Big Data: A Big Deal
Big wave surfers ride waves at least six meters high. A wipeout could send them 15 meters below the punishing surface. Tossed about, they have around 20 seconds to get to the surface for air before the next wave hits. Those who ride these monster waves find a reward inaccessible to the hesitant.
Finance professionals need to be open-minded and willing to engage with the CIO on the benefits of budget channeled to Big Data capability
Big Data analytics is that huge wave. It’s a fast-moving body of fluid technological power, that’s changing the landscape of everything that drives human life. This process examines large amounts of data to uncover hidden patterns, correlations and insights. For decades businesses ran manual analyses to gather information through slow and inefficient traditional business intelligence solutions. Now, many are setting out to ride the Big Data analytic capability wave, so identifying radical new insights with unprecedented speed. Efficiencies, responsiveness, dexterity and a competitive edge as yet unseen, are up for grabs.
Big Data analysis is an infinity mirror. Both structured and unstructured data can be being quickly mined in an endless number of permutations and combinations. The outputs are staggering in depth and we’ve only skimmed the surface.
Our business services millions of lives. Data is my world. As a CFO, I have first-hand experience of both the benefits that this sort of capability offers as well as the risks. There is a continued healthy tension between IT and Finance around budgets, capital IT spend and innovation spend. Finance professionals need to be open-minded and willing to engage with the CIO on the benefits of budget channeled to Big Data capability.
We’ve purchased high-performance data warehousing software and an external Risk Rating Tool, which was integrated into the company environment recently and brought tremendous, advanced analytics applications and returns. The system’s capabilities include data exploration, data transformation, statistical model building, testing, and scoring - to produce forensics reports. Now, day-to-day data mining and predictive analytics happens within seconds or, at most, a few minutes (some past data extractions took more than 12 hours to run).
I have seen the results having consistent and significant increase in the volume of potential fraud cases exposed for investigation. Migrating to the externally acquired Risk Rating tool onto our own database, we have been able to assess thousands of providers for fraud-risk through 26 measures that give us a score, almost instantaneously. Our Forensic Investigations Unit’s projects are prioritized based on these scores, saving time and resources. The recovery of funds lost to fraud and our ROI have both significantly outpaced expectations–in at 30 million dollars per year.
We have also partnered with a global Big Data software and systems provider to implement a Big Data Warehouse that will enable the collection of massive volumes of structured and unstructured data and the curation of data into an analytics-ready asset a fully integrated stack of open-source components, tailored for enterprise usage.
My advice? Invest in and develop sophisticated software, and statistical tools to support your businesses. Used in a responsible and confidential manner to create products and value for the consumer in a seamless offering, as Big Data is forming the backbone of future business.