The Force Awakens: Data Science in Banking

by Edward O'Brien 0

Digital data has snowballed, with the proliferation of the internet, smartphones and other devices. Companies and governments alike recognise the massive potential in using this information – also known as “big data” – to drive real value for customers, and improve efficiency.

Big data could transform businesses and economies, but the real game changer is data science.

Data science goes beyond traditional statistics to extract actionable insights from information – not just the sort of information you might find in a spreadsheet, but everything from emails and phone calls to text, images, video, social media data streaming, internet searches, GPS locations and computer logs.

With powerful new techniques, including complex machine-learning algorithms, data science enables us to process data better, faster and cheaper than ever before.

We’re already seeing significant benefits of this – in areas such as national security, business intelligence (BI), law enforcement, financial analysis, health care and disaster preparedness. From location analytics to predictive marketing to cognitive computing, the array of possibilities is overwhelming, sometimes even life-saving. The New York City Fire Department, for example, was one of the earlier success stories of using data science to proactively identify buildings most at risk from fire.

Banking: unleashing the power of big data

For banks – in an era when banking is becoming commoditised – the mining of big data provides a massive opportunity to stand out from the competition. Every banking transaction is a nugget of data, so the industry sits on vast stores of information.

By using data science to collect and analyse big data, banks can improve, or reinvent, nearly every aspect of banking. Data science can enable hyper-targeted marketing, optimised transaction processing, personalised wealth management advice and more – the potential is endless.

A large proportion of the current big data projects in banking revolve around customers – driving sales, boosting retention, improving service, and identifying needs, so the right offers can be served up at the right time.

The power of digital data, data science, and analytics continues to be discussed within the “C” suites of leading financial institutions and fintech providers. For today’s retail banks and credit unions, much of their immediate attention is being made on customer and predictive analytics to provide insight into such areas as identifying next-best-product-to-offer and ideal customer and member profiles. One potential challenge to consider is how such data is being used. Legal and compliance teams are working hard to define how, when, and whether such data should be used, so there are no unintended biases introduced into client outreach initiatives and pre-screened offers.

Overview by Ed O’Brien, Director, Banking Channels Advisory Service at Mercator Advisory Group

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