Next-Generation Fraud Detection System Using AI And Blockchain for Real-Time Monitoring and Payment Integrity

Abstract

The increasing use of digital payment platforms has led to a rapid rise in financial frauds, making traditional detection systems less effective against modern attack patterns. To address this issue, this work presents a system that combines Artificial Intelligence, Explainable AI, and Blockchain into a single framework for secure and transparent fraud detection. The system is designed to analyze transactions in real time, identify suspicious activities, and maintain a tamper-proof record of decisions. The proposed system processes each transaction through an AI-based analysis module that generates a risk score. Based on this score, transactions are either approved or flagged for review. Along with the prediction, an explainability layer provides clear reasons behind each decision, improving system transparency. To ensure trust and auditability, all important transaction evidence is stored securely, with its integrity protected through blockchain-based hashing. The system also includes an interactive dashboard that allows users to monitor transaction activity, view analytics, and understand system behavior visually. Screens such as live analytics, transaction flow visualization, and performance metrics help in better understanding and managing fraud detection processes. Overall, the system focuses on delivering a practical, user-friendly, and secure solution that not only detects fraud but also builds trust through transparency and verifiable records.