LexisNexis® Rooftop
Get a more accurate view of roof risk by combining imagery analytics with claims-driven context.
LexisNexis® Rooftop combines what you can see with what you can’t see for a more accurate roof inspection report score.
Do you know your current roof risk?
Roof-related home insurance claims are accelerating both in frequency and severity due to extreme weather events and escalating roof repair and replacement costs. Knowing the true condition of a roof is critical to make the best decisions regarding risk exposure. But it’s complicated.
With wind and hail losses representing nearly half of all losses in home insurance, asking consumers the age of their roof is no longer enough. LexisNexis® Rooftop combines aerial imagery data with claims-driven context so that insurers can improve the customer experience and make better decisions at underwriting, bind and renewal. Leveraging existing connections to our platform, home insurers can:
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Automate decision-making
Depend on a meaningful roof risk score for critical inspection and underwriting decisions |
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Accurately assess risk
Empower your team with a comprehensive suite of 50 roof and property attributes including imagery |
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Improve the customer experience Provide the right rate and speed up the underwriting process |
Discover a better way to predict roof risk by downloading the Rooftop white paper today.
Access Whitepaper Here
Rooftop is a consumer reporting agency product provided by LexisNexis Risk Solutions and is fully compliant with the Fair Credit Reporting Act, 15 U.S.C. 1681, et seq. Due to the nature of the origin of public record information, the public records and commercially available data sources used in reports may contain errors. Source data is sometimes reported or entered inaccurately, processed poorly or incorrectly, and is generally not free from defect. This product or service aggregates and reports data, as provided by the public records and commercially available data sources, and is not the source of the data, nor is it a comprehensive compilation of the data. Before relying on any data, it should be independently verified.