Patent Issued for Community-based digital transaction authentication (USPTO 11475489): United Services Automobile Association

2022 NOV 08 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Desai, Snehal (Richardson, TX, US), Erickson, Jennifer Hunt (San Antonio, TX, US), Hartshorn, Joel S. (Ollalla, WA, US), Khmelev, Yevgeniy Viatcheslavovich (San Antonio, TX, US), Lopez, Jeanie Graciela (San Antonio, TX, US), Prasad, Bharat (San Antonio, TX, US), Schwarz, Jr., Thomas Wayne (Helotes, TX, US), Serrao, Nolan (Plano, TX, US), filed on July 31, 2020, was published online on October 18, 2022, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11475489 is assigned to United Services Automobile Association (San Antonio, Texas, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “The present disclosure relates generally to systems and methods to facilitate digital transactions. More specifically, the techniques discussed herein relate to utilizing a distributed ledger to authenticate users and perform digital transactions.

“This section is intended to introduce the reader to various aspects of art that may be related to various aspects of the present disclosure, which are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present disclosure. Accordingly, it may be understood that these statements are to be read in this light, and not as admissions of prior art.

“Communities include homes, businesses, parks, governmental buildings, and the like. When deciding whether to reside in a particular community, individuals may evaluate various aspects of the homes, building, businesses, and other features provided within the community. In the digital age, data regarding the community may be used to help individuals better assess a likelihood that community may address or fit a certain set of rules for an individual or a business. As such, it is now recognized that improved systems and methods for evaluating a community fit for an individual or business based on data regarding various aspects of the community may assist individuals and businesses in identifying a community that may enable the individuals or businesses to achieve certain goals.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “One or more specific embodiments of the present disclosure are described above. In an effort to provide a concise description of these embodiments, all features of an actual implementation may not be described in the specification. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers’ specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and time consuming, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure.

“When introducing elements of various embodiments of the present disclosure, the articles “a,” “an,” and “the” are intended to mean that there are one or more of the elements. The terms “comprising,” “including,” and “having” are intended to be inclusive and mean that there may be additional elements other than the listed elements. Additionally, it should be understood that references to “one embodiment” or “an embodiment” of the present disclosure are not intended to be interpreted as excluding the existence of additional embodiments that also incorporate the recited features.

“Present embodiments are generally directed toward community and/or location-based processes performed and recorded within a distributed ledger (e.g., blockchain) to enable accurate and secure digital transactions. As discussed below, various types of information (e.g., school district rating, property value, parks, available businesses) regarding communities (e.g., counties, cities, towns, municipalities) may be utilized to determine community factors associated with the communities. The community factors may be determined based on data provided from various sensors (e.g., vehicle sensors, image data from cameras, traffic light cameras), digital reviews provided on a website, a social media application, or the like. As discussed below, community factors may be utilized for a variety of purposes and applications, such as to compare communities to one another. As another example, community factors may be utilized to enable machine learning algorithms, artificial intelligence (AI) systems, or other suitable computing systems to determine target communities for businesses to be opened and/or services to be provided. Additionally, community factors may be used to determine whether there is a community gap, or a perceived or estimated desire for a particular type of business or service within a community. By utilizing community factors to determine whether there is a community gap for a particular type of business or service, a level of subjectivity associated with issuing a loan may be reduced or eliminated. For example, when different people review information that may be included in a loan application, they may reach different opinions about whether a particular investment (e.g., a new business) is desired within a community, which can lead to subjectively different opinions about whether a load should be issued or the amount of a loan to be issued. By utilizing community factors, such subjectivity may be reduced or eliminated.

“As additionally discussed herein, identification and reputation data for users may be determined based on data (e.g., social media data, online data, review data, financial data) made available regarding users (e.g., of a digital application). For example, identification and reputation data related to the perceived trustworthiness or reliability of a user to repay a loan may be determined based the user’s financial data. The community factor data, the identification data, and the reputation data may be stored, for example, on a distributed ledger (e.g., blockchain), and users may provide permission settings regarding access to their data. Digital transactions between users or entities may occur over the distributed ledger. For example, financial transactions, such as loans, may be carried out between users via the distributed ledger. The identity of one or more of the users may be authenticated, information about the users may be shared, and each user may make a decision to engage in a transaction based on a relevant community factor and/or a user’s reputation score. Indeed, in some embodiments, a computing system may automatically perform the transaction in response to the relevant community factor and/or the user’s reputation score meeting some threshold. Accordingly, secure digital transactions may be provided between users, users and organizations, and the like.

“As another example, a review score or reputation score for an entity (e.g., a business) may be determined based on user reviews or ratings. Users may be authenticated, and information associated with each user may be utilized to determine how heavily the user’s review or rating should be weighed in determining the review score or reputation score for the entity or if the user’s review will even be utilized in determining the review score or reputation score for the entity. For example, user authentication may be performed utilizing a distributed ledger. Reviews from unauthenticated users may be discarded. Reviews from authenticated users may be weighted based on information associated with the entity being reviewed and the user reviewing the entity. For example, a location and a class or type of the entity may be considered, as may one or more locations associated with the user. The review score may be determined based on a weighting assigned to a review or rating assigned to the user. Accordingly, accurate, secure, and region or locale-specific ratings may be provided and stored on the distributed ledger. Furthermore, by utilizing authenticated users and basing the reputation or review scores on one or more locations (e.g., one or more locations associated with an authenticated user and/or an entity being reviewed), a review scores and reputations scores may be objectively more accurate than other ratings or rating techniques. For example, online reviews or ratings for products or entities (e.g., businesses) may be influenced, often times negatively, by unverified or false reviews that have been provided. Such ratings or reviews may sometimes be provided by people, while other times, these reviews could be generated by software. By utilizing the techniques described herein, more accurate and secure ratings may be provided, for example, because reviews provided by unverified or unauthenticated sources (e.g., users or user accounts) may be identified and not considered (or weighted relatively lowly) when determining a rating or score for an entity being reviewed. Additionally, by utilizing the location of the entity being reviewed and/or the location of a user leaving the review, the authenticity of the review may be determined, thereby increasing the accuracy of the rating or reviews for the entity.”

The claims supplied by the inventors are:

“1. A decentralized identity management system comprising one or more processors configured to: receive, from an electronic device of a user, review data regarding an entity and transaction data indicative of a purchase made by the user from the entity, wherein the review data comprises a rating associated with the entity; authenticate the user based on a first location associated with the entity, a second location associated with the user, a third location associated with the user retrieved from a distributed ledger, and the transaction data, wherein the second location is received from a location sensor disposed within the electronic device during a time period that corresponds to the review data being received; determine a weight for the review data based on the first location and the second location, wherein the weight is inversely proportional to a distance between the first location and the second location; determine a reputation score for the entity based on the weight and the rating of the review data; and store the reputation score on the distributed ledger.

“2. The decentralized identity management system of claim 1, wherein the one or more processors are configured to determine the third location associated with the user based on a profile of the user stored in the distributed ledger.

“3. The decentralized identity management system of claim 1, wherein the third location of the user corresponds to a residential address of the user.

“4. The decentralized identity management system of claim 1, wherein the first location associated with the entity comprises a physical location of the entity.

“5. The decentralized identity management system of claim 1, wherein the first location associated with the entity comprises a location associated with a good or service provided by the entity.

“6. The decentralized identity management system of claim 1, wherein the one or more processors are configured to determine the reputation score based on the distance between the first location associated with the entity and the second location associated with the user.

“7. The decentralized identity management system of claim 6, wherein the first location comprises a location associated with a good or service provided by the entity.

“8. The decentralized identity management system of claim 6, wherein the first location comprises a physical location of the entity.

“9. The decentralized identity management system of claim 1, wherein the second location associated with the user comprises a location of the user at a time of submitting the review data.

“10. A non-transitory computer-readable medium comprising instructions that, when executed, are configured to cause one or more processors to: receive, from an electronic device of a user, review data regarding an entity and transaction data indicative of a purchase made by the user from the entity, wherein the review data comprises a rating associated with the entity; authenticate the user based on a first location associated with the entity, a second location associated with the user, a third location associated with the user retrieved from a distributed ledger, and the transaction data, wherein the second location is received from a location sensor disposed within the electronic device during a time period that corresponds to the review data being received; determine a weight for the review data based on the first location and the second location, wherein the weight is inversely proportional to a distance between the first location and the second location; determine a reputation score for the entity based on the weight and the rating of the review data; and store the reputation score on the distributed ledger.

“11. The non-transitory computer-readable medium of claim 10, wherein the first location comprises a physical location of the entity and a location associated with a good or service provided by the entity.

“12. The non-transitory computer-readable medium of claim 11, wherein the instructions are configured to cause the one or more processors to determine the reputation score based on the location associated with the good or service provided by the entity.

“13. The non-transitory computer-readable medium of claim 12, wherein the instructions are configured to cause the one or more processors to determine the reputation score based on a distance between the second location associated with the user and the location associated with the good or service provided by the entity.

“14. The non-transitory computer-readable medium of claim 13, wherein the second location associated with the user comprises a place of residence of the user.

“15. A computer-implemented method, comprising: receiving, via one or more processors, review data regarding an entity and transaction data indicative of a purchase made by a user from the entity, wherein the review data comprises a rating associated with the entity from an electronic device of a user; authenticating, via the one or more processors, the user based on a first location associated with the entity, a second location associated with the user, a third location associated with the user retrieved from a distributed ledger, and the transaction data, wherein the second location is received from a location sensor disposed within the electronic device during a time period that corresponds to the review data being received; determining, via the one or more processors, a weight for the review data based on the first location and the second location, wherein the weight is inversely proportional to a distance between the first location and the second location; determining, via the one or more processors, a reputation score for the entity based on the weight and the rating of the review data; and storing, via the one or more processors, the reputation score on the distributed ledger.

“16. The method of claim 15, wherein determining the reputation score comprises modifying a preexisting reputation score based on the review data.

“17. The method of claim 15, wherein the second location associated with the user comprises a location of the user at a time of submitting the review data or a place of residence of the user.

“18. The method of claim 15, wherein the entity comprises a restaurant.

“19. The method of claim 18, wherein determining the first location associated with entity comprises determining a location associated with a type of food served by the restaurant.”

URL and more information on this patent, see: Desai, Snehal. Community-based digital transaction authentication. U.S. Patent Number 11475489, filed July 31, 2020, and published online on October 18, 2022. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11475489.PN.&OS=PN/11475489RS=PN/11475489

(Our reports deliver fact-based news of research and discoveries from around the world.)