Using Automation and AI to Combat Money Laundering

Money laundering, which is the criminal activity of processing criminal proceeds to disguise their origin is one of the gravest problems faced by the global economy, and its size is growing rapidly. It is estimated that 2- 5% of the global GDP or US$800 billion to US$2 trillion is being laundered every year across the globe. Banks have begun to understand that their legacy rules-based systems cannot effectively mitigate risks related to money laundering. There is a need to embrace advanced technology that can effectively solve their problems of getting involved in money laundering cases. This white paper outlines a case study focusing on the effectiveness and limitations of Artificial Intelligence (AI) in detecting and preventing money laundering activities. It will provide an overview of the design, architecture, implementation, and testing of such a strategy.