New Ripjar Research Reveals Widespread Adoption of GenAI for Anti-Money Laundering Screening and Monitoring

Ripjar, a leading provider for monitoring and investigating threats, risks and criminal activity, has today launched new research which reveals that over 60% of compliance teams anticipate widespread adoption of Generative AI (GenAI) for customer Anti-Money Laundering (AML) screening and monitoring within their organisation in the next two years. This trend highlights a significant shift in the industry to draw on more advanced technologies enhancing compliance processes and addressing challenges in financial crime prevention.

The findings highlight many benefits to the increased usage of GenAI in compliance teams. Looking ahead, an eye-catching 98% of compliance leaders anticipate a significant reduction in false positives due to GenAI, underpinning its potential to enhance accuracy and efficiency in compliance processes.

The most prominent application of GenAI in customer screening and monitoring, according to the research, is case management and decision support (37%), closely followed by contextual analysis of names (35%). Similarly, 35% of compliance teams use, or want to use it, to support investigations. The range of applications demonstrates the versatility of GenAI in addressing complex compliance challenges. 

In addition, Ripjar identified several key benefits of using GenAI in compliance for sanction screening, adverse media and PEP checks. Half of compliance (50%) teams emphasised increased efficiency as a main benefit and improved accuracy (48%) and enhanced risk discovery (47%) closely followed. Notably, 44% of participants also highlighted cost reduction and 50% cited significant time saving, demonstrating that the advantages of GenAI extend beyond just speed and ease of work. 

Gabriel Hopkins, Chief Product Officer at Ripjar says: “While there are structural issues to navigate, it is fantastic to see such broad consensus that GenAI offers a transformative opportunity for many areas in compliance, particularly in the fight against money laundering and terrorist financing. With its ability to enhance efficiency, improve accuracy and reduce false positives, GenAI is poised to change how compliance teams approach critical tasks such as extended customer due diligence. With the right support, these new technologies promise a future for compliance that is both more efficient – consuming fewer resources – and more effective – uncovering more true risk. 

 “We will encounter challenges as banks and financial organisations grapple with the best approach to adoption, particularly due to concerns about predictability and explainability in regulated environments. Further clarity from regulators will help to support organisations on the journey. Savvy organisations are planning now for how they can leverage the latest techniques to transform their approaches to compliance. The best solutions will combine different AI and machine learning techniques with the finely honed capabilities of traditional human-led compliance teams, ensuring a balanced and responsible approach.”