system

Abstract

We provide the system. [Solution] An information processing device that receives personal information from a user and generates an asset plan based on said personal information, A search device that searches for related financial transaction products based on the aforementioned asset plan and creates a list of suggestions, An information transmission device that provides search results to the user and accepts the provision of additional information or inquiries, A processing unit equipped with an electronic payment function that allows users to purchase selected financial products on the spot, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] There is a need for a system that can lower the psychological hurdle and enable people to obtain information with confidence for those who want to consult about the selection of financial products and asset management but feel resistance to direct dialogue with experts. Also, there is a need for a means to efficiently propose appropriate financial products based on an individual's life plan rather than passive product proposals.

Means for Solving the Problems

[0005] This invention solves this problem by generating an asset plan based on personal data received from the user, effectively searching for financial products that fit that plan, and creating a list of suggestions. Furthermore, it provides the user with search results and communication means that enable responses to additional information and questions, allowing the user to select financial products with confidence. In addition, data verification means are used to confirm the accuracy of the input data from the user in advance, thereby increasing the reliability of the suggestions.

[0006] "Personal data from users" refers to information such as income, savings, family structure, and age that users enter or provide to the system.

[0007] An "information processing unit" is a functional part within a system that receives input data, performs analysis and calculations, and generates specific results.

[0008] An "asset plan" is a plan that outlines policies and strategies for future asset management based on the user's financial situation and life stage.

[0009] A "search method" is a system that searches for and collects data that matches specific criteria from multiple databases and information sources.

[0010] "Financial products" refer to various products offered by financial institutions for asset management and risk management, such as investment trusts, insurance, and stocks.

[0011] "Communication methods" refer to the interfaces and protocols between systems for sending and receiving data, and are technologies that enable information transmission.

[0012] A "data verification mechanism" is a system that evaluates whether the data provided by the user is accurate and makes corrections or adjustments as necessary.

[0013] A "suggestion list" is a list of financial products that are best suited to the user's situation and includes information to support decision-making. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0015] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the 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.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0028] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a system that allows users to smoothly consult about asset management and financial product selection without direct interaction. The system begins with the input of user data, then creates an individualized life plan through an AI agent, and finally proposes the most suitable financial products based on that plan.

[0036] Users access a dedicated application or website using a device such as a smartphone or computer. The device displays a screen prompting the user to enter personal information. Users enter their income, savings, age, family structure, etc., and submit the information.

[0037] The terminal sends user input data to the server. The server stores the received data in a database and verifies its accuracy using data validation tools. After confirming that the data is appropriate, the server activates the AI ​​agent.

[0038] The AI ​​agent performs calculations to create an asset plan based on the user's personal data received. This involves referencing historical market data and the latest financial information. The AI ​​agent then creates an optimal life plan tailored to the user's life stage and future goals.

[0039] Subsequently, the server proposes financial products based on the life plan generated by the AI. The proposals are made by searching for the most suitable products from the databases of partner insurance companies and financial institutions and creating a list of suggestions.

[0040] The device presents the user with a list of suggested search results. The user reviews the list and, if they have further questions, can send a query to the server via the device. The server's AI agent generates answers and additional advice to the questions and responds to the user through the device.

[0041] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen can use this system if they want to find appropriate insurance and asset management methods while considering their family's future plans. Once the user inputs the necessary data, an AI agent will use that information to suggest pension savings plans and insurance products that cover children's education expenses, and will also provide timely feedback on the advantages and disadvantages of each.

[0042] In this way, the present invention provides an environment in which users can effectively and efficiently plan their assets and select appropriate financial products without feeling any psychological resistance.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] Users access a dedicated application or website and open a personal information input screen. Users enter the necessary information, such as income, savings, age, and family structure, and then submit the information.

[0046] Step 2:

[0047] The terminal receives input data from the user and formats it. The formatted data is then prepared as a transmission request to the server.

[0048] Step 3:

[0049] The server receives user data sent from the terminal and stores its contents in a database. Data validation is used to verify the accuracy of the received data and check for errors.

[0050] Step 4:

[0051] The server activates the AI ​​agent after verifying that the data is accurate. The AI ​​agent analyzes the user data and performs calculations to create a life plan.

[0052] Step 5:

[0053] The server searches for the most suitable financial products based on the life plan generated by the AI ​​agent. It retrieves insurance and investment product information from partner databases and compiles them into a list of suggestions.

[0054] Step 6:

[0055] The server sends the generated list of suggestions to the terminal. The terminal then displays this list of suggestions to the user.

[0056] Step 7:

[0057] The user reviews the displayed list of suggestions and, if they have any questions, enter them via their device. The questions are then sent to the server.

[0058] Step 8:

[0059] The server receives the user's question and instructs the AI ​​agent to analyze the question and generate an answer. The generated answer is then sent to the user via the terminal.

[0060] Step 9:

[0061] The terminal displays the AI's response received from the server to the user. The user then uses the provided information to make decisions about the optimal asset management and financial products.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] In recent years, consumers have had to choose from a diverse range of financial products and investment methods, and the process has become increasingly complex. Traditional methods required users to individually gather information and select products suitable for their circumstances, which required considerable time and effort. This often led to inefficient investment planning and caused stress for users. Therefore, there is a need for a method that allows users to easily and efficiently select the products best suited to their needs.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; generation means for performing calculations by referring to past market data and the latest information to create an optimal plan; and search means for searching for related products and creating a list of suggestions based on the plan generated using a generation AI model. This enables users to efficiently receive optimal asset plans and product suggestions based on their own information.

[0067] "Information processing means" refers to a computer system or program for generating plans based on personal data received from users.

[0068] "Generation means" refers to a device that includes algorithms and programs for creating an optimal plan by referring to past market data and the latest information.

[0069] A "generative AI model" refers to artificial intelligence technology used to analyze received data and make optimal suggestions.

[0070] "Search method" refers to a system or program for searching a database for relevant products based on the generated plan and creating a list of suggestions.

[0071] "Communication means" refers to communication devices and programs that use a network to provide users with search results and additional information, and to receive questions and information from users.

[0072] "Data verification means" refers to a program or device that has a verification function to confirm the accuracy and consistency of data entered by the user.

[0073] To implement this invention, a system is required in which a user, a terminal, and a server work in cooperation. The user accesses a dedicated application or website using a terminal such as a smartphone or personal computer. This terminal provides the user with a screen for entering personal data such as income, savings, age, and family structure. The data entered by the user is transmitted to the server via the terminal.

[0074] The server stores the received personal data in a database using information processing tools and applies data verification tools to confirm the accuracy of the data. If the data is deemed valid, the server activates a generation tool and uses historical market data and the latest financial information to create an optimal plan using a generation AI model. Based on this plan, the server searches for relevant products in the product database. This is done using a search tool to generate a suggestion list containing the optimal products.

[0075] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen might use this system to find insurance and investment methods suitable for their family's future planning. In this case, the user inputs the necessary information into the system. The server uses an AI agent to suggest pension savings plans and insurance products that cover education expenses, and also provides feedback on the advantages and disadvantages of each product.

[0076] An example of a prompt might be: "I'm a 30-year-old male with an annual income of 5 million yen and savings of 2 million yen. I would like a proposal for a long-term asset management plan and insurance that can cover education expenses for my family (wife and two children)."

[0077] In this way, the system assists users in efficiently developing optimal asset plans and selecting appropriate products.

[0078] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0079] Step 1:

[0080] Users access a dedicated application or website using their device. Here, users enter personal information such as income, savings, age, and family structure. The input screen performs real-time error checking to ensure accurate and complete data entry, verifying that all required fields are included. This data is then transmitted from the device to the server.

[0081] Step 2:

[0082] The terminal collects input data from the user and sends it to the server. The server receives this data and stores it in a database using information processing tools. Specifically, the server verifies the integrity of the received data and checks the accuracy of each item using data verification tools. For example, if there is inconsistent or missing data, the server generates an error message and sends it to the terminal.

[0083] Step 3:

[0084] After the server determines that the data is correct, it activates a generation process using a generative AI model. Here, the server takes user data as input and calculates an optimal asset plan for the individual, referencing historical market data and the latest financial information. This process utilizes simulation technology to generate multiple scenarios tailored to the user's life stage, ultimately determining the optimal plan as the output.

[0085] Step 4:

[0086] Based on the generated plan, the server searches a database of relevant products. Using the search mechanism, it lists financial and insurance products that match the individual user's needs. As output, a proposal list containing information such as product names, interest rates, and risk assessments is generated and sent to the terminal.

[0087] Step 5:

[0088] The terminal displays a list of suggestions received from the server to the user. The user reviews the suggested products and selects the option that suits them best. The user can also send additional questions to the server via the terminal. The user interface displays information in a visually organized manner to enable comparison of options.

[0089] Step 6:

[0090] The server receives inquiries from users and uses a generative AI model to generate appropriate additional information and advice. In this process, the AI ​​understands the question using prompts, forms an accurate answer as output, and sends it to the terminal. The user can then review this answer and make further decisions.

[0091] (Application Example 1)

[0092] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0093] In modern society, asset management and the selection of financial products are complex and time-consuming processes for users. In particular, there is a need to provide users with a means to effectively and efficiently select the optimal financial products and to purchase them easily. Furthermore, there is a need for a system that can respond to additional user inquiries about the proposed financial products.

[0094] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0095] In this invention, the server includes an information processing device that receives personal information from a user and generates an asset plan; a search device that searches for relevant financial trading products based on the asset plan and creates a list of suggestions; an information transmission device that provides the user with the search results and accepts additional information or inquiries; and a processing device equipped with an electronic payment function that allows the user to purchase the financial trading product selected on the spot. This enables the user to easily select and purchase the optimal financial trading product based on their asset plan, and also allows for a quick response to additional inquiries.

[0096] "Personal information" refers to data necessary for creating an asset plan, such as a user's income, savings, age, and family structure.

[0097] An "asset plan" is an optimal plan created by an AI agent based on the user's personal information to achieve future financial goals.

[0098] An "information processing device" is a device that analyzes personal information received from users and performs calculations to generate asset plans.

[0099] "Financial transaction products" refer to financial products such as insurance, investment trusts, and pension plans intended for asset management.

[0100] A "search device" is a device that searches for the most suitable financial transaction products based on an asset plan and creates a list of suggestions.

[0101] The "Proposal List" is a list of financial products provided to the user that match their asset plan.

[0102] An "information transmission device" is a device that provides search results to the user and has the function of providing additional information or accepting inquiries.

[0103] An "electronic payment function" is a system that provides a means of payment for users to purchase financial products of their choice on the spot.

[0104] The system that implements this application example consists of a terminal such as a smartphone and a server. The user accesses the application through the terminal and enters personal information such as income, savings, and family structure. The terminal sends the entered information to the server.

[0105] The server stores personal information received from users in a dedicated database and verifies its accuracy using data validation methods. This process is handled by an AI agent using Python and TENSORFLOW®, which generates asset plans by referencing historical market data and financial trends. Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions and creates a list of suggestions.

[0106] Users can view a list of suggestions on their terminal and select financial products that interest them. Through an information transmission device, users can send additional questions, and an AI agent will provide appropriate answers and further advice. Furthermore, a processing unit with electronic payment capabilities allows users to purchase their selected financial products on the spot.

[0107] As a concrete example, consider a user who is 35 years old, has an annual income of 6 million yen and savings of 3 million yen, and is seeking advice on funding their child's education. Using this system, an AI agent can create an asset plan based on this information and suggest appropriate educational insurance or investment trusts. The user can immediately review these suggestions and purchase their chosen financial products within the app.

[0108] Examples of prompt statements to input into the generative AI model are as follows:

[0109] "Please propose an ideal investment plan for a 35-year-old user with an annual income of 6 million yen and savings of 3 million yen. A plan that specifically considers children's education expenses is particularly important."

[0110] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0111] Step 1:

[0112] The user accesses the application using their device and enters personal information such as income, savings, age, and family structure. The device then sends the entered information to the server. This input data is organized in JSON format and sent to the server via a communication protocol.

[0113] Step 2:

[0114] The server stores the received personal information in a database. The Django framework in Python is used for this data storage. Once the database write is complete, data validation is performed to verify the integrity of the input data. This checks for outliers and missing values ​​to ensure there are no problems.

[0115] Step 3:

[0116] The server launches an AI agent using Python and TensorFlow to generate an asset plan based on verified personal information. The user's income and age are provided as input data, and the AI ​​model analyzes this data to output an appropriate financial plan through calculations. These calculations refer to historical market data and the latest financial information.

[0117] Step 4:

[0118] Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions. The search is performed using SQL queries, and multiple financial products are returned as search results. This information is organized into a list of suggestions.

[0119] Step 5:

[0120] The terminal displays a list of suggestions received from the server to the user. The user selects products of interest based on this list. Detailed information about the selected financial products is then presented to the user.

[0121] Step 6:

[0122] The user enters and submits an additional question from their device. This question is sent to the server via an information transmission device. The server uses an AI agent to analyze the question and generate appropriate answers and advice. The generated information is then formatted and displayed on the device.

[0123] Step 7:

[0124] When a user proceeds with purchasing a financial product they have selected, the terminal initiates the purchase process via its electronic payment function. The server processes the user's payment information through the payment gateway and completes the transaction. After confirmation that the payment is complete, a purchase completion notification is displayed on the user's terminal.

[0125] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0126] This invention provides a more personalized experience by combining a system that effectively proposes asset plans and related financial products using the user's personal data with an emotion engine that recognizes the user's emotions. The system starts with the input of user data, followed by the creation of a life plan by an AI agent, the proposal of financial products, and the adjustment of proposals based on the analysis of the user's emotions.

[0127] Users use devices such as smartphones or computers to enter the necessary information via a dedicated application or website. Users input their income, savings, age, family structure, etc., into their devices and submit the data. The device then sends this data to the server.

[0128] The server stores the received user data in a database and verifies its accuracy using data validation tools. It then activates an AI agent to generate the user's life plan. Historical market data and the latest financial information are used in this process. Based on the life plan, the server searches the database for multiple products to suggest the most suitable financial instruments and creates a list of recommendations.

[0129] Next, the emotion engine activates and evaluates the user's emotional state by analyzing user input and actions. For example, if the user is hesitant or unsure about a choice, this engine recognizes this and adjusts the suggestions and the order in which information is displayed.

[0130] The device displays customized content to the user based on a list of suggestions provided by the server and analysis results from the sentiment engine. Depending on the user's response, the device can request further information, which is sent to the server. The server uses an AI agent to analyze and generate answers to the user's additional inquiries, and provides the results to the user.

[0131] For example, if a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future, this system will generate a life plan based on the user's data and suggest insurance products suitable for saving for education. If the user expresses anxiety or doubt about the suggestion, the emotion engine will detect this, and the server will restructure the suggestion and provide more reassuring information to support the user's decision-making.

[0132] In this way, the system of the present invention takes into account not only the user's personal needs but also their emotional aspects, realizing a more comprehensive and user-friendly financial service experience.

[0133] The following describes the processing flow.

[0134] Step 1:

[0135] The user accesses a dedicated application or website and opens a screen to enter personal information. The user enters the necessary information such as income, savings, age, and family structure, and then presses the submit button.

[0136] Step 2:

[0137] The terminal receives input data from the user and converts it to the appropriate format. The terminal then creates and sends a request to send the formatted data to the server.

[0138] Step 3:

[0139] The server receives user data sent from the terminal. The server uses data verification means to confirm the accuracy of the received data. After confirming the accuracy of the data, it saves it to the database.

[0140] Step 4:

[0141] The server activates an AI agent, analyzes user data, and generates a life plan. Based on market data and financial information, the AI ​​agent develops the optimal strategy for the user's life plan.

[0142] Step 5:

[0143] The server suggests relevant financial products based on the generated life plan. It retrieves information from partner databases, selects the most suitable products, and creates a list of suggestions.

[0144] Step 6:

[0145] The server uses an emotion engine to analyze the user's emotional state from their input and interactions. Based on this analysis, it adjusts the display order and details of suggested content.

[0146] Step 7:

[0147] The device displays a list of suggestions to the user that reflect the analysis results of the emotion engine. The user reviews the suggestions and enters additional questions or feedback as needed.

[0148] Step 8:

[0149] The device sends the user's question to the server. The server uses an AI agent to analyze the question and generate answers and additional information.

[0150] Step 9:

[0151] The server sends the generated response to the terminal. The terminal presents the received information to the user and continues to provide support to assist the user in making decisions.

[0152] (Example 2)

[0153] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0154] In conventional systems, the emotional aspects of users were not considered when providing plans and proposals based on their personal data, which sometimes caused anxiety and doubt among users. Furthermore, the customization of proposals was insufficient, resulting in users not receiving the optimal service.

[0155] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0156] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; search means for searching for related products based on said plan and creating a list of suggestions; and emotion analysis means for analyzing the user's emotional state and adjusting the content of the suggestions. This makes it possible to provide customized suggestions that take the user's emotions into consideration.

[0157] "Information processing means" refers to devices or software that have the ability to generate plans based on personal data received from users.

[0158] "Search means" refers to devices or software that have the function of searching for relevant products from a database or other source based on the generated plan and creating a list of suggestions.

[0159] "Emotional analysis means" refers to devices or software that analyze user input data and behavior to evaluate the user's emotional state and adjust the suggested content based on that.

[0160] "Communication means" refers to devices and software that provide users with customized search results and suggestions, and that also accept additional information and questions from users.

[0161] This invention is a system that utilizes a user's personal data to effectively suggest products related to their asset plan. Furthermore, by combining this system with an emotion analysis function that recognizes the user's emotions, it provides a more personalized experience.

[0162] First, the user uses a smartphone or computer as their device to access a dedicated application or website and enters personal data such as income, savings, age, and family structure. The user then submits this information to proceed to the next step.

[0163] The terminal sends the data entered by the user to the server. The server stores the received data in a database and verifies the accuracy of the data using data validation methods. The server activates an AI agent to generate the user's asset plan, utilizing a generative AI model in this process. It leverages historical market data and the latest information to construct a plan tailored to the user's situation.

[0164] Furthermore, the server searches the database for relevant products based on the plan and creates a list of optimal product suggestions. Then, it uses sentiment analysis tools to analyze user data and behavior and evaluate the user's emotional state. If it detects user doubts or anxieties, it adjusts the suggestions and provides information to alleviate those anxieties.

[0165] A concrete example of its use is when a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future plans. Based on this data, the system suggests products suitable for saving for education. If the user expresses concerns about the suggestions, sentiment analysis detects this, and the server presents more persuasive information.

[0166] This system utilizes generative AI models to propose optimal plans and products to users, providing comprehensive services that also take into account user emotions.

[0167] An example of a prompt message would be, "Please suggest the optimal life plan and financial products for a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen."

[0168] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0169] Step 1:

[0170] The user activates the device and opens a dedicated application or website. The user enters personal data such as income, savings, age, and family structure into a form and clicks the "Submit" button. The input here is the user's personal information, and the output is a data package prepared for transmission to the device. This data serves as the basic information necessary for subsequent processing.

[0171] Step 2:

[0172] The terminal packages the personal data entered by the user and sends it to the server via a secure network. At this point, the input is a data package, and the output is data formatted in a format that the server can receive. This transmission allows the user data to proceed to central processing.

[0173] Step 3:

[0174] The server processes the received data and stores it in the database. The input here is user data sent from the terminal, and the output is the data in the format stored in the database. Furthermore, data validation measures are used to check the integrity and accuracy of the data, and any inaccurate data is corrected or a warning is generated.

[0175] Step 4:

[0176] The server activates an AI agent and uses a generated AI model to create a user's asset plan. Here, the input is verified user data, and the output is the user's life plan. Specifically, it uses historical market data and the latest financial information to create future asset formation scenarios based on the user's data.

[0177] Step 5:

[0178] The server searches the database for relevant products based on the generated life plan and generates a list of suggestions. The input is the life plan, and the output is a list of financial products tailored to the user's needs. It retrieves product characteristics from the database and analyzes past performance.

[0179] Step 6:

[0180] The server uses sentiment analysis tools to analyze user input and behavior and evaluate their emotional state. Input consists of user behavior logs and responses, while output is an evaluation indicating the emotional situation. This analysis helps understand how the user feels about the proposal.

[0181] Step 7:

[0182] The server adjusts the suggestions based on sentiment analysis, creating optimized information. The input is the emotional state and a list of suggestions, and the output is customized suggestions. This results in information display that provides users with a sense of security.

[0183] Step 8:

[0184] The terminal visualizes and displays customized information received from the server to the user. The input is the server's pre-configured output, and the output is the information displayed on the user's screen. It is important to present this information clearly using list formats or infographics.

[0185] Step 9:

[0186] When a user requests additional information or enters a question, the terminal sends that request to the server. Here, the input is the user's request or question, and the output is the request sent to the server. This feature provides additional support for the user's questions.

[0187] Step 10:

[0188] The server uses an AI agent to analyze additional requests from the user and generate appropriate responses. The input is the user's request, and the output is the answer or additional information. Finally, the results are provided to the user via the terminal.

[0189] (Application Example 2)

[0190] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0191] Traditional financial services often fail to consider the individual emotions of users, resulting in an inability to recommend appropriate financial products. Furthermore, they lack mechanisms to support users' daily purchasing behavior, and specific savings suggestions tailored to users' emotions are insufficient.

[0192] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing means that receives personal data from a user and generates an asset plan based on the personal data; a search means that searches for related financial products based on the asset plan and creates a list of suggestions; an emotion analysis means that analyzes the user's emotions and adjusts the content of the suggestions based on the analysis results; and a purchase support means that provides savings suggestions based on the user's daily emotional state. This makes it possible to provide users with appropriate financial product suggestions that take their emotions into consideration and to support them in managing their daily expenses.

[0193] "Personal data" refers to basic information about a user, such as age, income, and savings, and is used to generate financial plans.

[0194] An "asset plan" is a long-term financial guideline generated based on the user's personal data, tailored to the user's life stage.

[0195] "Information processing means" refers to system components that analyze personal data received from users and generate asset plans.

[0196] A "search tool" is a system component that searches a database for relevant financial products based on the generated asset plan and creates a list of suggestions.

[0197] "Communication methods" refer to system elements that provide users with search results, as well as the role of providing additional information and accepting questions.

[0198] An "emotion analysis tool" is a system component that analyzes the user's emotional state from their input and actions, and adjusts the suggested content based on the results.

[0199] "Purchase support tools" are support functions that provide more appropriate savings suggestions based on the user's daily emotional state.

[0200] The system for implementing this invention uses the user's personal data and emotional data to perform asset management and purchasing support. The user inputs their personal data through a device such as a smartphone or tablet. The device then transmits this data to the server.

[0201] The server generates an asset plan using information processing means based on the received personal data. The asset plan is enhanced by a search means that searches for relevant financial products in the server's database and creates a list of suggestions. The list of suggestions created by the search means is provided to the user via communication means.

[0202] Furthermore, the server uses emotion analysis tools to analyze the user's emotional state based on their input data and behavior. This analysis is used to adjust the suggested content to match the user's emotions. In the user's daily purchasing behavior, the purchasing support tools provide savings suggestions based on the user's emotional state. This allows the user to receive more personalized suggestions that take their emotions into consideration.

[0203] For example, if a user shows signs of anxiety while shopping at a supermarket, an emotion analysis tool can detect that emotion, and the server can use purchasing support tools to suggest a more appropriate shopping list to help them stay within their monthly budget.

[0204] An example of a prompt to input into a generative AI model is: "When a user is feeling anxious, how can you improve the suggestion to make it more reassuring? Consider the results of the emotion engine analysis and explain your approach." By using this prompt, the generative AI model can gain new insights to improve the user experience.

[0205] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0206] Step 1:

[0207] The user inputs various personal data, such as age, income, savings, and family structure, through the terminal. The terminal then sends this data to the server. In this case, input is via keyboard or voice input by the user, and output is the transmission of data to the server.

[0208] Step 2:

[0209] The server processes the received personal data using information processing tools to generate an asset plan. Here, various asset management plans are created based on the personal data, and these are then processed to form a life plan. The output is the generated asset plan.

[0210] Step 3:

[0211] The server uses a search mechanism to retrieve relevant financial products from the database based on the asset plan and creates a list of suggestions. In this step, the asset plan is used as input, the characteristics of the relevant financial products are evaluated, and data calculations are performed to add appropriate products to the list based on that information. The output is the suggestion list.

[0212] Step 4:

[0213] The server uses emotion analysis tools to analyze user behavior and input data, and then analyzes the user's emotional state. Here, user input is used as the input, and data analysis techniques are applied to identify emotions. The output is the analysis result.

[0214] Step 5:

[0215] The server adjusts the suggestion list based on the sentiment analysis results and generates necessary savings suggestions using purchase support methods. The inputs in this step are the sentiment analysis results and the suggestion list, and the output is a customized suggestion list and savings strategies.

[0216] Step 6:

[0217] The terminal displays the final list of suggestions and savings proposals from the server to the user. The user can ask further questions about the suggestions as needed, and these questions are sent back to the server. Input is data from the server, and output is a visual and auditory presentation of information to the user.

[0218] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0219] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0220] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0221] [Second Embodiment]

[0222] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0223] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0224] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0225] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0226] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0227] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0228] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0229] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0230] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0231] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0232] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0233] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0234] This invention provides a system that allows users to smoothly consult about asset management and financial product selection without direct interaction. The system begins with the input of user data, then creates an individualized life plan through an AI agent, and finally proposes the most suitable financial products based on that plan.

[0235] Users access a dedicated application or website using a device such as a smartphone or computer. The device displays a screen prompting the user to enter personal information. Users enter their income, savings, age, family structure, etc., and submit the information.

[0236] The terminal sends user input data to the server. The server stores the received data in a database and verifies its accuracy using data validation tools. After confirming that the data is appropriate, the server activates the AI ​​agent.

[0237] The AI ​​agent performs calculations to create an asset plan based on the user's personal data received. This involves referencing historical market data and the latest financial information. The AI ​​agent then creates an optimal life plan tailored to the user's life stage and future goals.

[0238] Subsequently, the server proposes financial products based on the life plan generated by the AI. The proposals are made by searching for the most suitable products from the databases of partner insurance companies and financial institutions and creating a list of suggestions.

[0239] The device presents the user with a list of suggested search results. The user reviews the list and, if they have further questions, can send a query to the server via the device. The server's AI agent generates answers and additional advice to the questions and responds to the user through the device.

[0240] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen can use this system if they want to find appropriate insurance and asset management methods while considering their family's future plans. Once the user inputs the necessary data, an AI agent will use that information to suggest pension savings plans and insurance products that cover children's education expenses, and will also provide timely feedback on the advantages and disadvantages of each.

[0241] In this way, the present invention provides an environment in which users can effectively and efficiently plan their assets and select appropriate financial products without feeling any psychological resistance.

[0242] The following describes the processing flow.

[0243] Step 1:

[0244] Users access a dedicated application or website and open a personal information input screen. Users enter the necessary information, such as income, savings, age, and family structure, and then submit the information.

[0245] Step 2:

[0246] The terminal receives input data from the user and formats it. The formatted data is then prepared as a transmission request to the server.

[0247] Step 3:

[0248] The server receives user data sent from the terminal and stores its contents in a database. Data validation is used to verify the accuracy of the received data and check for errors.

[0249] Step 4:

[0250] The server activates the AI ​​agent after verifying that the data is accurate. The AI ​​agent analyzes the user data and performs calculations to create a life plan.

[0251] Step 5:

[0252] The server searches for the most suitable financial products based on the life plan generated by the AI ​​agent. It retrieves insurance and investment product information from partner databases and compiles them into a list of suggestions.

[0253] Step 6:

[0254] The server sends the generated list of suggestions to the terminal. The terminal then displays this list of suggestions to the user.

[0255] Step 7:

[0256] The user reviews the displayed list of suggestions and, if they have any questions, enter them via their device. The questions are then sent to the server.

[0257] Step 8:

[0258] The server receives the user's question and instructs the AI ​​agent to analyze the question and generate an answer. The generated answer is then sent to the user via the terminal.

[0259] Step 9:

[0260] The terminal displays the AI's response received from the server to the user. The user then uses the provided information to make decisions about the optimal asset management and financial products.

[0261] (Example 1)

[0262] Next, we will describe Example 1. 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."

[0263] In recent years, consumers have had to choose from a diverse range of financial products and investment methods, and the process has become increasingly complex. Traditional methods required users to individually gather information and select products suitable for their circumstances, which required considerable time and effort. This often led to inefficient investment planning and caused stress for users. Therefore, there is a need for a method that allows users to easily and efficiently select the products best suited to their needs.

[0264] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0265] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; generation means for performing calculations by referring to past market data and the latest information to create an optimal plan; and search means for searching for related products and creating a list of suggestions based on the plan generated using a generation AI model. This enables users to efficiently receive optimal asset plans and product suggestions based on their own information.

[0266] "Information processing means" refers to a computer system or program for generating plans based on personal data received from users.

[0267] "Generation means" refers to a device that includes algorithms and programs for creating an optimal plan by referring to past market data and the latest information.

[0268] A "generative AI model" refers to artificial intelligence technology used to analyze received data and make optimal suggestions.

[0269] "Search method" refers to a system or program for searching a database for relevant products based on the generated plan and creating a list of suggestions.

[0270] "Communication means" refers to communication devices and programs that use a network to provide users with search results and additional information, and to receive questions and information from users.

[0271] "Data verification means" refers to a program or device that has a verification function to confirm the accuracy and consistency of data entered by the user.

[0272] To implement this invention, a system is required in which a user, a terminal, and a server work in cooperation. The user accesses a dedicated application or website using a terminal such as a smartphone or personal computer. This terminal provides the user with a screen for entering personal data such as income, savings, age, and family structure. The data entered by the user is transmitted to the server via the terminal.

[0273] The server stores the received personal data in a database using information processing tools and applies data verification tools to confirm the accuracy of the data. If the data is deemed valid, the server activates a generation tool and uses historical market data and the latest financial information to create an optimal plan using a generation AI model. Based on this plan, the server searches for relevant products in the product database. This is done using a search tool to generate a suggestion list containing the optimal products.

[0274] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen might use this system to find insurance and investment methods suitable for their family's future planning. In this case, the user inputs the necessary information into the system. The server uses an AI agent to suggest pension savings plans and insurance products that cover education expenses, and also provides feedback on the advantages and disadvantages of each product.

[0275] An example of a prompt might be: "I'm a 30-year-old male with an annual income of 5 million yen and savings of 2 million yen. I would like a proposal for a long-term asset management plan and insurance that can cover education expenses for my family (wife and two children)."

[0276] In this way, the system assists users in efficiently developing optimal asset plans and selecting appropriate products.

[0277] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0278] Step 1:

[0279] The user accesses a dedicated application or website using a terminal. Here, the user inputs personal information such as income, savings, age, family composition, etc. On the input screen, error checking is performed in real time to ensure that the data is accurately and completely entered, and to check that no mandatory items are missing. This data is sent from the terminal to the server as input.

[0280] Step 2:

[0281] The terminal aggregates the input data from the user and sends it to the server. The server receives this data and stores it in the database by means of information processing. Specifically, the server checks the integrity of the received data and uses data verification means to check the accuracy of each item. For example, if there is inconsistent or missing data, the server generates an error message and sends it to the terminal.

[0282] Step 3:

[0283] After determining that the data is correct, the server activates the generation means using the generated AI model. Here, the server uses the user data as input and calculates the optimal asset plan for the individual while referring to past market data and the latest financial information. In this process, simulation technology is utilized to generate multiple scenarios according to the user's life stage, and the optimal plan is determined as the output.

[0284] Step 4:

[0285] Based on the generated plan, the server searches the database of relevant products. Using the search means, financial products and insurance products that match the individual user needs are listed. As the output, a proposal list containing information such as product name, interest rate, risk assessment, etc. is generated and sent to the terminal.

[0286] Step 5:

[0287] The terminal displays a list of suggestions received from the server to the user. The user reviews the suggested products and selects the option that suits them best. The user can also send additional questions to the server via the terminal. The user interface displays information in a visually organized manner to enable comparison of options.

[0288] Step 6:

[0289] The server receives inquiries from users and uses a generative AI model to generate appropriate additional information and advice. In this process, the AI ​​understands the question using prompts, forms an accurate answer as output, and sends it to the terminal. The user can then review this answer and make further decisions.

[0290] (Application Example 1)

[0291] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0292] In modern society, asset management and the selection of financial products are complex and time-consuming processes for users. In particular, there is a need to provide users with a means to effectively and efficiently select the optimal financial products and to purchase them easily. Furthermore, there is a need for a system that can respond to additional user inquiries about the proposed financial products.

[0293] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0294] In this invention, the server includes an information processing device that receives personal information from a user and generates an asset plan; a search device that searches for relevant financial trading products based on the asset plan and creates a list of suggestions; an information transmission device that provides the user with the search results and accepts additional information or inquiries; and a processing device equipped with an electronic payment function that allows the user to purchase the financial trading product selected on the spot. This enables the user to easily select and purchase the optimal financial trading product based on their asset plan, and also allows for a quick response to additional inquiries.

[0295] "Personal information" refers to data necessary for creating an asset plan, such as a user's income, savings, age, and family structure.

[0296] An "asset plan" is an optimal plan created by an AI agent based on the user's personal information to achieve future financial goals.

[0297] An "information processing device" is a device that analyzes personal information received from users and performs calculations to generate asset plans.

[0298] "Financial transaction products" refer to financial products such as insurance, investment trusts, and pension plans intended for asset management.

[0299] A "search device" is a device that searches for the most suitable financial transaction products based on an asset plan and creates a list of suggestions.

[0300] The "Proposal List" is a list of financial products provided to the user that match their asset plan.

[0301] An "information transmission device" is a device that provides search results to the user and has the function of providing additional information or accepting inquiries.

[0302] An "electronic payment function" is a system that provides a means of payment for users to purchase financial products of their choice on the spot.

[0303] The system that realizes this application example is configured by using a terminal such as a smartphone and a server. The user accesses the application through the terminal and inputs personal information such as income, savings, and family composition. The terminal transmits the input information to the server.

[0304] The server stores the personal information received from the user in a dedicated database and verifies its accuracy using data verification means. In this process, an AI agent using Python and TensorFlow is in charge and generates an asset plan by referring to past market data and financial trends. Based on the generated asset plan, the server searches for the optimal financial trading products from the database of partner financial institutions and creates a list of proposals.

[0305] The user can check the list of proposals on the terminal and select the financial trading products they are interested in. Through the information transmission device, the user can send additional questions, and the AI agent will return appropriate answers and further advice. Also, with a processing device equipped with an electronic payment function, the user can purchase the selected financial trading products immediately.

[0306] As a specific example, consider the case where the user has a situation of "annual income of 6 million yen and savings of 3 million yen" and is seeking advice on educational funds for their children at the age of 35. By using this system, the AI agent can create an asset plan based on this information and propose appropriate educational insurance and investment trusts. The user can immediately check these proposals and purchase the selected financial trading products within the application.

[0307] An example of the prompt text input to the generation AI model is as follows.

[0308] "Please propose a recommended asset management plan for the case where the user has an annual income of 6 million yen, savings of 3 million yen, and is 35 years old. A plan considering especially educational funds for children is required."

[0309] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0310] Step 1:

[0311] The user accesses the application using their device and enters personal information such as income, savings, age, and family structure. The device then sends the entered information to the server. This input data is organized in JSON format and sent to the server via a communication protocol.

[0312] Step 2:

[0313] The server stores the received personal information in a database. The Django framework in Python is used for this data storage. Once the database write is complete, data validation is performed to verify the integrity of the input data. This checks for outliers and missing values ​​to ensure there are no problems.

[0314] Step 3:

[0315] The server launches an AI agent using Python and TensorFlow to generate an asset plan based on verified personal information. The user's income and age are provided as input data, and the AI ​​model analyzes this data to output an appropriate financial plan through calculations. These calculations refer to historical market data and the latest financial information.

[0316] Step 4:

[0317] Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions. The search is performed using SQL queries, and multiple financial products are returned as search results. This information is organized into a list of suggestions.

[0318] Step 5:

[0319] The terminal displays a list of suggestions received from the server to the user. The user selects products of interest based on this list. Detailed information about the selected financial products is then presented to the user.

[0320] Step 6:

[0321] The user enters and submits an additional question from their device. This question is sent to the server via an information transmission device. The server uses an AI agent to analyze the question and generate appropriate answers and advice. The generated information is then formatted and displayed on the device.

[0322] Step 7:

[0323] When a user proceeds with purchasing a financial product they have selected, the terminal initiates the purchase process via its electronic payment function. The server processes the user's payment information through the payment gateway and completes the transaction. After confirmation that the payment is complete, a purchase completion notification is displayed on the user's terminal.

[0324] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0325] This invention provides a more personalized experience by combining a system that effectively proposes asset plans and related financial products using the user's personal data with an emotion engine that recognizes the user's emotions. The system starts with the input of user data, followed by the creation of a life plan by an AI agent, the proposal of financial products, and the adjustment of proposals based on the analysis of the user's emotions.

[0326] Users use devices such as smartphones or computers to enter the necessary information via a dedicated application or website. Users input their income, savings, age, family structure, etc., into their devices and submit the data. The device then sends this data to the server.

[0327] The server stores the received user data in a database and verifies its accuracy using data validation tools. It then activates an AI agent to generate the user's life plan. Historical market data and the latest financial information are used in this process. Based on the life plan, the server searches the database for multiple products to suggest the most suitable financial instruments and creates a list of recommendations.

[0328] Next, the emotion engine activates and evaluates the user's emotional state by analyzing user input and actions. For example, if the user is hesitant or unsure about a choice, this engine recognizes this and adjusts the suggestions and the order in which information is displayed.

[0329] The device displays customized content to the user based on a list of suggestions provided by the server and analysis results from the sentiment engine. Depending on the user's response, the device can request further information, which is sent to the server. The server uses an AI agent to analyze and generate answers to the user's additional inquiries, and provides the results to the user.

[0330] For example, if a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future, this system will generate a life plan based on the user's data and suggest insurance products suitable for saving for education. If the user expresses anxiety or doubt about the suggestion, the emotion engine will detect this, and the server will restructure the suggestion and provide more reassuring information to support the user's decision-making.

[0331] In this way, the system of the present invention takes into account not only the user's personal needs but also their emotional aspects, realizing a more comprehensive and user-friendly financial service experience.

[0332] The following describes the processing flow.

[0333] Step 1:

[0334] The user accesses a dedicated application or website and opens a screen to enter personal information. The user enters the necessary information such as income, savings, age, and family structure, and then presses the submit button.

[0335] Step 2:

[0336] The terminal receives input data from the user and converts it to the appropriate format. The terminal then creates and sends a request to send the formatted data to the server.

[0337] Step 3:

[0338] The server receives user data sent from the terminal. The server uses data verification means to confirm the accuracy of the received data. After confirming the accuracy of the data, it saves it to the database.

[0339] Step 4:

[0340] The server activates an AI agent, analyzes user data, and generates a life plan. Based on market data and financial information, the AI ​​agent develops the optimal strategy for the user's life plan.

[0341] Step 5:

[0342] The server suggests relevant financial products based on the generated life plan. It retrieves information from partner databases, selects the most suitable products, and creates a list of suggestions.

[0343] Step 6:

[0344] The server uses an emotion engine to analyze the user's emotional state from their input and interactions. Based on this analysis, it adjusts the display order and details of suggested content.

[0345] Step 7:

[0346] The device displays a list of suggestions to the user that reflect the analysis results of the emotion engine. The user reviews the suggestions and enters additional questions or feedback as needed.

[0347] Step 8:

[0348] The device sends the user's question to the server. The server uses an AI agent to analyze the question and generate answers and additional information.

[0349] Step 9:

[0350] The server sends the generated response to the terminal. The terminal presents the received information to the user and continues to provide support to assist the user in making decisions.

[0351] (Example 2)

[0352] Next, we will describe Example 2. 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".

[0353] In conventional systems, the emotional aspects of users were not considered when providing plans and proposals based on their personal data, which sometimes caused anxiety and doubt among users. Furthermore, the customization of proposals was insufficient, resulting in users not receiving the optimal service.

[0354] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0355] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; search means for searching for related products based on said plan and creating a list of suggestions; and emotion analysis means for analyzing the user's emotional state and adjusting the content of the suggestions. This makes it possible to provide customized suggestions that take the user's emotions into consideration.

[0356] "Information processing means" refers to devices or software that have the ability to generate plans based on personal data received from users.

[0357] "Search means" refers to devices or software that have the function of searching for relevant products from a database or other source based on the generated plan and creating a list of suggestions.

[0358] "Emotional analysis means" refers to devices or software that analyze user input data and behavior to evaluate the user's emotional state and adjust the suggested content based on that.

[0359] "Communication means" refers to devices and software that provide users with customized search results and suggestions, and that also accept additional information and questions from users.

[0360] This invention is a system that utilizes a user's personal data to effectively suggest products related to their asset plan. Furthermore, by combining this system with an emotion analysis function that recognizes the user's emotions, it provides a more personalized experience.

[0361] First, the user uses a smartphone or computer as their device to access a dedicated application or website and enters personal data such as income, savings, age, and family structure. The user then submits this information to proceed to the next step.

[0362] The terminal sends the data entered by the user to the server. The server stores the received data in a database and verifies the accuracy of the data using data validation methods. The server activates an AI agent to generate the user's asset plan, utilizing a generative AI model in this process. It leverages historical market data and the latest information to construct a plan tailored to the user's situation.

[0363] Furthermore, the server searches the database for relevant products based on the plan and creates a list of optimal product suggestions. Then, it uses sentiment analysis tools to analyze user data and behavior and evaluate the user's emotional state. If it detects user doubts or anxieties, it adjusts the suggestions and provides information to alleviate those anxieties.

[0364] A concrete example of its use is when a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future plans. Based on this data, the system suggests products suitable for saving for education. If the user expresses concerns about the suggestions, sentiment analysis detects this, and the server presents more persuasive information.

[0365] This system utilizes generative AI models to propose optimal plans and products to users, providing comprehensive services that also take into account user emotions.

[0366] An example of a prompt message would be, "Please suggest the optimal life plan and financial products for a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen."

[0367] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0368] Step 1:

[0369] The user activates the device and opens a dedicated application or website. The user enters personal data such as income, savings, age, and family structure into a form and clicks the "Submit" button. The input here is the user's personal information, and the output is a data package prepared for transmission to the device. This data serves as the basic information necessary for subsequent processing.

[0370] Step 2:

[0371] The terminal packages the personal data entered by the user and sends it to the server via a secure network. At this point, the input is a data package, and the output is data formatted in a format that the server can receive. This transmission allows the user data to proceed to central processing.

[0372] Step 3:

[0373] The server processes the received data and stores it in the database. The input here is user data sent from the terminal, and the output is the data in the format stored in the database. Furthermore, data validation measures are used to check the integrity and accuracy of the data, and any inaccurate data is corrected or a warning is generated.

[0374] Step 4:

[0375] The server activates an AI agent and uses a generated AI model to create a user's asset plan. Here, the input is verified user data, and the output is the user's life plan. Specifically, it uses historical market data and the latest financial information to create future asset formation scenarios based on the user's data.

[0376] Step 5:

[0377] The server searches the database for relevant products based on the generated life plan and generates a list of suggestions. The input is the life plan, and the output is a list of financial products tailored to the user's needs. It retrieves product characteristics from the database and analyzes past performance.

[0378] Step 6:

[0379] The server uses sentiment analysis tools to analyze user input and behavior and evaluate their emotional state. Input consists of user behavior logs and responses, while output is an evaluation indicating the emotional situation. This analysis helps understand how the user feels about the proposal.

[0380] Step 7:

[0381] The server adjusts the suggestions based on sentiment analysis, creating optimized information. The input is the emotional state and a list of suggestions, and the output is customized suggestions. This results in information display that provides users with a sense of security.

[0382] Step 8:

[0383] The terminal visualizes and displays customized information received from the server to the user. The input is the server's pre-configured output, and the output is the information displayed on the user's screen. It is important to present this information clearly using list formats or infographics.

[0384] Step 9:

[0385] When a user requests additional information or enters a question, the terminal sends that request to the server. Here, the input is the user's request or question, and the output is the request sent to the server. This feature provides additional support for the user's questions.

[0386] Step 10:

[0387] The server uses an AI agent to analyze additional requests from the user and generate appropriate responses. The input is the user's request, and the output is the answer or additional information. Finally, the results are provided to the user via the terminal.

[0388] (Application Example 2)

[0389] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0390] Traditional financial services often fail to consider the individual emotions of users, resulting in an inability to recommend appropriate financial products. Furthermore, they lack mechanisms to support users' daily purchasing behavior, and specific savings suggestions tailored to users' emotions are insufficient.

[0391] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing means that receives personal data from a user and generates an asset plan based on the personal data; a search means that searches for related financial products based on the asset plan and creates a list of suggestions; an emotion analysis means that analyzes the user's emotions and adjusts the content of the suggestions based on the analysis results; and a purchase support means that provides savings suggestions based on the user's daily emotional state. This makes it possible to provide users with appropriate financial product suggestions that take their emotions into consideration and to support them in managing their daily expenses.

[0392] "Personal data" refers to basic information about a user, such as age, income, and savings, and is used to generate financial plans.

[0393] An "asset plan" is a long-term financial guideline generated based on the user's personal data, tailored to the user's life stage.

[0394] "Information processing means" refers to system components that analyze personal data received from users and generate asset plans.

[0395] A "search tool" is a system component that searches a database for relevant financial products based on the generated asset plan and creates a list of suggestions.

[0396] "Communication methods" refer to system elements that provide users with search results, as well as the role of providing additional information and accepting questions.

[0397] An "emotion analysis tool" is a system component that analyzes the user's emotional state from their input and actions, and adjusts the suggested content based on the results.

[0398] "Purchase support tools" are support functions that provide more appropriate savings suggestions based on the user's daily emotional state.

[0399] The system for implementing this invention uses the user's personal data and emotional data to perform asset management and purchasing support. The user inputs their personal data through a device such as a smartphone or tablet. The device then transmits this data to the server.

[0400] The server generates an asset plan using information processing means based on the received personal data. The asset plan is enhanced by a search means that searches for relevant financial products in the server's database and creates a list of suggestions. The list of suggestions created by the search means is provided to the user via communication means.

[0401] Furthermore, the server uses emotion analysis tools to analyze the user's emotional state based on their input data and behavior. This analysis is used to adjust the suggested content to match the user's emotions. In the user's daily purchasing behavior, the purchasing support tools provide savings suggestions based on the user's emotional state. This allows the user to receive more personalized suggestions that take their emotions into consideration.

[0402] For example, if a user shows signs of anxiety while shopping at a supermarket, an emotion analysis tool can detect that emotion, and the server can use purchasing support tools to suggest a more appropriate shopping list to help them stay within their monthly budget.

[0403] An example of a prompt to input into a generative AI model is: "When a user is feeling anxious, how can you improve the suggestion to make it more reassuring? Consider the results of the emotion engine analysis and explain your approach." By using this prompt, the generative AI model can gain new insights to improve the user experience.

[0404] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0405] Step 1:

[0406] The user inputs various personal data, such as age, income, savings, and family structure, through the terminal. The terminal then sends this data to the server. In this case, input is via keyboard or voice input by the user, and output is the transmission of data to the server.

[0407] Step 2:

[0408] The server processes the received personal data using information processing tools to generate an asset plan. Here, various asset management plans are created based on the personal data, and these are then processed to form a life plan. The output is the generated asset plan.

[0409] Step 3:

[0410] The server uses a search mechanism to retrieve relevant financial products from the database based on the asset plan and creates a list of suggestions. In this step, the asset plan is used as input, the characteristics of the relevant financial products are evaluated, and data calculations are performed to add appropriate products to the list based on that information. The output is the suggestion list.

[0411] Step 4:

[0412] The server uses emotion analysis tools to analyze user behavior and input data, and then analyzes the user's emotional state. Here, user input is used as the input, and data analysis techniques are applied to identify emotions. The output is the analysis result.

[0413] Step 5:

[0414] The server adjusts the suggestion list based on the sentiment analysis results and generates necessary savings suggestions using purchase support methods. The inputs in this step are the sentiment analysis results and the suggestion list, and the output is a customized suggestion list and savings strategies.

[0415] Step 6:

[0416] The terminal displays the final list of suggestions and savings proposals from the server to the user. The user can ask further questions about the suggestions as needed, and these questions are sent back to the server. Input is data from the server, and output is a visual and auditory presentation of information to the user.

[0417] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0418] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0419] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0420] [Third Embodiment]

[0421] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0422] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0423] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0424] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0425] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0426] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0427] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0428] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0429] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0430] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0431] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0432] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0433] This invention provides a system that allows users to smoothly consult about asset management and financial product selection without direct interaction. The system begins with the input of user data, then creates an individualized life plan through an AI agent, and finally proposes the most suitable financial products based on that plan.

[0434] Users access a dedicated application or website using a device such as a smartphone or computer. The device displays a screen prompting the user to enter personal information. Users enter their income, savings, age, family structure, etc., and submit the information.

[0435] The terminal sends user input data to the server. The server stores the received data in a database and verifies its accuracy using data validation tools. After confirming that the data is appropriate, the server activates the AI ​​agent.

[0436] The AI ​​agent performs calculations to create an asset plan based on the user's personal data received. This involves referencing historical market data and the latest financial information. The AI ​​agent then creates an optimal life plan tailored to the user's life stage and future goals.

[0437] Subsequently, the server proposes financial products based on the life plan generated by the AI. The proposals are made by searching for the most suitable products from the databases of partner insurance companies and financial institutions and creating a list of suggestions.

[0438] The device presents the user with a list of suggested search results. The user reviews the list and, if they have further questions, can send a query to the server via the device. The server's AI agent generates answers and additional advice to the questions and responds to the user through the device.

[0439] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen can use this system if they want to find appropriate insurance and asset management methods while considering their family's future plans. Once the user inputs the necessary data, an AI agent will use that information to suggest pension savings plans and insurance products that cover children's education expenses, and will also provide timely feedback on the advantages and disadvantages of each.

[0440] In this way, the present invention provides an environment in which users can effectively and efficiently plan their assets and select appropriate financial products without feeling any psychological resistance.

[0441] The following describes the processing flow.

[0442] Step 1:

[0443] Users access a dedicated application or website and open a personal information input screen. Users enter the necessary information, such as income, savings, age, and family structure, and then submit the information.

[0444] Step 2:

[0445] The terminal receives input data from the user and formats it. The formatted data is then prepared as a transmission request to the server.

[0446] Step 3:

[0447] The server receives user data sent from the terminal and stores its contents in a database. Data validation is used to verify the accuracy of the received data and check for errors.

[0448] Step 4:

[0449] The server activates the AI ​​agent after verifying that the data is accurate. The AI ​​agent analyzes the user data and performs calculations to create a life plan.

[0450] Step 5:

[0451] The server searches for the most suitable financial products based on the life plan generated by the AI ​​agent. It retrieves insurance and investment product information from partner databases and compiles them into a list of suggestions.

[0452] Step 6:

[0453] The server sends the generated list of suggestions to the terminal. The terminal then displays this list of suggestions to the user.

[0454] Step 7:

[0455] The user reviews the displayed list of suggestions and, if they have any questions, enter them via their device. The questions are then sent to the server.

[0456] Step 8:

[0457] The server receives the user's question and instructs the AI ​​agent to analyze the question and generate an answer. The generated answer is then sent to the user via the terminal.

[0458] Step 9:

[0459] The terminal displays the AI's response received from the server to the user. The user then uses the provided information to make decisions about the optimal asset management and financial products.

[0460] (Example 1)

[0461] Next, we will describe Example 1. 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."

[0462] In recent years, consumers have had to choose from a diverse range of financial products and investment methods, and the process has become increasingly complex. Traditional methods required users to individually gather information and select products suitable for their circumstances, which required considerable time and effort. This often led to inefficient investment planning and caused stress for users. Therefore, there is a need for a method that allows users to easily and efficiently select the products best suited to their needs.

[0463] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0464] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; generation means for performing calculations by referring to past market data and the latest information to create an optimal plan; and search means for searching for related products and creating a list of suggestions based on the plan generated using a generation AI model. This enables users to efficiently receive optimal asset plans and product suggestions based on their own information.

[0465] "Information processing means" refers to a computer system or program for generating plans based on personal data received from users.

[0466] "Generation means" refers to a device that includes algorithms and programs for creating an optimal plan by referring to past market data and the latest information.

[0467] A "generative AI model" refers to artificial intelligence technology used to analyze received data and make optimal suggestions.

[0468] "Search method" refers to a system or program for searching a database for relevant products based on the generated plan and creating a list of suggestions.

[0469] "Communication means" refers to communication devices and programs that use a network to provide users with search results and additional information, and to receive questions and information from users.

[0470] "Data verification means" refers to a program or device that has a verification function to confirm the accuracy and consistency of data entered by the user.

[0471] To implement this invention, a system is required in which a user, a terminal, and a server work in cooperation. The user accesses a dedicated application or website using a terminal such as a smartphone or personal computer. This terminal provides the user with a screen for entering personal data such as income, savings, age, and family structure. The data entered by the user is transmitted to the server via the terminal.

[0472] The server stores the received personal data in a database using information processing tools and applies data verification tools to confirm the accuracy of the data. If the data is deemed valid, the server activates a generation tool and uses historical market data and the latest financial information to create an optimal plan using a generation AI model. Based on this plan, the server searches for relevant products in the product database. This is done using a search tool to generate a suggestion list containing the optimal products.

[0473] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen might use this system to find insurance and investment methods suitable for their family's future planning. In this case, the user inputs the necessary information into the system. The server uses an AI agent to suggest pension savings plans and insurance products that cover education expenses, and also provides feedback on the advantages and disadvantages of each product.

[0474] An example of a prompt might be: "I'm a 30-year-old male with an annual income of 5 million yen and savings of 2 million yen. I would like a proposal for a long-term asset management plan and insurance that can cover education expenses for my family (wife and two children)."

[0475] In this way, the system assists users in efficiently developing optimal asset plans and selecting appropriate products.

[0476] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0477] Step 1:

[0478] Users access a dedicated application or website using their device. Here, users enter personal information such as income, savings, age, and family structure. The input screen performs real-time error checking to ensure accurate and complete data entry, verifying that all required fields are included. This data is then transmitted from the device to the server.

[0479] Step 2:

[0480] The terminal collects input data from the user and sends it to the server. The server receives this data and stores it in a database using information processing tools. Specifically, the server verifies the integrity of the received data and checks the accuracy of each item using data verification tools. For example, if there is inconsistent or missing data, the server generates an error message and sends it to the terminal.

[0481] Step 3:

[0482] After the server determines that the data is correct, it activates a generation process using a generative AI model. Here, the server takes user data as input and calculates an optimal asset plan for the individual, referencing historical market data and the latest financial information. This process utilizes simulation technology to generate multiple scenarios tailored to the user's life stage, ultimately determining the optimal plan as the output.

[0483] Step 4:

[0484] Based on the generated plan, the server searches a database of relevant products. Using the search mechanism, it lists financial and insurance products that match the individual user's needs. As output, a proposal list containing information such as product names, interest rates, and risk assessments is generated and sent to the terminal.

[0485] Step 5:

[0486] The terminal displays a list of suggestions received from the server to the user. The user reviews the suggested products and selects the option that suits them best. The user can also send additional questions to the server via the terminal. The user interface displays information in a visually organized manner to enable comparison of options.

[0487] Step 6:

[0488] The server receives inquiries from users and uses a generative AI model to generate appropriate additional information and advice. In this process, the AI ​​understands the question using prompts, forms an accurate answer as output, and sends it to the terminal. The user can then review this answer and make further decisions.

[0489] (Application Example 1)

[0490] Next, we will explain Application Example 1. In the following explanation, 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."

[0491] In modern society, asset management and the selection of financial products are complex and time-consuming processes for users. In particular, there is a need to provide users with a means to effectively and efficiently select the optimal financial products and to purchase them easily. Furthermore, there is a need for a system that can respond to additional user inquiries about the proposed financial products.

[0492] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0493] In this invention, the server includes an information processing device that receives personal information from a user and generates an asset plan; a search device that searches for relevant financial trading products based on the asset plan and creates a list of suggestions; an information transmission device that provides the user with the search results and accepts additional information or inquiries; and a processing device equipped with an electronic payment function that allows the user to purchase the financial trading product selected on the spot. This enables the user to easily select and purchase the optimal financial trading product based on their asset plan, and also allows for a quick response to additional inquiries.

[0494] "Personal information" refers to data necessary for creating an asset plan, such as a user's income, savings, age, and family structure.

[0495] An "asset plan" is an optimal plan created by an AI agent based on the user's personal information to achieve future financial goals.

[0496] An "information processing device" is a device that analyzes personal information received from users and performs calculations to generate asset plans.

[0497] "Financial transaction products" refer to financial products such as insurance, investment trusts, and pension plans intended for asset management.

[0498] A "search device" is a device that searches for the most suitable financial transaction products based on an asset plan and creates a list of suggestions.

[0499] The "Proposal List" is a list of financial products provided to the user that match their asset plan.

[0500] An "information transmission device" is a device that provides search results to the user and has the function of providing additional information or accepting inquiries.

[0501] An "electronic payment function" is a system that provides a means of payment for users to purchase financial products of their choice on the spot.

[0502] The system that implements this application example consists of a terminal such as a smartphone and a server. The user accesses the application through the terminal and enters personal information such as income, savings, and family structure. The terminal sends the entered information to the server.

[0503] The server stores personal information received from users in a dedicated database and verifies its accuracy using data validation methods. This process is handled by an AI agent using Python and TensorFlow, which generates asset plans by referencing historical market data and financial trends. Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions and creates a list of suggestions.

[0504] Users can view a list of suggestions on their terminal and select financial products that interest them. Through an information transmission device, users can send additional questions, and an AI agent will provide appropriate answers and further advice. Furthermore, a processing unit with electronic payment capabilities allows users to purchase their selected financial products on the spot.

[0505] As a concrete example, consider a user who is 35 years old, has an annual income of 6 million yen and savings of 3 million yen, and is seeking advice on funding their child's education. Using this system, an AI agent can create an asset plan based on this information and suggest appropriate educational insurance or investment trusts. The user can immediately review these suggestions and purchase their chosen financial products within the app.

[0506] Examples of prompt statements to input into the generative AI model are as follows:

[0507] "Please propose an ideal investment plan for a 35-year-old user with an annual income of 6 million yen and savings of 3 million yen. A plan that specifically considers children's education expenses is particularly important."

[0508] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0509] Step 1:

[0510] The user accesses the application using their device and enters personal information such as income, savings, age, and family structure. The device then sends the entered information to the server. This input data is organized in JSON format and sent to the server via a communication protocol.

[0511] Step 2:

[0512] The server stores the received personal information in a database. The Django framework in Python is used for this data storage. Once the database write is complete, data validation is performed to verify the integrity of the input data. This checks for outliers and missing values ​​to ensure there are no problems.

[0513] Step 3:

[0514] The server launches an AI agent using Python and TensorFlow to generate an asset plan based on verified personal information. The user's income and age are provided as input data, and the AI ​​model analyzes this data to output an appropriate financial plan through calculations. These calculations refer to historical market data and the latest financial information.

[0515] Step 4:

[0516] Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions. The search is performed using SQL queries, and multiple financial products are returned as search results. This information is organized into a list of suggestions.

[0517] Step 5:

[0518] The terminal displays a list of suggestions received from the server to the user. The user selects products of interest based on this list. Detailed information about the selected financial products is then presented to the user.

[0519] Step 6:

[0520] The user enters and submits an additional question from their device. This question is sent to the server via an information transmission device. The server uses an AI agent to analyze the question and generate appropriate answers and advice. The generated information is then formatted and displayed on the device.

[0521] Step 7:

[0522] When a user proceeds with purchasing a financial product they have selected, the terminal initiates the purchase process via its electronic payment function. The server processes the user's payment information through the payment gateway and completes the transaction. After confirmation that the payment is complete, a purchase completion notification is displayed on the user's terminal.

[0523] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0524] This invention provides a more personalized experience by combining a system that effectively proposes asset plans and related financial products using the user's personal data with an emotion engine that recognizes the user's emotions. The system starts with the input of user data, followed by the creation of a life plan by an AI agent, the proposal of financial products, and the adjustment of proposals based on the analysis of the user's emotions.

[0525] Users use devices such as smartphones or computers to enter the necessary information via a dedicated application or website. Users input their income, savings, age, family structure, etc., into their devices and submit the data. The device then sends this data to the server.

[0526] The server stores the received user data in a database and verifies its accuracy using data validation tools. It then activates an AI agent to generate the user's life plan. Historical market data and the latest financial information are used in this process. Based on the life plan, the server searches the database for multiple products to suggest the most suitable financial instruments and creates a list of recommendations.

[0527] Next, the emotion engine activates and evaluates the user's emotional state by analyzing user input and actions. For example, if the user is hesitant or unsure about a choice, this engine recognizes this and adjusts the suggestions and the order in which information is displayed.

[0528] The device displays customized content to the user based on a list of suggestions provided by the server and analysis results from the sentiment engine. Depending on the user's response, the device can request further information, which is sent to the server. The server uses an AI agent to analyze and generate answers to the user's additional inquiries, and provides the results to the user.

[0529] For example, if a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future, this system will generate a life plan based on the user's data and suggest insurance products suitable for saving for education. If the user expresses anxiety or doubt about the suggestion, the emotion engine will detect this, and the server will restructure the suggestion and provide more reassuring information to support the user's decision-making.

[0530] In this way, the system of the present invention takes into account not only the user's personal needs but also their emotional aspects, realizing a more comprehensive and user-friendly financial service experience.

[0531] The following describes the processing flow.

[0532] Step 1:

[0533] The user accesses a dedicated application or website and opens a screen to enter personal information. The user enters the necessary information such as income, savings, age, and family structure, and then presses the submit button.

[0534] Step 2:

[0535] The terminal receives input data from the user and converts it to the appropriate format. The terminal then creates and sends a request to send the formatted data to the server.

[0536] Step 3:

[0537] The server receives user data sent from the terminal. The server uses data verification means to confirm the accuracy of the received data. After confirming the accuracy of the data, it saves it to the database.

[0538] Step 4:

[0539] The server activates an AI agent, analyzes user data, and generates a life plan. Based on market data and financial information, the AI ​​agent develops the optimal strategy for the user's life plan.

[0540] Step 5:

[0541] The server suggests relevant financial products based on the generated life plan. It retrieves information from partner databases, selects the most suitable products, and creates a list of suggestions.

[0542] Step 6:

[0543] The server uses an emotion engine to analyze the user's emotional state from their input and interactions. Based on this analysis, it adjusts the display order and details of suggested content.

[0544] Step 7:

[0545] The device displays a list of suggestions to the user that reflect the analysis results of the emotion engine. The user reviews the suggestions and enters additional questions or feedback as needed.

[0546] Step 8:

[0547] The device sends the user's question to the server. The server uses an AI agent to analyze the question and generate answers and additional information.

[0548] Step 9:

[0549] The server sends the generated response to the terminal. The terminal presents the received information to the user and continues to provide support to assist the user in making decisions.

[0550] (Example 2)

[0551] Next, we will describe Example 2. 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."

[0552] In conventional systems, the emotional aspects of users were not considered when providing plans and proposals based on their personal data, which sometimes caused anxiety and doubt among users. Furthermore, the customization of proposals was insufficient, resulting in users not receiving the optimal service.

[0553] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0554] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; search means for searching for related products based on said plan and creating a list of suggestions; and emotion analysis means for analyzing the user's emotional state and adjusting the content of the suggestions. This makes it possible to provide customized suggestions that take the user's emotions into consideration.

[0555] "Information processing means" refers to devices or software that have the ability to generate plans based on personal data received from users.

[0556] "Search means" refers to devices or software that have the function of searching for relevant products from a database or other source based on the generated plan and creating a list of suggestions.

[0557] "Emotional analysis means" refers to devices or software that analyze user input data and behavior to evaluate the user's emotional state and adjust the suggested content based on that.

[0558] "Communication means" refers to devices and software that provide users with customized search results and suggestions, and that also accept additional information and questions from users.

[0559] This invention is a system that utilizes a user's personal data to effectively suggest products related to their asset plan. Furthermore, by combining this system with an emotion analysis function that recognizes the user's emotions, it provides a more personalized experience.

[0560] First, the user uses a smartphone or computer as their device to access a dedicated application or website and enters personal data such as income, savings, age, and family structure. The user then submits this information to proceed to the next step.

[0561] The terminal sends the data entered by the user to the server. The server stores the received data in a database and verifies the accuracy of the data using data validation methods. The server activates an AI agent to generate the user's asset plan, utilizing a generative AI model in this process. It leverages historical market data and the latest information to construct a plan tailored to the user's situation.

[0562] Furthermore, the server searches the database for relevant products based on the plan and creates a list of optimal product suggestions. Then, it uses sentiment analysis tools to analyze user data and behavior and evaluate the user's emotional state. If it detects user doubts or anxieties, it adjusts the suggestions and provides information to alleviate those anxieties.

[0563] A concrete example of its use is when a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future plans. Based on this data, the system suggests products suitable for saving for education. If the user expresses concerns about the suggestions, sentiment analysis detects this, and the server presents more persuasive information.

[0564] This system utilizes generative AI models to propose optimal plans and products to users, providing comprehensive services that also take into account user emotions.

[0565] An example of a prompt message would be, "Please suggest the optimal life plan and financial products for a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen."

[0566] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0567] Step 1:

[0568] The user activates the device and opens a dedicated application or website. The user enters personal data such as income, savings, age, and family structure into a form and clicks the "Submit" button. The input here is the user's personal information, and the output is a data package prepared for transmission to the device. This data serves as the basic information necessary for subsequent processing.

[0569] Step 2:

[0570] The terminal packages the personal data entered by the user and sends it to the server via a secure network. At this point, the input is a data package, and the output is data formatted in a format that the server can receive. This transmission allows the user data to proceed to central processing.

[0571] Step 3:

[0572] The server processes the received data and stores it in the database. The input here is user data sent from the terminal, and the output is the data in the format stored in the database. Furthermore, data validation measures are used to check the integrity and accuracy of the data, and any inaccurate data is corrected or a warning is generated.

[0573] Step 4:

[0574] The server activates an AI agent and uses a generated AI model to create a user's asset plan. Here, the input is verified user data, and the output is the user's life plan. Specifically, it uses historical market data and the latest financial information to create future asset formation scenarios based on the user's data.

[0575] Step 5:

[0576] The server searches the database for relevant products based on the generated life plan and generates a list of suggestions. The input is the life plan, and the output is a list of financial products tailored to the user's needs. It retrieves product characteristics from the database and analyzes past performance.

[0577] Step 6:

[0578] The server uses sentiment analysis tools to analyze user input and behavior and evaluate their emotional state. Input consists of user behavior logs and responses, while output is an evaluation indicating the emotional situation. This analysis helps understand how the user feels about the proposal.

[0579] Step 7:

[0580] The server adjusts the suggestions based on sentiment analysis, creating optimized information. The input is the emotional state and a list of suggestions, and the output is customized suggestions. This results in information display that provides users with a sense of security.

[0581] Step 8:

[0582] The terminal visualizes and displays customized information received from the server to the user. The input is the server's pre-configured output, and the output is the information displayed on the user's screen. It is important to present this information clearly using list formats or infographics.

[0583] Step 9:

[0584] When a user requests additional information or enters a question, the terminal sends that request to the server. Here, the input is the user's request or question, and the output is the request sent to the server. This feature provides additional support for the user's questions.

[0585] Step 10:

[0586] The server uses an AI agent to analyze additional requests from the user and generate appropriate responses. The input is the user's request, and the output is the answer or additional information. Finally, the results are provided to the user via the terminal.

[0587] (Application Example 2)

[0588] Next, we will explain application example 2. In the following explanation, 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."

[0589] Traditional financial services often fail to consider the individual emotions of users, resulting in an inability to recommend appropriate financial products. Furthermore, they lack mechanisms to support users' daily purchasing behavior, and specific savings suggestions tailored to users' emotions are insufficient.

[0590] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing means that receives personal data from a user and generates an asset plan based on the personal data; a search means that searches for related financial products based on the asset plan and creates a list of suggestions; an emotion analysis means that analyzes the user's emotions and adjusts the content of the suggestions based on the analysis results; and a purchase support means that provides savings suggestions based on the user's daily emotional state. This makes it possible to provide users with appropriate financial product suggestions that take their emotions into consideration and to support them in managing their daily expenses.

[0591] "Personal data" refers to basic information about a user, such as age, income, and savings, and is used to generate financial plans.

[0592] An "asset plan" is a long-term financial guideline generated based on the user's personal data, tailored to the user's life stage.

[0593] "Information processing means" refers to system components that analyze personal data received from users and generate asset plans.

[0594] A "search tool" is a system component that searches a database for relevant financial products based on the generated asset plan and creates a list of suggestions.

[0595] "Communication methods" refer to system elements that provide users with search results, as well as the role of providing additional information and accepting questions.

[0596] An "emotion analysis tool" is a system component that analyzes the user's emotional state from their input and actions, and adjusts the suggested content based on the results.

[0597] "Purchase support tools" are support functions that provide more appropriate savings suggestions based on the user's daily emotional state.

[0598] The system for implementing this invention uses the user's personal data and emotional data to perform asset management and purchasing support. The user inputs their personal data through a device such as a smartphone or tablet. The device then transmits this data to the server.

[0599] The server generates an asset plan using information processing means based on the received personal data. The asset plan is enhanced by a search means that searches for relevant financial products in the server's database and creates a list of suggestions. The list of suggestions created by the search means is provided to the user via communication means.

[0600] Furthermore, the server uses emotion analysis tools to analyze the user's emotional state based on their input data and behavior. This analysis is used to adjust the suggested content to match the user's emotions. In the user's daily purchasing behavior, the purchasing support tools provide savings suggestions based on the user's emotional state. This allows the user to receive more personalized suggestions that take their emotions into consideration.

[0601] For example, if a user shows signs of anxiety while shopping at a supermarket, an emotion analysis tool can detect that emotion, and the server can use purchasing support tools to suggest a more appropriate shopping list to help them stay within their monthly budget.

[0602] An example of a prompt to input into a generative AI model is: "When a user is feeling anxious, how can you improve the suggestion to make it more reassuring? Consider the results of the emotion engine analysis and explain your approach." By using this prompt, the generative AI model can gain new insights to improve the user experience.

[0603] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0604] Step 1:

[0605] The user inputs various personal data, such as age, income, savings, and family structure, through the terminal. The terminal then sends this data to the server. In this case, input is via keyboard or voice input by the user, and output is the transmission of data to the server.

[0606] Step 2:

[0607] The server processes the received personal data using information processing tools to generate an asset plan. Here, various asset management plans are created based on the personal data, and these are then processed to form a life plan. The output is the generated asset plan.

[0608] Step 3:

[0609] The server uses a search mechanism to retrieve relevant financial products from the database based on the asset plan and creates a list of suggestions. In this step, the asset plan is used as input, the characteristics of the relevant financial products are evaluated, and data calculations are performed to add appropriate products to the list based on that information. The output is the suggestion list.

[0610] Step 4:

[0611] The server uses emotion analysis tools to analyze user behavior and input data, and then analyzes the user's emotional state. Here, user input is used as the input, and data analysis techniques are applied to identify emotions. The output is the analysis result.

[0612] Step 5:

[0613] The server adjusts the suggestion list based on the sentiment analysis results and generates necessary savings suggestions using purchase support methods. The inputs in this step are the sentiment analysis results and the suggestion list, and the output is a customized suggestion list and savings strategies.

[0614] Step 6:

[0615] The terminal displays the final list of suggestions and savings proposals from the server to the user. The user can ask further questions about the suggestions as needed, and these questions are sent back to the server. Input is data from the server, and output is a visual and auditory presentation of information to the user.

[0616] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0617] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0618] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0619] [Fourth Embodiment]

[0620] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0621] As shown in Figure 7, the 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.

[0622] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0623] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0624] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0625] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0626] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0627] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0628] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0629] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0630] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0631] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0632] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0633] This invention provides a system that allows users to smoothly consult about asset management and financial product selection without direct interaction. The system begins with the input of user data, then creates an individualized life plan through an AI agent, and finally proposes the most suitable financial products based on that plan.

[0634] Users access a dedicated application or website using a device such as a smartphone or computer. The device displays a screen prompting the user to enter personal information. Users enter their income, savings, age, family structure, etc., and submit the information.

[0635] The terminal sends user input data to the server. The server stores the received data in a database and verifies its accuracy using data validation tools. After confirming that the data is appropriate, the server activates the AI ​​agent.

[0636] The AI ​​agent performs calculations to create an asset plan based on the user's personal data received. This involves referencing historical market data and the latest financial information. The AI ​​agent then creates an optimal life plan tailored to the user's life stage and future goals.

[0637] Subsequently, the server proposes financial products based on the life plan generated by the AI. The proposals are made by searching for the most suitable products from the databases of partner insurance companies and financial institutions and creating a list of suggestions.

[0638] The device presents the user with a list of suggested search results. The user reviews the list and, if they have further questions, can send a query to the server via the device. The server's AI agent generates answers and additional advice to the questions and responds to the user through the device.

[0639] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen can use this system if they want to find appropriate insurance and asset management methods while considering their family's future plans. Once the user inputs the necessary data, an AI agent will use that information to suggest pension savings plans and insurance products that cover children's education expenses, and will also provide timely feedback on the advantages and disadvantages of each.

[0640] In this way, the present invention provides an environment in which users can effectively and efficiently plan their assets and select appropriate financial products without feeling any psychological resistance.

[0641] The following describes the processing flow.

[0642] Step 1:

[0643] Users access a dedicated application or website and open a personal information input screen. Users enter the necessary information, such as income, savings, age, and family structure, and then submit the information.

[0644] Step 2:

[0645] The terminal receives input data from the user and formats it. The formatted data is then prepared as a transmission request to the server.

[0646] Step 3:

[0647] The server receives user data sent from the terminal and stores its contents in a database. Data validation is used to verify the accuracy of the received data and check for errors.

[0648] Step 4:

[0649] The server activates the AI ​​agent after verifying that the data is accurate. The AI ​​agent analyzes the user data and performs calculations to create a life plan.

[0650] Step 5:

[0651] The server searches for the most suitable financial products based on the life plan generated by the AI ​​agent. It retrieves insurance and investment product information from partner databases and compiles them into a list of suggestions.

[0652] Step 6:

[0653] The server sends the generated list of suggestions to the terminal. The terminal then displays this list of suggestions to the user.

[0654] Step 7:

[0655] The user reviews the displayed list of suggestions and, if they have any questions, enter them via their device. The questions are then sent to the server.

[0656] Step 8:

[0657] The server receives the user's question and instructs the AI ​​agent to analyze the question and generate an answer. The generated answer is then sent to the user via the terminal.

[0658] Step 9:

[0659] The terminal displays the AI's response received from the server to the user. The user then uses the provided information to make decisions about the optimal asset management and financial products.

[0660] (Example 1)

[0661] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0662] In recent years, consumers have had to choose from a diverse range of financial products and investment methods, and the process has become increasingly complex. Traditional methods required users to individually gather information and select products suitable for their circumstances, which required considerable time and effort. This often led to inefficient investment planning and caused stress for users. Therefore, there is a need for a method that allows users to easily and efficiently select the products best suited to their needs.

[0663] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0664] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; generation means for performing calculations by referring to past market data and the latest information to create an optimal plan; and search means for searching for related products and creating a list of suggestions based on the plan generated using a generation AI model. This enables users to efficiently receive optimal asset plans and product suggestions based on their own information.

[0665] "Information processing means" refers to a computer system or program for generating plans based on personal data received from users.

[0666] "Generation means" refers to a device that includes algorithms and programs for creating an optimal plan by referring to past market data and the latest information.

[0667] A "generative AI model" refers to artificial intelligence technology used to analyze received data and make optimal suggestions.

[0668] "Search method" refers to a system or program for searching a database for relevant products based on the generated plan and creating a list of suggestions.

[0669] "Communication means" refers to communication devices and programs that use a network to provide users with search results and additional information, and to receive questions and information from users.

[0670] "Data verification means" refers to a program or device that has a verification function to confirm the accuracy and consistency of data entered by the user.

[0671] To implement this invention, a system is required in which a user, a terminal, and a server work in cooperation. The user accesses a dedicated application or website using a terminal such as a smartphone or personal computer. This terminal provides the user with a screen for entering personal data such as income, savings, age, and family structure. The data entered by the user is transmitted to the server via the terminal.

[0672] The server stores the received personal data in a database using information processing tools and applies data verification tools to confirm the accuracy of the data. If the data is deemed valid, the server activates a generation tool and uses historical market data and the latest financial information to create an optimal plan using a generation AI model. Based on this plan, the server searches for relevant products in the product database. This is done using a search tool to generate a suggestion list containing the optimal products.

[0673] For example, a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen might use this system to find insurance and investment methods suitable for their family's future planning. In this case, the user inputs the necessary information into the system. The server uses an AI agent to suggest pension savings plans and insurance products that cover education expenses, and also provides feedback on the advantages and disadvantages of each product.

[0674] An example of a prompt might be: "I'm a 30-year-old male with an annual income of 5 million yen and savings of 2 million yen. I would like a proposal for a long-term asset management plan and insurance that can cover education expenses for my family (wife and two children)."

[0675] In this way, the system assists users in efficiently developing optimal asset plans and selecting appropriate products.

[0676] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0677] Step 1:

[0678] Users access a dedicated application or website using their device. Here, users enter personal information such as income, savings, age, and family structure. The input screen performs real-time error checking to ensure accurate and complete data entry, verifying that all required fields are included. This data is then transmitted from the device to the server.

[0679] Step 2:

[0680] The terminal collects input data from the user and sends it to the server. The server receives this data and stores it in a database using information processing tools. Specifically, the server verifies the integrity of the received data and checks the accuracy of each item using data verification tools. For example, if there is inconsistent or missing data, the server generates an error message and sends it to the terminal.

[0681] Step 3:

[0682] After the server determines that the data is correct, it activates a generation process using a generative AI model. Here, the server takes user data as input and calculates an optimal asset plan for the individual, referencing historical market data and the latest financial information. This process utilizes simulation technology to generate multiple scenarios tailored to the user's life stage, ultimately determining the optimal plan as the output.

[0683] Step 4:

[0684] Based on the generated plan, the server searches a database of relevant products. Using the search mechanism, it lists financial and insurance products that match the individual user's needs. As output, a proposal list containing information such as product names, interest rates, and risk assessments is generated and sent to the terminal.

[0685] Step 5:

[0686] The terminal displays a list of suggestions received from the server to the user. The user reviews the suggested products and selects the option that suits them best. The user can also send additional questions to the server via the terminal. The user interface displays information in a visually organized manner to enable comparison of options.

[0687] Step 6:

[0688] The server receives inquiries from users and uses a generative AI model to generate appropriate additional information and advice. In this process, the AI ​​understands the question using prompts, forms an accurate answer as output, and sends it to the terminal. The user can then review this answer and make further decisions.

[0689] (Application Example 1)

[0690] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0691] In modern society, asset management and the selection of financial products are complex and time-consuming processes for users. In particular, there is a need to provide users with a means to effectively and efficiently select the optimal financial products and to purchase them easily. Furthermore, there is a need for a system that can respond to additional user inquiries about the proposed financial products.

[0692] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0693] In this invention, the server includes an information processing device that receives personal information from a user and generates an asset plan; a search device that searches for relevant financial trading products based on the asset plan and creates a list of suggestions; an information transmission device that provides the user with the search results and accepts additional information or inquiries; and a processing device equipped with an electronic payment function that allows the user to purchase the financial trading product selected on the spot. This enables the user to easily select and purchase the optimal financial trading product based on their asset plan, and also allows for a quick response to additional inquiries.

[0694] "Personal information" refers to data necessary for creating an asset plan, such as a user's income, savings, age, and family structure.

[0695] An "asset plan" is an optimal plan created by an AI agent based on the user's personal information to achieve future financial goals.

[0696] An "information processing device" is a device that analyzes personal information received from users and performs calculations to generate asset plans.

[0697] "Financial transaction products" refer to financial products such as insurance, investment trusts, and pension plans intended for asset management.

[0698] A "search device" is a device that searches for the most suitable financial transaction products based on an asset plan and creates a list of suggestions.

[0699] The "Proposal List" is a list of financial products provided to the user that match their asset plan.

[0700] An "information transmission device" is a device that provides search results to the user and has the function of providing additional information or accepting inquiries.

[0701] An "electronic payment function" is a system that provides a means of payment for users to purchase financial products of their choice on the spot.

[0702] The system that implements this application example consists of a terminal such as a smartphone and a server. The user accesses the application through the terminal and enters personal information such as income, savings, and family structure. The terminal sends the entered information to the server.

[0703] The server stores personal information received from users in a dedicated database and verifies its accuracy using data validation methods. This process is handled by an AI agent using Python and TensorFlow, which generates asset plans by referencing historical market data and financial trends. Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions and creates a list of suggestions.

[0704] Users can view a list of suggestions on their terminal and select financial products that interest them. Through an information transmission device, users can send additional questions, and an AI agent will provide appropriate answers and further advice. Furthermore, a processing unit with electronic payment capabilities allows users to purchase their selected financial products on the spot.

[0705] As a concrete example, consider a user who is 35 years old, has an annual income of 6 million yen and savings of 3 million yen, and is seeking advice on funding their child's education. Using this system, an AI agent can create an asset plan based on this information and suggest appropriate educational insurance or investment trusts. The user can immediately review these suggestions and purchase their chosen financial products within the app.

[0706] Examples of prompt statements to input into the generative AI model are as follows:

[0707] "Please propose an ideal investment plan for a 35-year-old user with an annual income of 6 million yen and savings of 3 million yen. A plan that specifically considers children's education expenses is particularly important."

[0708] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0709] Step 1:

[0710] The user accesses the application using their device and enters personal information such as income, savings, age, and family structure. The device then sends the entered information to the server. This input data is organized in JSON format and sent to the server via a communication protocol.

[0711] Step 2:

[0712] The server stores the received personal information in a database. The Django framework in Python is used for this data storage. Once the database write is complete, data validation is performed to verify the integrity of the input data. This checks for outliers and missing values ​​to ensure there are no problems.

[0713] Step 3:

[0714] The server launches an AI agent using Python and TensorFlow to generate an asset plan based on verified personal information. The user's income and age are provided as input data, and the AI ​​model analyzes this data to output an appropriate financial plan through calculations. These calculations refer to historical market data and the latest financial information.

[0715] Step 4:

[0716] Based on the generated asset plan, the server searches for the most suitable financial products from the databases of partner financial institutions. The search is performed using SQL queries, and multiple financial products are returned as search results. This information is organized into a list of suggestions.

[0717] Step 5:

[0718] The terminal displays a list of suggestions received from the server to the user. The user selects products of interest based on this list. Detailed information about the selected financial products is then presented to the user.

[0719] Step 6:

[0720] The user enters and submits an additional question from their device. This question is sent to the server via an information transmission device. The server uses an AI agent to analyze the question and generate appropriate answers and advice. The generated information is then formatted and displayed on the device.

[0721] Step 7:

[0722] When a user proceeds with purchasing a financial product they have selected, the terminal initiates the purchase process via its electronic payment function. The server processes the user's payment information through the payment gateway and completes the transaction. After confirmation that the payment is complete, a purchase completion notification is displayed on the user's terminal.

[0723] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0724] This invention provides a more personalized experience by combining a system that effectively proposes asset plans and related financial products using the user's personal data with an emotion engine that recognizes the user's emotions. The system starts with the input of user data, followed by the creation of a life plan by an AI agent, the proposal of financial products, and the adjustment of proposals based on the analysis of the user's emotions.

[0725] Users use devices such as smartphones or computers to enter the necessary information via a dedicated application or website. Users input their income, savings, age, family structure, etc., into their devices and submit the data. The device then sends this data to the server.

[0726] The server stores the received user data in a database and verifies its accuracy using data validation tools. It then activates an AI agent to generate the user's life plan. Historical market data and the latest financial information are used in this process. Based on the life plan, the server searches the database for multiple products to suggest the most suitable financial instruments and creates a list of recommendations.

[0727] Next, the emotion engine activates and evaluates the user's emotional state by analyzing user input and actions. For example, if the user is hesitant or unsure about a choice, this engine recognizes this and adjusts the suggestions and the order in which information is displayed.

[0728] The device displays customized content to the user based on a list of suggestions provided by the server and analysis results from the sentiment engine. Depending on the user's response, the device can request further information, which is sent to the server. The server uses an AI agent to analyze and generate answers to the user's additional inquiries, and provides the results to the user.

[0729] For example, if a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future, this system will generate a life plan based on the user's data and suggest insurance products suitable for saving for education. If the user expresses anxiety or doubt about the suggestion, the emotion engine will detect this, and the server will restructure the suggestion and provide more reassuring information to support the user's decision-making.

[0730] In this way, the system of the present invention takes into account not only the user's personal needs but also their emotional aspects, realizing a more comprehensive and user-friendly financial service experience.

[0731] The following describes the processing flow.

[0732] Step 1:

[0733] The user accesses a dedicated application or website and opens a screen to enter personal information. The user enters the necessary information such as income, savings, age, and family structure, and then presses the submit button.

[0734] Step 2:

[0735] The terminal receives input data from the user and converts it to the appropriate format. The terminal then creates and sends a request to send the formatted data to the server.

[0736] Step 3:

[0737] The server receives user data sent from the terminal. The server uses data verification means to confirm the accuracy of the received data. After confirming the accuracy of the data, it saves it to the database.

[0738] Step 4:

[0739] The server activates an AI agent, analyzes user data, and generates a life plan. Based on market data and financial information, the AI ​​agent develops the optimal strategy for the user's life plan.

[0740] Step 5:

[0741] The server suggests relevant financial products based on the generated life plan. It retrieves information from partner databases, selects the most suitable products, and creates a list of suggestions.

[0742] Step 6:

[0743] The server uses an emotion engine to analyze the user's emotional state from their input and interactions. Based on this analysis, it adjusts the display order and details of suggested content.

[0744] Step 7:

[0745] The device displays a list of suggestions to the user that reflect the analysis results of the emotion engine. The user reviews the suggestions and enters additional questions or feedback as needed.

[0746] Step 8:

[0747] The device sends the user's question to the server. The server uses an AI agent to analyze the question and generate answers and additional information.

[0748] Step 9:

[0749] The server sends the generated response to the terminal. The terminal presents the received information to the user and continues to provide support to assist the user in making decisions.

[0750] (Example 2)

[0751] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0752] In conventional systems, the emotional aspects of users were not considered when providing plans and proposals based on their personal data, which sometimes caused anxiety and doubt among users. Furthermore, the customization of proposals was insufficient, resulting in users not receiving the optimal service.

[0753] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0754] In this invention, the server includes information processing means for receiving personal data from a user and generating a plan based on said personal data; search means for searching for related products based on said plan and creating a list of suggestions; and emotion analysis means for analyzing the user's emotional state and adjusting the content of the suggestions. This makes it possible to provide customized suggestions that take the user's emotions into consideration.

[0755] "Information processing means" refers to devices or software that have the ability to generate plans based on personal data received from users.

[0756] "Search means" refers to devices or software that have the function of searching for relevant products from a database or other source based on the generated plan and creating a list of suggestions.

[0757] "Emotional analysis means" refers to devices or software that analyze user input data and behavior to evaluate the user's emotional state and adjust the suggested content based on that.

[0758] "Communication means" refers to devices and software that provide users with customized search results and suggestions, and that also accept additional information and questions from users.

[0759] This invention is a system that utilizes a user's personal data to effectively suggest products related to their asset plan. Furthermore, by combining this system with an emotion analysis function that recognizes the user's emotions, it provides a more personalized experience.

[0760] First, the user uses a smartphone or computer as their device to access a dedicated application or website and enters personal data such as income, savings, age, and family structure. The user then submits this information to proceed to the next step.

[0761] The terminal sends the data entered by the user to the server. The server stores the received data in a database and verifies the accuracy of the data using data validation methods. The server activates an AI agent to generate the user's asset plan, utilizing a generative AI model in this process. It leverages historical market data and the latest information to construct a plan tailored to the user's situation.

[0762] Furthermore, the server searches the database for relevant products based on the plan and creates a list of optimal product suggestions. Then, it uses sentiment analysis tools to analyze user data and behavior and evaluate the user's emotional state. If it detects user doubts or anxieties, it adjusts the suggestions and provides information to alleviate those anxieties.

[0763] A concrete example of its use is when a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen is considering their family's future plans. Based on this data, the system suggests products suitable for saving for education. If the user expresses concerns about the suggestions, sentiment analysis detects this, and the server presents more persuasive information.

[0764] This system utilizes generative AI models to propose optimal plans and products to users, providing comprehensive services that also take into account user emotions.

[0765] An example of a prompt message would be, "Please suggest the optimal life plan and financial products for a 30-year-old user with an annual income of 5 million yen and savings of 2 million yen."

[0766] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0767] Step 1:

[0768] The user activates the device and opens a dedicated application or website. The user enters personal data such as income, savings, age, and family structure into a form and clicks the "Submit" button. The input here is the user's personal information, and the output is a data package prepared for transmission to the device. This data serves as the basic information necessary for subsequent processing.

[0769] Step 2:

[0770] The terminal packages the personal data entered by the user and sends it to the server via a secure network. At this point, the input is a data package, and the output is data formatted in a format that the server can receive. This transmission allows the user data to proceed to central processing.

[0771] Step 3:

[0772] The server processes the received data and stores it in the database. The input here is user data sent from the terminal, and the output is the data in the format stored in the database. Furthermore, data validation measures are used to check the integrity and accuracy of the data, and any inaccurate data is corrected or a warning is generated.

[0773] Step 4:

[0774] The server activates an AI agent and uses a generated AI model to create a user's asset plan. Here, the input is verified user data, and the output is the user's life plan. Specifically, it uses historical market data and the latest financial information to create future asset formation scenarios based on the user's data.

[0775] Step 5:

[0776] The server searches the database for relevant products based on the generated life plan and generates a list of suggestions. The input is the life plan, and the output is a list of financial products tailored to the user's needs. It retrieves product characteristics from the database and analyzes past performance.

[0777] Step 6:

[0778] The server uses sentiment analysis tools to analyze user input and behavior and evaluate their emotional state. Input consists of user behavior logs and responses, while output is an evaluation indicating the emotional situation. This analysis helps understand how the user feels about the proposal.

[0779] Step 7:

[0780] The server adjusts the suggestions based on sentiment analysis, creating optimized information. The input is the emotional state and a list of suggestions, and the output is customized suggestions. This results in information display that provides users with a sense of security.

[0781] Step 8:

[0782] The terminal visualizes and displays customized information received from the server to the user. The input is the server's pre-configured output, and the output is the information displayed on the user's screen. It is important to present this information clearly using list formats or infographics.

[0783] Step 9:

[0784] When a user requests additional information or enters a question, the terminal sends that request to the server. Here, the input is the user's request or question, and the output is the request sent to the server. This feature provides additional support for the user's questions.

[0785] Step 10:

[0786] The server uses an AI agent to analyze additional requests from the user and generate appropriate responses. The input is the user's request, and the output is the answer or additional information. Finally, the results are provided to the user via the terminal.

[0787] (Application Example 2)

[0788] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0789] Traditional financial services often fail to consider the individual emotions of users, resulting in an inability to recommend appropriate financial products. Furthermore, they lack mechanisms to support users' daily purchasing behavior, and specific savings suggestions tailored to users' emotions are insufficient.

[0790] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an information processing means that receives personal data from a user and generates an asset plan based on the personal data; a search means that searches for related financial products based on the asset plan and creates a list of suggestions; an emotion analysis means that analyzes the user's emotions and adjusts the content of the suggestions based on the analysis results; and a purchase support means that provides savings suggestions based on the user's daily emotional state. This makes it possible to provide users with appropriate financial product suggestions that take their emotions into consideration and to support them in managing their daily expenses.

[0791] "Personal data" refers to basic information about a user, such as age, income, and savings, and is used to generate financial plans.

[0792] An "asset plan" is a long-term financial guideline generated based on the user's personal data, tailored to the user's life stage.

[0793] "Information processing means" refers to system components that analyze personal data received from users and generate asset plans.

[0794] A "search tool" is a system component that searches a database for relevant financial products based on the generated asset plan and creates a list of suggestions.

[0795] "Communication methods" refer to system elements that provide users with search results, as well as the role of providing additional information and accepting questions.

[0796] An "emotion analysis tool" is a system component that analyzes the user's emotional state from their input and actions, and adjusts the suggested content based on the results.

[0797] "Purchase support tools" are support functions that provide more appropriate savings suggestions based on the user's daily emotional state.

[0798] The system for implementing this invention uses the user's personal data and emotional data to perform asset management and purchasing support. The user inputs their personal data through a device such as a smartphone or tablet. The device then transmits this data to the server.

[0799] The server generates an asset plan using information processing means based on the received personal data. The asset plan is enhanced by a search means that searches for relevant financial products in the server's database and creates a list of suggestions. The list of suggestions created by the search means is provided to the user via communication means.

[0800] Furthermore, the server uses emotion analysis tools to analyze the user's emotional state based on their input data and behavior. This analysis is used to adjust the suggested content to match the user's emotions. In the user's daily purchasing behavior, the purchasing support tools provide savings suggestions based on the user's emotional state. This allows the user to receive more personalized suggestions that take their emotions into consideration.

[0801] For example, if a user shows signs of anxiety while shopping at a supermarket, an emotion analysis tool can detect that emotion, and the server can use purchasing support tools to suggest a more appropriate shopping list to help them stay within their monthly budget.

[0802] An example of a prompt to input into a generative AI model is: "When a user is feeling anxious, how can you improve the suggestion to make it more reassuring? Consider the results of the emotion engine analysis and explain your approach." By using this prompt, the generative AI model can gain new insights to improve the user experience.

[0803] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0804] Step 1:

[0805] The user inputs various personal data, such as age, income, savings, and family structure, through the terminal. The terminal then sends this data to the server. In this case, input is via keyboard or voice input by the user, and output is the transmission of data to the server.

[0806] Step 2:

[0807] The server processes the received personal data using information processing tools to generate an asset plan. Here, various asset management plans are created based on the personal data, and these are then processed to form a life plan. The output is the generated asset plan.

[0808] Step 3:

[0809] The server uses a search mechanism to retrieve relevant financial products from the database based on the asset plan and creates a list of suggestions. In this step, the asset plan is used as input, the characteristics of the relevant financial products are evaluated, and data calculations are performed to add appropriate products to the list based on that information. The output is the suggestion list.

[0810] Step 4:

[0811] The server uses emotion analysis tools to analyze user behavior and input data, and then analyzes the user's emotional state. Here, user input is used as the input, and data analysis techniques are applied to identify emotions. The output is the analysis result.

[0812] Step 5:

[0813] The server adjusts the suggestion list based on the sentiment analysis results and generates necessary savings suggestions using purchase support methods. The inputs in this step are the sentiment analysis results and the suggestion list, and the output is a customized suggestion list and savings strategies.

[0814] Step 6:

[0815] The terminal displays the final list of suggestions and savings proposals from the server to the user. The user can ask further questions about the suggestions as needed, and these questions are sent back to the server. Input is data from the server, and output is a visual and auditory presentation of information to the user.

[0816] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0817] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0818] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0819] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0820] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0821] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0822] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0823] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0824] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0825] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0826] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0827] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0828] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0829] 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.

[0830] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0831] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0832] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0833] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0834] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0835] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0836] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0837] The following is further disclosed regarding the embodiments described above.

[0838] (Claim 1)

[0839] Information processing means that receives personal data from a user and generates an asset plan based on said personal data,

[0840] A search means that searches for relevant financial products based on the aforementioned asset plan and creates a list of proposed products,

[0841] A means of communication that provides users with search results and accepts requests for additional information or questions,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, comprising communication means for generating appropriate additional information from the suggestion list based on a question received from the user and transmitting it to the user.

[0845] (Claim 3)

[0846] The system according to claim 1, further comprising data verification means for verifying user input data and confirming its accuracy.

[0847] "Example 1"

[0848] (Claim 1)

[0849] Information processing means that receives personal data from a user and generates a plan based on said personal data,

[0850] A generation method that performs calculations by referring to past market data and the latest information to create an optimal plan,

[0851] A search method that searches for related products and creates a suggestion list based on a plan generated using a generative AI model,

[0852] A means of communication that provides users with search results and accepts requests for additional information or questions,

[0853] A system that includes this.

[0854] (Claim 2)

[0855] The system according to claim 1, comprising communication means for generating appropriate additional information from a suggestion list using a generative AI model based on a question received from the user, and transmitting it to the user.

[0856] (Claim 3)

[0857] The system according to claim 1, further comprising data verification means for verifying user input data and confirming its accuracy.

[0858] "Application Example 1"

[0859] (Claim 1)

[0860] An information processing device that receives personal information from a user and generates an asset plan based on said personal information,

[0861] A search device that searches for related financial transaction products based on the aforementioned asset plan and creates a list of suggestions,

[0862] An information transmission device that provides search results to the user and accepts the provision of additional information or inquiries,

[0863] A processing unit equipped with an electronic payment function that allows users to purchase selected financial products on the spot,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, further comprising an information transmission device that generates appropriate additional information from the proposal list based on a user inquiry received and transmits it to the user.

[0867] (Claim 3)

[0868] The system according to claim 1, further comprising data verification means for verifying user input information and confirming its accuracy.

[0869] "Example 2 of combining an emotion engine"

[0870] (Claim 1)

[0871] Information processing means that receives personal data from a user and generates a plan based on said personal data,

[0872] A search method that searches for related products based on the aforementioned plan and creates a list of suggestions,

[0873] A sentiment analysis tool that analyzes the user's emotional state and adjusts the suggested content accordingly,

[0874] A means of communication that provides users with customized search results and accepts additional information or questions,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, comprising communication means for generating appropriate additional information from the suggestion list based on a question received from the user and transmitting it to the user.

[0878] (Claim 3)

[0879] The system according to claim 1, further comprising data verification means for verifying user input data and confirming its accuracy.

[0880] "Application example 2 when combining with an emotional engine"

[0881] (Claim 1)

[0882] Information processing means that receives personal data from a user and generates an asset plan based on said personal data,

[0883] A search means that searches for relevant financial products based on the aforementioned asset plan and creates a list of proposed products,

[0884] A means of communication that provides users with search results and accepts requests for additional information or questions,

[0885] A sentiment analysis means that analyzes the user's emotions and adjusts the suggested content based on the analysis results,

[0886] A purchasing support tool that provides savings suggestions based on the user's daily emotional state,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, comprising communication means for generating appropriate additional information from the suggestion list based on a question received from the user and transmitting it to the user.

[0890] (Claim 3)

[0891] The system according to claim 1, further comprising data verification means for verifying user input data and confirming its accuracy. [Explanation of Symbols]

[0892] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An information processing device that receives personal information from a user and generates an asset plan based on said personal information, A search device that searches for related financial transaction products based on the aforementioned asset plan and creates a list of suggestions, An information transmission device that provides search results to the user and accepts the provision of additional information or inquiries, A processing unit equipped with an electronic payment function that allows users to purchase selected financial products on the spot, A system that includes this.

2. The system according to claim 1, further comprising an information transmission device that generates appropriate additional information from the proposal list based on a user inquiry received and transmits it to the user.

3. The system according to claim 1, further comprising data verification means for verifying user input information and confirming its accuracy.

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