Big Data – Big Risk?


It’s a match made in heaven – or so it seems.  “Big data” is the term commonly used to refer to the incredibly massive (and still growing) pool of data generated from the digital footprints of our daily lives.  It has evolved beyond the basic retail point-of-sale data on what we buy and where.  Now, big data includes many of our online actions, mobile phone activity, health information from our fitness trackers or smart watches, and all manner of information from the “internet of things” that increasingly permeate our lives.  Surely, all of this data can be used to more accurately assess risk and therefore more efficiently underwrite the insurance of those risks.

This recent Business Insurance article highlights the possibilities of big data and touts the potential benefits of reducing premium costs to consumers while simultaneously improving insurer loss ratios.  Last year, I read Eric Siegel’s book, Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die, which I highly recommend.  Mr. Siegel described how big data and the associated predictive analytics methodologies were used in President Obama’s successful 2012 reelection bid, and in improving Netflix’s movie recommendations.  Mr. Siegel included several examples of big data and predictive analytics at work, including the Target public relations snafu when they predicted a teenage pregnancy based on buying patterns and inadvertently informed the girl’s father of his daughter’s pregnancy before she did.  The book also described a life insurer who used big data to predict the likelihood of death within 18 months for its elderly policyholders.  Fascinating.  And a little creepy.

My purpose in raising this topic is that I believe we are in the midst of one of those historical moments when our technological capabilities have outpaced the evolution of our societal norms. We clearly have the data and the methods to predict more outcomes more accurately than ever before, but we struggle with the “creepy factor” which is just another way of expressing the inherent privacy concerns.  Do we really want to know when grandma is likely in her final 18 months of life?  Will we rejoice in lower life insurance premiums enough to live comfortably with the fact that our daily activities (and perhaps even our whereabouts) may be reported directly to the insurer by the device we wear on our wrist?  As an industry, is the appeal of big data so great that insurers will accept the cyber risk when a hacker steals sensitive detailed health information for nefarious purposes such as blackmail?

Oh, and don’t even get me started on semi-autonomous driverless cars… That’s a topic for another time.


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