Research points to importance of predictive analytics

Predictive analytics methodologies and better use of broader data sets will help the insurance industry prepare for future market challenges, new analyst research claims.

In its latest report Creating an insurance predictive analytics portfolio, Ovum claimed insurers should focus on creative initiatives that analyse data from a range of sources including social media, third parties and machine-to-machine communication if they want to succeed long-term.

In particular, it recommended applying predictive analytics to key areas of the business such as business operations, marketing and customer relations as the best way for insurers to determine which markets to enter or leave, shape target initiatives and estimate potential losses for the book of business as each customer comes on-board.

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“Insurers are already well aware of the impending threats/challenges including tightening regulation, demanding customers, an ageing population and weakened economies.” Ovum analyst, Barry Rabkin, said. “The critical differentiator for insurers will be minimising future risk through predictive analytics by tapping into the vast amounts of rich data.”

Rabkin also pointed to the increased importance of the data scientist’s role and claimed it will be as important as the more established data miner’s position across the insurance industry. These two roles should work in harmony to discuss ‘what if’ questions and define the parameters of predictive analytics initiatives, he said.

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