The Application of Artificial Intelligence in Combating Money Laundering

This article examines the application of artificial intelligence (AI) in detecting and combating money laundering within financial and banking systems. With the advancement of digital banking, money laundering techniques have become more complex, and AI has emerged as an effective tool for identifying criminal behaviors. The article introduces different types of AI, including Narrow AI (ANI), General AI (AGI), and Super AI (ASI), and evaluates their capabilities in predicting suspicious activities. It highlights the use of advanced algorithms such as neural networks and anti-money laundering (AML) models based on rule-based systems and transaction flow analysis, enabling the identification of transactional correlations. Furthermore, the stages of money laundering placement, layering, and integration are analyzed, along with AI-related challenges in monitoring transactions. The findings indicate that AI improves the security and efficiency of banking systems, reduces the risks associated with money laundering, and enhances public trust. By presenting successful case studies, this article encourages financial institutions to develop more advanced systems for combating money laundering effectively.

The Application of Artificial Intelligence in Combating Money Laundering Keywords:

Money Laundering , Artificial Intelligence , Anti-Money Laundering , Prevention