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What’s the Big Deal about Big Data?

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“Today, two major factors are poised to change the insurance industry in a way it hasn’t seen in more than 50 years — emerging capabilities enabled by cognitive computing and big data, and an empowered consumer.”

So begins a report from IBM called, “The future of insurance: How big data and cognitive computing are transforming the industry.” It explains the many ways that Big Data is improving the insurance industry. But, yeah, Big Data – Big Whoop, right? That seems like one of those things that you hear lots about but never see in the real world, like customer service or unconditional love.

In our magazine this month, Contributing Editor Linda Koco has a main feature on predictive analytics, which is basically one of the values in compiling voluminous data.

Many insurance companies are investing heavily in Big Data and analytics. In fact, LIMRA released a study recently showing that about 90 percent of carriers are using some degree of Big Data. And, “nearly half of companies are using big data analytics for six or more functions within their organizations, including: marketing initiatives, sales lead generation, underwriting, claims/fraud detection and prevention, improving sales productivity and product development,” LIMRA said in a press release.

A lot of that is pointed at agents to help them sell. That might seem odd, that a lot of numbers would help one person sell insurance to one other person. After all, this is a technology that helps Allianz review and analyze all its assets in a day rather than weeks or months. That ability helps the insurance giant maneuver in a day what used to take months to do, but what does it mean to an agent?

It turns out that more data allows individuals to do more precise things. It is a reversal of the disturbing dehumanizing trend of big companies getting bigger and more remote. When carriers just see risks and numbers, that does not help agents’ clients or business.

Analytics just might bring companies down from the 30,000-foot view to eye-level with agents and clients. Just like the old days. The really old days when an insurance company would examine each prospect’s special circumstances, according to the IBM report.

“Cognitive computing will allow underwriters to underwrite like their forebears—by evaluating the unique risks of each customer as opposed to aligning risk to a defined product,” according to the report. “And this work can happen in real time based on knowledge of the customer, past experiences and future predictions — at great scale.”

Companies would do this by using “a customer-centric approach to insurance. Each customer presents their own unique risk  profile. Insurers will be able to assess profiles at the customer level instead of assessing abstract personal attributes and relating them back to a rigidly defined product model.”

Altogether, this sounds like some exciting developments. Given the history of technology, we will hear the faint rumblings of these advances and then one day, there it is, a whole new way of doing business. Insurance and IT companies are working to bring this to the consumer level.

So, what can an agent do today? Learn what he or she can about it and be ready when these opportunities arrive. Because if agents and advisors are not going to run with this, companies will figure out another way to win this race.

 

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Steven A. Morelli is editor-in-chief for InsuranceNewsNet. He has more than 25 years of experience as a reporter and editor for newspapers, magazines and insurance periodicals. Connect with Steve →

  • DataH

    Steven, Big Data is surely a big deal. We definitely are seeing an increase in activity with companies responding to the impact big data has made on their business. For companies any size, getting meaningful insights from data analytics is an important priority. LexisNexis has open sourced its HPCC Systems big data platform which represents more than a decade of internal research and development in the big data analytics field. Designed by data scientists, their built-in libraries for Machine Learning and BI integration provide a complete integrated solution from data ingestion and data processing to data delivery. More at http://​hpccsystems​.com

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