Multi Model Fraud Analytics in Digital Payments: A UPI-Based Approach

Author(s)	Ms. Sneha D S, Sowmya V
Country	India
Abstract	The rapid growth of Unified Payments Interface (UPI transactions has made it an important method for transactions in worldwide. As the use of digital payment systems increases, the risk associated with like fraud has also become a serious concern. To tackle this, system uses a several machine learning models like random forest, XGBoost and LSTM to predict the chances of fraud in transactions. To improve the system transparency, the solution uses LIME to provide clear explanations for the system results. The application has a user-friendly interface where users can enter transaction details and can see the results. A voice alert system announces whether the transaction is fraudulent or not and a results email notification is automatically sent to the user based on the prediction.
Keywords	machine learning, LIME, flask app, voice alerts, email notification, admin dashboard, user management, finance
Field	Computer Applications
Published In	Volume 7, Issue 5, September-October 2025
Published On	2025-10-22
DOI	https://doi.org/10.36948/ijfmr.2025.v07i05.58530

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