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": 0.387813,
"end_time": "2025-07-15T10:55:51.576600",
"message_sent": true,
"start_time": "2025-07-15T10:55:51.188787",
"timestamp": "2025-07-15T10:55:51.576600",
"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": 0.553038,
"end_time": "2025-07-15T10:49:27.655240",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.102202",
"timestamp": "2025-07-15T10:49:27.655240",
"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": 0.220268,
"end_time": "2025-07-15T10:52:36.659957",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.439689",
"timestamp": "2025-07-15T10:52:36.659957",
"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": 0.324595,
"end_time": "2025-07-15T10:49:27.387936",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.063341",
"timestamp": "2025-07-15T10:49:27.387936",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are present and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies detected in the application data.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 850,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are present and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies detected in the application data.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are present and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies detected in the application data.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\\\"\\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": 4.876436,
"end_time": "2025-07-15T10:49:25.463309",
"message_sent": true,
"start_time": "2025-07-15T10:49:20.586873",
"timestamp": "2025-07-15T10:49:25.463309",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are present and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies detected in the application data.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are present and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies detected in the application data.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\\\"\\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": 0.209865,
"end_time": "2025-07-15T10:52:36.898154",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.688289",
"timestamp": "2025-07-15T10:52:36.898154",
"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/tmp35laehxp.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/tmp35laehxp.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/tmp3v09_tb0.py\", line 25, in \u003cmodule\u003e\n \"ratio_acceptable\": debt_to_income_ratio \u003c= 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/tmp3v09_tb0.py\", line 25, in \u003cmodule\u003e\n \"ratio_acceptable\": debt_to_income_ratio \u003c= 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": 0.247071,
"end_time": "2025-07-15T10:52:36.415563",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.168492",
"timestamp": "2025-07-15T10:52:36.415563",
"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\": \"UNRESOLVED\",\n \"risk_assessment\": \"High\",\n \"compliance_gaps_or_concerns\": [\n \"KYC compliance check unresolved\",\n \"AML screening unresolved\",\n \"Regulatory compliance unresolved\"\n ],\n \"recommendations\": [\n \"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\",\n \"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\"\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": 702,
"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\": \"UNRESOLVED\",\n \"risk_assessment\": \"High\",\n \"compliance_gaps_or_concerns\": [\n \"KYC compliance check unresolved\",\n \"AML screening unresolved\",\n \"Regulatory compliance unresolved\"\n ],\n \"recommendations\": [\n \"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\",\n \"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": \\\"High\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"KYC compliance check unresolved\\\",\\n \\\"AML screening unresolved\\\",\\n \\\"Regulatory compliance unresolved\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\\\",\\n \\\"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\\\"\\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": 5.202881,
"end_time": "2025-07-15T10:55:57.331770",
"message_sent": true,
"start_time": "2025-07-15T10:55:52.128889",
"timestamp": "2025-07-15T10:55:57.331770",
"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\": \"UNRESOLVED\",\n \"risk_assessment\": \"High\",\n \"compliance_gaps_or_concerns\": [\n \"KYC compliance check unresolved\",\n \"AML screening unresolved\",\n \"Regulatory compliance unresolved\"\n ],\n \"recommendations\": [\n \"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\",\n \"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": \\\"High\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"KYC compliance check unresolved\\\",\\n \\\"AML screening unresolved\\\",\\n \\\"Regulatory compliance unresolved\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\\\",\\n \\\"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\\\"\\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. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 309,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 1.956777,
"end_time": "2025-07-15T10:49:27.186704",
"message_sent": true,
"start_time": "2025-07-15T10:49:25.229927",
"timestamp": "2025-07-15T10:49:27.186704",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Outstanding Loans**: The individual has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- **Total Outstanding**: 125000 across both loans.\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\n\n### 5. Overall Risk Profile\nConsidering the factors:\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\n- **Repayment Patterns**: Excellent, which is a strong positive.\n- **Loan Burden Ratio**: Acceptable at 28%.\n- **Existing Loans**: Two loans with a manageable EMI.\n\n### Risk Score Calculation\nGiven the available data, we can assign a risk score based on the known factors:\n- Excellent repayment history: -10 points (reducing risk)\n- Loan burden ratio of 28%: -5 points (reducing risk)\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\n\nAssuming a base risk score of 50 (neutral):\n- Adjusting for repayment history: 50 - 10 = 40\n- Adjusting for loan burden ratio: 40 - 5 = 35\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\n\n### Final Risk Score\n**Risk Score: 55/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\n\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 561,
"model": "gpt-4o-mini",
"output_length": 3429,
"provider": "openai",
"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Outstanding Loans**: The individual has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- **Total Outstanding**: 125000 across both loans.\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\n\n### 5. Overall Risk Profile\nConsidering the factors:\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\n- **Repayment Patterns**: Excellent, which is a strong positive.\n- **Loan Burden Ratio**: Acceptable at 28%.\n- **Existing Loans**: Two loans with a manageable EMI.\n\n### Risk Score Calculation\nGiven the available data, we can assign a risk score based on the known factors:\n- Excellent repayment history: -10 points (reducing risk)\n- Loan burden ratio of 28%: -5 points (reducing risk)\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\n\nAssuming a base risk score of 50 (neutral):\n- Adjusting for repayment history: 50 - 10 = 40\n- Adjusting for loan burden ratio: 40 - 5 = 35\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\n\n### Final Risk Score\n**Risk Score: 55/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\n\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score\\\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history\\\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent\\\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Outstanding Loans**: The individual has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- **Total Outstanding**: 125000 across both loans.\\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\\n\\n### 5. Overall Risk Profile\\nConsidering the factors:\\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\\n- **Repayment Patterns**: Excellent, which is a strong positive.\\n- **Loan Burden Ratio**: Acceptable at 28%.\\n- **Existing Loans**: Two loans with a manageable EMI.\\n\\n### Risk Score Calculation\\nGiven the available data, we can assign a risk score based on the known factors:\\n- Excellent repayment history: -10 points (reducing risk)\\n- Loan burden ratio of 28%: -5 points (reducing risk)\\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\\n\\nAssuming a base risk score of 50 (neutral):\\n- Adjusting for repayment history: 50 - 10 = 40\\n- Adjusting for loan burden ratio: 40 - 5 = 35\\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\\n\\n### Final Risk Score\\n**Risk Score: 55/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\\n\\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\", \"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": 15.877624,
"end_time": "2025-07-15T10:52:52.806397",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.928773",
"timestamp": "2025-07-15T10:52:52.806397",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Outstanding Loans**: The individual has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- **Total Outstanding**: 125000 across both loans.\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\n\n### 5. Overall Risk Profile\nConsidering the factors:\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\n- **Repayment Patterns**: Excellent, which is a strong positive.\n- **Loan Burden Ratio**: Acceptable at 28%.\n- **Existing Loans**: Two loans with a manageable EMI.\n\n### Risk Score Calculation\nGiven the available data, we can assign a risk score based on the known factors:\n- Excellent repayment history: -10 points (reducing risk)\n- Loan burden ratio of 28%: -5 points (reducing risk)\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\n\nAssuming a base risk score of 50 (neutral):\n- Adjusting for repayment history: 50 - 10 = 40\n- Adjusting for loan burden ratio: 40 - 5 = 35\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\n\n### Final Risk Score\n**Risk Score: 55/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\n\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score\\\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history\\\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent\\\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Outstanding Loans**: The individual has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- **Total Outstanding**: 125000 across both loans.\\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\\n\\n### 5. Overall Risk Profile\\nConsidering the factors:\\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\\n- **Repayment Patterns**: Excellent, which is a strong positive.\\n- **Loan Burden Ratio**: Acceptable at 28%.\\n- **Existing Loans**: Two loans with a manageable EMI.\\n\\n### Risk Score Calculation\\nGiven the available data, we can assign a risk score based on the known factors:\\n- Excellent repayment history: -10 points (reducing risk)\\n- Loan burden ratio of 28%: -5 points (reducing risk)\\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\\n\\nAssuming a base risk score of 50 (neutral):\\n- Adjusting for repayment history: 50 - 10 = 40\\n- Adjusting for loan burden ratio: 40 - 5 = 35\\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\\n\\n### Final Risk Score\\n**Risk Score: 55/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\\n\\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\", \"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": "2025-07-15T11:02:03.209597",
"execution_mode": "distributed",
"start_time": "2025-07-15T10:49:18.697909",
"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": 1000000
},
"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\": 1000000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.249214,
"end_time": "2025-07-15T10:49:20.397826",
"message_sent": true,
"start_time": "2025-07-15T10:49:20.148612",
"timestamp": "2025-07-15T10:49:20.397826",
"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\": 1000000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "extract_application_info"
},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\n \n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\n \n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\n \n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\n \n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\n \n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\n\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.",
"execution_details": {
"actual_result": {
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"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\n \n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\n \n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\n \n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\n \n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\n \n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\n\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\\n \\n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\\n \\n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\\n \\n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\\n \\n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\\n \\n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\\n \\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\\n\\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\\n\\n5. **Confidence Level**: 95\\n\\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"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": 7.475718,
"end_time": "2025-07-15T10:56:04.761155",
"message_sent": true,
"start_time": "2025-07-15T10:55:57.285437",
"timestamp": "2025-07-15T10:56:04.761155",
"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**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\n \n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\n \n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\n \n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\n \n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\n \n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\n\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. 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A low or poor credit score could indicate a higher risk of default.\\n \\n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\\n \\n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\\n \\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\\n\\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\\n\\n5. **Confidence Level**: 95\\n\\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"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 \"stability_comment\": \"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"debt_servicing_comment\": \"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"financial_discipline_comment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved components.\",\n \"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\",\n \"Unverified financial discipline due to missing bank statement and tax return analysis.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\",\n \"Conduct a thorough review of tax returns to assess historical income and tax compliance.\",\n \"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\"\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 in a permanent position, indicating a stable income source.\n\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\n\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\n\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.",
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"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 \"stability_comment\": \"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"debt_servicing_comment\": \"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"financial_discipline_comment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved components.\",\n \"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\",\n \"Unverified financial discipline due to missing bank statement and tax return analysis.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\",\n \"Conduct a thorough review of tax returns to assess historical income and tax compliance.\",\n \"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\"\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 in a permanent position, indicating a stable income source.\n\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\n\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\n\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.\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 \\\"stability_comment\\\": \\\"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"debt_servicing_comment\\\": \\\"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"financial_discipline_comment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved components.\\\",\\n \\\"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\\\",\\n \\\"Unverified financial discipline due to missing bank statement and tax return analysis.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\\\",\\n \\\"Conduct a thorough review of tax returns to assess historical income and tax compliance.\\\",\\n \\\"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\\\"\\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 in a permanent position, indicating a stable income source.\\n\\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\\n\\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\\n\\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"financial_discipline_comment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved components.\",\n \"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\",\n \"Unverified financial discipline due to missing bank statement and tax return analysis.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\",\n \"Conduct a thorough review of tax returns to assess historical income and tax compliance.\",\n \"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\"\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 in a permanent position, indicating a stable income source.\n\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\n\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\n\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.\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 \\\"stability_comment\\\": \\\"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"debt_servicing_comment\\\": \\\"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"financial_discipline_comment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved components.\\\",\\n \\\"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\\\",\\n \\\"Unverified financial discipline due to missing bank statement and tax return analysis.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\\\",\\n \\\"Conduct a thorough review of tax returns to assess historical income and tax compliance.\\\",\\n \\\"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\\\"\\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 in a permanent position, indicating a stable income source.\\n\\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\\n\\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. 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"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": 0.553038,
"end_time": "2025-07-15T10:49:27.655240",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.102202",
"timestamp": "2025-07-15T10:49:27.655240",
"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": 0.220268,
"end_time": "2025-07-15T10:52:36.659957",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.439689",
"timestamp": "2025-07-15T10:52:36.659957",
"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": 0.324595,
"end_time": "2025-07-15T10:49:27.387936",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.063341",
"timestamp": "2025-07-15T10:49:27.387936",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are present and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies detected in the application data.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 850,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are present and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies detected in the application data.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are present and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies detected in the application data.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\\\"\\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": 4.876436,
"end_time": "2025-07-15T10:49:25.463309",
"message_sent": true,
"start_time": "2025-07-15T10:49:20.586873",
"timestamp": "2025-07-15T10:49:25.463309",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"All required fields are present and validated successfully.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies detected in the application data.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"All required fields are present and validated successfully.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"No inconsistencies noted as the validation results indicate that all information is complete and accurate.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies detected in the application data.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and accurate with no missing information or inconsistencies. However, a score of 95 is given instead of 100 due to the lack of additional context or supporting documentation that could further validate the applicant\u0027s financial situation.\\\"\\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": 0.209865,
"end_time": "2025-07-15T10:52:36.898154",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.688289",
"timestamp": "2025-07-15T10:52:36.898154",
"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/tmp35laehxp.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/tmp35laehxp.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/tmp3v09_tb0.py\", line 25, in \u003cmodule\u003e\n \"ratio_acceptable\": debt_to_income_ratio \u003c= 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/tmp3v09_tb0.py\", line 25, in \u003cmodule\u003e\n \"ratio_acceptable\": debt_to_income_ratio \u003c= 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": 0.247071,
"end_time": "2025-07-15T10:52:36.415563",
"message_sent": true,
"start_time": "2025-07-15T10:52:36.168492",
"timestamp": "2025-07-15T10:52:36.415563",
"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\": \"UNRESOLVED\",\n \"risk_assessment\": \"High\",\n \"compliance_gaps_or_concerns\": [\n \"KYC compliance check unresolved\",\n \"AML screening unresolved\",\n \"Regulatory compliance unresolved\"\n ],\n \"recommendations\": [\n \"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\",\n \"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\"\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": 702,
"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\": \"UNRESOLVED\",\n \"risk_assessment\": \"High\",\n \"compliance_gaps_or_concerns\": [\n \"KYC compliance check unresolved\",\n \"AML screening unresolved\",\n \"Regulatory compliance unresolved\"\n ],\n \"recommendations\": [\n \"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\",\n \"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": \\\"High\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"KYC compliance check unresolved\\\",\\n \\\"AML screening unresolved\\\",\\n \\\"Regulatory compliance unresolved\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\\\",\\n \\\"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\\\"\\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": 5.202881,
"end_time": "2025-07-15T10:55:57.331770",
"message_sent": true,
"start_time": "2025-07-15T10:55:52.128889",
"timestamp": "2025-07-15T10:55:57.331770",
"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\": \"UNRESOLVED\",\n \"risk_assessment\": \"High\",\n \"compliance_gaps_or_concerns\": [\n \"KYC compliance check unresolved\",\n \"AML screening unresolved\",\n \"Regulatory compliance unresolved\"\n ],\n \"recommendations\": [\n \"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\",\n \"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\"\n ],\n \"compliance_confidence_score\": 25\n }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"compliance_assessment\\\": {\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": \\\"High\\\",\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"KYC compliance check unresolved\\\",\\n \\\"AML screening unresolved\\\",\\n \\\"Regulatory compliance unresolved\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Immediately address the unresolved KYC compliance check to ensure identification and verification of customers.\\\",\\n \\\"Resolve the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Address the unresolved regulatory compliance issues to ensure adherence to applicable laws and regulations.\\\"\\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. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 309,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 1.956777,
"end_time": "2025-07-15T10:49:27.186704",
"message_sent": true,
"start_time": "2025-07-15T10:49:25.229927",
"timestamp": "2025-07-15T10:49:27.186704",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Outstanding Loans**: The individual has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- **Total Outstanding**: 125000 across both loans.\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\n\n### 5. Overall Risk Profile\nConsidering the factors:\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\n- **Repayment Patterns**: Excellent, which is a strong positive.\n- **Loan Burden Ratio**: Acceptable at 28%.\n- **Existing Loans**: Two loans with a manageable EMI.\n\n### Risk Score Calculation\nGiven the available data, we can assign a risk score based on the known factors:\n- Excellent repayment history: -10 points (reducing risk)\n- Loan burden ratio of 28%: -5 points (reducing risk)\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\n\nAssuming a base risk score of 50 (neutral):\n- Adjusting for repayment history: 50 - 10 = 40\n- Adjusting for loan burden ratio: 40 - 5 = 35\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\n\n### Final Risk Score\n**Risk Score: 55/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\n\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.",
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"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Outstanding Loans**: The individual has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- **Total Outstanding**: 125000 across both loans.\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\n\n### 5. Overall Risk Profile\nConsidering the factors:\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\n- **Repayment Patterns**: Excellent, which is a strong positive.\n- **Loan Burden Ratio**: Acceptable at 28%.\n- **Existing Loans**: Two loans with a manageable EMI.\n\n### Risk Score Calculation\nGiven the available data, we can assign a risk score based on the known factors:\n- Excellent repayment history: -10 points (reducing risk)\n- Loan burden ratio of 28%: -5 points (reducing risk)\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\n\nAssuming a base risk score of 50 (neutral):\n- Adjusting for repayment history: 50 - 10 = 40\n- Adjusting for loan burden ratio: 40 - 5 = 35\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\n\n### Final Risk Score\n**Risk Score: 55/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\n\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score\\\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history\\\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent\\\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Outstanding Loans**: The individual has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- **Total Outstanding**: 125000 across both loans.\\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\\n\\n### 5. Overall Risk Profile\\nConsidering the factors:\\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\\n- **Repayment Patterns**: Excellent, which is a strong positive.\\n- **Loan Burden Ratio**: Acceptable at 28%.\\n- **Existing Loans**: Two loans with a manageable EMI.\\n\\n### Risk Score Calculation\\nGiven the available data, we can assign a risk score based on the known factors:\\n- Excellent repayment history: -10 points (reducing risk)\\n- Loan burden ratio of 28%: -5 points (reducing risk)\\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\\n\\nAssuming a base risk score of 50 (neutral):\\n- Adjusting for repayment history: 50 - 10 = 40\\n- Adjusting for loan burden ratio: 40 - 5 = 35\\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\\n\\n### Final Risk Score\\n**Risk Score: 55/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\\n\\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
"duration_seconds": 15.877624,
"end_time": "2025-07-15T10:52:52.806397",
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"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Outstanding Loans**: The individual has two loans:\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\n- **Total Outstanding**: 125000 across both loans.\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\n\n### 5. Overall Risk Profile\nConsidering the factors:\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\n- **Repayment Patterns**: Excellent, which is a strong positive.\n- **Loan Burden Ratio**: Acceptable at 28%.\n- **Existing Loans**: Two loans with a manageable EMI.\n\n### Risk Score Calculation\nGiven the available data, we can assign a risk score based on the known factors:\n- Excellent repayment history: -10 points (reducing risk)\n- Loan burden ratio of 28%: -5 points (reducing risk)\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\n\nAssuming a base risk score of 50 (neutral):\n- Adjusting for repayment history: 50 - 10 = 40\n- Adjusting for loan burden ratio: 40 - 5 = 35\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\n\n### Final Risk Score\n**Risk Score: 55/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\n\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score\\\". Without a specific score, we cannot assess the risk accurately based on this factor. Typically, a score below 600 indicates high risk, while scores above 750 are considered low risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history\\\". A good credit history with timely payments would lower risk, while a history of defaults or late payments would increase it.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent\\\". This indicates that the individual has consistently made 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 individual is not over-leveraged. A ratio below 30% is generally considered acceptable.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Outstanding Loans**: The individual has two loans:\\n - Personal Loan: EMI of 3500, outstanding of 45000, remaining tenure of 18 months.\\n - Auto Loan: EMI of 4200, outstanding of 80000, remaining tenure of 24 months.\\n- **Total Outstanding**: 125000 across both loans.\\n- The total outstanding amount is significant, but given the excellent repayment track record and reasonable loan burden ratio, this does not immediately indicate high risk.\\n\\n### 5. Overall Risk Profile\\nConsidering the factors:\\n- **CIBIL Score**: Unknown, but critical for a complete assessment.\\n- **Repayment Patterns**: Excellent, which is a strong positive.\\n- **Loan Burden Ratio**: Acceptable at 28%.\\n- **Existing Loans**: Two loans with a manageable EMI.\\n\\n### Risk Score Calculation\\nGiven the available data, we can assign a risk score based on the known factors:\\n- Excellent repayment history: -10 points (reducing risk)\\n- Loan burden ratio of 28%: -5 points (reducing risk)\\n- Unknown CIBIL score and credit history: +20 points (increasing risk due to uncertainty)\\n\\nAssuming a base risk score of 50 (neutral):\\n- Adjusting for repayment history: 50 - 10 = 40\\n- Adjusting for loan burden ratio: 40 - 5 = 35\\n- Adjusting for unknown CIBIL score: 35 + 20 = 55\\n\\n### Final Risk Score\\n**Risk Score: 55/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain the CIBIL score and analyze the credit history to get a complete picture. If the score is low, work on improving it.\\n2. **Maintain Excellent Repayment Patterns**: Continue making timely payments to maintain the excellent repayment track record.\\n3. **Monitor Loan Burden**: Keep the loan burden ratio below 30% and avoid taking on additional debt unless necessary.\\n4. **Financial Planning**: Consider creating a budget to manage expenses and ensure that EMIs are comfortably manageable within monthly income.\\n5. **Credit Utilization**: If applicable, keep credit card utilization below 30% of the total limit to maintain a healthy credit profile.\\n\\nBy addressing the unknowns and maintaining good financial habits, the risk of default can be minimized.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 1000000
},
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 1000000}, \"missing_fields\": []}\n",
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"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 1000000}, \"missing_fields\": []}\n",
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"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\n \n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\n \n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\n \n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\n \n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\n \n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\n\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\n \n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\n \n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\n \n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\n \n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\n \n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\n\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\\n \\n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\\n \\n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\\n \\n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\\n \\n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\\n \\n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\\n \\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\\n\\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\\n\\n5. **Confidence Level**: 95\\n\\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. This raises red flags about the applicant\u0027s reliability and transparency.\n \n - **Document Verification**: The unresolved document verification suggests that the necessary documentation to support the application has not been adequately verified. This lack of verification can lead to potential fraud or misrepresentation, which is a significant risk for any lending decision.\n \n - **Income Assessment**: An unresolved income assessment means that we cannot confirm the applicant\u0027s ability to repay the loan based on their income. This is a critical factor in determining loan eligibility and repayment capacity.\n \n - **Credit Score**: The unresolved credit score calculation prevents us from understanding the applicant\u0027s creditworthiness. A low or poor credit score could indicate a higher risk of default.\n \n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\n \n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\n \n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\n\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n - **Application Quality**: The unresolved application quality check indicates that there are significant concerns regarding the completeness or accuracy of the application. 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A low or poor credit score could indicate a higher risk of default.\\n \\n - **Default Risk**: Without a proper evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is essential for making an informed lending decision.\\n \\n - **Compliance**: The unresolved compliance consolidation indicates potential regulatory or legal issues that could arise from approving the loan, which could expose the lender to legal liabilities.\\n \\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage additional debt, which is crucial for determining loan viability.\\n\\nGiven the multitude of unresolved issues, the overall risk profile of this application is deemed too high. Approving the loan under these circumstances would expose the lender to significant financial risk and potential regulatory issues.\\n\\n5. **Confidence Level**: 95\\n\\nThe confidence level is high due to the clear and significant unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"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 \"stability_comment\": \"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"debt_servicing_comment\": \"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"financial_discipline_comment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved components.\",\n \"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\",\n \"Unverified financial discipline due to missing bank statement and tax return analysis.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\",\n \"Conduct a thorough review of tax returns to assess historical income and tax compliance.\",\n \"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\"\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 in a permanent position, indicating a stable income source.\n\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\n\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\n\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.",
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Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"financial_discipline_comment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved components.\",\n \"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\",\n \"Unverified financial discipline due to missing bank statement and tax return analysis.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\",\n \"Conduct a thorough review of tax returns to assess historical income and tax compliance.\",\n \"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\"\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 in a permanent position, indicating a stable income source.\n\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\n\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\n\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.\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 \\\"stability_comment\\\": \\\"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"debt_servicing_comment\\\": \\\"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"financial_discipline_comment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved components.\\\",\\n \\\"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\\\",\\n \\\"Unverified financial discipline due to missing bank statement and tax return analysis.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\\\",\\n \\\"Conduct a thorough review of tax returns to assess historical income and tax compliance.\\\",\\n \\\"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\\\"\\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 in a permanent position, indicating a stable income source.\\n\\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\\n\\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\\n\\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_return_verification\": \"UNRESOLVED\",\n \"financial_discipline_comment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved components.\",\n \"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\",\n \"Unverified financial discipline due to missing bank statement and tax return analysis.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\",\n \"Conduct a thorough review of tax returns to assess historical income and tax compliance.\",\n \"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 65,\n \"justification\": \"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\"\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 in a permanent position, indicating a stable income source.\n\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\n\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\n\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. Recommendations focus on resolving the data issues for a comprehensive assessment.\n\n5. **Overall Income Adequacy Score**: A score of 65 reflects the strengths in employment stability but acknowledges the significant gaps in data that hinder a complete financial assessment. Further analysis is necessary to improve this score.\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 \\\"stability_comment\\\": \\\"The individual has a strong job stability score and is employed in a permanent position with a reputable employer. This indicates a high level of income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"debt_servicing_comment\\\": \\\"Unable to calculate debt-to-income ratio due to script failure. Further analysis is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_return_verification\\\": \\\"UNRESOLVED\\\",\\n \\\"financial_discipline_comment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. These documents are crucial for understanding spending habits and savings.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved components.\\\",\\n \\\"Potential instability in debt servicing capability due to lack of debt-to-income ratio.\\\",\\n \\\"Unverified financial discipline due to missing bank statement and tax return analysis.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to obtain a complete picture of income.\\\",\\n \\\"Conduct a thorough review of tax returns to assess historical income and tax compliance.\\\",\\n \\\"Calculate the debt-to-income ratio to evaluate the individual\u0027s ability to manage debt effectively.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 65,\\n \\\"justification\\\": \\\"The score reflects a strong employment situation but is tempered by the unresolved issues in debt servicing capability and financial discipline evaluation. Further data is needed for a more accurate assessment.\\\"\\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 in a permanent position, indicating a stable income source.\\n\\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to a script failure means we cannot assess this aspect effectively.\\n\\n3. **Financial Discipline Evaluation**: The lack of analysis on bank statements and tax returns prevents a thorough evaluation of the individual\u0027s financial habits.\\n\\n4. **Risk Factors and Recommendations**: Identified risks include incomplete data analysis and potential instability in debt servicing capability. 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"timestamp": "2025-07-15T10:55:57.252530",
"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\": 0.000909, \"started_at\": \"2025-07-15T10:55:57.138555\", \"ended_at\": \"2025-07-15T10:55:57.139464\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T10:55:57.138555",
"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": 0.267682,
"end_time": "2025-07-15T10:49:20.627112",
"message_sent": true,
"start_time": "2025-07-15T10:49:20.359430",
"timestamp": "2025-07-15T10:49:20.627112",
"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": 0.4852,
"end_time": "2025-07-15T10:49:24.761069",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.275869",
"timestamp": "2025-07-15T10:49:24.761069",
"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": 0.94304,
"end_time": "2025-07-15T10:49:25.292727",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.349687",
"timestamp": "2025-07-15T10:49:25.292727",
"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": 0.617669,
"end_time": "2025-07-15T10:49:28.034096",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.416427",
"timestamp": "2025-07-15T10:49:28.034096",
"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": 0.348706,
"end_time": "2025-07-15T10:49:24.582845",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.234139",
"timestamp": "2025-07-15T10:49:24.582845",
"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": 0.953607,
"end_time": "2025-07-15T10:49:25.267300",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.313693",
"timestamp": "2025-07-15T10:49:25.267300",
"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": 0.797837,
"end_time": "2025-07-15T10:49:27.937530",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.139693",
"timestamp": "2025-07-15T10:49:27.937530",
"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": 0.000909,
"ended_at": "2025-07-15T10:55:57.139464",
"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\": 0.000909, \"started_at\": \"2025-07-15T10:55:57.138555\", \"ended_at\": \"2025-07-15T10:55:57.139464\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.218933,
"end_time": "2025-07-15T10:55:57.252530",
"message_sent": true,
"start_time": "2025-07-15T10:55:57.033597",
"timestamp": "2025-07-15T10:55:57.252530",
"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\": 0.000909, \"started_at\": \"2025-07-15T10:55:57.138555\", \"ended_at\": \"2025-07-15T10:55:57.139464\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T10:55:57.138555",
"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": 0.267682,
"end_time": "2025-07-15T10:49:20.627112",
"message_sent": true,
"start_time": "2025-07-15T10:49:20.359430",
"timestamp": "2025-07-15T10:49:20.627112",
"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": 0.4852,
"end_time": "2025-07-15T10:49:24.761069",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.275869",
"timestamp": "2025-07-15T10:49:24.761069",
"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": 0.94304,
"end_time": "2025-07-15T10:49:25.292727",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.349687",
"timestamp": "2025-07-15T10:49:25.292727",
"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": 0.617669,
"end_time": "2025-07-15T10:49:28.034096",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.416427",
"timestamp": "2025-07-15T10:49:28.034096",
"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": 0.348706,
"end_time": "2025-07-15T10:49:24.582845",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.234139",
"timestamp": "2025-07-15T10:49:24.582845",
"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": 0.953607,
"end_time": "2025-07-15T10:49:25.267300",
"message_sent": true,
"start_time": "2025-07-15T10:49:24.313693",
"timestamp": "2025-07-15T10:49:25.267300",
"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": 0.797837,
"end_time": "2025-07-15T10:49:27.937530",
"message_sent": true,
"start_time": "2025-07-15T10:49:27.139693",
"timestamp": "2025-07-15T10:49:27.937530",
"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
}
}