It's no secret that Homeowners' insurance has taken a back seat to the Auto business for insurance carriers when it comes to profitabily and pricing sophistication.
So it's no surprise that the majority (84%) of 99 North American insurance professionals who responded to Verisk Insurance Solutions' "Homeowners Insurance Ratemaking Approaches Survey" noted that the " drive for greater profitability" has the greatest influence on Homeowners' rate change in the past year.
"With the realization that companies can no longer look to the Auto market to hit their growth goals, insurers are now focused on improving their Homeowners' pricing sophistication and use of analytics," the report states.
The use of analytics for Homeowners' ratemaking is increasing. In 2013, 37% of respondents said that they use predictive analytics, and now, 57% use the modeling.
Wwhile usage-based rating is huge in the Auto market, 90% of survey respondents say it will take more than three years for it to be used widely in the Homeowners' market, of which 38% say UBI will never be widely used. Only 5% of respondents are currently working on a UBI plan for Homeowners' insurance.
All survey respondents use some type of external data for risk selection and rating. The data types most commonly used are prior property losses, occupancy data, fire protection class and credit score.
The top concern for Homeowners' insurers is roof losses. Inspection practices vary widely, with 27% of repondents indicating that 100% of all new homes are inspected. Of those that inspect new homes, nearly two-thirds use only external physical inspections and 57% use both internal and external inspections.
During the underwriting process, the majority of the repondents (81%) do not use real-time catastrophe exposure information. The most common use of cat models is for hurricanes (69%), severe thunderstorms (64%), earthquake (55%), winter storm (39%) and fire following an earthquake (35%). In the future, insurers plan to incorporate model output in their ratemaking for severe thunderstorms.
The most comon way for using cat models in ratemaking is at the overall rate level (62% to 71% depending on catastrophe).
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