Survey: Claims, Customer Service and Underwriting Main Focus of Insurer Data Analytics

Three frontrunners lead US property & casualty (P&C) insurers’ priorities for data and advanced analytics: customer experience; claims management; and telematics data for pricing, customer selection and product design. This finding, and the growing range of data sources that insurers find valuable, are the key discoveries from a new survey about the future of advanced analytics. Willis Towers Watson, a leading global advisory, broking and solutions company, conducted the survey.

“Advanced analytics and emerging data sources are the new frontiers for transforming insurers’ operations and customer experiences,” said J.J. Ihrke, senior consultant, Insurance Consulting and Technology, Willis Towers Watson. “Insurers need to recognize that data are the primary source of value in analytics – but more data, in-depth analysis and new insights aren’t the end game – and they must stay on top of new technology that enhances analytical capability and system connectivity.”

Willis Towers Watson’s 2017/2018 Advanced Analytics Survey asked U.S. P&C insurance executives for their insights on the future of advanced analytics. Fifty-one P&C insurers participated in the web-based survey fielded in fourth quarter 2017: 33 multiline carriers, 14 commercial lines carriers and four personal lines carriers. Respondents included nine of the top 20 U.S. P&C insurers.

According to the survey, insurers acknowledge the high degree of importance for improving customer experience and say they’re striving to enhance it by harnessing data to establish faster service (67%), easier information access (65%), more personalized experiences (61%) and mobile-friendly applications (53%). The top data sources insurers plan to use for customer centricity include internal customer data (76%), customer interactions/surveys (69%) and auto telematics (57%).

“Insurers want to replicate the rapid and personalized user experience other industries have implemented, such as retailers, online environments and apps, which have raised consumers’ expectations for faster, smoother, more customized service,” said Ihrke.

The potential of advanced analytics to transform claim management is evident from the survey. Nearly three-quarters (74%) of respondents will use it to evaluate claims for litigation potential in the next two years compared with 15 percent who use it now. Insurers plan to increase advanced analytics over this time period for fraud potential evaluation related to claims (82% versus 26% now) and claim triage (80% versus 26% now).

Respondents expect usage-based insurance (UBI) to grow beyond auto and anticipate using telematics and technologies associated with the Internet of Things to personalize risk assessment for homeowners (0% today versus 65% in two years) and commercial property (0% today versus 38% in two years). The five-year outlook for telematics’ impact on insurers’ business will be on pricing (90%) and underwriting (80%).

Personal line insurers say the top-growing new data sources they plan to use two years from now include UBI (70%); unstructured internal claim information (61%); and smart home/smart building data, unstructured internal underwriting information and social media (52%). Asked the same question, commercial insurers named unstructured internal claim information (92%) and other unstructured customer information (54%).

Insurers plan to increase usage of artificial intelligence and machine learning and expect these techniques to reduce time spent by humans, identify high-risk cases and build risk models for better decision making. “The volumes and variability with data types and sources are difficult to manage using internal capacity, networks and processing systems. Insurers are actively exploring systems and technologies — principally, the cloud and Hadoop — to help them manage big data,” said Ben Williams, senior consultant, Insurance Consulting and Technology, Willis Towers Watson.

Eighty-three percent of respondents say the level of understanding of advanced analytics models outside of their modeling teams is moderate or very limited. The top challenges preventing them from becoming more data-driven are infrastructure, data warehouse constraints (51%), data accessibility, not easily integrated (41%), and information technology/services bottlenecks and lack of coordination (33%).

“The benefits of advanced analytics are hard to attain if companies can’t access and use data at the right time, in the right place and deploy it to the right people, including the end customer, in a comprehensible way,” said Williams. “Insurers still have work to do to improve the levels of understanding around advanced analytics outputs for those who use them within the business. They should focus their initial effort on sources of data. New or better experience data, predictors and customer response information will always trump new methods being thrown at the same data.”

Source: Willis Towers Watson