The role of AI and machine learning in fraud detection and financial security

Abstract

This technical article explores the transformative role of artificial intelligence and machine learning technologies in strengthening financial security frameworks and combating fraudulent activities across digital platforms. As financial transactions increasingly migrate to digital environments, traditional security measures prove inadequate against sophisticated fraud tactics. The article examines how AI-driven solutions leverage behavioral analytics, anomaly detection, and biometric authentication to create adaptive security systems that continuously evolve against emerging threats. By analyzing implementation strategies across major financial networks including credit card processors, mobile banking platforms, and cryptocurrency exchanges, the article provides a comprehensive overview of current applications while highlighting the challenges and opportunities that will shape the future landscape of financial security. Furthermore, the article identifies critical research priorities including quantum-resistant algorithms, federated learning approaches, explainable AI methodologies, and human-AI collaboration frameworks that will define the next generation of financial security systems in an increasingly complex threat environment.