{
  "tool_id": "ml-03-timeseries-anomaly-detector",
  "kernel_id": "ml-03-timeseries-anomaly-detector",
  "display_name": "Time-Series Anomaly Detector",
  "tool_version": "1.0.0",
  "mandate_type": "risk_control",
  "purpose": "Rolling-window z-score and STL-style seasonal decomposition anomaly detection on synthetic payment volume time series. Control chart (UCL/LCL 3σ), trend/seasonal/residual panel decomposition, anomaly flag table with severity, naïve ARIMA-lite 30-period forecast. Chains from SIM-03 (Basel RWA Scenario Modeler). Feeds RCA-01 (FRTB IMA). DORA Art.17 monitoring / EBA GL/2021/03 operational risk / PSD2 Art.96 fraud reporting.",
  "control_description": "Rolling-window z-score and STL-style seasonal decomposition anomaly detection on synthetic payment volume time series. Control chart (UCL/LCL 3σ), trend/seasonal/residual panel decomposition, anomaly flag table with severity, naïve ARIMA-lite 30-period forecast. Chains from SIM-03 (Basel RWA Scenario Modeler). Feeds RCA-01 (FRTB IMA). DORA Art.17 monitoring / EBA GL/2021/03 operational risk / PSD2 Art.96 fraud reporting.",
  "declared_inputs": [
    "sim-03-basel-rwa-scenario-modeler"
  ],
  "declared_outputs": [
    "rca-01-frtb-ima-pre-validator",
    "ptg-01-ap2-prompt-template-generator"
  ],
  "kernel_digest": "sha256:ae20b291caf5eac025d4e7103782427565fe7cf0c99f4045122257c87db0d9c6",
  "trust_label": "deferred -- deterministic source published, zkVM proof not yet generated",
  "data_vintage": "2026-07-10",
  "last_validated": "2026-07-10",
  "conformance_fixtures_vendored": false,
  "compute_proof_ready": "ready",
  "wave": 4,
  "source_url": "https://ainumbers.co/chaingraph/ml-03-timeseries-anomaly-detector.html",
  "generated_at": "2026-07-25T20:02:55.601Z"
}