Artificial Intelligence Models for Fraud Detection: Advancements, Challenges, and Future Prospects

Fraud detection has become a critical challenge in various industries, from finance to e-commerce and healthcare.Traditional fraud detection methods are no longer sufficient to combat increasingly sophisticated fraudulent schemes.Artificial Intelligence (AI) provides a robust solution by leveraging advanced algorithms and learning models to analyze large volumes of data in real-time, identify hidden patterns, and adapt to new fraud tactics.This paper explores state-of-the-art AI models that are transforming fraud detection, focusing on machine learning, deep learning, generative models, reinforcement learning, federated learning, and hybrid approaches.We present the strengths, applications, and challenges associated with each model, followed by an overview of future directions in AI-driven fraud prevention.