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View Weekly PageAnswer: Machine Learning
ML models analyze transaction patterns (amount, location, time, device) to detect anomalies indicating fraud. Techniques: supervised learning (labeled fraud data), unsupervised anomaly detection, and real-time scoring. Used by banks, UPI apps, and payment gateways. Continuous learning adapts to evolving fraud tactics while minimizing false positives.