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Banking on big data

Tackling bank's big data challenges with high-performance analytics

The dual impact of a slow global economic recovery combined with a significantly increased regulatory and compliance burden are causing banks to squeeze the last penny from every dollar as they look to reduce cost-to-income ratios to around 40 percent. The IDC predicts 2012 cost reductions of 30 percent or more for some banks.

According to the same IDC report, more than 40 percent of banks will ramp up to launch big data and analytics business and technology strategies. It’s important to understand that aging technology presents problems related not only to reliability and speed. Many aspects of the business are placed at risk by a poorly performing computing foundation.

David Wallace, Global Financial Services Marketing Manager at SAS, says “In the slow-growth economic environment, banks must improve their batting average by getting a hit every time they step up to the plate. Banks have the data that will help them do this. The key is to gain rapid insights from the data to achieve their goals.”

The answer lies in turbocharging your technology foundation with high-performance analytics. Turbocharging delivers the same result you would see with an automobile – more speed and greater efficiency. Faster analytics means your predictive modeling results won’t just get delivered more quickly – with optimization techniques, you’ll be able to identify the best future action to take considering both financial and organizational constraints. The result? The best opportunity to grow revenue at the lowest cost, leading to increased ROI.

Consider the perspective of Howard Rubin: “In 2006, the average financial services company required 1 .29 million instructions per second (MIPS) and .53 physical servers to support the processing needed for each $1 million in net revenue. At the close of 2010, the 1 .29 MIPS had increased by 38 percent, to 1 .79 MIPS, and the .53 physical servers increased by 46 percent, to .77 physical servers. During the same period, net revenue itself grew at a far slower rate (less than 19 percent). In general, the need for computing power is growing two-times to five-times faster than revenue.”

The bottom line: Your IT infrastructure should not impose constraints for analytics. If you manage your big data the right way, you will have the opportunity for incredible business advantage.

By using high-performance analytics, banks can:

  • Achieve better operational efficiency, which improves IT while reducing spending.
  • Acquire and retain profitable customers by delivering higher value.
  • Improve risk management – market, credit, liquidity and firmwide.
  • Strengthen the integration of social media with business processes and decision making.
  • Differentiate and innovate to stand out in the marketplace.

Download this free white paper to help you understand more of the capabilities of high-performance analytics. You can also take a look at how some key banks are putting high-performance analytics to work.

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One Trackback

  1. By Banking on big data - Part II - Risk Management on March 14, 2012 at 9:01 am

    [...] my previous post, I talked about the amazing value of high-performance analytics (HPA) for tackling the enormous [...]

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