Artificial Intelligence in the Fight Against Cyber Fraud: Challenges, Advances, and Future Directions

Abstract

Cyber fraud is exploding, literally. Digital finance's boom has just made us even more vulnerable, meaning we desperately need security systems that are not just smart, but truly adaptive. Thankfully, Artificial Intelligence (AI) has emerged as our strongest defense here, capable of real-time fraud detection, spotting anomalies, and even predicting what's coming next. This isn't just another look at AI; we're diving deep into the actual techniques that have tackled cyber fraud over the last ten years. That means exploring everything from supervised and unsupervised learning to the nuances of deep learning and hybrid methods. You'll see what really works from real-world datasets, and we'll unpack why certain models shine. We're even laying out a fresh framework designed to seriously boost both performance and transparency. Of course, the path isn't smooth. We tackle the tough stuff: adversarial attacks, those tricky model biases, and the big ethical questions. And as for what's next? We’ve charted the most exciting paths forward, highlighting where explainable AI, federated learning, and genuine ethical compliance will be game-changers. Consider this your essential guide if you're a researcher, developer, or policymaker committed to locking down our digital world with AI.