Big Data: How Insurance Agents Can Use It To Their Advantage

Big data is defined by The Economist as “an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process them using traditional data processing applications. The challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and privacy violations.”

Since the term first picked up steam, analysts have been looking for ways that it could be meaningful to the insurance agent.

Puneet Bharal of ACORD and Amir Halfon of MarkLogic, in their 2013 report “Making Sense of Big Data in Insurance,” write: “It is a truism that most customers only ever speak with their insurer or agent when obtaining premium quotes or managing a claim, and so carriers and/or their agents get few opportunities to develop a strong affinity with the customer.”

This comment — read the full report here — got me curious as to how big data could become a little more concrete for insurance agents across the country who are uncomfortable or unfamiliar with the rise of technology in their industry.

In a 2012 report (creatively) titled, “The Insurance Industry in 2012,” PricewaterhouseCoopers L.L.P. (PwC) says insurers using big data can “improve their overall performance by facilitating greater pricing accuracy, deeper relationships with customers, and more effective and efficient loss prevention.”

Today, PwC predicts the use of big data “eventually may transform the commercial insurance business model, as insurers find ways to use these new streams of information to radically alter business processes,” reports Business Insurance.

An example from the BI report follows:

“… a commercial fleet insurer may use actual data derived from telematic devices implanted in vehicles to underwrite a policy and set rates.

“‘Carriers may no longer need to compete on price; they instead may be able to assess the risk of individual customers based on their actual behaviors,’ the PwC report states. ‘Additionally, commercial insurance increasingly will be able to focus on providing customized, flexible products and value-added services that involve working with the clients to proactively avoid or reduce losses and manage risks.’”

This is all very nice, but what does it mean to the individual insurance agent, who continually feels left behind by the rise of big data?

According to Mark Breading, partner and chief research officer at Strategy Meets Action (SMA), big data is a very relevant matter to the agent/customer relationship.

“The customer experience and the producer experience is a huge overarching theme that we see in the industry,” said Breading in comments to Insurance Journal. “There are a lot of carriers investing a lot of money and energy and rethinking the experience of the policyholder — when and how they interact with them. Obviously the agent and broker have a big role in that given most insurance still flows through human intermediaries.”

An insurance agent in today’s market doesn’t have to worry about big data replacing him. Rather he can use it to become a more effective producer by first establishing trend lines for all his customers. How does he do that? By getting to KNOW his customers with questions like this:

How many are married? Single? Divorced or separated?

How many are parents to one or more children? How many have no interest in children?

How many are blue-collar workers? White-collar?

What age groups do they fall in to? How do they consume information?

What is the best way to reach out?

What life events are coming up that may justify the need for additional insurance products?


In Summary

The age of analytics is here, and it isn’t going anywhere. If anything, it will just get more nuanced and revealing. But as Breading points out in the IJ piece, “In the end, the winners will be those that master data and analytics. But there’s still plenty of time to get there … There’s certainly upswing in interest and investment in big data but we are still just on the front edge of this whole trend.”

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