{
  "$schema": "https://aigovernanceengineer.com/schemas/instructions-for-use.v1.json",
  "document_id": "ifu-credit-afford-03-3.2.0",
  "subject": "credit-afford-03@3.2.0",
  "provider": {
    "name": "Example Bank, retail credit models team",
    "contact": "ai-governance@example.org"
  },
  "intended_purpose": "Affordability score for consumer loan applications up to 30k EUR in ES and PT, as decision support for a trained credit analyst who takes the decision.",
  "performance": {
    "accuracy": [
      {
        "metric": "AUC",
        "value": "0.80",
        "conditions": "held-out 2025 applications"
      },
      {
        "metric": "approval-rate ratio across age bands",
        "value": "0.86",
        "conditions": "held-out 2025 applications"
      }
    ],
    "robustness": "Scores are stable under plus or minus 5% noise on declared income; not tested on incomes above 250k EUR.",
    "cybersecurity": "Batch scoring inside the origination network; no applicant-facing interface.",
    "circumstances_affecting_performance": [
      "self-employed applicants with under 12 months of history",
      "sharp interest-rate changes"
    ]
  },
  "known_risks": [
    "indirect discrimination by age if used outside the validated range",
    "over-reliance by analysts on the score"
  ],
  "explanation_capabilities": "Top five reason codes per score, from monotonic feature contributions.",
  "performance_by_group": [
    {
      "group": "applicants over 75",
      "note": "too few cases to establish performance; refer to manual assessment"
    }
  ],
  "input_data_specifications": "Application fields as defined in the origination schema v12; must not receive health or nationality data.",
  "training_data_information": "Applications 2019 to 2025 with 12-month outcomes; see dataset card loan-apps-2019-2025.",
  "output_interpretation": "A score of 0 to 1000 with reason codes. It is an input to the analyst, never a decision; referral band 450 to 550.",
  "predetermined_changes": [
    "quarterly recalibration of the score-to-band mapping within declared metrics"
  ],
  "human_oversight_measures": "Every application is decided by an analyst, who sees the score, the reason codes and the data used, and can override with a logged reason.",
  "resources_and_maintenance": {
    "compute_and_hardware": "Standard batch compute, under 1 CPU-hour per day.",
    "expected_lifetime": "Until 2029, subject to annual review.",
    "maintenance": "Monthly monitoring report; retraining is a new release."
  },
  "logging": "Each score, its reason codes and any override are written to the application record and kept ten years.",
  "issued": "2026-08-20"
}