Machine Learning in Fraud Detection

Machine learning in fraud detection involves using algorithms to analyze patterns in data and identify unusual behaviors that may indicate fraudulent activity. By training on historical data, these systems learn what normal transactions look like and can flag anomalies in real-time. For instance, if a user suddenly makes large purchases from an unfamiliar location, the system can raise an alert. This technology helps businesses quickly detect and respond to potential fraud, reducing losses and improving security while continuously learning and adapting to new tactics used by fraudsters.