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How to Use AI to Combat Money Laundering

Financial fraud and compliance are reaching a critical point. As criminals get more sophisticated with each passing year, financial institutions also need to make the most out of emerging technologies to stay one step ahead of bad actors.

Traditional Anti-Money Laundering (AML) systems are no longer cutting it when it comes to combating financial crime, with many detection systems providing inaccurate results due to outdated rules or thresholds. In fact, for AML alerts, a high false-positive rate is the norm.

As a result, many institutions are adopting AI-driven technologies to help them with their AML efforts.

How AI detects money laundering

AI tools can detect money laundering in several different ways by using specialised algorithms. Essentially, these algorithms analyse vast pools of data and raise a red flag if something is found such as unusual transactions or account activity that could be considered suspicious.

There are a few ways AI can spot suspicious behaviour. Firstly, AI can analyse customers’ transaction behaviour to make predictions about that user in the future. This system becomes sensitive to changes in behaviour, no matter how subtle, and can flag any suspicious changes in behaviour that could be missed by traditional AML systems.

AI can also enhance the customer due diligence and know your customer processes, allowing both of these to be carried out faster and in more detail. AI can provide financial institutions with a greater range of customer data for AML purposes that can be used in risk assessments, suspicious activity reports, and in the case of investigations.

One aspect of using AI in AML that makes its adoption a no-brainer is its ability to automatically generate suspicious activity reports. Before these reports are submitted to the relevant authorities, they go through an internal reporting process. Algorithms can be used to pre-fill reports with relevant data and to standardise language and terminology, saving AML employees valuable time when dealing with possibly suspicious activity.

Plus, AI can be leveraged by financial institutions to manage their vast amounts of unstructured data. To be AML compliant, banks need to be able to analyse their unstructured data as part of transaction monitoring, sanctions screening, and more, and this is made much easier with AI.

Stay ahead in the race against financial crime with Eastnets

With Eastnets SafeWatch AML, you can detect and block money laundering and suspicious activity in a heartbeat. In fact, our AML and counter-terrorism suite of solutions are chosen and trusted by more than 600 financial organisations around the world.

With our always-on technology, you can stop money launderers in their tracks as the crime is carried out, in real-time and offline. We use AI to monitor historic transactions and social relationships between accounts to create an AI-driven risk score. Our solution also leverages the power of AI models in the refinement of AML rules to reduce false positives significantly.

If you want to adopt next-level behavioural monitoring for your financial institution, get in touch to request a demo here.


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