Fraud Detection & Anomaly Detection Questions

Techniques for identifying fraudulent activities and anomalies using machine learning and AI. Covers supervised and unsupervised methods, anomaly detection algorithms (e.g., Isolation Forest, LOF, One-Class SVM), feature engineering for fraud patterns, model evaluation, deployment considerations (real-time vs batch), and governance of fraud-detection systems.