Organized fraudsters love the big data battle because – for many organizations – siloed data and too much data make finding fraud as difficult as finding the same needle in a new haystack. Ellen Joyner says firms can bring big data and organized fraudsters down to size with a layered analytics approach combined with high-performance computing.
The challenge to accomplishing something big – really big – is often getting the right people on board from the beginning. Tham Ming Soong, former United Overseas Bank CRO, talks with SAS CEO Jim Goodnight about UOB’s success with big data and high-performance analytics.
Financial institutions now need to execute risk management decisions in a more timely manner.This GARP Webcast – presented by SAS – will examine the new technology paradigms that are enabling more timely financial risk management practices.
What do you get when you combine big data with high-performance analytics? Big ideas that lead to big changes. In short, a seismic revolution that’s changing the way the world works.
Using high-performance analytics, banks can turn their big data into pertinent new business insights that guide faster, better decisions. Here are some examples of how key banks are acheiving results by pairing advanced analytics with turbocharged technology – high-performance analytics.
Olivia Rud, respected BI thought leader and author, spoke at the IFSUG Summit about the speed of technological changes and the volume and complexity of data that industry practitioners are now dealing with. Predictive analytics was the tool of choice when desktop computing was state-of-the-art and is still cutting edge now that big data from mobile and social threatens organizations.
The banking sector routinely manages big data, which means big challenges – but also big opportunities. Using high-performance analytics, banks can turn their big data into pertinent new business insights that guide faster, better decisions. As a result, banks can successfully manage risk, retain profitable customers, improve operational efficiency and differentiate themselves in the marketplace for competitive advantage.
In risk management, the time table for decision-making gets shorter and shorter as the volume and velocity of data expands. With no room for error, how can firms deal with big data effectively? Alison Bolen says, “Samsung Securities gets it.” Read the ninth post in her “HPA once a day” series to learn what Samsung Securities is doing and how you can apply it to your big data problem.
Fraud remains a huge problem around the globe, and Canada is no exception. According to a recent study of more than 1000 senior Canadian business executives, even though 80 percent felt that fraud prevention and detection were a priority, only 9 percent are using business analytics software effectively to help detect fraud! Without analytics, how are you finding and stopping fraud?
Today’s corporate and personal economies are far more technology-intense than in 1980, and the overall technology economy is growing even as the global economy stagnates. This article from Dr. Howard Rubin in Wall Street &Technology explores the need for growth in technology spending as revenues remain steady.
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