Patent Issued for Intelligent Product Plan Dataset (USPTO 10,803,514)

2020 OCT 26 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- According to news reporting originating from Alexandria, Virginia, by NewsRx journalists, a patent by the inventors Campbell, III, Allan A. (Wilbraham, MA); Nadeau, Patrick H. (Wolcott, CT), filed on November 18, 2016, was published online on October 26, 2020.

The assignee for this patent, patent number 10,803,514, is Massachusetts Mutual Life Insurance Company (Springfield, Massachusetts, United States).

Reporters obtained the following quote from the background information supplied by the inventors: “Several institutions offer users the opportunity to generate custom financial plans based on information provided by the users. An accurate estimation of future income is a vital and important factor in determining an accurate financial plan. Traditionally, many institutions have manually estimated users’ future income based on trends and cost of living increases, which relies heavily on information provided by users and is a time-consuming, inaccurate, and arduous process because many users fail to provide full and detailed information because of their unwillingness to devote the time and energy required. As the processing power of computers allow for greater computer functionality and the Internet technology era allows for interconnectivity between computing systems, many users access online resources to provide their information and request custom financial plans. But since the implementation of these more sophisticated online tools, several shortcomings in these technologies have been identified and have created a new set of challenges. For example, users’ information may be incomplete due to a service disruption or a network failure. As a result, institutions that utilize existing and conventional methods provide limited and generalized financial plan recommendations and/or plans based on inaccurate or limited user information. Moreover, existing and conventional methods fail to cure the user information deficiency or other shortcomings due to a high volume of user information existing on different networks and computing infrastructures. Managing such information on different platforms is difficult due to number, size, and content of data associated with the users. For example, conventional software solutions may not accurately estimate a future income because data associated with users’ future income is usually stored in different databases (e.g., employers’ database, social media databases, and the like) and may not be readily available.”

In addition to obtaining background information on this patent, NewsRx editors also obtained the inventors’ summary information for this patent: “For the aforementioned reasons, there is a need for a more efficient and faster system and method for processing large data sets associated with users, which would allow institutions to profile users in a more efficient manner than possible with human-intervention data-driven analysis. There is a need for a network and computer-specific solution to reduce the level of data-entry efforts required from the users. These features allow performing large work such as time-consuming analysis, data-entry tasks, and generating a future income/custom financial plans in a more efficient manner than other approaches including manual work performed by humans or other conventional software methods.

“In an embodiment a method for generating an intelligent product plan dataset. The method comprises receiving, by a server, a first request from a client computing device to generate a product plan dataset for a user. The method comprises generating, by the server, a first instruction configured to display a user interface configured to receive a first set of data associated with the user, wherein the first set of data comprises at least a current salary value associated with the user. The method comprises upon transmitting the first instruction to the client computing device, receiving by the server, the first set of data from the client computing device. The method comprises generating, by the server, a second instruction configured to query a second set of data associated with the user, wherein the second set of data is not associated with the first set of data. The method comprises upon transmitting the second instruction to a first database, receiving by the sever, the second set of data. The method comprises generating, by the server, a third instruction to store updated user data in a second database, wherein the updated user data comprises the first and the second sets of data. The method comprises determining, by the server, a maximum salary value for the user based on the updated user data, wherein the maximum salary value is calculated based on at least one of demographic data and a current salary value associated with the user. The method comprises determining, by the server, a likelihood of promotion for the user based on the updated user data, wherein the likelihood of promotion is calculated based on at least one of a demographic data and a performance review associated with the user. The method comprises determining, by the server, a future income value for the user, based on the current salary value, maximum salary value, and the likelihood of promotion value. The method further comprises generating, by the server, a product plan dataset based at least on the likelihood of promotion, maximum salary value, and the future income value.

“In another embodiment a computer system for generation of an intelligent product plan dataset is provided. The computer system comprises a server, which is configured to receive a first request from a client computing device to generate a product plan dataset for a user. The server is configured to generate a first instruction configured to display a user interface configured to receive a first set of data associated with the user, wherein the first set of data comprises at least a current salary value associated with the user. The server is configured to upon transmitting the first instruction to the client computing device, receive the first set of data from the client computing device. The server is configured to generate a second instruction configured to query a second set of data associated with the user, wherein the second set of data is not associated with the first set of data. The server is configured to upon transmitting the second instruction to a first database, receive the second set of data. The server is configured to generate a third instruction to store updated user data in a second database, wherein the updated user data comprises the first and the second sets of data. The server is configured to determine a maximum salary value for the user based on the updated user data, wherein the maximum salary value is calculated based on at least one of demographic data and a current salary value associated with the user. The server is configured to determine a likelihood of promotion for the user based on the updated user data, wherein the likelihood of promotion is calculated based on at least one of a demographic data and a performance review associated with the user. The server is configured to determine a future income value for the user, based on the current salary value, maximum salary value, and the likelihood of promotion value. The server is further configured to generate a product plan dataset based at least on the likelihood of promotion, maximum salary value, and the future income value.

“The method described here may enable the access to different programs/software applications within a single platform that may improve the experience of clients and agents regarding the offering of financial products. Numerous other aspects, features and benefits of the present disclosure may be made apparent from the following detailed description taken together with the figures included below.”

The claims supplied by the inventors are:

“What is claimed is:

“1. A method comprising: receiving, by a server, a first request from a client computing device to generate a product plan dataset for a user; generating, by the server, a first instruction configured to display a user interface configured to receive a first set of data associated with the user, wherein the first set of data comprises at least a current salary value associated with the user; upon transmitting the first instruction to the client computing device, receiving by the server, the first set of data from the client computing device; generating, by the server, a second instruction configured to query a second set of data associated with the user, wherein the second set of data is not associated with the first set of data; upon transmitting the second instruction to a first database, receiving by the server, the second set of data; generating, by the server, a third instruction to store updated user data in a second database, wherein the updated user data comprises the first and the second sets of data; successively executing, by the server, the plurality of software applications to generate the product plan dataset based on a likelihood of promotion, a maximum salary value, and a future income value, wherein an order of the successive execution of the plurality of software applications is based on a priority value associated with each software application, the priority value corresponding to an amount of system resources required to execute each respective software application and an availability of system resources associated with the server, and wherein the server allocates system resources to each software application in accordance with the priority value associated with each software application, and wherein the server is configured to: determine upon execution of a first application having a first priority value, the maximum salary value for the user based on the updated user data, wherein the maximum salary value is calculated based on at least one of demographic data and the current salary value associated with the user; determine upon execution of a second application having a second priority value, the likelihood of promotion for the user based on the updated user data, wherein the likelihood of promotion is calculated based on at least one of demographic data and a performance review associated with the user; and determine, upon execution of a third application, the future income value for the user, based on the current salary value, the maximum salary value, and the likelihood of promotion value.

“2. The method of claim 1, wherein the second set of data comprises at least one of behavioral data, social annotations, recommendations, social activities, the user’s demographic data, a performance review, and job history associated with the user.

“3. The method of claim 1, further comprising: upon transmitting the second instruction to the first database, receiving by the server, the second set of data, wherein the second set of data comprises a performance review associated with the user; semantically parsing, by the server, terms used within the performance review; assigning, by the server, a score associated with each semantically parsed term associated with good performance used within the performance review; determining, by the server, an average assigned score associated with each score associated with the semantically parsed term; and determining, by the server, the likelihood of promotion based on the average assigned score.

“4. The method of claim 3, wherein the maximum salary value is generated based on the likelihood of promotion.

“5. The method of claim 3, wherein the semantically parsed terms comprise: career development, management, leadership, and opportunity for growth.

“6. The method of claim 1, further comprising: determining, by the server, missing data, wherein the missing data comprises data requested within a data input field of the user interface, wherein the missing data is not received form the user interface; generating, by the server, a fourth instruction configured to query the missing data; upon transmitting the fourth instruction to the first database, receiving by the server, the missing data; and generating, by the server, a fifth instruction to store the updated user data in the second database, wherein the updated user data comprises the missing data, the first set of data, and the second set of data.

“7. The method of claim 1, wherein the second instruction is received from the user interface.

“8. The method of claim 1, wherein the first set of data is determined based on a received audio file associated with the user.

“9. The method of claim 1, wherein the product plan dataset is generated in response to the future income value satisfying a pre-determined threshold.

“10. A computer system comprising: a server configured to: receive a first request from a client computing device to generate a product plan dataset for a user; generate a first instruction configured to display a user interface configured to receive a first set of data associated with the user, wherein the first set of data comprises at least a current salary value associated with the user; upon transmitting the first instruction to the client computing device, receive the first set of data from the client computing device; generate a second instruction configured to query a second set of data associated with the user, wherein the second set of data is not associated with the first set of data; upon transmitting the second instruction to a first database, receive the second set of data; generate a third instruction to store updated user data in a second database, wherein the updated user data comprises the first and the second sets of data; successively execute the plurality of software applications to generate the product plan dataset based on a likelihood of promotion, a maximum salary value, and a future income value, wherein an order of the successive execution of the plurality of software applications is based on a priority value associated with each software application, the priority value corresponding to an amount of system resources required to execute each respective software application and an availability of system resources associated with the server, and wherein the server allocates system resources to each software application in accordance with the priority value associated with each software application; determine upon execution of a first application having a first priority number a maximum salary value for the user based on the updated user data, wherein the maximum salary value is calculated based on at least one of demographic data and the current salary value associated with the user; determine upon execution of a second application having a second priority number a likelihood of promotion for the user based on the updated user data, wherein the likelihood of promotion is calculated based on at least one of demographic data and a performance review associated with the user; determine upon execution of a third application a future income value for the user, based on the current salary value, maximum salary value, and the likelihood of promotion value.

“11. The computer system of claim 10, wherein the second set of data comprises at least one of behavioral data, social annotations, recommendations, social activities, the user’s demographic data, performance review, and job history associated with the user.

“12. The computer system of claim 10, wherein the server is further configured to: upon transmitting the second instruction to a first database, receive the second set of data, wherein the second set of data comprises a performance review associated with the user; semantically parse terms used within the performance review; assign a score associated with each semantically parsed term associated with good performance used within the performance review; determine an average assigned score associated with each score associated with the semantically parsed term; and determine the likelihood of promotion based on the average assigned score.

“13. The computer system of claim 12, wherein the maximum salary value is generated based on the likelihood of promotion.

“14. The computer system of claim 12, wherein the semantically parsed terms comprise: career development, management, leadership, and opportunity for growth.

“15. The computer system of claim 10, wherein the server is further configured to: determine missing data, wherein the missing data comprises data requested within a data input field of the user interface, wherein the missing data is not received form the user interface; generate a fourth instruction configured to query the missing data; upon transmitting the fourth instruction to the first database, receive the missing data; and generate a fifth instruction to store updated user data in the second database, wherein the updated user data comprises the missing data, the first set of data, and the second set of data.

“16. The computer system of claim 10, wherein the server is configured to receive the second instruction from the user interface.

“17. The computer system of claim 10, wherein the first set of data is determined based on a received audio file associated with the user.

“18. The computer system of claim 10, wherein the server is configured to generate the product plan dataset in response to the future income value satisfying a pre-determined threshold.”

For more information, see this patent: Campbell, III, Allan A.; Nadeau, Patrick H. Intelligent Product Plan Dataset. U.S. Patent Number 10,803,514, filed November 18, 2016, and published online on October 26, 2020. 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=10,803,514.PN.&OS=PN/10,803,514RS=PN/10,803,514

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