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P&C Insurers See Value — and Improvements in Performance — Around Predictive Analytics

ARLINGTON, Va., March 01, 2016 (GLOBE NEWSWIRE) -- Over the next two years, many property & casualty (P&C) insurers expect to advance their use of predictive analytics to both improve business performance and leverage big data, according to Willis Towers Watson (NASDAQ:WLTW), a leading global advisory, broking and solutions company. This seemingly makes sound business sense, as more than four in five insurers (83%) that have already implemented predictive models have recognized a positive impact on their carrier’s profitability.

Willis Towers Watson’s Predictive Modeling survey found that even with insurers continuing to apply predictive modeling techniques to the tried and true areas of underwriting and risk selection, carriers anticipate significantly increasing model use across a number of other important business areas. For example, just 17% of respondents are currently using predictive modeling for claim triage, but more than half (52%) intend to join them in the next two years. And only 10% utilize modeling for evaluation of litigation potential today, yet half (51%) plan to do so within the same time frame.

Insurers also project their big data usage to grow across many business functions. Presently, big data is most useful for insurers’ work associated with pricing, underwriting and risk selection (42%). Tellingly, respondents say big data is not significantly helping any other business area. In fact, the next-highest function for which big data sources are being used to improve decision making (product development) received less than 20% consensus. Insurers do expect that to change. Nearly half believe big data will benefit their company in two years in a diverse set of areas including pricing, underwriting and risk selection (48%); making better management decisions (46%); and loss control and claim management (44%).

Usage-based insurance (UBI) information is the big data source that insurers think will increase the most over the next two years, followed by agent interactions via web, clickstream, phone and email. Ten percent of respondents currently use UBI as a big data source, though this is expected to grow to 42% over the next two years. Similarly, merely 2% use agent interactions as a big data source now, but this is expected to grow to 27% over the same time period.

“Insurers that embrace predictive modeling complexity by focusing on data enrichment, advanced analytics and technology can achieve a significant return on their investment,” said Klayton Southwood, director, P&C practice, Willis Towers Watson. “Carriers that catapult beyond their competition do so, in part, by leveraging superior data organization and analysis. For those insurers aspiring to unlock the potential of big data, they must be strategic, persistent and consistent.”

Even as enriching models with new data sources for broader application is ripe with potential, survey results illustrated some of the significant challenges insurers face. Half of the respondents indicated that people issues, such as resource availability, training, skills and capabilities, are their primary challenge to using big data. Data capture and availability ranks second (44%), as many carriers struggle with legacy policy administration systems that were not designed to capture and report data at the current needed level of granularity.

“Larger carriers have been more active in exploring big data applications that use both internal and external data,” said Southwood. “Smaller carriers will need to strategically assess their options, develop big data capabilities and become fast followers of larger carriers when size and scale issues make using data from internal interactions unfeasible.”

Personal lines carriers remain the market’s predictive analytics leaders, though standard commercial lines and specialty lines carriers are steadily advancing model use. “Many commercial insurers have gained experience using predictive models as benchmarks for underwriting and pricing, and are now starting to realize the value of modeling across all lines of their business.”

About the survey

Willis Towers Watson’s 2015 Predictive Modeling and Big Data Survey asked U.S. P&C insurance executives how they are using, or plan to use, predictive analytics and big data. The survey was fielded from September 9 to November 2, 2015. Respondents comprise 11% of U.S. personal lines carriers and 17% of commercial lines carriers.

About Willis Towers Watson

Willis Towers Watson (NASDAQ:WLTW) is a leading global advisory, broking and solutions company that helps clients around the world turn risk into a path for growth. With roots dating to 1828, Willis Towers Watson has 39,000 employees in more than 120 countries. We design and deliver solutions that manage risk, optimize benefits, cultivate talent, and expand the power of capital to protect and strengthen institutions and individuals. Our unique perspective allows us to see the critical intersections between talent, assets and ideas — the dynamic formula that drives business performance. Together, we unlock potential. Learn more at willistowerswatson.com.

Media contact Josh Wozman: +1 703 258 7670 josh.wozman@willistowerswatson.com

Source:Willis Towers Watson Public Limited Company