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How artificial intelligence can help brokers close sales


September 20, 2018   by Greg Meckbach


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Artificial intelligence could help a brokerage figure out how likely a prospective client is to actually buy insurance.

At least that’s what officials with Surex Direct are hoping.

Magreth, Alta.-based Surex Direct places home, auto and commercial lines and says it can deliver 10 quotes online in 10 minutes or less.

If a person gives Surex information to generate a home or auto quote, the brokerage defines that person as a lead, said Matt Alston, co-founder and chief operating officer of Surex.

“We are trying to build out sophistication in scoring leads,” Alston said in an interview. The goal is to use artificial intelligence to “know which leads we should focus on” and decide which broker should follow up with the prospective client.

If the computer software can “guesstimate which leads are going to be more likely to buy over others, then our brokers are putting their efforts towards the highest likelihood of getting a sale,” Alston said.

AI is when computer software can identify patterns and make decisions without decisions, consulting firm Strategy Meets Action notes. Machine learning is when software “learns” from large data sets.

“With AI, we need a lot of data,” Alston said, adding Surex is in the “early stages” of building a data set of customer leads.

Research firm Tractica recently predicted worldwide revenue from AI software implementations will increase from US$8.1 billion in 2018 to US$105.8 billion by 2025. Those dollar figures are for software licences alone in all industries, not just insurance. It’s a fraction of total spending if one includes systems integration and maintenance, Tractica lead analyts Aditya Kaul told Canadian Underwriter earlier.

At Surex Direct, there is a movement afoot to use machine learning to analyze claims data from the carriers with whom Surex Direct places insurance.

Alston said Surex may be able to take claims data and help its carriers “be more sophisticated” in pricing.

“Brokers are in a position to do that, because we have access to every quote we’ve ever done, every sale, in all 10 of our markets. One insurance carrier is just looking at their data.”

Some applications of AI include optical character recognition, autonomous driving and natural language processing, Craig Beattie, a London, England-based senior analyst with Celent, told Canadian Underwriter earlier.

In the past, “someone had to tell a computer exactly what to do and given a set of inputs, you could predict what the outputs would be,” Beattie said at the time. “Machine learning allows a computer to understand something from experience, so it adapts to a set of data or a set of inputs.”


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