Capturing the flavors of roof risk with reliable data

May 17, 2022 / 2 min read

Some homeowners insurers may find that their solutions for capturing roof risk aren’t fully baked. They may be following an outdated recipe, or skimping on some core ingredients or otherwise missing them altogether, and what’s there may not mix into a harmonious whole.

roof-risk-with-reliable-data

Roof age inaccuracies cost homeowners insurers $1.31 billion in premiums annually.

However, there’s a lot at stake in getting the recipe right. Verisk estimates U.S. roof claims exceeded $19 billion in 2021, making up about 30 percent of all property loss dollars. Inaccuracies in roof age cost homeowners insurers on the whole $1.31 billion in premiums annually.

Multiple insurers faced different challenges around roof risk and searched for solutions. Verisk has created case studies to follow their journeys:

Staying on top of roof condition – A single-state property insurer with plans to expand its territory sought an alternative to on-site property inspections, which were costly while often failing to collect critical risk information. See how Verisk’s high-resolution aerial imagery, proprietary data, and advanced analytics exceled in testing on hundreds of properties—and positioned the insurer to better address a range of needs.

Grappling with age and condition – A major national personal lines insurer sought to better understand inconsistent correlations between roof condition and age in its homeowners portfolio. Learn how aerial and permit data from Verisk’s vast resources helped benchmark the insurer’s portfolio against market norms—and revealed property-level deviations from general assumptions about roof condition and age.

Taking charge of solar – A leading national personal lines insurer sought a better grasp of its risk exposure surrounding solar panels as their popularity surges, especially in states with favorable climates for this green energy source. Read about how the insurer screened nearly 73,000 policies with Verisk permit data and aerial imagery and identified homes with solar panels in selected states across the country.

Responding to hail damage with current replacement data –An insurer may need to better understand their exposures amid volatile roof replacement costs. For example, the rising incidence of hail and other weather perils, together with high materials and labor costs since the onset of the pandemic, can pose an expensive problem for many insurers.

Property-specific data can support a range of use cases. It can help guide underwriting and inspection decisions in a line where 90 percent of business is renewals but only 10 percent of properties are inspected. More data up front can help drive straight-through processing, and continually refreshed data can support even more efficient and effective mitigation and monitoring strategies.