Conservative estimates put the percentage of illicit transactions, that are stopped, at 1%. Though regulatory authorities have levied heavy fines on global banking conglomerates, there is still a lot that slips through the cracks – estimated at 5% of global GDP.

On the other hand, AML processes already consume a large number of resources – manpower, capital, hardware, etc. Typically, AML functions are based on rules, and these methods, do little to alleviate pain points.

To complicate matters further, authorities are now pressuring banks and other FIs to adopt more sophisticated analytics in their workflows. But this could very well be a blessing in disguise, as older rule-based systems are known to generate large amounts of false positives.

To infinity, and beyond

Moving to a technologically advanced system can greatly reduce the time spent in investigating false leads, and offer a flexible platform that grows with changing regulations, and simultaneously adapts to new modes of money-laundering. Artificial Intelligence and Machine Learning can help enhance, automate and identify fraudulent transactions and money laundering activities.

In any system, the alerts themselves do not drive up costs. However, the investigations based on false positives may lead to multiple SAR filings, that in turn become an expensive affair for any organization. Furthermore, pattern recognition algorithms can understand the big picture, connect fraudulent transactions and bridge the gap between human-understanding and compliance.

With digitization of economies, there are increasingly innovative methods of money laundering which may not fulfill parameters matching previous dubious transactions. In such a case, a system with the ability to detect anomalies and intelligently assign a risk index, can save time, and cost of compliance.

Turning ideas into reality

The industry is now pivoting, with many banks rethinking their approach to KYC and AML. With numerous tech startups offering a range of FinTech products, barriers are always crumbling, and the benefits quickly become too obvious to ignore. As pioneering banks are finding out, artificial intelligence and machine learning are for AML are at that point.

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