Big data a big deal? For many U.S. life, P&C insurers, not yet

The report defines big data as internal and external data, structured and unstructured, typically collected in enormous volumes at a rapid speed. It is generally characterized by the “3 V’s” — Volume, Velocity and Variety — and is often too large to be processed by traditional technology.

Among the report’s key findings:

• Only about half of insurers actively derive value from analytics in key areas like product development and producer management. While the realized business value in areas like actuarial and pricing is widespread, many insurers have not been able to apply analytics to effectively improve performance in other areas.

• Predictive models are used by most insurers in some element of the value chain, with the most commonly used models focused in the areas of risk and profitability. For life/annuity insurers, common models include financial projections and both product and customer profitability, while P/C insurers also commonly use underwriter risk score in addition.

• Big data is becoming more important, but is not yet a priority at most insurers. Most carriers are still maturing and expanding their use of traditional data analytics and predictive models to improve processes, reduce losses, and generally improve their book of business. Insurers have become more conservative in their projected adoption plans for big data in the last two years.

• Smaller insurers are also embracing big data. In Novarica’s 2013 study, big data usage among smaller insurers was significantly behind that of larger insurers. This gap is narrowing.

• Insurers best positioned to profit from the value of analytics and big data have created a culture wherein business leaders trust analytics and act on the insights provided. 

The 58 insurer CIOs polled identify the following as current and expected sources of big data: