Guest Blog Feature | Big data brings its own set of risks

This NICSA News guest blog feature was written by Ed Marcarelli, Hydrakos Consulting and the NICSA Technology Committee.

Intermediary OversightIn his recent book, The Signal and the Noise:  Why So Many Predictions Fail – but Some Don’t , Nate Silver looks at the use of Big Data in predictive analytics.  Among the many insightful observations is “Data-driven predictions can succeed- and they can fail.  It is when we deny our role in the process that the odds of failure rise.” 

The implications for financial services and other firms were made clear in a recent Wall Street Journal article “The Risks of Big Data for Companies” authored by John Jordon, a professor at the Smeal College of Business at Penn State University. Dr. Jordon looks at the risks inherent in the actions companies take to make meaningful use of Big Data. He points out: “…in our rush to embrace the possibilities of big data, we may be overlooking the challenges that big data poses—including the way companies interpret the information, manage the politics of data and find the necessary talent to make sense of the flood of new information.” Take his first point, how companies interpret information.

Why this is so challenging is the subject of another of Nate Silver’s observations: “The numbers have no way of speaking for themselves. We speak for them. We imbue them with meaning.” It isn’t simply a matter of collecting the data and running it through some magic algorithm and coming up with the right answer. One need only think back to the spectacular failure of risk models that preceded the financial crisis to appreciate the problem. As Dr. Jordon points out “[m]any managers also lack basic numeracy, so getting decision makers who can grasp more sophisticated statistical mechanics can be a challenge.”

The other challenges Dr. Jordon points out are the organizational politics emerging from attempts to compile and act on the data. Finding the talent needed to make sense of the data and use it to the firm’s advantage are also fraught with risk. He notes that “[f]ew companies have in-house experts who can even make a business case to justify the cost of hiring big-data experts, let alone assess the quality of the applicants.” Given the short time Big Data tools and techniques have been around, the pool of candidates is small and the portion of this group who understand the financial services industry is smaller yet.

How companies need to address these challenges is no surprise. According to Dr. Jordan “the principles of good management extend to the domain of big data. Before businesses can profit from big data, managers must refuse to get lost in the noise that can obscure the basic forces represented by customers, value and execution.” One way companies are doing this is through a Data Strategy. A well thought out, comprehensive approach to all aspects of data – ownership, security, storage technology, analysis and distribution – can mitigate the risks associated with Big Data.

As Nate Silver observes, “[w]e face danger whenever information growth outpaces our ability to understand it.” Tackling Big Data means inviting very rapid information growth – and the challenges that go with it.



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