{
  "tool_id": "art-79-settlement-fail-predictor",
  "note": "golden_hash empty until first `node golden-parity.test.mjs --update`.",
  "vectors": [
    {
      "name": "default-inputs",
      "policy_parameters": {},
      "output_payload": {
        "scored_trades": [],
        "batch_fail_rate_estimate": 0,
        "top_drivers": [],
        "trade_count": 0,
        "methodology": {
          "description": "Transparent weighted feature scorecard. Feature weights are documented above. No ML black-box — fully interpretable.",
          "feature_weights": {
            "ssi_match_status": "mismatched=0.45, missing=0.65",
            "deadline_proximity": "tight=0.20, breached=0.50",
            "inventory_status": "short=0.20, uncertain=0.10",
            "counterparty_fail_band": "med=0.15, high=0.30",
            "liquidity_tier": "semi_liquid=0.15, illiquid=0.30",
            "partial_available": "false=0 (no deduction), true=-0.05"
          },
          "data_source": "SSI fail-rate: ~30% of fails (EquiLend / FinOps — verify current data)"
        },
        "note": "DECISION-SUPPORT DRAFT — probability scores are indicative band estimates from a weighted categorical scorecard. Not a machine-learning model. Feature weights are approximate; calibrate against your firm's actual fail history. No PII — all features are categorical/band-level."
      },
      "golden_hash": "de4b1600b05c5b529e00b22ed53a7c2920dad91b64fddad8e9cc914cd2d5bb35"
    }
  ]
}