The Use of Artificial Intelligence in Anti-Money Laundering (AML)

Money Laundering has affected the entire world from its beginning. Financial institutions were threatened by the act of money laundering worldwide. This research study discusses how Artificial Intelligence (AI) can be used to fight against money laundering and also discusses about the three stages of money laundering and the use of AI technologies in these stages to combat the effect of money laundering. Further, this study discusses about the technologies such as Machine Learning (ML), Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) to fight against money laundering. Further, this research study elaborates on how AI can help in establishing effective Anti-Money Laundering (AML) system, which consists of Know Your Customer (KYC), risk management, customer due diligence, and transaction monitoring. This research study discusses about the challenges that outburst while using AI. The challenges encountered are inadequate data concerns, the requirement of a skilled workforce, and the risk of failure and inclination. Further, it also provides possible suggestions for the challenges, such as peril-based technique, incorporation of KYC data, uninterrupted surveillance, and human supervision. Finally, this study concludes by stating the substantial possibility of AI in improving the AML process by detecting and preventing money laundering activities.