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.
Consider the number of decisions your firm makes everyday. How long does it take to ensure that those are the right decisions? You see, it’s not just about making decisions faster, it’s about the assurance of making the right decisions fast. Oliver Schabenberger, Lead Architect of SAS High Performance Analytics, says, “We’re solving business problems that have performance issues in such a way that we not only make them faster, but also make transformational change, from hours to seconds and from minutes to seconds.”
Starting in 2007, according to IDC, the amount of data captured and replicated worldwide outgrew our storage capacity. The data – and that gap – have been growing exponentially ever since. How are financial services firms handling the big data problem?
Dr. Howard Rubin gives a high-level assessment of the cost of data, both to financial services firms and to organizations at large. His assessment brings home the ringing statement, “It’s the data, stupid.” Does your firm value its data as a corporate asset?