Credit card fraud is a growing challenge in the digital era, with cybercriminals adopting advanced methods to exploit online transactions. This creates economic losses and impacts businesses and individuals alike, emphasizing the need for robust fraud detection systems. Balancing fraud prevention with a smooth customer experience is critical.
In this project, we will analyze credit card transaction data to identify unusual behavioural patterns that may indicate fraud. We will employ advanced data processing and machine learning techniques The primary objective of this project is to develop a machine-learning-based system for detecting credit card fraud. The system will integrate multiple algorithms to identify suspicious transactions and feature an intuitive user interface for interacting with detection results. The focus is on delivering an accurate, fast, and user-friendly solution to reduce financial fraud.