Patent Issued for Biometric-based payment rewards (USPTO 11922447): Block Inc.

2024 MAR 27 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Chiu, Emily (San Francisco, CA, US), filed on May 12, 2021, was published online on March 5, 2024, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11922447 is assigned to Block Inc. (Oakland, California, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “Generally, a variety of devices exist for monitoring the health or wellness of a patient or other individual, and many such devices are wearable. For example, fitness trackers (e.g., wristbands), smart watches, and smart rings can include sensors that monitor the wearer’s heart rate, physical activity, and sleeping patterns. Other wearable devices, such as ECG monitors, blood pressure monitors, glucose monitors, or biosensors, can be used to monitor a variety of other health-related characteristics. Such devices can provide wearers with fitness and health recommendations and can be synced with various smartphone apps.

“Health or wellness information is used by insurance companies to determine how risky it may be to provide health or life insurance to individuals. In general, individuals who are unhealthy can be more risky to insure and can be forced to pay higher insurance premiums. On the other hand, individuals who are healthy can be less risky to insure and may be able to pay lower insurance premiums. Many individuals are able to receive insurance coverage through an employer; however, many other individuals who are unemployed, self-employed, or work for small companies may be unable to take advantage of insurance provided through employers.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “Various examples of the present technology are discussed in detail below. While specific implementations are discussed, it should be understood that this is done for illustration purposes only. A person skilled in the relevant art will recognize that other components and configurations may be used without parting from the spirit and scope of the present technology.

“There is a need for improved systems and methods for monitoring and improving user wellness and for implementing insurance policies based on wellness information. In various examples, the subject matter described herein relates to systems and methods for improving user wellness. The wellness of a user can be determined based on data received from a biometric device worn by the user and/or from data indicative of user behavior. Such user behavior data can include, for example, data related to purchases made by the user, which can indicate whether the user is engaging in healthy activities (e.g., purchasing healthy foods and exercising) or unhealthy activities (e.g., purchasing junk food). In an effort to improve user wellness, the user can be provided with an offer (e.g., a reward offer) to purchase a product or service associated with healthy or positive user behavior as indicated through use of a machine learning model applied to previous purchase activity and biometric data from users on the payment platform in accordance with one example. The user can activate the offer by purchasing the product or service from a merchant. In response to the purchase, the systems and methods described herein can update a wellness profile for the user. For example, the systems and methods can obtain updated biometric data for the user and, based on such data, can calculate a new or updated wellness score for the user. Additional reward offers can be presented to the user, in an effort to improve overall user wellness.

“Further, in additional examples, the user wellness information can be used to implement one or more insurance policies for the user. For example, the systems and methods described herein can be used to present the user with an offer to obtain medical or life insurance. The systems and methods can monitor the wellness of the user and, based thereon, determine that an existing policy should be updated. For example, as user wellness improves (e.g., due to the user accepting reward offers), the systems and methods can determine that the user is entitled to an updated policy that provides greater protection and/or is lower cost, compared to an existing policy. The updated policy can be offered to the user and, if the user accepts the offer, the systems and methods can implement the updated policy for the user. The systems and methods include a payment service that can process the user’s payments for the policy.

“Advantageously, the technology described herein solves the problem of prior payment systems by determining savings and rewards for users and related entities based on purchase behavior, biometric data, and/or other wellness data. The present platform identifies savings that, when implemented, may expand services of the payment system to more users. By adding more users to system services, the machine learning and intelligent features of the system may improve models and/or generate novel models that are more efficient and/or accurate. The expanded access to both biometric and payment datasets via a payment platform allows the platform to map user outcomes more efficiently and accurately. Similarly, in some instances, by distributing workload to user devices (e.g., for collecting wellness data), the platform may reduce the workload expected from its servers and can eliminate a majority of unnecessary network traffic that would otherwise burden the system’s communications. Furthermore, intelligent systems for predicting user preferences and learning from user reactions benefit from biometric modelling, which provides access to user similarities and interests that would otherwise be inaccessible.

“Further, the technology described herein for determining rewards based on biometric data (and other wellness data) provides significant improvement to payment platforms and reward services. Payment platforms generally fail to expand beyond financial discounts, while reward services often publish rewards to users based on generic user demographics determined in the past. This may be sufficient for encouraging simplistic consumer activity, such as shopping at a particular merchant; however, the systems and methods described herein can encourage user activity and determine benefits from such activity by implementing user models based on biometric data, payment activity, or both. Further, by providing intelligent recommendations of wellness-centered rewards through machine learning used by a payment platform, bandwidth can be conserved because users and merchants connected to the platform do not need to search a merchant database or transaction history of others to find meaningful rewards. This can reduce network congestion and improve processing time associated with reward determinations.”

The claims supplied by the inventors are:

“1. A computer-implemented method, comprising: receiving, by a payment service system (PSS) at a first time, a first biometric dataset produced by a wearable device associated with a user of a plurality of users, wherein individual users of the plurality of users are associated with corresponding user accounts with the PSS, and wherein individual user accounts of the corresponding user accounts are associated with respective wellness profiles indicating a wellness of a respective user of the plurality of users over a timeframe; training, by the PSS and using training data, a machine learning model that uses as input user behavior and outputs a reward offer associated with behavior that improves a wellness score for the user, wherein the training data comprises one or more of wellness scores, wellness profiles, biometric patterns, purchase activity, or rewards offers associated with the plurality of users; determining, by the PSS and based on the machine learning model, the reward offer for the user, wherein the reward offer is associated with a merchant having a merchant account associated with the PSS; presenting, by the PSS and via an application executing on a mobile device of the user, the reward offer for activation on a user account of the user, wherein activation of the reward offer causes an association of the reward offer with the user account; receiving, by the PSS and from the mobile device, an indication that the user has activated the reward offer via a transaction with the merchant; obtaining, by the PSS and at a second time, a second biometric dataset produced by the wearable device, wherein the second time is based at least in part on activation of the reward offer; and updating, by the PSS based on a comparison of the second biometric dataset and the first biometric dataset, a wellness profile of the user.

“2. The computer-implemented method of claim 1, wherein updating the wellness profile comprises determining a change in the wellness profile.

“3. The computer-implemented method of claim 2, further comprising: determining, by the PSS, an improvement score based on differences between the first biometric dataset and the second biometric dataset, wherein the improvement score represents a positive or negative correlation between activating the reward offer and the change in the wellness profile; and updating, by the PSS, the machine learning model based on the improvement score.

“4. A computer-implemented method, comprising: receiving, by a platform server at a first time, a first set of wellness data for a user of a plurality of users, wherein individual users of the plurality of users are associated with corresponding user accounts of a platform, and wherein individual user accounts of the corresponding user accounts are associated with respective wellness profiles indicating a wellness of a respective user of the plurality of users over a timeframe; training, by the platform and using training data, a machine learning model that uses as input user behavior and outputs a reward offer associated with behavior that improves a wellness score for the user, wherein the training data comprises one or more of wellness scores, wellness profiles, biometric patterns, purchase activity, or rewards offers associated with the plurality of users; determining, by the platform server and based on the machine learning model, the reward offer associated with a positive user behavior for the user, wherein the reward offer is associated with a merchant have a merchant account associated with the platform; presenting, by the platform server and via an application executing on a mobile device of the user, the reward offer for activation on a user account of the user; receiving, by the platform server and from the mobile device, an indication that the user has activated the reward offer via a transaction with the merchant; obtaining, by the platform server and at a second time, a second set of wellness data for the user, wherein the second time is based at least in part on activation of the reward offer; and updating, by the platform server, a wellness profile of the user based on the indication that the user has activated the reward offer and a comparison of the first set of wellness data and the second set of wellness data.

“5. The computer-implemented method of claim 4, wherein the first set of wellness data and the second set of wellness data comprise biometric data produced by a wearable device associated with the user.

“6. The computer-implemented method of claim 4, wherein the first set of wellness data and the second set of wellness data comprise behavior data associated with the user, and wherein the behavior data comprises purchase data associated with the user.

“7. The computer-implemented method of claim 4, wherein the training data comprises the wellness profiles.

“8. The computer-implemented method of claim 4, wherein the wellness of the user improves when the user engages in the positive user behavior associated with the reward offer.

“9. The computer-implemented method of claim 4, wherein activation of the reward offer utilizes an association of the reward offer with the user account.

“10. The computer-implemented method of claim 4, wherein updating the wellness profile comprises determining a change in the wellness profile.

“11. The computer-implemented method of claim 10, further comprising determining, by the platform server, an improvement score based on differences between the first set of wellness data and the second set of wellness data, wherein the improvement score represents a positive or negative correlation between activating the reward offer and the change in the wellness profile.

“12. The computer-implemented method of claim 10, wherein the computer-implemented method further comprises: updating, by the platform server, the machine learning model based on the change in the wellness profile.

“13. A system comprising: one or more computer systems programmed to perform operations comprising: receiving, by a platform server at a first time, a first set of wellness data for a user of a plurality of users, wherein individual users of the plurality of users are associated with corresponding user accounts of a platform, and wherein individual user accounts of the corresponding user accounts are associated with respective wellness profiles indicating a wellness of a respective user of the plurality of users over a timeframe; training, by the platform and using training data, a machine learning model that uses as input user behavior and outputs a reward offer associated with behavior that improves a wellness score for the user, wherein the training data comprises one or more of wellness scores, wellness profiles, biometric patterns, purchase activity, or rewards offers associated with the plurality of users; determining, by the platform server and based on the machine learning model, the reward offer associated with a positive user behavior for the user, wherein the reward offer is associated with a merchant have a merchant account associated with the platform; presenting, by the platform server and via an application executing on a mobile device of the user, the reward offer for activation on a user account of the user; receiving, by the platform server and from the mobile device, an indication that the user has activated the reward offer via a transaction with the merchant; obtaining, by the platform server and at a second time, a second set of wellness data for the user, wherein the second time is based at least in part on activation of the reward offer; and updating, by the platform server, a wellness profile of the user based on the indication that the user has activated the reward offer and a comparison of the first set of wellness data and the second set of wellness data.

“14. The system of claim 13, wherein the first set of wellness data and the second set of wellness data comprise biometric data produced by a wearable device associated with the user.

“15. The system of claim 13, wherein the first set of wellness data and the second set of wellness data comprise behavior data associated with the user, and wherein the behavior data comprises purchase data associated with the user.

“16. The system of claim 13, wherein the training data comprises the wellness profiles.

“17. The computer-implemented method of claim 1, wherein the machine learning model comprises a first machine learning model, the computer-implemented method further comprising: determining the second time based at least in part on a second machine learning model.

“18. The computer-implemented method of claim 1, wherein basing the second time at least in part on activation of the reward offer comprises based the second time on at least one of: a type of the reward offer; a projected duration of time for the reward offer to impact health; a time when the reward offer was activated; or a quantity of biometric data collected.

“19. The system of claim 13, wherein updating the wellness profile comprises determining a change in the wellness profile.

“20. The system of claim 19, the operations further comprising: updating, by the platform server, the machine learning model based on the change in the wellness profile.”

URL and more information on this patent, see: Chiu, Emily. Biometric-based payment rewards. U.S. Patent Number 11922447, filed May 12, 2021, and published online on March 5, 2024. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11922447)&db=USPAT&type=ids

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