Year: 2025
Type: article
Abstract: : Because of its user-friendliness and real-time transactions, the Unified Payments Interface (UPI) has completely transformed digital payments. On the other hand, fraud has increased as a result of this quick acceptance. It offers a fresh method for identifying UPI fraud by utilizing behavioural analytics and cutting-edge machine learning algorithms. We create a strong detection system that accurately detects suspicious activity by utilizing a wide range of data, including transaction patterns, user behaviours, and past fraud incidents. To improve the security of UPI transactions, our method incorporates features including anomaly detection and pattern recognition. The usefulness of our model in reducing monetary losses and preserving user confidence in digital payment systems is demonstrated by experimental results that show a notable improvement in fraud detection rates when compared to conventional methods.
Authors: Bindela.Akhila -, Mr.C.Lakshminath Reddy -, Putluru Bhavana -, Chekka Anitha -, Bellary Jayasimha Raju -
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4409617170