ML-01 · Regulatory Compliance & Resilience · Anomaly Detection · Native JS

Isolation Forest Transaction Anomaly Detector

Isolation Forest anomaly detection on synthetic transaction batches. Scores each transaction across four features (amount, hour-of-day, counterparty frequency, recency) using a 10-tree forest with subsampled isolation. Anomaly score near 1.0 = isolated quickly = anomalous. All computation is client-side — no transaction data transmitted. Chains from ART-10 (AMLA typology scoring).

detect_transaction_anomalies risk_control EU AI Act AMLA 2024 FCA Consumer Duty Isolation Forest
Preset 1
Payment Stream
1,000 txns · 5% anomaly rate · large-amount outliers
Preset 2
Wire Transfers
500 txns · 8% anomaly rate · unusual timing + amount
Preset 3
High-Risk Corridor
750 txns · 12% anomaly rate · multi-feature outliers
Chain Intake — paste AP2 JSON from ART-10 (AMLA Typology Risk Scorer)