Execution Details COMPLETED

{
  "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": 0.235547,
      "end_time": "2025-07-16T07:43:17.513726",
      "message_sent": true,
      "start_time": "2025-07-16T07:43:17.278179",
      "timestamp": "2025-07-16T07:43:17.513726",
      "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": 0.488948,
      "end_time": "2025-07-16T07:39:46.084078",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:45.595130",
      "timestamp": "2025-07-16T07:39:46.084078",
      "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": 0.212024,
      "end_time": "2025-07-16T07:42:59.371799",
      "message_sent": true,
      "start_time": "2025-07-16T07:42:59.159775",
      "timestamp": "2025-07-16T07:42:59.371799",
      "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": 0.413659,
      "end_time": "2025-07-16T07:39:45.938742",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:45.525083",
      "timestamp": "2025-07-16T07:39:45.938742",
      "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": "Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\n\nHere\u2019s the assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\n\n2. **Consistency of Information**:\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\n\n3. **Red Flags or Inconsistencies**:\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\n\n4. **Overall Application Quality Score**:\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\n\nBased on this analysis, the overall application quality score is **10** out of 100.\n\nHere is the JSON response with the assessment:\n\n```json\n{\n  \"data_completeness\": \"Incomplete - customer information could not be extracted.\",\n  \"data_accuracy\": \"Cannot assess due to missing data.\",\n  \"information_consistency\": \"No information available to evaluate consistency.\",\n  \"red_flags\": \"Failure to extract customer information indicates potential issues.\",\n  \"overall_quality_score\": 10\n}\n```",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 506,
          "model": "gpt-4o-mini",
          "output_length": 1984,
          "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": "Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\n\nHere\u2019s the assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\n\n2. **Consistency of Information**:\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\n\n3. **Red Flags or Inconsistencies**:\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\n\n4. **Overall Application Quality Score**:\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\n\nBased on this analysis, the overall application quality score is **10** out of 100.\n\nHere is the JSON response with the assessment:\n\n```json\n{\n  \"data_completeness\": \"Incomplete - customer information could not be extracted.\",\n  \"data_accuracy\": \"Cannot assess due to missing data.\",\n  \"information_consistency\": \"No information available to evaluate consistency.\",\n  \"red_flags\": \"Failure to extract customer information indicates potential issues.\",\n  \"overall_quality_score\": 10\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\\n\\nHere\\u2019s the assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\\n\\n2. **Consistency of Information**:\\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\\n\\n3. **Red Flags or Inconsistencies**:\\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\\n\\n4. **Overall Application Quality Score**:\\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\\n\\nBased on this analysis, the overall application quality score is **10** out of 100.\\n\\nHere is the JSON response with the assessment:\\n\\n```json\\n{\\n  \\\"data_completeness\\\": \\\"Incomplete - customer information could not be extracted.\\\",\\n  \\\"data_accuracy\\\": \\\"Cannot assess due to missing data.\\\",\\n  \\\"information_consistency\\\": \\\"No information available to evaluate consistency.\\\",\\n  \\\"red_flags\\\": \\\"Failure to extract customer information indicates potential issues.\\\",\\n  \\\"overall_quality_score\\\": 10\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 376, \"total_tokens\": 562, \"estimated_cost\": {\"amount\": 0.000253, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": "",
        "token_usage": {
          "completion_tokens": 376,
          "estimated_cost": {
            "amount": 0.000253,
            "currency": "USD"
          },
          "model": "gpt-4o-mini",
          "prompt_tokens": 186,
          "provider": "openai",
          "total_tokens": 562
        }
      },
      "duration_seconds": 6.842099,
      "end_time": "2025-07-16T07:39:37.912882",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:31.070783",
      "timestamp": "2025-07-16T07:39:37.912882",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "underwriting_analyst",
    "output": "Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\n\nHere\u2019s the assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\n\n2. **Consistency of Information**:\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\n\n3. **Red Flags or Inconsistencies**:\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\n\n4. **Overall Application Quality Score**:\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\n\nBased on this analysis, the overall application quality score is **10** out of 100.\n\nHere is the JSON response with the assessment:\n\n```json\n{\n  \"data_completeness\": \"Incomplete - customer information could not be extracted.\",\n  \"data_accuracy\": \"Cannot assess due to missing data.\",\n  \"information_consistency\": \"No information available to evaluate consistency.\",\n  \"red_flags\": \"Failure to extract customer information indicates potential issues.\",\n  \"overall_quality_score\": 10\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\\n\\nHere\\u2019s the assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\\n\\n2. **Consistency of Information**:\\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\\n\\n3. **Red Flags or Inconsistencies**:\\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\\n\\n4. **Overall Application Quality Score**:\\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\\n\\nBased on this analysis, the overall application quality score is **10** out of 100.\\n\\nHere is the JSON response with the assessment:\\n\\n```json\\n{\\n  \\\"data_completeness\\\": \\\"Incomplete - customer information could not be extracted.\\\",\\n  \\\"data_accuracy\\\": \\\"Cannot assess due to missing data.\\\",\\n  \\\"information_consistency\\\": \\\"No information available to evaluate consistency.\\\",\\n  \\\"red_flags\\\": \\\"Failure to extract customer information indicates potential issues.\\\",\\n  \\\"overall_quality_score\\\": 10\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 376, \"total_tokens\": 562, \"estimated_cost\": {\"amount\": 0.000253, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "application_quality_check",
    "token_usage": {
      "completion_tokens": 376,
      "estimated_cost": {
        "amount": 0.000253,
        "currency": "USD"
      },
      "model": "gpt-4o-mini",
      "prompt_tokens": 186,
      "provider": "openai",
      "total_tokens": 562
    }
  },
  "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": 0.191274,
      "end_time": "2025-07-16T07:42:59.591076",
      "message_sent": true,
      "start_time": "2025-07-16T07:42:59.399802",
      "timestamp": "2025-07-16T07:42:59.591076",
      "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": {
    "cibil_score": 720,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.212566,
      "end_time": "2025-07-16T07:43:16.985138",
      "message_sent": true,
      "start_time": "2025-07-16T07:43:16.772572",
      "timestamp": "2025-07-16T07:43:16.985138",
      "worker_executed": true,
      "workers_notified": true
    },
    "internal_credit_score": 337.9,
    "min_required_score": 650,
    "output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
    "return_code": 0,
    "risk_category": "high",
    "score_acceptable": false,
    "scoring_factors": {
      "cibil_contribution": 288.0,
      "loan_burden_contribution": 7.2,
      "payment_history_contribution": 29.7,
      "utilization_contribution": 12.96
    },
    "status": "completed",
    "stderr": "",
    "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/tmpbmrel1ji.py\", line 13, in \u003cmodule\u003e\n    loan_amount = UNRESOLVED_loan_amount\n                  ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\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/tmpbmrel1ji.py\", line 13, in \u003cmodule\u003e\n    loan_amount = UNRESOLVED_loan_amount\n                  ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\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": 0.205084,
      "end_time": "2025-07-16T07:42:59.126461",
      "message_sent": true,
      "start_time": "2025-07-16T07:42:58.921377",
      "timestamp": "2025-07-16T07:42:59.126461",
      "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": "Based on the provided compliance check results, here is a comprehensive compliance assessment:\n\n```json\n{\n  \"overall_compliance_status\": \"Compliant\",\n  \"risk_assessment\": {\n    \"KYC\": {\n      \"status\": \"Compliant\",\n      \"risk_category\": \"Low\",\n      \"compliance_score\": 98.5\n    },\n    \"AML\": {\n      \"status\": \"Cleared\",\n      \"risk_rating\": \"Low\",\n      \"compliance_score\": 96.8\n    },\n    \"Regulatory Compliance\": {\n      \"regulatory_risk\": \"Minimal\",\n      \"compliance_score\": 97.2\n    },\n    \"Internal Policy\": {\n      \"policy_version\": \"2024.1\",\n      \"policy_compliance_score\": 95.5\n    }\n  },\n  \"compliance_gaps_or_concerns\": [],\n  \"recommendations_for_proceeding\": [\n    \"Continue monitoring compliance with KYC and AML regulations.\",\n    \"Maintain adherence to internal policies and regulatory guidelines.\",\n    \"Regularly review and update compliance measures to ensure ongoing compliance.\"\n  ],\n  \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.",
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          "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"
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        "model_client_id": "compliance_reviewer",
        "output": "Based on the provided compliance check results, here is a comprehensive compliance assessment:\n\n```json\n{\n  \"overall_compliance_status\": \"Compliant\",\n  \"risk_assessment\": {\n    \"KYC\": {\n      \"status\": \"Compliant\",\n      \"risk_category\": \"Low\",\n      \"compliance_score\": 98.5\n    },\n    \"AML\": {\n      \"status\": \"Cleared\",\n      \"risk_rating\": \"Low\",\n      \"compliance_score\": 96.8\n    },\n    \"Regulatory Compliance\": {\n      \"regulatory_risk\": \"Minimal\",\n      \"compliance_score\": 97.2\n    },\n    \"Internal Policy\": {\n      \"policy_version\": \"2024.1\",\n      \"policy_compliance_score\": 95.5\n    }\n  },\n  \"compliance_gaps_or_concerns\": [],\n  \"recommendations_for_proceeding\": [\n    \"Continue monitoring compliance with KYC and AML regulations.\",\n    \"Maintain adherence to internal policies and regulatory guidelines.\",\n    \"Regularly review and update compliance measures to ensure ongoing compliance.\"\n  ],\n  \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive compliance assessment:\\n\\n```json\\n{\\n  \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n  \\\"risk_assessment\\\": {\\n    \\\"KYC\\\": {\\n      \\\"status\\\": \\\"Compliant\\\",\\n      \\\"risk_category\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 98.5\\n    },\\n    \\\"AML\\\": {\\n      \\\"status\\\": \\\"Cleared\\\",\\n      \\\"risk_rating\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 96.8\\n    },\\n    \\\"Regulatory Compliance\\\": {\\n      \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n      \\\"compliance_score\\\": 97.2\\n    },\\n    \\\"Internal Policy\\\": {\\n      \\\"policy_version\\\": \\\"2024.1\\\",\\n      \\\"policy_compliance_score\\\": 95.5\\n    }\\n  },\\n  \\\"compliance_gaps_or_concerns\\\": [],\\n  \\\"recommendations_for_proceeding\\\": [\\n    \\\"Continue monitoring compliance with KYC and AML regulations.\\\",\\n    \\\"Maintain adherence to internal policies and regulatory guidelines.\\\",\\n    \\\"Regularly review and update compliance measures to ensure ongoing compliance.\\\"\\n  ],\\n  \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2556, \"completion_tokens\": 379, \"total_tokens\": 2935, \"estimated_cost\": {\"amount\": 0.000611, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "model_client_id": "compliance_reviewer",
    "output": "Based on the provided compliance check results, here is a comprehensive compliance assessment:\n\n```json\n{\n  \"overall_compliance_status\": \"Compliant\",\n  \"risk_assessment\": {\n    \"KYC\": {\n      \"status\": \"Compliant\",\n      \"risk_category\": \"Low\",\n      \"compliance_score\": 98.5\n    },\n    \"AML\": {\n      \"status\": \"Cleared\",\n      \"risk_rating\": \"Low\",\n      \"compliance_score\": 96.8\n    },\n    \"Regulatory Compliance\": {\n      \"regulatory_risk\": \"Minimal\",\n      \"compliance_score\": 97.2\n    },\n    \"Internal Policy\": {\n      \"policy_version\": \"2024.1\",\n      \"policy_compliance_score\": 95.5\n    }\n  },\n  \"compliance_gaps_or_concerns\": [],\n  \"recommendations_for_proceeding\": [\n    \"Continue monitoring compliance with KYC and AML regulations.\",\n    \"Maintain adherence to internal policies and regulatory guidelines.\",\n    \"Regularly review and update compliance measures to ensure ongoing compliance.\"\n  ],\n  \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive compliance assessment:\\n\\n```json\\n{\\n  \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n  \\\"risk_assessment\\\": {\\n    \\\"KYC\\\": {\\n      \\\"status\\\": \\\"Compliant\\\",\\n      \\\"risk_category\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 98.5\\n    },\\n    \\\"AML\\\": {\\n      \\\"status\\\": \\\"Cleared\\\",\\n      \\\"risk_rating\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 96.8\\n    },\\n    \\\"Regulatory Compliance\\\": {\\n      \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n      \\\"compliance_score\\\": 97.2\\n    },\\n    \\\"Internal Policy\\\": {\\n      \\\"policy_version\\\": \\\"2024.1\\\",\\n      \\\"policy_compliance_score\\\": 95.5\\n    }\\n  },\\n  \\\"compliance_gaps_or_concerns\\\": [],\\n  \\\"recommendations_for_proceeding\\\": [\\n    \\\"Continue monitoring compliance with KYC and AML regulations.\\\",\\n    \\\"Maintain adherence to internal policies and regulatory guidelines.\\\",\\n    \\\"Regularly review and update compliance measures to ensure ongoing compliance.\\\"\\n  ],\\n  \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2556, \"completion_tokens\": 379, \"total_tokens\": 2935, \"estimated_cost\": {\"amount\": 0.000611, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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  "consolidate_document_verification": {
    "agent_type": "assistant",
    "ai_response": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \"not found\" or \"not provided,\" indicating a significant gap in the documentation process.\n\n3. **Risk Factors Identified**:\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\n\n4. **Recommendation for Proceeding**:\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n  \"overall_verification_success_rate\": \"0%\",\n  \"consistency_across_documents\": \"No documents provided or verified.\",\n  \"risk_factors_identified\": \"High risk due to absence of essential identification documents.\",\n  \"recommendation\": \"Reject the application and request necessary documents for verification.\"\n}\n```",
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          "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": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \"not found\" or \"not provided,\" indicating a significant gap in the documentation process.\n\n3. **Risk Factors Identified**:\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\n\n4. **Recommendation for Proceeding**:\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n  \"overall_verification_success_rate\": \"0%\",\n  \"consistency_across_documents\": \"No documents provided or verified.\",\n  \"risk_factors_identified\": \"High risk due to absence of essential identification documents.\",\n  \"recommendation\": \"Reject the application and request necessary documents for verification.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \\\"not found\\\" or \\\"not provided,\\\" indicating a significant gap in the documentation process.\\n\\n3. **Risk Factors Identified**:\\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\\n\\n4. **Recommendation for Proceeding**:\\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n  \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n  \\\"consistency_across_documents\\\": \\\"No documents provided or verified.\\\",\\n  \\\"risk_factors_identified\\\": \\\"High risk due to absence of essential identification documents.\\\",\\n  \\\"recommendation\\\": \\\"Reject the application and request necessary documents for verification.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 895, \"completion_tokens\": 308, \"total_tokens\": 1203, \"estimated_cost\": {\"amount\": 0.000319, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "model": "gpt-4o-mini",
    "model_client_id": "underwriting_analyst",
    "output": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \"not found\" or \"not provided,\" indicating a significant gap in the documentation process.\n\n3. **Risk Factors Identified**:\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\n\n4. **Recommendation for Proceeding**:\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n  \"overall_verification_success_rate\": \"0%\",\n  \"consistency_across_documents\": \"No documents provided or verified.\",\n  \"risk_factors_identified\": \"High risk due to absence of essential identification documents.\",\n  \"recommendation\": \"Reject the application and request necessary documents for verification.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \\\"not found\\\" or \\\"not provided,\\\" indicating a significant gap in the documentation process.\\n\\n3. **Risk Factors Identified**:\\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\\n\\n4. **Recommendation for Proceeding**:\\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n  \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n  \\\"consistency_across_documents\\\": \\\"No documents provided or verified.\\\",\\n  \\\"risk_factors_identified\\\": \\\"High risk due to absence of essential identification documents.\\\",\\n  \\\"recommendation\\\": \\\"Reject the application and request necessary documents for verification.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 895, \"completion_tokens\": 308, \"total_tokens\": 1203, \"estimated_cost\": {\"amount\": 0.000319, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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  "evaluate_default_risk": {
    "agent_type": "assistant",
    "ai_response": "Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\n\n### Credit Data Analysis\n\n1. **CIBIL Score**:\n   - **Score**: 720 (Good)\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\n\n2. **Credit History**:\n   - **Total Accounts**: 8 (6 active, 2 closed)\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\n   - **Repayment Behavior**:\n     - **Defaults**: 0.0%\n     - **30 Days Late**: 12.0%\n     - **60 Days Late**: 2.5%\n     - **90 Days Late**: 0.5%\n     - **Never Missed**: 85.0%\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\n\n3. **Existing Loans**:\n   - **Total Monthly EMI**: 7700\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\n\n### Risk Score Calculation\n\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\n\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\n\n### Total Risk Score Calculation\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\n- **Risk Score**: 60 out of 100\n\n### Default Risk Assessment\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\n\n### Conclusion\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.",
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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"
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        "model_client_id": "risk_assessor",
        "output": "Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\n\n### Credit Data Analysis\n\n1. **CIBIL Score**:\n   - **Score**: 720 (Good)\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\n\n2. **Credit History**:\n   - **Total Accounts**: 8 (6 active, 2 closed)\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\n   - **Repayment Behavior**:\n     - **Defaults**: 0.0%\n     - **30 Days Late**: 12.0%\n     - **60 Days Late**: 2.5%\n     - **90 Days Late**: 0.5%\n     - **Never Missed**: 85.0%\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\n\n3. **Existing Loans**:\n   - **Total Monthly EMI**: 7700\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\n\n### Risk Score Calculation\n\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\n\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\n\n### Total Risk Score Calculation\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\n- **Risk Score**: 60 out of 100\n\n### Default Risk Assessment\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\n\n### Conclusion\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\\n\\n### Credit Data Analysis\\n\\n1. **CIBIL Score**:\\n   - **Score**: 720 (Good)\\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\\n\\n2. **Credit History**:\\n   - **Total Accounts**: 8 (6 active, 2 closed)\\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\\n   - **Repayment Behavior**:\\n     - **Defaults**: 0.0%\\n     - **30 Days Late**: 12.0%\\n     - **60 Days Late**: 2.5%\\n     - **90 Days Late**: 0.5%\\n     - **Never Missed**: 85.0%\\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\\n\\n3. **Existing Loans**:\\n   - **Total Monthly EMI**: 7700\\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\\n\\n### Risk Score Calculation\\n\\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\\n\\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\\n\\n### Total Risk Score Calculation\\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\\n- **Risk Score**: 60 out of 100\\n\\n### Default Risk Assessment\\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\\n\\n### Conclusion\\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1769, \"completion_tokens\": 810, \"total_tokens\": 2579, \"estimated_cost\": {\"amount\": 0.000751, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "output": "Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\n\n### Credit Data Analysis\n\n1. **CIBIL Score**:\n   - **Score**: 720 (Good)\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\n\n2. **Credit History**:\n   - **Total Accounts**: 8 (6 active, 2 closed)\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\n   - **Repayment Behavior**:\n     - **Defaults**: 0.0%\n     - **30 Days Late**: 12.0%\n     - **60 Days Late**: 2.5%\n     - **90 Days Late**: 0.5%\n     - **Never Missed**: 85.0%\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\n\n3. **Existing Loans**:\n   - **Total Monthly EMI**: 7700\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\n\n### Risk Score Calculation\n\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\n\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\n\n### Total Risk Score Calculation\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\n- **Risk Score**: 60 out of 100\n\n### Default Risk Assessment\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\n\n### Conclusion\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\\n\\n### Credit Data Analysis\\n\\n1. **CIBIL Score**:\\n   - **Score**: 720 (Good)\\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\\n\\n2. **Credit History**:\\n   - **Total Accounts**: 8 (6 active, 2 closed)\\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\\n   - **Repayment Behavior**:\\n     - **Defaults**: 0.0%\\n     - **30 Days Late**: 12.0%\\n     - **60 Days Late**: 2.5%\\n     - **90 Days Late**: 0.5%\\n     - **Never Missed**: 85.0%\\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\\n\\n3. **Existing Loans**:\\n   - **Total Monthly EMI**: 7700\\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\\n\\n### Risk Score Calculation\\n\\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\\n\\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\\n\\n### Total Risk Score Calculation\\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\\n- **Risk Score**: 60 out of 100\\n\\n### Default Risk Assessment\\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\\n\\n### Conclusion\\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1769, \"completion_tokens\": 810, \"total_tokens\": 2579, \"estimated_cost\": {\"amount\": 0.000751, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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  "extract_application_info": {
    "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpbzqd7dt4.py\", line 18, in \u003cmodule\u003e\n    \"requested_amount\": UNRESOLVED_loan_amount\n                        ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
    "execution_details": {
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    "output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpbzqd7dt4.py\", line 18, in \u003cmodule\u003e\n    \"requested_amount\": UNRESOLVED_loan_amount\n                        ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
    "status": "FAILED",
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  "final_underwriting_analysis": {
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    "ai_response": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable due to application decline.\n- **Loan Term**: Not applicable due to application decline.\n- **Repayment Schedule**: Not applicable due to application decline.\n\n#### Risk Mitigation Measures:\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\n\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\n\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\n\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\n\n#### Confidence Level: 95\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.",
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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": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable due to application decline.\n- **Loan Term**: Not applicable due to application decline.\n- **Repayment Schedule**: Not applicable due to application decline.\n\n#### Risk Mitigation Measures:\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\n\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\n\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\n\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\n\n#### Confidence Level: 95\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable due to application decline.\\n- **Loan Term**: Not applicable due to application decline.\\n- **Repayment Schedule**: Not applicable due to application decline.\\n\\n#### Risk Mitigation Measures:\\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\\n\\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\\n\\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\\n\\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\\n\\n#### Confidence Level: 95\\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6019, \"completion_tokens\": 484, \"total_tokens\": 6503, \"estimated_cost\": {\"amount\": 0.001193, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable due to application decline.\n- **Loan Term**: Not applicable due to application decline.\n- **Repayment Schedule**: Not applicable due to application decline.\n\n#### Risk Mitigation Measures:\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\n\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\n\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\n\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\n\n#### Confidence Level: 95\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable due to application decline.\\n- **Loan Term**: Not applicable due to application decline.\\n- **Repayment Schedule**: Not applicable due to application decline.\\n\\n#### Risk Mitigation Measures:\\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\\n\\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\\n\\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\\n\\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\\n\\n#### Confidence Level: 95\\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6019, \"completion_tokens\": 484, \"total_tokens\": 6503, \"estimated_cost\": {\"amount\": 0.001193, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "task_id": "final_underwriting_analysis",
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  },
  "flag_for_manual_review": {
    "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpnabc2fdg.py\", line 11, in \u003cmodule\u003e\n    \"loan_amount\": UNRESOLVED_loan_amount,\n                   ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\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/tmpnabc2fdg.py\", line 11, in \u003cmodule\u003e\n    \"loan_amount\": UNRESOLVED_loan_amount,\n                   ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
    "status": "FAILED",
    "task_id": "flag_for_manual_review"
  },
  "generate_final_output": {
    "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmp974inpov.py\", line 16, in \u003cmodule\u003e\n    \"debt_to_income_ratio\": UNRESOLVED_calculate_debt_to_income.debt_to_income_ratio,\n                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_debt_to_income\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/tmp974inpov.py\", line 16, in \u003cmodule\u003e\n    \"debt_to_income_ratio\": UNRESOLVED_calculate_debt_to_income.debt_to_income_ratio,\n                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_debt_to_income\u0027 is not defined\n",
    "status": "FAILED",
    "task_id": "generate_final_output"
  },
  "income_assessment": {
    "agent_type": "assistant",
    "ai_response": "Based on the comprehensive income data provided, here is a detailed assessment:\n\n```json\n{\n  \"income_stability_assessment\": {\n    \"annual_net_income\": 81600,\n    \"monthly_net_income\": 6800,\n    \"employment_duration\": \"2.5 years\",\n    \"salary_consistency\": true,\n    \"recent_increment\": true,\n    \"stability_score\": 90,\n    \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\"\n  },\n  \"debt_servicing_capability\": {\n    \"monthly_debts\": 5800,\n    \"average_monthly_credits\": 7200,\n    \"debt_to_income_ratio\": 80.95,\n    \"loan_emis_detected\": 2,\n    \"bounced_transactions\": 0,\n    \"comments\": \"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\"\n  },\n  \"financial_discipline_evaluation\": {\n    \"financial_discipline_score\": 85.5,\n    \"account_balance_trend\": \"stable\",\n    \"salary_credits_consistent\": true,\n    \"irregular_transactions\": false,\n    \"comments\": \"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\"\n  },\n  \"risk_factors_and_recommendations\": {\n    \"high_debt_to_income_ratio\": true,\n    \"recommendations\": [\n      \"Consider advising the applicant to reduce existing debt before applying for additional loans.\",\n      \"Monitor future income growth and stability to reassess debt servicing capability.\"\n    ],\n    \"comments\": \"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\"\n  },\n  \"overall_income_adequacy_score\": 75,\n  \"comments\": \"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.",
    "execution_details": {
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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"
        },
        "input_format": "json",
        "model_client_id": "underwriting_analyst",
        "output": "Based on the comprehensive income data provided, here is a detailed assessment:\n\n```json\n{\n  \"income_stability_assessment\": {\n    \"annual_net_income\": 81600,\n    \"monthly_net_income\": 6800,\n    \"employment_duration\": \"2.5 years\",\n    \"salary_consistency\": true,\n    \"recent_increment\": true,\n    \"stability_score\": 90,\n    \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\"\n  },\n  \"debt_servicing_capability\": {\n    \"monthly_debts\": 5800,\n    \"average_monthly_credits\": 7200,\n    \"debt_to_income_ratio\": 80.95,\n    \"loan_emis_detected\": 2,\n    \"bounced_transactions\": 0,\n    \"comments\": \"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\"\n  },\n  \"financial_discipline_evaluation\": {\n    \"financial_discipline_score\": 85.5,\n    \"account_balance_trend\": \"stable\",\n    \"salary_credits_consistent\": true,\n    \"irregular_transactions\": false,\n    \"comments\": \"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\"\n  },\n  \"risk_factors_and_recommendations\": {\n    \"high_debt_to_income_ratio\": true,\n    \"recommendations\": [\n      \"Consider advising the applicant to reduce existing debt before applying for additional loans.\",\n      \"Monitor future income growth and stability to reassess debt servicing capability.\"\n    ],\n    \"comments\": \"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\"\n  },\n  \"overall_income_adequacy_score\": 75,\n  \"comments\": \"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment:\\n\\n```json\\n{\\n  \\\"income_stability_assessment\\\": {\\n    \\\"annual_net_income\\\": 81600,\\n    \\\"monthly_net_income\\\": 6800,\\n    \\\"employment_duration\\\": \\\"2.5 years\\\",\\n    \\\"salary_consistency\\\": true,\\n    \\\"recent_increment\\\": true,\\n    \\\"stability_score\\\": 90,\\n    \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\\\"\\n  },\\n  \\\"debt_servicing_capability\\\": {\\n    \\\"monthly_debts\\\": 5800,\\n    \\\"average_monthly_credits\\\": 7200,\\n    \\\"debt_to_income_ratio\\\": 80.95,\\n    \\\"loan_emis_detected\\\": 2,\\n    \\\"bounced_transactions\\\": 0,\\n    \\\"comments\\\": \\\"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\\\"\\n  },\\n  \\\"financial_discipline_evaluation\\\": {\\n    \\\"financial_discipline_score\\\": 85.5,\\n    \\\"account_balance_trend\\\": \\\"stable\\\",\\n    \\\"salary_credits_consistent\\\": true,\\n    \\\"irregular_transactions\\\": false,\\n    \\\"comments\\\": \\\"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\\\"\\n  },\\n  \\\"risk_factors_and_recommendations\\\": {\\n    \\\"high_debt_to_income_ratio\\\": true,\\n    \\\"recommendations\\\": [\\n      \\\"Consider advising the applicant to reduce existing debt before applying for additional loans.\\\",\\n      \\\"Monitor future income growth and stability to reassess debt servicing capability.\\\"\\n    ],\\n    \\\"comments\\\": \\\"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\\\"\\n  },\\n  \\\"overall_income_adequacy_score\\\": 75,\\n  \\\"comments\\\": \\\"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1226, \"completion_tokens\": 589, \"total_tokens\": 1815, \"estimated_cost\": {\"amount\": 0.000537, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "model": "gpt-4o-mini",
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    "output": "Based on the comprehensive income data provided, here is a detailed assessment:\n\n```json\n{\n  \"income_stability_assessment\": {\n    \"annual_net_income\": 81600,\n    \"monthly_net_income\": 6800,\n    \"employment_duration\": \"2.5 years\",\n    \"salary_consistency\": true,\n    \"recent_increment\": true,\n    \"stability_score\": 90,\n    \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\"\n  },\n  \"debt_servicing_capability\": {\n    \"monthly_debts\": 5800,\n    \"average_monthly_credits\": 7200,\n    \"debt_to_income_ratio\": 80.95,\n    \"loan_emis_detected\": 2,\n    \"bounced_transactions\": 0,\n    \"comments\": \"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\"\n  },\n  \"financial_discipline_evaluation\": {\n    \"financial_discipline_score\": 85.5,\n    \"account_balance_trend\": \"stable\",\n    \"salary_credits_consistent\": true,\n    \"irregular_transactions\": false,\n    \"comments\": \"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\"\n  },\n  \"risk_factors_and_recommendations\": {\n    \"high_debt_to_income_ratio\": true,\n    \"recommendations\": [\n      \"Consider advising the applicant to reduce existing debt before applying for additional loans.\",\n      \"Monitor future income growth and stability to reassess debt servicing capability.\"\n    ],\n    \"comments\": \"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\"\n  },\n  \"overall_income_adequacy_score\": 75,\n  \"comments\": \"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment:\\n\\n```json\\n{\\n  \\\"income_stability_assessment\\\": {\\n    \\\"annual_net_income\\\": 81600,\\n    \\\"monthly_net_income\\\": 6800,\\n    \\\"employment_duration\\\": \\\"2.5 years\\\",\\n    \\\"salary_consistency\\\": true,\\n    \\\"recent_increment\\\": true,\\n    \\\"stability_score\\\": 90,\\n    \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\\\"\\n  },\\n  \\\"debt_servicing_capability\\\": {\\n    \\\"monthly_debts\\\": 5800,\\n    \\\"average_monthly_credits\\\": 7200,\\n    \\\"debt_to_income_ratio\\\": 80.95,\\n    \\\"loan_emis_detected\\\": 2,\\n    \\\"bounced_transactions\\\": 0,\\n    \\\"comments\\\": \\\"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\\\"\\n  },\\n  \\\"financial_discipline_evaluation\\\": {\\n    \\\"financial_discipline_score\\\": 85.5,\\n    \\\"account_balance_trend\\\": \\\"stable\\\",\\n    \\\"salary_credits_consistent\\\": true,\\n    \\\"irregular_transactions\\\": false,\\n    \\\"comments\\\": \\\"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\\\"\\n  },\\n  \\\"risk_factors_and_recommendations\\\": {\\n    \\\"high_debt_to_income_ratio\\\": true,\\n    \\\"recommendations\\\": [\\n      \\\"Consider advising the applicant to reduce existing debt before applying for additional loans.\\\",\\n      \\\"Monitor future income growth and stability to reassess debt servicing capability.\\\"\\n    ],\\n    \\\"comments\\\": \\\"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\\\"\\n  },\\n  \\\"overall_income_adequacy_score\\\": 75,\\n  \\\"comments\\\": \\\"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1226, \"completion_tokens\": 589, \"total_tokens\": 1815, \"estimated_cost\": {\"amount\": 0.000537, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "credit_score_threshold_met": true,
    "employment_criteria_met": true,
    "exceptions_required": [],
    "execution_details": {
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        "output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
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    "geographic_restrictions_met": true,
    "income_criteria_met": true,
    "loan_amount_within_limits": true,
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    "output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
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    "data_privacy_compliant": true,
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      "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": 0.235547,
        "end_time": "2025-07-16T07:43:17.513726",
        "message_sent": true,
        "start_time": "2025-07-16T07:43:17.278179",
        "timestamp": "2025-07-16T07:43:17.513726",
        "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": 0.488948,
        "end_time": "2025-07-16T07:39:46.084078",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:45.595130",
        "timestamp": "2025-07-16T07:39:46.084078",
        "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": 0.212024,
        "end_time": "2025-07-16T07:42:59.371799",
        "message_sent": true,
        "start_time": "2025-07-16T07:42:59.159775",
        "timestamp": "2025-07-16T07:42:59.371799",
        "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": 0.413659,
        "end_time": "2025-07-16T07:39:45.938742",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:45.525083",
        "timestamp": "2025-07-16T07:39:45.938742",
        "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": "Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\n\nHere\u2019s the assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\n\n2. **Consistency of Information**:\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\n\n3. **Red Flags or Inconsistencies**:\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\n\n4. **Overall Application Quality Score**:\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\n\nBased on this analysis, the overall application quality score is **10** out of 100.\n\nHere is the JSON response with the assessment:\n\n```json\n{\n  \"data_completeness\": \"Incomplete - customer information could not be extracted.\",\n  \"data_accuracy\": \"Cannot assess due to missing data.\",\n  \"information_consistency\": \"No information available to evaluate consistency.\",\n  \"red_flags\": \"Failure to extract customer information indicates potential issues.\",\n  \"overall_quality_score\": 10\n}\n```",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 506,
            "model": "gpt-4o-mini",
            "output_length": 1984,
            "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": "Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\n\nHere\u2019s the assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\n\n2. **Consistency of Information**:\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\n\n3. **Red Flags or Inconsistencies**:\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\n\n4. **Overall Application Quality Score**:\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\n\nBased on this analysis, the overall application quality score is **10** out of 100.\n\nHere is the JSON response with the assessment:\n\n```json\n{\n  \"data_completeness\": \"Incomplete - customer information could not be extracted.\",\n  \"data_accuracy\": \"Cannot assess due to missing data.\",\n  \"information_consistency\": \"No information available to evaluate consistency.\",\n  \"red_flags\": \"Failure to extract customer information indicates potential issues.\",\n  \"overall_quality_score\": 10\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\\n\\nHere\\u2019s the assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\\n\\n2. **Consistency of Information**:\\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\\n\\n3. **Red Flags or Inconsistencies**:\\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\\n\\n4. **Overall Application Quality Score**:\\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\\n\\nBased on this analysis, the overall application quality score is **10** out of 100.\\n\\nHere is the JSON response with the assessment:\\n\\n```json\\n{\\n  \\\"data_completeness\\\": \\\"Incomplete - customer information could not be extracted.\\\",\\n  \\\"data_accuracy\\\": \\\"Cannot assess due to missing data.\\\",\\n  \\\"information_consistency\\\": \\\"No information available to evaluate consistency.\\\",\\n  \\\"red_flags\\\": \\\"Failure to extract customer information indicates potential issues.\\\",\\n  \\\"overall_quality_score\\\": 10\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 376, \"total_tokens\": 562, \"estimated_cost\": {\"amount\": 0.000253, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": "",
          "token_usage": {
            "completion_tokens": 376,
            "estimated_cost": {
              "amount": 0.000253,
              "currency": "USD"
            },
            "model": "gpt-4o-mini",
            "prompt_tokens": 186,
            "provider": "openai",
            "total_tokens": 562
          }
        },
        "duration_seconds": 6.842099,
        "end_time": "2025-07-16T07:39:37.912882",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:31.070783",
        "timestamp": "2025-07-16T07:39:37.912882",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\n\nHere\u2019s the assessment based on the available information:\n\n1. **Data Completeness and Accuracy**:\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\n\n2. **Consistency of Information**:\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\n\n3. **Red Flags or Inconsistencies**:\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\n\n4. **Overall Application Quality Score**:\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\n\nBased on this analysis, the overall application quality score is **10** out of 100.\n\nHere is the JSON response with the assessment:\n\n```json\n{\n  \"data_completeness\": \"Incomplete - customer information could not be extracted.\",\n  \"data_accuracy\": \"Cannot assess due to missing data.\",\n  \"information_consistency\": \"No information available to evaluate consistency.\",\n  \"red_flags\": \"Failure to extract customer information indicates potential issues.\",\n  \"overall_quality_score\": 10\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided information, it appears that there was an error in extracting the customer information from the loan application. The error message indicates that the variable `UNRESOLVED_extract_application_info.customer_info` is not defined, which suggests that the application data is either missing or improperly referenced.\\n\\nHere\\u2019s the assessment based on the available information:\\n\\n1. **Data Completeness and Accuracy**:\\n   - **Completeness**: The application data is incomplete as the customer information could not be extracted. Without this data, it is impossible to assess the applicant\u0027s financial situation, creditworthiness, or any other relevant factors.\\n   - **Accuracy**: Since the data could not be retrieved, accuracy cannot be assessed.\\n\\n2. **Consistency of Information**:\\n   - There is no information available to evaluate consistency. The absence of customer data means we cannot compare or validate any details against other provided information.\\n\\n3. **Red Flags or Inconsistencies**:\\n   - The primary red flag is the failure to extract customer information. This indicates a potential issue with the application process or data entry, which could lead to further complications in the underwriting process.\\n\\n4. **Overall Application Quality Score**:\\n   - Given the critical failure to retrieve customer information, the overall quality score of this application is extremely low. The lack of data prevents any meaningful assessment of the applicant\u0027s qualifications.\\n\\nBased on this analysis, the overall application quality score is **10** out of 100.\\n\\nHere is the JSON response with the assessment:\\n\\n```json\\n{\\n  \\\"data_completeness\\\": \\\"Incomplete - customer information could not be extracted.\\\",\\n  \\\"data_accuracy\\\": \\\"Cannot assess due to missing data.\\\",\\n  \\\"information_consistency\\\": \\\"No information available to evaluate consistency.\\\",\\n  \\\"red_flags\\\": \\\"Failure to extract customer information indicates potential issues.\\\",\\n  \\\"overall_quality_score\\\": 10\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 186, \"completion_tokens\": 376, \"total_tokens\": 562, \"estimated_cost\": {\"amount\": 0.000253, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "application_quality_check",
      "token_usage": {
        "completion_tokens": 376,
        "estimated_cost": {
          "amount": 0.000253,
          "currency": "USD"
        },
        "model": "gpt-4o-mini",
        "prompt_tokens": 186,
        "provider": "openai",
        "total_tokens": 562
      }
    },
    "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": 0.191274,
        "end_time": "2025-07-16T07:42:59.591076",
        "message_sent": true,
        "start_time": "2025-07-16T07:42:59.399802",
        "timestamp": "2025-07-16T07:42:59.591076",
        "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": {
      "cibil_score": 720,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.212566,
        "end_time": "2025-07-16T07:43:16.985138",
        "message_sent": true,
        "start_time": "2025-07-16T07:43:16.772572",
        "timestamp": "2025-07-16T07:43:16.985138",
        "worker_executed": true,
        "workers_notified": true
      },
      "internal_credit_score": 337.9,
      "min_required_score": 650,
      "output": "__OUTPUTS__ {\"internal_credit_score\": 337.9, \"cibil_score\": 720, \"score_acceptable\": false, \"min_required_score\": 650, \"risk_category\": \"high\", \"scoring_factors\": {\"cibil_contribution\": 288.0, \"payment_history_contribution\": 29.7, \"utilization_contribution\": 12.96, \"loan_burden_contribution\": 7.2}}\n",
      "return_code": 0,
      "risk_category": "high",
      "score_acceptable": false,
      "scoring_factors": {
        "cibil_contribution": 288.0,
        "loan_burden_contribution": 7.2,
        "payment_history_contribution": 29.7,
        "utilization_contribution": 12.96
      },
      "status": "completed",
      "stderr": "",
      "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/tmpbmrel1ji.py\", line 13, in \u003cmodule\u003e\n    loan_amount = UNRESOLVED_loan_amount\n                  ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\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/tmpbmrel1ji.py\", line 13, in \u003cmodule\u003e\n    loan_amount = UNRESOLVED_loan_amount\n                  ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\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": 0.205084,
        "end_time": "2025-07-16T07:42:59.126461",
        "message_sent": true,
        "start_time": "2025-07-16T07:42:58.921377",
        "timestamp": "2025-07-16T07:42:59.126461",
        "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": "Based on the provided compliance check results, here is a comprehensive compliance assessment:\n\n```json\n{\n  \"overall_compliance_status\": \"Compliant\",\n  \"risk_assessment\": {\n    \"KYC\": {\n      \"status\": \"Compliant\",\n      \"risk_category\": \"Low\",\n      \"compliance_score\": 98.5\n    },\n    \"AML\": {\n      \"status\": \"Cleared\",\n      \"risk_rating\": \"Low\",\n      \"compliance_score\": 96.8\n    },\n    \"Regulatory Compliance\": {\n      \"regulatory_risk\": \"Minimal\",\n      \"compliance_score\": 97.2\n    },\n    \"Internal Policy\": {\n      \"policy_version\": \"2024.1\",\n      \"policy_compliance_score\": 95.5\n    }\n  },\n  \"compliance_gaps_or_concerns\": [],\n  \"recommendations_for_proceeding\": [\n    \"Continue monitoring compliance with KYC and AML regulations.\",\n    \"Maintain adherence to internal policies and regulatory guidelines.\",\n    \"Regularly review and update compliance measures to ensure ongoing compliance.\"\n  ],\n  \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.",
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            "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"
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          "model_client_id": "compliance_reviewer",
          "output": "Based on the provided compliance check results, here is a comprehensive compliance assessment:\n\n```json\n{\n  \"overall_compliance_status\": \"Compliant\",\n  \"risk_assessment\": {\n    \"KYC\": {\n      \"status\": \"Compliant\",\n      \"risk_category\": \"Low\",\n      \"compliance_score\": 98.5\n    },\n    \"AML\": {\n      \"status\": \"Cleared\",\n      \"risk_rating\": \"Low\",\n      \"compliance_score\": 96.8\n    },\n    \"Regulatory Compliance\": {\n      \"regulatory_risk\": \"Minimal\",\n      \"compliance_score\": 97.2\n    },\n    \"Internal Policy\": {\n      \"policy_version\": \"2024.1\",\n      \"policy_compliance_score\": 95.5\n    }\n  },\n  \"compliance_gaps_or_concerns\": [],\n  \"recommendations_for_proceeding\": [\n    \"Continue monitoring compliance with KYC and AML regulations.\",\n    \"Maintain adherence to internal policies and regulatory guidelines.\",\n    \"Regularly review and update compliance measures to ensure ongoing compliance.\"\n  ],\n  \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive compliance assessment:\\n\\n```json\\n{\\n  \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n  \\\"risk_assessment\\\": {\\n    \\\"KYC\\\": {\\n      \\\"status\\\": \\\"Compliant\\\",\\n      \\\"risk_category\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 98.5\\n    },\\n    \\\"AML\\\": {\\n      \\\"status\\\": \\\"Cleared\\\",\\n      \\\"risk_rating\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 96.8\\n    },\\n    \\\"Regulatory Compliance\\\": {\\n      \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n      \\\"compliance_score\\\": 97.2\\n    },\\n    \\\"Internal Policy\\\": {\\n      \\\"policy_version\\\": \\\"2024.1\\\",\\n      \\\"policy_compliance_score\\\": 95.5\\n    }\\n  },\\n  \\\"compliance_gaps_or_concerns\\\": [],\\n  \\\"recommendations_for_proceeding\\\": [\\n    \\\"Continue monitoring compliance with KYC and AML regulations.\\\",\\n    \\\"Maintain adherence to internal policies and regulatory guidelines.\\\",\\n    \\\"Regularly review and update compliance measures to ensure ongoing compliance.\\\"\\n  ],\\n  \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2556, \"completion_tokens\": 379, \"total_tokens\": 2935, \"estimated_cost\": {\"amount\": 0.000611, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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      "model": "gpt-4o-mini",
      "model_client_id": "compliance_reviewer",
      "output": "Based on the provided compliance check results, here is a comprehensive compliance assessment:\n\n```json\n{\n  \"overall_compliance_status\": \"Compliant\",\n  \"risk_assessment\": {\n    \"KYC\": {\n      \"status\": \"Compliant\",\n      \"risk_category\": \"Low\",\n      \"compliance_score\": 98.5\n    },\n    \"AML\": {\n      \"status\": \"Cleared\",\n      \"risk_rating\": \"Low\",\n      \"compliance_score\": 96.8\n    },\n    \"Regulatory Compliance\": {\n      \"regulatory_risk\": \"Minimal\",\n      \"compliance_score\": 97.2\n    },\n    \"Internal Policy\": {\n      \"policy_version\": \"2024.1\",\n      \"policy_compliance_score\": 95.5\n    }\n  },\n  \"compliance_gaps_or_concerns\": [],\n  \"recommendations_for_proceeding\": [\n    \"Continue monitoring compliance with KYC and AML regulations.\",\n    \"Maintain adherence to internal policies and regulatory guidelines.\",\n    \"Regularly review and update compliance measures to ensure ongoing compliance.\"\n  ],\n  \"compliance_confidence_score\": 97.0\n}\n```\n\n### Summary of the Assessment:\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided compliance check results, here is a comprehensive compliance assessment:\\n\\n```json\\n{\\n  \\\"overall_compliance_status\\\": \\\"Compliant\\\",\\n  \\\"risk_assessment\\\": {\\n    \\\"KYC\\\": {\\n      \\\"status\\\": \\\"Compliant\\\",\\n      \\\"risk_category\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 98.5\\n    },\\n    \\\"AML\\\": {\\n      \\\"status\\\": \\\"Cleared\\\",\\n      \\\"risk_rating\\\": \\\"Low\\\",\\n      \\\"compliance_score\\\": 96.8\\n    },\\n    \\\"Regulatory Compliance\\\": {\\n      \\\"regulatory_risk\\\": \\\"Minimal\\\",\\n      \\\"compliance_score\\\": 97.2\\n    },\\n    \\\"Internal Policy\\\": {\\n      \\\"policy_version\\\": \\\"2024.1\\\",\\n      \\\"policy_compliance_score\\\": 95.5\\n    }\\n  },\\n  \\\"compliance_gaps_or_concerns\\\": [],\\n  \\\"recommendations_for_proceeding\\\": [\\n    \\\"Continue monitoring compliance with KYC and AML regulations.\\\",\\n    \\\"Maintain adherence to internal policies and regulatory guidelines.\\\",\\n    \\\"Regularly review and update compliance measures to ensure ongoing compliance.\\\"\\n  ],\\n  \\\"compliance_confidence_score\\\": 97.0\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Overall Compliance Status**: The applicant is compliant with all necessary regulations and internal policies.\\n2. **Risk Assessment**: All areas (KYC, AML, Regulatory Compliance, Internal Policy) show low risk and high compliance scores.\\n3. **Compliance Gaps or Concerns**: No significant gaps or concerns were identified in the compliance checks.\\n4. **Recommendations for Proceeding**: Ongoing monitoring and adherence to compliance measures are recommended to maintain the current compliance status.\\n5. **Compliance Confidence Score**: A score of 97.0 reflects a high level of confidence in the compliance status of the applicant.\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 2556, \"completion_tokens\": 379, \"total_tokens\": 2935, \"estimated_cost\": {\"amount\": 0.000611, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
      "provider": "openai",
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    "consolidate_document_verification": {
      "agent_type": "assistant",
      "ai_response": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \"not found\" or \"not provided,\" indicating a significant gap in the documentation process.\n\n3. **Risk Factors Identified**:\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\n\n4. **Recommendation for Proceeding**:\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n  \"overall_verification_success_rate\": \"0%\",\n  \"consistency_across_documents\": \"No documents provided or verified.\",\n  \"risk_factors_identified\": \"High risk due to absence of essential identification documents.\",\n  \"recommendation\": \"Reject the application and request necessary documents for verification.\"\n}\n```",
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            "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": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \"not found\" or \"not provided,\" indicating a significant gap in the documentation process.\n\n3. **Risk Factors Identified**:\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\n\n4. **Recommendation for Proceeding**:\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n  \"overall_verification_success_rate\": \"0%\",\n  \"consistency_across_documents\": \"No documents provided or verified.\",\n  \"risk_factors_identified\": \"High risk due to absence of essential identification documents.\",\n  \"recommendation\": \"Reject the application and request necessary documents for verification.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \\\"not found\\\" or \\\"not provided,\\\" indicating a significant gap in the documentation process.\\n\\n3. **Risk Factors Identified**:\\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\\n\\n4. **Recommendation for Proceeding**:\\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n  \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n  \\\"consistency_across_documents\\\": \\\"No documents provided or verified.\\\",\\n  \\\"risk_factors_identified\\\": \\\"High risk due to absence of essential identification documents.\\\",\\n  \\\"recommendation\\\": \\\"Reject the application and request necessary documents for verification.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 895, \"completion_tokens\": 308, \"total_tokens\": 1203, \"estimated_cost\": {\"amount\": 0.000319, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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            "provider": "openai",
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      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\n\n1. **Overall Verification Success Rate**:\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\n\n2. **Consistency Across Documents**:\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \"not found\" or \"not provided,\" indicating a significant gap in the documentation process.\n\n3. **Risk Factors Identified**:\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\n\n4. **Recommendation for Proceeding**:\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\n\nHere is the JSON response with the consolidated assessment:\n\n```json\n{\n  \"overall_verification_success_rate\": \"0%\",\n  \"consistency_across_documents\": \"No documents provided or verified.\",\n  \"risk_factors_identified\": \"High risk due to absence of essential identification documents.\",\n  \"recommendation\": \"Reject the application and request necessary documents for verification.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"Based on the provided document verification results for PAN, Aadhaar, Passport, and Address Proof, here is a comprehensive assessment:\\n\\n1. **Overall Verification Success Rate**:\\n   - All document verifications have failed, resulting in a success rate of **0%**. None of the required documents were found or validated.\\n\\n2. **Consistency Across Documents**:\\n   - There is a complete lack of consistency as no documents were provided or verified. All verification attempts returned a status of \\\"not found\\\" or \\\"not provided,\\\" indicating a significant gap in the documentation process.\\n\\n3. **Risk Factors Identified**:\\n   - The absence of essential identification documents (PAN, Aadhaar, Passport, Address Proof) poses a high risk for identity verification and fraud. The failure to provide these documents raises concerns about the applicant\u0027s legitimacy and ability to fulfill identification requirements.\\n\\n4. **Recommendation for Proceeding**:\\n   - It is recommended to **reject the application** due to the complete lack of valid identification documents. The applicant should be advised to provide the necessary documents for verification. If the applicant is unable to provide these documents, further processing should not continue.\\n\\nHere is the JSON response with the consolidated assessment:\\n\\n```json\\n{\\n  \\\"overall_verification_success_rate\\\": \\\"0%\\\",\\n  \\\"consistency_across_documents\\\": \\\"No documents provided or verified.\\\",\\n  \\\"risk_factors_identified\\\": \\\"High risk due to absence of essential identification documents.\\\",\\n  \\\"recommendation\\\": \\\"Reject the application and request necessary documents for verification.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 895, \"completion_tokens\": 308, \"total_tokens\": 1203, \"estimated_cost\": {\"amount\": 0.000319, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "evaluate_default_risk": {
      "agent_type": "assistant",
      "ai_response": "Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\n\n### Credit Data Analysis\n\n1. **CIBIL Score**:\n   - **Score**: 720 (Good)\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\n\n2. **Credit History**:\n   - **Total Accounts**: 8 (6 active, 2 closed)\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\n   - **Repayment Behavior**:\n     - **Defaults**: 0.0%\n     - **30 Days Late**: 12.0%\n     - **60 Days Late**: 2.5%\n     - **90 Days Late**: 0.5%\n     - **Never Missed**: 85.0%\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\n\n3. **Existing Loans**:\n   - **Total Monthly EMI**: 7700\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\n\n### Risk Score Calculation\n\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\n\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\n\n### Total Risk Score Calculation\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\n- **Risk Score**: 60 out of 100\n\n### Default Risk Assessment\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\n\n### Conclusion\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.",
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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"
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          "output": "Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\n\n### Credit Data Analysis\n\n1. **CIBIL Score**:\n   - **Score**: 720 (Good)\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\n\n2. **Credit History**:\n   - **Total Accounts**: 8 (6 active, 2 closed)\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\n   - **Repayment Behavior**:\n     - **Defaults**: 0.0%\n     - **30 Days Late**: 12.0%\n     - **60 Days Late**: 2.5%\n     - **90 Days Late**: 0.5%\n     - **Never Missed**: 85.0%\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\n\n3. **Existing Loans**:\n   - **Total Monthly EMI**: 7700\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\n\n### Risk Score Calculation\n\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\n\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\n\n### Total Risk Score Calculation\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\n- **Risk Score**: 60 out of 100\n\n### Default Risk Assessment\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\n\n### Conclusion\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\\n\\n### Credit Data Analysis\\n\\n1. **CIBIL Score**:\\n   - **Score**: 720 (Good)\\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\\n\\n2. **Credit History**:\\n   - **Total Accounts**: 8 (6 active, 2 closed)\\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\\n   - **Repayment Behavior**:\\n     - **Defaults**: 0.0%\\n     - **30 Days Late**: 12.0%\\n     - **60 Days Late**: 2.5%\\n     - **90 Days Late**: 0.5%\\n     - **Never Missed**: 85.0%\\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\\n\\n3. **Existing Loans**:\\n   - **Total Monthly EMI**: 7700\\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\\n\\n### Risk Score Calculation\\n\\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\\n\\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\\n\\n### Total Risk Score Calculation\\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\\n- **Risk Score**: 60 out of 100\\n\\n### Default Risk Assessment\\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\\n\\n### Conclusion\\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1769, \"completion_tokens\": 810, \"total_tokens\": 2579, \"estimated_cost\": {\"amount\": 0.000751, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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      "output": "Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\n\n### Credit Data Analysis\n\n1. **CIBIL Score**:\n   - **Score**: 720 (Good)\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\n\n2. **Credit History**:\n   - **Total Accounts**: 8 (6 active, 2 closed)\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\n   - **Repayment Behavior**:\n     - **Defaults**: 0.0%\n     - **30 Days Late**: 12.0%\n     - **60 Days Late**: 2.5%\n     - **90 Days Late**: 0.5%\n     - **Never Missed**: 85.0%\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\n\n3. **Existing Loans**:\n   - **Total Monthly EMI**: 7700\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\n\n### Risk Score Calculation\n\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\n\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\n\n### Total Risk Score Calculation\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\n- **Risk Score**: 60 out of 100\n\n### Default Risk Assessment\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\n\n### Recommendations\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\n\n### Conclusion\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\n__OUTPUTS__ {\"ai_response\": \"Based on the provided credit data, here is a comprehensive analysis of the default risk along with a risk score and recommendations:\\n\\n### Credit Data Analysis\\n\\n1. **CIBIL Score**:\\n   - **Score**: 720 (Good)\\n   - **Score Range**: Indicates a good creditworthiness, suggesting that the applicant is likely to repay debts.\\n   - **Payment History**: 99% on-time payments demonstrate strong repayment behavior.\\n\\n2. **Credit History**:\\n   - **Total Accounts**: 8 (6 active, 2 closed)\\n   - **Credit Mix**: A diverse mix of credit accounts (credit cards, personal loans, auto loans) is beneficial for credit scoring.\\n   - **Repayment Behavior**:\\n     - **Defaults**: 0.0%\\n     - **30 Days Late**: 12.0%\\n     - **60 Days Late**: 2.5%\\n     - **90 Days Late**: 0.5%\\n     - **Never Missed**: 85.0%\\n   - **Average Account Age**: 32 months indicates a relatively mature credit history.\\n   - **Credit Utilization**: 35.5% is within a healthy range (generally below 30% is ideal, but 35.5% is acceptable).\\n\\n3. **Existing Loans**:\\n   - **Total Monthly EMI**: 7700\\n   - **Loan Burden Ratio**: 0.28 (28% of income is used for loan repayments, which is reasonable).\\n   - **Outstanding Loans**: Total outstanding amount is 125,000, with a good repayment track record.\\n\\n### Risk Score Calculation\\n\\nBased on the analysis of the above factors, we can assign a risk score (1-100) where a higher score indicates a higher risk of default:\\n\\n- **CIBIL Score**: 720 (Good) - Low risk contribution: 10 points\\n- **Payment History**: 99% on-time - Very low risk contribution: 5 points\\n- **Credit Mix**: Diverse accounts - Low risk contribution: 5 points\\n- **Repayment Behavior**: 0.0% defaults, 85% never missed - Low risk contribution: 5 points\\n- **Credit Utilization**: 35.5% - Moderate risk contribution: 15 points\\n- **Loan Burden Ratio**: 28% - Moderate risk contribution: 10 points\\n- **Recent Inquiries**: 2 inquiries - Moderate risk contribution: 10 points\\n\\n### Total Risk Score Calculation\\n- **Total Risk Points**: 10 + 5 + 5 + 5 + 15 + 10 + 10 = 60\\n- **Risk Score**: 60 out of 100\\n\\n### Default Risk Assessment\\n- **Overall Risk Profile**: The applicant has a good credit score, excellent payment history, and a reasonable loan burden ratio. However, the credit utilization is slightly above the ideal range, and there are recent inquiries that could indicate a search for additional credit.\\n\\n### Recommendations\\n1. **Maintain Good Payment Behavior**: Continue making timely payments to maintain the high credit score and avoid any late payments.\\n2. **Reduce Credit Utilization**: Aim to lower the credit utilization ratio below 30% by paying down credit card balances.\\n3. **Monitor Loan Burden**: While the current loan burden ratio is acceptable, it is advisable to keep it under review, especially if considering new loans.\\n4. **Limit New Credit Inquiries**: Avoid applying for new credit in the near term to prevent additional inquiries that could impact the credit score.\\n5. **Consider Debt Repayment Strategies**: If possible, prioritize paying off higher-interest loans to reduce overall debt faster.\\n\\n### Conclusion\\nThe applicant exhibits a good credit profile with a moderate risk score of 60. By following the recommendations, the applicant can further improve their creditworthiness and reduce the risk of default.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1769, \"completion_tokens\": 810, \"total_tokens\": 2579, \"estimated_cost\": {\"amount\": 0.000751, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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    "extract_application_info": {
      "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpbzqd7dt4.py\", line 18, in \u003cmodule\u003e\n    \"requested_amount\": UNRESOLVED_loan_amount\n                        ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
      "execution_details": {
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      "output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpbzqd7dt4.py\", line 18, in \u003cmodule\u003e\n    \"requested_amount\": UNRESOLVED_loan_amount\n                        ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
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    "final_underwriting_analysis": {
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      "ai_response": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable due to application decline.\n- **Loan Term**: Not applicable due to application decline.\n- **Repayment Schedule**: Not applicable due to application decline.\n\n#### Risk Mitigation Measures:\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\n\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\n\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\n\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\n\n#### Confidence Level: 95\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.",
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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": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable due to application decline.\n- **Loan Term**: Not applicable due to application decline.\n- **Repayment Schedule**: Not applicable due to application decline.\n\n#### Risk Mitigation Measures:\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\n\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\n\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\n\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\n\n#### Confidence Level: 95\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable due to application decline.\\n- **Loan Term**: Not applicable due to application decline.\\n- **Repayment Schedule**: Not applicable due to application decline.\\n\\n#### Risk Mitigation Measures:\\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\\n\\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\\n\\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\\n\\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\\n\\n#### Confidence Level: 95\\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6019, \"completion_tokens\": 484, \"total_tokens\": 6503, \"estimated_cost\": {\"amount\": 0.001193, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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      "output": "### Final Recommendation: DECLINE\n\n#### Loan Terms and Conditions:\n- **Loan Amount**: Not applicable due to application decline.\n- **Interest Rate**: Not applicable due to application decline.\n- **Loan Term**: Not applicable due to application decline.\n- **Repayment Schedule**: Not applicable due to application decline.\n\n#### Risk Mitigation Measures:\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\n\n#### Reasoning for Decision:\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\n\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\n\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\n\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\n\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\n\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\n\n#### Confidence Level: 95\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\n__OUTPUTS__ {\"ai_response\": \"### Final Recommendation: DECLINE\\n\\n#### Loan Terms and Conditions:\\n- **Loan Amount**: Not applicable due to application decline.\\n- **Interest Rate**: Not applicable due to application decline.\\n- **Loan Term**: Not applicable due to application decline.\\n- **Repayment Schedule**: Not applicable due to application decline.\\n\\n#### Risk Mitigation Measures:\\n- **Documentation Requirement**: The applicant must provide valid identification documents (PAN, Aadhaar, Passport, Address Proof) before any future applications can be considered.\\n- **Debt Management Advice**: If the applicant wishes to reapply in the future, they should be advised to reduce their existing debt levels to improve their debt-to-income ratio.\\n\\n#### Reasoning for Decision:\\n1. **Application Quality**: The application quality score is extremely low at **10 out of 100** due to the inability to extract customer information. This indicates a significant issue with the application process or data entry, making it impossible to assess the applicant\u0027s financial situation or creditworthiness.\\n\\n2. **Document Verification**: All required identification documents failed verification, resulting in a **0% success rate**. The absence of essential identification documents raises high risks for identity verification and fraud, leading to concerns about the applicant\u0027s legitimacy.\\n\\n3. **Income Assessment**: While the applicant has a stable income and demonstrates financial discipline, the high debt-to-income ratio of **80.95%** poses a significant risk for loan repayment. This level of debt servicing capability is concerning, especially given the applicant\u0027s current financial obligations.\\n\\n4. **Credit Profile**: The applicant has a good CIBIL score of **720**, indicating good creditworthiness. However, the overall risk profile is moderated by the high debt-to-income ratio and the recent inquiries for credit, which suggest potential financial strain.\\n\\n5. **Compliance Status**: Although the applicant is compliant with KYC and AML regulations, the lack of valid identification documents and the overall application quality issues overshadow this positive aspect.\\n\\nGiven these factors, the decision to decline the application is based on the critical failures in documentation and the inability to assess the applicant\u0027s financial stability adequately. The applicant should be encouraged to rectify the documentation issues and manage their existing debts before reapplying.\\n\\n#### Confidence Level: 95\\nThis confidence level reflects a strong certainty in the decision due to the clear documentation failures and the high risk associated with the applicant\u0027s current financial situation.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 6019, \"completion_tokens\": 484, \"total_tokens\": 6503, \"estimated_cost\": {\"amount\": 0.001193, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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          "amount": 0.001193,
          "currency": "USD"
        },
        "model": "gpt-4o-mini",
        "prompt_tokens": 6019,
        "provider": "openai",
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      }
    },
    "flag_for_manual_review": {
      "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpnabc2fdg.py\", line 11, in \u003cmodule\u003e\n    \"loan_amount\": UNRESOLVED_loan_amount,\n                   ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\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/tmpnabc2fdg.py\", line 11, in \u003cmodule\u003e\n    \"loan_amount\": UNRESOLVED_loan_amount,\n                   ^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_loan_amount\u0027 is not defined\n",
      "status": "FAILED",
      "task_id": "flag_for_manual_review"
    },
    "generate_final_output": {
      "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmp974inpov.py\", line 16, in \u003cmodule\u003e\n    \"debt_to_income_ratio\": UNRESOLVED_calculate_debt_to_income.debt_to_income_ratio,\n                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_debt_to_income\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/tmp974inpov.py\", line 16, in \u003cmodule\u003e\n    \"debt_to_income_ratio\": UNRESOLVED_calculate_debt_to_income.debt_to_income_ratio,\n                            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_debt_to_income\u0027 is not defined\n",
      "status": "FAILED",
      "task_id": "generate_final_output"
    },
    "income_assessment": {
      "agent_type": "assistant",
      "ai_response": "Based on the comprehensive income data provided, here is a detailed assessment:\n\n```json\n{\n  \"income_stability_assessment\": {\n    \"annual_net_income\": 81600,\n    \"monthly_net_income\": 6800,\n    \"employment_duration\": \"2.5 years\",\n    \"salary_consistency\": true,\n    \"recent_increment\": true,\n    \"stability_score\": 90,\n    \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\"\n  },\n  \"debt_servicing_capability\": {\n    \"monthly_debts\": 5800,\n    \"average_monthly_credits\": 7200,\n    \"debt_to_income_ratio\": 80.95,\n    \"loan_emis_detected\": 2,\n    \"bounced_transactions\": 0,\n    \"comments\": \"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\"\n  },\n  \"financial_discipline_evaluation\": {\n    \"financial_discipline_score\": 85.5,\n    \"account_balance_trend\": \"stable\",\n    \"salary_credits_consistent\": true,\n    \"irregular_transactions\": false,\n    \"comments\": \"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\"\n  },\n  \"risk_factors_and_recommendations\": {\n    \"high_debt_to_income_ratio\": true,\n    \"recommendations\": [\n      \"Consider advising the applicant to reduce existing debt before applying for additional loans.\",\n      \"Monitor future income growth and stability to reassess debt servicing capability.\"\n    ],\n    \"comments\": \"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\"\n  },\n  \"overall_income_adequacy_score\": 75,\n  \"comments\": \"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.",
      "execution_details": {
        "actual_result": {
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            "provider": "openai",
            "system_message": "You are a senior financial analyst specializing in income assessment for loan underwriting.\n\nAnalyze the provided income data and provide:\n1. Income stability assessment\n2. Debt servicing capability\n3. Financial discipline evaluation\n4. Risk factors and recommendations\n5. Overall income adequacy score (1-100)\n\nReturn a detailed JSON assessment.\n"
          },
          "input_format": "json",
          "model_client_id": "underwriting_analyst",
          "output": "Based on the comprehensive income data provided, here is a detailed assessment:\n\n```json\n{\n  \"income_stability_assessment\": {\n    \"annual_net_income\": 81600,\n    \"monthly_net_income\": 6800,\n    \"employment_duration\": \"2.5 years\",\n    \"salary_consistency\": true,\n    \"recent_increment\": true,\n    \"stability_score\": 90,\n    \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\"\n  },\n  \"debt_servicing_capability\": {\n    \"monthly_debts\": 5800,\n    \"average_monthly_credits\": 7200,\n    \"debt_to_income_ratio\": 80.95,\n    \"loan_emis_detected\": 2,\n    \"bounced_transactions\": 0,\n    \"comments\": \"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\"\n  },\n  \"financial_discipline_evaluation\": {\n    \"financial_discipline_score\": 85.5,\n    \"account_balance_trend\": \"stable\",\n    \"salary_credits_consistent\": true,\n    \"irregular_transactions\": false,\n    \"comments\": \"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\"\n  },\n  \"risk_factors_and_recommendations\": {\n    \"high_debt_to_income_ratio\": true,\n    \"recommendations\": [\n      \"Consider advising the applicant to reduce existing debt before applying for additional loans.\",\n      \"Monitor future income growth and stability to reassess debt servicing capability.\"\n    ],\n    \"comments\": \"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\"\n  },\n  \"overall_income_adequacy_score\": 75,\n  \"comments\": \"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment:\\n\\n```json\\n{\\n  \\\"income_stability_assessment\\\": {\\n    \\\"annual_net_income\\\": 81600,\\n    \\\"monthly_net_income\\\": 6800,\\n    \\\"employment_duration\\\": \\\"2.5 years\\\",\\n    \\\"salary_consistency\\\": true,\\n    \\\"recent_increment\\\": true,\\n    \\\"stability_score\\\": 90,\\n    \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\\\"\\n  },\\n  \\\"debt_servicing_capability\\\": {\\n    \\\"monthly_debts\\\": 5800,\\n    \\\"average_monthly_credits\\\": 7200,\\n    \\\"debt_to_income_ratio\\\": 80.95,\\n    \\\"loan_emis_detected\\\": 2,\\n    \\\"bounced_transactions\\\": 0,\\n    \\\"comments\\\": \\\"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\\\"\\n  },\\n  \\\"financial_discipline_evaluation\\\": {\\n    \\\"financial_discipline_score\\\": 85.5,\\n    \\\"account_balance_trend\\\": \\\"stable\\\",\\n    \\\"salary_credits_consistent\\\": true,\\n    \\\"irregular_transactions\\\": false,\\n    \\\"comments\\\": \\\"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\\\"\\n  },\\n  \\\"risk_factors_and_recommendations\\\": {\\n    \\\"high_debt_to_income_ratio\\\": true,\\n    \\\"recommendations\\\": [\\n      \\\"Consider advising the applicant to reduce existing debt before applying for additional loans.\\\",\\n      \\\"Monitor future income growth and stability to reassess debt servicing capability.\\\"\\n    ],\\n    \\\"comments\\\": \\\"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\\\"\\n  },\\n  \\\"overall_income_adequacy_score\\\": 75,\\n  \\\"comments\\\": \\\"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1226, \"completion_tokens\": 589, \"total_tokens\": 1815, \"estimated_cost\": {\"amount\": 0.000537, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
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            "provider": "openai",
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        "duration_seconds": 12.583351,
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      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "Based on the comprehensive income data provided, here is a detailed assessment:\n\n```json\n{\n  \"income_stability_assessment\": {\n    \"annual_net_income\": 81600,\n    \"monthly_net_income\": 6800,\n    \"employment_duration\": \"2.5 years\",\n    \"salary_consistency\": true,\n    \"recent_increment\": true,\n    \"stability_score\": 90,\n    \"comments\": \"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\"\n  },\n  \"debt_servicing_capability\": {\n    \"monthly_debts\": 5800,\n    \"average_monthly_credits\": 7200,\n    \"debt_to_income_ratio\": 80.95,\n    \"loan_emis_detected\": 2,\n    \"bounced_transactions\": 0,\n    \"comments\": \"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\"\n  },\n  \"financial_discipline_evaluation\": {\n    \"financial_discipline_score\": 85.5,\n    \"account_balance_trend\": \"stable\",\n    \"salary_credits_consistent\": true,\n    \"irregular_transactions\": false,\n    \"comments\": \"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\"\n  },\n  \"risk_factors_and_recommendations\": {\n    \"high_debt_to_income_ratio\": true,\n    \"recommendations\": [\n      \"Consider advising the applicant to reduce existing debt before applying for additional loans.\",\n      \"Monitor future income growth and stability to reassess debt servicing capability.\"\n    ],\n    \"comments\": \"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\"\n  },\n  \"overall_income_adequacy_score\": 75,\n  \"comments\": \"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\"\n}\n```\n\n### Summary of the Assessment:\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\n__OUTPUTS__ {\"ai_response\": \"Based on the comprehensive income data provided, here is a detailed assessment:\\n\\n```json\\n{\\n  \\\"income_stability_assessment\\\": {\\n    \\\"annual_net_income\\\": 81600,\\n    \\\"monthly_net_income\\\": 6800,\\n    \\\"employment_duration\\\": \\\"2.5 years\\\",\\n    \\\"salary_consistency\\\": true,\\n    \\\"recent_increment\\\": true,\\n    \\\"stability_score\\\": 90,\\n    \\\"comments\\\": \\\"The applicant has a stable employment history with consistent salary payments and a recent increment, indicating a positive income trajectory.\\\"\\n  },\\n  \\\"debt_servicing_capability\\\": {\\n    \\\"monthly_debts\\\": 5800,\\n    \\\"average_monthly_credits\\\": 7200,\\n    \\\"debt_to_income_ratio\\\": 80.95,\\n    \\\"loan_emis_detected\\\": 2,\\n    \\\"bounced_transactions\\\": 0,\\n    \\\"comments\\\": \\\"The debt-to-income ratio is high at approximately 80.95%, which may indicate potential challenges in servicing additional debt. However, the absence of bounced transactions is a positive sign.\\\"\\n  },\\n  \\\"financial_discipline_evaluation\\\": {\\n    \\\"financial_discipline_score\\\": 85.5,\\n    \\\"account_balance_trend\\\": \\\"stable\\\",\\n    \\\"salary_credits_consistent\\\": true,\\n    \\\"irregular_transactions\\\": false,\\n    \\\"comments\\\": \\\"The applicant demonstrates strong financial discipline with a high score and stable account balance trends. Consistent salary credits further support this evaluation.\\\"\\n  },\\n  \\\"risk_factors_and_recommendations\\\": {\\n    \\\"high_debt_to_income_ratio\\\": true,\\n    \\\"recommendations\\\": [\\n      \\\"Consider advising the applicant to reduce existing debt before applying for additional loans.\\\",\\n      \\\"Monitor future income growth and stability to reassess debt servicing capability.\\\"\\n    ],\\n    \\\"comments\\\": \\\"While the applicant shows strong financial discipline and stability, the high debt-to-income ratio poses a risk for loan repayment.\\\"\\n  },\\n  \\\"overall_income_adequacy_score\\\": 75,\\n  \\\"comments\\\": \\\"The overall income adequacy score reflects a balance between stable income and high debt levels. The applicant is financially disciplined but should address existing debts to improve loan servicing capability.\\\"\\n}\\n```\\n\\n### Summary of the Assessment:\\n1. **Income Stability Assessment**: The applicant has a stable income with a positive growth trend and consistent salary payments.\\n2. **Debt Servicing Capability**: The high debt-to-income ratio indicates potential challenges in servicing additional debt, despite a good income level.\\n3. **Financial Discipline Evaluation**: The applicant shows strong financial discipline with consistent salary credits and no bounced transactions.\\n4. **Risk Factors and Recommendations**: The primary risk is the high debt-to-income ratio. Recommendations include reducing existing debt before applying for new loans.\\n5. **Overall Income Adequacy Score**: The score of 75 reflects a solid income situation but highlights the need for caution regarding debt levels.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\", \"token_usage\": {\"prompt_tokens\": 1226, \"completion_tokens\": 589, \"total_tokens\": 1815, \"estimated_cost\": {\"amount\": 0.000537, \"currency\": \"USD\"}, \"model\": \"gpt-4o-mini\", \"provider\": \"openai\"}}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "income_assessment",
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    },
    "internal_policy_check": {
      "age_criteria_met": true,
      "credit_score_threshold_met": true,
      "employment_criteria_met": true,
      "exceptions_required": [],
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
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        "duration_seconds": 0.235423,
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      },
      "geographic_restrictions_met": true,
      "income_criteria_met": true,
      "loan_amount_within_limits": true,
      "ltv_ratio_acceptable": true,
      "output": "__OUTPUTS__ {\"loan_amount_within_limits\": true, \"ltv_ratio_acceptable\": true, \"income_criteria_met\": true, \"age_criteria_met\": true, \"employment_criteria_met\": true, \"credit_score_threshold_met\": true, \"geographic_restrictions_met\": true, \"policy_compliance_score\": 95.5, \"exceptions_required\": [], \"policy_version\": \"2024.1\"}\n",
      "policy_compliance_score": 95.5,
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      "task_id": "internal_policy_check"
    },
    "kyc_compliance_check": {
      "address_verified": true,
      "compliance_score": 98.5,
      "documents_complete": true,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
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      },
      "identity_verified": true,
      "income_verified": true,
      "kyc_status": "compliant",
      "last_updated": "2024-07-15",
      "output": "__OUTPUTS__ {\"kyc_status\": \"compliant\", \"identity_verified\": true, \"address_verified\": true, \"income_verified\": true, \"documents_complete\": true, \"risk_category\": \"low\", \"compliance_score\": 98.5, \"last_updated\": \"2024-07-15\", \"regulatory_requirements_met\": true}\n",
      "regulatory_requirements_met": true,
      "return_code": 0,
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        "end_time": "2025-07-16T07:39:38.098498",
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      "iterations_completed": 10,
      "loop_result": {
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      "output": "Loop completed after 10 iterations",
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      "stderr": "",
      "task_id": "process_documents_loop"
    },
    "regulatory_compliance": {
      "audit_trail_complete": true,
      "compliance_score": 97.2,
      "consumer_protection_compliant": true,
      "data_privacy_compliant": true,
      "disclosure_requirements_met": true,
      "documentation_complete": true,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
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    "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"
        }
      ],
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      "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\": 0.001272, \"started_at\": \"2025-07-16T07:43:24.932342\", \"ended_at\": \"2025-07-16T07:43:24.933614\"}",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.177649,
        "end_time": "2025-07-16T07:43:25.002344",
        "message_sent": true,
        "start_time": "2025-07-16T07:43:24.824695",
        "timestamp": "2025-07-16T07:43:25.002344",
        "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\": 0.001272, \"started_at\": \"2025-07-16T07:43:24.932342\", \"ended_at\": \"2025-07-16T07:43:24.933614\"}",
      "return_code": 0,
      "route_reason": "no_conditions_matched",
      "router_type": "condition",
      "selected_route": "manual_review_path",
      "started_at": "2025-07-16T07:43:24.932342",
      "status": "completed",
      "stderr": "",
      "task_id": "underwriting_decision_router"
    },
    "upload_to_supabase": {
      "bucket_name": "loan-approval",
      "columns_count": 110,
      "csv_structure": {
        "column_count": 110,
        "columns": [
          "processing_timestamp",
          "workflow_id",
          "workflow_version",
          "application_id",
          "requested_amount",
          "processing_date",
          "workflow_status",
          "customer_id",
          "applicant_name",
          "email",
          "phone",
          "address",
          "employment_status",
          "annual_income",
          "loan_purpose",
          "pan_number",
          "pan_verified",
          "pan_verification_score",
          "pan_name_match",
          "aadhaar_masked",
          "aadhaar_verified",
          "aadhaar_verification_score",
          "aadhaar_address_match",
          "passport_number",
          "passport_verified",
          "passport_verification_score",
          "address_proof_type",
          "address_proof_verified",
          "address_proof_verification_score",
          "total_uploaded_documents",
          "total_processed_documents",
          "documents_successfully_processed",
          "average_ocr_confidence",
          "document_types_found",
          "ocr_extraction_successful",
          "high_confidence_documents",
          "low_confidence_documents",
          "pan_card_ocr_extracted",
          "pan_card_ocr_confidence",
          "aadhaar_ocr_extracted",
          "aadhaar_ocr_confidence",
          "passport_ocr_extracted",
          "passport_ocr_confidence",
          "address_proof_ocr_extracted",
          "address_proof_ocr_confidence",
          "monthly_gross_salary",
          "monthly_net_salary",
          "annual_gross_income",
          "annual_net_income",
          "employer_name",
          "employment_duration",
          "salary_consistency",
          "recent_increment",
          "employment_confirmed",
          "designation",
          "employment_type",
          "job_stability_score",
          "average_monthly_credits",
          "account_balance_trend",
          "minimum_balance",
          "maximum_balance",
          "bounced_transactions",
          "loan_emis_detected",
          "financial_discipline_score",
          "declared_tax_income",
          "tax_paid",
          "tax_compliance_score",
          "debt_to_income_ratio",
          "existing_debt_payments",
          "proposed_emi",
          "total_debt_payments",
          "ratio_acceptable",
          "cibil_score",
          "credit_score_range",
          "credit_history_length",
          "total_accounts",
          "active_accounts",
          "credit_utilization",
          "payment_history",
          "recent_inquiries",
          "internal_credit_score",
          "score_acceptable",
          "risk_category",
          "total_outstanding_loans",
          "number_of_existing_loans",
          "total_monthly_emi",
          "loan_burden_ratio",
          "repayment_track_record",
          "kyc_status",
          "kyc_compliance_score",
          "identity_verified",
          "address_verified",
          "income_verified",
          "documents_complete",
          "aml_status",
          "aml_compliance_score",
          "watchlist_check",
          "pep_screening",
          "sanctions_check",
          "manual_review_required",
          "rbi_guidelines_met",
          "lending_norms_compliant",
          "regulatory_compliance_score",
          "internal_policy_compliance_score",
          "final_decision",
          "decision_confidence",
          "overall_processing_status",
          "processing_time_minutes",
          "processed_by",
          "processing_node"
        ],
        "key_metrics": {
          "aml_cleared": false,
          "avg_ocr_confidence": 0.0,
          "cibil_score": 0,
          "credit_score": 0,
          "documents_processed": 0,
          "documents_uploaded": 0,
          "kyc_compliant": false,
          "ocr_successful": false,
          "ratio_acceptable": false,
          "risk_category": "unknown"
        },
        "row_count": 1
      },
      "data_summary": {
        "applicant_name": "Unknown Applicant",
        "application_id": "UNRESOLVED_application_id",
        "average_ocr_confidence": 0.0,
        "cibil_score": 0,
        "debt_to_income_ratio": 0,
        "final_decision": "PENDING",
        "internal_credit_score": 0,
        "ocr_extraction_successful": false,
        "requested_amount": 0,
        "risk_category": "unknown",
        "total_processed_documents": 0,
        "total_uploaded_documents": 0
      },
      "execution_details": {
        "actual_result": {
          "output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\", \"upload_timestamp\": \"2025-07-16T07:49:36.216631\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 2.533247,
        "end_time": "2025-07-16T07:49:36.484955",
        "message_sent": true,
        "start_time": "2025-07-16T07:49:33.951708",
        "timestamp": "2025-07-16T07:49:36.484955",
        "worker_executed": true,
        "workers_notified": true
      },
      "file_size_bytes": 2803,
      "filename": "loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv",
      "output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\", \"upload_timestamp\": \"2025-07-16T07:49:36.216631\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
      "public_url": "https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?",
      "records_uploaded": 1,
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "upload_to_supabase",
      "upload_status": "success",
      "upload_timestamp": "2025-07-16T07:49:36.216631"
    },
    "validate_application_fields": {
      "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmp_bxzsn2l.py\", line 8, in \u003cmodule\u003e\n    customer_info = UNRESOLVED_extract_application_info.customer_info\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\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_bxzsn2l.py\", line 8, in \u003cmodule\u003e\n    customer_info = UNRESOLVED_extract_application_info.customer_info\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\n",
      "status": "FAILED",
      "task_id": "validate_application_fields"
    },
    "verify_aadhaar": {
      "aadhaar_masked": "N/A",
      "address_match": false,
      "address_on_aadhaar": "N/A",
      "biometric_verified": false,
      "date_of_birth": "N/A",
      "document_found": false,
      "error": "Aadhaar card not found in uploaded documents",
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.48993,
        "end_time": "2025-07-16T07:39:38.698399",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:38.208469",
        "timestamp": "2025-07-16T07:39:38.698399",
        "worker_executed": true,
        "workers_notified": true
      },
      "extracted_from_ocr": false,
      "is_valid": false,
      "last_updated": "N/A",
      "name_on_aadhaar": "N/A",
      "ocr_confidence": 0.0,
      "output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_aadhaar",
      "verification_score": 0.0
    },
    "verify_address_proof": {
      "address_confirmed": "N/A",
      "address_match": false,
      "document_date": "N/A",
      "document_found": false,
      "document_type": "N/A",
      "error": "Address proof document not found in uploaded documents",
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.512685,
        "end_time": "2025-07-16T07:39:38.849059",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:38.336374",
        "timestamp": "2025-07-16T07:39:38.849059",
        "worker_executed": true,
        "workers_notified": true
      },
      "extracted_from_ocr": false,
      "is_valid": false,
      "name_on_document": "N/A",
      "ocr_confidence": 0.0,
      "output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_address_proof",
      "total_address_documents": 0,
      "verification_score": 0.0
    },
    "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": 0.258616,
        "end_time": "2025-07-16T07:39:46.230738",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:45.972122",
        "timestamp": "2025-07-16T07:39:46.230738",
        "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": {
      "document_found": false,
      "error": "PAN card not found in uploaded documents",
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.410378,
        "end_time": "2025-07-16T07:39:38.553840",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:38.143462",
        "timestamp": "2025-07-16T07:39:38.553840",
        "worker_executed": true,
        "workers_notified": true
      },
      "extracted_from_ocr": false,
      "father_name": "N/A",
      "is_valid": false,
      "name_match": false,
      "ocr_confidence": 0.0,
      "output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
      "pan_number": "N/A",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_pan_card",
      "verification_score": 0.0,
      "verified_name": "N/A"
    },
    "verify_passport": {
      "document_found": false,
      "document_provided": false,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.309988,
        "end_time": "2025-07-16T07:39:38.588648",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:38.278660",
        "timestamp": "2025-07-16T07:39:38.588648",
        "worker_executed": true,
        "workers_notified": true
      },
      "expiry_date": "N/A",
      "extracted_from_ocr": false,
      "is_valid": false,
      "issuing_authority": "N/A",
      "name_on_passport": "N/A",
      "note": "Passport not provided - optional document",
      "ocr_confidence": 0.0,
      "output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
      "passport_number": "N/A",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_passport",
      "verification_score": 0.0
    },
    "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": 0.231419,
        "end_time": "2025-07-16T07:39:45.906842",
        "message_sent": true,
        "start_time": "2025-07-16T07:39:45.675423",
        "timestamp": "2025-07-16T07:39:45.906842",
        "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": 0.001272,
    "ended_at": "2025-07-16T07:43:24.933614",
    "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\": 0.001272, \"started_at\": \"2025-07-16T07:43:24.932342\", \"ended_at\": \"2025-07-16T07:43:24.933614\"}",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.177649,
      "end_time": "2025-07-16T07:43:25.002344",
      "message_sent": true,
      "start_time": "2025-07-16T07:43:24.824695",
      "timestamp": "2025-07-16T07:43:25.002344",
      "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\": 0.001272, \"started_at\": \"2025-07-16T07:43:24.932342\", \"ended_at\": \"2025-07-16T07:43:24.933614\"}",
    "return_code": 0,
    "route_reason": "no_conditions_matched",
    "router_type": "condition",
    "selected_route": "manual_review_path",
    "started_at": "2025-07-16T07:43:24.932342",
    "status": "completed",
    "stderr": "",
    "task_id": "underwriting_decision_router"
  },
  "upload_to_supabase": {
    "bucket_name": "loan-approval",
    "columns_count": 110,
    "csv_structure": {
      "column_count": 110,
      "columns": [
        "processing_timestamp",
        "workflow_id",
        "workflow_version",
        "application_id",
        "requested_amount",
        "processing_date",
        "workflow_status",
        "customer_id",
        "applicant_name",
        "email",
        "phone",
        "address",
        "employment_status",
        "annual_income",
        "loan_purpose",
        "pan_number",
        "pan_verified",
        "pan_verification_score",
        "pan_name_match",
        "aadhaar_masked",
        "aadhaar_verified",
        "aadhaar_verification_score",
        "aadhaar_address_match",
        "passport_number",
        "passport_verified",
        "passport_verification_score",
        "address_proof_type",
        "address_proof_verified",
        "address_proof_verification_score",
        "total_uploaded_documents",
        "total_processed_documents",
        "documents_successfully_processed",
        "average_ocr_confidence",
        "document_types_found",
        "ocr_extraction_successful",
        "high_confidence_documents",
        "low_confidence_documents",
        "pan_card_ocr_extracted",
        "pan_card_ocr_confidence",
        "aadhaar_ocr_extracted",
        "aadhaar_ocr_confidence",
        "passport_ocr_extracted",
        "passport_ocr_confidence",
        "address_proof_ocr_extracted",
        "address_proof_ocr_confidence",
        "monthly_gross_salary",
        "monthly_net_salary",
        "annual_gross_income",
        "annual_net_income",
        "employer_name",
        "employment_duration",
        "salary_consistency",
        "recent_increment",
        "employment_confirmed",
        "designation",
        "employment_type",
        "job_stability_score",
        "average_monthly_credits",
        "account_balance_trend",
        "minimum_balance",
        "maximum_balance",
        "bounced_transactions",
        "loan_emis_detected",
        "financial_discipline_score",
        "declared_tax_income",
        "tax_paid",
        "tax_compliance_score",
        "debt_to_income_ratio",
        "existing_debt_payments",
        "proposed_emi",
        "total_debt_payments",
        "ratio_acceptable",
        "cibil_score",
        "credit_score_range",
        "credit_history_length",
        "total_accounts",
        "active_accounts",
        "credit_utilization",
        "payment_history",
        "recent_inquiries",
        "internal_credit_score",
        "score_acceptable",
        "risk_category",
        "total_outstanding_loans",
        "number_of_existing_loans",
        "total_monthly_emi",
        "loan_burden_ratio",
        "repayment_track_record",
        "kyc_status",
        "kyc_compliance_score",
        "identity_verified",
        "address_verified",
        "income_verified",
        "documents_complete",
        "aml_status",
        "aml_compliance_score",
        "watchlist_check",
        "pep_screening",
        "sanctions_check",
        "manual_review_required",
        "rbi_guidelines_met",
        "lending_norms_compliant",
        "regulatory_compliance_score",
        "internal_policy_compliance_score",
        "final_decision",
        "decision_confidence",
        "overall_processing_status",
        "processing_time_minutes",
        "processed_by",
        "processing_node"
      ],
      "key_metrics": {
        "aml_cleared": false,
        "avg_ocr_confidence": 0.0,
        "cibil_score": 0,
        "credit_score": 0,
        "documents_processed": 0,
        "documents_uploaded": 0,
        "kyc_compliant": false,
        "ocr_successful": false,
        "ratio_acceptable": false,
        "risk_category": "unknown"
      },
      "row_count": 1
    },
    "data_summary": {
      "applicant_name": "Unknown Applicant",
      "application_id": "UNRESOLVED_application_id",
      "average_ocr_confidence": 0.0,
      "cibil_score": 0,
      "debt_to_income_ratio": 0,
      "final_decision": "PENDING",
      "internal_credit_score": 0,
      "ocr_extraction_successful": false,
      "requested_amount": 0,
      "risk_category": "unknown",
      "total_processed_documents": 0,
      "total_uploaded_documents": 0
    },
    "execution_details": {
      "actual_result": {
        "output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\", \"upload_timestamp\": \"2025-07-16T07:49:36.216631\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 2.533247,
      "end_time": "2025-07-16T07:49:36.484955",
      "message_sent": true,
      "start_time": "2025-07-16T07:49:33.951708",
      "timestamp": "2025-07-16T07:49:36.484955",
      "worker_executed": true,
      "workers_notified": true
    },
    "file_size_bytes": 2803,
    "filename": "loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv",
    "output": "Error parsing previous node data: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\nGenerated CSV file: loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\nCSV content size: 2803 characters\nData rows: 1\nColumns: 110\nFile uploaded successfully to Supabase\nUpload completed successfully\nPublic URL: https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\nRecords uploaded: 1\n__OUTPUTS__ {\"upload_status\": \"success\", \"bucket_name\": \"loan-approval\", \"filename\": \"loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv\", \"file_size_bytes\": 2803, \"public_url\": \"https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?\", \"upload_timestamp\": \"2025-07-16T07:49:36.216631\", \"records_uploaded\": 1, \"columns_count\": 110, \"data_summary\": {\"application_id\": \"UNRESOLVED_application_id\", \"applicant_name\": \"Unknown Applicant\", \"requested_amount\": 0, \"internal_credit_score\": 0, \"debt_to_income_ratio\": 0, \"final_decision\": \"PENDING\", \"cibil_score\": 0, \"risk_category\": \"unknown\", \"total_uploaded_documents\": 0, \"total_processed_documents\": 0, \"average_ocr_confidence\": 0.0, \"ocr_extraction_successful\": false}, \"csv_structure\": {\"columns\": [\"processing_timestamp\", \"workflow_id\", \"workflow_version\", \"application_id\", \"requested_amount\", \"processing_date\", \"workflow_status\", \"customer_id\", \"applicant_name\", \"email\", \"phone\", \"address\", \"employment_status\", \"annual_income\", \"loan_purpose\", \"pan_number\", \"pan_verified\", \"pan_verification_score\", \"pan_name_match\", \"aadhaar_masked\", \"aadhaar_verified\", \"aadhaar_verification_score\", \"aadhaar_address_match\", \"passport_number\", \"passport_verified\", \"passport_verification_score\", \"address_proof_type\", \"address_proof_verified\", \"address_proof_verification_score\", \"total_uploaded_documents\", \"total_processed_documents\", \"documents_successfully_processed\", \"average_ocr_confidence\", \"document_types_found\", \"ocr_extraction_successful\", \"high_confidence_documents\", \"low_confidence_documents\", \"pan_card_ocr_extracted\", \"pan_card_ocr_confidence\", \"aadhaar_ocr_extracted\", \"aadhaar_ocr_confidence\", \"passport_ocr_extracted\", \"passport_ocr_confidence\", \"address_proof_ocr_extracted\", \"address_proof_ocr_confidence\", \"monthly_gross_salary\", \"monthly_net_salary\", \"annual_gross_income\", \"annual_net_income\", \"employer_name\", \"employment_duration\", \"salary_consistency\", \"recent_increment\", \"employment_confirmed\", \"designation\", \"employment_type\", \"job_stability_score\", \"average_monthly_credits\", \"account_balance_trend\", \"minimum_balance\", \"maximum_balance\", \"bounced_transactions\", \"loan_emis_detected\", \"financial_discipline_score\", \"declared_tax_income\", \"tax_paid\", \"tax_compliance_score\", \"debt_to_income_ratio\", \"existing_debt_payments\", \"proposed_emi\", \"total_debt_payments\", \"ratio_acceptable\", \"cibil_score\", \"credit_score_range\", \"credit_history_length\", \"total_accounts\", \"active_accounts\", \"credit_utilization\", \"payment_history\", \"recent_inquiries\", \"internal_credit_score\", \"score_acceptable\", \"risk_category\", \"total_outstanding_loans\", \"number_of_existing_loans\", \"total_monthly_emi\", \"loan_burden_ratio\", \"repayment_track_record\", \"kyc_status\", \"kyc_compliance_score\", \"identity_verified\", \"address_verified\", \"income_verified\", \"documents_complete\", \"aml_status\", \"aml_compliance_score\", \"watchlist_check\", \"pep_screening\", \"sanctions_check\", \"manual_review_required\", \"rbi_guidelines_met\", \"lending_norms_compliant\", \"regulatory_compliance_score\", \"internal_policy_compliance_score\", \"final_decision\", \"decision_confidence\", \"overall_processing_status\", \"processing_time_minutes\", \"processed_by\", \"processing_node\"], \"column_count\": 110, \"row_count\": 1, \"key_metrics\": {\"credit_score\": 0, \"cibil_score\": 0, \"risk_category\": \"unknown\", \"kyc_compliant\": false, \"aml_cleared\": false, \"ratio_acceptable\": false, \"documents_uploaded\": 0, \"documents_processed\": 0, \"ocr_successful\": false, \"avg_ocr_confidence\": 0.0}}}\n",
    "public_url": "https://mbauzgvitqvxceqanzjw.supabase.co/storage/v1/object/public/loan-approval/loan_underwriting_UNRESOLVED_application_id_20250716_074935.csv?",
    "records_uploaded": 1,
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "upload_to_supabase",
    "upload_status": "success",
    "upload_timestamp": "2025-07-16T07:49:36.216631"
  },
  "validate_application_fields": {
    "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmp_bxzsn2l.py\", line 8, in \u003cmodule\u003e\n    customer_info = UNRESOLVED_extract_application_info.customer_info\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\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_bxzsn2l.py\", line 8, in \u003cmodule\u003e\n    customer_info = UNRESOLVED_extract_application_info.customer_info\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_extract_application_info\u0027 is not defined\n",
    "status": "FAILED",
    "task_id": "validate_application_fields"
  },
  "verify_aadhaar": {
    "aadhaar_masked": "N/A",
    "address_match": false,
    "address_on_aadhaar": "N/A",
    "biometric_verified": false,
    "date_of_birth": "N/A",
    "document_found": false,
    "error": "Aadhaar card not found in uploaded documents",
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.48993,
      "end_time": "2025-07-16T07:39:38.698399",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:38.208469",
      "timestamp": "2025-07-16T07:39:38.698399",
      "worker_executed": true,
      "workers_notified": true
    },
    "extracted_from_ocr": false,
    "is_valid": false,
    "last_updated": "N/A",
    "name_on_aadhaar": "N/A",
    "ocr_confidence": 0.0,
    "output": "__OUTPUTS__ {\"aadhaar_masked\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"biometric_verified\": false, \"verification_score\": 0.0, \"last_updated\": \"N/A\", \"name_on_aadhaar\": \"N/A\", \"address_on_aadhaar\": \"N/A\", \"date_of_birth\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Aadhaar card not found in uploaded documents\"}\n",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_aadhaar",
    "verification_score": 0.0
  },
  "verify_address_proof": {
    "address_confirmed": "N/A",
    "address_match": false,
    "document_date": "N/A",
    "document_found": false,
    "document_type": "N/A",
    "error": "Address proof document not found in uploaded documents",
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.512685,
      "end_time": "2025-07-16T07:39:38.849059",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:38.336374",
      "timestamp": "2025-07-16T07:39:38.849059",
      "worker_executed": true,
      "workers_notified": true
    },
    "extracted_from_ocr": false,
    "is_valid": false,
    "name_on_document": "N/A",
    "ocr_confidence": 0.0,
    "output": "__OUTPUTS__ {\"document_type\": \"N/A\", \"is_valid\": false, \"address_match\": false, \"document_date\": \"N/A\", \"verification_score\": 0.0, \"address_confirmed\": \"N/A\", \"name_on_document\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"Address proof document not found in uploaded documents\", \"total_address_documents\": 0}\n",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_address_proof",
    "total_address_documents": 0,
    "verification_score": 0.0
  },
  "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": 0.258616,
      "end_time": "2025-07-16T07:39:46.230738",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:45.972122",
      "timestamp": "2025-07-16T07:39:46.230738",
      "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": {
    "document_found": false,
    "error": "PAN card not found in uploaded documents",
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.410378,
      "end_time": "2025-07-16T07:39:38.553840",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:38.143462",
      "timestamp": "2025-07-16T07:39:38.553840",
      "worker_executed": true,
      "workers_notified": true
    },
    "extracted_from_ocr": false,
    "father_name": "N/A",
    "is_valid": false,
    "name_match": false,
    "ocr_confidence": 0.0,
    "output": "__OUTPUTS__ {\"pan_number\": \"N/A\", \"is_valid\": false, \"name_match\": false, \"status\": \"not_found\", \"verification_score\": 0.0, \"verified_name\": \"N/A\", \"father_name\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"error\": \"PAN card not found in uploaded documents\"}\n",
    "pan_number": "N/A",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_pan_card",
    "verification_score": 0.0,
    "verified_name": "N/A"
  },
  "verify_passport": {
    "document_found": false,
    "document_provided": false,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.309988,
      "end_time": "2025-07-16T07:39:38.588648",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:38.278660",
      "timestamp": "2025-07-16T07:39:38.588648",
      "worker_executed": true,
      "workers_notified": true
    },
    "expiry_date": "N/A",
    "extracted_from_ocr": false,
    "is_valid": false,
    "issuing_authority": "N/A",
    "name_on_passport": "N/A",
    "note": "Passport not provided - optional document",
    "ocr_confidence": 0.0,
    "output": "__OUTPUTS__ {\"passport_number\": \"N/A\", \"is_valid\": false, \"expiry_date\": \"N/A\", \"issuing_authority\": \"N/A\", \"verification_score\": 0.0, \"document_provided\": false, \"name_on_passport\": \"N/A\", \"ocr_confidence\": 0.0, \"document_found\": false, \"extracted_from_ocr\": false, \"note\": \"Passport not provided - optional document\"}\n",
    "passport_number": "N/A",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_passport",
    "verification_score": 0.0
  },
  "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": 0.231419,
      "end_time": "2025-07-16T07:39:45.906842",
      "message_sent": true,
      "start_time": "2025-07-16T07:39:45.675423",
      "timestamp": "2025-07-16T07:39:45.906842",
      "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
  }
}