BI can be used to prevent money laundering

Analytics tools have grown more sophisticated in recent years. This trend has not gone unnoticed by creative IT users, who have developed several unique and powerful uses for the systems. According to Sourcing Focus contributor Simon Asplen-Taylor, the financial industry could have a vital new role for business intelligence software – the fight against money laundering fraud.

Financial accountability through data

New big data analytics processes designed to extract meaningful information from social networks could be among the tools that fight money laundering, according to Asplen-Taylor. He noted that with such systems, eyed by marketers to personalize customer recommendations, bankers could make meaningful links between an account-holder’s financial history and personal data such as employment and personal events.

Asplen-Taylor specified that the way to ensure criminals are caught and unimportant activity is ignored is based on a concept much desired in modern analytics use – a single, unified view of each customer. He suggested that uniting all of a customer’s accounts under one banner i s the first step toward this clarity, the second consisting of adding new but unorthodox data sources through high-powered analytics.

While banks could fight crime through big data, the revolution has not yet started. According to Asplen-Taylor, this is because institutions are thinking on a case-by-case tactical level rather than in terms of overarching strategy. He argued that business intelligence backed by long term plans could grant an edge to its adopters.

Beyond fraud

According to a Computing report, financial institutions have a variety of plans for big data analytics, not all of which are meant to catch criminals. The source stated that some banks hope to use data the same way retailers do – to sell goods and services to the customers most prone to buying them. In the case of financial institutions, the desired effect is an increase in credit card usage. Much like a store, banks can offer tailored promotions. Lenders can even team up with retailers to present mutually beneficial options.

Whether weeding criminals out of the system or making sure customers spend at a certain rate, big data can assist financial institutions. Always privy to  a vast array of numerical data, banks can now synthesize that knowledge with more esoteric facts from a wide variety of sources.

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