Execution Details COMPLETED

Comprehensive Loan Underwriting Workflow

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Execution Information

Execution ID: a838fbbd-490e-4a8b-9559-2feb1628b5e5

Workflow ID: loan_underwriting_workflow

Status: COMPLETED

Started: 2025-07-15 12:34:30

Completed: N/A

Duration:

Quick Actions

View JSON

Execution Inputs

{
  "EXECUTION_ID": "a838fbbd-490e-4a8b-9559-2feb1628b5e5",
  "applicant_data": "{}",
  "application_id": "123",
  "execution_id": "a838fbbd-490e-4a8b-9559-2feb1628b5e5",
  "loan_amount": 100000,
  "max_debt_to_income_ratio": 0.4,
  "min_credit_score": 650,
  "uploaded_documents": "[]"
}

Execution Outputs

Workflow Execution Summary

Mode: Distributed
Tasks: 25/28
Duration: N/A
Dependencies: No

Started: 2025-07-15 12:34:30
Ended: 2025-07-15 12:44:16
Status: FAILED

Task Results & Logs

aml_screening

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:05

verify_aadhaar

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:37

verify_pan_card

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:37

verify_passport

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:37

check_cibil_score

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:51

income_assessment

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:42

verify_employment

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:41

verify_tax_returns

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:41

analyze_salary_slips

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:40

kyc_compliance_check

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:04

verify_address_proof

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:37

assess_existing_loans

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:52

evaluate_default_risk

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:52

generate_final_output

FAILED

Duration: N/A
Dependencies: No

Thread: N/A
Started:

internal_policy_check

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:06

regulatory_compliance

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:05

analyze_credit_history

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:52

calculate_credit_score

FAILED

Duration: N/A
Dependencies: No

Thread: N/A
Started:

flag_for_manual_review

FAILED

Duration: N/A
Dependencies: No

Thread: N/A
Started:

analyze_bank_statements

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:40

calculate_debt_to_income

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:41

compliance_consolidation

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:06

extract_application_info

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:32

application_quality_check

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:32

final_underwriting_analysis

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:11

validate_application_fields

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:32

underwriting_decision_router

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:38:11

consolidate_document_verification

COMPLETED

Duration: Calculating...
Dependencies: No

Thread: N/A
Started: 12:34:38

Complete Execution Output (JSON):

{
  "aml_screening": {
    "adverse_media": "no_hits",
    "aml_status": "cleared",
    "compliance_score": 96.8,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"aml_status\": \"cleared\", \"watchlist_check\": \"no_matches\", \"pep_screening\": \"not_identified\", \"sanctions_check\": \"cleared\", \"adverse_media\": \"no_hits\", \"risk_rating\": \"low\", \"compliance_score\": 96.8, \"screening_date\": \"2024-07-15\", \"manual_review_required\": false}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.469051,
      "end_time": "2025-07-15T12:38:05.784309",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:05.315258",
      "timestamp": "2025-07-15T12:38:05.784309",
      "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": 0.753435,
      "end_time": "2025-07-15T12:34:41.729184",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:40.975749",
      "timestamp": "2025-07-15T12:34:41.729184",
      "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": 0.275186,
      "end_time": "2025-07-15T12:34:52.494558",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:52.219372",
      "timestamp": "2025-07-15T12:34:52.494558",
      "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": 0.424006,
      "end_time": "2025-07-15T12:34:41.358513",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:40.934507",
      "timestamp": "2025-07-15T12:34:41.358513",
      "worker_executed": true,
      "workers_notified": true
    },
    "monthly_gross": 8500,
    "monthly_net": 6800,
    "output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
    "recent_increment": true,
    "return_code": 0,
    "salary_consistency": true,
    "status": "completed",
    "stderr": "",
    "task_id": "analyze_salary_slips"
  },
  "application_quality_check": {
    "agent_type": "assistant",
    "ai_response": "```json\n{\n  \"data_completeness_and_accuracy\": {\n    \"missing_fields\": [],\n    \"validation_passed\": true,\n    \"completion_percentage\": 100.0,\n    \"assessment\": \"The application data is complete with no missing fields, and all provided information has passed validation checks.\"\n  },\n  \"consistency_of_information\": {\n    \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n  },\n  \"red_flags_or_inconsistencies\": {\n    \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\"\n  },\n  \"overall_application_quality_score\": 95,\n  \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\"\n}\n```",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 246,
          "model": "gpt-4o-mini",
          "output_length": 1130,
          "provider": "openai",
          "system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
        },
        "input_format": "json",
        "model_client_id": "underwriting_analyst",
        "output": "```json\n{\n  \"data_completeness_and_accuracy\": {\n    \"missing_fields\": [],\n    \"validation_passed\": true,\n    \"completion_percentage\": 100.0,\n    \"assessment\": \"The application data is complete with no missing fields, and all provided information has passed validation checks.\"\n  },\n  \"consistency_of_information\": {\n    \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n  },\n  \"red_flags_or_inconsistencies\": {\n    \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\"\n  },\n  \"overall_application_quality_score\": 95,\n  \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"data_completeness_and_accuracy\\\": {\\n    \\\"missing_fields\\\": [],\\n    \\\"validation_passed\\\": true,\\n    \\\"completion_percentage\\\": 100.0,\\n    \\\"assessment\\\": \\\"The application data is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n  },\\n  \\\"consistency_of_information\\\": {\\n    \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n  },\\n  \\\"red_flags_or_inconsistencies\\\": {\\n    \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\\\"\\n  },\\n  \\\"overall_application_quality_score\\\": 95,\\n  \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 5.634861,
      "end_time": "2025-07-15T12:34:38.448777",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:32.813916",
      "timestamp": "2025-07-15T12:34:38.448777",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "underwriting_analyst",
    "output": "```json\n{\n  \"data_completeness_and_accuracy\": {\n    \"missing_fields\": [],\n    \"validation_passed\": true,\n    \"completion_percentage\": 100.0,\n    \"assessment\": \"The application data is complete with no missing fields, and all provided information has passed validation checks.\"\n  },\n  \"consistency_of_information\": {\n    \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n  },\n  \"red_flags_or_inconsistencies\": {\n    \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\"\n  },\n  \"overall_application_quality_score\": 95,\n  \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"data_completeness_and_accuracy\\\": {\\n    \\\"missing_fields\\\": [],\\n    \\\"validation_passed\\\": true,\\n    \\\"completion_percentage\\\": 100.0,\\n    \\\"assessment\\\": \\\"The application data is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n  },\\n  \\\"consistency_of_information\\\": {\\n    \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n  },\\n  \\\"red_flags_or_inconsistencies\\\": {\\n    \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\\\"\\n  },\\n  \\\"overall_application_quality_score\\\": 95,\\n  \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "application_quality_check"
  },
  "assess_existing_loans": {
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.276419,
      "end_time": "2025-07-15T12:34:52.800187",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:52.523768",
      "timestamp": "2025-07-15T12:34:52.800187",
      "worker_executed": true,
      "workers_notified": true
    },
    "loan_burden_ratio": 0.28,
    "loan_details": [
      {
        "emi": 3500,
        "outstanding": 45000,
        "remaining_tenure": "18 months",
        "type": "personal_loan"
      },
      {
        "emi": 4200,
        "outstanding": 80000,
        "remaining_tenure": "24 months",
        "type": "auto_loan"
      }
    ],
    "number_of_loans": 2,
    "output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
    "repayment_track_record": "excellent",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "assess_existing_loans",
    "total_monthly_emi": 7700,
    "total_outstanding": 125000
  },
  "calculate_credit_score": {
    "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpzav0jklx.py\", line 9, in \u003cmodule\u003e\n    cibil_score = UNRESOLVED_check_cibil_score.credit_score\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
    "execution_details": {
      "failed": true,
      "message_sent": true,
      "worker_executed": true,
      "workers_notified": true
    },
    "output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpzav0jklx.py\", line 9, in \u003cmodule\u003e\n    cibil_score = UNRESOLVED_check_cibil_score.credit_score\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
    "status": "FAILED",
    "task_id": "calculate_credit_score"
  },
  "calculate_debt_to_income": {
    "debt_to_income_ratio": 0.4142156862745098,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.481118,
      "end_time": "2025-07-15T12:34:42.153491",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:41.672373",
      "timestamp": "2025-07-15T12:34:42.153491",
      "worker_executed": true,
      "workers_notified": true
    },
    "existing_debt_payments": 2400,
    "max_allowed_ratio": 0.4,
    "monthly_net_income": 6800,
    "output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
    "proposed_emi": 416.6666666666667,
    "ratio_acceptable": false,
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "calculate_debt_to_income",
    "total_debt_payments": 2816.6666666666665
  },
  "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": 0.319322,
      "end_time": "2025-07-15T12:34:52.266908",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:51.947586",
      "timestamp": "2025-07-15T12:34:52.266908",
      "worker_executed": true,
      "workers_notified": true
    },
    "last_updated": "2024-06-01",
    "output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
    "payment_history": "99% on-time",
    "recent_inquiries": 2,
    "return_code": 0,
    "score_range": "Good",
    "status": "completed",
    "stderr": "",
    "task_id": "check_cibil_score",
    "total_accounts": 8
  },
  "compliance_consolidation": {
    "agent_type": "assistant",
    "ai_response": "```json\n{\n  \"compliance_assessment\": {\n    \"overall_compliance_status\": \"UNRESOLVED\",\n    \"risk_assessment\": \"High\",\n    \"compliance_gaps_or_concerns\": [\n      {\n        \"issue\": \"KYC Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\"\n      },\n      {\n        \"issue\": \"AML Screening\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\"\n      },\n      {\n        \"issue\": \"Regulatory Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\"\n      }\n    ],\n    \"recommendations_for_proceeding\": [\n      \"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\",\n      \"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\",\n      \"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\",\n      \"Regularly review and update internal policies to align with current regulations and best practices.\"\n    ],\n    \"compliance_confidence_score\": 25\n  }\n}\n```",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 571,
          "model": "gpt-4o-mini",
          "output_length": 1367,
          "provider": "openai",
          "system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
        },
        "input_format": "json",
        "model_client_id": "compliance_reviewer",
        "output": "```json\n{\n  \"compliance_assessment\": {\n    \"overall_compliance_status\": \"UNRESOLVED\",\n    \"risk_assessment\": \"High\",\n    \"compliance_gaps_or_concerns\": [\n      {\n        \"issue\": \"KYC Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\"\n      },\n      {\n        \"issue\": \"AML Screening\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\"\n      },\n      {\n        \"issue\": \"Regulatory Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\"\n      }\n    ],\n    \"recommendations_for_proceeding\": [\n      \"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\",\n      \"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\",\n      \"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\",\n      \"Regularly review and update internal policies to align with current regulations and best practices.\"\n    ],\n    \"compliance_confidence_score\": 25\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"compliance_assessment\\\": {\\n    \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n    \\\"risk_assessment\\\": \\\"High\\\",\\n    \\\"compliance_gaps_or_concerns\\\": [\\n      {\\n        \\\"issue\\\": \\\"KYC Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"AML Screening\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\\\"\\n      }\\n    ],\\n    \\\"recommendations_for_proceeding\\\": [\\n      \\\"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\\\",\\n      \\\"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\\\",\\n      \\\"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\\\",\\n      \\\"Regularly review and update internal policies to align with current regulations and best practices.\\\"\\n    ],\\n    \\\"compliance_confidence_score\\\": 25\\n  }\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 6.38987,
      "end_time": "2025-07-15T12:38:12.677345",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:06.287475",
      "timestamp": "2025-07-15T12:38:12.677345",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "compliance_reviewer",
    "output": "```json\n{\n  \"compliance_assessment\": {\n    \"overall_compliance_status\": \"UNRESOLVED\",\n    \"risk_assessment\": \"High\",\n    \"compliance_gaps_or_concerns\": [\n      {\n        \"issue\": \"KYC Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\"\n      },\n      {\n        \"issue\": \"AML Screening\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\"\n      },\n      {\n        \"issue\": \"Regulatory Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\"\n      }\n    ],\n    \"recommendations_for_proceeding\": [\n      \"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\",\n      \"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\",\n      \"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\",\n      \"Regularly review and update internal policies to align with current regulations and best practices.\"\n    ],\n    \"compliance_confidence_score\": 25\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"compliance_assessment\\\": {\\n    \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n    \\\"risk_assessment\\\": \\\"High\\\",\\n    \\\"compliance_gaps_or_concerns\\\": [\\n      {\\n        \\\"issue\\\": \\\"KYC Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"AML Screening\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\\\"\\n      }\\n    ],\\n    \\\"recommendations_for_proceeding\\\": [\\n      \\\"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\\\",\\n      \\\"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\\\",\\n      \\\"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\\\",\\n      \\\"Regularly review and update internal policies to align with current regulations and best practices.\\\"\\n    ],\\n    \\\"compliance_confidence_score\\\": 25\\n  }\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "compliance_consolidation"
  },
  "consolidate_document_verification": {
    "agent_type": "assistant",
    "ai_response": "```json\n{\n  \"overall_verification_success_rate\": 100,\n  \"consistency_across_documents\": true,\n  \"risk_factors_identified\": [],\n  \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 822,
          "model": "gpt-4o-mini",
          "output_length": 285,
          "provider": "openai",
          "system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
        },
        "input_format": "json",
        "model_client_id": "underwriting_analyst",
        "output": "```json\n{\n  \"overall_verification_success_rate\": 100,\n  \"consistency_across_documents\": true,\n  \"risk_factors_identified\": [],\n  \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"overall_verification_success_rate\\\": 100,\\n  \\\"consistency_across_documents\\\": true,\\n  \\\"risk_factors_identified\\\": [],\\n  \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 3.083139,
      "end_time": "2025-07-15T12:34:41.480689",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:38.397550",
      "timestamp": "2025-07-15T12:34:41.480689",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "underwriting_analyst",
    "output": "```json\n{\n  \"overall_verification_success_rate\": 100,\n  \"consistency_across_documents\": true,\n  \"risk_factors_identified\": [],\n  \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"overall_verification_success_rate\\\": 100,\\n  \\\"consistency_across_documents\\\": true,\\n  \\\"risk_factors_identified\\\": [],\\n  \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "consolidate_document_verification"
  },
  "evaluate_default_risk": {
    "agent_type": "assistant",
    "ai_response": "To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \"excellent.\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nConsidering the factors analyzed:\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (moderate risk)\n\nBased on these factors, we can assign a risk score:\n- Excellent repayment history: 10 points (low risk)\n- Loan burden ratio: 20 points (low risk)\n- Unknown credit score: 40 points (average risk)\n- Overall risk score = 10 + 20 + 40 = 70\n\n### Final Risk Score\n**Risk Score: 70/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\n\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 561,
          "model": "gpt-4o-mini",
          "output_length": 3380,
          "provider": "openai",
          "system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
        },
        "input_format": "json",
        "model_client_id": "risk_assessor",
        "output": "To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \"excellent.\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nConsidering the factors analyzed:\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (moderate risk)\n\nBased on these factors, we can assign a risk score:\n- Excellent repayment history: 10 points (low risk)\n- Loan burden ratio: 20 points (low risk)\n- Unknown credit score: 40 points (average risk)\n- Overall risk score = 10 + 20 + 40 = 70\n\n### Final Risk Score\n**Risk Score: 70/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\n\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \\\"excellent.\\\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nConsidering the factors analyzed:\\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (moderate risk)\\n\\nBased on these factors, we can assign a risk score:\\n- Excellent repayment history: 10 points (low risk)\\n- Loan burden ratio: 20 points (low risk)\\n- Unknown credit score: 40 points (average risk)\\n- Overall risk score = 10 + 20 + 40 = 70\\n\\n### Final Risk Score\\n**Risk Score: 70/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\\n\\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 12.168591,
      "end_time": "2025-07-15T12:35:04.926106",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:52.757515",
      "timestamp": "2025-07-15T12:35:04.926106",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "risk_assessor",
    "output": "To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \"excellent.\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nConsidering the factors analyzed:\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (moderate risk)\n\nBased on these factors, we can assign a risk score:\n- Excellent repayment history: 10 points (low risk)\n- Loan burden ratio: 20 points (low risk)\n- Unknown credit score: 40 points (average risk)\n- Overall risk score = 10 + 20 + 40 = 70\n\n### Final Risk Score\n**Risk Score: 70/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\n\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \\\"excellent.\\\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nConsidering the factors analyzed:\\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (moderate risk)\\n\\nBased on these factors, we can assign a risk score:\\n- Excellent repayment history: 10 points (low risk)\\n- Loan burden ratio: 20 points (low risk)\\n- Unknown credit score: 40 points (average risk)\\n- Overall risk score = 10 + 20 + 40 = 70\\n\\n### Final Risk Score\\n**Risk Score: 70/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\\n\\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "evaluate_default_risk"
  },
  "execution_summary": {
    "completed_tasks": 25,
    "dependencies_detected": false,
    "end_time": "2025-07-15T12:44:16.167076",
    "execution_mode": "distributed",
    "start_time": "2025-07-15T12:34:30.267473",
    "total_tasks": 28
  },
  "extract_application_info": {
    "customer_info": {
      "address": "123 Main St, City, State 12345",
      "annual_income": 75000,
      "customer_id": "CUST_12345",
      "email": "john.doe@email.com",
      "employment_status": "employed",
      "full_name": "John Doe",
      "loan_purpose": "home_purchase",
      "phone": "+1-555-0123",
      "requested_amount": 100000
    },
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 100000}, \"missing_fields\": []}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.243581,
      "end_time": "2025-07-15T12:34:32.524026",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:32.280445",
      "timestamp": "2025-07-15T12:34:32.524026",
      "worker_executed": true,
      "workers_notified": true
    },
    "extraction_success": true,
    "missing_fields": [],
    "output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 100000}, \"missing_fields\": []}\n",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "extract_application_info"
  },
  "final_underwriting_analysis": {
    "agent_type": "assistant",
    "ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\n   \n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\n   \n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n   \n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\n   \n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\n   \n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\n   \n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\n\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 484,
          "model": "gpt-4o-mini",
          "output_length": 2166,
          "provider": "openai",
          "system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
        },
        "input_format": "json",
        "model_client_id": "underwriting_analyst",
        "output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\n   \n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\n   \n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n   \n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\n   \n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\n   \n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\n   \n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\n\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\\n   \\n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\\n   \\n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n   \\n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\\n   \\n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\\n   \\n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\\n   \\n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 7.595531,
      "end_time": "2025-07-15T12:38:19.350027",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:11.754496",
      "timestamp": "2025-07-15T12:38:19.350027",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "underwriting_analyst",
    "output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\n   \n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\n   \n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n   \n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\n   \n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\n   \n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\n   \n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\n\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\\n   \\n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\\n   \\n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n   \\n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\\n   \\n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\\n   \\n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\\n   \\n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "final_underwriting_analysis"
  },
  "flag_for_manual_review": {
    "error": "Unsupported task type: human",
    "execution_details": {
      "failed": true,
      "message_sent": true,
      "worker_executed": true,
      "workers_notified": true
    },
    "output": "Task failed: Unsupported task type: human",
    "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/tmpjtpjfxcd.py\", line 15, in \u003cmodule\u003e\n    \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
    "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/tmpjtpjfxcd.py\", line 15, in \u003cmodule\u003e\n    \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
    "status": "FAILED",
    "task_id": "generate_final_output"
  },
  "income_assessment": {
    "agent_type": "assistant",
    "ai_response": "```json\n{\n  \"income_assessment\": {\n    \"income_stability\": {\n      \"assessment\": \"Stable\",\n      \"details\": {\n        \"employment_type\": \"Permanent\",\n        \"job_stability_score\": 88.5,\n        \"employer_rating\": \"A+\",\n        \"probation_status\": \"Confirmed\",\n        \"employment_verified\": true,\n        \"reference_check_passed\": true\n      }\n    },\n    \"debt_servicing_capability\": {\n      \"assessment\": \"Marginally Acceptable\",\n      \"details\": {\n        \"monthly_net_income\": 6800,\n        \"total_debt_payments\": 2816.67,\n        \"proposed_emi\": 416.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"max_allowed_ratio\": 0.4,\n        \"ratio_acceptable\": false\n      }\n    },\n    \"financial_discipline\": {\n      \"assessment\": \"Moderate\",\n      \"details\": {\n        \"existing_debt_payments\": 2400,\n        \"total_debt_payments\": 2816.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"indication_of_financial_discipline\": \"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\"\n      }\n    },\n    \"risk_factors_and_recommendations\": {\n      \"risk_factors\": [\n        \"Debt-to-income ratio exceeds acceptable limits.\",\n        \"Existing debt payments are high relative to income.\"\n      ],\n      \"recommendations\": [\n        \"Consider reducing existing debt before applying for new loans.\",\n        \"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\",\n        \"Maintain a close watch on monthly expenses to ensure they do not exceed income.\"\n      ]\n    },\n    \"overall_income_adequacy_score\": 65\n  }\n}\n```",
    "execution_details": {
      "actual_result": {
        "agent_type": "assistant",
        "execution_details": {
          "agent_type": "assistant",
          "input_length": 782,
          "model": "gpt-4o-mini",
          "output_length": 1598,
          "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": "```json\n{\n  \"income_assessment\": {\n    \"income_stability\": {\n      \"assessment\": \"Stable\",\n      \"details\": {\n        \"employment_type\": \"Permanent\",\n        \"job_stability_score\": 88.5,\n        \"employer_rating\": \"A+\",\n        \"probation_status\": \"Confirmed\",\n        \"employment_verified\": true,\n        \"reference_check_passed\": true\n      }\n    },\n    \"debt_servicing_capability\": {\n      \"assessment\": \"Marginally Acceptable\",\n      \"details\": {\n        \"monthly_net_income\": 6800,\n        \"total_debt_payments\": 2816.67,\n        \"proposed_emi\": 416.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"max_allowed_ratio\": 0.4,\n        \"ratio_acceptable\": false\n      }\n    },\n    \"financial_discipline\": {\n      \"assessment\": \"Moderate\",\n      \"details\": {\n        \"existing_debt_payments\": 2400,\n        \"total_debt_payments\": 2816.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"indication_of_financial_discipline\": \"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\"\n      }\n    },\n    \"risk_factors_and_recommendations\": {\n      \"risk_factors\": [\n        \"Debt-to-income ratio exceeds acceptable limits.\",\n        \"Existing debt payments are high relative to income.\"\n      ],\n      \"recommendations\": [\n        \"Consider reducing existing debt before applying for new loans.\",\n        \"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\",\n        \"Maintain a close watch on monthly expenses to ensure they do not exceed income.\"\n      ]\n    },\n    \"overall_income_adequacy_score\": 65\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"income_assessment\\\": {\\n    \\\"income_stability\\\": {\\n      \\\"assessment\\\": \\\"Stable\\\",\\n      \\\"details\\\": {\\n        \\\"employment_type\\\": \\\"Permanent\\\",\\n        \\\"job_stability_score\\\": 88.5,\\n        \\\"employer_rating\\\": \\\"A+\\\",\\n        \\\"probation_status\\\": \\\"Confirmed\\\",\\n        \\\"employment_verified\\\": true,\\n        \\\"reference_check_passed\\\": true\\n      }\\n    },\\n    \\\"debt_servicing_capability\\\": {\\n      \\\"assessment\\\": \\\"Marginally Acceptable\\\",\\n      \\\"details\\\": {\\n        \\\"monthly_net_income\\\": 6800,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"proposed_emi\\\": 416.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"max_allowed_ratio\\\": 0.4,\\n        \\\"ratio_acceptable\\\": false\\n      }\\n    },\\n    \\\"financial_discipline\\\": {\\n      \\\"assessment\\\": \\\"Moderate\\\",\\n      \\\"details\\\": {\\n        \\\"existing_debt_payments\\\": 2400,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"indication_of_financial_discipline\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\\\"\\n      }\\n    },\\n    \\\"risk_factors_and_recommendations\\\": {\\n      \\\"risk_factors\\\": [\\n        \\\"Debt-to-income ratio exceeds acceptable limits.\\\",\\n        \\\"Existing debt payments are high relative to income.\\\"\\n      ],\\n      \\\"recommendations\\\": [\\n        \\\"Consider reducing existing debt before applying for new loans.\\\",\\n        \\\"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\\\",\\n        \\\"Maintain a close watch on monthly expenses to ensure they do not exceed income.\\\"\\n      ]\\n    },\\n    \\\"overall_income_adequacy_score\\\": 65\\n  }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
        "output_format": "json",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 9.943372,
      "end_time": "2025-07-15T12:34:51.990866",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:42.047494",
      "timestamp": "2025-07-15T12:34:51.990866",
      "worker_executed": true,
      "workers_notified": true
    },
    "model": "gpt-4o-mini",
    "model_client_id": "underwriting_analyst",
    "output": "```json\n{\n  \"income_assessment\": {\n    \"income_stability\": {\n      \"assessment\": \"Stable\",\n      \"details\": {\n        \"employment_type\": \"Permanent\",\n        \"job_stability_score\": 88.5,\n        \"employer_rating\": \"A+\",\n        \"probation_status\": \"Confirmed\",\n        \"employment_verified\": true,\n        \"reference_check_passed\": true\n      }\n    },\n    \"debt_servicing_capability\": {\n      \"assessment\": \"Marginally Acceptable\",\n      \"details\": {\n        \"monthly_net_income\": 6800,\n        \"total_debt_payments\": 2816.67,\n        \"proposed_emi\": 416.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"max_allowed_ratio\": 0.4,\n        \"ratio_acceptable\": false\n      }\n    },\n    \"financial_discipline\": {\n      \"assessment\": \"Moderate\",\n      \"details\": {\n        \"existing_debt_payments\": 2400,\n        \"total_debt_payments\": 2816.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"indication_of_financial_discipline\": \"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\"\n      }\n    },\n    \"risk_factors_and_recommendations\": {\n      \"risk_factors\": [\n        \"Debt-to-income ratio exceeds acceptable limits.\",\n        \"Existing debt payments are high relative to income.\"\n      ],\n      \"recommendations\": [\n        \"Consider reducing existing debt before applying for new loans.\",\n        \"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\",\n        \"Maintain a close watch on monthly expenses to ensure they do not exceed income.\"\n      ]\n    },\n    \"overall_income_adequacy_score\": 65\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"income_assessment\\\": {\\n    \\\"income_stability\\\": {\\n      \\\"assessment\\\": \\\"Stable\\\",\\n      \\\"details\\\": {\\n        \\\"employment_type\\\": \\\"Permanent\\\",\\n        \\\"job_stability_score\\\": 88.5,\\n        \\\"employer_rating\\\": \\\"A+\\\",\\n        \\\"probation_status\\\": \\\"Confirmed\\\",\\n        \\\"employment_verified\\\": true,\\n        \\\"reference_check_passed\\\": true\\n      }\\n    },\\n    \\\"debt_servicing_capability\\\": {\\n      \\\"assessment\\\": \\\"Marginally Acceptable\\\",\\n      \\\"details\\\": {\\n        \\\"monthly_net_income\\\": 6800,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"proposed_emi\\\": 416.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"max_allowed_ratio\\\": 0.4,\\n        \\\"ratio_acceptable\\\": false\\n      }\\n    },\\n    \\\"financial_discipline\\\": {\\n      \\\"assessment\\\": \\\"Moderate\\\",\\n      \\\"details\\\": {\\n        \\\"existing_debt_payments\\\": 2400,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"indication_of_financial_discipline\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\\\"\\n      }\\n    },\\n    \\\"risk_factors_and_recommendations\\\": {\\n      \\\"risk_factors\\\": [\\n        \\\"Debt-to-income ratio exceeds acceptable limits.\\\",\\n        \\\"Existing debt payments are high relative to income.\\\"\\n      ],\\n      \\\"recommendations\\\": [\\n        \\\"Consider reducing existing debt before applying for new loans.\\\",\\n        \\\"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\\\",\\n        \\\"Maintain a close watch on monthly expenses to ensure they do not exceed income.\\\"\\n      ]\\n    },\\n    \\\"overall_income_adequacy_score\\\": 65\\n  }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
    "provider": "openai",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "income_assessment"
  },
  "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": ""
      },
      "duration_seconds": 0.311171,
      "end_time": "2025-07-15T12:38:06.345673",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:06.034502",
      "timestamp": "2025-07-15T12:38:06.345673",
      "worker_executed": true,
      "workers_notified": true
    },
    "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,
    "policy_version": "2024.1",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "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",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.864319,
      "end_time": "2025-07-15T12:38:05.231378",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:04.367059",
      "timestamp": "2025-07-15T12:38:05.231378",
      "worker_executed": true,
      "workers_notified": true
    },
    "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,
    "risk_category": "low",
    "status": "completed",
    "stderr": "",
    "task_id": "kyc_compliance_check"
  },
  "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",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.324695,
      "end_time": "2025-07-15T12:38:06.135232",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:05.810537",
      "timestamp": "2025-07-15T12:38:06.135232",
      "worker_executed": true,
      "workers_notified": true
    },
    "lending_norms_compliant": true,
    "output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
    "rbi_guidelines_met": true,
    "regulatory_risk": "minimal",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "regulatory_compliance"
  },
  "status": "FAILED",
  "task_outputs": {
    "aml_screening": {
      "adverse_media": "no_hits",
      "aml_status": "cleared",
      "compliance_score": 96.8,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"aml_status\": \"cleared\", \"watchlist_check\": \"no_matches\", \"pep_screening\": \"not_identified\", \"sanctions_check\": \"cleared\", \"adverse_media\": \"no_hits\", \"risk_rating\": \"low\", \"compliance_score\": 96.8, \"screening_date\": \"2024-07-15\", \"manual_review_required\": false}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.469051,
        "end_time": "2025-07-15T12:38:05.784309",
        "message_sent": true,
        "start_time": "2025-07-15T12:38:05.315258",
        "timestamp": "2025-07-15T12:38:05.784309",
        "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": 0.753435,
        "end_time": "2025-07-15T12:34:41.729184",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:40.975749",
        "timestamp": "2025-07-15T12:34:41.729184",
        "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": 0.275186,
        "end_time": "2025-07-15T12:34:52.494558",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:52.219372",
        "timestamp": "2025-07-15T12:34:52.494558",
        "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": 0.424006,
        "end_time": "2025-07-15T12:34:41.358513",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:40.934507",
        "timestamp": "2025-07-15T12:34:41.358513",
        "worker_executed": true,
        "workers_notified": true
      },
      "monthly_gross": 8500,
      "monthly_net": 6800,
      "output": "__OUTPUTS__ {\"monthly_gross\": 8500, \"monthly_net\": 6800, \"annual_gross\": 102000, \"annual_net\": 81600, \"employer\": \"Tech Corp Ltd\", \"employment_duration\": \"2.5 years\", \"salary_consistency\": true, \"recent_increment\": true, \"deductions\": {\"tax\": 1200, \"pf\": 500, \"insurance\": 300}}\n",
      "recent_increment": true,
      "return_code": 0,
      "salary_consistency": true,
      "status": "completed",
      "stderr": "",
      "task_id": "analyze_salary_slips"
    },
    "application_quality_check": {
      "agent_type": "assistant",
      "ai_response": "```json\n{\n  \"data_completeness_and_accuracy\": {\n    \"missing_fields\": [],\n    \"validation_passed\": true,\n    \"completion_percentage\": 100.0,\n    \"assessment\": \"The application data is complete with no missing fields, and all provided information has passed validation checks.\"\n  },\n  \"consistency_of_information\": {\n    \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n  },\n  \"red_flags_or_inconsistencies\": {\n    \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\"\n  },\n  \"overall_application_quality_score\": 95,\n  \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\"\n}\n```",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 246,
            "model": "gpt-4o-mini",
            "output_length": 1130,
            "provider": "openai",
            "system_message": "You are an expert loan underwriting analyst. Review the application data and assess its quality.\n\nEvaluate:\n1. Data completeness and accuracy\n2. Consistency of information\n3. Red flags or inconsistencies\n4. Overall application quality score (1-100)\n\nReturn a JSON response with your assessment.\n"
          },
          "input_format": "json",
          "model_client_id": "underwriting_analyst",
          "output": "```json\n{\n  \"data_completeness_and_accuracy\": {\n    \"missing_fields\": [],\n    \"validation_passed\": true,\n    \"completion_percentage\": 100.0,\n    \"assessment\": \"The application data is complete with no missing fields, and all provided information has passed validation checks.\"\n  },\n  \"consistency_of_information\": {\n    \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n  },\n  \"red_flags_or_inconsistencies\": {\n    \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\"\n  },\n  \"overall_application_quality_score\": 95,\n  \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"data_completeness_and_accuracy\\\": {\\n    \\\"missing_fields\\\": [],\\n    \\\"validation_passed\\\": true,\\n    \\\"completion_percentage\\\": 100.0,\\n    \\\"assessment\\\": \\\"The application data is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n  },\\n  \\\"consistency_of_information\\\": {\\n    \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n  },\\n  \\\"red_flags_or_inconsistencies\\\": {\\n    \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\\\"\\n  },\\n  \\\"overall_application_quality_score\\\": 95,\\n  \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 5.634861,
        "end_time": "2025-07-15T12:34:38.448777",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:32.813916",
        "timestamp": "2025-07-15T12:34:38.448777",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "```json\n{\n  \"data_completeness_and_accuracy\": {\n    \"missing_fields\": [],\n    \"validation_passed\": true,\n    \"completion_percentage\": 100.0,\n    \"assessment\": \"The application data is complete with no missing fields, and all provided information has passed validation checks.\"\n  },\n  \"consistency_of_information\": {\n    \"assessment\": \"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\"\n  },\n  \"red_flags_or_inconsistencies\": {\n    \"assessment\": \"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\"\n  },\n  \"overall_application_quality_score\": 95,\n  \"overall_assessment\": \"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"data_completeness_and_accuracy\\\": {\\n    \\\"missing_fields\\\": [],\\n    \\\"validation_passed\\\": true,\\n    \\\"completion_percentage\\\": 100.0,\\n    \\\"assessment\\\": \\\"The application data is complete with no missing fields, and all provided information has passed validation checks.\\\"\\n  },\\n  \\\"consistency_of_information\\\": {\\n    \\\"assessment\\\": \\\"Since there are no missing fields and the validation has passed, the information appears to be consistent. However, further details on the specific data points would be needed for a deeper consistency check.\\\"\\n  },\\n  \\\"red_flags_or_inconsistencies\\\": {\\n    \\\"assessment\\\": \\\"No red flags or inconsistencies have been identified based on the provided validation results. However, without specific customer information, a thorough review for potential red flags cannot be conducted.\\\"\\n  },\\n  \\\"overall_application_quality_score\\\": 95,\\n  \\\"overall_assessment\\\": \\\"The application is of high quality due to its completeness and successful validation. A score of 95 reflects the strong quality, but further details on the actual customer information would be necessary for a more comprehensive evaluation.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "application_quality_check"
    },
    "assess_existing_loans": {
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.276419,
        "end_time": "2025-07-15T12:34:52.800187",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:52.523768",
        "timestamp": "2025-07-15T12:34:52.800187",
        "worker_executed": true,
        "workers_notified": true
      },
      "loan_burden_ratio": 0.28,
      "loan_details": [
        {
          "emi": 3500,
          "outstanding": 45000,
          "remaining_tenure": "18 months",
          "type": "personal_loan"
        },
        {
          "emi": 4200,
          "outstanding": 80000,
          "remaining_tenure": "24 months",
          "type": "auto_loan"
        }
      ],
      "number_of_loans": 2,
      "output": "__OUTPUTS__ {\"total_outstanding\": 125000, \"number_of_loans\": 2, \"loan_details\": [{\"type\": \"personal_loan\", \"outstanding\": 45000, \"emi\": 3500, \"remaining_tenure\": \"18 months\"}, {\"type\": \"auto_loan\", \"outstanding\": 80000, \"emi\": 4200, \"remaining_tenure\": \"24 months\"}], \"total_monthly_emi\": 7700, \"repayment_track_record\": \"excellent\", \"loan_burden_ratio\": 0.28}\n",
      "repayment_track_record": "excellent",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "assess_existing_loans",
      "total_monthly_emi": 7700,
      "total_outstanding": 125000
    },
    "calculate_credit_score": {
      "error": "Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpzav0jklx.py\", line 9, in \u003cmodule\u003e\n    cibil_score = UNRESOLVED_check_cibil_score.credit_score\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
      "execution_details": {
        "failed": true,
        "message_sent": true,
        "worker_executed": true,
        "workers_notified": true
      },
      "output": "Task failed: Python script failed with return code 1: Traceback (most recent call last):\n  File \"/tmp/tmpzav0jklx.py\", line 9, in \u003cmodule\u003e\n    cibil_score = UNRESOLVED_check_cibil_score.credit_score\n                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_check_cibil_score\u0027 is not defined\n",
      "status": "FAILED",
      "task_id": "calculate_credit_score"
    },
    "calculate_debt_to_income": {
      "debt_to_income_ratio": 0.4142156862745098,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.481118,
        "end_time": "2025-07-15T12:34:42.153491",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:41.672373",
        "timestamp": "2025-07-15T12:34:42.153491",
        "worker_executed": true,
        "workers_notified": true
      },
      "existing_debt_payments": 2400,
      "max_allowed_ratio": 0.4,
      "monthly_net_income": 6800,
      "output": "__OUTPUTS__ {\"monthly_net_income\": 6800, \"existing_debt_payments\": 2400, \"proposed_emi\": 416.6666666666667, \"total_debt_payments\": 2816.6666666666665, \"debt_to_income_ratio\": 0.4142156862745098, \"ratio_acceptable\": false, \"max_allowed_ratio\": 0.4}\n",
      "proposed_emi": 416.6666666666667,
      "ratio_acceptable": false,
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "calculate_debt_to_income",
      "total_debt_payments": 2816.6666666666665
    },
    "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": 0.319322,
        "end_time": "2025-07-15T12:34:52.266908",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:51.947586",
        "timestamp": "2025-07-15T12:34:52.266908",
        "worker_executed": true,
        "workers_notified": true
      },
      "last_updated": "2024-06-01",
      "output": "__OUTPUTS__ {\"credit_score\": 720, \"score_range\": \"Good\", \"last_updated\": \"2024-06-01\", \"credit_history_length\": \"5 years\", \"total_accounts\": 8, \"active_accounts\": 6, \"closed_accounts\": 2, \"credit_utilization\": 35.5, \"payment_history\": \"99% on-time\", \"recent_inquiries\": 2}\n",
      "payment_history": "99% on-time",
      "recent_inquiries": 2,
      "return_code": 0,
      "score_range": "Good",
      "status": "completed",
      "stderr": "",
      "task_id": "check_cibil_score",
      "total_accounts": 8
    },
    "compliance_consolidation": {
      "agent_type": "assistant",
      "ai_response": "```json\n{\n  \"compliance_assessment\": {\n    \"overall_compliance_status\": \"UNRESOLVED\",\n    \"risk_assessment\": \"High\",\n    \"compliance_gaps_or_concerns\": [\n      {\n        \"issue\": \"KYC Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\"\n      },\n      {\n        \"issue\": \"AML Screening\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\"\n      },\n      {\n        \"issue\": \"Regulatory Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\"\n      }\n    ],\n    \"recommendations_for_proceeding\": [\n      \"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\",\n      \"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\",\n      \"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\",\n      \"Regularly review and update internal policies to align with current regulations and best practices.\"\n    ],\n    \"compliance_confidence_score\": 25\n  }\n}\n```",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 571,
            "model": "gpt-4o-mini",
            "output_length": 1367,
            "provider": "openai",
            "system_message": "You are a compliance officer specializing in loan underwriting compliance.\n\nReview all compliance check results and provide:\n1. Overall compliance status\n2. Risk assessment\n3. Any compliance gaps or concerns\n4. Recommendations for proceeding\n5. Compliance confidence score (1-100)\n\nReturn a comprehensive compliance assessment in JSON format.\n"
          },
          "input_format": "json",
          "model_client_id": "compliance_reviewer",
          "output": "```json\n{\n  \"compliance_assessment\": {\n    \"overall_compliance_status\": \"UNRESOLVED\",\n    \"risk_assessment\": \"High\",\n    \"compliance_gaps_or_concerns\": [\n      {\n        \"issue\": \"KYC Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\"\n      },\n      {\n        \"issue\": \"AML Screening\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\"\n      },\n      {\n        \"issue\": \"Regulatory Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\"\n      }\n    ],\n    \"recommendations_for_proceeding\": [\n      \"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\",\n      \"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\",\n      \"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\",\n      \"Regularly review and update internal policies to align with current regulations and best practices.\"\n    ],\n    \"compliance_confidence_score\": 25\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"compliance_assessment\\\": {\\n    \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n    \\\"risk_assessment\\\": \\\"High\\\",\\n    \\\"compliance_gaps_or_concerns\\\": [\\n      {\\n        \\\"issue\\\": \\\"KYC Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"AML Screening\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\\\"\\n      }\\n    ],\\n    \\\"recommendations_for_proceeding\\\": [\\n      \\\"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\\\",\\n      \\\"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\\\",\\n      \\\"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\\\",\\n      \\\"Regularly review and update internal policies to align with current regulations and best practices.\\\"\\n    ],\\n    \\\"compliance_confidence_score\\\": 25\\n  }\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 6.38987,
        "end_time": "2025-07-15T12:38:12.677345",
        "message_sent": true,
        "start_time": "2025-07-15T12:38:06.287475",
        "timestamp": "2025-07-15T12:38:12.677345",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "compliance_reviewer",
      "output": "```json\n{\n  \"compliance_assessment\": {\n    \"overall_compliance_status\": \"UNRESOLVED\",\n    \"risk_assessment\": \"High\",\n    \"compliance_gaps_or_concerns\": [\n      {\n        \"issue\": \"KYC Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\"\n      },\n      {\n        \"issue\": \"AML Screening\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\"\n      },\n      {\n        \"issue\": \"Regulatory Compliance\",\n        \"status\": \"UNRESOLVED\",\n        \"description\": \"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\"\n      }\n    ],\n    \"recommendations_for_proceeding\": [\n      \"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\",\n      \"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\",\n      \"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\",\n      \"Regularly review and update internal policies to align with current regulations and best practices.\"\n    ],\n    \"compliance_confidence_score\": 25\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"compliance_assessment\\\": {\\n    \\\"overall_compliance_status\\\": \\\"UNRESOLVED\\\",\\n    \\\"risk_assessment\\\": \\\"High\\\",\\n    \\\"compliance_gaps_or_concerns\\\": [\\n      {\\n        \\\"issue\\\": \\\"KYC Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Know Your Customer compliance checks have not been resolved, indicating potential risks in customer identification and verification.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"AML Screening\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Anti-Money Laundering screening has not been resolved, posing risks of financial crime and regulatory penalties.\\\"\\n      },\\n      {\\n        \\\"issue\\\": \\\"Regulatory Compliance\\\",\\n        \\\"status\\\": \\\"UNRESOLVED\\\",\\n        \\\"description\\\": \\\"Regulatory compliance checks are unresolved, which may lead to violations of applicable laws and regulations.\\\"\\n      }\\n    ],\\n    \\\"recommendations_for_proceeding\\\": [\\n      \\\"Prioritize resolving KYC compliance issues by conducting thorough customer verification.\\\",\\n      \\\"Address AML screening concerns by implementing robust monitoring and reporting mechanisms.\\\",\\n      \\\"Ensure all regulatory compliance checks are completed and documented to avoid potential legal repercussions.\\\",\\n      \\\"Regularly review and update internal policies to align with current regulations and best practices.\\\"\\n    ],\\n    \\\"compliance_confidence_score\\\": 25\\n  }\\n}\\n```\", \"model_client_id\": \"compliance_reviewer\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "compliance_consolidation"
    },
    "consolidate_document_verification": {
      "agent_type": "assistant",
      "ai_response": "```json\n{\n  \"overall_verification_success_rate\": 100,\n  \"consistency_across_documents\": true,\n  \"risk_factors_identified\": [],\n  \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 822,
            "model": "gpt-4o-mini",
            "output_length": 285,
            "provider": "openai",
            "system_message": "You are a document verification specialist. Analyze all document verification results and provide a comprehensive assessment.\n\nConsider:\n1. Overall verification success rate\n2. Consistency across documents\n3. Risk factors identified\n4. Recommendation for proceeding\n\nReturn a JSON response with your analysis.\n"
          },
          "input_format": "json",
          "model_client_id": "underwriting_analyst",
          "output": "```json\n{\n  \"overall_verification_success_rate\": 100,\n  \"consistency_across_documents\": true,\n  \"risk_factors_identified\": [],\n  \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"overall_verification_success_rate\\\": 100,\\n  \\\"consistency_across_documents\\\": true,\\n  \\\"risk_factors_identified\\\": [],\\n  \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 3.083139,
        "end_time": "2025-07-15T12:34:41.480689",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:38.397550",
        "timestamp": "2025-07-15T12:34:41.480689",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "```json\n{\n  \"overall_verification_success_rate\": 100,\n  \"consistency_across_documents\": true,\n  \"risk_factors_identified\": [],\n  \"recommendation_for_proceeding\": \"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\"\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"overall_verification_success_rate\\\": 100,\\n  \\\"consistency_across_documents\\\": true,\\n  \\\"risk_factors_identified\\\": [],\\n  \\\"recommendation_for_proceeding\\\": \\\"All documents have been successfully verified with high scores and consistent information. Proceed with confidence.\\\"\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "consolidate_document_verification"
    },
    "evaluate_default_risk": {
      "agent_type": "assistant",
      "ai_response": "To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \"excellent.\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nConsidering the factors analyzed:\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (moderate risk)\n\nBased on these factors, we can assign a risk score:\n- Excellent repayment history: 10 points (low risk)\n- Loan burden ratio: 20 points (low risk)\n- Unknown credit score: 40 points (average risk)\n- Overall risk score = 10 + 20 + 40 = 70\n\n### Final Risk Score\n**Risk Score: 70/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\n\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 561,
            "model": "gpt-4o-mini",
            "output_length": 3380,
            "provider": "openai",
            "system_message": "You are a credit risk assessment specialist. Analyze the provided credit data and calculate default risk.\n\nConsider:\n1. Credit score and history\n2. Repayment patterns\n3. Credit utilization\n4. Existing loan burden\n5. Overall risk profile\n\nProvide a risk score (1-100, where 100 is highest risk) and detailed risk analysis.\n"
          },
          "input_format": "json",
          "model_client_id": "risk_assessor",
          "output": "To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \"excellent.\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nConsidering the factors analyzed:\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (moderate risk)\n\nBased on these factors, we can assign a risk score:\n- Excellent repayment history: 10 points (low risk)\n- Loan burden ratio: 20 points (low risk)\n- Unknown credit score: 40 points (average risk)\n- Overall risk score = 10 + 20 + 40 = 70\n\n### Final Risk Score\n**Risk Score: 70/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\n\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \\\"excellent.\\\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nConsidering the factors analyzed:\\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (moderate risk)\\n\\nBased on these factors, we can assign a risk score:\\n- Excellent repayment history: 10 points (low risk)\\n- Loan burden ratio: 20 points (low risk)\\n- Unknown credit score: 40 points (average risk)\\n- Overall risk score = 10 + 20 + 40 = 70\\n\\n### Final Risk Score\\n**Risk Score: 70/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\\n\\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 12.168591,
        "end_time": "2025-07-15T12:35:04.926106",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:52.757515",
        "timestamp": "2025-07-15T12:35:04.926106",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "risk_assessor",
      "output": "To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\n\n### 1. Credit Score and History\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \"excellent.\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\n\n### 2. Repayment Patterns\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\n\n### 3. Credit Utilization\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\n\n### 4. Existing Loan Burden\n- **Total Monthly EMI**: 7700\n- **Total Outstanding Loans**: 125000\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\n\n### 5. Overall Risk Profile\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\n\n### Risk Score Calculation\nConsidering the factors analyzed:\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\n- **Repayment Patterns**: Excellent (low risk)\n- **Credit Utilization**: 28% (low risk)\n- **Existing Loan Burden**: Manageable (moderate risk)\n\nBased on these factors, we can assign a risk score:\n- Excellent repayment history: 10 points (low risk)\n- Loan burden ratio: 20 points (low risk)\n- Unknown credit score: 40 points (average risk)\n- Overall risk score = 10 + 20 + 40 = 70\n\n### Final Risk Score\n**Risk Score: 70/100** (where 100 is the highest risk)\n\n### Recommendations\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\n\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\n__OUTPUTS__ {\"ai_response\": \"To analyze the provided credit data and calculate the default risk, we will evaluate the key components mentioned: credit score and history, repayment patterns, credit utilization, existing loan burden, and overall risk profile.\\n\\n### 1. Credit Score and History\\n- **CIBIL Score**: The score is unresolved, which means we cannot assess the risk based on this crucial metric. A low score typically indicates higher risk, while a high score suggests lower risk.\\n- **Credit History**: The history is also unresolved, but we note that the repayment track record is described as \\\"excellent.\\\" This suggests that the individual has consistently made payments on time, which is a positive indicator.\\n\\n### 2. Repayment Patterns\\n- **Repayment Track Record**: The individual has an excellent repayment track record. This indicates reliability in meeting payment obligations, which reduces default risk.\\n\\n### 3. Credit Utilization\\n- **Loan Burden Ratio**: The loan burden ratio is 0.28 (28%). This is calculated as the total monthly EMI divided by the total monthly income (assuming total monthly income is not provided, we can infer that a lower ratio indicates a manageable debt load). A ratio below 30% is generally considered acceptable, indicating that the individual is not over-leveraged.\\n\\n### 4. Existing Loan Burden\\n- **Total Monthly EMI**: 7700\\n- **Total Outstanding Loans**: 125000\\n- The individual has two loans: a personal loan with an outstanding balance of 45000 and an auto loan with an outstanding balance of 80000. The total outstanding debt is significant, but the excellent repayment history and manageable EMI suggest that the individual is capable of handling this debt.\\n\\n### 5. Overall Risk Profile\\n- Given the excellent repayment history and a loan burden ratio of 28%, the overall risk profile appears to be moderate. However, the unresolved CIBIL score and credit history are significant gaps in the analysis.\\n\\n### Risk Score Calculation\\nConsidering the factors analyzed:\\n- **Credit Score**: Unknown (assumed average risk due to lack of data)\\n- **Repayment Patterns**: Excellent (low risk)\\n- **Credit Utilization**: 28% (low risk)\\n- **Existing Loan Burden**: Manageable (moderate risk)\\n\\nBased on these factors, we can assign a risk score:\\n- Excellent repayment history: 10 points (low risk)\\n- Loan burden ratio: 20 points (low risk)\\n- Unknown credit score: 40 points (average risk)\\n- Overall risk score = 10 + 20 + 40 = 70\\n\\n### Final Risk Score\\n**Risk Score: 70/100** (where 100 is the highest risk)\\n\\n### Recommendations\\n1. **Resolve Credit Score Issues**: Obtain and review the CIBIL score to understand the full risk profile. If the score is low, take steps to improve it.\\n2. **Maintain Excellent Repayment Patterns**: Continue to make timely payments to maintain the excellent repayment track record.\\n3. **Monitor Credit Utilization**: Keep the loan burden ratio below 30% to ensure financial health.\\n4. **Consider Debt Management**: If additional loans are needed, consider consolidating existing loans or negotiating better terms to lower monthly payments.\\n5. **Regularly Review Credit Reports**: Regularly check credit reports for inaccuracies and resolve any discrepancies to ensure a favorable credit history.\\n\\nBy addressing the unresolved aspects of the credit data and maintaining good financial habits, the individual can further reduce their default risk.\", \"model_client_id\": \"risk_assessor\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "evaluate_default_risk"
    },
    "extract_application_info": {
      "customer_info": {
        "address": "123 Main St, City, State 12345",
        "annual_income": 75000,
        "customer_id": "CUST_12345",
        "email": "john.doe@email.com",
        "employment_status": "employed",
        "full_name": "John Doe",
        "loan_purpose": "home_purchase",
        "phone": "+1-555-0123",
        "requested_amount": 100000
      },
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 100000}, \"missing_fields\": []}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.243581,
        "end_time": "2025-07-15T12:34:32.524026",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:32.280445",
        "timestamp": "2025-07-15T12:34:32.524026",
        "worker_executed": true,
        "workers_notified": true
      },
      "extraction_success": true,
      "missing_fields": [],
      "output": "__OUTPUTS__ {\"extraction_success\": true, \"customer_info\": {\"customer_id\": \"CUST_12345\", \"full_name\": \"John Doe\", \"email\": \"john.doe@email.com\", \"phone\": \"+1-555-0123\", \"address\": \"123 Main St, City, State 12345\", \"employment_status\": \"employed\", \"annual_income\": 75000, \"loan_purpose\": \"home_purchase\", \"requested_amount\": 100000}, \"missing_fields\": []}\n",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "extract_application_info"
    },
    "final_underwriting_analysis": {
      "agent_type": "assistant",
      "ai_response": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\n   \n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\n   \n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n   \n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\n   \n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\n   \n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\n   \n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\n\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 484,
            "model": "gpt-4o-mini",
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            "provider": "openai",
            "system_message": "You are a senior underwriting manager making final loan decisions.\n\nAnalyze all assessment results and provide:\n1. Final recommendation (APPROVE/CONDITIONAL/DECLINE)\n2. Loan terms and conditions\n3. Risk mitigation measures\n4. Reasoning for decision\n5. Confidence level (1-100)\n\nConsider all factors: income, credit, compliance, and overall risk profile.\n"
          },
          "input_format": "json",
          "model_client_id": "underwriting_analyst",
          "output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\n   \n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\n   \n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n   \n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\n   \n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\n   \n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\n   \n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\n\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\\n   \\n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\\n   \\n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n   \\n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\\n   \\n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\\n   \\n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\\n   \\n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 7.595531,
        "end_time": "2025-07-15T12:38:19.350027",
        "message_sent": true,
        "start_time": "2025-07-15T12:38:11.754496",
        "timestamp": "2025-07-15T12:38:19.350027",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "1. **Final Recommendation**: DECLINE\n\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\n\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\n\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\n\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\n   \n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\n   \n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\n   \n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\n   \n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\n   \n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\n   \n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\n\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\n\n5. **Confidence Level**: 95\n\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\n__OUTPUTS__ {\"ai_response\": \"1. **Final Recommendation**: DECLINE\\n\\n2. **Loan Terms and Conditions**: N/A (Loan application is declined)\\n\\n3. **Risk Mitigation Measures**: N/A (Loan application is declined)\\n\\n4. **Reasoning for Decision**: The application presents multiple unresolved issues across critical assessment areas. Specifically, the following factors contribute to the decision to decline the loan:\\n\\n   - **Application Quality**: The unresolved application quality check indicates potential inconsistencies or missing information that could affect the overall assessment of the applicant\u0027s eligibility.\\n   \\n   - **Document Verification**: The unresolved status of document verification raises concerns about the authenticity and completeness of the submitted documentation, which is essential for making an informed lending decision.\\n   \\n   - **Income Assessment**: An unresolved income assessment means that we cannot accurately determine the applicant\u0027s ability to repay the loan based on their income, which is a fundamental aspect of underwriting.\\n   \\n   - **Credit Score**: Without a calculated credit score, we lack insight into the applicant\u0027s creditworthiness and history of managing debt, which is critical for assessing risk.\\n   \\n   - **Default Risk**: The unresolved evaluation of default risk means we cannot ascertain the likelihood of the applicant defaulting on the loan, leaving us exposed to potential financial loss.\\n   \\n   - **Compliance**: Unresolved compliance issues suggest that the application may not meet regulatory requirements, which could lead to legal and financial repercussions for the lending institution.\\n   \\n   - **Debt-to-Income Ratio**: Without a calculated debt-to-income ratio, we cannot evaluate the applicant\u0027s financial health and ability to manage existing and new debt obligations.\\n\\nGiven these unresolved issues, the overall risk profile of the applicant is deemed too high, and the lack of clarity in key areas makes it impossible to proceed with the loan.\\n\\n5. **Confidence Level**: 95\\n\\nThis high confidence level reflects the significant number of unresolved issues that indicate a lack of sufficient information to support a loan approval.\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "final_underwriting_analysis"
    },
    "flag_for_manual_review": {
      "error": "Unsupported task type: human",
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        "failed": true,
        "message_sent": true,
        "worker_executed": true,
        "workers_notified": true
      },
      "output": "Task failed: Unsupported task type: human",
      "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/tmpjtpjfxcd.py\", line 15, in \u003cmodule\u003e\n    \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
      "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/tmpjtpjfxcd.py\", line 15, in \u003cmodule\u003e\n    \"credit_score\": UNRESOLVED_calculate_credit_score.internal_credit_score,\n                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\nNameError: name \u0027UNRESOLVED_calculate_credit_score\u0027 is not defined\n",
      "status": "FAILED",
      "task_id": "generate_final_output"
    },
    "income_assessment": {
      "agent_type": "assistant",
      "ai_response": "```json\n{\n  \"income_assessment\": {\n    \"income_stability\": {\n      \"assessment\": \"Stable\",\n      \"details\": {\n        \"employment_type\": \"Permanent\",\n        \"job_stability_score\": 88.5,\n        \"employer_rating\": \"A+\",\n        \"probation_status\": \"Confirmed\",\n        \"employment_verified\": true,\n        \"reference_check_passed\": true\n      }\n    },\n    \"debt_servicing_capability\": {\n      \"assessment\": \"Marginally Acceptable\",\n      \"details\": {\n        \"monthly_net_income\": 6800,\n        \"total_debt_payments\": 2816.67,\n        \"proposed_emi\": 416.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"max_allowed_ratio\": 0.4,\n        \"ratio_acceptable\": false\n      }\n    },\n    \"financial_discipline\": {\n      \"assessment\": \"Moderate\",\n      \"details\": {\n        \"existing_debt_payments\": 2400,\n        \"total_debt_payments\": 2816.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"indication_of_financial_discipline\": \"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\"\n      }\n    },\n    \"risk_factors_and_recommendations\": {\n      \"risk_factors\": [\n        \"Debt-to-income ratio exceeds acceptable limits.\",\n        \"Existing debt payments are high relative to income.\"\n      ],\n      \"recommendations\": [\n        \"Consider reducing existing debt before applying for new loans.\",\n        \"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\",\n        \"Maintain a close watch on monthly expenses to ensure they do not exceed income.\"\n      ]\n    },\n    \"overall_income_adequacy_score\": 65\n  }\n}\n```",
      "execution_details": {
        "actual_result": {
          "agent_type": "assistant",
          "execution_details": {
            "agent_type": "assistant",
            "input_length": 782,
            "model": "gpt-4o-mini",
            "output_length": 1598,
            "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": "```json\n{\n  \"income_assessment\": {\n    \"income_stability\": {\n      \"assessment\": \"Stable\",\n      \"details\": {\n        \"employment_type\": \"Permanent\",\n        \"job_stability_score\": 88.5,\n        \"employer_rating\": \"A+\",\n        \"probation_status\": \"Confirmed\",\n        \"employment_verified\": true,\n        \"reference_check_passed\": true\n      }\n    },\n    \"debt_servicing_capability\": {\n      \"assessment\": \"Marginally Acceptable\",\n      \"details\": {\n        \"monthly_net_income\": 6800,\n        \"total_debt_payments\": 2816.67,\n        \"proposed_emi\": 416.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"max_allowed_ratio\": 0.4,\n        \"ratio_acceptable\": false\n      }\n    },\n    \"financial_discipline\": {\n      \"assessment\": \"Moderate\",\n      \"details\": {\n        \"existing_debt_payments\": 2400,\n        \"total_debt_payments\": 2816.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"indication_of_financial_discipline\": \"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\"\n      }\n    },\n    \"risk_factors_and_recommendations\": {\n      \"risk_factors\": [\n        \"Debt-to-income ratio exceeds acceptable limits.\",\n        \"Existing debt payments are high relative to income.\"\n      ],\n      \"recommendations\": [\n        \"Consider reducing existing debt before applying for new loans.\",\n        \"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\",\n        \"Maintain a close watch on monthly expenses to ensure they do not exceed income.\"\n      ]\n    },\n    \"overall_income_adequacy_score\": 65\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"income_assessment\\\": {\\n    \\\"income_stability\\\": {\\n      \\\"assessment\\\": \\\"Stable\\\",\\n      \\\"details\\\": {\\n        \\\"employment_type\\\": \\\"Permanent\\\",\\n        \\\"job_stability_score\\\": 88.5,\\n        \\\"employer_rating\\\": \\\"A+\\\",\\n        \\\"probation_status\\\": \\\"Confirmed\\\",\\n        \\\"employment_verified\\\": true,\\n        \\\"reference_check_passed\\\": true\\n      }\\n    },\\n    \\\"debt_servicing_capability\\\": {\\n      \\\"assessment\\\": \\\"Marginally Acceptable\\\",\\n      \\\"details\\\": {\\n        \\\"monthly_net_income\\\": 6800,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"proposed_emi\\\": 416.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"max_allowed_ratio\\\": 0.4,\\n        \\\"ratio_acceptable\\\": false\\n      }\\n    },\\n    \\\"financial_discipline\\\": {\\n      \\\"assessment\\\": \\\"Moderate\\\",\\n      \\\"details\\\": {\\n        \\\"existing_debt_payments\\\": 2400,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"indication_of_financial_discipline\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\\\"\\n      }\\n    },\\n    \\\"risk_factors_and_recommendations\\\": {\\n      \\\"risk_factors\\\": [\\n        \\\"Debt-to-income ratio exceeds acceptable limits.\\\",\\n        \\\"Existing debt payments are high relative to income.\\\"\\n      ],\\n      \\\"recommendations\\\": [\\n        \\\"Consider reducing existing debt before applying for new loans.\\\",\\n        \\\"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\\\",\\n        \\\"Maintain a close watch on monthly expenses to ensure they do not exceed income.\\\"\\n      ]\\n    },\\n    \\\"overall_income_adequacy_score\\\": 65\\n  }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
          "output_format": "json",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 9.943372,
        "end_time": "2025-07-15T12:34:51.990866",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:42.047494",
        "timestamp": "2025-07-15T12:34:51.990866",
        "worker_executed": true,
        "workers_notified": true
      },
      "model": "gpt-4o-mini",
      "model_client_id": "underwriting_analyst",
      "output": "```json\n{\n  \"income_assessment\": {\n    \"income_stability\": {\n      \"assessment\": \"Stable\",\n      \"details\": {\n        \"employment_type\": \"Permanent\",\n        \"job_stability_score\": 88.5,\n        \"employer_rating\": \"A+\",\n        \"probation_status\": \"Confirmed\",\n        \"employment_verified\": true,\n        \"reference_check_passed\": true\n      }\n    },\n    \"debt_servicing_capability\": {\n      \"assessment\": \"Marginally Acceptable\",\n      \"details\": {\n        \"monthly_net_income\": 6800,\n        \"total_debt_payments\": 2816.67,\n        \"proposed_emi\": 416.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"max_allowed_ratio\": 0.4,\n        \"ratio_acceptable\": false\n      }\n    },\n    \"financial_discipline\": {\n      \"assessment\": \"Moderate\",\n      \"details\": {\n        \"existing_debt_payments\": 2400,\n        \"total_debt_payments\": 2816.67,\n        \"debt_to_income_ratio\": 0.4142,\n        \"indication_of_financial_discipline\": \"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\"\n      }\n    },\n    \"risk_factors_and_recommendations\": {\n      \"risk_factors\": [\n        \"Debt-to-income ratio exceeds acceptable limits.\",\n        \"Existing debt payments are high relative to income.\"\n      ],\n      \"recommendations\": [\n        \"Consider reducing existing debt before applying for new loans.\",\n        \"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\",\n        \"Maintain a close watch on monthly expenses to ensure they do not exceed income.\"\n      ]\n    },\n    \"overall_income_adequacy_score\": 65\n  }\n}\n```\n__OUTPUTS__ {\"ai_response\": \"```json\\n{\\n  \\\"income_assessment\\\": {\\n    \\\"income_stability\\\": {\\n      \\\"assessment\\\": \\\"Stable\\\",\\n      \\\"details\\\": {\\n        \\\"employment_type\\\": \\\"Permanent\\\",\\n        \\\"job_stability_score\\\": 88.5,\\n        \\\"employer_rating\\\": \\\"A+\\\",\\n        \\\"probation_status\\\": \\\"Confirmed\\\",\\n        \\\"employment_verified\\\": true,\\n        \\\"reference_check_passed\\\": true\\n      }\\n    },\\n    \\\"debt_servicing_capability\\\": {\\n      \\\"assessment\\\": \\\"Marginally Acceptable\\\",\\n      \\\"details\\\": {\\n        \\\"monthly_net_income\\\": 6800,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"proposed_emi\\\": 416.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"max_allowed_ratio\\\": 0.4,\\n        \\\"ratio_acceptable\\\": false\\n      }\\n    },\\n    \\\"financial_discipline\\\": {\\n      \\\"assessment\\\": \\\"Moderate\\\",\\n      \\\"details\\\": {\\n        \\\"existing_debt_payments\\\": 2400,\\n        \\\"total_debt_payments\\\": 2816.67,\\n        \\\"debt_to_income_ratio\\\": 0.4142,\\n        \\\"indication_of_financial_discipline\\\": \\\"The debt-to-income ratio exceeds the acceptable threshold, indicating potential financial strain.\\\"\\n      }\\n    },\\n    \\\"risk_factors_and_recommendations\\\": {\\n      \\\"risk_factors\\\": [\\n        \\\"Debt-to-income ratio exceeds acceptable limits.\\\",\\n        \\\"Existing debt payments are high relative to income.\\\"\\n      ],\\n      \\\"recommendations\\\": [\\n        \\\"Consider reducing existing debt before applying for new loans.\\\",\\n        \\\"Explore options for increasing income or reducing expenses to improve debt-to-income ratio.\\\",\\n        \\\"Maintain a close watch on monthly expenses to ensure they do not exceed income.\\\"\\n      ]\\n    },\\n    \\\"overall_income_adequacy_score\\\": 65\\n  }\\n}\\n```\", \"model_client_id\": \"underwriting_analyst\", \"agent_type\": \"assistant\", \"model\": \"gpt-4o-mini\", \"provider\": \"openai\", \"status\": \"completed\"}",
      "provider": "openai",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "income_assessment"
    },
    "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": ""
        },
        "duration_seconds": 0.311171,
        "end_time": "2025-07-15T12:38:06.345673",
        "message_sent": true,
        "start_time": "2025-07-15T12:38:06.034502",
        "timestamp": "2025-07-15T12:38:06.345673",
        "worker_executed": true,
        "workers_notified": true
      },
      "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,
      "policy_version": "2024.1",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "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",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
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        "duration_seconds": 0.864319,
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        "workers_notified": true
      },
      "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,
      "risk_category": "low",
      "status": "completed",
      "stderr": "",
      "task_id": "kyc_compliance_check"
    },
    "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",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.324695,
        "end_time": "2025-07-15T12:38:06.135232",
        "message_sent": true,
        "start_time": "2025-07-15T12:38:05.810537",
        "timestamp": "2025-07-15T12:38:06.135232",
        "worker_executed": true,
        "workers_notified": true
      },
      "lending_norms_compliant": true,
      "output": "__OUTPUTS__ {\"rbi_guidelines_met\": true, \"lending_norms_compliant\": true, \"documentation_complete\": true, \"disclosure_requirements_met\": true, \"consumer_protection_compliant\": true, \"data_privacy_compliant\": true, \"compliance_score\": 97.2, \"audit_trail_complete\": true, \"regulatory_risk\": \"minimal\"}\n",
      "rbi_guidelines_met": true,
      "regulatory_risk": "minimal",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "regulatory_compliance"
    },
    "underwriting_decision_router": {
      "all_conditions_checked": [
        {
          "condition": "${calculate_credit_score.internal_credit_score} \u003c 600 || ${calculate_debt_to_income.debt_to_income_ratio} \u003e 0.50",
          "name": "high_risk_path",
          "result": false,
          "route": "decline_path"
        },
        {
          "condition": "${calculate_credit_score.internal_credit_score} \u003e= 600 \u0026\u0026 ${calculate_credit_score.internal_credit_score} \u003c 700",
          "name": "conditional_approval_path",
          "result": false,
          "route": "conditional_path"
        },
        {
          "condition": "${calculate_credit_score.internal_credit_score} \u003e= 700",
          "name": "standard_approval_path",
          "result": false,
          "route": "approval_path"
        }
      ],
      "duration_seconds": 0.002322,
      "ended_at": "2025-07-15T12:38:11.616824",
      "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\": 0.002322, \"started_at\": \"2025-07-15T12:38:11.614502\", \"ended_at\": \"2025-07-15T12:38:11.616824\"}",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.210994,
        "end_time": "2025-07-15T12:38:11.723211",
        "message_sent": true,
        "start_time": "2025-07-15T12:38:11.512217",
        "timestamp": "2025-07-15T12:38:11.723211",
        "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\": 0.002322, \"started_at\": \"2025-07-15T12:38:11.614502\", \"ended_at\": \"2025-07-15T12:38:11.616824\"}",
      "return_code": 0,
      "route_reason": "no_conditions_matched",
      "router_type": "condition",
      "selected_route": "manual_review_path",
      "started_at": "2025-07-15T12:38:11.614502",
      "status": "completed",
      "stderr": "",
      "task_id": "underwriting_decision_router"
    },
    "validate_application_fields": {
      "completion_percentage": 100.0,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.306413,
        "end_time": "2025-07-15T12:34:32.854694",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:32.548281",
        "timestamp": "2025-07-15T12:34:32.854694",
        "worker_executed": true,
        "workers_notified": true
      },
      "missing_fields": [],
      "output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "validate_application_fields",
      "validation_passed": true
    },
    "verify_aadhaar": {
      "aadhaar_masked": "1234-5678-9012",
      "address_match": true,
      "biometric_verified": true,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.496607,
        "end_time": "2025-07-15T12:34:37.917135",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:37.420528",
        "timestamp": "2025-07-15T12:34:37.917135",
        "worker_executed": true,
        "workers_notified": true
      },
      "is_valid": true,
      "last_updated": "2024-01-15",
      "output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_aadhaar",
      "verification_score": 98.2
    },
    "verify_address_proof": {
      "address_confirmed": "123 Main St, City, State 12345",
      "address_match": true,
      "document_date": "2024-06-15",
      "document_type": "utility_bill",
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.802213,
        "end_time": "2025-07-15T12:34:38.303341",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:37.501128",
        "timestamp": "2025-07-15T12:34:38.303341",
        "worker_executed": true,
        "workers_notified": true
      },
      "is_valid": true,
      "output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_address_proof",
      "verification_score": 92.3
    },
    "verify_employment": {
      "designation": "Senior Software Engineer",
      "employer_rating": "A+",
      "employment_confirmed": true,
      "employment_type": "permanent",
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.580478,
        "end_time": "2025-07-15T12:34:41.870395",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:41.289917",
        "timestamp": "2025-07-15T12:34:41.870395",
        "worker_executed": true,
        "workers_notified": true
      },
      "hr_contact_verified": true,
      "job_stability_score": 88.5,
      "output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
      "probation_status": "confirmed",
      "reference_check_passed": true,
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_employment"
    },
    "verify_pan_card": {
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.3626,
        "end_time": "2025-07-15T12:34:37.735706",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:37.373106",
        "timestamp": "2025-07-15T12:34:37.735706",
        "worker_executed": true,
        "workers_notified": true
      },
      "is_valid": true,
      "name_match": true,
      "output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
      "pan_number": "ABCDE1234F",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_pan_card",
      "verification_score": 95.5,
      "verified_name": "JOHN DOE"
    },
    "verify_passport": {
      "document_provided": true,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.783337,
        "end_time": "2025-07-15T12:34:38.245914",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:37.462577",
        "timestamp": "2025-07-15T12:34:38.245914",
        "worker_executed": true,
        "workers_notified": true
      },
      "expiry_date": "2030-12-31",
      "is_valid": true,
      "issuing_authority": "Government of India",
      "output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
      "passport_number": "A1234567",
      "return_code": 0,
      "status": "completed",
      "stderr": "",
      "task_id": "verify_passport",
      "verification_score": 96.8
    },
    "verify_tax_returns": {
      "declared_income": 98000,
      "discrepancies_found": false,
      "execution_details": {
        "actual_result": {
          "output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
          "return_code": 0,
          "status": "completed",
          "stderr": ""
        },
        "duration_seconds": 0.731322,
        "end_time": "2025-07-15T12:34:41.759137",
        "message_sent": true,
        "start_time": "2025-07-15T12:34:41.027815",
        "timestamp": "2025-07-15T12:34:41.759137",
        "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": 0.002322,
    "ended_at": "2025-07-15T12:38:11.616824",
    "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\": 0.002322, \"started_at\": \"2025-07-15T12:38:11.614502\", \"ended_at\": \"2025-07-15T12:38:11.616824\"}",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.210994,
      "end_time": "2025-07-15T12:38:11.723211",
      "message_sent": true,
      "start_time": "2025-07-15T12:38:11.512217",
      "timestamp": "2025-07-15T12:38:11.723211",
      "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\": 0.002322, \"started_at\": \"2025-07-15T12:38:11.614502\", \"ended_at\": \"2025-07-15T12:38:11.616824\"}",
    "return_code": 0,
    "route_reason": "no_conditions_matched",
    "router_type": "condition",
    "selected_route": "manual_review_path",
    "started_at": "2025-07-15T12:38:11.614502",
    "status": "completed",
    "stderr": "",
    "task_id": "underwriting_decision_router"
  },
  "validate_application_fields": {
    "completion_percentage": 100.0,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.306413,
      "end_time": "2025-07-15T12:34:32.854694",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:32.548281",
      "timestamp": "2025-07-15T12:34:32.854694",
      "worker_executed": true,
      "workers_notified": true
    },
    "missing_fields": [],
    "output": "__OUTPUTS__ {\"validation_passed\": true, \"missing_fields\": [], \"completion_percentage\": 100.0}\n",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "validate_application_fields",
    "validation_passed": true
  },
  "verify_aadhaar": {
    "aadhaar_masked": "1234-5678-9012",
    "address_match": true,
    "biometric_verified": true,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.496607,
      "end_time": "2025-07-15T12:34:37.917135",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:37.420528",
      "timestamp": "2025-07-15T12:34:37.917135",
      "worker_executed": true,
      "workers_notified": true
    },
    "is_valid": true,
    "last_updated": "2024-01-15",
    "output": "__OUTPUTS__ {\"aadhaar_masked\": \"1234-5678-9012\", \"is_valid\": true, \"address_match\": true, \"biometric_verified\": true, \"verification_score\": 98.2, \"last_updated\": \"2024-01-15\"}\n",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_aadhaar",
    "verification_score": 98.2
  },
  "verify_address_proof": {
    "address_confirmed": "123 Main St, City, State 12345",
    "address_match": true,
    "document_date": "2024-06-15",
    "document_type": "utility_bill",
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.802213,
      "end_time": "2025-07-15T12:34:38.303341",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:37.501128",
      "timestamp": "2025-07-15T12:34:38.303341",
      "worker_executed": true,
      "workers_notified": true
    },
    "is_valid": true,
    "output": "__OUTPUTS__ {\"document_type\": \"utility_bill\", \"is_valid\": true, \"address_match\": true, \"document_date\": \"2024-06-15\", \"verification_score\": 92.3, \"address_confirmed\": \"123 Main St, City, State 12345\"}\n",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_address_proof",
    "verification_score": 92.3
  },
  "verify_employment": {
    "designation": "Senior Software Engineer",
    "employer_rating": "A+",
    "employment_confirmed": true,
    "employment_type": "permanent",
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.580478,
      "end_time": "2025-07-15T12:34:41.870395",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:41.289917",
      "timestamp": "2025-07-15T12:34:41.870395",
      "worker_executed": true,
      "workers_notified": true
    },
    "hr_contact_verified": true,
    "job_stability_score": 88.5,
    "output": "__OUTPUTS__ {\"employment_confirmed\": true, \"designation\": \"Senior Software Engineer\", \"employment_type\": \"permanent\", \"probation_status\": \"confirmed\", \"employer_rating\": \"A+\", \"job_stability_score\": 88.5, \"reference_check_passed\": true, \"hr_contact_verified\": true}\n",
    "probation_status": "confirmed",
    "reference_check_passed": true,
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_employment"
  },
  "verify_pan_card": {
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.3626,
      "end_time": "2025-07-15T12:34:37.735706",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:37.373106",
      "timestamp": "2025-07-15T12:34:37.735706",
      "worker_executed": true,
      "workers_notified": true
    },
    "is_valid": true,
    "name_match": true,
    "output": "__OUTPUTS__ {\"pan_number\": \"ABCDE1234F\", \"is_valid\": true, \"name_match\": true, \"status\": \"active\", \"verification_score\": 95.5, \"verified_name\": \"JOHN DOE\"}\n",
    "pan_number": "ABCDE1234F",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_pan_card",
    "verification_score": 95.5,
    "verified_name": "JOHN DOE"
  },
  "verify_passport": {
    "document_provided": true,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.783337,
      "end_time": "2025-07-15T12:34:38.245914",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:37.462577",
      "timestamp": "2025-07-15T12:34:38.245914",
      "worker_executed": true,
      "workers_notified": true
    },
    "expiry_date": "2030-12-31",
    "is_valid": true,
    "issuing_authority": "Government of India",
    "output": "__OUTPUTS__ {\"passport_number\": \"A1234567\", \"is_valid\": true, \"expiry_date\": \"2030-12-31\", \"issuing_authority\": \"Government of India\", \"verification_score\": 96.8, \"document_provided\": true}\n",
    "passport_number": "A1234567",
    "return_code": 0,
    "status": "completed",
    "stderr": "",
    "task_id": "verify_passport",
    "verification_score": 96.8
  },
  "verify_tax_returns": {
    "declared_income": 98000,
    "discrepancies_found": false,
    "execution_details": {
      "actual_result": {
        "output": "__OUTPUTS__ {\"declared_income\": 98000, \"tax_paid\": 12000, \"returns_filed_consistently\": true, \"income_growth_trend\": \"positive\", \"discrepancies_found\": false, \"verification_with_govt\": true, \"tax_compliance_score\": 92.0}\n",
        "return_code": 0,
        "status": "completed",
        "stderr": ""
      },
      "duration_seconds": 0.731322,
      "end_time": "2025-07-15T12:34:41.759137",
      "message_sent": true,
      "start_time": "2025-07-15T12:34:41.027815",
      "timestamp": "2025-07-15T12:34:41.759137",
      "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
  }
}

Duration: N/A

Error: Python script failed with return code 1: Traceback (most recent call last): File "/tmp/tmpzav0jklx.py", line 9, in <module> cibil_score = UNRESOLVED_check_cibil_score.credit_score ^^^^^^^^^^^^^^^^^^^^^^^^^^^^ NameError: name 'UNRESOLVED_check_cibil_score' is not defined

flag_for_manual_review

FAILED

Started: 2025-07-15 12:34:30

Duration: N/A

Error: Unsupported task type: human

generate_final_output

FAILED

Started: 2025-07-15 12:34:30

Duration: N/A

Error: Python script failed with return code 1: Traceback (most recent call last): File "/tmp/tmpjtpjfxcd.py", line 15, in <module> "credit_score": UNRESOLVED_calculate_credit_score.internal_credit_score, ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ NameError: name 'UNRESOLVED_calculate_credit_score' is not defined

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Execution Details COMPLETED

Execution Information

Quick Actions

Execution Inputs

Execution Outputs

Workflow Execution Summary

Task Results & Logs

Task Executions

extract_application_info

Task Output

validate_application_fields

Task Output

application_quality_check

Task Output

verify_pan_card

Task Output

verify_aadhaar

Task Output

verify_passport

Task Output

verify_address_proof

Task Output

consolidate_document_verification

Task Output

analyze_salary_slips

Task Output

analyze_bank_statements

Task Output

verify_tax_returns

Task Output

verify_employment

Task Output

calculate_debt_to_income

Task Output

income_assessment

Task Output

check_cibil_score

Task Output

analyze_credit_history

Task Output

assess_existing_loans

Task Output

evaluate_default_risk

Task Output

kyc_compliance_check

Task Output

aml_screening

Task Output

regulatory_compliance

Task Output

internal_policy_check

Task Output

compliance_consolidation

Task Output

underwriting_decision_router

Task Output

final_underwriting_analysis

Task Output

calculate_credit_score

Task Output

flag_for_manual_review

Task Output

generate_final_output

Task Output

Generated Files

Execution Logs