UPI Fraud Transaction Detection using Machine Learning

Abstract

The rapid growth of digital payment systems and Unified Payments Interface (UPI) transactions has significantly transformed financial transactions by providing convenience, speed, and accessibility. However, this widespread adoption has also increased the risk of fraudulent activities, leading to substantial financial losses for users, banks, and payment service providers. To address this challenge, the proposed UPI Fraud Transaction Detection using Machine Learning system introduces an intelligent framework capable of identifying fraudulent transactions with high accuracy and efficiency. The system collects and preprocesses transaction data by handling missing values, converting categorical attributes into numerical formats, and normalizing the dataset to ensure data quality and consistency.