AI-Driven Fraud Detection in Financial Transactions: Techniques and Applications
Abstract
This paper explores the role of artificial intelligence in combating fraud within financial systems. It examines AI techniques such as anomaly detection, natural language processing (NLP), and predictive analytics to identify fraudulent activities in real-time. The study presents examples of AI-based fraud detection systems used in payment gateways, online banking, and insurance claims. By leveraging historical transaction data and behavioral patterns, these systems significantly enhance detection accuracy and reduce false positives. The paper also discusses challenges such as adversarial AI attacks and the need for robust data governance.
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