Majority of insurance carriers now using predictive analytics

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Two-thirds of U.S. property and casualty (P&C) insurers currently use predictive models for underwriting and risk selection, an increase of over 10 percentage points compared with last year, according to global advisory firm Willis Towers Watson.

Results from the firm’s recent study found that big data, notably from vehicle telematics and the Internet of Things (IoT), are opening up many new potential opportunities for carriers. Willis Towers Watson surveyed P&C insurance executives from September to October 2016.

While personal lines carriers continue to lead the way on predictive modeling, more commercial lines intend to build their capabilities within the next two years. For example, in claim triage, 15% use predictive models now compared with the 66% expected to use it in two years.

“The survey findings suggest that these could become increasingly important areas for performance differentiation, building on what many commercial lines carriers believe models have already helped achieve,” said J.J. Ihrke, senior consultant and actuary, Willis Towers Watson.

In order to sustain predictive model use, insurers need to unlock the value of data, according to the survey’s findings. Insurers say over the next two years big data will help them with pricing, underwriting and risk selection (92%), better management decisions (84%), and loss control and claim management (76%).

For the top-growing big data sources that insurers are already embracing, they think internal claim information (41%) and internal customer information (27%) are the most useful. Big data, from vehicle telematics and the IoT, are opening up many new potential avenues for improvement, as personal auto carriers expect to get much more driving data from connected cars (100%), apps (75%) and telecommunications (63%) in the next five years.

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