U.S. P&C insurers see value in predictive analytics: Willis Towers Watson survey

More than four in five property and casualty insurers in the United States that have already implemented predictive models have recognized a positive impact on their carrier’s profitability, according to a survey released by Willis Towers Watson.

The 2015 Predictive Modeling and Big Data Survey (U.S.), released earlier this week, found that 83% of insurers that have implemented predictive models have seen a positive impact on profitability. And over the next two years, many P&C insurers expect to advance their use of predictive analytics to both improve business performance and leverage big data, Willis Towers Watson, a global advisory, broking and solutions company, said in a statement. [click image below to enlarge]

Respondents to the survey, fielded last September to November, comprise 11% of U.S. personal lines carriers and 17% of commercial lines carriers.

The study 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, the statement said.

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%),” Willis Towers Watson said in the statement. [click image below to enlarge]

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 of Willis Towers Watson’s P&C practice, in the statement. “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.”

The survey also found that 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,” Southwood said.