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": 0.296991,
"end_time": "2025-07-15T11:47:08.211061",
"message_sent": true,
"start_time": "2025-07-15T11:47:07.914070",
"timestamp": "2025-07-15T11:47:08.211061",
"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": 0.486513,
"end_time": "2025-07-15T11:40:46.028890",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.542377",
"timestamp": "2025-07-15T11:40:46.028890",
"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": 0.251581,
"end_time": "2025-07-15T11:43:55.198302",
"message_sent": true,
"start_time": "2025-07-15T11:43:54.946721",
"timestamp": "2025-07-15T11:43:55.198302",
"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": 0.398617,
"end_time": "2025-07-15T11:40:45.900425",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.501808",
"timestamp": "2025-07-15T11:40:45.900425",
"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 is complete with no missing fields, and all provided information has passed validation checks.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1046,
"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 is complete with no missing fields, and all provided information has passed validation checks.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\"\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 is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\\\"\\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": 4.183411,
"end_time": "2025-07-15T11:40:43.115697",
"message_sent": true,
"start_time": "2025-07-15T11:40:38.932286",
"timestamp": "2025-07-15T11:40:43.115697",
"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 is complete with no missing fields, and all provided information has passed validation checks.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\"\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 is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\\\"\\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": 0.324871,
"end_time": "2025-07-15T11:43:55.559270",
"message_sent": true,
"start_time": "2025-07-15T11:43:55.234399",
"timestamp": "2025-07-15T11:43:55.559270",
"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/tmpasv_rod2.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/tmpasv_rod2.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/tmpk78w7hc7.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/tmpk78w7hc7.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": 0.262582,
"end_time": "2025-07-15T11:43:54.987348",
"message_sent": true,
"start_time": "2025-07-15T11:43:54.724766",
"timestamp": "2025-07-15T11:43:54.987348",
"worker_executed": true,
"workers_notified": true
},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"InternalPolicy\": \"Low risk; internal policy criteria are met.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\",\n \"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\",\n \"Continue to adhere to internal policy guidelines, as they are currently being met.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1206,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"InternalPolicy\": \"Low risk; internal policy criteria are met.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\",\n \"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\",\n \"Continue to adhere to internal policy guidelines, as they are currently being met.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"InternalPolicy\\\": \\\"Low risk; internal policy criteria are met.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\\\",\\n \\\"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\\\",\\n \\\"Continue to adhere to internal policy guidelines, as they are currently being met.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 5.213257,
"end_time": "2025-07-15T11:47:13.981556",
"message_sent": true,
"start_time": "2025-07-15T11:47:08.768299",
"timestamp": "2025-07-15T11:47:13.981556",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"InternalPolicy\": \"Low risk; internal policy criteria are met.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\",\n \"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\",\n \"Continue to adhere to internal policy guidelines, as they are currently being met.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"InternalPolicy\\\": \\\"Low risk; internal policy criteria are met.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\\\",\\n \\\"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\\\",\\n \\\"Continue to adhere to internal policy guidelines, as they are currently being met.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": {\n \"none\": true\n },\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 364,
"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 \"none\": true\n },\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\"\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 \\\"none\\\": true\\n },\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\\\"\\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": 2.522437,
"end_time": "2025-07-15T11:40:46.374284",
"message_sent": true,
"start_time": "2025-07-15T11:40:43.851847",
"timestamp": "2025-07-15T11:40:46.374284",
"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 \"none\": true\n },\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\"\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 \\\"none\\\": true\\n },\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\\\"\\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 key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Total Outstanding**: The total outstanding amount is 125,000.\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\n\n### Risk Score Calculation\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\n- **Repayment Track Record**: Excellent (score of 10).\n- **Loan Burden Ratio**: 28% (score of 20).\n- **Existing Loans**: Two loans (score of 15).\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\n\n### Risk Score Calculation\n- CIBIL Score: 50\n- Repayment Track Record: 10\n- Loan Burden Ratio: 20\n- Existing Loans: 15\n- Overall Risk Profile: 30 (due to unresolved credit score)\n\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\n\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\n\n**Final Risk Score = (125/125) * 100 = 100**\n\n### Default Risk Assessment\n- **Risk Score**: 100 (High Risk)\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\n\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 561,
"model": "gpt-4o-mini",
"output_length": 3383,
"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 key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Total Outstanding**: The total outstanding amount is 125,000.\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\n\n### Risk Score Calculation\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\n- **Repayment Track Record**: Excellent (score of 10).\n- **Loan Burden Ratio**: 28% (score of 20).\n- **Existing Loans**: Two loans (score of 15).\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\n\n### Risk Score Calculation\n- CIBIL Score: 50\n- Repayment Track Record: 10\n- Loan Burden Ratio: 20\n- Existing Loans: 15\n- Overall Risk Profile: 30 (due to unresolved credit score)\n\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\n\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\n\n**Final Risk Score = (125/125) * 100 = 100**\n\n### Default Risk Assessment\n- **Risk Score**: 100 (High Risk)\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\n\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Total Outstanding**: The total outstanding amount is 125,000.\\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\\n\\n### Risk Score Calculation\\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\\n- **Repayment Track Record**: Excellent (score of 10).\\n- **Loan Burden Ratio**: 28% (score of 20).\\n- **Existing Loans**: Two loans (score of 15).\\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\\n\\n### Risk Score Calculation\\n- CIBIL Score: 50\\n- Repayment Track Record: 10\\n- Loan Burden Ratio: 20\\n- Existing Loans: 15\\n- Overall Risk Profile: 30 (due to unresolved credit score)\\n\\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\\n\\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\\n\\n**Final Risk Score = (125/125) * 100 = 100**\\n\\n### Default Risk Assessment\\n- **Risk Score**: 100 (High Risk)\\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\\n\\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 13.051762,
"end_time": "2025-07-15T11:44:08.563781",
"message_sent": true,
"start_time": "2025-07-15T11:43:55.512019",
"timestamp": "2025-07-15T11:44:08.563781",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Total Outstanding**: The total outstanding amount is 125,000.\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\n\n### Risk Score Calculation\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\n- **Repayment Track Record**: Excellent (score of 10).\n- **Loan Burden Ratio**: 28% (score of 20).\n- **Existing Loans**: Two loans (score of 15).\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\n\n### Risk Score Calculation\n- CIBIL Score: 50\n- Repayment Track Record: 10\n- Loan Burden Ratio: 20\n- Existing Loans: 15\n- Overall Risk Profile: 30 (due to unresolved credit score)\n\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\n\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\n\n**Final Risk Score = (125/125) * 100 = 100**\n\n### Default Risk Assessment\n- **Risk Score**: 100 (High Risk)\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\n\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Total Outstanding**: The total outstanding amount is 125,000.\\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\\n\\n### Risk Score Calculation\\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\\n- **Repayment Track Record**: Excellent (score of 10).\\n- **Loan Burden Ratio**: 28% (score of 20).\\n- **Existing Loans**: Two loans (score of 15).\\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\\n\\n### Risk Score Calculation\\n- CIBIL Score: 50\\n- Repayment Track Record: 10\\n- Loan Burden Ratio: 20\\n- Existing Loans: 15\\n- Overall Risk Profile: 30 (due to unresolved credit score)\\n\\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\\n\\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\\n\\n**Final Risk Score = (125/125) * 100 = 100**\\n\\n### Default Risk Assessment\\n- **Risk Score**: 100 (High Risk)\\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\\n\\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "evaluate_default_risk"
},
"execution_summary": {
"completed_tasks": 24,
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"end_time": "2025-07-15T11:53:18.132793",
"execution_mode": "distributed",
"start_time": "2025-07-15T11:40:37.767295",
"total_tasks": 28
},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.252556,
"end_time": "2025-07-15T11:40:38.705422",
"message_sent": true,
"start_time": "2025-07-15T11:40:38.452866",
"timestamp": "2025-07-15T11:40:38.705422",
"worker_executed": true,
"workers_notified": true
},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "extract_application_info"
},
"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 484,
"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.271243,
"end_time": "2025-07-15T11:47:18.006852",
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"start_time": "2025-07-15T11:47:13.735609",
"timestamp": "2025-07-15T11:47:18.006852",
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},
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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, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"ai_response": "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 stability due to permanent employment and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"employment_type\": \"permanent\",\n \"recommendation\": \"Continue monitoring for any changes in employment status.\"\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to calculate due to unresolved debt-to-income ratio.\",\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation issue to assess servicing capability.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending analysis of salary slips and bank statements.\",\n \"recommendation\": \"Review salary slips and bank statements to evaluate spending habits and savings.\"\n },\n \"risk_factors\": {\n \"assessment\": \"Potential risks due to unresolved calculations and lack of detailed income data.\",\n \"identified_risks\": [\n \"Uncertainty in debt servicing capability\",\n \"Inadequate financial discipline assessment\",\n \"Dependence on employment stability\"\n ],\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary and bank statements.\",\n \"Consider additional income sources or savings to mitigate risks.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 75,\n \"justification\": \"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\"\n }\n }\n}\n```\n\n### Explanation of the Assessment:\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\n \n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\n\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\n\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.",
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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 stability due to permanent employment and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"employment_type\": \"permanent\",\n \"recommendation\": \"Continue monitoring for any changes in employment status.\"\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to calculate due to unresolved debt-to-income ratio.\",\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation issue to assess servicing capability.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending analysis of salary slips and bank statements.\",\n \"recommendation\": \"Review salary slips and bank statements to evaluate spending habits and savings.\"\n },\n \"risk_factors\": {\n \"assessment\": \"Potential risks due to unresolved calculations and lack of detailed income data.\",\n \"identified_risks\": [\n \"Uncertainty in debt servicing capability\",\n \"Inadequate financial discipline assessment\",\n \"Dependence on employment stability\"\n ],\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary and bank statements.\",\n \"Consider additional income sources or savings to mitigate risks.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 75,\n \"justification\": \"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\"\n }\n }\n}\n```\n\n### Explanation of the Assessment:\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\n \n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\n\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\n\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\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 stability due to permanent employment and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"recommendation\\\": \\\"Continue monitoring for any changes in employment status.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to calculate due to unresolved debt-to-income ratio.\\\",\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation issue to assess servicing capability.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending analysis of salary slips and bank statements.\\\",\\n \\\"recommendation\\\": \\\"Review salary slips and bank statements to evaluate spending habits and savings.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Potential risks due to unresolved calculations and lack of detailed income data.\\\",\\n \\\"identified_risks\\\": [\\n \\\"Uncertainty in debt servicing capability\\\",\\n \\\"Inadequate financial discipline assessment\\\",\\n \\\"Dependence on employment stability\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary and bank statements.\\\",\\n \\\"Consider additional income sources or savings to mitigate risks.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 75,\\n \\\"justification\\\": \\\"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\\\"\\n }\\n }\\n}\\n```\\n\\n### Explanation of the Assessment:\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\\n \\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\\n\\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\\n\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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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 stability due to permanent employment and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"employment_type\": \"permanent\",\n \"recommendation\": \"Continue monitoring for any changes in employment status.\"\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to calculate due to unresolved debt-to-income ratio.\",\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation issue to assess servicing capability.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending analysis of salary slips and bank statements.\",\n \"recommendation\": \"Review salary slips and bank statements to evaluate spending habits and savings.\"\n },\n \"risk_factors\": {\n \"assessment\": \"Potential risks due to unresolved calculations and lack of detailed income data.\",\n \"identified_risks\": [\n \"Uncertainty in debt servicing capability\",\n \"Inadequate financial discipline assessment\",\n \"Dependence on employment stability\"\n ],\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary and bank statements.\",\n \"Consider additional income sources or savings to mitigate risks.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 75,\n \"justification\": \"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\"\n }\n }\n}\n```\n\n### Explanation of the Assessment:\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\n \n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\n\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\n\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\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 stability due to permanent employment and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"recommendation\\\": \\\"Continue monitoring for any changes in employment status.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to calculate due to unresolved debt-to-income ratio.\\\",\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation issue to assess servicing capability.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending analysis of salary slips and bank statements.\\\",\\n \\\"recommendation\\\": \\\"Review salary slips and bank statements to evaluate spending habits and savings.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Potential risks due to unresolved calculations and lack of detailed income data.\\\",\\n \\\"identified_risks\\\": [\\n \\\"Uncertainty in debt servicing capability\\\",\\n \\\"Inadequate financial discipline assessment\\\",\\n \\\"Dependence on employment stability\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary and bank statements.\\\",\\n \\\"Consider additional income sources or savings to mitigate risks.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 75,\\n \\\"justification\\\": \\\"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\\\"\\n }\\n }\\n}\\n```\\n\\n### Explanation of the Assessment:\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\\n \\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\\n\\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\\n\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"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": 0.398617,
"end_time": "2025-07-15T11:40:45.900425",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.501808",
"timestamp": "2025-07-15T11:40:45.900425",
"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 is complete with no missing fields, and all provided information has passed validation checks.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1046,
"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 is complete with no missing fields, and all provided information has passed validation checks.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\"\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 is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\\\"\\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": 4.183411,
"end_time": "2025-07-15T11:40:43.115697",
"message_sent": true,
"start_time": "2025-07-15T11:40:38.932286",
"timestamp": "2025-07-15T11:40:43.115697",
"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 is complete with no missing fields, and all provided information has passed validation checks.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n },\n \"red_flags_or inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\"\n },\n \"overall_application_quality_score\": 95,\n \"comments\": \"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\"\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 is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n },\\n \\\"red_flags_or inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. The application appears to be in good standing.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"comments\\\": \\\"The application is complete and validated successfully. However, without specific details on the customer information, a perfect score cannot be assigned. A score of 95 reflects high quality with room for improvement in transparency.\\\"\\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": 0.324871,
"end_time": "2025-07-15T11:43:55.559270",
"message_sent": true,
"start_time": "2025-07-15T11:43:55.234399",
"timestamp": "2025-07-15T11:43:55.559270",
"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/tmpasv_rod2.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/tmpasv_rod2.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/tmpk78w7hc7.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/tmpk78w7hc7.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": 0.262582,
"end_time": "2025-07-15T11:43:54.987348",
"message_sent": true,
"start_time": "2025-07-15T11:43:54.724766",
"timestamp": "2025-07-15T11:43:54.987348",
"worker_executed": true,
"workers_notified": true
},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"InternalPolicy\": \"Low risk; internal policy criteria are met.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\",\n \"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\",\n \"Continue to adhere to internal policy guidelines, as they are currently being met.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1206,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"InternalPolicy\": \"Low risk; internal policy criteria are met.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\",\n \"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\",\n \"Continue to adhere to internal policy guidelines, as they are currently being met.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"InternalPolicy\\\": \\\"Low risk; internal policy criteria are met.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\\\",\\n \\\"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\\\",\\n \\\"Continue to adhere to internal policy guidelines, as they are currently being met.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 5.213257,
"end_time": "2025-07-15T11:47:13.981556",
"message_sent": true,
"start_time": "2025-07-15T11:47:08.768299",
"timestamp": "2025-07-15T11:47:13.981556",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"UNRESOLVED\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"InternalPolicy\": \"Low risk; internal policy criteria are met.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\",\n \"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\",\n \"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\",\n \"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\",\n \"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\",\n \"Continue to adhere to internal policy guidelines, as they are currently being met.\"\n ],\n \"compliance_confidence_score\": 30\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"InternalPolicy\\\": \\\"Low risk; internal policy criteria are met.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of non-compliance with customer identification regulations.\\\",\\n \\\"Unresolved AML screening could lead to potential violations of anti-money laundering laws.\\\",\\n \\\"Unresolved regulatory compliance issues may result in penalties or legal repercussions.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving the KYC compliance check to ensure customer identification processes are in place.\\\",\\n \\\"Address the unresolved AML screening to mitigate risks associated with money laundering activities.\\\",\\n \\\"Investigate and resolve any outstanding regulatory compliance issues to avoid potential legal consequences.\\\",\\n \\\"Continue to adhere to internal policy guidelines, as they are currently being met.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 30\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true\n },\n \"risk_factors_identified\": {\n \"none\": true\n },\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 822,
"model": "gpt-4o-mini",
"output_length": 364,
"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 \"none\": true\n },\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\"\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 \\\"none\\\": true\\n },\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\\\"\\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": 2.522437,
"end_time": "2025-07-15T11:40:46.374284",
"message_sent": true,
"start_time": "2025-07-15T11:40:43.851847",
"timestamp": "2025-07-15T11:40:46.374284",
"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 \"none\": true\n },\n \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\"\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 \\\"none\\\": true\\n },\\n \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistency. Proceed with the next steps in the process.\\\"\\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 key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Total Outstanding**: The total outstanding amount is 125,000.\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\n\n### Risk Score Calculation\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\n- **Repayment Track Record**: Excellent (score of 10).\n- **Loan Burden Ratio**: 28% (score of 20).\n- **Existing Loans**: Two loans (score of 15).\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\n\n### Risk Score Calculation\n- CIBIL Score: 50\n- Repayment Track Record: 10\n- Loan Burden Ratio: 20\n- Existing Loans: 15\n- Overall Risk Profile: 30 (due to unresolved credit score)\n\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\n\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\n\n**Final Risk Score = (125/125) * 100 = 100**\n\n### Default Risk Assessment\n- **Risk Score**: 100 (High Risk)\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\n\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.",
"execution_details": {
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"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data for default risk, we will evaluate the key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Total Outstanding**: The total outstanding amount is 125,000.\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\n\n### Risk Score Calculation\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\n- **Repayment Track Record**: Excellent (score of 10).\n- **Loan Burden Ratio**: 28% (score of 20).\n- **Existing Loans**: Two loans (score of 15).\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\n\n### Risk Score Calculation\n- CIBIL Score: 50\n- Repayment Track Record: 10\n- Loan Burden Ratio: 20\n- Existing Loans: 15\n- Overall Risk Profile: 30 (due to unresolved credit score)\n\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\n\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\n\n**Final Risk Score = (125/125) * 100 = 100**\n\n### Default Risk Assessment\n- **Risk Score**: 100 (High Risk)\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\n\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Total Outstanding**: The total outstanding amount is 125,000.\\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\\n\\n### Risk Score Calculation\\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\\n- **Repayment Track Record**: Excellent (score of 10).\\n- **Loan Burden Ratio**: 28% (score of 20).\\n- **Existing Loans**: Two loans (score of 15).\\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\\n\\n### Risk Score Calculation\\n- CIBIL Score: 50\\n- Repayment Track Record: 10\\n- Loan Burden Ratio: 20\\n- Existing Loans: 15\\n- Overall Risk Profile: 30 (due to unresolved credit score)\\n\\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\\n\\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\\n\\n**Final Risk Score = (125/125) * 100 = 100**\\n\\n### Default Risk Assessment\\n- **Risk Score**: 100 (High Risk)\\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\\n\\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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},
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"end_time": "2025-07-15T11:44:08.563781",
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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 key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: The total monthly EMI is 7700.\n- **Total Outstanding**: The total outstanding amount is 125,000.\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\n\n### Risk Score Calculation\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\n- **Repayment Track Record**: Excellent (score of 10).\n- **Loan Burden Ratio**: 28% (score of 20).\n- **Existing Loans**: Two loans (score of 15).\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\n\n### Risk Score Calculation\n- CIBIL Score: 50\n- Repayment Track Record: 10\n- Loan Burden Ratio: 20\n- Existing Loans: 15\n- Overall Risk Profile: 30 (due to unresolved credit score)\n\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\n\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\n\n**Final Risk Score = (125/125) * 100 = 100**\n\n### Default Risk Assessment\n- **Risk Score**: 100 (High Risk)\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\n\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data for default risk, we will evaluate the key components: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile. \\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which is critical as it is a primary indicator of creditworthiness. A low or unresolved score can significantly increase default risk.\\n- **Credit History**: The history is also unresolved. Without specific details, we cannot assess the length of credit history, types of credit used, or any past delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the borrower has consistently made payments on time, which is a positive factor in assessing default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This indicates that 28% of the borrower\u0027s income is being used to service existing debt, which is within a manageable range (generally, below 30% is considered good). \\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: The total monthly EMI is 7700.\\n- **Total Outstanding**: The total outstanding amount is 125,000.\\n- **Number of Loans**: The borrower has two loans (personal and auto), which can diversify risk but also indicates multiple obligations.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a manageable loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant red flags that could indicate potential issues.\\n\\n### Risk Score Calculation\\n- **CIBIL Score**: Unresolved (assume a score of 50 for calculation purposes, as it could be low).\\n- **Repayment Track Record**: Excellent (score of 10).\\n- **Loan Burden Ratio**: 28% (score of 20).\\n- **Existing Loans**: Two loans (score of 15).\\n- **Overall Risk Profile**: Considering the unresolved credit score and history, we will assign a higher risk score.\\n\\n### Risk Score Calculation\\n- CIBIL Score: 50\\n- Repayment Track Record: 10\\n- Loan Burden Ratio: 20\\n- Existing Loans: 15\\n- Overall Risk Profile: 30 (due to unresolved credit score)\\n\\n**Total Risk Score = 50 + 10 + 20 + 15 + 30 = 125**\\n\\nTo normalize this to a 1-100 scale, we can divide by 125 and multiply by 100:\\n\\n**Final Risk Score = (125/125) * 100 = 100**\\n\\n### Default Risk Assessment\\n- **Risk Score**: 100 (High Risk)\\n- The unresolved CIBIL score and credit history are major concerns that overshadow the otherwise positive repayment patterns and loan burden ratio. \\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to understand the actual creditworthiness.\\n2. **Review Credit History**: Analyze the credit history for any potential issues that need to be addressed.\\n3. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n4. **Consider Reducing Debt**: If possible, work on reducing the outstanding loans to lower the total monthly EMI and improve the loan burden ratio.\\n5. **Monitor Credit Utilization**: Keep credit utilization low to maintain a healthy credit profile.\\n\\nBy addressing the unresolved aspects of the credit data, the borrower can potentially lower their default risk and improve their overall creditworthiness.\", \"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",
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"timestamp": "2025-07-15T11:40:38.705422",
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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, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.",
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"system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
},
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\n\n5. **Confidence Level**: 95\n\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score calculation, default risk evaluation, compliance consolidation, and debt-to-income ratio calculation. Each of these factors is essential in determining the borrower\u0027s ability to repay the loan and the overall risk associated with lending to them. The lack of resolution in these areas indicates significant uncertainty regarding the applicant\u0027s financial stability and creditworthiness. Without clear and verified information, it is impossible to make an informed lending decision, and proceeding with the loan would expose the institution to undue risk.\\n\\n5. **Confidence Level**: 95\\n\\nThe high confidence level reflects the clear and present risks associated with the unresolved assessments, which collectively indicate that the applicant does not meet the necessary criteria for loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"flag_for_manual_review": {
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"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpk4_ijez8.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
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"output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpk4_ijez8.py\", line 15, in \u003cmodule\u003e\n \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
"status": "FAILED",
"task_id": "generate_final_output"
},
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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 stability due to permanent employment and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"employment_type\": \"permanent\",\n \"recommendation\": \"Continue monitoring for any changes in employment status.\"\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to calculate due to unresolved debt-to-income ratio.\",\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation issue to assess servicing capability.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending analysis of salary slips and bank statements.\",\n \"recommendation\": \"Review salary slips and bank statements to evaluate spending habits and savings.\"\n },\n \"risk_factors\": {\n \"assessment\": \"Potential risks due to unresolved calculations and lack of detailed income data.\",\n \"identified_risks\": [\n \"Uncertainty in debt servicing capability\",\n \"Inadequate financial discipline assessment\",\n \"Dependence on employment stability\"\n ],\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary and bank statements.\",\n \"Consider additional income sources or savings to mitigate risks.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 75,\n \"justification\": \"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\"\n }\n }\n}\n```\n\n### Explanation of the Assessment:\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\n \n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\n\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\n\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\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 stability due to permanent employment and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"recommendation\\\": \\\"Continue monitoring for any changes in employment status.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to calculate due to unresolved debt-to-income ratio.\\\",\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation issue to assess servicing capability.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending analysis of salary slips and bank statements.\\\",\\n \\\"recommendation\\\": \\\"Review salary slips and bank statements to evaluate spending habits and savings.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Potential risks due to unresolved calculations and lack of detailed income data.\\\",\\n \\\"identified_risks\\\": [\\n \\\"Uncertainty in debt servicing capability\\\",\\n \\\"Inadequate financial discipline assessment\\\",\\n \\\"Dependence on employment stability\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary and bank statements.\\\",\\n \\\"Consider additional income sources or savings to mitigate risks.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 75,\\n \\\"justification\\\": \\\"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\\\"\\n }\\n }\\n}\\n```\\n\\n### Explanation of the Assessment:\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\\n \\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\\n\\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\\n\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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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 stability due to permanent employment and confirmed probation status.\",\n \"job_stability_score\": 88.5,\n \"employer_rating\": \"A+\",\n \"employment_type\": \"permanent\",\n \"recommendation\": \"Continue monitoring for any changes in employment status.\"\n },\n \"debt_servicing_capability\": {\n \"assessment\": \"Unable to calculate due to unresolved debt-to-income ratio.\",\n \"debt_to_income_ratio\": \"Error in calculation\",\n \"recommendation\": \"Resolve the debt-to-income calculation issue to assess servicing capability.\"\n },\n \"financial_discipline\": {\n \"assessment\": \"Pending analysis of salary slips and bank statements.\",\n \"recommendation\": \"Review salary slips and bank statements to evaluate spending habits and savings.\"\n },\n \"risk_factors\": {\n \"assessment\": \"Potential risks due to unresolved calculations and lack of detailed income data.\",\n \"identified_risks\": [\n \"Uncertainty in debt servicing capability\",\n \"Inadequate financial discipline assessment\",\n \"Dependence on employment stability\"\n ],\n \"recommendations\": [\n \"Resolve the debt-to-income calculation error.\",\n \"Conduct a thorough review of salary and bank statements.\",\n \"Consider additional income sources or savings to mitigate risks.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 75,\n \"justification\": \"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\"\n }\n }\n}\n```\n\n### Explanation of the Assessment:\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\n \n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\n\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\n\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\n\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\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 stability due to permanent employment and confirmed probation status.\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"permanent\\\",\\n \\\"recommendation\\\": \\\"Continue monitoring for any changes in employment status.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"assessment\\\": \\\"Unable to calculate due to unresolved debt-to-income ratio.\\\",\\n \\\"debt_to_income_ratio\\\": \\\"Error in calculation\\\",\\n \\\"recommendation\\\": \\\"Resolve the debt-to-income calculation issue to assess servicing capability.\\\"\\n },\\n \\\"financial_discipline\\\": {\\n \\\"assessment\\\": \\\"Pending analysis of salary slips and bank statements.\\\",\\n \\\"recommendation\\\": \\\"Review salary slips and bank statements to evaluate spending habits and savings.\\\"\\n },\\n \\\"risk_factors\\\": {\\n \\\"assessment\\\": \\\"Potential risks due to unresolved calculations and lack of detailed income data.\\\",\\n \\\"identified_risks\\\": [\\n \\\"Uncertainty in debt servicing capability\\\",\\n \\\"Inadequate financial discipline assessment\\\",\\n \\\"Dependence on employment stability\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the debt-to-income calculation error.\\\",\\n \\\"Conduct a thorough review of salary and bank statements.\\\",\\n \\\"Consider additional income sources or savings to mitigate risks.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 75,\\n \\\"justification\\\": \\\"Score reflects high employment stability but is tempered by unresolved financial calculations and lack of detailed income data.\\\"\\n }\\n }\\n}\\n```\\n\\n### Explanation of the Assessment:\\n1. **Income Stability Assessment**: The individual has a high job stability score and is employed in a permanent position with a reputable employer, indicating a stable income source.\\n \\n2. **Debt Servicing Capability**: The inability to calculate the debt-to-income ratio due to an unresolved error prevents a clear assessment of the individual\u0027s capability to service debt.\\n\\n3. **Financial Discipline Evaluation**: Without the analysis of salary slips and bank statements, it is difficult to assess the individual\u0027s financial discipline. This requires further review.\\n\\n4. **Risk Factors and Recommendations**: The main risks identified include the uncertainty in debt servicing capability and the lack of detailed financial data. Recommendations focus on resolving the calculation issues and reviewing financial documents.\\n\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a generally positive assessment of income stability but acknowledges the need for further information to provide a comprehensive evaluation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.614875,
"end_time": "2025-07-15T11:40:46.453926",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.839051",
"timestamp": "2025-07-15T11:40:46.453926",
"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": 0.369325,
"end_time": "2025-07-15T11:40:43.315658",
"message_sent": true,
"start_time": "2025-07-15T11:40:42.946333",
"timestamp": "2025-07-15T11:40:43.315658",
"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": 0.857587,
"end_time": "2025-07-15T11:40:43.889914",
"message_sent": true,
"start_time": "2025-07-15T11:40:43.032327",
"timestamp": "2025-07-15T11:40:43.889914",
"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": 0.74893,
"end_time": "2025-07-15T11:40:46.329815",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.580885",
"timestamp": "2025-07-15T11:40:46.329815",
"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": 0.003368,
"ended_at": "2025-07-15T11:47:13.624225",
"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\": 0.003368, \"started_at\": \"2025-07-15T11:47:13.620857\", \"ended_at\": \"2025-07-15T11:47:13.624225\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.284116,
"end_time": "2025-07-15T11:47:13.795448",
"message_sent": true,
"start_time": "2025-07-15T11:47:13.511332",
"timestamp": "2025-07-15T11:47:13.795448",
"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\": 0.003368, \"started_at\": \"2025-07-15T11:47:13.620857\", \"ended_at\": \"2025-07-15T11:47:13.624225\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T11:47:13.620857",
"status": "completed",
"stderr": "",
"task_id": "underwriting_decision_router"
},
"validate_application_fields": {
"completion_percentage": 100.0,
"execution_details": {
"actual_result": {
"output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.243458,
"end_time": "2025-07-15T11:40:38.906928",
"message_sent": true,
"start_time": "2025-07-15T11:40:38.663470",
"timestamp": "2025-07-15T11:40:38.906928",
"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": 0.477665,
"end_time": "2025-07-15T11:40:43.469410",
"message_sent": true,
"start_time": "2025-07-15T11:40:42.991745",
"timestamp": "2025-07-15T11:40:43.469410",
"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": 0.847725,
"end_time": "2025-07-15T11:40:43.917426",
"message_sent": true,
"start_time": "2025-07-15T11:40:43.069701",
"timestamp": "2025-07-15T11:40:43.917426",
"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": 0.614875,
"end_time": "2025-07-15T11:40:46.453926",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.839051",
"timestamp": "2025-07-15T11:40:46.453926",
"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": 0.369325,
"end_time": "2025-07-15T11:40:43.315658",
"message_sent": true,
"start_time": "2025-07-15T11:40:42.946333",
"timestamp": "2025-07-15T11:40:43.315658",
"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": 0.857587,
"end_time": "2025-07-15T11:40:43.889914",
"message_sent": true,
"start_time": "2025-07-15T11:40:43.032327",
"timestamp": "2025-07-15T11:40:43.889914",
"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": 0.74893,
"end_time": "2025-07-15T11:40:46.329815",
"message_sent": true,
"start_time": "2025-07-15T11:40:45.580885",
"timestamp": "2025-07-15T11:40:46.329815",
"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
}
}