In today's business landscape the role of digital payments is getting more attractive not only to end-users but also to the cybercriminals. Fraudulent activities have grown more intricate and pervasive in our interconnected world. Ranging from credit card frauds and identity thefts to insurance and health care frauds, these actions have significant economic and social repercussions. Consequently, mitigating reputational risk and ensuring regulatory compliance have consistently been top priorities for banking and financial institutions. The purpose of this study is to examine the effect of Artificial Intelligence (AI) in supporting anti-fraud strategy for fraud detection and prevention, concerning the online payment frauds, in the banking industry.

This study aims to find out the pervasive payment frauds and the prevention methods along with understanding the significance and capabilities of AI-based Anti-Fraud Management Systems (AFMS). Employing a mixed-methods approach that synthesizes literature reviews, expert interviews, and surveys, this study not only identifies but also evaluates the practical applications of these AI technologies and also compares the AI methods with the traditional fraud detection techniques and addresses some key success factors (challenges) involved in their implementation within the banking industry.