Trust the Machine and Embrace Artificial Intelligence (AI) to Combat Money Laundering Activities

The research work is focused on examining the role of artificial intelligence (AI) in addressing challenges associated with money laundering in the banking sector. Money laundering is a global issue that threatens financial stability and international security, making anti-money laundering research crucial. Furthermore, just 0.2% of money laundered through the financial system is estimated to be seized. The crime is growing increasingly sophisticated and intricate, and the amount of the crime increases banks’ vulnerability. Researchers have begun to investigate the possibility of artificial intelligence approaches in this setting. However, a thorough assessment has identified a systematic knowledge deficit that systematically examines and synthesizes artificial intelligence techniques for anti-money laundering efforts in the banking industry. Therefore, this chapter is focused on a systematic review of key technologies categorized into artificial intelligence or machine learning (AI or ML), natural language processing (NLP), robotic process automation (RPA), and cloud-based solutions. However, various challenges concerned with these techniques, such as data quality, the nature of money laundering and data volume, and data heterogeneity, are also discussed. As a result, the findings add to the total knowledge base in anti-money laundering from the banking sector’s perspective. Additionally, future study directions were narrowed even further based on the limitations discovered.