This project focuses on detecting fraudulent financial transactions using machine learning techniques. By applying anomaly detection and pattern recognition, the system distinguishes between legitimate and suspicious activities. The model analyzes transaction patterns and supports real-time monitoring to improve fraud prevention accuracy.