Researchers Submit Patent Application, “System And Method Using Third-Party Data To Provide Risk Relationship Adjustment Recommendation Based On Upcoming Life Event”, for Approval (USPTO 20210192632)

2021 JUL 09 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- From Washington, D.C., NewsRx journalists report that a patent application by the inventors Amaral, Jennifer Maia (Simsbury, CT, US); Brown, Matthew (Cromwell, CT, US); Gimpl, Christopher J (Bristol, CT, US), filed on December 20, 2019, was made available online on June 24, 2021.

No assignee for this patent application has been made.

News editors obtained the following quote from the background information supplied by the inventors: “An entity may decide to enter into a risk relationship with an enterprise. For example, an employee might decide to purchase a voluntary group benefit insurance policy (e.g., associated with supplemental life insurance, short term disability insurance, etc.) from an insurer that is offered through his or her employer. Often, such a purchase needs to be made during an “open enrollment” period or within a pre-determined period of time of a “life event” (e.g., a birth, a marriage, a change in employment status, etc.).

“When an employee seeks insurance from an insurance company, the insurance company generally requests various information from the employee to determine an appropriate policy for the employee. Such information about an employee is typically stored in the insurance company’s database as insurance related data, which includes data that is directly related to various insurance parameters, or factors or criteria, as typically used by an insurance agent for determining the exact terms and conditions of the appropriate insurance policy, coverages, and their limits. However, specific information needed from an employee depends on the kind of insurance that an employee is seeking. This is because each type of insurance coverage is associated with a different set of parameters, or criteria, and specific information about an employee that is related to these parameters is used by an insurance agent to determine the exact terms and conditions of his/her insurance policy.

“After obtaining a policy, it is common for a policyholder’s parameter data to change due to the occurrence of a significant life event, which may make adjustments to the policy as appropriate. For example, after a policyholder has a child he or she might be interested in increasing the coverage amount of a supplemental life insurance policy. Accordingly, an insurance company or a third-party insurance underwriter may decide to offer such products to an employee after receiving a notification of such a change. Other examples of life events that may trigger changes in parameter data include: getting separated or divorced, having a family member move out (e.g., going to college), moving, changing job(s), and the like. Accordingly, an insurance company may want to receive updated parameter data about policyholders so that the insurance company can determine appropriate policy adjustments, if any, to make sure the policy holders are adequately covered.

“An experienced insurance agent can guide a policyholder through various questions targeted to obtain information related to any potential changes in parameter data to determine policy adjustments. Insurance underwriters use updated insurance information about policyholders to verify, accept, alter, or deny insurance adjustments as determined by insurance agents and to determine a monthly insurance premium for the policyholders if an adjusted policy is to be offered. Using an example in which a policyholder has gotten married, an agent might ask if the policyholder’s spouse has recently moved in with the policyholder in his/her existing home. If the policyholder has moved, the agent might ask if additional assets were brought in by the spouse to determine if a home owner’s insurance policy needs adjustments, e.g., an increase in coverage.

“However, such a process may be inefficient and require time and effort by both the insurance agent and the policyholder. Additionally, the process is inconvenient for policyholders who wish to update their insurance policies directly without the involvement of an insurance agent or the insurance company’s employee service department.

“It would be desirable to provide systems and methods for a risk relationship life event analytical modeling platform that allow faster, more accurate results as compared to traditional approaches.”

As a supplement to the background information on this patent application, NewsRx correspondents also obtained the inventors’ summary information for this patent application: “According to some embodiments, systems, methods, apparatus, computer program code and means are provided for a risk relationship life event analytical modeling platform that permits faster, more accurate results as compared to traditional approaches and that allows for flexibility and effectiveness when acting on those results. In some embodiments, a system may provide a risk relationship life event analytical modeling platform via a back-end application computer server of an enterprise. The system may include a risk relationship data store that contains electronic records representing potential risk relationships between the enterprise and a plurality of entities. Each record may include an electronic record identifier, at least one third-party indication associated with an upcoming life event, and a communication address. The server may determine a selected potential risk relationship and retrieve, from the risk relationship data store, the electronic record associated with the selected potential risk relationship. An analytical model may be executed based on the upcoming life event to generate a risk relationship adjustment recommendation for the selected potential risk relationship. The server may then automatically transmit information about the risk relationship adjustment recommendation to the communication address.

“Some embodiments comprise: means for determining, at the back-end application computer server, a selected potential risk relationship between the enterprise and an entity; means for retrieving, from a risk relationship data store, an electronic record associated with the selected potential risk relationship, including the at least one third-party indication associated with an upcoming life event and a communication address, wherein the risk relationship data store contains electronic records that represent a plurality of potential risk relationships between the enterprise and a plurality of entities, each electronic record including an electronic record identifier, at least one third-party indication associated with an upcoming life event, and a communication address; means for executing an analytical model based on the upcoming life event to generate a risk relationship adjustment recommendation for the selected potential risk relationship; and means for automatically transmitting information about the risk relationship adjustment recommendation to the communication address.

“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 provide a risk relationship life event analytical modeling platform in a way that provides faster, more accurate results as compared to traditional approaches. 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 system to provide a risk relationship life event analytical modeling platform via a back-end application computer server of an enterprise, comprising: (a) a risk relationship data store containing electronic records that represent a plurality of potential risk relationships between the enterprise and a plurality of entities, wherein each electronic record includes an electronic record identifier, at least one third-party indication associated with an upcoming life event, and a communication address; (b) the back-end application computer server, coupled to the risk relationship data store, programmed to: (i) determine a selected potential risk relationship between the enterprise and an entity, (ii) retrieve, from the risk relationship data store, the electronic record associated with the selected potential risk relationship, including the at least one third-party indication associated with an upcoming life event and a communication address, (iii) execute an analytical model based on the upcoming life event to generate a risk relationship adjustment recommendation for the selected potential risk relationship, and (iv) automatically transmit information about the risk relationship adjustment recommendation to the communication address; and © a communication port coupled to the back-end application computer server to facilitate a transmission of data with a remote device to support a graphical interactive user interface display via a distributed communication network, the interactive user interface display providing potential resource allocation data including the risk relationship adjustment recommendation.

“2. The system of claim 1, wherein the analytical model further executes based on internal data of the enterprise.

“3. The system of claim 2, wherein the analytical model is associated with at least one of: (i) employee segmentation, (ii) a product mixture based on employee segmentation, (iii) a cross-product sales offer, (iv) an up-sell product offer, (v) educational material.

“4. The system of claim 2, wherein the analytical model is associated with at least one of: (i) a machine learning model created based on historical risk relationship information, (ii) a predictive model, (iii) supervised learning, (iv) unsupervised learning, (v) reinforcement learning, (vi) self-learning, (vii) feature learning, (viii) sparse dictionary learning, (ix) anomaly detection, (x) association rules, (xi) an artificial neural network, (xii) a decision tree, (xiii) a support vector machine, (xiv) a Bayesian network, (xv) a genetic algorithm, and (xvi) federated learning.

“5. The system of claim 1, wherein the upcoming life event is associated with at least one of: (i) a birth, (ii) a change in marital status, (iii) an address change, (iv) a change in employment, and (v) an age change.

“6. The system of claim 5, wherein the third-party data is associated with at least one of: (i) employer data, (ii) government records, (iii) insurance data, and (iv) a credit score provider.

“7. The system of claim 1, wherein the risk relationship adjustment recommendation is associated with at least one of: (i) an optimum coverage selection, (ii) a cross-sell opportunity, (iii) a deductible change, (iv) a coverage change, and (v) a premium change.

“8. The system of claim 1, wherein the communication address is associated with at least one of: (i) a postal address, (ii) an email address, (iii) a telephone number, (iv) a text message, (v) a chat interface, and (vi) a video communication link.

“9. The system of claim 1, wherein the potential risk relationship is associated with at least one of: (i) an insurance group benefit offered by an employer, (ii) supplemental life insurance, (iii) short term disability insurance, (iv) long term disability insurance, (v) purchased time off, (vi) voluntary accident insurance, (vii) critical illness insurance, (viii) hospital indemnity insurance, (ix) a value added service, (x) legal services, and (xi) financial counseling services.

“10. A computerized method to provide a risk relationship life event analytical modeling platform via a back-end application computer server of an enterprise, comprising: determining, at the back-end application computer server, a selected potential risk relationship between the enterprise and an entity; retrieving, from a risk relationship data store, an electronic record associated with the selected potential risk relationship, including at least one third-party indication associated with an upcoming life event and a communication address, wherein the risk relationship data store contains electronic records that represent a plurality of potential risk relationships between the enterprise and a plurality of entities, each electronic record including an electronic record identifier, the at least one third-party indication associated with an upcoming life event, and a communication address; executing an analytical model based on the upcoming life event to generate a risk relationship adjustment recommendation for the selected potential risk relationship; and automatically transmitting information about the risk relationship adjustment recommendation to the communication address.

“11. The method of claim 10, wherein the analytical model further executes based on internal data of the enterprise.

“12. The method of claim 11, wherein the analytical model is associated with at least one of: (i) employee segmentation, (ii) a product mixture based on employee segmentation, (iii) a cross-product sales offer, (iv) an up-sell product offer, and (v) educational material.

“13. The method of claim 11, wherein the analytical model is associated with at least one of: (i) a machine learning model created based on historical risk relationship information, (ii) a predictive model, (iii) supervised learning, (iv) unsupervised learning, (v) reinforcement learning, (vi) self-learning, (vii) feature learning, (viii) sparse dictionary learning, (ix) anomaly detection, (x) association rules, (xi) an artificial neural network, (xii) a decision tree, (xiii) a support vector machine, (xiv) a Bayesian network, (xv) a genetic algorithm, and (xvi) federated learning.

“14. The method of claim 10, wherein the upcoming life event is associated with at least one of: (i) a birth, (ii) a change in marital status, (iii) an address change, (iv) a change in employment, and (v) an age change.

“15. The method of claim 14, wherein the third-party data is associated with at least one of: (i) employer data, (ii) government records, (iii) insurance data, and (iv) a credit score provider.

“16. A non-tangible, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method to provide a risk relationship life event analytical modeling platform via a back-end application computer server of an enterprise, the method comprising: determining, at the back-end application computer server, a selected potential risk relationship between the enterprise and an entity; retrieving, from a risk relationship data store, an electronic record associated with the selected potential risk relationship, including the at least one third-party indication associated with an upcoming life event and a communication address, wherein the risk relationship data store contains electronic records that represent a plurality of potential risk relationships between the enterprise and a plurality of entities, each electronic record including an electronic record identifier, at least one third-party indication associated with an upcoming life event, and a communication address; executing an analytical model based on the upcoming life event to generate a risk relationship adjustment recommendation for the selected potential risk relationship; and automatically transmitting information about the risk relationship adjustment recommendation to the communication address.

“17. The medium of claim 16, wherein the analytical model further executes based on internal data of the enterprise.

“18. The medium of claim 16, wherein the risk relationship adjustment recommendation is associated with at least one of: (i) an optimum coverage selection, (ii) a cross-sell opportunity, (iii) a deductible change, (iv) a coverage change, and (v) a premium change.

“19. The medium of claim 16, wherein the communication address is associated with at least one of: (i) a postal address, (ii) an email address, (iii) a telephone number, (iv) a text message, (v) a chat interface, and (vi) a video communication link.

“20. The medium of claim 16, wherein the potential risk relationship is associated with at least one of: (i) an insurance group benefit offered by an employer, (ii) supplemental life insurance, (iii) short term disability insurance, (iv) long term disability insurance, (v) purchased time off, (vi) voluntary accident insurance, (vii) critical illness insurance, (viii) hospital indemnity insurance, (ix) a value added service, (x) legal services, and (xi) financial counseling services.”

For additional information on this patent application, see: Amaral, Jennifer Maia; Brown, Matthew; Gimpl, Christopher J. System And Method Using Third-Party Data To Provide Risk Relationship Adjustment Recommendation Based On Upcoming Life Event. Filed December 20, 2019 and posted June 24, 2021. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220210192632%22.PGNR.&OS=DN/20210192632&RS=DN/20210192632

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