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": 0.298856,
"end_time": "2025-07-15T11:11:15.212104",
"message_sent": true,
"start_time": "2025-07-15T11:11:14.913248",
"timestamp": "2025-07-15T11:11:15.212104",
"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": 0.497922,
"end_time": "2025-07-15T11:04:50.839517",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.341595",
"timestamp": "2025-07-15T11:04:50.839517",
"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": 0.272227,
"end_time": "2025-07-15T11:08:00.147515",
"message_sent": true,
"start_time": "2025-07-15T11:07:59.875288",
"timestamp": "2025-07-15T11:08:00.147515",
"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": 0.370592,
"end_time": "2025-07-15T11:04:50.659868",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.289276",
"timestamp": "2025-07-15T11:04:50.659868",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1178,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\\\"\\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": 4.478143,
"end_time": "2025-07-15T11:04:47.907990",
"message_sent": true,
"start_time": "2025-07-15T11:04:43.429847",
"timestamp": "2025-07-15T11:04:47.907990",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\\\"\\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": 0.298206,
"end_time": "2025-07-15T11:08:00.479508",
"message_sent": true,
"start_time": "2025-07-15T11:08:00.181302",
"timestamp": "2025-07-15T11:08:00.479508",
"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/tmpgx8pln7k.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/tmpgx8pln7k.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/tmpaqmue9u6.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_variables.max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_variables\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/tmpaqmue9u6.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_variables.max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_variables\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": 0.326874,
"end_time": "2025-07-15T11:07:59.928949",
"message_sent": true,
"start_time": "2025-07-15T11:07:59.602075",
"timestamp": "2025-07-15T11:07:59.928949",
"worker_executed": true,
"workers_notified": true
},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\",\n \"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\",\n \"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1126,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\",\n \"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\",\n \"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\\\",\\n \\\"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.099453,
"end_time": "2025-07-15T11:11:19.925900",
"message_sent": true,
"start_time": "2025-07-15T11:11:15.826447",
"timestamp": "2025-07-15T11:11:19.925900",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\",\n \"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\",\n \"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\\\",\\n \\\"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
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"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
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"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.286666,
"end_time": "2025-07-15T11:04:50.437635",
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"start_time": "2025-07-15T11:04:48.150969",
"timestamp": "2025-07-15T11:04:50.437635",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
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"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\n\n### 5. Overall Risk Profile\n- **Risk Factors**:\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\n - Excellent repayment track record is a strong positive factor.\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\n\n### Risk Score Calculation\nGiven the available information, we can assign a risk score based on the following considerations:\n- **CIBIL Score**: Unknown (assumed neutral impact)\n- **Credit History**: Unknown (assumed neutral impact)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\n\n- Excellent repayment: -20 points (from a base of 100)\n- Reasonable loan burden: -10 points (from a base of 100)\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\n\n### Final Risk Score\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\n\n### Conclusion\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.",
"execution_details": {
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"provider": "openai",
"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\n\n### 5. Overall Risk Profile\n- **Risk Factors**:\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\n - Excellent repayment track record is a strong positive factor.\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\n\n### Risk Score Calculation\nGiven the available information, we can assign a risk score based on the following considerations:\n- **CIBIL Score**: Unknown (assumed neutral impact)\n- **Credit History**: Unknown (assumed neutral impact)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\n\n- Excellent repayment: -20 points (from a base of 100)\n- Reasonable loan burden: -10 points (from a base of 100)\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\n\n### Final Risk Score\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\n\n### Conclusion\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\\n\\n### 5. Overall Risk Profile\\n- **Risk Factors**:\\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\\n - Excellent repayment track record is a strong positive factor.\\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\\n\\n### Risk Score Calculation\\nGiven the available information, we can assign a risk score based on the following considerations:\\n- **CIBIL Score**: Unknown (assumed neutral impact)\\n- **Credit History**: Unknown (assumed neutral impact)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\\n\\n- Excellent repayment: -20 points (from a base of 100)\\n- Reasonable loan burden: -10 points (from a base of 100)\\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\\n\\n### Final Risk Score\\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\\n\\n### Conclusion\\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
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"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\n\n### 5. Overall Risk Profile\n- **Risk Factors**:\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\n - Excellent repayment track record is a strong positive factor.\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\n\n### Risk Score Calculation\nGiven the available information, we can assign a risk score based on the following considerations:\n- **CIBIL Score**: Unknown (assumed neutral impact)\n- **Credit History**: Unknown (assumed neutral impact)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\n\n- Excellent repayment: -20 points (from a base of 100)\n- Reasonable loan burden: -10 points (from a base of 100)\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\n\n### Final Risk Score\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\n\n### Conclusion\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\\n\\n### 5. Overall Risk Profile\\n- **Risk Factors**:\\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\\n - Excellent repayment track record is a strong positive factor.\\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\\n\\n### Risk Score Calculation\\nGiven the available information, we can assign a risk score based on the following considerations:\\n- **CIBIL Score**: Unknown (assumed neutral impact)\\n- **Credit History**: Unknown (assumed neutral impact)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\\n\\n- Excellent repayment: -20 points (from a base of 100)\\n- Reasonable loan burden: -10 points (from a base of 100)\\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\\n\\n### Final Risk Score\\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\\n\\n### Conclusion\\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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},
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},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s reliability.\n - **Document Verification**: Without a completed document verification process, we cannot confirm the authenticity of the applicant\u0027s submitted documents, which raises significant concerns about the integrity of the application.\n - **Income Assessment**: An unresolved income assessment means we cannot accurately determine the applicant\u0027s ability to repay the loan, which is a fundamental aspect of underwriting.\n - **Credit Score**: The lack of a calculated credit score prevents us from evaluating the applicant\u0027s creditworthiness and history of managing debt.\n - **Default Risk**: Without an evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is crucial for making an informed decision.\n - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory standards, which could expose the lender to legal and financial risks.\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage existing and new debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and the lack of critical information prevents us from making a responsible lending decision.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear presence of multiple unresolved issues that fundamentally undermine the viability of the loan application.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s reliability.\n - **Document Verification**: Without a completed document verification process, we cannot confirm the authenticity of the applicant\u0027s submitted documents, which raises significant concerns about the integrity of the application.\n - **Income Assessment**: An unresolved income assessment means we cannot accurately determine the applicant\u0027s ability to repay the loan, which is a fundamental aspect of underwriting.\n - **Credit Score**: The lack of a calculated credit score prevents us from evaluating the applicant\u0027s creditworthiness and history of managing debt.\n - **Default Risk**: Without an evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is crucial for making an informed decision.\n - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory standards, which could expose the lender to legal and financial risks.\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage existing and new debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and the lack of critical information prevents us from making a responsible lending decision.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear presence of multiple unresolved issues that fundamentally undermine the viability of the loan application.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\\n - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s reliability.\\n - **Document Verification**: Without a completed document verification process, we cannot confirm the authenticity of the applicant\u0027s submitted documents, which raises significant concerns about the integrity of the application.\\n - **Income Assessment**: An unresolved income assessment means we cannot accurately determine the applicant\u0027s ability to repay the loan, which is a fundamental aspect of underwriting.\\n - **Credit Score**: The lack of a calculated credit score prevents us from evaluating the applicant\u0027s creditworthiness and history of managing debt.\\n - **Default Risk**: Without an evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is crucial for making an informed decision.\\n - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory standards, which could expose the lender to legal and financial risks.\\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage existing and new debt.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and the lack of critical information prevents us from making a responsible lending decision.\\n\\n5. **Confidence Level**: 95\\n\\nThe confidence level is high due to the clear presence of multiple unresolved issues that fundamentally undermine the viability of the loan application.\", \"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_assessment\": {\n \"income_stability\": {\n \"assessment\": \"High\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to assess due to missing debt-to-income calculation.\",\n \"details\": {\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\"\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending further analysis\",\n \"details\": {\n \"salary_analysis\": \"Unresolved\",\n \"bank_statement_analysis\": \"Unresolved\",\n \"tax_returns\": \"Unresolved\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Moderate\",\n \"details\": {\n \"employment_stability\": \"High, but dependent on ongoing employment verification.\",\n \"debt_servicing\": \"Unknown due to unresolved calculations.\",\n \"financial_discipline\": \"Pending further analysis of salary, bank statements, and tax returns.\"\n },\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\",\n \"Consider additional documentation to support income verification.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"score_rationale\": {\n \"stability\": 90,\n \"debt_servicing\": 50,\n \"financial_discipline\": 60,\n \"risk_factors\": 70\n }\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\n\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\n\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\n\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\n\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"High\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to assess due to missing debt-to-income calculation.\",\n \"details\": {\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\"\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending further analysis\",\n \"details\": {\n \"salary_analysis\": \"Unresolved\",\n \"bank_statement_analysis\": \"Unresolved\",\n \"tax_returns\": \"Unresolved\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Moderate\",\n \"details\": {\n \"employment_stability\": \"High, but dependent on ongoing employment verification.\",\n \"debt_servicing\": \"Unknown due to unresolved calculations.\",\n \"financial_discipline\": \"Pending further analysis of salary, bank statements, and tax returns.\"\n },\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\",\n \"Consider additional documentation to support income verification.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"score_rationale\": {\n \"stability\": 90,\n \"debt_servicing\": 50,\n \"financial_discipline\": 60,\n \"risk_factors\": 70\n }\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\n\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\n\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\n\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\n\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\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_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to assess due to missing debt-to-income calculation.\\\",\\n \\\"details\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\\\"\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending further analysis\\\",\\n \\\"details\\\": {\\n \\\"salary_analysis\\\": \\\"Unresolved\\\",\\n \\\"bank_statement_analysis\\\": \\\"Unresolved\\\",\\n \\\"tax_returns\\\": \\\"Unresolved\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Moderate\\\",\\n \\\"details\\\": {\\n \\\"employment_stability\\\": \\\"High, but dependent on ongoing employment verification.\\\",\\n \\\"debt_servicing\\\": \\\"Unknown due to unresolved calculations.\\\",\\n \\\"financial_discipline\\\": \\\"Pending further analysis of salary, bank statements, and tax returns.\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\\\",\\n \\\"Consider additional documentation to support income verification.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"score_rationale\\\": {\\n \\\"stability\\\": 90,\\n \\\"debt_servicing\\\": 50,\\n \\\"financial_discipline\\\": 60,\\n \\\"risk_factors\\\": 70\\n }\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\\n\\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\\n\\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\\n\\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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This is critical for understanding the borrower\u0027s ability to service debt.\n\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\n\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\n\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\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_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to assess due to missing debt-to-income calculation.\\\",\\n \\\"details\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\\\"\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending further analysis\\\",\\n \\\"details\\\": {\\n \\\"salary_analysis\\\": \\\"Unresolved\\\",\\n \\\"bank_statement_analysis\\\": \\\"Unresolved\\\",\\n \\\"tax_returns\\\": \\\"Unresolved\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Moderate\\\",\\n \\\"details\\\": {\\n \\\"employment_stability\\\": \\\"High, but dependent on ongoing employment verification.\\\",\\n \\\"debt_servicing\\\": \\\"Unknown due to unresolved calculations.\\\",\\n \\\"financial_discipline\\\": \\\"Pending further analysis of salary, bank statements, and tax returns.\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\\\",\\n \\\"Consider additional documentation to support income verification.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"score_rationale\\\": {\\n \\\"stability\\\": 90,\\n \\\"debt_servicing\\\": 50,\\n \\\"financial_discipline\\\": 60,\\n \\\"risk_factors\\\": 70\\n }\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\\n\\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\\n\\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\\n\\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.279359,
"end_time": "2025-07-15T11:11:15.441603",
"message_sent": true,
"start_time": "2025-07-15T11:11:15.162244",
"timestamp": "2025-07-15T11:11:15.441603",
"worker_executed": true,
"workers_notified": true
},
"lending_norms_compliant": true,
"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"rbi_guidelines_met": true,
"regulatory_risk": "minimal",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "regulatory_compliance"
},
"status": "FAILED",
"task_outputs": {
"aml_screening": {
"adverse_media": "no_hits",
"aml_status": "cleared",
"compliance_score": 96.8,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"aml_status\": \"cleared\", \"watchlist_check\": \"no_matches\", \"pep_screening\": \"not_identified\", \"sanctions_check\": \"cleared\", \"adverse_media\": \"no_hits\", \"risk_rating\": \"low\", \"compliance_score\": 96.8, \"screening_date\": \"2024-07-15\", \"manual_review_required\": false}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.298856,
"end_time": "2025-07-15T11:11:15.212104",
"message_sent": true,
"start_time": "2025-07-15T11:11:14.913248",
"timestamp": "2025-07-15T11:11:15.212104",
"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": 0.497922,
"end_time": "2025-07-15T11:04:50.839517",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.341595",
"timestamp": "2025-07-15T11:04:50.839517",
"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": 0.272227,
"end_time": "2025-07-15T11:08:00.147515",
"message_sent": true,
"start_time": "2025-07-15T11:07:59.875288",
"timestamp": "2025-07-15T11:08:00.147515",
"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": 0.370592,
"end_time": "2025-07-15T11:04:50.659868",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.289276",
"timestamp": "2025-07-15T11:04:50.659868",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1178,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\\\"\\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": 4.478143,
"end_time": "2025-07-15T11:04:47.907990",
"message_sent": true,
"start_time": "2025-07-15T11:04:43.429847",
"timestamp": "2025-07-15T11:04:47.907990",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, and validation checks have passed, indicating that the information provided is likely accurate.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, further analysis of the actual customer information would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the absence of missing information and validation issues, though the lack of detailed customer information limits a more thorough analysis.\\\"\\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": 0.298206,
"end_time": "2025-07-15T11:08:00.479508",
"message_sent": true,
"start_time": "2025-07-15T11:08:00.181302",
"timestamp": "2025-07-15T11:08:00.479508",
"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/tmpgx8pln7k.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/tmpgx8pln7k.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/tmpaqmue9u6.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_variables.max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_variables\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/tmpaqmue9u6.py\", line 20, in \u003cmodule\u003e\n max_allowed_ratio = UNRESOLVED_variables.max_debt_to_income_ratio\n ^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_variables\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": 0.326874,
"end_time": "2025-07-15T11:07:59.928949",
"message_sent": true,
"start_time": "2025-07-15T11:07:59.602075",
"timestamp": "2025-07-15T11:07:59.928949",
"worker_executed": true,
"workers_notified": true
},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\",\n \"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\",\n \"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1126,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\",\n \"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\",\n \"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\\\",\\n \\\"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.099453,
"end_time": "2025-07-15T11:11:19.925900",
"message_sent": true,
"start_time": "2025-07-15T11:11:15.826447",
"timestamp": "2025-07-15T11:11:19.925900",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\",\n \"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\",\n \"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\",\n \"Continue to monitor internal policy adherence, as it currently shows strong compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately to mitigate identity fraud risk.\\\",\\n \\\"Address AML screening concerns to ensure compliance with anti-money laundering regulations.\\\",\\n \\\"Conduct a thorough review of regulatory compliance issues and implement necessary changes.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows strong compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 336,
"provider": "openai",
"system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 2.286666,
"end_time": "2025-07-15T11:04:50.437635",
"message_sent": true,
"start_time": "2025-07-15T11:04:48.150969",
"timestamp": "2025-07-15T11:04:50.437635",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": [],\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_verification_success_rate\\\": 100,\\n \\\"consistency_across_documents\\\": {\\n \\\"name_match\\\": true,\\n \\\"address_match\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "consolidate_document_verification"
},
"evaluate_default_risk": {
"agent_type": "assistant",
"ai_response": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\n\n### 5. Overall Risk Profile\n- **Risk Factors**:\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\n - Excellent repayment track record is a strong positive factor.\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\n\n### Risk Score Calculation\nGiven the available information, we can assign a risk score based on the following considerations:\n- **CIBIL Score**: Unknown (assumed neutral impact)\n- **Credit History**: Unknown (assumed neutral impact)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\n\n- Excellent repayment: -20 points (from a base of 100)\n- Reasonable loan burden: -10 points (from a base of 100)\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\n\n### Final Risk Score\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\n\n### Conclusion\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.",
"execution_details": {
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"provider": "openai",
"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\n\n### 5. Overall Risk Profile\n- **Risk Factors**:\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\n - Excellent repayment track record is a strong positive factor.\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\n\n### Risk Score Calculation\nGiven the available information, we can assign a risk score based on the following considerations:\n- **CIBIL Score**: Unknown (assumed neutral impact)\n- **Credit History**: Unknown (assumed neutral impact)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\n\n- Excellent repayment: -20 points (from a base of 100)\n- Reasonable loan burden: -10 points (from a base of 100)\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\n\n### Final Risk Score\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\n\n### Conclusion\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\\n\\n### 5. Overall Risk Profile\\n- **Risk Factors**:\\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\\n - Excellent repayment track record is a strong positive factor.\\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\\n\\n### Risk Score Calculation\\nGiven the available information, we can assign a risk score based on the following considerations:\\n- **CIBIL Score**: Unknown (assumed neutral impact)\\n- **Credit History**: Unknown (assumed neutral impact)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\\n\\n- Excellent repayment: -20 points (from a base of 100)\\n- Reasonable loan burden: -10 points (from a base of 100)\\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\\n\\n### Final Risk Score\\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\\n\\n### Conclusion\\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
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},
"duration_seconds": 18.398164,
"end_time": "2025-07-15T11:08:18.830085",
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"start_time": "2025-07-15T11:08:00.431921",
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"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\n- **Credit History**: Similarly, the credit history is marked as \"UNRESOLVED_analyze_credit_history.\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\n\n### 5. Overall Risk Profile\n- **Risk Factors**:\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\n - Excellent repayment track record is a strong positive factor.\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\n\n### Risk Score Calculation\nGiven the available information, we can assign a risk score based on the following considerations:\n- **CIBIL Score**: Unknown (assumed neutral impact)\n- **Credit History**: Unknown (assumed neutral impact)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (low risk)\n\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\n\n- Excellent repayment: -20 points (from a base of 100)\n- Reasonable loan burden: -10 points (from a base of 100)\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\n\n### Final Risk Score\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\n\n### Conclusion\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the various factors mentioned and assign a risk score based on the information available.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on this crucial metric. A low score typically indicates higher risk, while a high score indicates lower risk.\\n- **Credit History**: Similarly, the credit history is marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without this information, we cannot determine the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%), which is within a reasonable range. A lower ratio indicates that the individual is not over-leveraged, which is a positive factor in assessing default risk.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700, which is manageable given the loan burden ratio.\\n- **Outstanding Loans**: The individual has two loans with a total outstanding amount of 125,000. The types of loans (personal and auto) are common, and the remaining tenures are reasonable (18 and 24 months).\\n\\n### 5. Overall Risk Profile\\n- **Risk Factors**:\\n - Lack of CIBIL score and credit history data is a significant gap in the analysis.\\n - Excellent repayment track record is a strong positive factor.\\n - Reasonable loan burden ratio suggests that the individual is not over-leveraged.\\n\\n### Risk Score Calculation\\nGiven the available information, we can assign a risk score based on the following considerations:\\n- **CIBIL Score**: Unknown (assumed neutral impact)\\n- **Credit History**: Unknown (assumed neutral impact)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (low risk)\\n\\nConsidering the excellent repayment track record and reasonable loan burden ratio, but factoring in the unknowns regarding the credit score and history, we can assign a risk score as follows:\\n\\n- Excellent repayment: -20 points (from a base of 100)\\n- Reasonable loan burden: -10 points (from a base of 100)\\n- Unknown credit score and history: +30 points (increased risk due to uncertainty)\\n\\n### Final Risk Score\\n**Risk Score: 100 - 20 - 10 + 30 = 100 - 0 = 70**\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and review the CIBIL score to better understand creditworthiness.\\n2. **Analyze Credit History**: Review the credit history for any missed payments or negative marks that could affect future lending.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments on existing loans to maintain the excellent repayment track record.\\n4. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health and improve creditworthiness.\\n5. **Consider Financial Counseling**: If there are uncertainties regarding credit management, consider consulting with a financial advisor to improve overall credit health.\\n\\n### Conclusion\\nThe overall risk score of 70 indicates a moderate risk of default, primarily due to the lack of information regarding the CIBIL score and credit history. Addressing these gaps will provide a clearer picture of the individual\u0027s credit risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
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},
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"end_time": "2025-07-15T11:04:43.210185",
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"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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},
"final_underwriting_analysis": {
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"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s reliability.\n - **Document Verification**: Without a completed document verification process, we cannot confirm the authenticity of the applicant\u0027s submitted documents, which raises significant concerns about the integrity of the application.\n - **Income Assessment**: An unresolved income assessment means we cannot accurately determine the applicant\u0027s ability to repay the loan, which is a fundamental aspect of underwriting.\n - **Credit Score**: The lack of a calculated credit score prevents us from evaluating the applicant\u0027s creditworthiness and history of managing debt.\n - **Default Risk**: Without an evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is crucial for making an informed decision.\n - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory standards, which could expose the lender to legal and financial risks.\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage existing and new debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and the lack of critical information prevents us from making a responsible lending decision.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear presence of multiple unresolved issues that fundamentally undermine the viability of the loan application.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\n - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s reliability.\n - **Document Verification**: Without a completed document verification process, we cannot confirm the authenticity of the applicant\u0027s submitted documents, which raises significant concerns about the integrity of the application.\n - **Income Assessment**: An unresolved income assessment means we cannot accurately determine the applicant\u0027s ability to repay the loan, which is a fundamental aspect of underwriting.\n - **Credit Score**: The lack of a calculated credit score prevents us from evaluating the applicant\u0027s creditworthiness and history of managing debt.\n - **Default Risk**: Without an evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is crucial for making an informed decision.\n - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory standards, which could expose the lender to legal and financial risks.\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage existing and new debt.\n\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and the lack of critical information prevents us from making a responsible lending decision.\n\n5. **Confidence Level**: 95\n\nThe confidence level is high due to the clear presence of multiple unresolved issues that fundamentally undermine the viability of the loan application.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically:\\n - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s reliability.\\n - **Document Verification**: Without a completed document verification process, we cannot confirm the authenticity of the applicant\u0027s submitted documents, which raises significant concerns about the integrity of the application.\\n - **Income Assessment**: An unresolved income assessment means we cannot accurately determine the applicant\u0027s ability to repay the loan, which is a fundamental aspect of underwriting.\\n - **Credit Score**: The lack of a calculated credit score prevents us from evaluating the applicant\u0027s creditworthiness and history of managing debt.\\n - **Default Risk**: Without an evaluation of default risk, we cannot ascertain the likelihood of the applicant defaulting on the loan, which is crucial for making an informed decision.\\n - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory standards, which could expose the lender to legal and financial risks.\\n - **Debt-to-Income Ratio**: An unresolved debt-to-income calculation means we cannot assess the applicant\u0027s financial health and ability to manage existing and new debt.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is too high, and the lack of critical information prevents us from making a responsible lending decision.\\n\\n5. **Confidence Level**: 95\\n\\nThe confidence level is high due to the clear presence of multiple unresolved issues that fundamentally undermine the viability of the loan application.\", \"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_assessment\": {\n \"income_stability\": {\n \"assessment\": \"High\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to assess due to missing debt-to-income calculation.\",\n \"details\": {\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\"\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending further analysis\",\n \"details\": {\n \"salary_analysis\": \"Unresolved\",\n \"bank_statement_analysis\": \"Unresolved\",\n \"tax_returns\": \"Unresolved\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Moderate\",\n \"details\": {\n \"employment_stability\": \"High, but dependent on ongoing employment verification.\",\n \"debt_servicing\": \"Unknown due to unresolved calculations.\",\n \"financial_discipline\": \"Pending further analysis of salary, bank statements, and tax returns.\"\n },\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\",\n \"Consider additional documentation to support income verification.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"score_rationale\": {\n \"stability\": 90,\n \"debt_servicing\": 50,\n \"financial_discipline\": 60,\n \"risk_factors\": 70\n }\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\n\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\n\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\n\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\n\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.",
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"system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
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"output": "Based on the provided income data and the context of the analysis, here is a detailed JSON assessment:\n\n```json\n{\n \"income_assessment\": {\n \"income_stability\": {\n \"assessment\": \"High\",\n \"details\": {\n \"employment_type\": \"Permanent\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"probation_status\": \"Confirmed\",\n \"employment_verified\": true,\n \"reference_check_passed\": true\n }\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to assess due to missing debt-to-income calculation.\",\n \"details\": {\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\"\n }\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending further analysis\",\n \"details\": {\n \"salary_analysis\": \"Unresolved\",\n \"bank_statement_analysis\": \"Unresolved\",\n \"tax_returns\": \"Unresolved\"\n }\n },\n \"risk_factors\": {\n \"assessment\": \"Moderate\",\n \"details\": {\n \"employment_stability\": \"High, but dependent on ongoing employment verification.\",\n \"debt_servicing\": \"Unknown due to unresolved calculations.\",\n \"financial_discipline\": \"Pending further analysis of salary, bank statements, and tax returns.\"\n },\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\",\n \"Consider additional documentation to support income verification.\"\n ]\n },\n \"overall_income_adequacy_score\": 75,\n \"score_rationale\": {\n \"stability\": 90,\n \"debt_servicing\": 50,\n \"financial_discipline\": 60,\n \"risk_factors\": 70\n }\n }\n}\n```\n\n### Explanation of the JSON Assessment:\n\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\n\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\n\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\n\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\n\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\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_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to assess due to missing debt-to-income calculation.\\\",\\n \\\"details\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\\\"\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending further analysis\\\",\\n \\\"details\\\": {\\n \\\"salary_analysis\\\": \\\"Unresolved\\\",\\n \\\"bank_statement_analysis\\\": \\\"Unresolved\\\",\\n \\\"tax_returns\\\": \\\"Unresolved\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Moderate\\\",\\n \\\"details\\\": {\\n \\\"employment_stability\\\": \\\"High, but dependent on ongoing employment verification.\\\",\\n \\\"debt_servicing\\\": \\\"Unknown due to unresolved calculations.\\\",\\n \\\"financial_discipline\\\": \\\"Pending further analysis of salary, bank statements, and tax returns.\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\\\",\\n \\\"Consider additional documentation to support income verification.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"score_rationale\\\": {\\n \\\"stability\\\": 90,\\n \\\"debt_servicing\\\": 50,\\n \\\"financial_discipline\\\": 60,\\n \\\"risk_factors\\\": 70\\n }\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\\n\\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\\n\\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\\n\\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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This is critical for understanding the borrower\u0027s ability to service debt.\n\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\n\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\n\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\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_assessment\\\": {\\n \\\"income_stability\\\": {\\n \\\"assessment\\\": \\\"High\\\",\\n \\\"details\\\": {\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"employment_verified\\\": true,\\n \\\"reference_check_passed\\\": true\\n }\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to assess due to missing debt-to-income calculation.\\\",\\n \\\"details\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation error to evaluate debt servicing capability.\\\"\\n }\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending further analysis\\\",\\n \\\"details\\\": {\\n \\\"salary_analysis\\\": \\\"Unresolved\\\",\\n \\\"bank_statement_analysis\\\": \\\"Unresolved\\\",\\n \\\"tax_returns\\\": \\\"Unresolved\\\"\\n }\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Moderate\\\",\\n \\\"details\\\": {\\n \\\"employment_stability\\\": \\\"High, but dependent on ongoing employment verification.\\\",\\n \\\"debt_servicing\\\": \\\"Unknown due to unresolved calculations.\\\",\\n \\\"financial_discipline\\\": \\\"Pending further analysis of salary, bank statements, and tax returns.\\\"\\n },\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary slips, bank statements, and tax returns to assess financial discipline.\\\",\\n \\\"Consider additional documentation to support income verification.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": 75,\\n \\\"score_rationale\\\": {\\n \\\"stability\\\": 90,\\n \\\"debt_servicing\\\": 50,\\n \\\"financial_discipline\\\": 60,\\n \\\"risk_factors\\\": 70\\n }\\n }\\n}\\n```\\n\\n### Explanation of the JSON Assessment:\\n\\n1. **Income Stability Assessment**: The employment details indicate a high level of stability due to a permanent position, high employer rating, and confirmed probation status.\\n\\n2. **Debt Servicing Capability**: Unable to assess due to an error in the debt-to-income calculation. This is critical for understanding the borrower\u0027s ability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Pending further analysis as the salary slips, bank statements, and tax returns are unresolved.\\n\\n4. **Risk Factors and Recommendations**: The assessment indicates moderate risk due to the unknown debt servicing capability and pending financial discipline analysis. Recommendations include resolving the debt-to-income calculation error and reviewing additional financial documentation.\\n\\n5. **Overall Income Adequacy Score**: A score of 75 reflects a strong employment situation but is tempered by the unresolved issues regarding debt servicing and financial discipline. The score is derived from individual assessments of stability, debt servicing, financial discipline, and risk factors.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.279359,
"end_time": "2025-07-15T11:11:15.441603",
"message_sent": true,
"start_time": "2025-07-15T11:11:15.162244",
"timestamp": "2025-07-15T11:11:15.441603",
"worker_executed": true,
"workers_notified": true
},
"lending_norms_compliant": true,
"output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
"rbi_guidelines_met": true,
"regulatory_risk": "minimal",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "regulatory_compliance"
},
"underwriting_decision_router": {
"all_conditions_checked": [
{
"condition": "${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50",
"name": "high_risk_path",
"result": false,
"route": "decline_path"
},
{
"condition": "${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700",
"name": "conditional_approval_path",
"result": false,
"route": "conditional_path"
},
{
"condition": "${calculate_credit_score.internal_credit_score} \u003e= 700",
"name": "standard_approval_path",
"result": false,
"route": "approval_path"
}
],
"duration_seconds": 0.000903,
"ended_at": "2025-07-15T11:11:19.981636",
"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\": 0.000903, \"started_at\": \"2025-07-15T11:11:19.980733\", \"ended_at\": \"2025-07-15T11:11:19.981636\"}",
"return_code": 0,
"status": "completed",
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},
"duration_seconds": 0.28091,
"end_time": "2025-07-15T11:11:20.145718",
"message_sent": true,
"start_time": "2025-07-15T11:11:19.864808",
"timestamp": "2025-07-15T11:11:20.145718",
"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\": 0.000903, \"started_at\": \"2025-07-15T11:11:19.980733\", \"ended_at\": \"2025-07-15T11:11:19.981636\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T11:11:19.980733",
"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": ""
},
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"end_time": "2025-07-15T11:04:43.465581",
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"timestamp": "2025-07-15T11:04:43.465581",
"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": 0.516981,
"end_time": "2025-07-15T11:04:47.742048",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.225067",
"timestamp": "2025-07-15T11:04:47.742048",
"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": 0.935089,
"end_time": "2025-07-15T11:04:48.242701",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.307612",
"timestamp": "2025-07-15T11:04:48.242701",
"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": 0.559631,
"end_time": "2025-07-15T11:04:51.256698",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.697067",
"timestamp": "2025-07-15T11:04:51.256698",
"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": 0.361102,
"end_time": "2025-07-15T11:04:47.549792",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.188690",
"timestamp": "2025-07-15T11:04:47.549792",
"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": 0.942937,
"end_time": "2025-07-15T11:04:48.207755",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.264818",
"timestamp": "2025-07-15T11:04:48.207755",
"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": 0.78659,
"end_time": "2025-07-15T11:04:51.170107",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.383517",
"timestamp": "2025-07-15T11:04:51.170107",
"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": 0.000903,
"ended_at": "2025-07-15T11:11:19.981636",
"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\": 0.000903, \"started_at\": \"2025-07-15T11:11:19.980733\", \"ended_at\": \"2025-07-15T11:11:19.981636\"}",
"return_code": 0,
"status": "completed",
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},
"duration_seconds": 0.28091,
"end_time": "2025-07-15T11:11:20.145718",
"message_sent": true,
"start_time": "2025-07-15T11:11:19.864808",
"timestamp": "2025-07-15T11:11:20.145718",
"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\": 0.000903, \"started_at\": \"2025-07-15T11:11:19.980733\", \"ended_at\": \"2025-07-15T11:11:19.981636\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T11:11:19.980733",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"validate_application_fields": {
"completion_percentage": 100.0,
"execution_details": {
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"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.294761,
"end_time": "2025-07-15T11:04:43.465581",
"message_sent": true,
"start_time": "2025-07-15T11:04:43.170820",
"timestamp": "2025-07-15T11:04:43.465581",
"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",
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},
"duration_seconds": 0.516981,
"end_time": "2025-07-15T11:04:47.742048",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.225067",
"timestamp": "2025-07-15T11:04:47.742048",
"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": 0.935089,
"end_time": "2025-07-15T11:04:48.242701",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.307612",
"timestamp": "2025-07-15T11:04:48.242701",
"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": 0.559631,
"end_time": "2025-07-15T11:04:51.256698",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.697067",
"timestamp": "2025-07-15T11:04:51.256698",
"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": 0.361102,
"end_time": "2025-07-15T11:04:47.549792",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.188690",
"timestamp": "2025-07-15T11:04:47.549792",
"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,
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},
"duration_seconds": 0.942937,
"end_time": "2025-07-15T11:04:48.207755",
"message_sent": true,
"start_time": "2025-07-15T11:04:47.264818",
"timestamp": "2025-07-15T11:04:48.207755",
"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": 0.78659,
"end_time": "2025-07-15T11:04:51.170107",
"message_sent": true,
"start_time": "2025-07-15T11:04:50.383517",
"timestamp": "2025-07-15T11:04:51.170107",
"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
}
}