Enhancing Fraud Detection With AI in International Systems
Mustafa Kayyali · Advances in computational intelligence and robotics book series · 2025
Fraud, in its evolving digital forms, poses an immense challenge to global financial stability. This chapter explores how artificial intelligence, particularly machine learning, is reshaping the way fraud is detected and prevented across international financial systems. By tracing the shift from traditional rule-based approaches to dynamic, data-driven methods, the authors examine the integration of AI tools within diverse accounting frameworks. The chapter also navigates the ethical and legal complexities surrounding algorithmic oversight and cross-border data governance. In doing so, it presents a critical look at both the promise and peril of relying on intelligent systems in a domain as sensitive as financial integrity. Ultimately, this work advocates for a balanced, collaborative future—where innovation in fraud detection is met with global regulatory alignment and a firm commitment to transparency.