In today’s highly regulated financial environment, effective compliance is more important than ever. From anti-money laundering (AML) to know your customer (KYC) and beyond, businesses must be able to stay on top of the ever-tightening regulations in order to remain compliant and avoid costly fines, reputational damage and legal repercussions. The use of Artificial Intelligence (AI) is no exception. AI is now transforming financial crime compliance, enabling organisations to improve their compliance efforts in a number of ways:
Enhanced risk assessment
AI can help businesses identify and analyse potential compliance risks more quickly and accurately than ever before. By analysing vast amounts of data from multiple sources, AI-powered risk assessment solutions can identify patterns and anomalies that might otherwise go undetected. This can help businesses stay on top of emerging risks and take proactive steps to mitigate them.
Improved monitoring
One of the key challenges in compliance is monitoring transactions to identify suspicious activity. Traditional methods of transaction monitoring rely on rules-based systems that can result in large numbers of false positives, making it costly for compliance teams to sift through alerts to identify genuinely suspicious activity. AI driven machine learning transaction monitoring solutions, on the other hand, can learn from past transactions and identify patterns that indicate potential suspicious activity. This can help reduce false positives and ensure that compliance teams can focus their efforts where they are most needed.
Streamlined due diligence
KYC due diligence can be a time-consuming and resource-intensive process. AI-powered due diligence solutions can automate many of the tasks involved in KYC, including identity verification and risk assessment. This can help businesses to onboard new customers more quickly and efficiently, while still remaining compliant with regulatory requirements.
Faster investigations
When potential compliance issues arise, AI can help businesses investigate them more quickly and efficiently. By analysing large amounts of data and identifying potential links and patterns, AI-powered investigation tools can help compliance teams to identify the root causes of issues and take appropriate action to address them.
Overcoming risks and challenges to unlock the full potential of AI
The use of AI in fighting financial crime also presents challenges to ensure its responsible and equitable implementation. These include ethical considerations, for example, unrepresentative datasets that result in biases that skew machine learning models towards or against certain demographics, resulting in algorithmic discrimination; and practical considerations, such as the need for appropriate technical skills, rigorous testing, and tuning of models.
Regulators globally are united in requiring accountability, fairness, and transparency in AI use to mitigate the risks associated with inherent bias. Technological advances, combined with these ethical and moral considerations, have helped ensure the best AI-powered AML systems are now highly explainable, accountable, and user friendly. The integration of AI with human intelligence is essential to ensure ethical and compliant interpretation of outputs.
Napier’s newly published whitepaper- “AI Regulation: Global Approaches to Combat Money Laundering” enables compliance professionals to understand how AI regulations differ from jurisdiction to jurisdiction. It aims to help compliance teams understand the regulatory direction of travel, and to ensure they have the right governance in place to implement AI ethically. Get your copy here.
Photo by Sander Weeteling on Unsplash
