Patent Issued for Methods and systems for improving the underwriting process (USPTO 11854088): Massachusetts Mutual Life Insurance Company

2024 JAN 16 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- Massachusetts Mutual Life Insurance Company (Springfield, Massachusetts, United States) has been issued patent number 11854088, according to news reporting originating out of Alexandria, Virginia, by NewsRx editors.

The patent’s inventors are Ross, Gareth (Amherst, MA, US), Walker, Tricia (East Hampton, MA, US).

This patent was filed on October 25, 2021 and was published online on December 26, 2023.

From the background information supplied by the inventors, news correspondents obtained the following quote: “Underwriting is the process that financial service providers use to determine eligibility of their costumers to receive their products (equity capital, insurance, mortgage or credit). Currently, the underwriting process may be described almost entirely as a manual process. Trained individuals, or underwriters, traditionally perform the underwriting process. The underwriting process may be very time-consuming and may involve the analysis of a plurality of underwriting standards set by a financial institution. Furthermore, the underwriting process may be biased by the judgment of the underwriter. Variation in factors such as underwriter training, experience, and quality of previous assessments may cause underwriters to make different decisions and judgments. As a result, there can be a large amount of variability and inconsistencies in the insurance underwriting process. Therefore, there is a need to improve conventional underwriting methods.”

Supplementing the background information on this patent, NewsRx reporters also obtained the inventors’ summary information for this patent: “A system and method for improving the underwriting process are disclosed. According to an embodiment, the underwriting system operates within a system architecture that includes components that dynamically interact with each other through network connections. In this embodiment, the system includes one or more client computing devices, one or more external sources, one or more internal databases, an underwriting platform, and one or more of the following software modules: analytical engine, ranking module, underwriting heuristics, and decision tools. Further to this embodiment, the system includes a user interface to interact with users (agents/underwriters) by means of a client computing device.

“According to some embodiments, a method for improving the underwriting process within an insurance company includes a plurality of steps performed by a processor. The steps include: retrieving outcome data to select and determine best underwriters; reviewing associated data that is associated with the best underwriters to understand decision and triage process; determining significance of key data elements; building a heuristic underwriting model; testing the model; and deploying decision tool within an underwriting platform.

“By executing this method through the exemplary operating environments, big data analytics and data mining techniques can be implement for a more efficient and faster processing of larger data sets. In this way, efficiencies are created by providing the financial or insurance company with ways to improve the current underwriting process. In addition, the agents/underwriters can receive automatic suggestions or checklists with valuable information before making important decisions when underwriting an applicant for one or more insurance products. These features allow performing large work such as heavy calculations and time consuming analysis in a more efficient manner than other approaches such as manual work performed by humans.

“In one embodiment, a computer-implemented method comprises determining, by a server, a subset of underwriter profiles from a set of former and current underwriter profiles based upon performance of the underwriters associated with the subset of underwriter profiles for a set of historic data obtained from an internal database; identifying, by the server, variables that are statistically similar for underwritten records associated with the subset of underwriter profiles, wherein the variables represent decision heuristics of the underwriters associated with the subset of underwriter profiles; generating, by the server, a heuristic underwriting computer model that generates a resolution based upon the identified variables that are statistically similar for underwritten records associated with the subset of underwriter profiles; and generating, by the server, a decision tool based on the heuristic underwriting computer model for an underwriting platform.

“In another embodiment, a system comprises an analytical engine server comprising a first module configured for determining, by the analytical engine server, a subset of underwriter profiles from a set of former and current underwriter profiles based upon performance of the underwriters associated with the subset of underwriter profiles for a set of historic data obtained from an internal database; a second module configured for identifying, by the analytical engine server, variables that are statistically similar for underwritten records associated with the subset of underwriter profiles, wherein the variables represent decision heuristics of the underwriters associated with the subset of underwriter profiles; a third module configured for generating, by the analytical engine server, a heuristic underwriting computer model that generates a resolution based upon the identified variables that are statistically similar for underwritten records associated with the subset of underwriter profiles; and a fourth module configured for generating, by the analytical engine server, a decision tool based on the heuristic underwriting computer model for an underwriting platform.”

The claims supplied by the inventors are:

“1. A computer-implemented method comprising: identifying, by a server, a set of existing users from an internal database, each existing user having a performance satisfying a threshold based on a set of historic data from the internal database and a set of outcome data retrieved from one or more external databases; training, by the server, an artificial intelligence model based on a set of decisions made for previously considered customers by each user within the set of existing users and one or more attributes associated with each previously considered customer, the artificial intelligence model configured to emulate decision patterns corresponding to processing of the previously considered customers by each user within the set of existing users; and upon receiving an input of information of a potential customer, executing, by the server, the artificial intelligence model to generate a new decision for the potential customer.

“2. The method according to claim 1, wherein the one or more external databases comprise at least one social networking database.

“3. The method according to claim 1, further comprising: generating, by the server, a decision tool user interface configured to implement the artificial intelligence model, wherein the decision tool user interface is configured to receive the input of information of the potential customer.

“4. The method according to claim 3, further comprising: when an inputted decision of a user interacting with the decision tool user interface differs from the decision generated via the artificial intelligence model, displaying, by the server, an alert on the decision tool user interface before allowing the user to proceed with the decision.

“5. The method according to claim 1, wherein the generated decision comprises at least one of a risk score calculation, a risk of loss assessment, or a risk classification for the potential customer.

“6. The method according to claim 1, wherein the input of information of the potential customer corresponds to a life event and a selected product or service.

“7. The method according to claim 1, wherein the artificial intelligence model is based at least in part on third party data.

“8. The method according to claim 1, further comprising: training, by the server, the artificial intelligence model utilizing a support vector machine algorithm.

“9. The method according to claim 1, further comprising: updating, by the server, the artificial intelligence model periodically based on new decisions made by the set of existing users.

“10. A system comprising a server comprising a processor and a non-transitory computer-readable medium containing instructions that when executed by the processor causes the processor to perform operations comprising: identifying a set of existing users from an internal database, each existing user having a performance satisfying a threshold based on a set of historic data from the internal database and a set of outcome data retrieved from one or more external databases; training an artificial intelligence model based on a set of decisions made for previously considered customers by each user within the set of existing users and one or more attributes associated with each previously considered customer, the artificial intelligence model configured to emulate decision patterns corresponding to processing of the previously considered customers by each user within the set of existing users; and upon receiving an input of information of a potential customer, executing the artificial intelligence model to generate a new decision for the potential customer.

“11. The system according to claim 10, wherein the one or more external databases comprise at least one social networking database.

“12. The system according to claim 10, wherein the instructions further cause the processor to generate a decision tool user interface configured to implement the artificial intelligence model, wherein the decision tool user interface is configured to receive the input of information of the potential customer.

“13. The system according to claim 12, wherein the instructions further cause the processor to when an inputted decision of a user interacting with the decision tool user interface differs from the decision generated via the artificial intelligence model, and display an alert on the decision tool user interface before allowing the user to proceed with the decision.

“14. The system according to claim 10, wherein the generated decision comprises at least one of a risk score calculation, a risk of loss assessment, or a risk classification for the potential customer.

“15. The system according to claim 10, wherein the input of information of the potential customer corresponds to a life event and a selected product or service.

“16. The system according to claim 10, wherein the artificial intelligence model is based at least in part on third party data.

“17. The system according to claim 10, wherein the instructions further cause the processor to train the artificial intelligence model utilizing a support vector machine algorithm.

“18. The system according to claim 10, wherein the instructions further cause the processor to update the artificial intelligence model periodically based on new decisions made by the set of existing users.”

For the URL and additional information on this patent, see: Ross, Gareth. Methods and systems for improving the underwriting process. U.S. Patent Number 11854088, filed October 25, 2021, and published online on December 26, 2023. Patent URL (for desktop use only): https://ppubs.uspto.gov/pubwebapp/external.html?q=(11854088)&db=USPAT&type=ids

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