Patent Issued for Roof risk data analytics system to accurately estimate roof risk information (USPTO 11816738): Hartford Fire Insurance Company

2023 DEC 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Coonrod, Lane Garrison (Charlotte, NC, US), Holden, Sean David (Northampton, MA, US), filed on January 18, 2022, was published online on November 14, 2023, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11816738 is assigned to Hartford Fire Insurance Company (Hartford, Connecticut, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “An enterprise may enter into a risk relationship with a risk relationship provider (e.g., an insurer) to protect itself from damages associated with a building’s roof. For example, the risk relationship may provide payments associated with roof leaks, damages due to fire, vandalism, hail, tornados, etc. Several factors may influence the amount of risk associated with a particular roof, such as roof size, the age of the roof, the materials used to construct the roof, etc. To help determine this information, FIG. 1 is a high-level block diagram of a roof data collection system 100. A back-end application computer server 150 may collect information to be processed by a roof risk platform 155. In some cases, a user might self-report roof estimated information via a remote user device 160 such as a telephone or computer. For example, an insurer might ask a business “how old is your roof” and the business might reply “I’m not sure, may be around ten years old?” This information may then be used to calculate attributes of an insurance policy (e.g., premium values, exclusions risk classifications, etc.) and the results may be contained in a risk relationship data store 110. Such an approach, however, can be a time consuming and unreliable process. In other cases, the insurer might arrange to perform an in-person inspection of a roof. This, however, can be an expensive way to collect information.

“It would be desirable to provide systems and methods to accurately and/or automatically estimate roof risk information and mitigation strategies in a way that provides fast and accurate results. Moreover, the roof information should be easy to access, understand, update, etc.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “According to some embodiments, systems, methods, apparatus, computer program code and means are provided to accurately and/or automatically estimate roof risk information and mitigation strategies in a way that provides fast and accurate results and that allow for flexibility and effectiveness when responding to those results.

“In some embodiments, a risk relationship data store contains electronic records, each electronic record representing a risk relationship between an enterprise and a risk relationship provider (e.g., an insurer), and including, for each risk relationship, an electronic record identifier and a set of roof attribute values. A back-end application computer server may receive, from a third-party data source, roof information for a roof of a building associated with a risk relationship. The computer server may then correlate the received roof information with a particular electronic record in the risk relationship data store. A roof attribute value of the particular electronic record may be updated in accordance with the roof information received from the third-party data source, and a predictive analytics engine of the computer server may then calculate a roof risk score associated with the particular electronic record.

“Some embodiments comprise: means for receiving, by a back-end application computer server from a third-party data source, roof information for a roof of a building associated with a risk relationship; means for correlating the received roof information with a particular electronic record in a risk relationship data store that contains electronic records, each electronic record representing a risk relationship between an enterprise and a risk relationship provider, and including, for each risk relationship, an electronic record identifier and a set of roof attribute values; means for updating a roof attribute value of the particular electronic record in accordance with the roof information received from the third-party data source; and means for calculating, by a predictive analytics engine, a roof risk score associated with the particular electronic record.

“In some embodiments, a communication device associated with a back-end application computer server exchanges information with remote devices in connection with an interactive graphical user interface. The information may be exchanged, for example, via public and/or proprietary communication networks.

“A technical effect of some embodiments of the invention is an improved and computerized way to accurately and/or automatically estimate roof risk information and mitigation strategies in a way that provides fast and accurate results. With these and other advantages and features that will become hereinafter apparent, a more complete understanding of the nature of the invention can be obtained by referring to the following detailed description and to the drawings appended hereto.”

The claims supplied by the inventors are:

“1. A roof risk data analytics system implemented via a back-end application computer server, comprising: (a) a risk relationship data store that contains electronic records, each electronic record representing a risk relationship between an enterprise and a risk relationship provider, and including, for each risk relationship, an electronic record identifier and a set of roof attribute values; (b) the back-end application computer server, coupled to the risk relationship data store, including: a computer processor, and a computer memory, coupled to the computer processor, storing instructions that, when executed by the computer processor, cause the back-end application computer server to: receive, from a third-party data source, roof information for a roof of a building associated with a risk relationship, receive street level imagery for the roof of the building; automatically correlate the received third-party roof information and street level imagery to create correlated roof information for a particular electronic record in the risk relationship data store, analyze the correlated roof information using a machine learning algorithm and historic insurance claim data to determine an updated roof attribute value; update a roof attribute value of the particular electronic record in accordance with the updated roof attribute value, and calculate, by a predictive analytics engine, a roof risk score associated with the particular electronic record; and © a communication port coupled to the back-end application computer server to facilitate a transmission of data with remote user devices to support interactive user interface displays, including the roof risk score, via a distributed communication network.

“2. The system of claim 1, wherein the third-party data source is associated with at least one of: (i) a roof vendor, (ii) a roof installer, (iii) a governmental agency, (iv) a roof material, and (v) a roof warranty.

“3. The system of claim 1, wherein the back-end application computer server is further programmed to use the street level images to construct a three-dimensional model associated with the updated roof attribute data.

“4. The system of claim 1, wherein the updated roof attribute data is associated with at least one of: (i) a roof square footage, (ii) a roof age, (iii) a roof covering material, (iv) a roof shape, (v) a roof risk evaluation, and (vi) a roof hazard.

“5. The system of claim 1, wherein the updated roof attribute data is associated with at least one of: (i) a solar panel, (ii) a chimney, (iii) building heating or cooling equipment, (iv) a water tank, (v) a gutter condition, (vi) a roof extension, (vii) a satellite dish, (viii) public roof use, and (ix) a skylight.

“6. The system of claim 1, wherein the building is associated with at least one of: (i) an office building, (ii) a warehouse, (iii) a residence, (iv) a hanger, (v) a retail establishment, (vi) a stadium, and (vii) any other building structure that is associated with a risk relationship.

“7. The system of claim 1, wherein the risk relationship is associated with an insurance policy and the risk score is to be used in connection with at least one of: (i) insurance policy underwriting, (ii) insurance premium pricing, (iii) insurance physical inspection decisions, (iv) service levels, (v) insurance policy renewals, and (vi) insurance claim servicing.

“8. The system of claim 1, wherein the roof risk score is utilized to automatically establish a communication link with an electronic address associated with the risk relationship and transmit at least one of: (i) an email message, (ii) a calendar event, and (iii) a workflow instruction.

“9. A computerized roof risk data analytics method implemented via a back-end application computer server, comprising: receiving, by a computer processor of the back-end application computer server from a third-party data source, roof information for a roof of a building associated with a risk relationship; receiving, by the computer processor, street level imagery for the roof of the building; automatically correlating the received third-party roof information and street level imagery to created correlated roof information for a particular electronic record in a risk relationship data store that contains electronic records, each electronic record representing a risk relationship between an enterprise and a risk relationship provider, and including, for each risk relationship, an electronic record identifier and a set of roof attribute values; analyzing, by the computer processor, the correlated roof information using a machine learning algorithm and historic insurance claim data to determine an updated roof attribute value; updating a roof attribute value of the particular electronic record in accordance with the updated roof attribute value; and calculating, by a predictive analytics engine, a roof risk score associated with the particular electronic record.

“10. The method of claim 9, wherein the third-party data source is associated with at least one of: (i) a roof vendor, (ii) a roof installer, (iii) a governmental agency, (iv) a roof material, and (v) a roof warranty.

“11. The method of claim 9, wherein the back-end application computer server is further programmed to use the street level images to construct a three-dimensional model associated with the updated roof attribute data.

“12. The method of claim 9, wherein the updated roof attribute data is associated with at least one of: (i) a roof square footage, (ii) a roof age, (iii) a roof covering material, (iv) a roof shape, (v) a roof risk evaluation, and (vi) a roof hazard.

“13. The method of claim 9, wherein the updated roof attribute data is associated with at least one of: (i) a solar panel, (ii) a chimney, (iii) building heating or cooling equipment, (iv) a water tank, (v) a gutter condition, (vi) a roof extension, (vii) a satellite dish, (viii) public roof use, and (ix) a skylight.

“14. The method of claim 9, wherein the building is associated with at least one of: (i) an office building, (ii) a warehouse, (iii) a residence, (iv) a hanger, (v) a retail establishment, (vi) a stadium, and (vii) any other building structure that is associated with a risk relationship.

“15. A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a roof risk data analytics method implemented via a back-end application computer server, the method comprising: receiving, by a computer processor of the back-end application computer server from a third-party data source, roof information for a roof of a building associated with a risk relationship; receiving, by the computer processor, street level imagery for the roof of the building; automatically correlating the received third-party roof information and street level imagery to create correlated roof information for a particular electronic record in a risk relationship data store that contains electronic records, each electronic record representing a risk relationship between an enterprise and a risk relationship provider, and including, for each risk relationship, an electronic record identifier and a set of roof attribute values; analyzing, by the computer processor, the correlated roof information using a machine learning algorithm and historic insurance claim data to determine an updated roof attribute value; updating a roof attribute value of the particular electronic record in accordance with the updated roof attribute value; and calculating, by a predictive analytics engine, a roof risk score associated with the particular electronic record.

“16. The medium of claim 15, wherein the third-party data source is associated with at least one of: (i) a roof vendor, (ii) a roof installer, (iii) a governmental agency, (iv) a roof material, and (v) a roof warranty.

“17. The medium of claim 15, wherein the back-end application computer server is further programmed to use the street level images to construct a three-dimensional model associated with the updated roof attribute data.

“18. The medium of claim 15, wherein the updated roof attribute data is associated with at least one of: (i) a roof square footage, (ii) a roof age, (iii) a roof covering material, (iv) a roof shape, (v) a roof risk evaluation, and (vi) a roof hazard.

“19. The medium of claim 15, wherein the updated roof attribute data is associated with at least one of: (i) a solar panel, (ii) a chimney, (iii) building heating or cooling equipment, (iv) a water tank, (v) a gutter condition, (vi) a roof extension, (vii) a satellite dish, (viii) public roof use, and (ix) a skylight.

“20. The medium of claim 15, wherein the building is associated with at least one of: (i) an office building, (ii) a warehouse, (iii) a residence, (iv) a hanger, (v) a retail establishment, (vi) a stadium, and (vii) any other building structure that is associated with a risk relationship.”

URL and more information on this patent, see: Coonrod, Lane Garrison. Roof risk data analytics system to accurately estimate roof risk information. U.S. Patent Number 11816738, filed January 18, 2022, and published online on November 14, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11816738)&db=USPAT&type=ids

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