Emerging Data Sources, Advanced Analytics Provide Expanding Universe Full of Promise for Insurers
Three frontrunners lead Canadian property & casualty (P&C) insurers' planned data sources for customer centricity: customer data, customer experience and social media. This finding, and the growing range of data sources that insurers find valuable, are key discoveries from a new survey about the future of advanced analytics.
"Advanced analytics and emerging data sources are transforming insurers' operations and customer experiences, but more data, in-depth analysis and new insights aren't the end game," said
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 (90%), easier information access (74%), more personalized experiences (68%) and mobile-friendly applications (58%). The top data sources insurers plan to use for customer centricity include internal customer data (79%), customer interactions/surveys (74%) and social media (47%).
To view the table, click here: https://www.willistowerswatson.com/en/press/2018/08/emerging-data-sources-and-advanced-analytics-provide-promise-for-insurers
"Retailers, online environments and apps have raised consumers' expectations for a faster, smoother, more customized service, and insurers are now turning their attention to replicating these experiences," said Begin.
The potential of advanced analytics to transform claim management is evident from the survey. More than half (67%) of respondents will use it to evaluate claims for litigation potential in the next two years compared with 7% who use it now.
Respondents expect usage-based insurance to grow beyond auto, and anticipate using telematics and technologies associated with the Internet of Things to personalize risk assessment for homeowners (6% today, versus 18% in two years) and commercial property (0% today, versus 13% in two years).
Personal line insurers say the new data sources they plan to use most in two years include unstructured internal claim information (74%), unstructured internal underwriting information (48%) and other unstructured internal customer information (42%).
Insurers plan to increase usage of artificial intelligence and machine learning, and expect these techniques to identify high-risk cases, reduce time spent by humans, better understand risk drivers, build risk models for better decision making and identify consumer patterns to reduce risk.
Ninety-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 (53%), data accessibility, difficulty of integration (47%), and information technology/services bottlenecks and lack of coordination (37%).
"While the benefits of advanced analytics are clear, insurers must access and deploy data to the right people at the right time for optimal benefit," said
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