Overview This project aims to develop a machine learning model for the prediction and detection of fraudulent transactions in a banking system. Fraudulent transactions can have severe financial implications for banks and customers alike, making accurate detection crucial for security and financial stability.
The primary goal of this project is to build a predictive model that can identify potentially fraudulent transactions based on historical transaction data, transaction attributes, and other relevant features.