Banking on Analytics

How High-Performance Analytics Tackle Big Data Challenges in Banking

As part of what Howard Rubin calls the most data-intensive economic sector in the world,1 financial services leaders know what big data is all about. Consider the astounding volumes of financial transactions that banks have managed for years – combined with vast customer, operational and regulatory data surging from multiple sources. It’s no wonder that 92 percent of the cost of business for financial services firms is data.2

What needs to be done with all that data? Clearly, operating from day to day requires banks to acquire, distribute, process, store, retrieve and deliver data that’s spread across multiple formats and locations. But going forward, banks must move well beyond those basics.

Soon, you will need to be able to quickly and effectively tap into and analyze every bit of available data – structured and unstructured alike – to make good decisions that strengthen and advance the business. More specifically, you’ll need to understand behavior and risk exposure at the customer level, across all touch points. Stay ahead of global competitors. Find the optimal channel mix for your customers. Replace or supplement traditional revenues with enticing new products and expand into new regions. Improve operational efficiencies. And adhere to a multitude of new regulatory requirements – 250 new ones alone stemming from 11 different regulatory bodies, just for the Dodd-Frank Act alone. Read More