Regulatory Compliance Transaction Anomaly Detection

Build an advanced anomaly detection system for financial transaction monitoring using unsupervised machine learning techniques. Create a JavaScript framework that can process massive transaction datasets, identify statistically significant deviations from normal behavior, and generate comprehensive compliance reports. Implement multiple detection algorithms including isolation forests, clustering techniques, and statistical hypothesis testing with robust visualization of potential risk indicators.