Abstract

In today’s rapidly evolving financial landscape, the adoption of Artificial Intelligence (AI) and Machine Learning (ML) technologies, coupled with the deployment of Business Rules Management Systems (BRMS), has transformed how financial transactions are conducted, monitored, and secured. With fraud, particularly in check deposit transactions, becoming increasingly sophisticated, financial institutions are turning to AI and ML to enhance their risk management strategies. This paper explores the integration of AI-driven models and business rules in financial transactions, focusing on their application in fraud detection and prevention. We also examine the associated challenges, such as data privacy, ethical concerns, and the need for regulatory frameworks, while outlining the opportunities that lie ahead for future financial innovation.