Unified Payments Interface Fraud Detection using Machine Learning
DOI:
https://doi.org/10.15680/IJCTECE.2026.0902007Keywords:
UPI fraud detection, machine learning, digital payments, financial security, fraud prediction, transaction analysis, real-time detection, cybersecurity, artificial intelligence, database integrationAbstract
Digital Payment Systems Have Become A Regular Part Of Everyday Life, And Upi Is One Of The Most Popular Methods Because It Makes Transactions Quick And Easy. As The Number Of Online Transactions Continues To Grow, Fraud Activities Have Also Increased, Creating Serious Concerns About Security And User Trust. This Project Aims To Develop a UPI Fraud Detection System That Helps Identify Suspicious Transactions and Reduce the Risk of Financial Fraud Using Machine learning Techniques. The System Works by Analysing Transaction Details Such As Transaction Amount, Sender and Receiver Information, and Transaction Patterns. Based On These Details, The Model Predicts Whether A Transaction Is Genuine Or Potentially Fraud. A Backend Can Developed Using Modern Web Technologies Handles Data Processing, Prediction, And Database Management, While The Frontend Provides A Simple Interface For Users To Register, Log In, And Perform Fraud Checks Easily. The System Also Stores Transaction Information for Future Analysis and Monitoring. Machine Learning With a Practical Web-Based Application, This Project Provides A Simple And Effective Approach To Improving The Security Of UPI Payments. The Main Goal Is To Show What Intelligent Systems Can Support Safer Digital Transactions And Help Users Feel More Confident While Using Online Payment Platforms.References
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