Fraud Detection in Payments Using Artificial Intelligence

This research paper explores the role of Artificial Intelligence (AI) in detecting and preventing fraud in digital payment systems. With the rapid growth of online transactions, fraudulent activities such as stolen card fraud, account takeover, identity theft, phishing, and spoofing have become major concerns. The paper discusses how AI-powered techniques including Machine Learning, Logistic Regression, Decision Trees, Random Forest, and Naive Bayes can be used to identify suspicious transaction patterns and improve fraud detection accuracy. It also highlights the importance of data mining, real-time monitoring, and advanced anomaly detection methods in strengthening digital payment security. The study concludes that AI has significant potential to reduce financial losses, improve trust in digital transactions, and enhance the overall security of the digital payment ecosystem.