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": 0.334788,
"end_time": "2025-07-15T11:15:55.786432",
"message_sent": true,
"start_time": "2025-07-15T11:15:55.451644",
"timestamp": "2025-07-15T11:15:55.786432",
"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": 0.480348,
"end_time": "2025-07-15T11:09:29.917027",
"message_sent": true,
"start_time": "2025-07-15T11:09:29.436679",
"timestamp": "2025-07-15T11:09:29.917027",
"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": 0.309468,
"end_time": "2025-07-15T11:12:41.923615",
"message_sent": true,
"start_time": "2025-07-15T11:12:41.614147",
"timestamp": "2025-07-15T11:12:41.923615",
"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": 0.391094,
"end_time": "2025-07-15T11:09:29.790611",
"message_sent": true,
"start_time": "2025-07-15T11:09:29.399517",
"timestamp": "2025-07-15T11:09:29.790611",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, indicating a high level of accuracy.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1088,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, indicating a high level of accuracy.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, indicating a high level of accuracy.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\\\"\\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": 4.483497,
"end_time": "2025-07-15T11:09:27.441281",
"message_sent": true,
"start_time": "2025-07-15T11:09:22.957784",
"timestamp": "2025-07-15T11:09:27.441281",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, indicating a high level of accuracy.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, indicating a high level of accuracy.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\\\"\\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": 0.316891,
"end_time": "2025-07-15T11:12:42.181063",
"message_sent": true,
"start_time": "2025-07-15T11:12:41.864172",
"timestamp": "2025-07-15T11:12:42.181063",
"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/tmp30cdjmkw.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/tmp30cdjmkw.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/tmp_od_sk78.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/tmp_od_sk78.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": 0.268663,
"end_time": "2025-07-15T11:12:41.662803",
"message_sent": true,
"start_time": "2025-07-15T11:12:41.394140",
"timestamp": "2025-07-15T11:12:41.662803",
"worker_executed": true,
"workers_notified": true
},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately.\",\n \"Conduct a thorough review and resolution of AML screening results.\",\n \"Ensure all regulatory compliance checks are addressed and resolved.\",\n \"Continue to monitor internal policy adherence, as it currently shows high compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1044,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately.\",\n \"Conduct a thorough review and resolution of AML screening results.\",\n \"Ensure all regulatory compliance checks are addressed and resolved.\",\n \"Continue to monitor internal policy adherence, as it currently shows high compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately.\\\",\\n \\\"Conduct a thorough review and resolution of AML screening results.\\\",\\n \\\"Ensure all regulatory compliance checks are addressed and resolved.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows high compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.312649,
"end_time": "2025-07-15T11:16:00.588697",
"message_sent": true,
"start_time": "2025-07-15T11:15:56.276048",
"timestamp": "2025-07-15T11:16:00.588697",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately.\",\n \"Conduct a thorough review and resolution of AML screening results.\",\n \"Ensure all regulatory compliance checks are addressed and resolved.\",\n \"Continue to monitor internal policy adherence, as it currently shows high compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately.\\\",\\n \\\"Conduct a thorough review and resolution of AML screening results.\\\",\\n \\\"Ensure all regulatory compliance checks are addressed and resolved.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows high compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true,\n \"biometric_verification\": true\n },\n \"risk_factors_identified\": [],\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": 380,
"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 \"biometric_verification\": true\n },\n \"risk_factors_identified\": [],\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 \\\"biometric_verification\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\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": 2.65486,
"end_time": "2025-07-15T11:09:30.226443",
"message_sent": true,
"start_time": "2025-07-15T11:09:27.571583",
"timestamp": "2025-07-15T11:09:30.226443",
"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 \"biometric_verification\": true\n },\n \"risk_factors_identified\": [],\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 \\\"biometric_verification\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\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 and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- **Number of Loans**: 2\n- **Types of Loans**: Personal loan and auto loan\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\n\n### Risk Score Calculation\nBased on the analysis:\n- Excellent repayment track record: -10 points (reduces risk)\n- Healthy loan burden ratio: -10 points (reduces risk)\n- Unresolved CIBIL score: +30 points (increases risk)\n- Unresolved credit history: +20 points (increases risk)\n\n### Final Risk Score\nStarting from a baseline risk score of 50 (neutral):\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\n- Final Risk Score = 50 + 30 = 80\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\n\n### Conclusion\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
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"agent_type": "assistant",
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"model": "gpt-4o-mini",
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"provider": "openai",
"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- **Number of Loans**: 2\n- **Types of Loans**: Personal loan and auto loan\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\n\n### Risk Score Calculation\nBased on the analysis:\n- Excellent repayment track record: -10 points (reduces risk)\n- Healthy loan burden ratio: -10 points (reduces risk)\n- Unresolved CIBIL score: +30 points (increases risk)\n- Unresolved credit history: +20 points (increases risk)\n\n### Final Risk Score\nStarting from a baseline risk score of 50 (neutral):\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\n- Final Risk Score = 50 + 30 = 80\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\n\n### Conclusion\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- **Number of Loans**: 2\\n- **Types of Loans**: Personal loan and auto loan\\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\\n\\n### Risk Score Calculation\\nBased on the analysis:\\n- Excellent repayment track record: -10 points (reduces risk)\\n- Healthy loan burden ratio: -10 points (reduces risk)\\n- Unresolved CIBIL score: +30 points (increases risk)\\n- Unresolved credit history: +20 points (increases risk)\\n\\n### Final Risk Score\\nStarting from a baseline risk score of 50 (neutral):\\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\\n- Final Risk Score = 50 + 30 = 80\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\\n\\n### Conclusion\\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 13.443171,
"end_time": "2025-07-15T11:12:55.577311",
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"start_time": "2025-07-15T11:12:42.134140",
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},
"model": "gpt-4o-mini",
"model_client_id": "risk_assessor",
"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- **Number of Loans**: 2\n- **Types of Loans**: Personal loan and auto loan\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\n\n### Risk Score Calculation\nBased on the analysis:\n- Excellent repayment track record: -10 points (reduces risk)\n- Healthy loan burden ratio: -10 points (reduces risk)\n- Unresolved CIBIL score: +30 points (increases risk)\n- Unresolved credit history: +20 points (increases risk)\n\n### Final Risk Score\nStarting from a baseline risk score of 50 (neutral):\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\n- Final Risk Score = 50 + 30 = 80\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\n\n### Conclusion\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- **Number of Loans**: 2\\n- **Types of Loans**: Personal loan and auto loan\\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\\n\\n### Risk Score Calculation\\nBased on the analysis:\\n- Excellent repayment track record: -10 points (reduces risk)\\n- Healthy loan burden ratio: -10 points (reduces risk)\\n- Unresolved CIBIL score: +30 points (increases risk)\\n- Unresolved credit history: +20 points (increases risk)\\n\\n### Final Risk Score\\nStarting from a baseline risk score of 50 (neutral):\\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\\n- Final Risk Score = 50 + 30 = 80\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\\n\\n### Conclusion\\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
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},
"execution_summary": {
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"execution_mode": "distributed",
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},
"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
"execution_details": {
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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},
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},
"extraction_success": true,
"missing_fields": [],
"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
"return_code": 0,
"status": "completed",
"stderr": "",
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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 Declined)**\n\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\n\n4. **Reasoning for Decision:**\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\n\n5. **Confidence Level: 95**\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.",
"execution_details": {
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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 Declined)**\n\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\n\n4. **Reasoning for Decision:**\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\n\n5. **Confidence Level: 95**\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation: DECLINE**\\n\\n2. **Loan Terms and Conditions: N/A (Loan Declined)**\\n\\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\\n\\n4. **Reasoning for Decision:**\\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \\n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \\n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\\n\\n5. **Confidence Level: 95**\\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
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"status": "completed",
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},
"duration_seconds": 5.870328,
"end_time": "2025-07-15T11:16:06.395780",
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"start_time": "2025-07-15T11:16:00.525452",
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"output": "1. **Final Recommendation: DECLINE**\n\n2. **Loan Terms and Conditions: N/A (Loan Declined)**\n\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\n\n4. **Reasoning for Decision:**\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\n\n5. **Confidence Level: 95**\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation: DECLINE**\\n\\n2. **Loan Terms and Conditions: N/A (Loan Declined)**\\n\\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\\n\\n4. **Reasoning for Decision:**\\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \\n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \\n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\\n\\n5. **Confidence Level: 95**\\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\", \"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 employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_title\": \"Senior Software Engineer\",\n \"employer_rating\": \"A+\",\n \"employment_type\": \"Permanent\",\n \"probation_status\": \"Confirmed\",\n \"job_stability_score\": 88.5,\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_returns\": \"UNRESOLVED\",\n \"assessment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\",\n \"Potential high debt-to-income ratio that cannot be assessed at this time.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\",\n \"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\",\n \"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 70,\n \"justification\": \"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\"\n }\n}\n```\n\n### Summary:\n- The individual has a stable job with a reputable employer, indicating good income stability.\n- The debt servicing capability cannot be assessed due to unresolved data.\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.",
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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 employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_title\": \"Senior Software Engineer\",\n \"employer_rating\": \"A+\",\n \"employment_type\": \"Permanent\",\n \"probation_status\": \"Confirmed\",\n \"job_stability_score\": 88.5,\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_returns\": \"UNRESOLVED\",\n \"assessment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\",\n \"Potential high debt-to-income ratio that cannot be assessed at this time.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\",\n \"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\",\n \"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 70,\n \"justification\": \"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\"\n }\n}\n```\n\n### Summary:\n- The individual has a stable job with a reputable employer, indicating good income stability.\n- The debt servicing capability cannot be assessed due to unresolved data.\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_title\\\": \\\"Senior Software Engineer\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_returns\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\\\",\\n \\\"Potential high debt-to-income ratio that cannot be assessed at this time.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\\\",\\n \\\"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\\\",\\n \\\"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 70,\\n \\\"justification\\\": \\\"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\\\"\\n }\\n}\\n```\\n\\n### Summary:\\n- The individual has a stable job with a reputable employer, indicating good income stability.\\n- The debt servicing capability cannot be assessed due to unresolved data.\\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\", \"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 employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_title\": \"Senior Software Engineer\",\n \"employer_rating\": \"A+\",\n \"employment_type\": \"Permanent\",\n \"probation_status\": \"Confirmed\",\n \"job_stability_score\": 88.5,\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_returns\": \"UNRESOLVED\",\n \"assessment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\",\n \"Potential high debt-to-income ratio that cannot be assessed at this time.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\",\n \"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\",\n \"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 70,\n \"justification\": \"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\"\n }\n}\n```\n\n### Summary:\n- The individual has a stable job with a reputable employer, indicating good income stability.\n- The debt servicing capability cannot be assessed due to unresolved data.\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_title\\\": \\\"Senior Software Engineer\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_returns\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\\\",\\n \\\"Potential high debt-to-income ratio that cannot be assessed at this time.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\\\",\\n \\\"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\\\",\\n \\\"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 70,\\n \\\"justification\\\": \\\"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\\\"\\n }\\n}\\n```\\n\\n### Summary:\\n- The individual has a stable job with a reputable employer, indicating good income stability.\\n- The debt servicing capability cannot be assessed due to unresolved data.\\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"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": 0.309468,
"end_time": "2025-07-15T11:12:41.923615",
"message_sent": true,
"start_time": "2025-07-15T11:12:41.614147",
"timestamp": "2025-07-15T11:12:41.923615",
"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": 0.391094,
"end_time": "2025-07-15T11:09:29.790611",
"message_sent": true,
"start_time": "2025-07-15T11:09:29.399517",
"timestamp": "2025-07-15T11:09:29.790611",
"worker_executed": true,
"workers_notified": true
},
"monthly_gross": 8500,
"monthly_net": 6800,
"output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
"recent_increment": true,
"return_code": 0,
"salary_consistency": true,
"status": "completed",
"stderr": "",
"task_id": "analyze_salary_slips"
},
"application_quality_check": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, indicating a high level of accuracy.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\"\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 246,
"model": "gpt-4o-mini",
"output_length": 1088,
"provider": "openai",
"system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
},
"input_format": "json",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, indicating a high level of accuracy.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, indicating a high level of accuracy.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\\\"\\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": 4.483497,
"end_time": "2025-07-15T11:09:27.441281",
"message_sent": true,
"start_time": "2025-07-15T11:09:22.957784",
"timestamp": "2025-07-15T11:09:27.441281",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "underwriting_analyst",
"output": "```json\n{\n \"data_completeness_and_accuracy\": {\n \"missing_fields\": [],\n \"validation_passed\": true,\n \"completion_percentage\": 100.0,\n \"assessment\": \"The application data is complete with no missing fields, indicating a high level of accuracy.\"\n },\n \"consistency_of_information\": {\n \"assessment\": \"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\"\n },\n \"red_flags_or_inconsistencies\": {\n \"assessment\": \"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\"\n },\n \"overall_application_quality_score\": 95,\n \"overall_assessment\": \"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"data_completeness_and_accuracy\\\": {\\n \\\"missing_fields\\\": [],\\n \\\"validation_passed\\\": true,\\n \\\"completion_percentage\\\": 100.0,\\n \\\"assessment\\\": \\\"The application data is complete with no missing fields, indicating a high level of accuracy.\\\"\\n },\\n \\\"consistency_of_information\\\": {\\n \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information is likely consistent. However, without specific details on the customer info, a deeper consistency check cannot be performed.\\\"\\n },\\n \\\"red_flags_or_inconsistencies\\\": {\\n \\\"assessment\\\": \\\"No red flags or inconsistencies were identified based on the provided validation results. However, further analysis of the customer info would be necessary to identify any potential issues.\\\"\\n },\\n \\\"overall_application_quality_score\\\": 95,\\n \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and accuracy. The absence of missing fields and successful validation contributes positively to the overall score. Further details on customer info would enhance the assessment.\\\"\\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": 0.316891,
"end_time": "2025-07-15T11:12:42.181063",
"message_sent": true,
"start_time": "2025-07-15T11:12:41.864172",
"timestamp": "2025-07-15T11:12:42.181063",
"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/tmp30cdjmkw.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/tmp30cdjmkw.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/tmp_od_sk78.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/tmp_od_sk78.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": 0.268663,
"end_time": "2025-07-15T11:12:41.662803",
"message_sent": true,
"start_time": "2025-07-15T11:12:41.394140",
"timestamp": "2025-07-15T11:12:41.662803",
"worker_executed": true,
"workers_notified": true
},
"last_updated": "2024-06-01",
"output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
"payment_history": "99% on-time",
"recent_inquiries": 2,
"return_code": 0,
"score_range": "Good",
"status": "completed",
"stderr": "",
"task_id": "check_cibil_score",
"total_accounts": 8
},
"compliance_consolidation": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately.\",\n \"Conduct a thorough review and resolution of AML screening results.\",\n \"Ensure all regulatory compliance checks are addressed and resolved.\",\n \"Continue to monitor internal policy adherence, as it currently shows high compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```",
"execution_details": {
"actual_result": {
"agent_type": "assistant",
"execution_details": {
"agent_type": "assistant",
"input_length": 571,
"model": "gpt-4o-mini",
"output_length": 1044,
"provider": "openai",
"system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
},
"input_format": "json",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately.\",\n \"Conduct a thorough review and resolution of AML screening results.\",\n \"Ensure all regulatory compliance checks are addressed and resolved.\",\n \"Continue to monitor internal policy adherence, as it currently shows high compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately.\\\",\\n \\\"Conduct a thorough review and resolution of AML screening results.\\\",\\n \\\"Ensure all regulatory compliance checks are addressed and resolved.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows high compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"output_format": "json",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 4.312649,
"end_time": "2025-07-15T11:16:00.588697",
"message_sent": true,
"start_time": "2025-07-15T11:15:56.276048",
"timestamp": "2025-07-15T11:16:00.588697",
"worker_executed": true,
"workers_notified": true
},
"model": "gpt-4o-mini",
"model_client_id": "compliance_reviewer",
"output": "```json\n{\n \"overall_compliance_status\": \"Non-compliant\",\n \"risk_assessment\": {\n \"KYC\": \"High risk due to unresolved KYC compliance check.\",\n \"AML\": \"High risk due to unresolved AML screening.\",\n \"Regulatory\": \"High risk due to unresolved regulatory compliance.\",\n \"Internal Policy\": \"Low risk; internal policy compliance score is high.\"\n },\n \"compliance_gaps_or_concerns\": [\n \"Unresolved KYC compliance check poses a significant risk of identity fraud.\",\n \"Unresolved AML screening increases the risk of money laundering activities.\",\n \"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\"\n ],\n \"recommendations_for_proceeding\": [\n \"Prioritize resolving KYC compliance issues immediately.\",\n \"Conduct a thorough review and resolution of AML screening results.\",\n \"Ensure all regulatory compliance checks are addressed and resolved.\",\n \"Continue to monitor internal policy adherence, as it currently shows high compliance.\"\n ],\n \"compliance_confidence_score\": 25\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n \\\"overall_compliance_status\\\": \\\"Non-compliant\\\",\\n \\\"risk_assessment\\\": {\\n \\\"KYC\\\": \\\"High risk due to unresolved KYC compliance check.\\\",\\n \\\"AML\\\": \\\"High risk due to unresolved AML screening.\\\",\\n \\\"Regulatory\\\": \\\"High risk due to unresolved regulatory compliance.\\\",\\n \\\"Internal Policy\\\": \\\"Low risk; internal policy compliance score is high.\\\"\\n },\\n \\\"compliance_gaps_or_concerns\\\": [\\n \\\"Unresolved KYC compliance check poses a significant risk of identity fraud.\\\",\\n \\\"Unresolved AML screening increases the risk of money laundering activities.\\\",\\n \\\"Unresolved regulatory compliance could lead to legal penalties and reputational damage.\\\"\\n ],\\n \\\"recommendations_for_proceeding\\\": [\\n \\\"Prioritize resolving KYC compliance issues immediately.\\\",\\n \\\"Conduct a thorough review and resolution of AML screening results.\\\",\\n \\\"Ensure all regulatory compliance checks are addressed and resolved.\\\",\\n \\\"Continue to monitor internal policy adherence, as it currently shows high compliance.\\\"\\n ],\\n \\\"compliance_confidence_score\\\": 25\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
"provider": "openai",
"return_code": 0,
"status": "completed",
"stderr": "",
"task_id": "compliance_consolidation"
},
"consolidate_document_verification": {
"agent_type": "assistant",
"ai_response": "```json\n{\n \"overall_verification_success_rate\": 100,\n \"consistency_across_documents\": {\n \"name_match\": true,\n \"address_match\": true,\n \"biometric_verification\": true\n },\n \"risk_factors_identified\": [],\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": 380,
"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 \"biometric_verification\": true\n },\n \"risk_factors_identified\": [],\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 \\\"biometric_verification\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\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": 2.65486,
"end_time": "2025-07-15T11:09:30.226443",
"message_sent": true,
"start_time": "2025-07-15T11:09:27.571583",
"timestamp": "2025-07-15T11:09:30.226443",
"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 \"biometric_verification\": true\n },\n \"risk_factors_identified\": [],\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 \\\"biometric_verification\\\": true\\n },\\n \\\"risk_factors_identified\\\": [],\\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 and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- **Number of Loans**: 2\n- **Types of Loans**: Personal loan and auto loan\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\n\n### Risk Score Calculation\nBased on the analysis:\n- Excellent repayment track record: -10 points (reduces risk)\n- Healthy loan burden ratio: -10 points (reduces risk)\n- Unresolved CIBIL score: +30 points (increases risk)\n- Unresolved credit history: +20 points (increases risk)\n\n### Final Risk Score\nStarting from a baseline risk score of 50 (neutral):\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\n- Final Risk Score = 50 + 30 = 80\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\n\n### Conclusion\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.",
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"system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
},
"input_format": "json",
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"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- **Number of Loans**: 2\n- **Types of Loans**: Personal loan and auto loan\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\n\n### Risk Score Calculation\nBased on the analysis:\n- Excellent repayment track record: -10 points (reduces risk)\n- Healthy loan burden ratio: -10 points (reduces risk)\n- Unresolved CIBIL score: +30 points (increases risk)\n- Unresolved credit history: +20 points (increases risk)\n\n### Final Risk Score\nStarting from a baseline risk score of 50 (neutral):\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\n- Final Risk Score = 50 + 30 = 80\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\n\n### Conclusion\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- **Number of Loans**: 2\\n- **Types of Loans**: Personal loan and auto loan\\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\\n\\n### Risk Score Calculation\\nBased on the analysis:\\n- Excellent repayment track record: -10 points (reduces risk)\\n- Healthy loan burden ratio: -10 points (reduces risk)\\n- Unresolved CIBIL score: +30 points (increases risk)\\n- Unresolved credit history: +20 points (increases risk)\\n\\n### Final Risk Score\\nStarting from a baseline risk score of 50 (neutral):\\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\\n- Final Risk Score = 50 + 30 = 80\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\\n\\n### Conclusion\\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is marked as \"UNRESOLVED_check_cibil_score,\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\n- **Credit History**: The history is also marked as \"UNRESOLVED_analyze_credit_history.\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The repayment track record is noted as \"excellent.\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- **Number of Loans**: 2\n- **Types of Loans**: Personal loan and auto loan\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\n\n### Risk Score Calculation\nBased on the analysis:\n- Excellent repayment track record: -10 points (reduces risk)\n- Healthy loan burden ratio: -10 points (reduces risk)\n- Unresolved CIBIL score: +30 points (increases risk)\n- Unresolved credit history: +20 points (increases risk)\n\n### Final Risk Score\nStarting from a baseline risk score of 50 (neutral):\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\n- Final Risk Score = 50 + 30 = 80\n\n### Recommendations\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\n\n### Conclusion\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will consider the various factors mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is marked as \\\"UNRESOLVED_check_cibil_score,\\\" which means we cannot assess the creditworthiness based on the score. A high CIBIL score (above 750) typically indicates lower risk, while a score below 600 indicates higher risk.\\n- **Credit History**: The history is also marked as \\\"UNRESOLVED_analyze_credit_history.\\\" Without specific details, we cannot evaluate the length of credit history, types of credit accounts, or any delinquencies.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The repayment track record is noted as \\\"excellent.\\\" This indicates that the individual has consistently made timely payments on their loans, which is a positive sign and reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This ratio is calculated as the total monthly EMI divided by the monthly income. A ratio below 30% is generally considered healthy, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- **Number of Loans**: 2\\n- **Types of Loans**: Personal loan and auto loan\\n- The existing loans are manageable given the repayment track record is excellent, and the loan burden ratio is within acceptable limits.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment track record and a healthy loan burden ratio, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history create uncertainty.\\n\\n### Risk Score Calculation\\nBased on the analysis:\\n- Excellent repayment track record: -10 points (reduces risk)\\n- Healthy loan burden ratio: -10 points (reduces risk)\\n- Unresolved CIBIL score: +30 points (increases risk)\\n- Unresolved credit history: +20 points (increases risk)\\n\\n### Final Risk Score\\nStarting from a baseline risk score of 50 (neutral):\\n- Adjustments: -10 (repayment) -10 (burden) +30 (CIBIL) +20 (history) = +30\\n- Final Risk Score = 50 + 30 = 80\\n\\n### Recommendations\\n1. **Resolve CIBIL Score**: Obtain and resolve the CIBIL score to better understand the creditworthiness.\\n2. **Review Credit History**: Analyze the credit history to identify any potential issues or areas for improvement.\\n3. **Maintain Repayment Discipline**: Continue the excellent repayment pattern to further enhance creditworthiness.\\n4. **Monitor Loan Utilization**: Keep the loan burden ratio below 30% to maintain a healthy financial profile.\\n5. **Consider Financial Counseling**: If there are any uncertainties or complexities in the financial situation, consider consulting a financial advisor.\\n\\n### Conclusion\\nThe calculated risk score is **80**, indicating a relatively high risk of default primarily due to unresolved credit score and history. Addressing these issues can help improve the overall risk profile.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"extract_application_info": {
"customer_info": {
"address": "123 Main St, City, State 12345",
"annual_income": 75000,
"customer_id": "CUST_12345",
"email": "john.doe@email.com",
"employment_status": "employed",
"full_name": "John Doe",
"loan_purpose": "home_purchase",
"phone": "+1-555-0123",
"requested_amount": 10000
},
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"output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 10000}, \"missing_fields\": []}\n",
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},
"extraction_success": true,
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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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"final_underwriting_analysis": {
"agent_type": "assistant",
"ai_response": "1. **Final Recommendation: DECLINE**\n\n2. **Loan Terms and Conditions: N/A (Loan Declined)**\n\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\n\n4. **Reasoning for Decision:**\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\n\n5. **Confidence Level: 95**\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.",
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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 Declined)**\n\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\n\n4. **Reasoning for Decision:**\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\n\n5. **Confidence Level: 95**\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation: DECLINE**\\n\\n2. **Loan Terms and Conditions: N/A (Loan Declined)**\\n\\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\\n\\n4. **Reasoning for Decision:**\\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \\n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \\n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\\n\\n5. **Confidence Level: 95**\\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\", \"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 Declined)**\n\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\n\n4. **Reasoning for Decision:**\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\n\n5. **Confidence Level: 95**\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation: DECLINE**\\n\\n2. **Loan Terms and Conditions: N/A (Loan Declined)**\\n\\n3. **Risk Mitigation Measures: N/A (Loan Declined)**\\n\\n4. **Reasoning for Decision:**\\n - The application presents multiple unresolved issues across critical assessment areas, including application quality, document verification, income assessment, credit score, default risk evaluation, compliance, and debt-to-income calculation. \\n - The lack of resolution in these areas indicates significant gaps in the applicant\u0027s financial profile and documentation, which are essential for making an informed lending decision. \\n - Without verified income, a calculated credit score, and a clear understanding of the applicant\u0027s debt-to-income ratio, the risk of default cannot be accurately assessed. This uncertainty poses a high risk to the lending institution.\\n - Compliance issues further complicate the situation, as any unresolved compliance concerns could lead to regulatory repercussions for the lender.\\n\\n5. **Confidence Level: 95**\\n - The decision to decline is based on the high level of uncertainty and unresolved issues in the application. Given the critical nature of these assessments, there is a strong confidence in the decision to decline the loan.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"generate_final_output": {
"error": "Python script failed with return code 1: Traceback (most recent call last):\n File \"/tmp/tmpwqocaqgw.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/tmpwqocaqgw.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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"income_assessment": {
"agent_type": "assistant",
"ai_response": "Based on the provided income data and the employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_title\": \"Senior Software Engineer\",\n \"employer_rating\": \"A+\",\n \"employment_type\": \"Permanent\",\n \"probation_status\": \"Confirmed\",\n \"job_stability_score\": 88.5,\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_returns\": \"UNRESOLVED\",\n \"assessment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\",\n \"Potential high debt-to-income ratio that cannot be assessed at this time.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\",\n \"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\",\n \"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 70,\n \"justification\": \"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\"\n }\n}\n```\n\n### Summary:\n- The individual has a stable job with a reputable employer, indicating good income stability.\n- The debt servicing capability cannot be assessed due to unresolved data.\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.",
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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 employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_title\": \"Senior Software Engineer\",\n \"employer_rating\": \"A+\",\n \"employment_type\": \"Permanent\",\n \"probation_status\": \"Confirmed\",\n \"job_stability_score\": 88.5,\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_returns\": \"UNRESOLVED\",\n \"assessment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\",\n \"Potential high debt-to-income ratio that cannot be assessed at this time.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\",\n \"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\",\n \"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 70,\n \"justification\": \"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\"\n }\n}\n```\n\n### Summary:\n- The individual has a stable job with a reputable employer, indicating good income stability.\n- The debt servicing capability cannot be assessed due to unresolved data.\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_title\\\": \\\"Senior Software Engineer\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_returns\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\\\",\\n \\\"Potential high debt-to-income ratio that cannot be assessed at this time.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\\\",\\n \\\"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\\\",\\n \\\"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 70,\\n \\\"justification\\\": \\\"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\\\"\\n }\\n}\\n```\\n\\n### Summary:\\n- The individual has a stable job with a reputable employer, indicating good income stability.\\n- The debt servicing capability cannot be assessed due to unresolved data.\\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"model": "gpt-4o-mini",
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"output": "Based on the provided income data and the employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\n\n```json\n{\n \"income_stability_assessment\": {\n \"job_title\": \"Senior Software Engineer\",\n \"employer_rating\": \"A+\",\n \"employment_type\": \"Permanent\",\n \"probation_status\": \"Confirmed\",\n \"job_stability_score\": 88.5,\n \"employment_confirmed\": true,\n \"reference_check_passed\": true,\n \"assessment\": \"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\"\n },\n \"debt_servicing_capability\": {\n \"debt_to_income_ratio\": \"UNRESOLVED\",\n \"assessment\": \"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\"\n },\n \"financial_discipline_evaluation\": {\n \"bank_statement_analysis\": \"UNRESOLVED\",\n \"tax_returns\": \"UNRESOLVED\",\n \"assessment\": \"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\"\n },\n \"risk_factors_and_recommendations\": {\n \"risk_factors\": [\n \"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\",\n \"Potential high debt-to-income ratio that cannot be assessed at this time.\"\n ],\n \"recommendations\": [\n \"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\",\n \"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\",\n \"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\"\n ]\n },\n \"overall_income_adequacy_score\": {\n \"score\": 70,\n \"justification\": \"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\"\n }\n}\n```\n\n### Summary:\n- The individual has a stable job with a reputable employer, indicating good income stability.\n- The debt servicing capability cannot be assessed due to unresolved data.\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided income data and the employment verification details, here is a comprehensive assessment of the individual\u0027s financial situation:\\n\\n```json\\n{\\n \\\"income_stability_assessment\\\": {\\n \\\"job_title\\\": \\\"Senior Software Engineer\\\",\\n \\\"employer_rating\\\": \\\"A+\\\",\\n \\\"employment_type\\\": \\\"Permanent\\\",\\n \\\"probation_status\\\": \\\"Confirmed\\\",\\n \\\"job_stability_score\\\": 88.5,\\n \\\"employment_confirmed\\\": true,\\n \\\"reference_check_passed\\\": true,\\n \\\"assessment\\\": \\\"The individual holds a stable position with a reputable employer, indicating a high level of job security and income stability.\\\"\\n },\\n \\\"debt_servicing_capability\\\": {\\n \\\"debt_to_income_ratio\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Unable to calculate the debt-to-income ratio due to a script error. Further analysis of income and debt obligations is required to assess the individual\u0027s capability to service existing and potential debt.\\\"\\n },\\n \\\"financial_discipline_evaluation\\\": {\\n \\\"bank_statement_analysis\\\": \\\"UNRESOLVED\\\",\\n \\\"tax_returns\\\": \\\"UNRESOLVED\\\",\\n \\\"assessment\\\": \\\"Without the analysis of bank statements and tax returns, it is difficult to evaluate the individual\u0027s financial discipline. A thorough review of spending habits and tax compliance is necessary.\\\"\\n },\\n \\\"risk_factors_and_recommendations\\\": {\\n \\\"risk_factors\\\": [\\n \\\"Incomplete income data analysis due to unresolved salary slips, bank statements, and tax returns.\\\",\\n \\\"Potential high debt-to-income ratio that cannot be assessed at this time.\\\"\\n ],\\n \\\"recommendations\\\": [\\n \\\"Resolve the issues with salary slip and bank statement analysis to gain a complete picture of income and expenses.\\\",\\n \\\"Conduct a thorough review of tax returns to ensure compliance and assess overall financial health.\\\",\\n \\\"Once the debt-to-income ratio can be calculated, evaluate the individual\u0027s ability to take on additional debt.\\\"\\n ]\\n },\\n \\\"overall_income_adequacy_score\\\": {\\n \\\"score\\\": 70,\\n \\\"justification\\\": \\\"While the individual has a stable job and a high job stability score, the lack of complete data on income and debt obligations limits the overall assessment. The score reflects a moderate level of income adequacy, contingent on resolving outstanding data issues.\\\"\\n }\\n}\\n```\\n\\n### Summary:\\n- The individual has a stable job with a reputable employer, indicating good income stability.\\n- The debt servicing capability cannot be assessed due to unresolved data.\\n- Financial discipline evaluation is incomplete without bank statements and tax returns.\\n- There are notable risk factors due to incomplete data, and recommendations are provided to address these issues.\\n- The overall income adequacy score is moderate, reflecting the current limitations in data analysis.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
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"output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
"pan_number": "ABCDE1234F",
"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": 0.656535,
"end_time": "2025-07-15T11:09:27.413677",
"message_sent": true,
"start_time": "2025-07-15T11:09:26.757142",
"timestamp": "2025-07-15T11:09:27.413677",
"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": 0.582274,
"end_time": "2025-07-15T11:09:30.063452",
"message_sent": true,
"start_time": "2025-07-15T11:09:29.481178",
"timestamp": "2025-07-15T11:09:30.063452",
"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": 0.000858,
"ended_at": "2025-07-15T11:16:00.359690",
"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\": 0.000858, \"started_at\": \"2025-07-15T11:16:00.358832\", \"ended_at\": \"2025-07-15T11:16:00.359690\"}",
"return_code": 0,
"status": "completed",
"stderr": ""
},
"duration_seconds": 0.220082,
"end_time": "2025-07-15T11:16:00.476751",
"message_sent": true,
"start_time": "2025-07-15T11:16:00.256669",
"timestamp": "2025-07-15T11:16:00.476751",
"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\": 0.000858, \"started_at\": \"2025-07-15T11:16:00.358832\", \"ended_at\": \"2025-07-15T11:16:00.359690\"}",
"return_code": 0,
"route_reason": "no_conditions_matched",
"router_type": "condition",
"selected_route": "manual_review_path",
"started_at": "2025-07-15T11:16:00.358832",
"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": 0.357567,
"end_time": "2025-07-15T11:09:23.024820",
"message_sent": true,
"start_time": "2025-07-15T11:09:22.667253",
"timestamp": "2025-07-15T11:09:23.024820",
"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": 0.526521,
"end_time": "2025-07-15T11:09:27.237160",
"message_sent": true,
"start_time": "2025-07-15T11:09:26.710639",
"timestamp": "2025-07-15T11:09:27.237160",
"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": 0.813385,
"end_time": "2025-07-15T11:09:27.611859",
"message_sent": true,
"start_time": "2025-07-15T11:09:26.798474",
"timestamp": "2025-07-15T11:09:27.611859",
"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": 0.566563,
"end_time": "2025-07-15T11:09:30.298266",
"message_sent": true,
"start_time": "2025-07-15T11:09:29.731703",
"timestamp": "2025-07-15T11:09:30.298266",
"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": 0.387775,
"end_time": "2025-07-15T11:09:27.059808",
"message_sent": true,
"start_time": "2025-07-15T11:09:26.672033",
"timestamp": "2025-07-15T11:09:27.059808",
"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": 0.656535,
"end_time": "2025-07-15T11:09:27.413677",
"message_sent": true,
"start_time": "2025-07-15T11:09:26.757142",
"timestamp": "2025-07-15T11:09:27.413677",
"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": 0.582274,
"end_time": "2025-07-15T11:09:30.063452",
"message_sent": true,
"start_time": "2025-07-15T11:09:29.481178",
"timestamp": "2025-07-15T11:09:30.063452",
"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
}
}