Although the property-casualty and health insurance sectors have rushed to embrace the benefits of big data and predictive modeling, life insurers are lagging far behind.
What’s the holdup? “Life insurance data is very misleading, it’s very technical and it’s very complicated,” says Dror Katzav, CEO of Atidot, a provider of big data and predictive analytics tools for the life insurance industry, who says most life insurers only utilize, at most, 20% of the “enormous amounts of data” they collect.
Consider the average life insurance policyholder. “You may have 20 years of universal life where your contribution and your interest rate went up or down, and meanwhile relevant events were happening all over the place, from market changes to your personal behaviors,” Katzav says. “How does that affect your propensity to lapse or to purchase? That’s a much more difficult question than you have a car, and you either had an accident or you didn’t.”
Artificial intelligence, machine learning and predictive modeling can help maximize profitability by analyzing the data an insurer has collected about an insured, combining it across siloed systems and then enriching it with information available from online sources “to build a good profile of who that insured is,” Katzav explains.
That level of personalization can improve the agent/client relationship, Katzav says: “You can leverage this data to say, ‘Based on my understanding, you recently moved from city center to suburbia, you now have kids, you now have a higher salary. You’re probably thinking about how to get your kids to college—maybe it’s a good time to really think about your savings and how you manage that.’”
“That would be a much more fruitful conversation between the adviser and their client, and it would help increase conversion rates,” Katzav continues. “You’re discussing the advantages and disadvantages—you’re helping them make a smarter decision, which is more valuable than, ‘I have this policy—do you want to buy it or not?’”
In this new equation, life insurance carriers become more than just your book of business—they become a source of valuable insights you may not otherwise be able to access [see sidebar].
“As an agent, you may be able to see your client moved from the city center to suburbia,” Katzav says. “But knowing how that affects the longevity of the policy—a good carrier should be able to provide an answer to that question.”
Jacquelyn Connelly is IA senior editor.
According to Katzav, big data technology is relevant only when you have enough samples.
“In some cases, ‘enough’ is 500. In other cases, ‘enough’ means 60,000,” Katzav explains. “One independent adviser does not have 60,000 customers.”
And that’s where carriers need to prove their clout: When selecting carrier partners, Katzav suggests asking yourself, “who can provide me with better insights on what’s going on with my customers?” —J.C.