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": 0.380654,
"end_time": "2025-07-15T12:23:59.743467",
"message_sent": true,
"start_time": "2025-07-15T12:23:59.362813",
"timestamp": "2025-07-15T12:23:59.743467",
"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": 0.47306,
"end_time": "2025-07-15T12:20:35.914998",
"message_sent": true,
"start_time": "2025-07-15T12:20:35.441938",
"timestamp": "2025-07-15T12:20:35.914998",
"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": 0.304265,
"end_time": "2025-07-15T12:20:44.515644",
"message_sent": true,
"start_time": "2025-07-15T12:20:44.211379",
"timestamp": "2025-07-15T12:20:44.515644",
"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": 0.380301,
"end_time": "2025-07-15T12:20:35.779224",
"message_sent": true,
"start_time": "2025-07-15T12:20:35.398923",
"timestamp": "2025-07-15T12:20:35.779224",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are filled out correctly, indicating a complete and accurate application.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 858,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are filled out correctly, indicating a complete and accurate application.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are filled out correctly, indicating a complete and accurate application.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\\\"\\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": 4.420337,
"end_time": "2025-07-15T12:20:33.049341",
"message_sent": true,
"start_time": "2025-07-15T12:20:28.629004",
"timestamp": "2025-07-15T12:20:33.049341",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are filled out correctly, indicating a complete and accurate application.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are filled out correctly, indicating a complete and accurate application.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\\\"\\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": 0.340389,
"end_time": "2025-07-15T12:20:44.781130",
"message_sent": true,
"start_time": "2025-07-15T12:20:44.440741",
"timestamp": "2025-07-15T12:20:44.781130",
"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/tmp5duyznru.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/tmp5duyznru.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": 0.330756,
"end_time": "2025-07-15T12:20:36.514295",
"message_sent": true,
"start_time": "2025-07-15T12:20:36.183539",
"timestamp": "2025-07-15T12:20:36.514295",
"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": 0.226253,
"end_time": "2025-07-15T12:20:44.181127",
"message_sent": true,
"start_time": "2025-07-15T12:20:43.954874",
"timestamp": "2025-07-15T12:20:44.181127",
"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\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high at 95.5.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\",\n \"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\",\n \"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1285,
"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\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high at 95.5.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\",\n \"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\",\n \"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high at 95.5.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\\\",\\n \\\"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\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": 5.946081,
"end_time": "2025-07-15T12:24:06.270849",
"message_sent": true,
"start_time": "2025-07-15T12:24:00.324768",
"timestamp": "2025-07-15T12:24:06.270849",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high at 95.5.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\",\n \"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\",\n \"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high at 95.5.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\\\",\\n \\\"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 336,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.403497,
"end_time": "2025-07-15T12:20:35.531038",
"message_sent": true,
"start_time": "2025-07-15T12:20:33.127541",
"timestamp": "2025-07-15T12:20:35.531038",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \"excellent,\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\n\n### 2. Repayment Patterns\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\n\n### 4. Existing Loan Burden\n- The borrower has two existing loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\n\n### 5. Overall Risk Profile\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- Excellent repayment history: Lowers risk significantly.\n- Reasonable loan burden ratio: Lowers risk.\n- Unresolved credit score and history: Increases risk.\n\n### Risk Score: \n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\n\n### Recommendations:\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\n\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 561,
"model": "gpt-4o-mini",
"output_length": 3223,
"provider": "openai",
"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \"excellent,\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\n\n### 2. Repayment Patterns\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\n\n### 4. Existing Loan Burden\n- The borrower has two existing loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\n\n### 5. Overall Risk Profile\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- Excellent repayment history: Lowers risk significantly.\n- Reasonable loan burden ratio: Lowers risk.\n- Unresolved credit score and history: Increases risk.\n\n### Risk Score: \n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\n\n### Recommendations:\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\n\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \\\"excellent,\\\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\\n\\n### 2. Repayment Patterns\\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\\n\\n### 4. Existing Loan Burden\\n- The borrower has two existing loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\\n\\n### 5. Overall Risk Profile\\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- Excellent repayment history: Lowers risk significantly.\\n- Reasonable loan burden ratio: Lowers risk.\\n- Unresolved credit score and history: Increases risk.\\n\\n### Risk Score: \\n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\\n\\n### Recommendations:\\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\\n\\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\", \"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": 16.625419,
"end_time": "2025-07-15T12:21:01.354349",
"message_sent": true,
"start_time": "2025-07-15T12:20:44.728930",
"timestamp": "2025-07-15T12:21:01.354349",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \"excellent,\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\n\n### 2. Repayment Patterns\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\n\n### 4. Existing Loan Burden\n- The borrower has two existing loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\n\n### 5. Overall Risk Profile\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- Excellent repayment history: Lowers risk significantly.\n- Reasonable loan burden ratio: Lowers risk.\n- Unresolved credit score and history: Increases risk.\n\n### Risk Score: \n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\n\n### Recommendations:\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\n\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \\\"excellent,\\\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\\n\\n### 2. Repayment Patterns\\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\\n\\n### 4. Existing Loan Burden\\n- The borrower has two existing loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\\n\\n### 5. Overall Risk Profile\\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- Excellent repayment history: Lowers risk significantly.\\n- Reasonable loan burden ratio: Lowers risk.\\n- Unresolved credit score and history: Increases risk.\\n\\n### Risk Score: \\n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\\n\\n### Recommendations:\\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\\n\\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\", \"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"
},
"execution_summary": {
"completed_tasks": 25,
"dependencies_detected": false,
"end_time": "2025-07-15T12:30:15.924480",
"execution_mode": "distributed",
"start_time": "2025-07-15T12:20:26.394946",
"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": 0.238727,
"end_time": "2025-07-15T12:20:28.296923",
"message_sent": true,
"start_time": "2025-07-15T12:20:28.058196",
"timestamp": "2025-07-15T12:20:28.296923",
"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "extract_application_info"
},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.",
"execution_details": {
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"execution_details": {
"agent_type": "assistant",
"input_length": 484,
"model": "gpt-4o-mini",
"output_length": 1888,
"provider": "openai",
"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but inferred to be reasonable based on income stability.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"potential_risks\": [\n \"Economic downturn affecting job stability\",\n \"Unexpected expenses that could impact debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Consider reducing existing debt to improve financial flexibility.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but inferred to be reasonable based on income stability.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"potential_risks\": [\n \"Economic downturn affecting job stability\",\n \"Unexpected expenses that could impact debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Consider reducing existing debt to improve financial flexibility.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but inferred to be reasonable based on income stability.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"potential_risks\\\": [\\n \\\"Economic downturn affecting job stability\\\",\\n \\\"Unexpected expenses that could impact debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Consider reducing existing debt to improve financial flexibility.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but inferred to be reasonable based on income stability.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"potential_risks\": [\n \"Economic downturn affecting job stability\",\n \"Unexpected expenses that could impact debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Consider reducing existing debt to improve financial flexibility.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but inferred to be reasonable based on income stability.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"potential_risks\\\": [\\n \\\"Economic downturn affecting job stability\\\",\\n \\\"Unexpected expenses that could impact debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Consider reducing existing debt to improve financial flexibility.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "__OUTPUTS__ {\"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": 0.304265,
"end_time": "2025-07-15T12:20:44.515644",
"message_sent": true,
"start_time": "2025-07-15T12:20:44.211379",
"timestamp": "2025-07-15T12:20:44.515644",
"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": 0.380301,
"end_time": "2025-07-15T12:20:35.779224",
"message_sent": true,
"start_time": "2025-07-15T12:20:35.398923",
"timestamp": "2025-07-15T12:20:35.779224",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are filled out correctly, indicating a complete and accurate application.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 858,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are filled out correctly, indicating a complete and accurate application.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are filled out correctly, indicating a complete and accurate application.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\\\"\\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": 4.420337,
"end_time": "2025-07-15T12:20:33.049341",
"message_sent": true,
"start_time": "2025-07-15T12:20:28.629004",
"timestamp": "2025-07-15T12:20:33.049341",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are filled out correctly, indicating a complete and accurate application.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are filled out correctly, indicating a complete and accurate application.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies were noted in the provided information. All data appears to align with standard expectations for a loan application.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified in the application data. The information provided is coherent and consistent.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing fields or inconsistencies. The high quality score reflects the thoroughness of the submission.\\\"\\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": 0.340389,
"end_time": "2025-07-15T12:20:44.781130",
"message_sent": true,
"start_time": "2025-07-15T12:20:44.440741",
"timestamp": "2025-07-15T12:20:44.781130",
"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/tmp5duyznru.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/tmp5duyznru.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": 0.330756,
"end_time": "2025-07-15T12:20:36.514295",
"message_sent": true,
"start_time": "2025-07-15T12:20:36.183539",
"timestamp": "2025-07-15T12:20:36.514295",
"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": 0.226253,
"end_time": "2025-07-15T12:20:44.181127",
"message_sent": true,
"start_time": "2025-07-15T12:20:43.954874",
"timestamp": "2025-07-15T12:20:44.181127",
"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\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high at 95.5.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\",\n \"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\",\n \"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1285,
"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\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high at 95.5.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\",\n \"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\",\n \"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high at 95.5.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\\\",\\n \\\"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\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": 5.946081,
"end_time": "2025-07-15T12:24:06.270849",
"message_sent": true,
"start_time": "2025-07-15T12:24:00.324768",
"timestamp": "2025-07-15T12:24:06.270849",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high at 95.5.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\",\n \"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\",\n \"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high at 95.5.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential money laundering risks and regulatory penalties.\\\",\\n \\\"Unresolved regulatory compliance check indicates potential violations of applicable laws and regulations.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering and ensure compliance with AML regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues to identify and rectify any potential violations.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 336,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.403497,
"end_time": "2025-07-15T12:20:35.531038",
"message_sent": true,
"start_time": "2025-07-15T12:20:33.127541",
"timestamp": "2025-07-15T12:20:35.531038",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \"excellent,\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\n\n### 2. Repayment Patterns\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\n\n### 4. Existing Loan Burden\n- The borrower has two existing loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\n\n### 5. Overall Risk Profile\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- Excellent repayment history: Lowers risk significantly.\n- Reasonable loan burden ratio: Lowers risk.\n- Unresolved credit score and history: Increases risk.\n\n### Risk Score: \n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\n\n### Recommendations:\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\n\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.",
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"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
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"output": "To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \"excellent,\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\n\n### 2. Repayment Patterns\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\n\n### 4. Existing Loan Burden\n- The borrower has two existing loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\n\n### 5. Overall Risk Profile\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- Excellent repayment history: Lowers risk significantly.\n- Reasonable loan burden ratio: Lowers risk.\n- Unresolved credit score and history: Increases risk.\n\n### Risk Score: \n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\n\n### Recommendations:\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\n\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \\\"excellent,\\\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\\n\\n### 2. Repayment Patterns\\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\\n\\n### 4. Existing Loan Burden\\n- The borrower has two existing loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\\n\\n### 5. Overall Risk Profile\\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- Excellent repayment history: Lowers risk significantly.\\n- Reasonable loan burden ratio: Lowers risk.\\n- Unresolved credit score and history: Increases risk.\\n\\n### Risk Score: \\n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\\n\\n### Recommendations:\\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\\n\\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
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"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \"excellent,\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\n\n### 2. Repayment Patterns\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\n\n### 4. Existing Loan Burden\n- The borrower has two existing loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\n\n### 5. Overall Risk Profile\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nGiven the factors analyzed:\n- Excellent repayment history: Lowers risk significantly.\n- Reasonable loan burden ratio: Lowers risk.\n- Unresolved credit score and history: Increases risk.\n\n### Risk Score: \n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\n\n### Recommendations:\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\n\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the key factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the borrower\u0027s creditworthiness based on this crucial metric. A low score would typically indicate higher risk, while a high score would suggest lower risk.\\n- **Credit History**: The credit history is also unresolved. However, the repayment track record is noted as \\\"excellent,\\\" which is a positive indicator. This suggests that the borrower has a history of making timely payments.\\n\\n### 2. Repayment Patterns\\n- The repayment track record is excellent, indicating that the borrower has consistently met their repayment obligations. This is a strong positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the borrower is not over-leveraged and can manage their debts effectively. A ratio below 30% is generally considered good.\\n\\n### 4. Existing Loan Burden\\n- The borrower has two existing loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- Total monthly EMI is 7700, which is manageable given the loan burden ratio of 28%. This indicates that the borrower is likely to be able to meet their monthly obligations.\\n\\n### 5. Overall Risk Profile\\n- Considering the excellent repayment track record, reasonable loan burden ratio, and manageable existing loans, the overall risk profile appears to be favorable. However, the unresolved credit score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nGiven the factors analyzed:\\n- Excellent repayment history: Lowers risk significantly.\\n- Reasonable loan burden ratio: Lowers risk.\\n- Unresolved credit score and history: Increases risk.\\n\\n### Risk Score: \\n- Based on the analysis, I would assign a risk score of **35 out of 100**. This indicates a relatively low risk of default, primarily due to the excellent repayment track record and manageable loan burden. However, the unresolved credit score and history prevent a lower score.\\n\\n### Recommendations:\\n1. **Resolve Credit Score**: Obtain and review the CIBIL score to get a complete picture of creditworthiness.\\n2. **Monitor Credit History**: Ensure that all credit accounts are being reported accurately and that there are no discrepancies.\\n3. **Maintain Repayment Discipline**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, consider paying down existing loans to further improve the loan burden ratio.\\n5. **Financial Planning**: Develop a financial plan to manage future borrowing and ensure that any new loans do not significantly increase the loan burden ratio.\\n\\nBy addressing the unresolved credit score and maintaining good repayment habits, the borrower can further reduce their default risk and improve their overall credit profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
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},
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"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",
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"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application.\\n - **Document Verification**: The unresolved document verification raises red flags about the authenticity or validity of the submitted documents, which is crucial for establishing trust in the applicant\u0027s financial situation.\\n - **Income Assessment**: An unresolved income assessment means we cannot confirm the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and past borrowing behavior.\\n - **Default Risk**: An unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for risk assessment.\\n - **Compliance**: Unresolved compliance issues suggest potential legal or regulatory concerns that could expose the lender to risks.\\n - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and we cannot proceed with the loan application. \\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the critical nature of the unresolved issues, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmp4599zq4q.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
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"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmp4599zq4q.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
"status": "FAILED",
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"income_assessment": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but inferred to be reasonable based on income stability.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"potential_risks\": [\n \"Economic downturn affecting job stability\",\n \"Unexpected expenses that could impact debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Consider reducing existing debt to improve financial flexibility.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 782,
"model": "gpt-4o-mini",
"output_length": 1463,
"provider": "openai",
"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but inferred to be reasonable based on income stability.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"potential_risks\": [\n \"Economic downturn affecting job stability\",\n \"Unexpected expenses that could impact debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Consider reducing existing debt to improve financial flexibility.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but inferred to be reasonable based on income stability.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"potential_risks\\\": [\\n \\\"Economic downturn affecting job stability\\\",\\n \\\"Unexpected expenses that could impact debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Consider reducing existing debt to improve financial flexibility.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
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},
"duration_seconds": 8.865295,
"end_time": "2025-07-15T12:20:45.334974",
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"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"Stable\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Adequate\",\n \"details\": {\n \"monthly_net_income\": 6800,\n \"total_debt_payments\": 2441.67,\n \"debt_to_income_ratio\": 0.3591,\n \"proposed_emi\": 41.67,\n \"max_allowed_ratio\": 0.4,\n \"ratio_acceptable\": true\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Good\",\n \"details\": {\n \"existing_debt_payments\": 2400,\n \"debt_to_income_ratio\": 0.3591,\n \"monthly_net_income\": 6800,\n \"savings_rate\": \"Not provided, but inferred to be reasonable based on income stability.\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Low\",\n \"details\": {\n \"potential_risks\": [\n \"Economic downturn affecting job stability\",\n \"Unexpected expenses that could impact debt servicing\"\n ],\n \"recommendations\": [\n \"Maintain an emergency fund covering at least 3-6 months of expenses.\",\n \"Consider reducing existing debt to improve financial flexibility.\"\n ]\n }\n },\n \"overall_income_adequacy_score\": 85\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"income_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"Stable\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Adequate\\\",\\n \\\"details\\\": {\\n \\\"monthly_net_income\\\": 6800,\\n \\\"total_debt_payments\\\": 2441.67,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"proposed_emi\\\": 41.67,\\n \\\"max_allowed_ratio\\\": 0.4,\\n \\\"ratio_acceptable\\\": true\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Good\\\",\\n \\\"details\\\": {\\n \\\"existing_debt_payments\\\": 2400,\\n \\\"debt_to_income_ratio\\\": 0.3591,\\n \\\"monthly_net_income\\\": 6800,\\n \\\"savings_rate\\\": \\\"Not provided, but inferred to be reasonable based on income stability.\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Low\\\",\\n \\\"details\\\": {\\n \\\"potential_risks\\\": [\\n \\\"Economic downturn affecting job stability\\\",\\n \\\"Unexpected expenses that could impact debt servicing\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Maintain an emergency fund covering at least 3-6 months of expenses.\\\",\\n \\\"Consider reducing existing debt to improve financial flexibility.\\\"\\n ]\\n }\\n },\\n \\\"overall_income_adequacy_score\\\": 85\\n }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
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"status": "completed",
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"task_id": "income_assessment"
},
"internal_policy_check": {
"age_criteria_met": true,
"credit_score_threshold_met": true,
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"output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
"return_code": 0,
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},
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},
"geographic_restrictions_met": true,
"income_criteria_met": true,
"loan_amount_within_limits": true,
"ltv_ratio_acceptable": true,
"output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
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"status": "completed",
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"task_id": "internal_policy_check"
},
"kyc_compliance_check": {
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"compliance_score": 98.5,
"documents_complete": true,
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"output": "__OUTPUTS__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
"return_code": 0,
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},
"duration_seconds": 0.339808,
"end_time": "2025-07-15T12:23:59.423087",
"message_sent": true,
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},
"identity_verified": true,
"income_verified": true,
"kyc_status": "compliant",
"last_updated": "2024-07-15",
"output": "__OUTPUTS__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
"regulatory_requirements_met": true,
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"consumer_protection_compliant": true,
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"actual_result": {
"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
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},
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},
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"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"rbi_guidelines_met": true,
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"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"
}
],
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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\": 0.003666, \"started_at\": \"2025-07-15T12:24:05.880562\", \"ended_at\": \"2025-07-15T12:24:05.884228\"}",
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"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",
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"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",
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},
"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": 0.58948,
"end_time": "2025-07-15T12:20:36.073442",
"message_sent": true,
"start_time": "2025-07-15T12:20:35.483962",
"timestamp": "2025-07-15T12:20:36.073442",
"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": 0.003666,
"ended_at": "2025-07-15T12:24:05.884228",
"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\": 0.003666, \"started_at\": \"2025-07-15T12:24:05.880562\", \"ended_at\": \"2025-07-15T12:24:05.884228\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.211624,
"end_time": "2025-07-15T12:24:05.998207",
"message_sent": true,
"start_time": "2025-07-15T12:24:05.786583",
"timestamp": "2025-07-15T12:24:05.998207",
"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\": 0.003666, \"started_at\": \"2025-07-15T12:24:05.880562\", \"ended_at\": \"2025-07-15T12:24:05.884228\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T12:24:05.880562",
"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": 0.344098,
"end_time": "2025-07-15T12:20:28.668551",
"message_sent": true,
"start_time": "2025-07-15T12:20:28.324453",
"timestamp": "2025-07-15T12:20:28.668551",
"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": 0.572154,
"end_time": "2025-07-15T12:20:32.677838",
"message_sent": true,
"start_time": "2025-07-15T12:20:32.105684",
"timestamp": "2025-07-15T12:20:32.677838",
"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": 0.958385,
"end_time": "2025-07-15T12:20:33.171125",
"message_sent": true,
"start_time": "2025-07-15T12:20:32.212740",
"timestamp": "2025-07-15T12:20:33.171125",
"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": 0.568644,
"end_time": "2025-07-15T12:20:36.283911",
"message_sent": true,
"start_time": "2025-07-15T12:20:35.715267",
"timestamp": "2025-07-15T12:20:36.283911",
"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": 0.413427,
"end_time": "2025-07-15T12:20:32.467943",
"message_sent": true,
"start_time": "2025-07-15T12:20:32.054516",
"timestamp": "2025-07-15T12:20:32.467943",
"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": 0.824621,
"end_time": "2025-07-15T12:20:32.987733",
"message_sent": true,
"start_time": "2025-07-15T12:20:32.163112",
"timestamp": "2025-07-15T12:20:32.987733",
"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": 0.58948,
"end_time": "2025-07-15T12:20:36.073442",
"message_sent": true,
"start_time": "2025-07-15T12:20:35.483962",
"timestamp": "2025-07-15T12:20:36.073442",
"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
}
}