With terrorist attacks on the rise, any legislation that creates a more hostile environment for the funding behind them must be welcomed.
The problem is, however much due diligence and additional risk assessment the new legislation introduces, it cannot be relied on to solve illicit money flows once and for all.
The level of sophistication that today’s terrorists and criminal organisations use to launder their money is frightening, and while the new legislation is a step in the right direction strategically, operationally the average company or financial institution is light years behind the techniques being employed by terrorist networks.
The transactional ecosystems within which criminals and terrorists hide their funds are so complex and vast that, manually, they can be near impossible to identify. The flow of illicit funds is often hidden in plain sight.
Red flags and all-important anomalies can often only be identified through the analysis of billions of financial transactions and broader datasets in real time.
This is beyond the limits of human intelligence, let alone conventional compliance, and can only be achieved through big data technologies that are enhanced by machine learning.
Effective anti-money laundering (AML) and combating the financing of terrorism (CFT) require not just tougher legislation but big data and machine learning-powered tools that can identify transactional patterns a human would never spot.
While lowering the cash payment threshold above which customer identification is required could be a deterrent for some criminals, without the ability to analyse and integrate billions of data points from multiple sources to detect criminal behaviours, this could result in an increased burden of false positives.
False positives are the results of investigations on perfectly legitimate customers, accounts or transactions that seem criminal but which, after a huge amount of time and money spent investigating them, prove to be perfectly innocent. They are the single biggest obstacle in the financial fight against terror.
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