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": 0.335057,
"end_time": "2025-07-15T12:04:48.789403",
"message_sent": true,
"start_time": "2025-07-15T12:04:48.454346",
"timestamp": "2025-07-15T12:04:48.789403",
"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": 0.530196,
"end_time": "2025-07-15T11:58:18.639934",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.109738",
"timestamp": "2025-07-15T11:58:18.639934",
"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": 0.361621,
"end_time": "2025-07-15T12:01:30.788950",
"message_sent": true,
"start_time": "2025-07-15T12:01:30.427329",
"timestamp": "2025-07-15T12:01:30.788950",
"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": 0.444225,
"end_time": "2025-07-15T11:58:18.512752",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.068527",
"timestamp": "2025-07-15T11:58:18.512752",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields. All required information has been provided and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\"\n },\n \"overall_application_quality_score\": 90,\n \"overall_assessment\": \"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1156,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields. All required information has been provided and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\"\n },\n \"overall_application_quality_score\": 90,\n \"overall_assessment\": \"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields. All required information has been provided and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 90,\\n \\\"overall_assessment\\\": \\\"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\\\"\\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": 4.923143,
"end_time": "2025-07-15T11:58:15.575348",
"message_sent": true,
"start_time": "2025-07-15T11:58:10.652205",
"timestamp": "2025-07-15T11:58:15.575348",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields. All required information has been provided and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\"\n },\n \"overall_application_quality_score\": 90,\n \"overall_assessment\": \"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields. All required information has been provided and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 90,\\n \\\"overall_assessment\\\": \\\"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\\\"\\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": 0.428797,
"end_time": "2025-07-15T12:01:31.137926",
"message_sent": true,
"start_time": "2025-07-15T12:01:30.709129",
"timestamp": "2025-07-15T12:01:31.137926",
"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/tmpz55_8pw5.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/tmpz55_8pw5.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": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpycuthhxd.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_max_debt_to_income_ratio\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/tmpycuthhxd.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_max_debt_to_income_ratio\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_debt_to_income"
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.319086,
"end_time": "2025-07-15T12:01:30.477880",
"message_sent": true,
"start_time": "2025-07-15T12:01:30.158794",
"timestamp": "2025-07-15T12:01:30.477880",
"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 \"compliance_assessment\": {\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": \"High risk due to unresolved KYC, AML, and regulatory compliance issues.\",\n \"compliance_gaps_or_concerns\": [\n {\n \"issue\": \"KYC Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\"\n },\n {\n \"issue\": \"AML Screening\",\n \"status\": \"Unresolved\",\n \"concern\": \"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\"\n },\n {\n \"issue\": \"Regulatory Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Non-compliance with regulatory standards can result in legal repercussions and fines.\"\n }\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\",\n \"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\",\n \"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\",\n \"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1359,
"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 \"compliance_assessment\": {\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": \"High risk due to unresolved KYC, AML, and regulatory compliance issues.\",\n \"compliance_gaps_or_concerns\": [\n {\n \"issue\": \"KYC Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\"\n },\n {\n \"issue\": \"AML Screening\",\n \"status\": \"Unresolved\",\n \"concern\": \"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\"\n },\n {\n \"issue\": \"Regulatory Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Non-compliance with regulatory standards can result in legal repercussions and fines.\"\n }\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\",\n \"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\",\n \"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\",\n \"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": \\\"High risk due to unresolved KYC, AML, and regulatory compliance issues.\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n {\\n \\\"issue\\\": \\\"KYC Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"AML Screening\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Non-compliance with regulatory standards can result in legal repercussions and fines.\\\"\\n }\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\\\",\\n \\\"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\\\",\\n \\\"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\\\",\\n \\\"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n }\\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": 7.037302,
"end_time": "2025-07-15T12:04:56.369897",
"message_sent": true,
"start_time": "2025-07-15T12:04:49.332595",
"timestamp": "2025-07-15T12:04:56.369897",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"compliance_assessment\": {\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": \"High risk due to unresolved KYC, AML, and regulatory compliance issues.\",\n \"compliance_gaps_or_concerns\": [\n {\n \"issue\": \"KYC Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\"\n },\n {\n \"issue\": \"AML Screening\",\n \"status\": \"Unresolved\",\n \"concern\": \"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\"\n },\n {\n \"issue\": \"Regulatory Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Non-compliance with regulatory standards can result in legal repercussions and fines.\"\n }\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\",\n \"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\",\n \"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\",\n \"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": \\\"High risk due to unresolved KYC, AML, and regulatory compliance issues.\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n {\\n \\\"issue\\\": \\\"KYC Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"AML Screening\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Non-compliance with regulatory standards can result in legal repercussions and fines.\\\"\\n }\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\\\",\\n \\\"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\\\",\\n \\\"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\\\",\\n \\\"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n }\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 336,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 1.901975,
"end_time": "2025-07-15T11:58:18.194819",
"message_sent": true,
"start_time": "2025-07-15T11:58:16.292844",
"timestamp": "2025-07-15T11:58:18.194819",
"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 evaluate the various factors mentioned:\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is described as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\n\n### Risk Score Calculation\nGiven the information provided, we can assign a risk score based on the factors analyzed:\n\n- **Credit Score**: Unresolved (assumed neutral impact)\n- **Credit History**: Excellent (low risk)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (moderate risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\n### Risk Score\n- **Credit Score Impact**: 50 (neutral)\n- **Credit History Impact**: 20 (excellent)\n- **Repayment Patterns Impact**: 15 (excellent)\n- **Credit Utilization Impact**: 25 (moderate)\n- **Existing Loan Burden Impact**: 15 (manageable)\n\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\n\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\n\n**Final Risk Score = (125 / 200) * 100 = 62.5**\n\n### Conclusion\n**Final Risk Score**: **63** (rounded)\n\n### Recommendations\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\n\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 561,
"model": "gpt-4o-mini",
"output_length": 3565,
"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 evaluate the various factors mentioned:\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is described as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\n\n### Risk Score Calculation\nGiven the information provided, we can assign a risk score based on the factors analyzed:\n\n- **Credit Score**: Unresolved (assumed neutral impact)\n- **Credit History**: Excellent (low risk)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (moderate risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\n### Risk Score\n- **Credit Score Impact**: 50 (neutral)\n- **Credit History Impact**: 20 (excellent)\n- **Repayment Patterns Impact**: 15 (excellent)\n- **Credit Utilization Impact**: 25 (moderate)\n- **Existing Loan Burden Impact**: 15 (manageable)\n\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\n\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\n\n**Final Risk Score = (125 / 200) * 100 = 62.5**\n\n### Conclusion\n**Final Risk Score**: **63** (rounded)\n\n### Recommendations\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\n\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the various factors mentioned:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is described as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\\n\\n### Risk Score Calculation\\nGiven the information provided, we can assign a risk score based on the factors analyzed:\\n\\n- **Credit Score**: Unresolved (assumed neutral impact)\\n- **Credit History**: Excellent (low risk)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (moderate risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\n### Risk Score\\n- **Credit Score Impact**: 50 (neutral)\\n- **Credit History Impact**: 20 (excellent)\\n- **Repayment Patterns Impact**: 15 (excellent)\\n- **Credit Utilization Impact**: 25 (moderate)\\n- **Existing Loan Burden Impact**: 15 (manageable)\\n\\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\\n\\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\\n\\n**Final Risk Score = (125 / 200) * 100 = 62.5**\\n\\n### Conclusion\\n**Final Risk Score**: **63** (rounded)\\n\\n### Recommendations\\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\\n\\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 19.443426,
"end_time": "2025-07-15T12:01:50.489895",
"message_sent": true,
"start_time": "2025-07-15T12:01:31.046469",
"timestamp": "2025-07-15T12:01:50.489895",
"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 evaluate the various factors mentioned:\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is described as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\n\n### Risk Score Calculation\nGiven the information provided, we can assign a risk score based on the factors analyzed:\n\n- **Credit Score**: Unresolved (assumed neutral impact)\n- **Credit History**: Excellent (low risk)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (moderate risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\n### Risk Score\n- **Credit Score Impact**: 50 (neutral)\n- **Credit History Impact**: 20 (excellent)\n- **Repayment Patterns Impact**: 15 (excellent)\n- **Credit Utilization Impact**: 25 (moderate)\n- **Existing Loan Burden Impact**: 15 (manageable)\n\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\n\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\n\n**Final Risk Score = (125 / 200) * 100 = 62.5**\n\n### Conclusion\n**Final Risk Score**: **63** (rounded)\n\n### Recommendations\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\n\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the various factors mentioned:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is described as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\\n\\n### Risk Score Calculation\\nGiven the information provided, we can assign a risk score based on the factors analyzed:\\n\\n- **Credit Score**: Unresolved (assumed neutral impact)\\n- **Credit History**: Excellent (low risk)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (moderate risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\n### Risk Score\\n- **Credit Score Impact**: 50 (neutral)\\n- **Credit History Impact**: 20 (excellent)\\n- **Repayment Patterns Impact**: 15 (excellent)\\n- **Credit Utilization Impact**: 25 (moderate)\\n- **Existing Loan Burden Impact**: 15 (manageable)\\n\\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\\n\\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\\n\\n**Final Risk Score = (125 / 200) * 100 = 62.5**\\n\\n### Conclusion\\n**Final Risk Score**: **63** (rounded)\\n\\n### Recommendations\\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\\n\\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "evaluate_default_risk"
},
"execution_summary": {
"completed_tasks": 24,
"dependencies_detected": false,
"end_time": "2025-07-15T12:11:00.419544",
"execution_mode": "distributed",
"start_time": "2025-07-15T11:58:08.825604",
"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": 0.275649,
"end_time": "2025-07-15T11:58:10.448772",
"message_sent": true,
"start_time": "2025-07-15T11:58:10.173123",
"timestamp": "2025-07-15T11:58:10.448772",
"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:**\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\n\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 484,
"model": "gpt-4o-mini",
"output_length": 2041,
"provider": "openai",
"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation:** DECLINE\n\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\n\n4. **Reasoning for Decision:**\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\n\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation:** DECLINE\\n\\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision:**\\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \\n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\\n\\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\", \"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": 7.470236,
"end_time": "2025-07-15T12:05:03.186096",
"message_sent": true,
"start_time": "2025-07-15T12:04:55.715860",
"timestamp": "2025-07-15T12:05:03.186096",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation:** DECLINE\n\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\n\n4. **Reasoning for Decision:**\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\n\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation:** DECLINE\\n\\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision:**\\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \\n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\\n\\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\", \"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": "final_underwriting_analysis"
},
"flag_for_manual_review": {
"error": "Unsupported task type: human",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Unsupported task type: human",
"status": "FAILED",
"task_id": "flag_for_manual_review"
},
"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmp3vmqdzxq.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",
"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/tmp3vmqdzxq.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "generate_final_output"
},
"income_assessment": {
"agent_type": "assistant",
"ai_response": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_stability_score\": 88.5,\n \"employment_type\": \"permanent\",\n \"employer_rating\": \"A+\",\n \"probation_status\": \"confirmed\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"assessment\": \"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Unresolved income data analysis may indicate potential issues with income verification.\",\n \"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\",\n \"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\",\n \"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\"\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\n \n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\n\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 883,
"model": "gpt-4o-mini",
"output_length": 3064,
"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": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_stability_score\": 88.5,\n \"employment_type\": \"permanent\",\n \"employer_rating\": \"A+\",\n \"probation_status\": \"confirmed\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"assessment\": \"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Unresolved income data analysis may indicate potential issues with income verification.\",\n \"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\",\n \"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\",\n \"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\"\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\n \n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\n\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"confirmed\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Unresolved income data analysis may indicate potential issues with income verification.\\\",\\n \\\"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\\\",\\n \\\"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\\\",\\n \\\"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\\\"\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\\n \\n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\\n\\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\", \"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": 11.615838,
"end_time": "2025-07-15T12:01:30.527322",
"message_sent": true,
"start_time": "2025-07-15T12:01:18.911484",
"timestamp": "2025-07-15T12:01:30.527322",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_stability_score\": 88.5,\n \"employment_type\": \"permanent\",\n \"employer_rating\": \"A+\",\n \"probation_status\": \"confirmed\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"assessment\": \"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Unresolved income data analysis may indicate potential issues with income verification.\",\n \"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\",\n \"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\",\n \"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\"\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\n \n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\n\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"confirmed\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Unresolved income data analysis may indicate potential issues with income verification.\\\",\\n \\\"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\\\",\\n \\\"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\\\",\\n \\\"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\\\"\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\\n \\n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\\n\\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\", \"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": "income_assessment"
},
"internal_policy_check": {
"age_criteria_met": true,
"credit_score_threshold_met": true,
"employment_criteria_met": true,
"exceptions_required": [],
"execution_details": {
"actual_result": {
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.257744,
"end_time": "2025-07-15T12:04:49.296545",
"message_sent": true,
"start_time": "2025-07-15T12:04:49.038801",
"timestamp": "2025-07-15T12:04:49.296545",
"worker_executed": true,
"workers_notified": true
},
"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",
"policy_compliance_score": 95.5,
"policy_version": "2024.1",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "internal_policy_check"
},
"kyc_compliance_check": {
"address_verified": true,
"compliance_score": 98.5,
"documents_complete": true,
"execution_details": {
"actual_result": {
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.299052,
"end_time": "2025-07-15T12:04:48.508258",
"message_sent": true,
"start_time": "2025-07-15T12:04:48.209206",
"timestamp": "2025-07-15T12:04:48.508258",
"worker_executed": true,
"workers_notified": true
},
"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,
"return_code": 0,
"risk_category": "low",
"status": "completed",
"stderr": "",
"task_id": "kyc_compliance_check"
},
"regulatory_compliance": {
"audit_trail_complete": true,
"compliance_score": 97.2,
"consumer_protection_compliant": true,
"data_privacy_compliant": true,
"disclosure_requirements_met": true,
"documentation_complete": true,
"execution_details": {
"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",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.265245,
"end_time": "2025-07-15T12:04:49.006041",
"message_sent": true,
"start_time": "2025-07-15T12:04:48.740796",
"timestamp": "2025-07-15T12:04:49.006041",
"worker_executed": true,
"workers_notified": true
},
"lending_norms_compliant": true,
"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,
"regulatory_risk": "minimal",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "regulatory_compliance"
},
"status": "FAILED",
"task_outputs": {
"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": 0.335057,
"end_time": "2025-07-15T12:04:48.789403",
"message_sent": true,
"start_time": "2025-07-15T12:04:48.454346",
"timestamp": "2025-07-15T12:04:48.789403",
"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": 0.530196,
"end_time": "2025-07-15T11:58:18.639934",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.109738",
"timestamp": "2025-07-15T11:58:18.639934",
"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": 0.361621,
"end_time": "2025-07-15T12:01:30.788950",
"message_sent": true,
"start_time": "2025-07-15T12:01:30.427329",
"timestamp": "2025-07-15T12:01:30.788950",
"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": 0.444225,
"end_time": "2025-07-15T11:58:18.512752",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.068527",
"timestamp": "2025-07-15T11:58:18.512752",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields. All required information has been provided and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\"\n },\n \"overall_application_quality_score\": 90,\n \"overall_assessment\": \"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1156,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields. All required information has been provided and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\"\n },\n \"overall_application_quality_score\": 90,\n \"overall_assessment\": \"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields. All required information has been provided and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 90,\\n \\\"overall_assessment\\\": \\\"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\\\"\\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": 4.923143,
"end_time": "2025-07-15T11:58:15.575348",
"message_sent": true,
"start_time": "2025-07-15T11:58:10.652205",
"timestamp": "2025-07-15T11:58:15.575348",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields. All required information has been provided and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\"\n },\n \"overall_application_quality_score\": 90,\n \"overall_assessment\": \"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields. All required information has been provided and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since the specific customer information is not provided, we cannot assess the consistency of the information. However, the validation results indicate that the data is complete.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the validation results. However, without specific customer details, further analysis cannot be performed.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 90,\\n \\\"overall_assessment\\\": \\\"The application is complete and validated successfully, indicating a high quality. However, the lack of specific customer information limits the ability to assess consistency and potential red flags. Therefore, a score of 90 is assigned, reflecting strong quality but acknowledging the need for more detailed information.\\\"\\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": 0.428797,
"end_time": "2025-07-15T12:01:31.137926",
"message_sent": true,
"start_time": "2025-07-15T12:01:30.709129",
"timestamp": "2025-07-15T12:01:31.137926",
"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/tmpz55_8pw5.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/tmpz55_8pw5.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": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpycuthhxd.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_max_debt_to_income_ratio\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/tmpycuthhxd.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_max_debt_to_income_ratio\u0027 is not defined\n",
"status": "FAILED",
"task_id": "calculate_debt_to_income"
},
"check_cibil_score": {
"active_accounts": 6,
"closed_accounts": 2,
"credit_history_length": "5 years",
"credit_score": 720,
"credit_utilization": 35.5,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.319086,
"end_time": "2025-07-15T12:01:30.477880",
"message_sent": true,
"start_time": "2025-07-15T12:01:30.158794",
"timestamp": "2025-07-15T12:01:30.477880",
"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 \"compliance_assessment\": {\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": \"High risk due to unresolved KYC, AML, and regulatory compliance issues.\",\n \"compliance_gaps_or_concerns\": [\n {\n \"issue\": \"KYC Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\"\n },\n {\n \"issue\": \"AML Screening\",\n \"status\": \"Unresolved\",\n \"concern\": \"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\"\n },\n {\n \"issue\": \"Regulatory Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Non-compliance with regulatory standards can result in legal repercussions and fines.\"\n }\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\",\n \"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\",\n \"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\",\n \"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1359,
"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 \"compliance_assessment\": {\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": \"High risk due to unresolved KYC, AML, and regulatory compliance issues.\",\n \"compliance_gaps_or_concerns\": [\n {\n \"issue\": \"KYC Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\"\n },\n {\n \"issue\": \"AML Screening\",\n \"status\": \"Unresolved\",\n \"concern\": \"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\"\n },\n {\n \"issue\": \"Regulatory Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Non-compliance with regulatory standards can result in legal repercussions and fines.\"\n }\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\",\n \"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\",\n \"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\",\n \"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": \\\"High risk due to unresolved KYC, AML, and regulatory compliance issues.\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n {\\n \\\"issue\\\": \\\"KYC Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"AML Screening\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Non-compliance with regulatory standards can result in legal repercussions and fines.\\\"\\n }\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\\\",\\n \\\"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\\\",\\n \\\"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\\\",\\n \\\"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n }\\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": 7.037302,
"end_time": "2025-07-15T12:04:56.369897",
"message_sent": true,
"start_time": "2025-07-15T12:04:49.332595",
"timestamp": "2025-07-15T12:04:56.369897",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"compliance_assessment\": {\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": \"High risk due to unresolved KYC, AML, and regulatory compliance issues.\",\n \"compliance_gaps_or_concerns\": [\n {\n \"issue\": \"KYC Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\"\n },\n {\n \"issue\": \"AML Screening\",\n \"status\": \"Unresolved\",\n \"concern\": \"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\"\n },\n {\n \"issue\": \"Regulatory Compliance\",\n \"status\": \"Unresolved\",\n \"concern\": \"Non-compliance with regulatory standards can result in legal repercussions and fines.\"\n }\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\",\n \"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\",\n \"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\",\n \"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": \\\"High risk due to unresolved KYC, AML, and regulatory compliance issues.\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n {\\n \\\"issue\\\": \\\"KYC Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Failure to meet Know Your Customer requirements can lead to identity fraud and regulatory penalties.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"AML Screening\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Inadequate Anti-Money Laundering measures increase the risk of financial crime.\\\"\\n },\\n {\\n \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n \\\"status\\\": \\\"Unresolved\\\",\\n \\\"concern\\\": \\\"Non-compliance with regulatory standards can result in legal repercussions and fines.\\\"\\n }\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues by implementing robust customer verification processes.\\\",\\n \\\"Enhance AML screening procedures to ensure all transactions are monitored and flagged appropriately.\\\",\\n \\\"Conduct a thorough review of regulatory compliance requirements and address any gaps immediately.\\\",\\n \\\"Consider a compliance training program for staff to ensure understanding of KYC, AML, and regulatory obligations.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n }\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 336,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 1.901975,
"end_time": "2025-07-15T11:58:18.194819",
"message_sent": true,
"start_time": "2025-07-15T11:58:16.292844",
"timestamp": "2025-07-15T11:58:18.194819",
"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 evaluate the various factors mentioned:\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is described as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\n\n### Risk Score Calculation\nGiven the information provided, we can assign a risk score based on the factors analyzed:\n\n- **Credit Score**: Unresolved (assumed neutral impact)\n- **Credit History**: Excellent (low risk)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (moderate risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\n### Risk Score\n- **Credit Score Impact**: 50 (neutral)\n- **Credit History Impact**: 20 (excellent)\n- **Repayment Patterns Impact**: 15 (excellent)\n- **Credit Utilization Impact**: 25 (moderate)\n- **Existing Loan Burden Impact**: 15 (manageable)\n\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\n\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\n\n**Final Risk Score = (125 / 200) * 100 = 62.5**\n\n### Conclusion\n**Final Risk Score**: **63** (rounded)\n\n### Recommendations\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\n\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 561,
"model": "gpt-4o-mini",
"output_length": 3565,
"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 evaluate the various factors mentioned:\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is described as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\n\n### Risk Score Calculation\nGiven the information provided, we can assign a risk score based on the factors analyzed:\n\n- **Credit Score**: Unresolved (assumed neutral impact)\n- **Credit History**: Excellent (low risk)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (moderate risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\n### Risk Score\n- **Credit Score Impact**: 50 (neutral)\n- **Credit History Impact**: 20 (excellent)\n- **Repayment Patterns Impact**: 15 (excellent)\n- **Credit Utilization Impact**: 25 (moderate)\n- **Existing Loan Burden Impact**: 15 (manageable)\n\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\n\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\n\n**Final Risk Score = (125 / 200) * 100 = 62.5**\n\n### Conclusion\n**Final Risk Score**: **63** (rounded)\n\n### Recommendations\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\n\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the various factors mentioned:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is described as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\\n\\n### Risk Score Calculation\\nGiven the information provided, we can assign a risk score based on the factors analyzed:\\n\\n- **Credit Score**: Unresolved (assumed neutral impact)\\n- **Credit History**: Excellent (low risk)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (moderate risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\n### Risk Score\\n- **Credit Score Impact**: 50 (neutral)\\n- **Credit History Impact**: 20 (excellent)\\n- **Repayment Patterns Impact**: 15 (excellent)\\n- **Credit Utilization Impact**: 25 (moderate)\\n- **Existing Loan Burden Impact**: 15 (manageable)\\n\\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\\n\\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\\n\\n**Final Risk Score = (125 / 200) * 100 = 62.5**\\n\\n### Conclusion\\n**Final Risk Score**: **63** (rounded)\\n\\n### Recommendations\\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\\n\\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 19.443426,
"end_time": "2025-07-15T12:01:50.489895",
"message_sent": true,
"start_time": "2025-07-15T12:01:31.046469",
"timestamp": "2025-07-15T12:01:50.489895",
"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 evaluate the various factors mentioned:\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is described as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\n\n### 5. Overall Risk Profile\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\n\n### Risk Score Calculation\nGiven the information provided, we can assign a risk score based on the factors analyzed:\n\n- **Credit Score**: Unresolved (assumed neutral impact)\n- **Credit History**: Excellent (low risk)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (moderate risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\n### Risk Score\n- **Credit Score Impact**: 50 (neutral)\n- **Credit History Impact**: 20 (excellent)\n- **Repayment Patterns Impact**: 15 (excellent)\n- **Credit Utilization Impact**: 25 (moderate)\n- **Existing Loan Burden Impact**: 15 (manageable)\n\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\n\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\n\n**Final Risk Score = (125 / 200) * 100 = 62.5**\n\n### Conclusion\n**Final Risk Score**: **63** (rounded)\n\n### Recommendations\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\n\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the various factors mentioned:\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this critical factor. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: The credit history is also unresolved. However, if we assume that the history is generally positive (as indicated by the repayment track record), this would suggest a lower risk.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is described as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive sign and reduces the risk of default.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is a reasonable level of debt relative to income, suggesting that the borrower is not over-leveraged. A lower ratio typically indicates lower risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable if the borrower\u0027s income supports this payment.\\n- **Outstanding Loans**: The borrower has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common and typically have different risk profiles, but the borrower seems to be managing them well.\\n\\n### 5. Overall Risk Profile\\n- **Number of Loans**: The borrower has two loans, which is not excessive, especially given the excellent repayment track record.\\n- **Remaining Tenure**: The remaining tenures of 18 and 24 months indicate that the borrower is nearing the end of their loan obligations, which can reduce risk as they will soon have fewer financial commitments.\\n\\n### Risk Score Calculation\\nGiven the information provided, we can assign a risk score based on the factors analyzed:\\n\\n- **Credit Score**: Unresolved (assumed neutral impact)\\n- **Credit History**: Excellent (low risk)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (moderate risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\n### Risk Score\\n- **Credit Score Impact**: 50 (neutral)\\n- **Credit History Impact**: 20 (excellent)\\n- **Repayment Patterns Impact**: 15 (excellent)\\n- **Credit Utilization Impact**: 25 (moderate)\\n- **Existing Loan Burden Impact**: 15 (manageable)\\n\\n**Total Risk Score = 50 + 20 + 15 + 25 + 15 = 125**\\n\\nTo normalize this to a scale of 1-100, we can divide by the maximum possible score (which we can assume to be 200 for this analysis):\\n\\n**Final Risk Score = (125 / 200) * 100 = 62.5**\\n\\n### Conclusion\\n**Final Risk Score**: **63** (rounded)\\n\\n### Recommendations\\n1. **Monitor Credit Score**: Resolve the issues related to the CIBIL score to get a clearer picture of creditworthiness.\\n2. **Maintain Excellent Repayment Patterns**: Continue the excellent repayment habits to further improve the credit profile.\\n3. **Manage Credit Utilization**: Keep the loan burden ratio below 30% to maintain a healthy credit profile.\\n4. **Consider Reducing Debt**: As the borrower approaches the end of their loan tenures, consider paying off any outstanding loans early if financially feasible.\\n5. **Avoid New Debt**: Until the current loans are paid off, avoid taking on new debt to maintain a stable financial position.\\n\\nOverall, the borrower shows a moderate risk of default, primarily due to the unresolved credit score. Addressing this issue and maintaining good financial habits will help in reducing the risk further.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "evaluate_default_risk"
},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.275649,
"end_time": "2025-07-15T11:58:10.448772",
"message_sent": true,
"start_time": "2025-07-15T11:58:10.173123",
"timestamp": "2025-07-15T11:58:10.448772",
"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:**\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\n\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 484,
"model": "gpt-4o-mini",
"output_length": 2041,
"provider": "openai",
"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation:** DECLINE\n\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\n\n4. **Reasoning for Decision:**\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\n\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation:** DECLINE\\n\\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision:**\\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \\n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\\n\\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\", \"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": 7.470236,
"end_time": "2025-07-15T12:05:03.186096",
"message_sent": true,
"start_time": "2025-07-15T12:04:55.715860",
"timestamp": "2025-07-15T12:05:03.186096",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation:** DECLINE\n\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\n\n4. **Reasoning for Decision:**\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\n\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\n\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation:** DECLINE\\n\\n2. **Loan Terms and Conditions:** N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures:** N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision:**\\n - The application has multiple unresolved issues that raise significant concerns regarding the applicant\u0027s overall risk profile. \\n - **Application Quality:** The unresolved application quality check indicates that there are potential discrepancies or missing information that could affect the integrity of the application.\\n - **Document Verification:** The unresolved document verification suggests that the supporting documents provided by the applicant have not been confirmed as authentic or complete, which is critical for assessing the applicant\u0027s financial situation.\\n - **Income Assessment:** An unresolved income assessment means that we cannot verify the applicant\u0027s income, which is essential for determining their ability to repay the loan.\\n - **Credit Score:** Without a calculated credit score, we cannot evaluate the applicant\u0027s creditworthiness, which is a key factor in underwriting decisions.\\n - **Default Risk:** An unresolved evaluation of default risk means we lack the necessary analysis to understand the likelihood of the applicant defaulting on the loan.\\n - **Compliance:** The unresolved compliance consolidation indicates that the application may not meet regulatory requirements, which could expose the lender to legal risks.\\n - **Debt-to-Income Ratio:** An unresolved calculation of the debt-to-income ratio prevents us from assessing the applicant\u0027s financial health and ability to manage additional debt.\\n\\nGiven the multitude of unresolved issues, the risk of approving this loan is too high. The lack of clarity and verification in critical areas such as income, creditworthiness, and compliance makes it impossible to proceed with confidence.\\n\\n5. **Confidence Level:** 95 (Due to the high number of unresolved issues, I am highly confident in the decision to decline the application.)\", \"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": "final_underwriting_analysis"
},
"flag_for_manual_review": {
"error": "Unsupported task type: human",
"execution_details": {
"failed": true,
"message_sent": true,
"worker_executed": true,
"workers_notified": true
},
"output": "Task failed: Unsupported task type: human",
"status": "FAILED",
"task_id": "flag_for_manual_review"
},
"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmp3vmqdzxq.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",
"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/tmp3vmqdzxq.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "generate_final_output"
},
"income_assessment": {
"agent_type": "assistant",
"ai_response": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_stability_score\": 88.5,\n \"employment_type\": \"permanent\",\n \"employer_rating\": \"A+\",\n \"probation_status\": \"confirmed\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"assessment\": \"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Unresolved income data analysis may indicate potential issues with income verification.\",\n \"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\",\n \"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\",\n \"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\"\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\n \n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\n\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 883,
"model": "gpt-4o-mini",
"output_length": 3064,
"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": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_stability_score\": 88.5,\n \"employment_type\": \"permanent\",\n \"employer_rating\": \"A+\",\n \"probation_status\": \"confirmed\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"assessment\": \"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Unresolved income data analysis may indicate potential issues with income verification.\",\n \"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\",\n \"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\",\n \"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\"\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\n \n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\n\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"confirmed\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Unresolved income data analysis may indicate potential issues with income verification.\\\",\\n \\\"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\\\",\\n \\\"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\\\",\\n \\\"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\\\"\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\\n \\n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\\n\\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\", \"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": 11.615838,
"end_time": "2025-07-15T12:01:30.527322",
"message_sent": true,
"start_time": "2025-07-15T12:01:18.911484",
"timestamp": "2025-07-15T12:01:30.527322",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_stability_score\": 88.5,\n \"employment_type\": \"permanent\",\n \"employer_rating\": \"A+\",\n \"probation_status\": \"confirmed\",\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"assessment\": \"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Unresolved income data analysis may indicate potential issues with income verification.\",\n \"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\",\n \"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\",\n \"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\"\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\n \n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\n\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"confirmed\\\",\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual has a high job stability score and is employed in a permanent position with a reputable employer. This indicates strong income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate debt-to-income ratio due to unresolved script error. Further analysis is required to determine the individual\u0027s capability to service debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Financial discipline cannot be accurately evaluated without the analysis of bank statements and tax returns. These documents are crucial for understanding spending habits and overall financial management.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Unresolved income data analysis may indicate potential issues with income verification.\\\",\\n \\\"Lack of debt-to-income ratio calculation limits understanding of debt servicing capability.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slips, bank statements, and tax returns to complete the income assessment.\\\",\\n \\\"Conduct a thorough review of the individual\u0027s financial habits through bank statement analysis.\\\",\\n \\\"Calculate the debt-to-income ratio to assess the individual\u0027s ability to manage existing and potential debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"While the individual has a stable job and a good employer rating, the unresolved data limits the ability to fully assess income adequacy. The score reflects a moderate level of confidence in income stability but highlights the need for further verification.\\\"\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed permanently, indicating strong income stability.\\n \\n2. **Debt Servicing Capability**: The debt-to-income ratio could not be calculated due to an unresolved script error, which is critical for assessing the ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of bank statements and tax returns, it is impossible to evaluate financial discipline accurately.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include unresolved income data and the inability to assess debt servicing capability. Recommendations focus on resolving these issues to complete the assessment.\\n\\n5. **Overall Income Adequacy Score**: A score of 65 reflects moderate confidence in income stability but emphasizes the need for further verification to improve the assessment.\", \"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": "income_assessment"
},
"internal_policy_check": {
"age_criteria_met": true,
"credit_score_threshold_met": true,
"employment_criteria_met": true,
"exceptions_required": [],
"execution_details": {
"actual_result": {
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.257744,
"end_time": "2025-07-15T12:04:49.296545",
"message_sent": true,
"start_time": "2025-07-15T12:04:49.038801",
"timestamp": "2025-07-15T12:04:49.296545",
"worker_executed": true,
"workers_notified": true
},
"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",
"policy_compliance_score": 95.5,
"policy_version": "2024.1",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "internal_policy_check"
},
"kyc_compliance_check": {
"address_verified": true,
"compliance_score": 98.5,
"documents_complete": true,
"execution_details": {
"actual_result": {
"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,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.299052,
"end_time": "2025-07-15T12:04:48.508258",
"message_sent": true,
"start_time": "2025-07-15T12:04:48.209206",
"timestamp": "2025-07-15T12:04:48.508258",
"worker_executed": true,
"workers_notified": true
},
"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,
"return_code": 0,
"risk_category": "low",
"status": "completed",
"stderr": "",
"task_id": "kyc_compliance_check"
},
"regulatory_compliance": {
"audit_trail_complete": true,
"compliance_score": 97.2,
"consumer_protection_compliant": true,
"data_privacy_compliant": true,
"disclosure_requirements_met": true,
"documentation_complete": true,
"execution_details": {
"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",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.265245,
"end_time": "2025-07-15T12:04:49.006041",
"message_sent": true,
"start_time": "2025-07-15T12:04:48.740796",
"timestamp": "2025-07-15T12:04:49.006041",
"worker_executed": true,
"workers_notified": true
},
"lending_norms_compliant": true,
"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,
"regulatory_risk": "minimal",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "regulatory_compliance"
},
"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": 0.000768,
"ended_at": "2025-07-15T12:04:55.595463",
"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\": 0.000768, \"started_at\": \"2025-07-15T12:04:55.594695\", \"ended_at\": \"2025-07-15T12:04:55.595463\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.179851,
"end_time": "2025-07-15T12:04:55.683395",
"message_sent": true,
"start_time": "2025-07-15T12:04:55.503544",
"timestamp": "2025-07-15T12:04:55.683395",
"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\": 0.000768, \"started_at\": \"2025-07-15T12:04:55.594695\", \"ended_at\": \"2025-07-15T12:04:55.595463\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T12:04:55.594695",
"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": 0.296863,
"end_time": "2025-07-15T11:58:10.701807",
"message_sent": true,
"start_time": "2025-07-15T11:58:10.404944",
"timestamp": "2025-07-15T11:58:10.701807",
"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": 0.464348,
"end_time": "2025-07-15T11:58:15.915526",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.451178",
"timestamp": "2025-07-15T11:58:15.915526",
"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": 0.873716,
"end_time": "2025-07-15T11:58:16.405062",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.531346",
"timestamp": "2025-07-15T11:58:16.405062",
"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": 0.508599,
"end_time": "2025-07-15T11:58:18.967446",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.458847",
"timestamp": "2025-07-15T11:58:18.967446",
"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": 0.35452,
"end_time": "2025-07-15T11:58:15.765866",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.411346",
"timestamp": "2025-07-15T11:58:15.765866",
"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": 0.880134,
"end_time": "2025-07-15T11:58:16.372433",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.492299",
"timestamp": "2025-07-15T11:58:16.372433",
"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": 0.744358,
"end_time": "2025-07-15T11:58:18.892949",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.148591",
"timestamp": "2025-07-15T11:58:18.892949",
"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": 0.000768,
"ended_at": "2025-07-15T12:04:55.595463",
"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\": 0.000768, \"started_at\": \"2025-07-15T12:04:55.594695\", \"ended_at\": \"2025-07-15T12:04:55.595463\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.179851,
"end_time": "2025-07-15T12:04:55.683395",
"message_sent": true,
"start_time": "2025-07-15T12:04:55.503544",
"timestamp": "2025-07-15T12:04:55.683395",
"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\": 0.000768, \"started_at\": \"2025-07-15T12:04:55.594695\", \"ended_at\": \"2025-07-15T12:04:55.595463\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T12:04:55.594695",
"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": 0.296863,
"end_time": "2025-07-15T11:58:10.701807",
"message_sent": true,
"start_time": "2025-07-15T11:58:10.404944",
"timestamp": "2025-07-15T11:58:10.701807",
"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": 0.464348,
"end_time": "2025-07-15T11:58:15.915526",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.451178",
"timestamp": "2025-07-15T11:58:15.915526",
"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": 0.873716,
"end_time": "2025-07-15T11:58:16.405062",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.531346",
"timestamp": "2025-07-15T11:58:16.405062",
"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": 0.508599,
"end_time": "2025-07-15T11:58:18.967446",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.458847",
"timestamp": "2025-07-15T11:58:18.967446",
"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": 0.35452,
"end_time": "2025-07-15T11:58:15.765866",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.411346",
"timestamp": "2025-07-15T11:58:15.765866",
"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": 0.880134,
"end_time": "2025-07-15T11:58:16.372433",
"message_sent": true,
"start_time": "2025-07-15T11:58:15.492299",
"timestamp": "2025-07-15T11:58:16.372433",
"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": 0.744358,
"end_time": "2025-07-15T11:58:18.892949",
"message_sent": true,
"start_time": "2025-07-15T11:58:18.148591",
"timestamp": "2025-07-15T11:58:18.892949",
"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
}
}