System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting information on employees' annual incomes, family structures, and defined contribution pension; means for acquiring detailed asset information with employees' consent; means for creating a highly accurate life plan based on the collected and acquired information using a generative AI technique; means for generating and providing individually customized advice based on the life plan; and means for displaying the advice and life plan on employees' terminals.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Employee life planning is extremely complex, making it difficult to provide accurate and appropriate advice and plans tailored to each employee's individual circumstances. Furthermore, because it is difficult to fully understand an employee's financial situation and future goals, creating a highly accurate life plan based on this information is not easy. Another challenge is the current lack of tools and methods for companies to improve employee welfare. [Means for solving the problem]

[0005] To solve the above problems, the present invention provides the following means. The system includes: a means for collecting information on employees' annual income, family structure, and defined contribution pension plans; a means for obtaining detailed asset information with the employee's consent; a means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information; a means for generating and providing individually customized advice based on the life plan; and a means for displaying the advice and life plan on the employee's device. Furthermore, the system includes a means for receiving feedback and a means for regenerating a life plan, and has the function of regenerating the life plan in response to an employee's request for revision, making it possible to meet the needs of each individual employee. Furthermore, the system achieves highly accurate life planning by utilizing generative AI technology to create an optimal plan based on future earnings and savings goals.

[0006] "Annual income information" refers to the total amount of income an employee receives in a year.

[0007] "Family composition information" is information about the composition of related parties in an employee's household, such as spouse and children.

[0008] "Defined contribution pension information" is information about the defined contribution pension plan to which an employee is enrolled, specifically data about contribution amounts and funded status.

[0009] "Means for obtaining consent" refers to the means for confirming consent before obtaining detailed data such as asset information from employees.

[0010] "Asset information" refers to detailed information about assets such as financial assets and real estate owned by employees.

[0011] "Generative AI technology" is a technology that uses artificial intelligence to analyze and predict data, and is particularly used to generate individual life plans.

[0012] A "life plan" is a plan for an employee's future life, including elements such as income, expenses, savings, and investments.

[0013] "Customized advice" refers to advice that is proposed based on an employee's individual circumstances and goals, and includes content that is individually optimized.

[0014] "Display means" refers to a means for displaying information on a terminal, and specifically refers to a display or screen display function.

[0015] "Feedback receiving means" refers to the means for receiving opinions and requests for corrections from employees.

[0016] The "regeneration means" is a means for regenerating a life plan based on feedback. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[0039] System program and processing explanation

[0040] Collecting basic information

[0041] The server displays an input form on the terminal to collect information about the employee's annual income, family structure, and defined contribution pension. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension of 80,000 yen are entered.

[0042] Obtaining consent and collecting details

[0043] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0044] Creating a life plan

[0045] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0046] Providing customized advice

[0047] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[0048] Presenting optimal plans and responding to feedback

[0049] When the user sends feedback on the advice or life plan, the server regenerates the life plan using the regeneration means, thereby providing an optimal life plan that meets the user's needs.

[0050] The above is the basic form for implementing the present invention, and by using this system, it is possible to realize highly accurate life planning tailored to the needs of each employee. This system is also useful as a tool for improving corporate employee benefits, and by supporting employees' life planning, it contributes to improving job satisfaction.

[0051] The processing flow will be explained below.

[0052] Step 1:

[0053] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[0054] Step 2:

[0055] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[0056] Step 3:

[0057] The device sends the entered basic information to the server, which stores the received information in a database.

[0058] Step 4:

[0059] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[0060] Step 5:

[0061] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[0062] Step 6:

[0063] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[0064] Step 7:

[0065] The device sends the entered details to the server, which stores the received information in a database.

[0066] Step 8:

[0067] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[0068] Step 9:

[0069] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[0070] Step 10:

[0071] The server transmits the generated advice and life plan to the terminal and notifies the user.

[0072] Step 11:

[0073] The user uses the terminal to display the advice and life plan and confirm the contents.

[0074] Step 12:

[0075] If necessary, the user can use the terminal to send feedback to the server, for example, to request correction if they feel the advice is inappropriate.

[0076] Step 13:

[0077] The server receives feedback from the user and regenerates the life plan using the regeneration means. The regenerated life plan and advice are again sent to the terminal and notified to the user.

[0078] This specific process flow allows users to receive detailed life plans and customized advice, making future planning clearer. Companies can also use this system as a tool to improve employee welfare.

[0079] Example 1

[0080] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0081] In modern society, employees need a wide range of information when creating their own life plans. In addition to basic information such as annual income, family structure, and defined contribution pension plans, there is a demand for tools that allow employees to create highly accurate life plans based on detailed asset information. However, conventional methods have made it difficult to properly collect this information and provide individually customized advice. There are also challenges in regenerating life plans that reflect user feedback. As a result, life plans tailored to the individual needs of employees have not been adequately provided.

[0082] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0083] In this invention, the server includes means for collecting information on employees' annual income, family composition, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's terminal, means for receiving feedback on the generated life plan and advice, and means for regenerating the life plan based on the feedback. This allows employees to receive a highly accurate life plan based on their detailed asset information, and further enables them to regenerate their life plan through feedback on the advice provided.

[0084] "Employee" refers to a person who is employed by a company or organization and performs work.

[0085] "Annual salary" refers to the total income earned by an employee in a year.

[0086] "Family structure" refers to the type and number of family members an employee shares in their household.

[0087] A "defined contribution pension" is a type of pension system in which employees make contributions for the future, with the contribution amount fixed.

[0088] "Consent" refers to an employee's willingness to consent to a particular action or collection of information.

[0089] "Detailed asset information" refers to detailed asset information such as employee savings, stock investments, and mortgage balances.

[0090] "Generative AI technology" refers to technology that uses artificial intelligence to analyze data and generate specific results or predictions.

[0091] A "highly accurate life plan" refers to a plan that makes highly accurate predictions about an employee's future plans based on the information provided.

[0092] "Customized advice" refers to specific advice tailored to an employee's individual circumstances and needs.

[0093] "Terminal" refers to an electronic device used by employees to input information or receive advice.

[0094] "Feedback" refers to opinions and reactions from employees, based on which the system's results and advice can be modified.

[0095] "Regeneration means" refers to the function of recreating a life plan based on feedback.

[0096] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[0097] The server displays an input form on the terminal to collect information about the employee's annual income, family composition, and defined contribution pension. The terminal displays this input form, and the user uses the terminal to enter the necessary information into this form. When the user clicks the submit button, the entered information is sent to the server. This basic information includes annual income, family composition, and defined contribution pension information. As a specific example, an annual income of 6 million yen, being married with one child, and a defined contribution pension of 80,000 yen are entered.

[0098] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The terminal displays this consent confirmation message, and the user clicks the consent button to indicate consent. Once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the send button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0099] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. This generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan. The system inputs prompts such as age, family composition, current savings, and investment status into the model to output a specific life plan.

[0100] As a specific example, a user's basic information is entered as an annual income of 7 million yen, family structure as married with two children, and a defined contribution pension of 120,000 yen, while detailed information includes savings of 3 million yen, stock investments of 2 million yen, and a mortgage balance of 12 million yen. Based on this, the generative AI model calculates a "plan to increase average annual savings to 3 million yen over the next 10 years."

[0101] The server generates individually customized advice based on the generated life plan. For example, it may include monthly savings goals, recommended investment percentages, and plans for future education expenses. The server sends this advice to the terminal and notifies the user. The user can review the advice and send feedback to the server if necessary. Specific advice provided may include "save 50,000 yen each month and invest 20% in stocks."

[0102] When a user sends feedback on advice or a life plan, the server regenerates the life plan using the regeneration means. This allows the server to provide an optimal life plan that meets the user's needs. For example, if a user sends feedback such as "I want to increase my monthly investment amount to 70,000 yen," the server generates a new life plan based on this information and presents it to the user again.

[0103] By using this system, employees can receive specific advice on their own life plans, improving the accuracy and adaptability of their life plans.It is also useful as a corporate employee benefits tool, supporting employees' life planning and contributing to improving job satisfaction.

[0104] An example of a prompt is, "Please enter your employee's annual income, family composition, and defined contribution pension information. Next, add detailed asset information such as savings, stock investments, and mortgage balance. We will generate your life plan based on this information."

[0105] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0106] Step 1:

[0107] Collecting basic information

[0108] The server generates an input form for collecting information about the user's annual income, family structure, and defined contribution pension plan, and sends it to the terminal. The input form includes specific fields (annual income, family structure, defined contribution pension plan).

[0109] The terminal displays the input form received from the server on the screen, allowing the user to enter the required information.

[0110] The user enters information about their annual income, family structure, and defined contribution pension plan into this form, and then clicks the submit button to send the information to the server. For example, the user enters information such as an annual income of 6 million yen, being married with one child, and a defined contribution pension plan of 80,000 yen.

[0111] Input: Annual income, family composition, defined contribution pension information

[0112] Output: Basic information sent to the server

[0113] Step 2:

[0114] Obtaining consent and collecting details

[0115] The server stores the collected basic information, and then generates and sends to the terminal a consent confirmation message for obtaining detailed asset information. The confirmation message includes an consent button.

[0116] The terminal displays the consent confirmation message received from the server on the screen.

[0117] The user indicates their consent by clicking the accept button. Once consent is confirmed, the server generates a detailed data entry form (savings, stock investments, mortgage balance, etc.) and sends it to the terminal.

[0118] The terminal displays a detailed data entry form on the screen.

[0119] The user enters detailed information (savings, stock investment, mortgage balance, etc.) and clicks the send button to send it to the server. For example, the user enters information such as savings of 2 million yen, stock investment of 3 million yen, and mortgage balance of 10 million yen.

[0120] Input: Confirm consent, detailed asset information

[0121] Output: Detailed asset information sent to the server

[0122] Step 3:

[0123] Creating a life plan

[0124] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The collected information is input into the generative AI model as a prompt. For example, it generates a prompt such as "annual income of 7 million yen, married, two children, savings of 3 million yen, stock investments of 2 million yen, and mortgage balance of 12 million yen."

[0125] Based on the information provided, the generative AI model calculates future earnings projections and savings goals to generate an optimal life plan.

[0126] Input: Basic information, detailed asset information

[0127] Output: Generated life plan

[0128] Step 4:

[0129] Providing customized advice

[0130] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[0131] The server sends the customized advice to the terminal and notifies the user.

[0132] The terminal displays the advice received from the server on the screen.

[0133] The user can check the advice and send feedback to the server if necessary. For example, advice such as "Save 50,000 yen every month and invest 20% in stocks" is provided.

[0134] Input: Generated life plan

[0135] Output: personalized advice

[0136] Step 5:

[0137] Responding to feedback and regenerating your life plan

[0138] When a user sends feedback on advice or a life plan, the server accepts the feedback.

[0139] Based on the feedback, the server regenerates the life plan using the regeneration means, and again inputs the collected information and the user's feedback as prompts into the generative AI model.

[0140] The server transmits the regenerated life plan to the terminal.

[0141] The terminal displays the updated life plan on the screen and notifies the user.

[0142] Input: User feedback

[0143] Output: Regenerated life plan

[0144] (Application example 1)

[0145] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0146] Conventional life planning systems lack the ability to provide personalized product recommendations based on individual financial situations and to continually update in response to user feedback, making it difficult for users to find the products that best fit their specific needs and future plans.

[0147] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0148] In this invention, the server includes means for collecting employee income information, family composition information, and defined contribution pension information, means for obtaining detailed financial asset information with the employee's consent, means for creating a highly accurate life planning plan using generative artificial intelligence technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life planning plan, means for displaying the advice and life planning plan on the employee's terminal, means for making individualized product suggestions in a virtual store based on the user's financial situation and life planning plan, and means for continually updating product suggestions based on user feedback. This makes it possible to provide product suggestions and services that are optimal for the user's specific needs and future plans.

[0149] "Income information" is information about an employee's annual income or salary.

[0150] "Family composition information" is information about the number of family members in an employee's household and their composition.

[0151] "Defined contribution pension information" is information regarding the amount and type of defined contribution pension to which an employee is enrolled.

[0152] "Detailed financial asset information" refers to information about specific financial assets such as savings, stock investments, and mortgage balances held by employees.

[0153] "Generative AI technology" is an AI technology that enables highly accurate planning and analysis based on various collected data.

[0154] A "life planning plan" is a future living plan that optimizes an employee's income, expenses, and assets.

[0155] "Customized advice" means specific advice tailored to each employee's individual situation based on collected information.

[0156] A "terminal" is a device that allows employees to enter information and view results.

[0157] A "virtual store" is a virtual business location that offers products and services over the Internet.

[0158] "Product proposals" are proposals for products and services recommended based on the user's financial situation and lifestyle planning plans.

[0159] "Feedback" refers to information that reflects user opinions, impressions, and areas for improvement.

[0160] "Updated on a regular basis" means changing information and proposals in a timely manner as needed.

[0161] MODE FOR CARRYING OUT THE INVENTION

[0162] The system for realizing this invention basically consists of a server, a terminal (a device used by the user), and a user. This system collects employee income information, family composition information, and defined contribution pension information, and obtains detailed financial asset information with the employee's consent. Based on this information, generative artificial intelligence technology is used to create a highly accurate life planning plan and provide individually customized advice. In addition, product suggestions are updated as needed based on user feedback, and personalized product suggestions are made in a virtual store.

[0163] Hardware and Software Configuration

[0164] The system is implemented using the following hardware and software:

[0165] Hardware: Smartphone, Head-Mounted Display (HMD), Server

[0166] Software: Python (programming language), Flask (for building web applications), TensorFlow (for generative artificial intelligence models)

[0167] Data processing and calculation

[0168] 1. Basic information collected:

[0169] Users use their smartphones or HMDs to input information about their income, family structure, and defined contribution pension plans, which is then sent to the server.

[0170] 2. Obtaining consent and collecting details:

[0171] The server displays a message on the terminal asking for consent to the collection of detailed financial asset information. If consent is given, the user enters details such as savings, stock investments, and mortgage balances, which are also sent to the server.

[0172] 3. Life planning generation:

[0173] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence model using TensorFlow. For example, it calculates future earnings forecasts and savings goals based on income, expenses, and assets to generate an optimal life planning plan.

[0174] 4. Providing customized advice:

[0175] Based on the generated life planning plan, the server generates individually customized advice and sends it to the user's terminal for display, allowing the user to create an action plan based on it.

[0176] 5. Product suggestions in virtual stores:

[0177] Based on the user's financial situation and life planning, personalized product recommendations are made within the virtual store, allowing users to easily find the products that best fit their future plans.

[0178] 6. Receiving Feedback and Updating:

[0179] The server receives feedback from users and updates product suggestions and advice as needed, ensuring that users always receive optimal suggestions based on the latest information.

[0180] Specific examples

[0181] For example, consider a user who has an annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen. If this user inputs their savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen, generative artificial intelligence technology will be used to generate a lifestyle planning plan and product recommendations that are optimal for that user. Data can be entered using the following prompt sentences:

[0182] Prompt Sentence Examples

[0183] Generate the optimal life plan and product proposals based on the following: annual income of 6 million yen, married family with one child, 80,000 yen in defined contribution pension. Savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[0184] In this way, it becomes possible to propose products and provide services that are optimal for the user's specific needs and future plans.

[0185] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0186] Step 1:

[0187] The user uses a smartphone or head-mounted display (HMD) to enter employee income information, family composition information, and defined contribution pension information into an input form on the terminal, which is then sent to the server.

[0188] Input: Income information, family structure information, defined contribution pension information

[0189] Output: Basic information sent to the server

[0190] Step 2:

[0191] The server displays a message on the terminal confirming consent to the collection of detailed financial asset information. When the user clicks the consent button, a detailed data input form is displayed on the terminal.

[0192] Input: Consent confirmation message

[0193] Output: User consent result, detailed data entry form

[0194] Step 3:

[0195] The user enters detailed information such as savings, stock investments, and mortgage balance into a detailed data input form and sends it to the server, which then receives detailed financial asset information.

[0196] Input: Savings, stock investments, mortgage balance, and other details

[0197] Output: Details sent to the server

[0198] Step 4:

[0199] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence (AI) model, specifically, TensorFlow to calculate future income projections and savings goals.

[0200] Input: Basic information, detailed information

[0201] Data processing / calculation: Calculation using generative artificial intelligence models

[0202] Output: Highly accurate life planning

[0203] Step 5:

[0204] Based on the generated life planning plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[0205] Input: Life Planning Plan

[0206] Output: Advice

[0207] Step 6:

[0208] The server sends the generated advice to the terminal and notifies the user, who can then check the advice content through the terminal.

[0209] Input: Advice

[0210] Output: Advice displayed on terminal

[0211] Step 7:

[0212] Based on lifestyle planning and advice, the system will suggest optimal products to users in a virtual store. Product suggestions are optimized for the user's future plans.

[0213] Input: Life planning, advice

[0214] Output: Personalized product recommendations in a virtual store

[0215] Step 8:

[0216] Users send feedback on product suggestions and advice to the server via their terminals, and the server receives this feedback and updates the product suggestions and advice as needed.

[0217] Input: User feedback

[0218] Output: Updated product suggestions and advice

[0219] By the above processing steps, the system of the present invention can provide optimal product proposals and services based on the specific needs and future plans of the user.

[0220] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0221] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and uses generative AI technology to create highly accurate life plans based on detailed asset information collected with the employee's consent, and provides customized advice based on those life plans. Furthermore, this invention combines an emotion engine that recognizes the user's emotions to generate data based on the user's emotions and reflect them in the life plans and advice. This system consists of a server, a terminal (a device used by the employee), an emotion engine, and a user (employee).

[0222] System program and processing explanation

[0223] Collecting basic information

[0224] The server displays an input form on the terminal to collect information on the employee's annual income, family structure, and defined contribution pension plan. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension plan of 80,000 yen are entered.

[0225] Obtaining consent and collecting details

[0226] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0227] Creating a life plan

[0228] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0229] Providing customized advice

[0230] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[0231] Use of emotion engine

[0232] The emotion engine recognizes the user's emotions by analyzing the user's voice input, facial expressions, and text input. For example, emotions such as stress or anxiety may be detected from the user's tone of voice and facial expressions while entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[0233] Presenting optimal plans and responding to feedback

[0234] The server transmits to the terminal a life plan and advice created in consideration of the emotional data. For example, if the user is feeling stressed, advice recommending low-risk investments is generated. If the user transmits feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the user.

[0235] For example, if a user inputs a desire to "make low-risk investments" and the server recognizes feelings of anxiety, the server will generate advice recommending low-risk investment plans that promise stable returns. This advice is more convincing because it takes the user's feelings into account.

[0236] This specific process flow allows users to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[0237] The processing flow will be explained below.

[0238] Step 1:

[0239] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[0240] Step 2:

[0241] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[0242] Step 3:

[0243] The device sends the entered basic information to the server, which stores the received information in a database.

[0244] Step 4:

[0245] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[0246] Step 5:

[0247] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[0248] Step 6:

[0249] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[0250] Step 7:

[0251] The device sends the entered details to the server, which stores the received information in a database.

[0252] Step 8:

[0253] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[0254] Step 9:

[0255] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[0256] Step 10:

[0257] The server transmits the generated advice and life plan to the terminal and notifies the user.

[0258] Step 11:

[0259] The server displays a confirmation message on the terminal to analyze the user's emotions using the emotion engine. If consent is obtained, the server starts the emotion engine.

[0260] Step 12:

[0261] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize the user's emotions. For example, if the user is feeling stressed or anxious while typing, it will send that information to the server.

[0262] Step 13:

[0263] The server generates a life plan and advice optimized for the user's mental state based on the emotional data received from the emotion engine. For example, if the emotion engine determines that the user wants to avoid high risks, it generates advice recommending low-risk investments.

[0264] Step 14:

[0265] The server transmits the optimized life plan and advice to the terminal and notifies the user.

[0266] Step 15:

[0267] The user can use the device to view and confirm the advice and life plan, and can provide feedback if necessary.

[0268] Step 16:

[0269] The server receives feedback from the user and makes any necessary modifications using the regeneration means. The modified life plan and advice are then sent back to the terminal and notified to the user.

[0270] Through this process, users receive detailed emotional life plans and customized advice, which improves employee well-being and provides peace of mind.

[0271] Example 2

[0272] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0273] In employee life planning, it is difficult for conventional systems to aggregate asset information and emotional data for each employee and provide highly accurate, customized plans and advice. As a result, it is not possible to create plans that reflect the specific financial situation and emotional state of employees, which has resulted in insufficient improvement in employee satisfaction and psychological security.

[0274] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0275] In this invention, the server includes means for collecting information on employees' income, family structure, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using AI generation technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's information terminal, means for recognizing the user's emotions, and means for modifying the life plan and advice based on the emotion data. This makes it possible to provide highly accurate life plans and customized advice that reflect not only the employee's specific asset information but also their emotion data.

[0276] "Income" refers to the total income, such as salary and bonuses, that an employee receives within a certain period of time.

[0277] "Family composition" refers to information indicating the number and relationships (spouse, children, etc.) of household members in the employee's household.

[0278] A "defined contribution pension" is a pension system in which employees join, and the amount of pension they receive after retirement is determined by the amount of their contributions and the results of their investments.

[0279] "Detailed asset information" refers to information that shows specific and detailed financial status, such as an employee's savings, stock investments, and mortgage balance.

[0280] "Generative AI technology" refers to technology that uses artificial intelligence to perform calculations based on collected data and generate optimal life plans and advice.

[0281] A "life plan" refers to an employee's long-term life plan and a plan for achieving their financial goals.

[0282] "Customized advice" refers to specific advice or suggestions tailored to an individual employee's circumstances.

[0283] "Information terminal" refers to devices such as computers and smartphones used by employees.

[0284] "Means of recognizing emotions" refers to technology that detects an employee's emotional state by analyzing their voice, facial expressions, text input, etc.

[0285] "Emotional Data" means information indicative of an employee's emotional state that is collected and analyzed using emotion recognition measures.

[0286] This invention is a system that collects employee income, family structure, and defined contribution pension information, and obtains detailed asset information with the employee's consent, then uses generative AI technology to generate highly accurate life plans and provide individually customized advice. Furthermore, by incorporating a means to recognize the user's emotions, it is possible to modify the life plans and advice based on emotional data.

[0287] Server and technologies used

[0288] The server is the central hardware that performs collection and processing, and each step utilizes software and technologies such as:

[0289] Collecting income, family structure, and defined contribution pension information: The server generates an HTML form and sends it to the device. The device uses a browser to display the form and sends the information entered by the user to the server.

[0290] Example: A form for entering an annual income of 6 million yen, married, with one child, and a defined contribution pension of 80,000 yen.

[0291] Consent confirmation to obtain detailed asset information: The server generates a consent confirmation message and sends it to the terminal. The terminal displays the consent confirmation message in a dialog format, and the user enters information such as savings, stock investments, and mortgage balance.

[0292] Example: A form for entering savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[0293] Generating a high-precision life plan using generative AI technology: The server sends prompts to the generative AI model based on the collected basic and detailed information to generate a life plan.

[0294] Example prompt: "Generate a life plan with an income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen."

[0295] Providing customized advice: Based on the generated life plan, the server uses a generative AI model to generate individual advice and notify the device.

[0296] Examples include monthly savings goals, recommended investment percentages, and plans for future education funding.

[0297] Emotion recognition and data reflection: The emotion engine analyzes the user's voice, facial expressions, and text input to detect their emotional state. The server then adjusts the life plan and advice based on the emotional data.

[0298] Example: If a user is feeling stressed, suggest low-risk investments.

[0299] Feedback and life plan regeneration: When the user submits feedback, the server sends prompts based on the feedback to the generative AI model to regenerate the life plan.

[0300] Example: If a user enters "I want to invest with less risk" and anxiety is detected, regenerate a low-risk investment plan.

[0301] In this way, the system aims to improve employee satisfaction and peace of mind by providing highly accurate life plans and customized advice that take into account employees' asset information and emotional data. Companies can use this system as a tool to improve employee welfare.

[0302] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0303] Step 1:

[0304] Collecting basic information

[0305] The server generates a form to collect basic employee information and sends it to the terminal.

[0306] Specific behavior: A form constructed in HTML format is generated, containing input fields for annual income, family composition, and defined contribution pension. This form is sent to the terminal as an HTTP response.

[0307] Input: None (initial step)

[0308] Output: Basic information input form

[0309] The terminal displays the received form to the user.

[0310] What it does: Displays a form in a web browser and waits for user input.

[0311] Input: Form sent from server

[0312] Output: User interface

[0313] The user enters their annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[0314] Specific operation: The user enters their annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen, and presses the send button.

[0315] Input: Annual income, family composition, defined contribution pension information

[0316] Output: Input data

[0317] The terminal transmits the information entered by the user to the server.

[0318] Specific operation: Form data is sent to the server via an HTTP request.

[0319] Input: Basic information entered by the user

[0320] Output: HTTP request (basic information)

[0321] Step 2:

[0322] Obtaining consent and collecting details

[0323] The server generates a consent confirmation message for collecting detailed asset information and sends it to the terminal.

[0324] Specific behavior: Generates a consent confirmation message in HTML dialog format and sends it to the device.

[0325] Input: User basic information

[0326] Output: Consent confirmation message

[0327] The terminal displays a consent confirmation message to the user.

[0328] What it does: Displays a dialog box and waits for user input.

[0329] Input: The consent confirmation message sent by the server

[0330] Output: User interface (agreement confirmation)

[0331] The user clicks the Agree button to open the detailed asset information input form.

[0332] Specific behavior: When you click the consent button, a form to enter detailed information will be displayed.

[0333] Input: Agree

[0334] Output: Detailed information input form

[0335] The user enters information such as savings, stock investments, and mortgage balance, and clicks the submit button.

[0336] Specific actions: Enter 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance, then press the send button.

[0337] Input: Savings, stock investments, mortgage balance, and other details

[0338] Output: Detailed information data

[0339] The terminal sends the details entered by the user to the server.

[0340] Specific behavior: Sends detailed information to the server in the form of an HTTP request.

[0341] Input: User details

[0342] Output: HTTP request (detailed information)

[0343] Step 3:

[0344] Creating a life plan

[0345] The server sends prompts to the generative AI model based on the collected basic and detailed information.

[0346] Specific operation: Generate a prompt such as "Please generate a life plan with income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen" and send it to the generative AI model.

[0347] Input: Basic information, detailed information

[0348] Output: Prompt(Income 6 million yen, Expenses 3 million yen, Savings 2 million yen)

[0349] The generative AI model generates a life plan based on prompts.

[0350] Specific operation: The AI ​​model analyzes the input data and outputs an appropriate life plan and calculation results.

[0351] Input: prompt

[0352] Output: Life Plan

[0353] The server saves the generated life plan and proceeds to the next step.

[0354] Specific behavior: Save the generated life plan in the database.

[0355] Input: Life Plan

[0356] Output: Saved life plan

[0357] Step 4:

[0358] Providing customized advice

[0359] Based on the life plan, the server uses a generative AI model to generate individually customized advice.

[0360] What it does: Generates recommendations including monthly savings goals, recommended investment percentages, and future education funding plans.

[0361] Input: Life Plan

[0362] Output: Advisory data

[0363] The server sends the advice to the terminal and notifies the user.

[0364] Specific operation: The advice content is sent to the device in JSON format and notified to the user via a pop-up notification or other means.

[0365] Input: Advisory data

[0366] Output: Advice given

[0367] The user reviews the advice and sends feedback to the server if desired.

[0368] Specific actions: Check the advice, enter your questions or comments, and then press the send button.

[0369] Input: Feedback

[0370] Output: Feedback sent

[0371] Step 5:

[0372] Emotion recognition and data reflection

[0373] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize their emotional state.

[0374] Specific operation: Analyzes voice and facial expression data collected using a camera and microphone to identify emotions.

[0375] Input: Voice, facial expressions, text input

[0376] Output: Emotion data

[0377] The server modifies the life plan and advice based on the emotional data.

[0378] What it does: If stress is detected, it will revise its advice to suggest less risky investments.

[0379] Input: Emotion data

[0380] Output: Revised life plan and advice

[0381] Step 6:

[0382] Presenting optimal plans and responding to feedback

[0383] The server transmits a life plan and advice that takes into account the emotional data to the terminal.

[0384] Specific operation: The updated life plan and advice are sent to the device in JSON format and the user is notified via a pop-up notification, etc.

[0385] Input: Revised life plan and advice

[0386] Output: Notified remediation plan and advice

[0387] The user then checks the presented life plan and advice and sends feedback as necessary.

[0388] Specific actions: Review the presented plan, enter your wishes and questions, and press the submit button.

[0389] Input: New feedback

[0390] Output: Feedback sent

[0391] The server receives the feedback and regenerates the life plan and advice.

[0392] What it does: Send prompts based on the new feedback to the AI ​​model to recreate the life plan.

[0393] Input: New feedback

[0394] Output: Regenerated life plan and advice

[0395] (Application example 2)

[0396] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0397] A life plan provision system based on employee annual income, family structure, and defined contribution pension information had the problem of being unable to provide advice that took employees' emotions into consideration. Furthermore, when employees provided feedback on their life plans, it was difficult to recreate an optimal life plan based on their emotions. This resulted in a lack of advice that was truly useful and provided employees with psychological reassurance.

[0398] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0399] In this invention, the server includes a means for collecting information on employees' annual income, family structure, and defined contribution pension plans, a means for obtaining detailed asset information with the employee's consent, and a means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information. This makes it possible to provide highly accurate life plans and individually customized advice that take into account the employee's emotional data.

[0400] "Employee" refers to a person who is employed by a company or organization.

[0401] "Annual income information" refers to information on the total income an employee receives in a year.

[0402] "Family composition information" refers to detailed information such as the number of family members and their relationships with each other.

[0403] "Defined contribution pension information" refers to information regarding the defined contribution pension plan to which an employee is enrolled.

[0404] "Consent" refers to an employee's act of giving permission for the collection and use of information.

[0405] "Detailed asset information" refers to detailed financial information such as an employee's savings, investments, and loans.

[0406] "Generative AI technology" refers to technology that uses artificial intelligence technology to generate highly accurate results.

[0407] A "life plan" is a planned arrangement of future income, assets, and living conditions.

[0408] "Individually tailored advice" refers to specific advice that is developed taking into account the employee's individual information.

[0409] An "emotion engine" refers to technology that recognizes emotions by analyzing a user's voice, facial expressions, text input, etc.

[0410] "Emotion data" refers to data relating to the user's emotions recognized by the emotion engine.

[0411] "Devices" refers to devices such as smartphones and computers used by employees.

[0412] "Feedback" refers to employees' opinions, impressions, and requests for corrections regarding the system.

[0413] "Regeneration means" refers to technology for receiving feedback and regenerating a life plan.

[0414] To implement this invention, it is necessary to build a system that uses a server, terminals, employees, an emotion engine, and a generative AI model. The specific system configuration and processing content are described below.

[0415] Collecting basic information

[0416] The terminal displays an input form for collecting the employee's annual income information, family composition information, and defined contribution pension information. The employee enters the necessary information into the input form and clicks the submit button. The entered information is sent to the server.

[0417] For example, information such as annual income of 6 million yen, being married with one child, and having a defined contribution pension of 80,000 yen is entered.

[0418] Obtaining consent and collecting details

[0419] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The employee clicks the consent button to indicate consent, and once the server has confirmed consent, a detailed data input form is displayed on the terminal. The employee enters detailed information such as savings, stock investments, and mortgage balance into this form and clicks the submit button. For example, information such as savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen may be entered.

[0420] Use of emotion engine

[0421] The emotion engine recognizes employees' emotions by analyzing their voice, facial expressions, and text inputs. For example, emotions such as stress or anxiety may be detected from the employee's tone of voice and facial expressions while they are entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[0422] Creating a life plan

[0423] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0424] Example prompt sentence:

[0425] Annual income: 6 million yen

[0426] Family: Married, one child

[0427] Defined contribution pension: 80,000 yen

[0428] Savings: 2 million yen

[0429] Stock investment: 3 million yen

[0430] Mortgage balance: 10 million yen

[0431] Sentiment: I want to invest with less risk

[0432] Providing customized advice

[0433] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and plans for future education expenses. This advice is sent to the employee's device and notified to the employee. The employee can review it and provide feedback to the server if necessary.

[0434] Presenting optimal plans and responding to feedback

[0435] The server transmits the life plan and advice created by taking the emotional data into consideration to the terminal. For example, if the employee is feeling stressed, advice recommending low-risk investments is generated. If the employee provides feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the employee.

[0436] This specific process allows employees to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[0437] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0438] Step 1:

[0439] The terminal displays an input form for collecting employee annual income information, family composition information, and defined contribution pension information.

[0440] Input: None

[0441] Specific operation: The user enters annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[0442] Data processing / calculation: The terminal sends the input information to the server.

[0443] Output: The basic information collected is sent to the server.

[0444] Step 2:

[0445] The server displays a consent confirmation message on the terminal to obtain detailed asset information.

[0446] Input: Basic information (annual income, family composition, defined contribution pension information)

[0447] Specific action: The user clicks the consent button.

[0448] Data processing / calculation: If consent is confirmed, a detailed data entry form will be displayed on the terminal.

[0449] Output: A confirmation that consent has been given and a detailed data entry form will be displayed on the terminal.

[0450] Step 3:

[0451] The device collects detailed asset information (savings, stock investments, mortgage balances, etc.).

[0452] Input: Information entered into the detailed data entry form

[0453] Specific Actions: The user enters detailed asset information and clicks the submit button.

[0454] Data processing / calculation: The terminal sends the entered detailed information to the server.

[0455] Output: The detailed asset information collected is sent to the server.

[0456] Step 4:

[0457] The server uses an emotion engine to analyze the user's voice input, facial expressions, and text input to obtain emotion data.

[0458] Input: Voice input, facial expressions, text input

[0459] Specific operation: The user inputs a preference such as "I want to make an investment with low risk."

[0460] Data processing / calculation: The emotion engine analyzes the input data and generates emotion data.

[0461] Output: The analyzed emotion data is sent to the server.

[0462] Step 5:

[0463] The server uses a generative AI model to create a highly accurate life plan based on the collected basic information, detailed information, and emotional data.

[0464] Input: Basic information, detailed information, emotional data

[0465] Specific operation: The server generates prompt sentences for the generative AI model and creates a life plan based on them.

[0466] Data processing / calculation: The generative AI model calculates future earnings projections and savings goals, generating a highly accurate life plan.

[0467] Output: The generated life plan is obtained.

[0468] Step 6:

[0469] The server generates individually customized advice based on the generated life plan and transmits it to the user terminal.

[0470] Input: Generated life plan

[0471] Specific operation: The server analyzes the life plan and generates appropriate advice.

[0472] Data processing / computation: Generative AI models generate customized advice.

[0473] Output: The generated advice is sent to the user terminal.

[0474] Step 7:

[0475] The terminal receives feedback from the user.

[0476] Input: User feedback

[0477] Specific operation: The user inputs opinions and requests for revisions to the life plan and advice.

[0478] Data processing / calculation: The device sends feedback to the server.

[0479] Output: Feedback is sent to the server.

[0480] Step 8:

[0481] The server receives the feedback and recreates the life plan.

[0482] Input: User feedback, existing life plans, detailed information, emotional data

[0483] Specific operation: The server reuses the generated AI model to create a new life plan.

[0484] Data processing / computation: A generative AI model takes feedback and other information into account to generate a new life plan.

[0485] Output: A regenerated life plan is obtained.

[0486] Step 9:

[0487] The server transmits the regenerated life plan and advice to the user terminal.

[0488] Input: Regenerated life plan

[0489] Specific operation: The server transmits the new life plan and advice to the user terminal.

[0490] Data processing / calculation: The regenerated life plan is displayed on the user's device along with customized advice.

[0491] Output: The new life plan and advice are displayed on the user's terminal.

[0492] This process allows employees to receive detailed life plans and customized advice, and by taking emotions into account, the proposals are more relevant and convincing to the employee.

[0493] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0494] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0495] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0496] [Second embodiment]

[0497] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0498] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0499] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0500] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0501] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0502] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0503] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0504] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0505] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0506] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0507] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0508] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0509] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[0510] System program and processing explanation

[0511] Collecting basic information

[0512] The server displays an input form on the terminal to collect information about the employee's annual income, family structure, and defined contribution pension. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension of 80,000 yen are entered.

[0513] Obtaining consent and collecting details

[0514] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0515] Creating a life plan

[0516] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0517] Providing customized advice

[0518] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[0519] Presenting optimal plans and responding to feedback

[0520] When the user sends feedback on the advice or life plan, the server regenerates the life plan using the regeneration means, thereby providing an optimal life plan that meets the user's needs.

[0521] The above is the basic form for implementing the present invention, and by using this system, it is possible to realize highly accurate life planning tailored to the needs of each employee. This system is also useful as a tool for improving corporate employee benefits, and by supporting employees' life planning, it contributes to improving job satisfaction.

[0522] The processing flow will be explained below.

[0523] Step 1:

[0524] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[0525] Step 2:

[0526] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[0527] Step 3:

[0528] The device sends the entered basic information to the server, which stores the received information in a database.

[0529] Step 4:

[0530] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[0531] Step 5:

[0532] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[0533] Step 6:

[0534] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[0535] Step 7:

[0536] The device sends the entered details to the server, which stores the received information in a database.

[0537] Step 8:

[0538] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[0539] Step 9:

[0540] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[0541] Step 10:

[0542] The server transmits the generated advice and life plan to the terminal and notifies the user.

[0543] Step 11:

[0544] The user uses the terminal to display the advice and life plan and confirm the contents.

[0545] Step 12:

[0546] If necessary, the user can use the terminal to send feedback to the server, for example, to request correction if they feel the advice is inappropriate.

[0547] Step 13:

[0548] The server receives feedback from the user and regenerates the life plan using the regeneration means. The regenerated life plan and advice are again sent to the terminal and notified to the user.

[0549] This specific process flow allows users to receive detailed life plans and customized advice, making future planning clearer. Companies can also use this system as a tool to improve employee welfare.

[0550] Example 1

[0551] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0552] In modern society, employees need a wide range of information when creating their own life plans. In addition to basic information such as annual income, family structure, and defined contribution pension plans, there is a demand for tools that allow employees to create highly accurate life plans based on detailed asset information. However, conventional methods have made it difficult to properly collect this information and provide individually customized advice. There are also challenges in regenerating life plans that reflect user feedback. As a result, life plans tailored to the individual needs of employees have not been adequately provided.

[0553] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0554] In this invention, the server includes means for collecting information on employees' annual income, family composition, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's terminal, means for receiving feedback on the generated life plan and advice, and means for regenerating the life plan based on the feedback. This allows employees to receive a highly accurate life plan based on their detailed asset information, and further enables them to regenerate their life plan through feedback on the advice provided.

[0555] "Employee" refers to a person who is employed by a company or organization and performs work.

[0556] "Annual salary" refers to the total income earned by an employee in a year.

[0557] "Family structure" refers to the type and number of family members an employee shares in their household.

[0558] A "defined contribution pension" is a type of pension system in which employees make contributions for the future, with the contribution amount fixed.

[0559] "Consent" refers to an employee's willingness to consent to a particular action or collection of information.

[0560] "Detailed asset information" refers to detailed asset information such as employee savings, stock investments, and mortgage balances.

[0561] "Generative AI technology" refers to technology that uses artificial intelligence to analyze data and generate specific results or predictions.

[0562] A "highly accurate life plan" refers to a plan that makes highly accurate predictions about an employee's future plans based on the information provided.

[0563] "Customized advice" refers to specific advice tailored to an employee's individual circumstances and needs.

[0564] "Terminal" refers to an electronic device used by employees to input information or receive advice.

[0565] "Feedback" refers to opinions and reactions from employees, based on which the system's results and advice can be modified.

[0566] "Regeneration means" refers to the function of recreating a life plan based on feedback.

[0567] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[0568] The server displays an input form on the terminal to collect information about the employee's annual income, family composition, and defined contribution pension. The terminal displays this input form, and the user uses the terminal to enter the necessary information into this form. When the user clicks the submit button, the entered information is sent to the server. This basic information includes annual income, family composition, and defined contribution pension information. As a specific example, an annual income of 6 million yen, being married with one child, and a defined contribution pension of 80,000 yen are entered.

[0569] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The terminal displays this consent confirmation message, and the user clicks the consent button to indicate consent. Once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the send button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0570] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. This generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan. The system inputs prompts such as age, family composition, current savings, and investment status into the model to output a specific life plan.

[0571] As a specific example, a user's basic information is entered as an annual income of 7 million yen, family structure as married with two children, and a defined contribution pension of 120,000 yen, while detailed information includes savings of 3 million yen, stock investments of 2 million yen, and a mortgage balance of 12 million yen. Based on this, the generative AI model calculates a "plan to increase average annual savings to 3 million yen over the next 10 years."

[0572] The server generates individually customized advice based on the generated life plan. For example, it may include monthly savings goals, recommended investment percentages, and plans for future education expenses. The server sends this advice to the terminal and notifies the user. The user can review the advice and send feedback to the server if necessary. Specific advice provided may include "save 50,000 yen each month and invest 20% in stocks."

[0573] When a user sends feedback on advice or a life plan, the server regenerates the life plan using the regeneration means. This allows the server to provide an optimal life plan that meets the user's needs. For example, if a user sends feedback such as "I want to increase my monthly investment amount to 70,000 yen," the server generates a new life plan based on this information and presents it to the user again.

[0574] By using this system, employees can receive specific advice on their own life plans, improving the accuracy and adaptability of their life plans.It is also useful as a corporate employee benefits tool, supporting employees' life planning and contributing to improving job satisfaction.

[0575] An example of a prompt is, "Please enter your employee's annual income, family composition, and defined contribution pension information. Next, add detailed asset information such as savings, stock investments, and mortgage balance. We will generate your life plan based on this information."

[0576] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0577] Step 1:

[0578] Collecting basic information

[0579] The server generates an input form for collecting information about the user's annual income, family structure, and defined contribution pension plan, and sends it to the terminal. The input form includes specific fields (annual income, family structure, defined contribution pension plan).

[0580] The terminal displays the input form received from the server on the screen, allowing the user to enter the required information.

[0581] The user enters information about their annual income, family structure, and defined contribution pension plan into this form, and then clicks the submit button to send the information to the server. For example, the user enters information such as an annual income of 6 million yen, being married with one child, and a defined contribution pension plan of 80,000 yen.

[0582] Input: Annual income, family composition, defined contribution pension information

[0583] Output: Basic information sent to the server

[0584] Step 2:

[0585] Obtaining consent and collecting details

[0586] The server stores the collected basic information, and then generates and sends to the terminal a consent confirmation message for obtaining detailed asset information. The confirmation message includes an consent button.

[0587] The terminal displays the consent confirmation message received from the server on the screen.

[0588] The user indicates their consent by clicking the accept button. Once consent is confirmed, the server generates a detailed data entry form (savings, stock investments, mortgage balance, etc.) and sends it to the terminal.

[0589] The terminal displays a detailed data entry form on the screen.

[0590] The user enters detailed information (savings, stock investment, mortgage balance, etc.) and clicks the send button to send it to the server. For example, the user enters information such as savings of 2 million yen, stock investment of 3 million yen, and mortgage balance of 10 million yen.

[0591] Input: Confirm consent, detailed asset information

[0592] Output: Detailed asset information sent to the server

[0593] Step 3:

[0594] Creating a life plan

[0595] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The collected information is input into the generative AI model as a prompt. For example, it generates a prompt such as "annual income of 7 million yen, married, two children, savings of 3 million yen, stock investments of 2 million yen, and mortgage balance of 12 million yen."

[0596] Based on the information provided, the generative AI model calculates future earnings projections and savings goals to generate an optimal life plan.

[0597] Input: Basic information, detailed asset information

[0598] Output: Generated life plan

[0599] Step 4:

[0600] Providing customized advice

[0601] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[0602] The server sends the customized advice to the terminal and notifies the user.

[0603] The terminal displays the advice received from the server on the screen.

[0604] The user can check the advice and send feedback to the server if necessary. For example, advice such as "Save 50,000 yen every month and invest 20% in stocks" is provided.

[0605] Input: Generated life plan

[0606] Output: personalized advice

[0607] Step 5:

[0608] Responding to feedback and regenerating your life plan

[0609] When a user sends feedback on advice or a life plan, the server accepts the feedback.

[0610] Based on the feedback, the server regenerates the life plan using the regeneration means, and again inputs the collected information and the user's feedback as prompts into the generative AI model.

[0611] The server transmits the regenerated life plan to the terminal.

[0612] The terminal displays the updated life plan on the screen and notifies the user.

[0613] Input: User feedback

[0614] Output: Regenerated life plan

[0615] (Application example 1)

[0616] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0617] Conventional life planning systems lack the ability to provide personalized product recommendations based on individual financial situations and to continually update in response to user feedback, making it difficult for users to find the products that best fit their specific needs and future plans.

[0618] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0619] In this invention, the server includes means for collecting employee income information, family composition information, and defined contribution pension information, means for obtaining detailed financial asset information with the employee's consent, means for creating a highly accurate life planning plan using generative artificial intelligence technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life planning plan, means for displaying the advice and life planning plan on the employee's terminal, means for making individualized product suggestions in a virtual store based on the user's financial situation and life planning plan, and means for continually updating product suggestions based on user feedback. This makes it possible to provide product suggestions and services that are optimal for the user's specific needs and future plans.

[0620] "Income information" is information about an employee's annual income or salary.

[0621] "Family composition information" is information about the number of family members in an employee's household and their composition.

[0622] "Defined contribution pension information" is information regarding the amount and type of defined contribution pension to which an employee is enrolled.

[0623] "Detailed financial asset information" refers to information about specific financial assets such as savings, stock investments, and mortgage balances held by employees.

[0624] "Generative AI technology" is an AI technology that enables highly accurate planning and analysis based on various collected data.

[0625] A "life planning plan" is a future living plan that optimizes an employee's income, expenses, and assets.

[0626] "Customized advice" means specific advice tailored to each employee's individual situation based on collected information.

[0627] A "terminal" is a device that allows employees to enter information and view results.

[0628] A "virtual store" is a virtual business location that offers products and services over the Internet.

[0629] "Product proposals" are proposals for products and services recommended based on the user's financial situation and lifestyle planning plans.

[0630] "Feedback" refers to information that reflects user opinions, impressions, and areas for improvement.

[0631] "Updated on a regular basis" means changing information and proposals in a timely manner as needed.

[0632] MODE FOR CARRYING OUT THE INVENTION

[0633] The system for realizing this invention basically consists of a server, a terminal (a device used by the user), and a user. This system collects employee income information, family composition information, and defined contribution pension information, and obtains detailed financial asset information with the employee's consent. Based on this information, generative artificial intelligence technology is used to create a highly accurate life planning plan and provide individually customized advice. In addition, product suggestions are updated as needed based on user feedback, and personalized product suggestions are made in a virtual store.

[0634] Hardware and Software Configuration

[0635] The system is implemented using the following hardware and software:

[0636] Hardware: Smartphone, Head-Mounted Display (HMD), Server

[0637] Software: Python (programming language), Flask (for building web applications), TensorFlow (for generative artificial intelligence models)

[0638] Data processing and calculation

[0639] 1. Basic information collected:

[0640] Users use their smartphones or HMDs to input information about their income, family structure, and defined contribution pension plans, which is then sent to the server.

[0641] 2. Obtaining consent and collecting details:

[0642] The server displays a message on the terminal asking for consent to the collection of detailed financial asset information. If consent is given, the user enters details such as savings, stock investments, and mortgage balances, which are also sent to the server.

[0643] 3. Life planning generation:

[0644] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence model using TensorFlow. For example, it calculates future earnings forecasts and savings goals based on income, expenses, and assets to generate an optimal life planning plan.

[0645] 4. Providing customized advice:

[0646] Based on the generated life planning plan, the server generates individually customized advice and sends it to the user's terminal for display, allowing the user to create an action plan based on it.

[0647] 5. Product suggestions in virtual stores:

[0648] Based on the user's financial situation and life planning, personalized product recommendations are made within the virtual store, allowing users to easily find the products that best fit their future plans.

[0649] 6. Receiving Feedback and Updating:

[0650] The server receives feedback from users and updates product suggestions and advice as needed, ensuring that users always receive optimal suggestions based on the latest information.

[0651] Specific examples

[0652] For example, consider a user who has an annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen. If this user inputs their savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen, generative artificial intelligence technology will be used to generate a lifestyle planning plan and product recommendations that are optimal for that user. Data can be entered using the following prompt sentences:

[0653] Prompt Sentence Examples

[0654] Generate the optimal life plan and product proposals based on the following: annual income of 6 million yen, married family with one child, 80,000 yen in defined contribution pension. Savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[0655] In this way, it becomes possible to propose products and provide services that are optimal for the user's specific needs and future plans.

[0656] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0657] Step 1:

[0658] The user uses a smartphone or head-mounted display (HMD) to enter employee income information, family composition information, and defined contribution pension information into an input form on the terminal, which is then sent to the server.

[0659] Input: Income information, family structure information, defined contribution pension information

[0660] Output: Basic information sent to the server

[0661] Step 2:

[0662] The server displays a message on the terminal confirming consent to the collection of detailed financial asset information. When the user clicks the consent button, a detailed data input form is displayed on the terminal.

[0663] Input: Consent confirmation message

[0664] Output: User consent result, detailed data entry form

[0665] Step 3:

[0666] The user enters detailed information such as savings, stock investments, and mortgage balance into a detailed data input form and sends it to the server, which then receives detailed financial asset information.

[0667] Input: Savings, stock investments, mortgage balance, and other details

[0668] Output: Details sent to the server

[0669] Step 4:

[0670] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence (AI) model, specifically, TensorFlow to calculate future income projections and savings goals.

[0671] Input: Basic information, detailed information

[0672] Data processing / calculation: Calculation using generative artificial intelligence models

[0673] Output: Highly accurate life planning

[0674] Step 5:

[0675] Based on the generated life planning plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[0676] Input: Life Planning Plan

[0677] Output: Advice

[0678] Step 6:

[0679] The server sends the generated advice to the terminal and notifies the user, who can then check the advice content through the terminal.

[0680] Input: Advice

[0681] Output: Advice displayed on terminal

[0682] Step 7:

[0683] Based on lifestyle planning and advice, the system will suggest optimal products to users in a virtual store. Product suggestions are optimized for the user's future plans.

[0684] Input: Life planning, advice

[0685] Output: Personalized product recommendations in a virtual store

[0686] Step 8:

[0687] Users send feedback on product suggestions and advice to the server via their terminals, and the server receives this feedback and updates the product suggestions and advice as needed.

[0688] Input: User feedback

[0689] Output: Updated product suggestions and advice

[0690] By the above processing steps, the system of the present invention can provide optimal product proposals and services based on the specific needs and future plans of the user.

[0691] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0692] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and uses generative AI technology to create highly accurate life plans based on detailed asset information collected with the employee's consent, and provides customized advice based on those life plans. Furthermore, this invention combines an emotion engine that recognizes the user's emotions to generate data based on the user's emotions and reflect them in the life plans and advice. This system consists of a server, a terminal (a device used by the employee), an emotion engine, and a user (employee).

[0693] System program and processing explanation

[0694] Collecting basic information

[0695] The server displays an input form on the terminal to collect information on the employee's annual income, family structure, and defined contribution pension plan. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension plan of 80,000 yen are entered.

[0696] Obtaining consent and collecting details

[0697] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0698] Creating a life plan

[0699] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0700] Providing customized advice

[0701] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[0702] Use of emotion engine

[0703] The emotion engine recognizes the user's emotions by analyzing the user's voice input, facial expressions, and text input. For example, emotions such as stress or anxiety may be detected from the user's tone of voice and facial expressions while entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[0704] Presenting optimal plans and responding to feedback

[0705] The server transmits to the terminal a life plan and advice created in consideration of the emotional data. For example, if the user is feeling stressed, advice recommending low-risk investments is generated. If the user transmits feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the user.

[0706] For example, if a user inputs a desire to "make low-risk investments" and the server recognizes feelings of anxiety, the server will generate advice recommending low-risk investment plans that promise stable returns. This advice is more convincing because it takes the user's feelings into account.

[0707] This specific process flow allows users to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[0708] The processing flow will be explained below.

[0709] Step 1:

[0710] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[0711] Step 2:

[0712] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[0713] Step 3:

[0714] The device sends the entered basic information to the server, which stores the received information in a database.

[0715] Step 4:

[0716] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[0717] Step 5:

[0718] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[0719] Step 6:

[0720] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[0721] Step 7:

[0722] The device sends the entered details to the server, which stores the received information in a database.

[0723] Step 8:

[0724] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[0725] Step 9:

[0726] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[0727] Step 10:

[0728] The server transmits the generated advice and life plan to the terminal and notifies the user.

[0729] Step 11:

[0730] The server displays a confirmation message on the terminal to analyze the user's emotions using the emotion engine. If consent is obtained, the server starts the emotion engine.

[0731] Step 12:

[0732] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize the user's emotions. For example, if the user is feeling stressed or anxious while typing, it will send that information to the server.

[0733] Step 13:

[0734] The server generates a life plan and advice optimized for the user's mental state based on the emotional data received from the emotion engine. For example, if the emotion engine determines that the user wants to avoid high risks, it generates advice recommending low-risk investments.

[0735] Step 14:

[0736] The server transmits the optimized life plan and advice to the terminal and notifies the user.

[0737] Step 15:

[0738] The user can use the device to view and confirm the advice and life plan, and can provide feedback if necessary.

[0739] Step 16:

[0740] The server receives feedback from the user and makes any necessary modifications using the regeneration means. The modified life plan and advice are then sent back to the terminal and notified to the user.

[0741] Through this process, users receive detailed emotional life plans and customized advice, which improves employee well-being and provides peace of mind.

[0742] Example 2

[0743] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0744] In employee life planning, it is difficult for conventional systems to aggregate asset information and emotional data for each employee and provide highly accurate, customized plans and advice. As a result, it is not possible to create plans that reflect the specific financial situation and emotional state of employees, which has resulted in insufficient improvement in employee satisfaction and psychological security.

[0745] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0746] In this invention, the server includes means for collecting information on employees' income, family structure, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using AI generation technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's information terminal, means for recognizing the user's emotions, and means for modifying the life plan and advice based on the emotion data. This makes it possible to provide highly accurate life plans and customized advice that reflect not only the employee's specific asset information but also their emotion data.

[0747] "Income" refers to the total income, such as salary and bonuses, that an employee receives within a certain period of time.

[0748] "Family composition" refers to information indicating the number and relationships (spouse, children, etc.) of household members in the employee's household.

[0749] A "defined contribution pension" is a pension system in which employees join, and the amount of pension they receive after retirement is determined by the amount of their contributions and the results of their investments.

[0750] "Detailed asset information" refers to information that shows specific and detailed financial status, such as an employee's savings, stock investments, and mortgage balance.

[0751] "Generative AI technology" refers to technology that uses artificial intelligence to perform calculations based on collected data and generate optimal life plans and advice.

[0752] A "life plan" refers to an employee's long-term life plan and a plan for achieving their financial goals.

[0753] "Customized advice" refers to specific advice or suggestions tailored to an individual employee's circumstances.

[0754] "Information terminal" refers to devices such as computers and smartphones used by employees.

[0755] "Means of recognizing emotions" refers to technology that detects an employee's emotional state by analyzing their voice, facial expressions, text input, etc.

[0756] "Emotional Data" means information indicative of an employee's emotional state that is collected and analyzed using emotion recognition measures.

[0757] This invention is a system that collects employee income, family structure, and defined contribution pension information, and obtains detailed asset information with the employee's consent, then uses generative AI technology to generate highly accurate life plans and provide individually customized advice. Furthermore, by incorporating a means to recognize the user's emotions, it is possible to modify the life plans and advice based on emotional data.

[0758] Server and technologies used

[0759] The server is the central hardware that performs collection and processing, and each step utilizes software and technologies such as:

[0760] Collecting income, family structure, and defined contribution pension information: The server generates an HTML form and sends it to the device. The device uses a browser to display the form and sends the information entered by the user to the server.

[0761] Example: A form for entering an annual income of 6 million yen, married, with one child, and a defined contribution pension of 80,000 yen.

[0762] Consent confirmation to obtain detailed asset information: The server generates a consent confirmation message and sends it to the terminal. The terminal displays the consent confirmation message in a dialog format, and the user enters information such as savings, stock investments, and mortgage balance.

[0763] Example: A form for entering savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[0764] Generating a high-precision life plan using generative AI technology: The server sends prompts to the generative AI model based on the collected basic and detailed information to generate a life plan.

[0765] Example prompt: "Generate a life plan with an income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen."

[0766] Providing customized advice: Based on the generated life plan, the server uses a generative AI model to generate individual advice and notify the device.

[0767] Examples include monthly savings goals, recommended investment percentages, and plans for future education funding.

[0768] Emotion recognition and data reflection: The emotion engine analyzes the user's voice, facial expressions, and text input to detect their emotional state. The server then adjusts the life plan and advice based on the emotional data.

[0769] Example: If a user is feeling stressed, suggest low-risk investments.

[0770] Feedback and life plan regeneration: When the user submits feedback, the server sends prompts based on the feedback to the generative AI model to regenerate the life plan.

[0771] Example: If a user enters "I want to invest with less risk" and anxiety is detected, regenerate a low-risk investment plan.

[0772] In this way, the system aims to improve employee satisfaction and peace of mind by providing highly accurate life plans and customized advice that take into account employees' asset information and emotional data. Companies can use this system as a tool to improve employee welfare.

[0773] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0774] Step 1:

[0775] Collecting basic information

[0776] The server generates a form to collect basic employee information and sends it to the terminal.

[0777] Specific behavior: A form constructed in HTML format is generated, containing input fields for annual income, family composition, and defined contribution pension. This form is sent to the terminal as an HTTP response.

[0778] Input: None (initial step)

[0779] Output: Basic information input form

[0780] The terminal displays the received form to the user.

[0781] What it does: Displays a form in a web browser and waits for user input.

[0782] Input: Form sent from server

[0783] Output: User interface

[0784] The user enters their annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[0785] Specific operation: The user enters their annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen, and presses the send button.

[0786] Input: Annual income, family composition, defined contribution pension information

[0787] Output: Input data

[0788] The terminal transmits the information entered by the user to the server.

[0789] Specific operation: Form data is sent to the server via an HTTP request.

[0790] Input: Basic information entered by the user

[0791] Output: HTTP request (basic information)

[0792] Step 2:

[0793] Obtaining consent and collecting details

[0794] The server generates a consent confirmation message for collecting detailed asset information and sends it to the terminal.

[0795] Specific behavior: Generates a consent confirmation message in HTML dialog format and sends it to the device.

[0796] Input: User basic information

[0797] Output: Consent confirmation message

[0798] The terminal displays a consent confirmation message to the user.

[0799] What it does: Displays a dialog box and waits for user input.

[0800] Input: The consent confirmation message sent by the server

[0801] Output: User interface (agreement confirmation)

[0802] The user clicks the Agree button to open the detailed asset information input form.

[0803] Specific behavior: When you click the consent button, a form to enter detailed information will be displayed.

[0804] Input: Agree

[0805] Output: Detailed information input form

[0806] The user enters information such as savings, stock investments, and mortgage balance, and clicks the submit button.

[0807] Specific actions: Enter 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance, then press the send button.

[0808] Input: Savings, stock investments, mortgage balance, and other details

[0809] Output: Detailed information data

[0810] The terminal sends the details entered by the user to the server.

[0811] Specific behavior: Sends detailed information to the server in the form of an HTTP request.

[0812] Input: User details

[0813] Output: HTTP request (detailed information)

[0814] Step 3:

[0815] Creating a life plan

[0816] The server sends prompts to the generative AI model based on the collected basic and detailed information.

[0817] Specific operation: Generate a prompt such as "Please generate a life plan with income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen" and send it to the generative AI model.

[0818] Input: Basic information, detailed information

[0819] Output: Prompt(Income 6 million yen, Expenses 3 million yen, Savings 2 million yen)

[0820] The generative AI model generates a life plan based on prompts.

[0821] Specific operation: The AI ​​model analyzes the input data and outputs an appropriate life plan and calculation results.

[0822] Input: prompt

[0823] Output: Life Plan

[0824] The server saves the generated life plan and proceeds to the next step.

[0825] Specific behavior: Save the generated life plan in the database.

[0826] Input: Life Plan

[0827] Output: Saved life plan

[0828] Step 4:

[0829] Providing customized advice

[0830] Based on the life plan, the server uses a generative AI model to generate individually customized advice.

[0831] What it does: Generates recommendations including monthly savings goals, recommended investment percentages, and future education funding plans.

[0832] Input: Life Plan

[0833] Output: Advisory data

[0834] The server sends the advice to the terminal and notifies the user.

[0835] Specific operation: The advice content is sent to the device in JSON format and notified to the user via a pop-up notification or other means.

[0836] Input: Advisory data

[0837] Output: Advice given

[0838] The user reviews the advice and sends feedback to the server if desired.

[0839] Specific actions: Check the advice, enter your questions or comments, and then press the send button.

[0840] Input: Feedback

[0841] Output: Feedback sent

[0842] Step 5:

[0843] Emotion recognition and data reflection

[0844] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize their emotional state.

[0845] Specific operation: Analyzes voice and facial expression data collected using a camera and microphone to identify emotions.

[0846] Input: Voice, facial expressions, text input

[0847] Output: Emotion data

[0848] The server modifies the life plan and advice based on the emotional data.

[0849] What it does: If stress is detected, it will revise its advice to suggest less risky investments.

[0850] Input: Emotion data

[0851] Output: Revised life plan and advice

[0852] Step 6:

[0853] Presenting optimal plans and responding to feedback

[0854] The server transmits a life plan and advice that takes into account the emotional data to the terminal.

[0855] Specific operation: The updated life plan and advice are sent to the device in JSON format and the user is notified via a pop-up notification, etc.

[0856] Input: Revised life plan and advice

[0857] Output: Notified remediation plan and advice

[0858] The user then checks the presented life plan and advice and sends feedback as necessary.

[0859] Specific actions: Review the presented plan, enter your wishes and questions, and press the submit button.

[0860] Input: New feedback

[0861] Output: Feedback sent

[0862] The server receives the feedback and regenerates the life plan and advice.

[0863] What it does: Send prompts based on the new feedback to the AI ​​model to recreate the life plan.

[0864] Input: New feedback

[0865] Output: Regenerated life plan and advice

[0866] (Application example 2)

[0867] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0868] A life plan provision system based on employee annual income, family structure, and defined contribution pension information had the problem of being unable to provide advice that took employees' emotions into consideration. Furthermore, when employees provided feedback on their life plans, it was difficult to recreate an optimal life plan based on their emotions. This resulted in a lack of advice that was truly useful and provided employees with psychological reassurance.

[0869] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0870] In this invention, the server includes a means for collecting information on employees' annual income, family structure, and defined contribution pension plans, a means for obtaining detailed asset information with the employee's consent, and a means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information. This makes it possible to provide highly accurate life plans and individually customized advice that take into account the employee's emotional data.

[0871] "Employee" refers to a person who is employed by a company or organization.

[0872] "Annual income information" refers to information on the total income an employee receives in a year.

[0873] "Family composition information" refers to detailed information such as the number of family members and their relationships with each other.

[0874] "Defined contribution pension information" refers to information regarding the defined contribution pension plan to which an employee is enrolled.

[0875] "Consent" refers to an employee's act of giving permission for the collection and use of information.

[0876] "Detailed asset information" refers to detailed financial information such as an employee's savings, investments, and loans.

[0877] "Generative AI technology" refers to technology that uses artificial intelligence technology to generate highly accurate results.

[0878] A "life plan" is a planned arrangement of future income, assets, and living conditions.

[0879] "Individually tailored advice" refers to specific advice that is developed taking into account the employee's individual information.

[0880] An "emotion engine" refers to technology that recognizes emotions by analyzing a user's voice, facial expressions, text input, etc.

[0881] "Emotion data" refers to data relating to the user's emotions recognized by the emotion engine.

[0882] "Devices" refers to devices such as smartphones and computers used by employees.

[0883] "Feedback" refers to employees' opinions, impressions, and requests for corrections regarding the system.

[0884] "Regeneration means" refers to technology for receiving feedback and regenerating a life plan.

[0885] To implement this invention, it is necessary to build a system that uses a server, terminals, employees, an emotion engine, and a generative AI model. The specific system configuration and processing content are described below.

[0886] Collecting basic information

[0887] The terminal displays an input form for collecting the employee's annual income information, family composition information, and defined contribution pension information. The employee enters the necessary information into the input form and clicks the submit button. The entered information is sent to the server.

[0888] For example, information such as annual income of 6 million yen, being married with one child, and having a defined contribution pension of 80,000 yen is entered.

[0889] Obtaining consent and collecting details

[0890] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The employee clicks the consent button to indicate consent, and once the server has confirmed consent, a detailed data input form is displayed on the terminal. The employee enters detailed information such as savings, stock investments, and mortgage balance into this form and clicks the submit button. For example, information such as savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen may be entered.

[0891] Use of emotion engine

[0892] The emotion engine recognizes employees' emotions by analyzing their voice, facial expressions, and text inputs. For example, emotions such as stress or anxiety may be detected from the employee's tone of voice and facial expressions while they are entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[0893] Creating a life plan

[0894] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0895] Example prompt sentence:

[0896] Annual income: 6 million yen

[0897] Family: Married, one child

[0898] Defined contribution pension: 80,000 yen

[0899] Savings: 2 million yen

[0900] Stock investment: 3 million yen

[0901] Mortgage balance: 10 million yen

[0902] Sentiment: I want to invest with less risk

[0903] Providing customized advice

[0904] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and plans for future education expenses. This advice is sent to the employee's device and notified to the employee. The employee can review it and provide feedback to the server if necessary.

[0905] Presenting optimal plans and responding to feedback

[0906] The server transmits the life plan and advice created by taking the emotional data into consideration to the terminal. For example, if the employee is feeling stressed, advice recommending low-risk investments is generated. If the employee provides feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the employee.

[0907] This specific process allows employees to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[0908] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0909] Step 1:

[0910] The terminal displays an input form for collecting employee annual income information, family composition information, and defined contribution pension information.

[0911] Input: None

[0912] Specific operation: The user enters annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[0913] Data processing / calculation: The terminal sends the input information to the server.

[0914] Output: The basic information collected is sent to the server.

[0915] Step 2:

[0916] The server displays a consent confirmation message on the terminal to obtain detailed asset information.

[0917] Input: Basic information (annual income, family composition, defined contribution pension information)

[0918] Specific action: The user clicks the consent button.

[0919] Data processing / calculation: If consent is confirmed, a detailed data entry form will be displayed on the terminal.

[0920] Output: A confirmation that consent has been given and a detailed data entry form will be displayed on the terminal.

[0921] Step 3:

[0922] The device collects detailed asset information (savings, stock investments, mortgage balances, etc.).

[0923] Input: Information entered into the detailed data entry form

[0924] Specific Actions: The user enters detailed asset information and clicks the submit button.

[0925] Data processing / calculation: The terminal sends the entered detailed information to the server.

[0926] Output: The detailed asset information collected is sent to the server.

[0927] Step 4:

[0928] The server uses an emotion engine to analyze the user's voice input, facial expressions, and text input to obtain emotion data.

[0929] Input: Voice input, facial expressions, text input

[0930] Specific operation: The user inputs a preference such as "I want to make an investment with low risk."

[0931] Data processing / calculation: The emotion engine analyzes the input data and generates emotion data.

[0932] Output: The analyzed emotion data is sent to the server.

[0933] Step 5:

[0934] The server uses a generative AI model to create a highly accurate life plan based on the collected basic information, detailed information, and emotional data.

[0935] Input: Basic information, detailed information, emotional data

[0936] Specific operation: The server generates prompt sentences for the generative AI model and creates a life plan based on them.

[0937] Data processing / calculation: The generative AI model calculates future earnings projections and savings goals, generating a highly accurate life plan.

[0938] Output: The generated life plan is obtained.

[0939] Step 6:

[0940] The server generates individually customized advice based on the generated life plan and transmits it to the user terminal.

[0941] Input: Generated life plan

[0942] Specific operation: The server analyzes the life plan and generates appropriate advice.

[0943] Data processing / computation: Generative AI models generate customized advice.

[0944] Output: The generated advice is sent to the user terminal.

[0945] Step 7:

[0946] The terminal receives feedback from the user.

[0947] Input: User feedback

[0948] Specific operation: The user inputs opinions and requests for revisions to the life plan and advice.

[0949] Data processing / calculation: The device sends feedback to the server.

[0950] Output: Feedback is sent to the server.

[0951] Step 8:

[0952] The server receives the feedback and recreates the life plan.

[0953] Input: User feedback, existing life plans, detailed information, emotional data

[0954] Specific operation: The server reuses the generated AI model to create a new life plan.

[0955] Data processing / computation: A generative AI model takes feedback and other information into account to generate a new life plan.

[0956] Output: A regenerated life plan is obtained.

[0957] Step 9:

[0958] The server transmits the regenerated life plan and advice to the user terminal.

[0959] Input: Regenerated life plan

[0960] Specific operation: The server transmits the new life plan and advice to the user terminal.

[0961] Data processing / calculation: The regenerated life plan is displayed on the user's device along with customized advice.

[0962] Output: The new life plan and advice are displayed on the user's terminal.

[0963] This process allows employees to receive detailed life plans and customized advice, and by taking emotions into account, the proposals are more relevant and convincing to the employee.

[0964] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0965] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0966] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0967] [Third embodiment]

[0968] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0969] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0970] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0971] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0972] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0973] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0974] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0975] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0976] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0977] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0978] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0979] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0980] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[0981] System program and processing explanation

[0982] Collecting basic information

[0983] The server displays an input form on the terminal to collect information about the employee's annual income, family structure, and defined contribution pension. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension of 80,000 yen are entered.

[0984] Obtaining consent and collecting details

[0985] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[0986] Creating a life plan

[0987] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[0988] Providing customized advice

[0989] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[0990] Presenting optimal plans and responding to feedback

[0991] When the user sends feedback on the advice or life plan, the server regenerates the life plan using the regeneration means, thereby providing an optimal life plan that meets the user's needs.

[0992] The above is the basic form for implementing the present invention, and by using this system, it is possible to realize highly accurate life planning tailored to the needs of each employee. This system is also useful as a tool for improving corporate employee benefits, and by supporting employees' life planning, it contributes to improving job satisfaction.

[0993] The processing flow will be explained below.

[0994] Step 1:

[0995] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[0996] Step 2:

[0997] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[0998] Step 3:

[0999] The device sends the entered basic information to the server, which stores the received information in a database.

[1000] Step 4:

[1001] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[1002] Step 5:

[1003] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[1004] Step 6:

[1005] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[1006] Step 7:

[1007] The device sends the entered details to the server, which stores the received information in a database.

[1008] Step 8:

[1009] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[1010] Step 9:

[1011] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[1012] Step 10:

[1013] The server transmits the generated advice and life plan to the terminal and notifies the user.

[1014] Step 11:

[1015] The user uses the terminal to display the advice and life plan and confirm the contents.

[1016] Step 12:

[1017] If necessary, the user can use the terminal to send feedback to the server, for example, to request correction if they feel the advice is inappropriate.

[1018] Step 13:

[1019] The server receives feedback from the user and regenerates the life plan using the regeneration means. The regenerated life plan and advice are again sent to the terminal and notified to the user.

[1020] This specific process flow allows users to receive detailed life plans and customized advice, making future planning clearer. Companies can also use this system as a tool to improve employee welfare.

[1021] Example 1

[1022] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1023] In modern society, employees need a wide range of information when creating their own life plans. In addition to basic information such as annual income, family structure, and defined contribution pension plans, there is a demand for tools that allow employees to create highly accurate life plans based on detailed asset information. However, conventional methods have made it difficult to properly collect this information and provide individually customized advice. There are also challenges in regenerating life plans that reflect user feedback. As a result, life plans tailored to the individual needs of employees have not been adequately provided.

[1024] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1025] In this invention, the server includes means for collecting information on employees' annual income, family composition, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's terminal, means for receiving feedback on the generated life plan and advice, and means for regenerating the life plan based on the feedback. This allows employees to receive a highly accurate life plan based on their detailed asset information, and further enables them to regenerate their life plan through feedback on the advice provided.

[1026] "Employee" refers to a person who is employed by a company or organization and performs work.

[1027] "Annual salary" refers to the total income earned by an employee in a year.

[1028] "Family structure" refers to the type and number of family members an employee shares in their household.

[1029] A "defined contribution pension" is a type of pension system in which employees make contributions for the future, with the contribution amount fixed.

[1030] "Consent" refers to an employee's willingness to consent to a particular action or collection of information.

[1031] "Detailed asset information" refers to detailed asset information such as employee savings, stock investments, and mortgage balances.

[1032] "Generative AI technology" refers to technology that uses artificial intelligence to analyze data and generate specific results or predictions.

[1033] A "highly accurate life plan" refers to a plan that makes highly accurate predictions about an employee's future plans based on the information provided.

[1034] "Customized advice" refers to specific advice tailored to an employee's individual circumstances and needs.

[1035] "Terminal" refers to an electronic device used by employees to input information or receive advice.

[1036] "Feedback" refers to opinions and reactions from employees, based on which the system's results and advice can be modified.

[1037] "Regeneration means" refers to the function of recreating a life plan based on feedback.

[1038] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[1039] The server displays an input form on the terminal to collect information about the employee's annual income, family composition, and defined contribution pension. The terminal displays this input form, and the user uses the terminal to enter the necessary information into this form. When the user clicks the submit button, the entered information is sent to the server. This basic information includes annual income, family composition, and defined contribution pension information. As a specific example, an annual income of 6 million yen, being married with one child, and a defined contribution pension of 80,000 yen are entered.

[1040] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The terminal displays this consent confirmation message, and the user clicks the consent button to indicate consent. Once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the send button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[1041] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. This generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan. The system inputs prompts such as age, family composition, current savings, and investment status into the model to output a specific life plan.

[1042] As a specific example, a user's basic information is entered as an annual income of 7 million yen, family structure as married with two children, and a defined contribution pension of 120,000 yen, while detailed information includes savings of 3 million yen, stock investments of 2 million yen, and a mortgage balance of 12 million yen. Based on this, the generative AI model calculates a "plan to increase average annual savings to 3 million yen over the next 10 years."

[1043] The server generates individually customized advice based on the generated life plan. For example, it may include monthly savings goals, recommended investment percentages, and plans for future education expenses. The server sends this advice to the terminal and notifies the user. The user can review the advice and send feedback to the server if necessary. Specific advice provided may include "save 50,000 yen each month and invest 20% in stocks."

[1044] When a user sends feedback on advice or a life plan, the server regenerates the life plan using the regeneration means. This allows the server to provide an optimal life plan that meets the user's needs. For example, if a user sends feedback such as "I want to increase my monthly investment amount to 70,000 yen," the server generates a new life plan based on this information and presents it to the user again.

[1045] By using this system, employees can receive specific advice on their own life plans, improving the accuracy and adaptability of their life plans.It is also useful as a corporate employee benefits tool, supporting employees' life planning and contributing to improving job satisfaction.

[1046] An example of a prompt is, "Please enter your employee's annual income, family composition, and defined contribution pension information. Next, add detailed asset information such as savings, stock investments, and mortgage balance. We will generate your life plan based on this information."

[1047] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1048] Step 1:

[1049] Collecting basic information

[1050] The server generates an input form for collecting information about the user's annual income, family structure, and defined contribution pension plan, and sends it to the terminal. The input form includes specific fields (annual income, family structure, defined contribution pension plan).

[1051] The terminal displays the input form received from the server on the screen, allowing the user to enter the required information.

[1052] The user enters information about their annual income, family structure, and defined contribution pension plan into this form, and then clicks the submit button to send the information to the server. For example, the user enters information such as an annual income of 6 million yen, being married with one child, and a defined contribution pension plan of 80,000 yen.

[1053] Input: Annual income, family composition, defined contribution pension information

[1054] Output: Basic information sent to the server

[1055] Step 2:

[1056] Obtaining consent and collecting details

[1057] The server stores the collected basic information, and then generates and sends to the terminal a consent confirmation message for obtaining detailed asset information. The confirmation message includes an consent button.

[1058] The terminal displays the consent confirmation message received from the server on the screen.

[1059] The user indicates their consent by clicking the accept button. Once consent is confirmed, the server generates a detailed data entry form (savings, stock investments, mortgage balance, etc.) and sends it to the terminal.

[1060] The terminal displays a detailed data entry form on the screen.

[1061] The user enters detailed information (savings, stock investment, mortgage balance, etc.) and clicks the send button to send it to the server. For example, the user enters information such as savings of 2 million yen, stock investment of 3 million yen, and mortgage balance of 10 million yen.

[1062] Input: Confirm consent, detailed asset information

[1063] Output: Detailed asset information sent to the server

[1064] Step 3:

[1065] Creating a life plan

[1066] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The collected information is input into the generative AI model as a prompt. For example, it generates a prompt such as "annual income of 7 million yen, married, two children, savings of 3 million yen, stock investments of 2 million yen, and mortgage balance of 12 million yen."

[1067] Based on the information provided, the generative AI model calculates future earnings projections and savings goals to generate an optimal life plan.

[1068] Input: Basic information, detailed asset information

[1069] Output: Generated life plan

[1070] Step 4:

[1071] Providing customized advice

[1072] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[1073] The server sends the customized advice to the terminal and notifies the user.

[1074] The terminal displays the advice received from the server on the screen.

[1075] The user can check the advice and send feedback to the server if necessary. For example, advice such as "Save 50,000 yen every month and invest 20% in stocks" is provided.

[1076] Input: Generated life plan

[1077] Output: personalized advice

[1078] Step 5:

[1079] Responding to feedback and regenerating your life plan

[1080] When a user sends feedback on advice or a life plan, the server accepts the feedback.

[1081] Based on the feedback, the server regenerates the life plan using the regeneration means, and again inputs the collected information and the user's feedback as prompts into the generative AI model.

[1082] The server transmits the regenerated life plan to the terminal.

[1083] The terminal displays the updated life plan on the screen and notifies the user.

[1084] Input: User feedback

[1085] Output: Regenerated life plan

[1086] (Application example 1)

[1087] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1088] Conventional life planning systems lack the ability to provide personalized product recommendations based on individual financial situations and to continually update in response to user feedback, making it difficult for users to find the products that best fit their specific needs and future plans.

[1089] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1090] In this invention, the server includes means for collecting employee income information, family composition information, and defined contribution pension information, means for obtaining detailed financial asset information with the employee's consent, means for creating a highly accurate life planning plan using generative artificial intelligence technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life planning plan, means for displaying the advice and life planning plan on the employee's terminal, means for making individualized product suggestions in a virtual store based on the user's financial situation and life planning plan, and means for continually updating product suggestions based on user feedback. This makes it possible to provide product suggestions and services that are optimal for the user's specific needs and future plans.

[1091] "Income information" is information about an employee's annual income or salary.

[1092] "Family composition information" is information about the number of family members in an employee's household and their composition.

[1093] "Defined contribution pension information" is information regarding the amount and type of defined contribution pension to which an employee is enrolled.

[1094] "Detailed financial asset information" refers to information about specific financial assets such as savings, stock investments, and mortgage balances held by employees.

[1095] "Generative AI technology" is an AI technology that enables highly accurate planning and analysis based on various collected data.

[1096] A "life planning plan" is a future living plan that optimizes an employee's income, expenses, and assets.

[1097] "Customized advice" means specific advice tailored to each employee's individual situation based on collected information.

[1098] A "terminal" is a device that allows employees to enter information and view results.

[1099] A "virtual store" is a virtual business location that offers products and services over the Internet.

[1100] "Product proposals" are proposals for products and services recommended based on the user's financial situation and lifestyle planning plans.

[1101] "Feedback" refers to information that reflects user opinions, impressions, and areas for improvement.

[1102] "Updated on a regular basis" means changing information and proposals in a timely manner as needed.

[1103] MODE FOR CARRYING OUT THE INVENTION

[1104] The system for realizing this invention basically consists of a server, a terminal (a device used by the user), and a user. This system collects employee income information, family composition information, and defined contribution pension information, and obtains detailed financial asset information with the employee's consent. Based on this information, generative artificial intelligence technology is used to create a highly accurate life planning plan and provide individually customized advice. In addition, product suggestions are updated as needed based on user feedback, and personalized product suggestions are made in a virtual store.

[1105] Hardware and Software Configuration

[1106] The system is implemented using the following hardware and software:

[1107] Hardware: Smartphone, Head-Mounted Display (HMD), Server

[1108] Software: Python (programming language), Flask (for building web applications), TensorFlow (for generative artificial intelligence models)

[1109] Data processing and calculation

[1110] 1. Basic information collected:

[1111] Users use their smartphones or HMDs to input information about their income, family structure, and defined contribution pension plans, which is then sent to the server.

[1112] 2. Obtaining consent and collecting details:

[1113] The server displays a message on the terminal asking for consent to the collection of detailed financial asset information. If consent is given, the user enters details such as savings, stock investments, and mortgage balances, which are also sent to the server.

[1114] 3. Life planning generation:

[1115] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence model using TensorFlow. For example, it calculates future earnings forecasts and savings goals based on income, expenses, and assets to generate an optimal life planning plan.

[1116] 4. Providing customized advice:

[1117] Based on the generated life planning plan, the server generates individually customized advice and sends it to the user's terminal for display, allowing the user to create an action plan based on it.

[1118] 5. Product suggestions in virtual stores:

[1119] Based on the user's financial situation and life planning, personalized product recommendations are made within the virtual store, allowing users to easily find the products that best fit their future plans.

[1120] 6. Receiving Feedback and Updating:

[1121] The server receives feedback from users and updates product suggestions and advice as needed, ensuring that users always receive optimal suggestions based on the latest information.

[1122] Specific examples

[1123] For example, consider a user who has an annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen. If this user inputs their savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen, generative artificial intelligence technology will be used to generate a lifestyle planning plan and product recommendations that are optimal for that user. Data can be entered using the following prompt sentences:

[1124] Prompt Sentence Examples

[1125] Generate the optimal life plan and product proposals based on the following: annual income of 6 million yen, married family with one child, 80,000 yen in defined contribution pension. Savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[1126] In this way, it becomes possible to propose products and provide services that are optimal for the user's specific needs and future plans.

[1127] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1128] Step 1:

[1129] The user uses a smartphone or head-mounted display (HMD) to enter employee income information, family composition information, and defined contribution pension information into an input form on the terminal, which is then sent to the server.

[1130] Input: Income information, family structure information, defined contribution pension information

[1131] Output: Basic information sent to the server

[1132] Step 2:

[1133] The server displays a message on the terminal confirming consent to the collection of detailed financial asset information. When the user clicks the consent button, a detailed data input form is displayed on the terminal.

[1134] Input: Consent confirmation message

[1135] Output: User consent result, detailed data entry form

[1136] Step 3:

[1137] The user enters detailed information such as savings, stock investments, and mortgage balance into a detailed data input form and sends it to the server, which then receives detailed financial asset information.

[1138] Input: Savings, stock investments, mortgage balance, and other details

[1139] Output: Details sent to the server

[1140] Step 4:

[1141] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence (AI) model, specifically, TensorFlow to calculate future income projections and savings goals.

[1142] Input: Basic information, detailed information

[1143] Data processing / calculation: Calculation using generative artificial intelligence models

[1144] Output: Highly accurate life planning

[1145] Step 5:

[1146] Based on the generated life planning plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[1147] Input: Life Planning Plan

[1148] Output: Advice

[1149] Step 6:

[1150] The server sends the generated advice to the terminal and notifies the user, who can then check the advice content through the terminal.

[1151] Input: Advice

[1152] Output: Advice displayed on terminal

[1153] Step 7:

[1154] Based on lifestyle planning and advice, the system will suggest optimal products to users in a virtual store. Product suggestions are optimized for the user's future plans.

[1155] Input: Life planning, advice

[1156] Output: Personalized product recommendations in a virtual store

[1157] Step 8:

[1158] Users send feedback on product suggestions and advice to the server via their terminals, and the server receives this feedback and updates the product suggestions and advice as needed.

[1159] Input: User feedback

[1160] Output: Updated product suggestions and advice

[1161] By the above processing steps, the system of the present invention can provide optimal product proposals and services based on the specific needs and future plans of the user.

[1162] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1163] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and uses generative AI technology to create highly accurate life plans based on detailed asset information collected with the employee's consent, and provides customized advice based on those life plans. Furthermore, this invention combines an emotion engine that recognizes the user's emotions to generate data based on the user's emotions and reflect them in the life plans and advice. This system consists of a server, a terminal (a device used by the employee), an emotion engine, and a user (employee).

[1164] System program and processing explanation

[1165] Collecting basic information

[1166] The server displays an input form on the terminal to collect information on the employee's annual income, family structure, and defined contribution pension plan. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension plan of 80,000 yen are entered.

[1167] Obtaining consent and collecting details

[1168] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[1169] Creating a life plan

[1170] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[1171] Providing customized advice

[1172] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[1173] Use of emotion engine

[1174] The emotion engine recognizes the user's emotions by analyzing the user's voice input, facial expressions, and text input. For example, emotions such as stress or anxiety may be detected from the user's tone of voice and facial expressions while entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[1175] Presenting optimal plans and responding to feedback

[1176] The server transmits to the terminal a life plan and advice created in consideration of the emotional data. For example, if the user is feeling stressed, advice recommending low-risk investments is generated. If the user transmits feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the user.

[1177] For example, if a user inputs a desire to "make low-risk investments" and the server recognizes feelings of anxiety, the server will generate advice recommending low-risk investment plans that promise stable returns. This advice is more convincing because it takes the user's feelings into account.

[1178] This specific process flow allows users to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[1179] The processing flow will be explained below.

[1180] Step 1:

[1181] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[1182] Step 2:

[1183] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[1184] Step 3:

[1185] The device sends the entered basic information to the server, which stores the received information in a database.

[1186] Step 4:

[1187] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[1188] Step 5:

[1189] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[1190] Step 6:

[1191] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[1192] Step 7:

[1193] The device sends the entered details to the server, which stores the received information in a database.

[1194] Step 8:

[1195] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[1196] Step 9:

[1197] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[1198] Step 10:

[1199] The server transmits the generated advice and life plan to the terminal and notifies the user.

[1200] Step 11:

[1201] The server displays a confirmation message on the terminal to analyze the user's emotions using the emotion engine. If consent is obtained, the server starts the emotion engine.

[1202] Step 12:

[1203] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize the user's emotions. For example, if the user is feeling stressed or anxious while typing, it will send that information to the server.

[1204] Step 13:

[1205] The server generates a life plan and advice optimized for the user's mental state based on the emotional data received from the emotion engine. For example, if the emotion engine determines that the user wants to avoid high risks, it generates advice recommending low-risk investments.

[1206] Step 14:

[1207] The server transmits the optimized life plan and advice to the terminal and notifies the user.

[1208] Step 15:

[1209] The user can use the device to view and confirm the advice and life plan, and can provide feedback if necessary.

[1210] Step 16:

[1211] The server receives feedback from the user and makes any necessary modifications using the regeneration means. The modified life plan and advice are then sent back to the terminal and notified to the user.

[1212] Through this process, users receive detailed emotional life plans and customized advice, which improves employee well-being and provides peace of mind.

[1213] Example 2

[1214] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1215] In employee life planning, it is difficult for conventional systems to aggregate asset information and emotional data for each employee and provide highly accurate, customized plans and advice. As a result, it is not possible to create plans that reflect the specific financial situation and emotional state of employees, which has resulted in insufficient improvement in employee satisfaction and psychological security.

[1216] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1217] In this invention, the server includes means for collecting information on employees' income, family structure, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using AI generation technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's information terminal, means for recognizing the user's emotions, and means for modifying the life plan and advice based on the emotion data. This makes it possible to provide highly accurate life plans and customized advice that reflect not only the employee's specific asset information but also their emotion data.

[1218] "Income" refers to the total income, such as salary and bonuses, that an employee receives within a certain period of time.

[1219] "Family composition" refers to information indicating the number and relationships (spouse, children, etc.) of household members in the employee's household.

[1220] A "defined contribution pension" is a pension system in which employees join, and the amount of pension they receive after retirement is determined by the amount of their contributions and the results of their investments.

[1221] "Detailed asset information" refers to information that shows specific and detailed financial status, such as an employee's savings, stock investments, and mortgage balance.

[1222] "Generative AI technology" refers to technology that uses artificial intelligence to perform calculations based on collected data and generate optimal life plans and advice.

[1223] A "life plan" refers to an employee's long-term life plan and a plan for achieving their financial goals.

[1224] "Customized advice" refers to specific advice or suggestions tailored to an individual employee's circumstances.

[1225] "Information terminal" refers to devices such as computers and smartphones used by employees.

[1226] "Means of recognizing emotions" refers to technology that detects an employee's emotional state by analyzing their voice, facial expressions, text input, etc.

[1227] "Emotional Data" means information indicative of an employee's emotional state that is collected and analyzed using emotion recognition measures.

[1228] This invention is a system that collects employee income, family structure, and defined contribution pension information, and obtains detailed asset information with the employee's consent, then uses generative AI technology to generate highly accurate life plans and provide individually customized advice. Furthermore, by incorporating a means to recognize the user's emotions, it is possible to modify the life plans and advice based on emotional data.

[1229] Server and technologies used

[1230] The server is the central hardware that performs collection and processing, and each step utilizes software and technologies such as:

[1231] Collecting income, family structure, and defined contribution pension information: The server generates an HTML form and sends it to the device. The device uses a browser to display the form and sends the information entered by the user to the server.

[1232] Example: A form for entering an annual income of 6 million yen, married, with one child, and a defined contribution pension of 80,000 yen.

[1233] Consent confirmation to obtain detailed asset information: The server generates a consent confirmation message and sends it to the terminal. The terminal displays the consent confirmation message in a dialog format, and the user enters information such as savings, stock investments, and mortgage balance.

[1234] Example: A form for entering savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[1235] Generating a high-precision life plan using generative AI technology: The server sends prompts to the generative AI model based on the collected basic and detailed information to generate a life plan.

[1236] Example prompt: "Generate a life plan with an income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen."

[1237] Providing customized advice: Based on the generated life plan, the server uses a generative AI model to generate individual advice and notify the device.

[1238] Examples include monthly savings goals, recommended investment percentages, and plans for future education funding.

[1239] Emotion recognition and data reflection: The emotion engine analyzes the user's voice, facial expressions, and text input to detect their emotional state. The server then adjusts the life plan and advice based on the emotional data.

[1240] Example: If a user is feeling stressed, suggest low-risk investments.

[1241] Feedback and life plan regeneration: When the user submits feedback, the server sends prompts based on the feedback to the generative AI model to regenerate the life plan.

[1242] Example: If a user enters "I want to invest with less risk" and anxiety is detected, regenerate a low-risk investment plan.

[1243] In this way, the system aims to improve employee satisfaction and peace of mind by providing highly accurate life plans and customized advice that take into account employees' asset information and emotional data. Companies can use this system as a tool to improve employee welfare.

[1244] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1245] Step 1:

[1246] Collecting basic information

[1247] The server generates a form to collect basic employee information and sends it to the terminal.

[1248] Specific behavior: A form constructed in HTML format is generated, containing input fields for annual income, family composition, and defined contribution pension. This form is sent to the terminal as an HTTP response.

[1249] Input: None (initial step)

[1250] Output: Basic information input form

[1251] The terminal displays the received form to the user.

[1252] What it does: Displays a form in a web browser and waits for user input.

[1253] Input: Form sent from server

[1254] Output: User interface

[1255] The user enters their annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[1256] Specific operation: The user enters their annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen, and presses the send button.

[1257] Input: Annual income, family composition, defined contribution pension information

[1258] Output: Input data

[1259] The terminal transmits the information entered by the user to the server.

[1260] Specific operation: Form data is sent to the server via an HTTP request.

[1261] Input: Basic information entered by the user

[1262] Output: HTTP request (basic information)

[1263] Step 2:

[1264] Obtaining consent and collecting details

[1265] The server generates a consent confirmation message for collecting detailed asset information and sends it to the terminal.

[1266] Specific behavior: Generates a consent confirmation message in HTML dialog format and sends it to the device.

[1267] Input: User basic information

[1268] Output: Consent confirmation message

[1269] The terminal displays a consent confirmation message to the user.

[1270] What it does: Displays a dialog box and waits for user input.

[1271] Input: The consent confirmation message sent by the server

[1272] Output: User interface (agreement confirmation)

[1273] The user clicks the Agree button to open the detailed asset information input form.

[1274] Specific behavior: When you click the consent button, a form to enter detailed information will be displayed.

[1275] Input: Agree

[1276] Output: Detailed information input form

[1277] The user enters information such as savings, stock investments, and mortgage balance, and clicks the submit button.

[1278] Specific actions: Enter 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance, then press the send button.

[1279] Input: Savings, stock investments, mortgage balance, and other details

[1280] Output: Detailed information data

[1281] The terminal sends the details entered by the user to the server.

[1282] Specific behavior: Sends detailed information to the server in the form of an HTTP request.

[1283] Input: User details

[1284] Output: HTTP request (detailed information)

[1285] Step 3:

[1286] Creating a life plan

[1287] The server sends prompts to the generative AI model based on the collected basic and detailed information.

[1288] Specific operation: Generate a prompt such as "Please generate a life plan with income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen" and send it to the generative AI model.

[1289] Input: Basic information, detailed information

[1290] Output: Prompt(Income 6 million yen, Expenses 3 million yen, Savings 2 million yen)

[1291] The generative AI model generates a life plan based on prompts.

[1292] Specific operation: The AI ​​model analyzes the input data and outputs an appropriate life plan and calculation results.

[1293] Input: prompt

[1294] Output: Life Plan

[1295] The server saves the generated life plan and proceeds to the next step.

[1296] Specific behavior: Save the generated life plan in the database.

[1297] Input: Life Plan

[1298] Output: Saved life plan

[1299] Step 4:

[1300] Providing customized advice

[1301] Based on the life plan, the server uses a generative AI model to generate individually customized advice.

[1302] What it does: Generates recommendations including monthly savings goals, recommended investment percentages, and future education funding plans.

[1303] Input: Life Plan

[1304] Output: Advisory data

[1305] The server sends the advice to the terminal and notifies the user.

[1306] Specific operation: The advice content is sent to the device in JSON format and notified to the user via a pop-up notification or other means.

[1307] Input: Advisory data

[1308] Output: Advice given

[1309] The user reviews the advice and sends feedback to the server if desired.

[1310] Specific actions: Check the advice, enter your questions or comments, and then press the send button.

[1311] Input: Feedback

[1312] Output: Feedback sent

[1313] Step 5:

[1314] Emotion recognition and data reflection

[1315] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize their emotional state.

[1316] Specific operation: Analyzes voice and facial expression data collected using a camera and microphone to identify emotions.

[1317] Input: Voice, facial expressions, text input

[1318] Output: Emotion data

[1319] The server modifies the life plan and advice based on the emotional data.

[1320] What it does: If stress is detected, it will revise its advice to suggest less risky investments.

[1321] Input: Emotion data

[1322] Output: Revised life plan and advice

[1323] Step 6:

[1324] Presenting optimal plans and responding to feedback

[1325] The server transmits a life plan and advice that takes into account the emotional data to the terminal.

[1326] Specific operation: The updated life plan and advice are sent to the device in JSON format and the user is notified via a pop-up notification, etc.

[1327] Input: Revised life plan and advice

[1328] Output: Notified remediation plan and advice

[1329] The user then checks the presented life plan and advice and sends feedback as necessary.

[1330] Specific actions: Review the presented plan, enter your wishes and questions, and press the submit button.

[1331] Input: New feedback

[1332] Output: Feedback sent

[1333] The server receives the feedback and regenerates the life plan and advice.

[1334] What it does: Send prompts based on the new feedback to the AI ​​model to recreate the life plan.

[1335] Input: New feedback

[1336] Output: Regenerated life plan and advice

[1337] (Application example 2)

[1338] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1339] A life plan provision system based on employee annual income, family structure, and defined contribution pension information had the problem of being unable to provide advice that took employees' emotions into consideration. Furthermore, when employees provided feedback on their life plans, it was difficult to recreate an optimal life plan based on their emotions. This resulted in a lack of advice that was truly useful and provided employees with psychological reassurance.

[1340] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1341] In this invention, the server includes a means for collecting information on employees' annual income, family structure, and defined contribution pension plans, a means for obtaining detailed asset information with the employee's consent, and a means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information. This makes it possible to provide highly accurate life plans and individually customized advice that take into account the employee's emotional data.

[1342] "Employee" refers to a person who is employed by a company or organization.

[1343] "Annual income information" refers to information on the total income an employee receives in a year.

[1344] "Family composition information" refers to detailed information such as the number of family members and their relationships with each other.

[1345] "Defined contribution pension information" refers to information regarding the defined contribution pension plan to which an employee is enrolled.

[1346] "Consent" refers to an employee's act of giving permission for the collection and use of information.

[1347] "Detailed asset information" refers to detailed financial information such as an employee's savings, investments, and loans.

[1348] "Generative AI technology" refers to technology that uses artificial intelligence technology to generate highly accurate results.

[1349] A "life plan" is a planned arrangement of future income, assets, and living conditions.

[1350] "Individually tailored advice" refers to specific advice that is developed taking into account the employee's individual information.

[1351] An "emotion engine" refers to technology that recognizes emotions by analyzing a user's voice, facial expressions, text input, etc.

[1352] "Emotion data" refers to data relating to the user's emotions recognized by the emotion engine.

[1353] "Devices" refers to devices such as smartphones and computers used by employees.

[1354] "Feedback" refers to employees' opinions, impressions, and requests for corrections regarding the system.

[1355] "Regeneration means" refers to technology for receiving feedback and regenerating a life plan.

[1356] To implement this invention, it is necessary to build a system that uses a server, terminals, employees, an emotion engine, and a generative AI model. The specific system configuration and processing content are described below.

[1357] Collecting basic information

[1358] The terminal displays an input form for collecting the employee's annual income information, family composition information, and defined contribution pension information. The employee enters the necessary information into the input form and clicks the submit button. The entered information is sent to the server.

[1359] For example, information such as annual income of 6 million yen, being married with one child, and having a defined contribution pension of 80,000 yen is entered.

[1360] Obtaining consent and collecting details

[1361] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The employee clicks the consent button to indicate consent, and once the server has confirmed consent, a detailed data input form is displayed on the terminal. The employee enters detailed information such as savings, stock investments, and mortgage balance into this form and clicks the submit button. For example, information such as savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen may be entered.

[1362] Use of emotion engine

[1363] The emotion engine recognizes employees' emotions by analyzing their voice, facial expressions, and text inputs. For example, emotions such as stress or anxiety may be detected from the employee's tone of voice and facial expressions while they are entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[1364] Creating a life plan

[1365] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[1366] Example prompt sentence:

[1367] Annual income: 6 million yen

[1368] Family: Married, one child

[1369] Defined contribution pension: 80,000 yen

[1370] Savings: 2 million yen

[1371] Stock investment: 3 million yen

[1372] Mortgage balance: 10 million yen

[1373] Sentiment: I want to invest with less risk

[1374] Providing customized advice

[1375] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and plans for future education expenses. This advice is sent to the employee's device and notified to the employee. The employee can review it and provide feedback to the server if necessary.

[1376] Presenting optimal plans and responding to feedback

[1377] The server transmits the life plan and advice created by taking the emotional data into consideration to the terminal. For example, if the employee is feeling stressed, advice recommending low-risk investments is generated. If the employee provides feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the employee.

[1378] This specific process allows employees to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[1379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1380] Step 1:

[1381] The terminal displays an input form for collecting employee annual income information, family composition information, and defined contribution pension information.

[1382] Input: None

[1383] Specific operation: The user enters annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[1384] Data processing / calculation: The terminal sends the input information to the server.

[1385] Output: The basic information collected is sent to the server.

[1386] Step 2:

[1387] The server displays a consent confirmation message on the terminal to obtain detailed asset information.

[1388] Input: Basic information (annual income, family composition, defined contribution pension information)

[1389] Specific action: The user clicks the consent button.

[1390] Data processing / calculation: If consent is confirmed, a detailed data entry form will be displayed on the terminal.

[1391] Output: A confirmation that consent has been given and a detailed data entry form will be displayed on the terminal.

[1392] Step 3:

[1393] The device collects detailed asset information (savings, stock investments, mortgage balances, etc.).

[1394] Input: Information entered into the detailed data entry form

[1395] Specific Actions: The user enters detailed asset information and clicks the submit button.

[1396] Data processing / calculation: The terminal sends the entered detailed information to the server.

[1397] Output: The detailed asset information collected is sent to the server.

[1398] Step 4:

[1399] The server uses an emotion engine to analyze the user's voice input, facial expressions, and text input to obtain emotion data.

[1400] Input: Voice input, facial expressions, text input

[1401] Specific operation: The user inputs a preference such as "I want to make an investment with low risk."

[1402] Data processing / calculation: The emotion engine analyzes the input data and generates emotion data.

[1403] Output: The analyzed emotion data is sent to the server.

[1404] Step 5:

[1405] The server uses a generative AI model to create a highly accurate life plan based on the collected basic information, detailed information, and emotional data.

[1406] Input: Basic information, detailed information, emotional data

[1407] Specific operation: The server generates prompt sentences for the generative AI model and creates a life plan based on them.

[1408] Data processing / calculation: The generative AI model calculates future earnings projections and savings goals, generating a highly accurate life plan.

[1409] Output: The generated life plan is obtained.

[1410] Step 6:

[1411] The server generates individually customized advice based on the generated life plan and transmits it to the user terminal.

[1412] Input: Generated life plan

[1413] Specific operation: The server analyzes the life plan and generates appropriate advice.

[1414] Data processing / computation: Generative AI models generate customized advice.

[1415] Output: The generated advice is sent to the user terminal.

[1416] Step 7:

[1417] The terminal receives feedback from the user.

[1418] Input: User feedback

[1419] Specific operation: The user inputs opinions and requests for revisions to the life plan and advice.

[1420] Data processing / calculation: The device sends feedback to the server.

[1421] Output: Feedback is sent to the server.

[1422] Step 8:

[1423] The server receives the feedback and recreates the life plan.

[1424] Input: User feedback, existing life plans, detailed information, emotional data

[1425] Specific operation: The server reuses the generated AI model to create a new life plan.

[1426] Data processing / computation: A generative AI model takes feedback and other information into account to generate a new life plan.

[1427] Output: A regenerated life plan is obtained.

[1428] Step 9:

[1429] The server transmits the regenerated life plan and advice to the user terminal.

[1430] Input: Regenerated life plan

[1431] Specific operation: The server transmits the new life plan and advice to the user terminal.

[1432] Data processing / calculation: The regenerated life plan is displayed on the user's device along with customized advice.

[1433] Output: The new life plan and advice are displayed on the user's terminal.

[1434] This process allows employees to receive detailed life plans and customized advice, and by taking emotions into account, the proposals are more relevant and convincing to the employee.

[1435] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1436] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1437] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1438] [Fourth embodiment]

[1439] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1440] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1441] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1442] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1443] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1444] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1445] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1446] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1447] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1448] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1449] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1450] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1451] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1452] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[1453] System program and processing explanation

[1454] Collecting basic information

[1455] The server displays an input form on the terminal to collect information about the employee's annual income, family structure, and defined contribution pension. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension of 80,000 yen are entered.

[1456] Obtaining consent and collecting details

[1457] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[1458] Creating a life plan

[1459] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[1460] Providing customized advice

[1461] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[1462] Presenting optimal plans and responding to feedback

[1463] When the user sends feedback on the advice or life plan, the server regenerates the life plan using the regeneration means, thereby providing an optimal life plan that meets the user's needs.

[1464] The above is the basic form for implementing the present invention, and by using this system, it is possible to realize highly accurate life planning tailored to the needs of each employee. This system is also useful as a tool for improving corporate employee benefits, and by supporting employees' life planning, it contributes to improving job satisfaction.

[1465] The processing flow will be explained below.

[1466] Step 1:

[1467] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[1468] Step 2:

[1469] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[1470] Step 3:

[1471] The device sends the entered basic information to the server, which stores the received information in a database.

[1472] Step 4:

[1473] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[1474] Step 5:

[1475] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[1476] Step 6:

[1477] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[1478] Step 7:

[1479] The device sends the entered details to the server, which stores the received information in a database.

[1480] Step 8:

[1481] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[1482] Step 9:

[1483] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[1484] Step 10:

[1485] The server transmits the generated advice and life plan to the terminal and notifies the user.

[1486] Step 11:

[1487] The user uses the terminal to display the advice and life plan and confirm the contents.

[1488] Step 12:

[1489] If necessary, the user can use the terminal to send feedback to the server, for example, to request correction if they feel the advice is inappropriate.

[1490] Step 13:

[1491] The server receives feedback from the user and regenerates the life plan using the regeneration means. The regenerated life plan and advice are again sent to the terminal and notified to the user.

[1492] This specific process flow allows users to receive detailed life plans and customized advice, making future planning clearer. Companies can also use this system as a tool to improve employee welfare.

[1493] Example 1

[1494] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1495] In modern society, employees need a wide range of information when creating their own life plans. In addition to basic information such as annual income, family structure, and defined contribution pension plans, there is a demand for tools that allow employees to create highly accurate life plans based on detailed asset information. However, conventional methods have made it difficult to properly collect this information and provide individually customized advice. There are also challenges in regenerating life plans that reflect user feedback. As a result, life plans tailored to the individual needs of employees have not been adequately provided.

[1496] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1497] In this invention, the server includes means for collecting information on employees' annual income, family composition, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's terminal, means for receiving feedback on the generated life plan and advice, and means for regenerating the life plan based on the feedback. This allows employees to receive a highly accurate life plan based on their detailed asset information, and further enables them to regenerate their life plan through feedback on the advice provided.

[1498] "Employee" refers to a person who is employed by a company or organization and performs work.

[1499] "Annual salary" refers to the total income earned by an employee in a year.

[1500] "Family structure" refers to the type and number of family members an employee shares in their household.

[1501] A "defined contribution pension" is a type of pension system in which employees make contributions for the future, with the contribution amount fixed.

[1502] "Consent" refers to an employee's willingness to consent to a particular action or collection of information.

[1503] "Detailed asset information" refers to detailed asset information such as employee savings, stock investments, and mortgage balances.

[1504] "Generative AI technology" refers to technology that uses artificial intelligence to analyze data and generate specific results or predictions.

[1505] A "highly accurate life plan" refers to a plan that makes highly accurate predictions about an employee's future plans based on the information provided.

[1506] "Customized advice" refers to specific advice tailored to an employee's individual circumstances and needs.

[1507] "Terminal" refers to an electronic device used by employees to input information or receive advice.

[1508] "Feedback" refers to opinions and reactions from employees, based on which the system's results and advice can be modified.

[1509] "Regeneration means" refers to the function of recreating a life plan based on feedback.

[1510] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and creates highly accurate life plans using AI technology based on detailed asset information collected with the employees' consent, and provides customized advice based on the life plans. This system consists of a server, terminals (devices used by employees), and users (employees).

[1511] The server displays an input form on the terminal to collect information about the employee's annual income, family composition, and defined contribution pension. The terminal displays this input form, and the user uses the terminal to enter the necessary information into this form. When the user clicks the submit button, the entered information is sent to the server. This basic information includes annual income, family composition, and defined contribution pension information. As a specific example, an annual income of 6 million yen, being married with one child, and a defined contribution pension of 80,000 yen are entered.

[1512] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The terminal displays this consent confirmation message, and the user clicks the consent button to indicate consent. Once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the send button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[1513] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. This generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan. The system inputs prompts such as age, family composition, current savings, and investment status into the model to output a specific life plan.

[1514] As a specific example, a user's basic information is entered as an annual income of 7 million yen, family structure as married with two children, and a defined contribution pension of 120,000 yen, while detailed information includes savings of 3 million yen, stock investments of 2 million yen, and a mortgage balance of 12 million yen. Based on this, the generative AI model calculates a "plan to increase average annual savings to 3 million yen over the next 10 years."

[1515] The server generates individually customized advice based on the generated life plan. For example, it may include monthly savings goals, recommended investment percentages, and plans for future education expenses. The server sends this advice to the terminal and notifies the user. The user can review the advice and send feedback to the server if necessary. Specific advice provided may include "save 50,000 yen each month and invest 20% in stocks."

[1516] When a user sends feedback on advice or a life plan, the server regenerates the life plan using the regeneration means. This allows the server to provide an optimal life plan that meets the user's needs. For example, if a user sends feedback such as "I want to increase my monthly investment amount to 70,000 yen," the server generates a new life plan based on this information and presents it to the user again.

[1517] By using this system, employees can receive specific advice on their own life plans, improving the accuracy and adaptability of their life plans.It is also useful as a corporate employee benefits tool, supporting employees' life planning and contributing to improving job satisfaction.

[1518] An example of a prompt is, "Please enter your employee's annual income, family composition, and defined contribution pension information. Next, add detailed asset information such as savings, stock investments, and mortgage balance. We will generate your life plan based on this information."

[1519] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1520] Step 1:

[1521] Collecting basic information

[1522] The server generates an input form for collecting information about the user's annual income, family structure, and defined contribution pension plan, and sends it to the terminal. The input form includes specific fields (annual income, family structure, defined contribution pension plan).

[1523] The terminal displays the input form received from the server on the screen, allowing the user to enter the required information.

[1524] The user enters information about their annual income, family structure, and defined contribution pension plan into this form, and then clicks the submit button to send the information to the server. For example, the user enters information such as an annual income of 6 million yen, being married with one child, and a defined contribution pension plan of 80,000 yen.

[1525] Input: Annual income, family composition, defined contribution pension information

[1526] Output: Basic information sent to the server

[1527] Step 2:

[1528] Obtaining consent and collecting details

[1529] The server stores the collected basic information, and then generates and sends to the terminal a consent confirmation message for obtaining detailed asset information. The confirmation message includes an consent button.

[1530] The terminal displays the consent confirmation message received from the server on the screen.

[1531] The user indicates their consent by clicking the accept button. Once consent is confirmed, the server generates a detailed data entry form (savings, stock investments, mortgage balance, etc.) and sends it to the terminal.

[1532] The terminal displays a detailed data entry form on the screen.

[1533] The user enters detailed information (savings, stock investment, mortgage balance, etc.) and clicks the send button to send it to the server. For example, the user enters information such as savings of 2 million yen, stock investment of 3 million yen, and mortgage balance of 10 million yen.

[1534] Input: Confirm consent, detailed asset information

[1535] Output: Detailed asset information sent to the server

[1536] Step 3:

[1537] Creating a life plan

[1538] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The collected information is input into the generative AI model as a prompt. For example, it generates a prompt such as "annual income of 7 million yen, married, two children, savings of 3 million yen, stock investments of 2 million yen, and mortgage balance of 12 million yen."

[1539] Based on the information provided, the generative AI model calculates future earnings projections and savings goals to generate an optimal life plan.

[1540] Input: Basic information, detailed asset information

[1541] Output: Generated life plan

[1542] Step 4:

[1543] Providing customized advice

[1544] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[1545] The server sends the customized advice to the terminal and notifies the user.

[1546] The terminal displays the advice received from the server on the screen.

[1547] The user can check the advice and send feedback to the server if necessary. For example, advice such as "Save 50,000 yen every month and invest 20% in stocks" is provided.

[1548] Input: Generated life plan

[1549] Output: personalized advice

[1550] Step 5:

[1551] Responding to feedback and regenerating your life plan

[1552] When a user sends feedback on advice or a life plan, the server accepts the feedback.

[1553] Based on the feedback, the server regenerates the life plan using the regeneration means, and again inputs the collected information and the user's feedback as prompts into the generative AI model.

[1554] The server transmits the regenerated life plan to the terminal.

[1555] The terminal displays the updated life plan on the screen and notifies the user.

[1556] Input: User feedback

[1557] Output: Regenerated life plan

[1558] (Application example 1)

[1559] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1560] Conventional life planning systems lack the ability to provide personalized product recommendations based on individual financial situations and to continually update in response to user feedback, making it difficult for users to find the products that best fit their specific needs and future plans.

[1561] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1562] In this invention, the server includes means for collecting employee income information, family composition information, and defined contribution pension information, means for obtaining detailed financial asset information with the employee's consent, means for creating a highly accurate life planning plan using generative artificial intelligence technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life planning plan, means for displaying the advice and life planning plan on the employee's terminal, means for making individualized product suggestions in a virtual store based on the user's financial situation and life planning plan, and means for continually updating product suggestions based on user feedback. This makes it possible to provide product suggestions and services that are optimal for the user's specific needs and future plans.

[1563] "Income information" is information about an employee's annual income or salary.

[1564] "Family composition information" is information about the number of family members in an employee's household and their composition.

[1565] "Defined contribution pension information" is information regarding the amount and type of defined contribution pension to which an employee is enrolled.

[1566] "Detailed financial asset information" refers to information about specific financial assets such as savings, stock investments, and mortgage balances held by employees.

[1567] "Generative AI technology" is an AI technology that enables highly accurate planning and analysis based on various collected data.

[1568] A "life planning plan" is a future living plan that optimizes an employee's income, expenses, and assets.

[1569] "Customized advice" means specific advice tailored to each employee's individual situation based on collected information.

[1570] A "terminal" is a device that allows employees to enter information and view results.

[1571] A "virtual store" is a virtual business location that offers products and services over the Internet.

[1572] "Product proposals" are proposals for products and services recommended based on the user's financial situation and lifestyle planning plans.

[1573] "Feedback" refers to information that reflects user opinions, impressions, and areas for improvement.

[1574] "Updated on a regular basis" means changing information and proposals in a timely manner as needed.

[1575] MODE FOR CARRYING OUT THE INVENTION

[1576] The system for realizing this invention basically consists of a server, a terminal (a device used by the user), and a user. This system collects employee income information, family composition information, and defined contribution pension information, and obtains detailed financial asset information with the employee's consent. Based on this information, generative artificial intelligence technology is used to create a highly accurate life planning plan and provide individually customized advice. In addition, product suggestions are updated as needed based on user feedback, and personalized product suggestions are made in a virtual store.

[1577] Hardware and Software Configuration

[1578] The system is implemented using the following hardware and software:

[1579] Hardware: Smartphone, Head-Mounted Display (HMD), Server

[1580] Software: Python (programming language), Flask (for building web applications), TensorFlow (for generative artificial intelligence models)

[1581] Data processing and calculation

[1582] 1. Basic information collected:

[1583] Users use their smartphones or HMDs to input information about their income, family structure, and defined contribution pension plans, which is then sent to the server.

[1584] 2. Obtaining consent and collecting details:

[1585] The server displays a message on the terminal asking for consent to the collection of detailed financial asset information. If consent is given, the user enters details such as savings, stock investments, and mortgage balances, which are also sent to the server.

[1586] 3. Life planning generation:

[1587] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence model using TensorFlow. For example, it calculates future earnings forecasts and savings goals based on income, expenses, and assets to generate an optimal life planning plan.

[1588] 4. Providing customized advice:

[1589] Based on the generated life planning plan, the server generates individually customized advice and sends it to the user's terminal for display, allowing the user to create an action plan based on it.

[1590] 5. Product suggestions in virtual stores:

[1591] Based on the user's financial situation and life planning, personalized product recommendations are made within the virtual store, allowing users to easily find the products that best fit their future plans.

[1592] 6. Receiving Feedback and Updating:

[1593] The server receives feedback from users and updates product suggestions and advice as needed, ensuring that users always receive optimal suggestions based on the latest information.

[1594] Specific examples

[1595] For example, consider a user who has an annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen. If this user inputs their savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen, generative artificial intelligence technology will be used to generate a lifestyle planning plan and product recommendations that are optimal for that user. Data can be entered using the following prompt sentences:

[1596] Prompt Sentence Examples

[1597] Generate the optimal life plan and product proposals based on the following: annual income of 6 million yen, married family with one child, 80,000 yen in defined contribution pension. Savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[1598] In this way, it becomes possible to propose products and provide services that are optimal for the user's specific needs and future plans.

[1599] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1600] Step 1:

[1601] The user uses a smartphone or head-mounted display (HMD) to enter employee income information, family composition information, and defined contribution pension information into an input form on the terminal, which is then sent to the server.

[1602] Input: Income information, family structure information, defined contribution pension information

[1603] Output: Basic information sent to the server

[1604] Step 2:

[1605] The server displays a message on the terminal confirming consent to the collection of detailed financial asset information. When the user clicks the consent button, a detailed data input form is displayed on the terminal.

[1606] Input: Consent confirmation message

[1607] Output: User consent result, detailed data entry form

[1608] Step 3:

[1609] The user enters detailed information such as savings, stock investments, and mortgage balance into a detailed data input form and sends it to the server, which then receives detailed financial asset information.

[1610] Input: Savings, stock investments, mortgage balance, and other details

[1611] Output: Details sent to the server

[1612] Step 4:

[1613] The server uses the collected basic and detailed information to generate a highly accurate life planning plan using a generative artificial intelligence (AI) model, specifically, TensorFlow to calculate future income projections and savings goals.

[1614] Input: Basic information, detailed information

[1615] Data processing / calculation: Calculation using generative artificial intelligence models

[1616] Output: Highly accurate life planning

[1617] Step 5:

[1618] Based on the generated life planning plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education funding plans.

[1619] Input: Life Planning Plan

[1620] Output: Advice

[1621] Step 6:

[1622] The server sends the generated advice to the terminal and notifies the user, who can then check the advice content through the terminal.

[1623] Input: Advice

[1624] Output: Advice displayed on terminal

[1625] Step 7:

[1626] Based on lifestyle planning and advice, the system will suggest optimal products to users in a virtual store. Product suggestions are optimized for the user's future plans.

[1627] Input: Life planning, advice

[1628] Output: Personalized product recommendations in a virtual store

[1629] Step 8:

[1630] Users send feedback on product suggestions and advice to the server via their terminals, and the server receives this feedback and updates the product suggestions and advice as needed.

[1631] Input: User feedback

[1632] Output: Updated product suggestions and advice

[1633] By the above processing steps, the system of the present invention can provide optimal product proposals and services based on the specific needs and future plans of the user.

[1634] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1635] This invention is a system that collects employees' annual income information, family composition information, and defined contribution pension information, and uses generative AI technology to create highly accurate life plans based on detailed asset information collected with the employee's consent, and provides customized advice based on those life plans. Furthermore, this invention combines an emotion engine that recognizes the user's emotions to generate data based on the user's emotions and reflect them in the life plans and advice. This system consists of a server, a terminal (a device used by the employee), an emotion engine, and a user (employee).

[1636] System program and processing explanation

[1637] Collecting basic information

[1638] The server displays an input form on the terminal to collect information on the employee's annual income, family structure, and defined contribution pension plan. The user uses the terminal to enter the necessary information into this form and clicks the send button, which sends the entered information to the server. As a specific example, an annual income of 6 million yen, married with one child, and a defined contribution pension plan of 80,000 yen are entered.

[1639] Obtaining consent and collecting details

[1640] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The user clicks the consent button to indicate consent, and once the server confirms consent, a detailed data input form is displayed on the terminal. The user enters detailed information such as savings, stock investments, and mortgage balance into this form, and clicks the submit button to send it to the server. For example, savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen are entered.

[1641] Creating a life plan

[1642] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[1643] Providing customized advice

[1644] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and future education fund planning. The server sends this advice to the user's device and notifies them. The user can review it and provide feedback to the server if necessary.

[1645] Use of emotion engine

[1646] The emotion engine recognizes the user's emotions by analyzing the user's voice input, facial expressions, and text input. For example, emotions such as stress or anxiety may be detected from the user's tone of voice and facial expressions while entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[1647] Presenting optimal plans and responding to feedback

[1648] The server transmits to the terminal a life plan and advice created in consideration of the emotional data. For example, if the user is feeling stressed, advice recommending low-risk investments is generated. If the user transmits feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the user.

[1649] For example, if a user inputs a desire to "make low-risk investments" and the server recognizes feelings of anxiety, the server will generate advice recommending low-risk investment plans that promise stable returns. This advice is more convincing because it takes the user's feelings into account.

[1650] This specific process flow allows users to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[1651] The processing flow will be explained below.

[1652] Step 1:

[1653] The server displays a basic information input form on the terminal, which includes fields for inputting annual income information, family structure information, and defined contribution pension information.

[1654] Step 2:

[1655] The user uses the terminal to enter information into a basic information input form. For example, the user enters an annual income of 6 million yen, is married with one child, and has a defined contribution pension of 80,000 yen.

[1656] Step 3:

[1657] The device sends the entered basic information to the server, which stores the received information in a database.

[1658] Step 4:

[1659] The server displays a consent form on the device requesting consent for the collection of detailed information, stating that detailed asset information (savings, stock investments, mortgage balance, etc.) will be collected.

[1660] Step 5:

[1661] The user indicates consent by clicking the consent button in the consent confirmation message using the terminal, and upon consent, the server displays a detailed data entry form on the terminal.

[1662] Step 6:

[1663] The user uses the terminal to enter information into a detailed data entry form, for example, 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance.

[1664] Step 7:

[1665] The device sends the entered details to the server, which stores the received information in a database.

[1666] Step 8:

[1667] The server creates a life plan based on basic and detailed information using a generative AI model, which analyzes the input data and generates a life plan that includes future income projections, expenditure calculations, savings goals, etc.

[1668] Step 9:

[1669] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and education funding plans.

[1670] Step 10:

[1671] The server transmits the generated advice and life plan to the terminal and notifies the user.

[1672] Step 11:

[1673] The server displays a confirmation message on the terminal to analyze the user's emotions using the emotion engine. If consent is obtained, the server starts the emotion engine.

[1674] Step 12:

[1675] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize the user's emotions. For example, if the user is feeling stressed or anxious while typing, it will send that information to the server.

[1676] Step 13:

[1677] The server generates a life plan and advice optimized for the user's mental state based on the emotional data received from the emotion engine. For example, if the emotion engine determines that the user wants to avoid high risks, it generates advice recommending low-risk investments.

[1678] Step 14:

[1679] The server transmits the optimized life plan and advice to the terminal and notifies the user.

[1680] Step 15:

[1681] The user can use the device to view and confirm the advice and life plan, and can provide feedback if necessary.

[1682] Step 16:

[1683] The server receives feedback from the user and makes any necessary modifications using the regeneration means. The modified life plan and advice are then sent back to the terminal and notified to the user.

[1684] Through this process, users receive detailed emotional life plans and customized advice, which improves employee well-being and provides peace of mind.

[1685] Example 2

[1686] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1687] In employee life planning, it is difficult for conventional systems to aggregate asset information and emotional data for each employee and provide highly accurate, customized plans and advice. As a result, it is not possible to create plans that reflect the specific financial situation and emotional state of employees, which has resulted in insufficient improvement in employee satisfaction and psychological security.

[1688] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1689] In this invention, the server includes means for collecting information on employees' income, family structure, and defined contribution pension plans, means for obtaining detailed asset information with the employee's consent, means for creating a highly accurate life plan using AI generation technology based on the collected and obtained information, means for generating and providing individually customized advice based on the life plan, means for displaying the advice and life plan on the employee's information terminal, means for recognizing the user's emotions, and means for modifying the life plan and advice based on the emotion data. This makes it possible to provide highly accurate life plans and customized advice that reflect not only the employee's specific asset information but also their emotion data.

[1690] "Income" refers to the total income, such as salary and bonuses, that an employee receives within a certain period of time.

[1691] "Family composition" refers to information indicating the number and relationships (spouse, children, etc.) of household members in the employee's household.

[1692] A "defined contribution pension" is a pension system in which employees join, and the amount of pension they receive after retirement is determined by the amount of their contributions and the results of their investments.

[1693] "Detailed asset information" refers to information that shows specific and detailed financial status, such as an employee's savings, stock investments, and mortgage balance.

[1694] "Generative AI technology" refers to technology that uses artificial intelligence to perform calculations based on collected data and generate optimal life plans and advice.

[1695] A "life plan" refers to an employee's long-term life plan and a plan for achieving their financial goals.

[1696] "Customized advice" refers to specific advice or suggestions tailored to an individual employee's circumstances.

[1697] "Information terminal" refers to devices such as computers and smartphones used by employees.

[1698] "Means of recognizing emotions" refers to technology that detects an employee's emotional state by analyzing their voice, facial expressions, text input, etc.

[1699] "Emotional Data" means information indicative of an employee's emotional state that is collected and analyzed using emotion recognition measures.

[1700] This invention is a system that collects employee income, family structure, and defined contribution pension information, and obtains detailed asset information with the employee's consent, then uses generative AI technology to generate highly accurate life plans and provide individually customized advice. Furthermore, by incorporating a means to recognize the user's emotions, it is possible to modify the life plans and advice based on emotional data.

[1701] Server and technologies used

[1702] The server is the central hardware that performs collection and processing, and each step utilizes software and technologies such as:

[1703] Collecting income, family structure, and defined contribution pension information: The server generates an HTML form and sends it to the device. The device uses a browser to display the form and sends the information entered by the user to the server.

[1704] Example: A form for entering an annual income of 6 million yen, married, with one child, and a defined contribution pension of 80,000 yen.

[1705] Consent confirmation to obtain detailed asset information: The server generates a consent confirmation message and sends it to the terminal. The terminal displays the consent confirmation message in a dialog format, and the user enters information such as savings, stock investments, and mortgage balance.

[1706] Example: A form for entering savings of 2 million yen, stock investments of 3 million yen, and a mortgage balance of 10 million yen.

[1707] Generating a high-precision life plan using generative AI technology: The server sends prompts to the generative AI model based on the collected basic and detailed information to generate a life plan.

[1708] Example prompt: "Generate a life plan with an income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen."

[1709] Providing customized advice: Based on the generated life plan, the server uses a generative AI model to generate individual advice and notify the device.

[1710] Examples include monthly savings goals, recommended investment percentages, and plans for future education funding.

[1711] Emotion recognition and data reflection: The emotion engine analyzes the user's voice, facial expressions, and text input to detect their emotional state. The server then adjusts the life plan and advice based on the emotional data.

[1712] Example: If a user is feeling stressed, suggest low-risk investments.

[1713] Feedback and life plan regeneration: When the user submits feedback, the server sends prompts based on the feedback to the generative AI model to regenerate the life plan.

[1714] Example: If a user enters "I want to invest with less risk" and anxiety is detected, regenerate a low-risk investment plan.

[1715] In this way, the system aims to improve employee satisfaction and peace of mind by providing highly accurate life plans and customized advice that take into account employees' asset information and emotional data. Companies can use this system as a tool to improve employee welfare.

[1716] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1717] Step 1:

[1718] Collecting basic information

[1719] The server generates a form to collect basic employee information and sends it to the terminal.

[1720] Specific behavior: A form constructed in HTML format is generated, containing input fields for annual income, family composition, and defined contribution pension. This form is sent to the terminal as an HTTP response.

[1721] Input: None (initial step)

[1722] Output: Basic information input form

[1723] The terminal displays the received form to the user.

[1724] What it does: Displays a form in a web browser and waits for user input.

[1725] Input: Form sent from server

[1726] Output: User interface

[1727] The user enters their annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[1728] Specific operation: The user enters their annual income of 6 million yen, is married, has one child, and has a defined contribution pension of 80,000 yen, and presses the send button.

[1729] Input: Annual income, family composition, defined contribution pension information

[1730] Output: Input data

[1731] The terminal transmits the information entered by the user to the server.

[1732] Specific operation: Form data is sent to the server via an HTTP request.

[1733] Input: Basic information entered by the user

[1734] Output: HTTP request (basic information)

[1735] Step 2:

[1736] Obtaining consent and collecting details

[1737] The server generates a consent confirmation message for collecting detailed asset information and sends it to the terminal.

[1738] Specific behavior: Generates a consent confirmation message in HTML dialog format and sends it to the device.

[1739] Input: User basic information

[1740] Output: Consent confirmation message

[1741] The terminal displays a consent confirmation message to the user.

[1742] What it does: Displays a dialog box and waits for user input.

[1743] Input: The consent confirmation message sent by the server

[1744] Output: User interface (agreement confirmation)

[1745] The user clicks the Agree button to open the detailed asset information input form.

[1746] Specific behavior: When you click the consent button, a form to enter detailed information will be displayed.

[1747] Input: Agree

[1748] Output: Detailed information input form

[1749] The user enters information such as savings, stock investments, and mortgage balance, and clicks the submit button.

[1750] Specific actions: Enter 2 million yen in savings, 3 million yen in stock investments, and 10 million yen in mortgage balance, then press the send button.

[1751] Input: Savings, stock investments, mortgage balance, and other details

[1752] Output: Detailed information data

[1753] The terminal sends the details entered by the user to the server.

[1754] Specific behavior: Sends detailed information to the server in the form of an HTTP request.

[1755] Input: User details

[1756] Output: HTTP request (detailed information)

[1757] Step 3:

[1758] Creating a life plan

[1759] The server sends prompts to the generative AI model based on the collected basic and detailed information.

[1760] Specific operation: Generate a prompt such as "Please generate a life plan with income of 6 million yen, expenses of 3 million yen, and savings of 2 million yen" and send it to the generative AI model.

[1761] Input: Basic information, detailed information

[1762] Output: Prompt(Income 6 million yen, Expenses 3 million yen, Savings 2 million yen)

[1763] The generative AI model generates a life plan based on prompts.

[1764] Specific operation: The AI ​​model analyzes the input data and outputs an appropriate life plan and calculation results.

[1765] Input: prompt

[1766] Output: Life Plan

[1767] The server saves the generated life plan and proceeds to the next step.

[1768] Specific behavior: Save the generated life plan in the database.

[1769] Input: Life Plan

[1770] Output: Saved life plan

[1771] Step 4:

[1772] Providing customized advice

[1773] Based on the life plan, the server uses a generative AI model to generate individually customized advice.

[1774] What it does: Generates recommendations including monthly savings goals, recommended investment percentages, and future education funding plans.

[1775] Input: Life Plan

[1776] Output: Advisory data

[1777] The server sends the advice to the terminal and notifies the user.

[1778] Specific operation: The advice content is sent to the device in JSON format and notified to the user via a pop-up notification or other means.

[1779] Input: Advisory data

[1780] Output: Advice given

[1781] The user reviews the advice and sends feedback to the server if desired.

[1782] Specific actions: Check the advice, enter your questions or comments, and then press the send button.

[1783] Input: Feedback

[1784] Output: Feedback sent

[1785] Step 5:

[1786] Emotion recognition and data reflection

[1787] The emotion engine analyzes the user's voice input, facial expressions, and text input to recognize their emotional state.

[1788] Specific operation: Analyzes voice and facial expression data collected using a camera and microphone to identify emotions.

[1789] Input: Voice, facial expressions, text input

[1790] Output: Emotion data

[1791] The server modifies the life plan and advice based on the emotional data.

[1792] What it does: If stress is detected, it will revise its advice to suggest less risky investments.

[1793] Input: Emotion data

[1794] Output: Revised life plan and advice

[1795] Step 6:

[1796] Presenting optimal plans and responding to feedback

[1797] The server transmits a life plan and advice that takes into account the emotional data to the terminal.

[1798] Specific operation: The updated life plan and advice are sent to the device in JSON format and the user is notified via a pop-up notification, etc.

[1799] Input: Revised life plan and advice

[1800] Output: Notified remediation plan and advice

[1801] The user then checks the presented life plan and advice and sends feedback as necessary.

[1802] Specific actions: Review the presented plan, enter your wishes and questions, and press the submit button.

[1803] Input: New feedback

[1804] Output: Feedback sent

[1805] The server receives the feedback and regenerates the life plan and advice.

[1806] What it does: Send prompts based on the new feedback to the AI ​​model to recreate the life plan.

[1807] Input: New feedback

[1808] Output: Regenerated life plan and advice

[1809] (Application example 2)

[1810] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1811] A life plan provision system based on employee annual income, family structure, and defined contribution pension information had the problem of being unable to provide advice that took employees' emotions into consideration. Furthermore, when employees provided feedback on their life plans, it was difficult to recreate an optimal life plan based on their emotions. This resulted in a lack of advice that was truly useful and provided employees with psychological reassurance.

[1812] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1813] In this invention, the server includes a means for collecting information on employees' annual income, family structure, and defined contribution pension plans, a means for obtaining detailed asset information with the employee's consent, and a means for creating a highly accurate life plan using generative AI technology based on the collected and obtained information. This makes it possible to provide highly accurate life plans and individually customized advice that take into account the employee's emotional data.

[1814] "Employee" refers to a person who is employed by a company or organization.

[1815] "Annual income information" refers to information on the total income an employee receives in a year.

[1816] "Family composition information" refers to detailed information such as the number of family members and their relationships with each other.

[1817] "Defined contribution pension information" refers to information regarding the defined contribution pension plan to which an employee is enrolled.

[1818] "Consent" refers to an employee's act of giving permission for the collection and use of information.

[1819] "Detailed asset information" refers to detailed financial information such as an employee's savings, investments, and loans.

[1820] "Generative AI technology" refers to technology that uses artificial intelligence technology to generate highly accurate results.

[1821] A "life plan" is a planned arrangement of future income, assets, and living conditions.

[1822] "Individually tailored advice" refers to specific advice that is developed taking into account the employee's individual information.

[1823] An "emotion engine" refers to technology that recognizes emotions by analyzing a user's voice, facial expressions, text input, etc.

[1824] "Emotion data" refers to data relating to the user's emotions recognized by the emotion engine.

[1825] "Devices" refers to devices such as smartphones and computers used by employees.

[1826] "Feedback" refers to employees' opinions, impressions, and requests for corrections regarding the system.

[1827] "Regeneration means" refers to technology for receiving feedback and regenerating a life plan.

[1828] To implement this invention, it is necessary to build a system that uses a server, terminals, employees, an emotion engine, and a generative AI model. The specific system configuration and processing content are described below.

[1829] Collecting basic information

[1830] The terminal displays an input form for collecting the employee's annual income information, family composition information, and defined contribution pension information. The employee enters the necessary information into the input form and clicks the submit button. The entered information is sent to the server.

[1831] For example, information such as annual income of 6 million yen, being married with one child, and having a defined contribution pension of 80,000 yen is entered.

[1832] Obtaining consent and collecting details

[1833] Next, the server displays a consent confirmation message on the terminal to obtain detailed asset information. The employee clicks the consent button to indicate consent, and once the server has confirmed consent, a detailed data input form is displayed on the terminal. The employee enters detailed information such as savings, stock investments, and mortgage balance into this form and clicks the submit button. For example, information such as savings of 2 million yen, stock investments of 3 million yen, and mortgage balance of 10 million yen may be entered.

[1834] Use of emotion engine

[1835] The emotion engine recognizes employees' emotions by analyzing their voice, facial expressions, and text inputs. For example, emotions such as stress or anxiety may be detected from the employee's tone of voice and facial expressions while they are entering information. This emotional data is sent to the server and reflected in the creation of life plans and advice.

[1836] Creating a life plan

[1837] The server aggregates the collected basic and detailed information and uses a generative AI model to create a highly accurate life plan. The generative AI model calculates future earnings projections and savings goals based on the employee's income, expenses, and asset information, and generates an optimal life plan.

[1838] Example prompt sentence:

[1839] Annual income: 6 million yen

[1840] Family: Married, one child

[1841] Defined contribution pension: 80,000 yen

[1842] Savings: 2 million yen

[1843] Stock investment: 3 million yen

[1844] Mortgage balance: 10 million yen

[1845] Sentiment: I want to invest with less risk

[1846] Providing customized advice

[1847] Based on the generated life plan, the server generates personalized advice, including monthly savings goals, recommended investment percentages, and plans for future education expenses. This advice is sent to the employee's device and notified to the employee. The employee can review it and provide feedback to the server if necessary.

[1848] Presenting optimal plans and responding to feedback

[1849] The server transmits the life plan and advice created by taking the emotional data into consideration to the terminal. For example, if the employee is feeling stressed, advice recommending low-risk investments is generated. If the employee provides feedback on the advice or life plan, the server regenerates the life plan using the regeneration means. The regenerated life plan and advice are again transmitted to the terminal and notified to the employee.

[1850] This specific process allows employees to receive detailed life plans and customized advice, and provides emotionally-conscious planning, giving them peace of mind. Companies can also use this system as a tool to improve employee welfare.

[1851] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1852] Step 1:

[1853] The terminal displays an input form for collecting employee annual income information, family composition information, and defined contribution pension information.

[1854] Input: None

[1855] Specific operation: The user enters annual income, family composition, and defined contribution pension information into the form and clicks the submit button.

[1856] Data processing / calculation: The terminal sends the input information to the server.

[1857] Output: The basic information collected is sent to the server.

[1858] Step 2:

[1859] The server displays a consent confirmation message on the terminal to obtain detailed asset information.

[1860] Input: Basic information (annual income, family composition, defined contribution pension information)

[1861] Specific action: The user clicks the consent button.

[1862] Data processing / calculation: If consent is confirmed, a detailed data entry form will be displayed on the terminal.

[1863] Output: A confirmation that consent has been given and a detailed data entry form will be displayed on the terminal.

[1864] Step 3:

[1865] The device collects detailed asset information (savings, stock investments, mortgage balances, etc.).

[1866] Input: Information entered into the detailed data entry form

[1867] Specific Actions: The user enters detailed asset information and clicks the submit button.

[1868] Data processing / calculation: The terminal sends the entered detailed information to the server.

[1869] Output: The detailed asset information collected is sent to the server.

[1870] Step 4:

[1871] The server uses an emotion engine to analyze the user's voice input, facial expressions, and text input to obtain emotion data.

[1872] Input: Voice input, facial expressions, text input

[1873] Specific operation: The user inputs a preference such as "I want to make an investment with low risk."

[1874] Data processing / calculation: The emotion engine analyzes the input data and generates emotion data.

[1875] Output: The analyzed emotion data is sent to the server.

[1876] Step 5:

[1877] The server uses a generative AI model to create a highly accurate life plan based on the collected basic information, detailed information, and emotional data.

[1878] Input: Basic information, detailed information, emotional data

[1879] Specific operation: The server generates prompt sentences for the generative AI model and creates a life plan based on them.

[1880] Data processing / calculation: The generative AI model calculates future earnings projections and savings goals, generating a highly accurate life plan.

[1881] Output: The generated life plan is obtained.

[1882] Step 6:

[1883] The server generates individually customized advice based on the generated life plan and transmits it to the user terminal.

[1884] Input: Generated life plan

[1885] Specific operation: The server analyzes the life plan and generates appropriate advice.

[1886] Data processing / computation: Generative AI models generate customized advice.

[1887] Output: The generated advice is sent to the user terminal.

[1888] Step 7:

[1889] The terminal receives feedback from the user.

[1890] Input: User feedback

[1891] Specific operation: The user inputs opinions and requests for revisions to the life plan and advice.

[1892] Data processing / calculation: The device sends feedback to the server.

[1893] Output: Feedback is sent to the server.

[1894] Step 8:

[1895] The server receives the feedback and recreates the life plan.

[1896] Input: User feedback, existing life plans, detailed information, emotional data

[1897] Specific operation: The server reuses the generated AI model to create a new life plan.

[1898] Data processing / computation: A generative AI model takes feedback and other information into account to generate a new life plan.

[1899] Output: A regenerated life plan is obtained.

[1900] Step 9:

[1901] The server transmits the regenerated life plan and advice to the user terminal.

[1902] Input: Regenerated life plan

[1903] Specific operation: The server transmits the new life plan and advice to the user terminal.

[1904] Data processing / calculation: The regenerated life plan is displayed on the user's device along with customized advice.

[1905] Output: The new life plan and advice are displayed on the user's terminal.

[1906] This process allows employees to receive detailed life plans and customized advice, and by taking emotions into account, the proposals are more relevant and convincing to the employee.

[1907] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1908] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1909] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1910] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1911] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1912] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1913] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1914] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1915] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1916] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1917] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1918] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1919] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1920] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1921] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1922] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1923] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1924] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1925] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1926] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1927] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1928] The following is further disclosed regarding the above embodiment.

[1929] (Claim 1)

[1930] A means of collecting information on employees' annual income, family structure, and defined contribution pension plans;

[1931] A means of obtaining detailed asset information with employee consent;

[1932] A means for creating a highly accurate life plan using generative AI technology based on the collected and acquired information;

[1933] A means for generating and providing individually customized advice based on the life plan;

[1934] a means for displaying the advice and life plan on an employee's terminal;

[1935] A system including:

[1936] (Claim 2)

[1937] 2. The system according to claim 1, further comprising a feedback receiving means and a life plan regenerating means, and regenerating the life plan in response to a request for modification from the employee.

[1938] (Claim 3)

[1939] 10. The system of claim 1, wherein the generative AI technology generates an optimal plan based on future earnings and savings goals.

[1940] "Example 1"

[1941] (Claim 1)

[1942] A means of collecting information on employees' annual income, family structure, and defined contribution pension plans;

[1943] A means of obtaining detailed asset information with employee consent;

[1944] A means for creating a highly accurate life plan using generative AI technology based on the collected and acquired information;

[1945] A means for generating and providing individually customized advice based on the life plan;

[1946] a means for displaying the advice and life plan on an employee's terminal;

[1947] A means for receiving feedback on the generated life plan and advice;

[1948] A means for regenerating a life plan based on the feedback;

[1949] A system including:

[1950] (Claim 2)

[1951] 2. The system according to claim 1, further comprising a feedback receiving means and a life plan regenerating means, and regenerating the life plan in response to a request for modification from the employee.

[1952] (Claim 3)

[1953] 10. The system of claim 1, wherein the generative AI technology generates an optimal plan based on future earnings and savings goals.

[1954] "Application Example 1"

[1955] (Claim 1)

[1956] A means of collecting employee income information, family structure information, and defined contribution pension information;

[1957] A means of obtaining detailed financial information from employees with their consent;

[1958] A means for creating a highly accurate life planning plan using generative artificial intelligence technology based on the collected and acquired information;

[1959] A means for generating and providing individually customized advice based on the life planning plan;

[1960] means for displaying the advice and life planning plan on an employee's terminal;

[1961] means for providing personalized product recommendations in a virtual store based on the user's financial situation and life planning plan;

[1962] A means to continually update product suggestions based on user feedback,

[1963] A system including:

[1964] (Claim 2)

[1965] 2. The system according to claim 1, further comprising a feedback receiving means and a life planning plan regenerating means, and regenerating the life planning plan in response to a request for modification from the employee.

[1966] (Claim 3)

[1967] 10. The system of claim 1, wherein the generative artificial intelligence technology generates an optimal plan based on future earnings and savings goals.

[1968] "Example 2: Combining Emotion Engines"

[1969] (Claim 1)

[1970] A means of collecting information on employees' income, family structure, and defined contribution pension plans;

[1971] A means of obtaining detailed asset information with employee consent;

[1972] A means for creating a highly accurate life plan using generative AI technology based on the collected and acquired information;

[1973] A means for generating and providing individually customized advice based on the life plan;

[1974] a means for displaying the advice and life plan on an employee's information terminal;

[1975] means for recognizing a user's emotion;

[1976] a means for modifying life plans and advice based on the emotional data;

[1977] A system including:

[1978] (Claim 2)

[1979] 2. The system according to claim 1, further comprising a feedback receiving means and a life plan regenerating means, and regenerating the life plan in response to a request for modification from the employee.

[1980] (Claim 3)

[1981] 10. The system of claim 1, wherein the generative AI technology generates an optimal plan based on future earnings and savings goals.

[1982] "Application example 2 when combining emotion engines"

[1983] (Claim 1)

[1984] A means of collecting information on employees' annual income, family structure, and defined contribution pension plans;

[1985] A means of obtaining detailed asset information with employee consent;

[1986] A means of creating a highly accurate life plan using generative AI technology based on the collected and acquired information;

[1987] A means for generating and providing individually customized advice based on the life plan;

[1988] A means for acquiring emotion data using an emotion engine that recognizes emotions by analyzing a user's voice input, facial expression, and text input;

[1989] A means for taking the acquired emotional data into consideration and reflecting it in life plans and advice;

[1990] a means for displaying the advice and life plan on an employee's terminal;

[1991] A system including:

[1992] (Claim 2)

[1993] 2. The system according to claim 1, further comprising a feedback receiving means and a life plan regenerating means, and regenerating the life plan in response to a request for modification from the employee.

[1994] (Claim 3)

[1995] 10. The system of claim 1, wherein the generative AI technology generates an optimal plan based on future earnings and savings goals. [Explanation of symbols]

[1996] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> <...

Claims

1. A means of collecting information on employees' annual income, family structure, and defined contribution pension plans; A means of obtaining detailed asset information with employee consent; A means for creating a highly accurate life plan using generative AI technology based on the collected and acquired information; A means for generating and providing individually customized advice based on the life plan; a means for displaying the advice and life plan on an employee's terminal; A system including:

2. 2. The system according to claim 1, further comprising a feedback receiving means and a life plan regenerating means, which regenerates the life plan in response to a request for modification from the employee.

3. The system of claim 1 , wherein the generative AI technology generates an optimal plan based on future earnings and savings goals.

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