses that could affect debt servicing.\\\"\\n ],\\n \\\"overall_income_adequacy_score\\\": 88\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "Route selected: manual_review_path\n__OUTPUTS__ {\"router_type\": \"condition\", \"selected_route\": \"manual_review_path\", \"route_reason\": \"no_conditions_matched\", \"evaluation_details\": {}, \"all_conditions_checked\": [{\"name\": \"high_risk_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50\", \"result\": false, \"route\": \"decline_path\"}, {\"name\": \"conditional_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700\", \"result\": false, \"route\": \"conditional_path\"}, {\"name\": \"standard_approval_path\", \"condition\": \"${calculate_credit_score.internal_credit_score} \u003e= 700\", \"result\": false, \"route\": \"approval_path\"}], \"duration_seconds\": 0.000801, \"started_at\": \"2025-07-15T12:54:20.606893\", \"ended_at\": \"2025-07-15T12:54:20.607694\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.433833,
"end_time": "2025-07-15T12:54:20.905019",
"message_sent": true,
"start_time": "2025-07-15T12:54:20.471186",
"timestamp": "2025-07-15T12:54:20.905019",
"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\": 0.000801, \"started_at\": \"2025-07-15T12:54:20.606893\", \"ended_at\": \"2025-07-15T12:54:20.607694\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T12:54:20.606893",
"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": 0.293733,
"end_time": "2025-07-15T12:50:34.069453",
"message_sent": true,
"start_time": "2025-07-15T12:50:33.775720",
"timestamp": "2025-07-15T12:50:34.069453",
"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": 0.464934,
"end_time": "2025-07-15T12:50:38.489727",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.024793",
"timestamp": "2025-07-15T12:50:38.489727",
"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": 0.798491,
"end_time": "2025-07-15T12:50:38.906454",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.107963",
"timestamp": "2025-07-15T12:50:38.906454",
"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": 0.518039,
"end_time": "2025-07-15T12:50:42.087344",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.569305",
"timestamp": "2025-07-15T12:50:42.087344",
"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": 0.341896,
"end_time": "2025-07-15T12:50:38.324776",
"message_sent": true,
"start_time": "2025-07-15T12:50:37.982880",
"timestamp": "2025-07-15T12:50:38.324776",
"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": 0.684357,
"end_time": "2025-07-15T12:50:38.750638",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.066281",
"timestamp": "2025-07-15T12:50:38.750638",
"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": 0.634493,
"end_time": "2025-07-15T12:50:41.963916",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.329423",
"timestamp": "2025-07-15T12:50:41.963916",
"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": 0.000801,
"ended_at": "2025-07-15T12:54:20.607694",
"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\": 0.000801, \"started_at\": \"2025-07-15T12:54:20.606893\", \"ended_at\": \"2025-07-15T12:54:20.607694\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.433833,
"end_time": "2025-07-15T12:54:20.905019",
"message_sent": true,
"start_time": "2025-07-15T12:54:20.471186",
"timestamp": "2025-07-15T12:54:20.905019",
"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\": 0.000801, \"started_at\": \"2025-07-15T12:54:20.606893\", \"ended_at\": \"2025-07-15T12:54:20.607694\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T12:54:20.606893",
"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": 0.293733,
"end_time": "2025-07-15T12:50:34.069453",
"message_sent": true,
"start_time": "2025-07-15T12:50:33.775720",
"timestamp": "2025-07-15T12:50:34.069453",
"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": 0.464934,
"end_time": "2025-07-15T12:50:38.489727",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.024793",
"timestamp": "2025-07-15T12:50:38.489727",
"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": 0.798491,
"end_time": "2025-07-15T12:50:38.906454",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.107963",
"timestamp": "2025-07-15T12:50:38.906454",
"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": 0.518039,
"end_time": "2025-07-15T12:50:42.087344",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.569305",
"timestamp": "2025-07-15T12:50:42.087344",
"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": 0.341896,
"end_time": "2025-07-15T12:50:38.324776",
"message_sent": true,
"start_time": "2025-07-15T12:50:37.982880",
"timestamp": "2025-07-15T12:50:38.324776",
"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": 0.684357,
"end_time": "2025-07-15T12:50:38.750638",
"message_sent": true,
"start_time": "2025-07-15T12:50:38.066281",
"timestamp": "2025-07-15T12:50:38.750638",
"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": 0.634493,
"end_time": "2025-07-15T12:50:41.963916",
"message_sent": true,
"start_time": "2025-07-15T12:50:41.329423",
"timestamp": "2025-07-15T12:50:41.963916",
"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
}
}