Data analytics 'a key part of bank AML processes'

Of the many technologies and processes available to help financial institutions (FIs) in their anti-money laundering (AML) efforts, one of the most valuable is big data analytics.
 
That's according to Rasha Abdel Jalil, business analyst and project manager at financial services solutions provider EastNets. In an article for Bobsguide, she explored how data analytics and visualisation are revolutionising AML.
 
Many FIs now view big data analytics as an essential tool in tracking money laundering activities, according to Ms Jalil.
 
Regulatory demands mean that banks and other financial services organisations must take a rigorous approach to acquiring the right information about their customers. This occurs as part of the onboarding process but is also an ongoing practice, with databases requiring consistent updating to ensure the information is accurate.
 
This data collection and maintenance is obligatory from an AML and know-your-customer compliance perspective, but Ms Jalil pointed out that businesses can also see it as an opportunity to strengthen their position in a competitive marketplace.
 
"While collecting customer information is a mandatory obligation for FIs for regulatory purposes, banks should extend this process to their advantage, since customer information gives them an edge and a possible competitive advantage," she explained.
 
"This can be achieved by categorising the client's information on different layers based on several criteria to understand thoroughly the distribution and the type of clients."
 
Ms Jalil also emphasised the importance of good data visualisation, which can be achieved through the use of systems to access the most relevant, targeted information at the right time. This addresses the problem of trying to gain relevant or valuable insights from large amounts of raw data.
 
As well as making it easier for companies of all kinds to better understand and engage with their customers, data analytics holds significant potential for business functions such as supply chain risk management and marketing strategy.

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