Covering Disruptive Technology Powering Business in The Digital Age

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The Force Awakens: Data Science in Banking
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March 3, 2016

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, 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, optimized transaction processing, personalized 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.

Banks can model their clients’ financial performance on multiple data sources and scenarios. Data science can also help strengthen risk management in areas such as cards fraud detection, financial crime compliance, credit scoring, stress-testing and cyber analytics.

The promise of Big Data is even greater than this, however, potentially opening up whole new frontiers in financial services.

Over 1.7 billion people with mobile phones are currently excluded from the formal financial system. This makes them invisible to credit bureaus, but they are increasingly becoming discoverable through their mobile footprint. Several innovative FinTech firms have already started building predictive models using this type of unconventional data to assess credit risk and provide new types of financing.

This article was originally published mis-asia.com and can be viewed in full here

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