Analytics is key to reducing money-laundering crimes
Since banks are the first and last line of defence when it comes to identifying money-laundering transactions, they need the right tools, in the form of advanced analytics, to assist them.
With an increasing number of corruption stories appearing in the South African press, matters that are often linked closely to issues of money-laundering, there is a clear and growing need for government and financial entities to take a closer look at ways to prevent this from happening.
The African continent as a whole has traditionally lagged developed markets in terms of promulgating legislation to combat money-laundering. And where there is legislation, enforcement is lacking, something that criminals have clearly taken advantage of.
However, says William Lawrence, Regional Practice Lead: Fraud and Financial Crimes at SAS, banks are facing increasing pressure from two main sources to get their systems and processes in order. Regulators are starting to take compliance seriously, as seen in the recent promulgation of a number of new laws. Furthermore, they are under increasing pressure from global financial markets to play their part in the fight against money-laundering.
"Banks are essentially the first and last line of defence when it comes to identifying money-laundering transactions. Increasingly, they are expected to implement controls and processes aimed at detecting and investigating suspicious activity. Some of the common challenges we see within banks include the issue of adequately verifying customers and screening them against sanctions lists and watch-lists, monitoring suspicious transactions and reporting transactions above a stipulated threshold," he says.
"But, these are not the only reasons why fraudulent transactions are going unnoticed. Remember that many banks still have departments that operate within silos, to the extent that, for example, the retail banking division may not have a clue what the business banking division is doing. This introduces the risk of missing direct and indirect links between a customer and another account with known links to organised crime."
Furthermore, adds Lawrence, while banks may have systems in place to detect suspicious activity, these systems tend to flag thousands of transactions a day, making it impossible for a compliance division, one with limited resources, to investigate every alert. This inevitably allows some criminal transactions to slip through the cracks.
"This is where advanced analytics can play a major role in fighting the growing concerns over money-laundering. As soon as a transaction enters the banking system, advanced analytics solutions like array processing will allow the organisation to monitor multiple risks during a single pass of data. This gives them the ability to process more transactions in less time, something that is particularly crucial in light of the fact that banks only have a short window during which to report suspicious activity to the regulator.
"Advanced analytics solutions are able to utilise very specific algorithms to subject every transaction to analytical processing. This, in turn, enables them to check for anomalous behaviour, screen customers against watch-lists and allow for the building of a single view of the customer, including how many direct and indirect links he or she has with other accounts in the bank," he continues.
And since all this happens behind the scenes, explains Lawrence, it occurs without annoying those customers who are conducting legitimate transactions, but whose activity might be erroneously flagged as suspicious. Instead, sophisticated analytical models within modern solutions are able to drill down into thousands of transactions and will only flag those with a high propensity for money-laundering and/or fraud. By increasing the integrity of the alerts, the number of transactions that need to be investigated are brought down to a more manageable level, thereby greatly improving detection accuracy.
"The fact that there are fewer false positives also reduces compliance costs, as investigators spend less time processing legitimate exceptions and more time focusing on high-risk events. With advanced analytics, banks can take a risk-based approach to monitoring transactions for illicit activity, using a combination of segmentation, behavioural and peer-based analytics techniques, leading to improved detection accuracy. With multiple detection methods and faster processing, banks can also monitor more risks in large data volumes in minutes.
"It is clear that legislation is taking the matter of money-laundering seriously; there is also a solid commitment by banks to deal with this crime. Once the right technology, in the form of advanced analytics, is added to the equation, we will have a perfect trifecta that will make life easier for the authorities, and conversely, much more difficult for the criminals," he concludes.