UPI Fraud Detection Using Machine Learning - Khopade, Nilam Prakash; Vitalkar, Shubhangi M. (International Journal of Research in Interdisciplinary Studies, 2025)
In recent years, digital transactions have surged, driven by convenience and accessibility, but this growth has also led to a rise in online payment fraud. According to the Reserve Bank of India, digital payment volumes and values increased by 216% and 10%, respectively, from March 2019 to March 2022. While consumers increasingly embrace digital payments, security concerns and a lack of awareness about safe online practices persist. Just a few years ago, online payments were rare, but today, UPI QR codes are commonplace, even at doorsteps. This widespread adoption has attracted fraudsters who exploit vulnerabilities to deceive users and siphon funds. Fortunately, digital transactions are trackable, enabling analysis with advanced tools. This study aims to develop a machine learning model to detect fraudulent transactions by analysing patterns in a transaction dataset, enhancing the security of online payments.