Patent Issued for Social network risk analysis (USPTO 11727496): Allstate Insurance Company

2023 SEP 06 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Peccei, Christian (Palo Alto, CA, US), Warden, Thomas (Belmont, CA, US), filed on November 10, 2020, was published online on August 15, 2023, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11727496 is assigned to Allstate Insurance Company (Northbrook, Illinois, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “Social networks link people that share common interests and habits. The rapid growth of the Internet has facilitated the ability of social networks to connect people all across the world. Entities such as individuals, groups, and organizations now use social networks to share ideas, collaborate on projects, find job opportunities, and establish personal relationships, among other things.

“An entity may become a part of a social network by providing information about itself to others already in a network. For instance, through many Internet networking sites, an individual is linked to a list of friends based on various factors, including a past relationship, a shared interest, a similar job, a similar age, etc.

“As social networks have become more pervasive, the amount of data describing members of any given network has ballooned. However, adequate techniques for analyzing this data to provide information about the members of the network have yet to be developed.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “In light of the foregoing background, the following presents a simplified summary of the present disclosure in order to provide a basic understanding of some aspects of the invention. This summary is not an extensive overview of the invention. It is not intended to identify key or critical elements of the invention or to delineate the scope of the invention. The following summary merely presents some concepts of the invention in a simplified form as a prelude to the more detailed description provided below.

“Aspects of the disclosure address one or more of the issues mentioned above by disclosing methods, computer readable media, and apparatuses for creating a social network and using data derived from a social network. The data may be used to assess risk associated with members within the network.

“With another aspect of the disclosure, social network data may be used to determine a group rate that may apply to members within a community of the social network.

“With yet another aspect of the disclosure, centrality measures may be determined based on the roles of members within a community of the social network.

“Aspects of the disclosure relate to determining and using a trust score for a member within a community of the social network.”

The claims supplied by the inventors are:

“1. A method comprising: generating, by a first computing device and using data received from a server hosting a social network website, a social network community graph for an entity, wherein the social network community graph connects the entity to a first community member who is connected to a plurality of other community members; identifying, by the first computing device, one or more characteristics of interest to the entity; receiving, by the first computing device and from one or more second computing devices associated with one or more other community members of the plurality of other community members, feedback on at least one characteristic of interest, of the one or more characteristics of interest, for the first community member; computing, by the first computing device and based on the received feedback on the at least one characteristic of interest, a peer review score for the first community member; and determining, by the first computing device and based on the peer review score for the first community member, a rate for insuring the first community member.

“2. The method of claim 1, further comprising: adjusting, by the first computing device and based on the peer review score for the first community member, a price for a product or service offered to the first community member.

“3. The method of claim 1, further comprising: adjusting, by the first computing device and based on the peer review score for the first community member, a price for a product or service offered to the first community member and to each of the plurality of other community members.

“4. The method of claim 1, further comprising: determining, by the first computing device and based on receiving the feedback from the one or more other community members, a discount or reward to offer the one or more other community members.

“5. The method of claim 1, further comprising: aggregating, by the first computing device, the received feedback; and sending, by the first computing device and to a computing device associated with the first community member, the aggregated feedback.

“6. The method of claim 1, wherein computing the peer review score is further based on a length of time that the plurality of other community members connected to the first community member have been associated with the entity.

“7. The method of claim 1, wherein the one or more characteristics of interest comprise at least one of: a driving skill, a driving behavior, or a professional skill.

“8. A first computing device comprising: one or more processors; and memory storing computer-readable instructions that, when executed by the one or more processors, cause the first computing device to: generate, using data received from a server hosting a social network website, a social network community graph for an entity, wherein the social network community graph connects the entity to a first community member who is connected to a plurality of other community members; identify one or more characteristics of interest to the entity; receive, from one or more second computing devices associated with one or more other community members of the plurality of other community members, feedback on at least one characteristic of interest, of the one or more characteristic of interest, for the first community member; compute, based on the received feedback on the at least one characteristics of interest, a peer review score for the first community member; and determine, based on the peer review score for the first community member, a rate for insuring the first community member.

“9. The first computing device of claim 8, wherein the computer-readable instructions, when executed by the one or more processors, further cause the first computing device to: adjust, based on the peer review score for the first community member, a price for a product or service offered to the first community member.

“10. The first computing device of claim 8, wherein the computer-readable instructions, when executed by the one or more processors, further cause the first computing device to: adjust, based on the peer review score for the first community member, a price for a product or service offered to the first community member and to each of the plurality of other community members.

“11. The first computing device of claim 8, wherein the computer-readable instructions, when executed by the one or more processors, further cause the first computing device to: determine, based on receiving the feedback from the one or more other community members, a discount or reward to offer the one or more other community members.

“12. The first computing device of claim 8, wherein the computer-readable instructions, when executed by the one or more processors, further cause the first computing device to: aggregate the received feedback; and send, to a computing device associated with the first community member, the aggregated feedback.

“13. The first computing device of claim 8, wherein the computer-readable instructions, when executed by the one or more processors, cause the first computing device to compute the peer review score further based on a length of time that the plurality of other community members connected to the first community member have been associated with the entity.

“14. The first computing device of claim 8, wherein the one or more characteristics of interest comprise at least one of: a driving skill, a driving behavior, or a professional skill.

“15. A non-transitory, computer-readable storage medium storing instructions that, when executed by a processor of a computing device, cause the computing device to: generate, using data received from a server hosting a social network website, a social network community graph for an entity, wherein the social network community graph connects the entity to a first community member who is connected to a plurality of other community members; identify one or more characteristics of interest to the entity; receive, from one or more second computing devices associated with one or more other community members of the plurality of other community members, feedback on at least one characteristic of interest, of the one or more characteristic of interest, for the first community member; compute, based on the received feedback on the at least one characteristics of interest, a peer review score for the first community member; and determine, based on the peer review score for the first community member, a rate for insuring the first community member.

“16. The non-transitory, computer-readable storage medium of claim 15, wherein the instructions, when executed by the processor, further cause the computing device to: adjust, based on the peer review score for the first community member, a price for a product or service offered to the first community member.

“17. The non-transitory, computer-readable storage medium of claim 15, wherein the instructions, when executed by the processor, further cause the computing device to: adjust, based on the peer review score for the first community member, a price for a product or service offered to the first community member and to each of the plurality of other community members.

“18. The non-transitory, computer-readable storage medium of claim 15, wherein the instructions, when executed by the processor, further cause the computing device to: determine, based on receiving the feedback from the one or more other community members, a discount or reward to offer the one or more other community members.

“19. The non-transitory, computer-readable storage medium of claim 15, wherein the instructions, when executed by the processor, further cause the computing device to: aggregate the received feedback; and send, to a computing device associated with the first community member, the aggregated feedback.

“20. The non-transitory, computer-readable storage medium of claim 15, wherein the instructions, when executed by the processor, cause the computing device to compute the peer review score further based on a length of time that the plurality of other community members connected to the first community member have been associated with the entity.”

URL and more information on this patent, see: Peccei, Christian. Social network risk analysis. U.S. Patent Number 11727496, filed November 10, 2020, and published online on August 15, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11727496)&db=USPAT&type=ids

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