Compliance Copilot - AI Transaction Alert Triage

Compliance Copilot addresses one of the biggest challenges in financial crime operations: alert fatigue caused by high false-positive rates in transaction monitoring systems. Compliance teams often receive thousands of alerts weekly, making it difficult to quickly identify truly suspicious behavior. This project introduces an AI-powered alert triage system that combines deterministic, auditable risk scoring with generative AI explanations. Each transaction alert is evaluated using transparent risk signals such as transaction amount deviation, behavioral patterns (velocity and burst activity), and geographic corridor risk. Alerts are scored on a 0–100 scale and classified as High, Medium, or Low risk. A local large language model is then used to generate concise, analyst-ready explanations that clearly summarize why an alert was flagged and recommend next investigative steps. This approach preserves explainability and regulatory trust while significantly reducing manual review effort. By collapsing large alert volumes into a small set of high-confidence cases with clear reasoning, Compliance Copilot demonstrates how AI can improve operational efficiency, decision quality, and regulatory readiness in real-world compliance workflows. All data used is synthetic and the system is designed to integrate easily into existing monitoring pipelines.