Sarcouncil Journal of Engineering and Computer Sciences

Abstract: This article explores the transformative role of artificial intelligence in combating financial crimes related to child exploitation materials. By exploring how AI-enhanced systems revolutionize transaction monitoring, customer due diligence, and suspicious activity reporting within financial institutions, the article demonstrates how advanced algorithms, machine learning models, and natural language processing enable the detection of subtle transaction patterns that traditional systems fail to identify. The article analyzes implementation challenges, including data privacy concerns, false positive management, and balancing automation with human oversight, while addressing ethical considerations in AI deployment. Drawing from authoritative sources, including FATF reports and scholarly research, the article outlines emerging trends in cross-institutional collaboration through federated learning approaches and graph-based analytics that significantly improve detection capabilities without compromising data privacy. The findings suggest that a holistic approach integrating financial intelligence across multiple stakeholders offers the most promising path forward in disrupting the financial networks that enable child exploitation.