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.
While banks have historically been good at running analytics at a product level, such as credit cards, or mortgages, very few have done so holistically, looking across inter-connected customer relationships that could offer a business opportunity - say when an individual customer works for, supplies or purchases from a company that is also a client of the bank. The evolving field of data science facilitates this seamless view.
Our team of experts in Big Data technologies and BI will help to identify your Big Data problem and assist you in setting up a proof of concept in your datacenter or on the cloud.
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