Unified Payments Interface (UPI) transactions require advanced technologies for rapid and accurate fraud detection. UPI systems face threats such as phishing, spoofing, and unauthorized access as digital payments expand. Effective detection leverages machine learning, behavioral analytics, and real-time monitoring to analyze transaction patterns, user behavior, and device data. This study develops a secure cryptographic model using the Weighted Hyperbolic Curve Cryptography (WHCC) approach for UPI scam detection in web applications. The WHCC model efficiently monitors transactions by evaluating key attributes. Simulation results indicate a high transaction score of 0.91, demonstrating its effectiveness in fraud prevention.