About this document
UPI Fraud Detection with Machine Learning by soundaryakalai2002 is a document available to read on EtoBox.
The document discusses using machine learning algorithms to detect fraudulent transactions in Unified Payments Interface (UPI) systems. It proposes using an XGBoost model to analyze transaction features and classify transactions as fraudulent or legitimate. The model would be trained on a dataset of past transactions containing examples of both. This could help enhance security for UPI users and financial institutions by preventing unauthorized access and identity theft through fraudulent transactions.
- Author
- soundaryakalai2002
- Language
- EN