AI-Based Fraud Detection System

The AI-Based Fraud Detection System is a mini project designed to leverage machine learning algorithms to identify and prevent fraudulent activities in financial transactions. The project involves collecting and preprocessing historical transaction data, which includes features such as transaction amount, location, time, and user behavior patterns. By employing techniques such as logistic regression, decision trees, or more advanced models like neural networks, the system is trained to recognize anomalies and flag suspicious transactions in real time. The implementation incorporates performance metrics like accuracy, precision, and recall to evaluate the effectiveness of the model. Additionally, the project aims to create a user-friendly interface that allows stakeholders to monitor alerts and generate reports, thereby enhancing the overall security and integrity of financial operations.