The impact of artificial intelligence requirements in preventing money laundering operations

Abstract

This research aims to explore the impact of artificial intelligence requirements on the prevention of money laundering operations, by analyzing the role of smart technologies in enhancing the capabilities of financial institutions to detect suspicious activities early and develop control methods. The research addresses artificial intelligence-based systems such as big data analysis, machine learning, and natural language processing, and their role in identifying unusual financial patterns that may indicate money laundering. By analyzing data from banks and financial institutions, the research highlights how artificial intelligence can improve monitoring and regulatory compliance processes, and reduce reliance on traditional manual examination. The research also addresses the challenges associated with the application of these technologies, such as costs and infrastructure, and recommends developing effective strategies for adopting artificial intelligence in the financial sector as part of global efforts to combat money laundering. The research finds that the use of artificial intelligence significantly enhances the ability of institutions to detect and identify illegal activities faster and more accurately, which contributes to reducing financial risks and achieving compliance with international laws.