System

Abstract

To provide a system.SOLUTION: Provided is a system comprising: means for generating a prompt sentence that instructs a generative AI model to create advice as a financial planner, based on household account book data input by a user; means for generating the advice using the generative AI model based on the household account book data and the prompt sentence; and means for offering the generated advice to the user.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

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

[0003] [Patent Document 1] JP 2022-180282 A Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional household accounting apps, it is difficult for users to understand their own household finances and get advice on making appropriate financial plans. In addition, advice from financial planners requires specialized knowledge and is difficult for general users to understand. Furthermore, consulting with a financial planner takes time and money, so it is not something that anyone can use casually. [Means for solving the problem]

[0005] This invention adds generative AI functionality to a household accounting app, providing financial planner advice "anytime, for anyone, in an easy-to-understand, affordable way." Advice is provided in chat format, in an easy-to-understand way, just like consulting with a financial planner, on an ongoing basis, rather than one-off basis. Accurate advice and support is provided through continuous learning of personal information (attributes, household accounting app, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local living information, etc.). Support and automatic creation of complicated tax returns is realized. [Brief description of the drawings]

[0006] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Diagram 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. FIG. [Diagram 3] FIG. 11 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Diagram 5] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 13 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 13 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 2 is a sequence diagram showing a process flow of the data processing system in the first embodiment of the first form example. [Figure 12]FIG. 11 is a sequence diagram showing a process flow of the data processing system in the application example 1 of the first embodiment. [Figure 13] FIG. 11 is a sequence diagram showing a process flow of the data processing system in the second embodiment of the second embodiment. [Figure 14] FIG. 13 is a sequence diagram showing a process flow of the data processing system in application example 2 of embodiment 2. [Figure 15] FIG. 13 is a sequence diagram showing a process flow of a data processing system in a third embodiment of the present invention. [Figure 16] FIG. 13 is a sequence diagram showing a process flow of the data processing system in the third application example of the third embodiment. [Figure 17] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when combined with an emotion engine. [Figure 19] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system according to the embodiment 2 of the second embodiment in the case where an emotion engine is combined. [Figure 20] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when combined with an emotion engine. [Figure 21] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in the embodiment 3 of the embodiment 3 in the case where an emotion engine is combined. [Figure 22] FIG. 13 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when combined with an emotion engine. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] In the following embodiments, a signed processor (hereinafter simply referred to as a "processor") may be one arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be one type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] In the following embodiments, a signed RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0011] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0012] In the following embodiments, a communication I / F (Interface) with a code is an interface including a communication processor and an antenna. The communication I / F controls communication between multiple computers. An example of a communication standard applied to the communication I / F is a wireless communication standard including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0013] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. In addition, in this specification, the same idea as "A and / or B" is also applied when three or more things are expressed by connecting them with "and / or."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0017] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0018] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0019] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (e.g., a pen or a finger) to receive user input by touch. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicative of the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicative of the user input.

[0020] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (e.g., voice 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 voice according to instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a Complementary Metal-Oxide-Semiconductor (CMOS) image sensor or a Charge Coupled Device (CCD) image sensor.

[0021] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54.

[0022] FIG. 2 shows an example of main functions of the data processing device 12 and the smart device 14.

[0023] As shown in Fig. 2, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32. The specific process program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific process program 56 from the storage 32, and executes the read specific process program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific process program 56 executed on the RAM 30.

[0024] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0025] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores a reception output program 60. The reception output program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads out 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 the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] One embodiment of the present invention is a system that adds generative AI functions to a household accounting app. This system automatically generates advice from a financial planner based on household accounting data entered by the user. The generated advice is provided to the user in a format that is easy for the user to understand, such as a chat format.

[0029] "Example 2"

[0030] Furthermore, as another embodiment of the present invention, there is a system that provides accurate advice and support by combining personal information (attributes, household accounting apps, My Number Portal, etc.) with external information (tax systems, asset management, real estate, financial products, local life information, etc.). This system is capable of providing personalized advice tailored to the user's lifestyle and asset situation.

[0031] "Example 3"

[0032] As another embodiment of the present invention, there is a system that realizes automatic creation and support of complicated tax returns. This system can reduce the time and effort required for users to file tax and insurance returns and prevent mistakes. For example, when creating a tax return for year-end adjustment, the system can automatically generate the return based on the data entered by the user into a household accounting application.

[0033] The process flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user enters their income and expenditure information into the household accounting app.

[0036] Step 2: The generative AI analyzes the information entered by the user and understands the user's financial situation.

[0037] Step 3: The generative AI automatically generates FP advice and provides it to the user.

[0038] "Example 2"

[0039] Step 1: The user enters their income and expenditure information into the household accounting app.

[0040] Step 2: The system combines personal information (attributes, household accounting apps, My Number Portal, etc.) with external information (tax systems, asset management, real estate, financial products, local lifestyle information, etc.) to provide accurate advice and support.

[0041] "Example 3"

[0042] Step 1: The user enters their income and expenditure information into the household accounting app.

[0043] Step 2: The system will automatically create and provide support for complicated tax returns and other documents based on the information entered by the user.

[0044] Step 3: For example, when preparing a year-end tax return, the system automatically generates the return based on the data the user entered into the household accounting app.

[0045] Example 1

[0046] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0047] Conventional household accounting apps allow users to understand their own household finances, but to get professional advice, they must consult a financial planner separately. In addition, the cost and effort required to get advice makes it difficult to receive ongoing support. Furthermore, users must themselves fill out complicated tax returns and gather external information, which places a heavy burden on them. To solve these issues, there is a need for a system that adds generative AI functionality to household accounting apps and automatically generates and continuously provides advice from financial planners.

[0048] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0049] In this invention, the server includes a means for generating a prompt sentence based on household accounting data input by the user and sending it to the generative AI model, a means for the generative AI model to generate advice based on the prompt sentence and for the server to receive the advice, and a means for the server to send the generated advice to the user's terminal. This allows the user to automatically and continuously receive expert advice, reducing the burden of household accounting management.

[0050] A "household accounting app" is software that allows users to input and manage household data such as income, expenses, and savings.

[0051] "Generative AI" is an artificial intelligence technology that automatically generates responses and advice in natural language based on input data.

[0052] A financial planner is an expert who analyzes the financial situation of individuals and families and suggests optimal asset management and savings methods.

[0053] A "prompt sentence" is an instruction sentence input to a generative AI, which contains the information that the AI ​​uses to generate responses and advice.

[0054] A "server" is a computer system whose role is to receive data from users, process it, and send it to the generative AI.

[0055] "Terminal" means the device through which a User enters household accounting data and receives generated advice.

[0056] "Database" refers to an information management system for storing household accounting data and generated advice.

[0057] "Chat format" refers to an interface format for interaction between a user and a system, in which messages are exchanged.

[0058] "Personal information" refers to individual information such as user attributes, household accounting data, portal sites, etc.

[0059] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0060] "Continuous learning" is the process by which generative AI continues to learn from user data and external information in order to provide more accurate advice.

[0061] "Returns" means any tax returns or other official reports that you are required to submit.

[0062] This invention is a system that adds generative AI functionality to a household accounting app, automatically generating advice from a financial planner based on household accounting data entered by the user, and providing it in chat format. This system enables users to efficiently manage their household finances and receive continuous expert advice.

[0063] Hardware and Software Used

[0064] Hardware

[0065] Server: Receives, stores, and analyzes data, sends prompts to the generative AI model, receives generated advice, and sends it to the user device.

[0066] Terminal: The device (smartphone, tablet, PC, etc.) where the user enters their household accounting data and receives the generated advice.

[0067] software

[0068] Financial accounting app: An application that allows users to enter data such as income, expenses, and savings goals.

[0069] Generative AI model: An artificial intelligence technology that generates advice based on an input prompt (e.g., GPT-4 (registered trademark) by OpenAI (registered trademark)).

[0070] Database: An information management system (e.g. MySQL, PostgreSQL) for storing the accounting data and the generated advice.

[0071] Data processing and calculation

[0072] Enter and send household accounting data

[0073] The user uses the household accounting app to input data such as income, expenses, and savings goals. For example, monthly income is 300,000 yen, rent is 100,000 yen, food expenses are 50,000 yen, transportation expenses are 20,000 yen, other expenses are 30,000 yen, and savings goal is 50,000 yen. The device then transmits this data to the server.

[0074] Data storage and analysis

[0075] The server saves the received household accounting data in the database. Next, the server generates a prompt based on the saved data. For example, it generates the following prompt:

[0076] The user's monthly income is 300,000 yen, and his expenses are as follows: rent 100,000 yen, food 50,000 yen, transportation 20,000 yen, other 30,000 yen. The user's savings goal is 50,000 yen per month. Based on this, please provide some advice as a financial planner.

[0077] Generating and serving advice

[0078] The server sends the generated prompt sentence to the generative AI model. The generative AI model generates advice based on the prompt sentence. For example, it generates advice like the following:

[0079] Your monthly income is 300,000 yen and your total expenses are 200,000 yen. To achieve your savings goal of 50,000 yen, you can save the remaining 50,000 yen. Review your food expenses and other expenses and see if there are any areas where you can save money. It would also be a good idea to think about ways to increase your income.

[0080] The server receives the generated advice and transmits it to the user's terminal, where the user can receive the advice in chat format.

[0081] Examples

[0082] For example, when a user opens a household accounting app and enters income and expenditure data, the app provides an input form. After the user finishes entering the data, he or she presses the "Submit" button. The device sends this data to the server, which then stores the data in a database. The server then sends a prompt to the generative AI model and receives the generated advice. Finally, the server sends the advice to the user's device, and the user checks the advice in the app.

[0083] In this way, users can automatically and continuously receive expert advice, easing the burden of managing their household finances.

[0084] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0085] Step 1:

[0086] The user enters household accounting data

[0087] Users use a household accounting app to input data such as income, expenses, and savings goals. For example, monthly income is 300,000 yen, rent is 100,000 yen, food expenses are 50,000 yen, transportation expenses are 20,000 yen, other expenses are 30,000 yen, and savings goal is 50,000 yen. The input data is temporarily stored on the device.

[0088] Step 2:

[0089] The terminal sends the input data to the server

[0090] The terminal transmits the household accounting data entered by the user to the server. This transmission is secure using the HTTPS protocol. The input data includes information such as income, expenses, and savings goals.

[0091] Step 3:

[0092] The server saves the data to a database

[0093] The server stores the received household accounting data in a database, using a relational database such as MySQL or PostgreSQL. The stored data includes information such as the user's income, expenses, and savings goals.

[0094] Step 4:

[0095] The server sends a prompt to the generative AI model.

[0096] The server generates a prompt sentence based on the saved household accounting data. For example, it generates a prompt sentence like, "The user's monthly income is 300,000 yen, and the expenses are as follows: rent 100,000 yen, food 50,000 yen, transportation 20,000 yen, other 30,000 yen. The user's savings goal is 50,000 yen per month. Based on this, please provide some advice as a financial planner." The generated prompt sentence is sent to the generative AI model.

[0097] Step 5:

[0098] Generative AI models generate advice

[0099] A generative AI model (for example, OpenAI's GPT-4) generates advice based on the prompt text sent from the server. The generative AI model analyzes the household accounting data included in the prompt text and generates appropriate advice. For example, it generates advice such as, "Your monthly income is 300,000 yen, and your total expenses are 200,000 yen. To achieve your savings goal of 50,000 yen, you can save the remaining 50,000 yen. Please review your food expenses and other expenses and consider whether there are any areas where you can save money. It would also be a good idea to think about ways to increase your income."

[0100] Step 6:

[0101] The server receives the generated advice

[0102] The server receives advice generated from the generative AI model in a format that is easy for the user to understand.

[0103] Step 7:

[0104] The server sends advice to the device

[0105] The server transmits the generated advice to the user's terminal, again securely using the HTTPS protocol. The transmitted data is the generated advice.

[0106] Step 8:

[0107] User receives advice

[0108] Users receive the generated advice via their device. The advice is displayed in chat format, and users can use it to review and improve their household finances.

[0109] (Application example 1)

[0110] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0111] Conventional household accounting apps require users to manually input data, and require separate consultation with a financial planner (FP) to receive advice. This is time-consuming for users, making it difficult for them to continue using the apps. In addition, when using electronic payment services, expenditure data is not automatically reflected in the household accounting app, making expenditure management cumbersome.

[0112] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0113] In this invention, the server includes a means for providing a generative AI function to a household accounting app, making advice from a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in chat format that is easy to understand and similar to consulting a financial planner, not just one-time but continuous, not one-time, but continuous, and provides accurate advice and support through continuous learning of personal information (attributes, household accounting app, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically creating and supporting complicated tax returns, etc., and a means for automatically recording expenditure data in a household accounting book when using an electronic payment service, analyzing the data with a generative AI, and providing advice from a financial planner in chat format. This allows users to manage their expenditure data hassle-free and receive accurate advice on an ongoing basis.

[0114] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[0115] "Generative AI" is an artificial intelligence technology that automatically generates responses and suggestions for specific tasks based on data entered by the user.

[0116] "FP" stands for financial planner, a professional who provides financial planning and investment advice to individuals and companies.

[0117] "Chat style" refers to an interface style in which a user and a system exchange information in a dialogue format.

[0118] "Personal information" refers to information about individuals contained in user attributes, data from household accounting apps, My Number Portal, etc.

[0119] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0120] "Continuous learning" is a function that enables the system to continually learn from user data and external information in order to provide more accurate advice.

[0121] An "electronic payment service" is an online payment system that enables users to pay for goods and services via the Internet.

[0122] "Expense data" refers to information such as the amount, date, and category when a user purchases a product or service.

[0123] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[0124] In order to implement this invention, it is necessary to build a system in which a household accounting app is given generative AI functionality, expenditure data is automatically recorded in the household accounting book when using electronic payment services, and the generative AI analyzes the data and provides advice from a financial planner in chat format.

[0125] The server collects the user's spending data and analyzes it using a generative AI model. Specifically, the server automatically obtains spending data from the user's electronic payment service and records it in the household accounting app. At this time, the spending data is organized by category and displayed so that the user's household financial situation can be seen at a glance.

[0126] Next, the server uses a generative AI model to generate FP advice based on the user's spending data. This generative AI model uses OpenAI's GPT-3 (registered trademark) and other models. The generated advice is provided to the user in a chat format that is easy for the user to understand. For example, the following prompt sentences are used:

[0127] User spending data: {"2023-10-01": {"food": 5000, "transport": 2000, "entertainment": 3000}, "2023-10-02": {"food": 4500, "transport": 1500, "entertainment": 2500}, "2023-10-03": {"food": 4000, "transport": 1000, "entertainment": 2000}}

[0128] As a financial planner, you can provide advice based on this data.

[0129] The generated advice may look something like this:

[0130] FP Tip: Food costs make up a large portion of your total expenses. You can save by buying in bulk once a week and eating out less. You should also reassess your transportation costs. Using a commuter pass for public transportation can help you save even more.

[0131] Users can access the household accounting app using a smartphone, tablet, or other device and check the generated advice. When users input a question, the generative AI model generates an answer in real time and provides it in chat format.

[0132] The system allows users to effortlessly manage their spending data and receive accurate advice on an ongoing basis. The hardware required is a smartphone or tablet with an internet connection, and a server. The software uses Python, OpenAI API, and JSON files.

[0133] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0134] Step 1:

[0135] The server automatically obtains spending data from the user's electronic payment service. The input is the transaction data of the user's electronic payment service, and the output is spending data organized by category. Specifically, the server accesses the electronic payment service through an API to obtain the user's spending information. This data is stored in the form of dates, categories, amounts, etc.

[0136] Step 2:

[0137] The server records the acquired expenditure data in the household accounting app. The input is the expenditure data organized by category acquired in step 1, and the output is the expenditure data saved in the household accounting app. Specifically, the server writes the expenditure data to the database of the household accounting app so that the user can check it through the app.

[0138] Step 3:

[0139] The server uses a generative AI model to generate FP advice based on the expenditure data recorded in the household accounting app. The input is the expenditure data stored in the household accounting app, and the output is the generated FP advice. Specifically, the server inputs the expenditure data as a prompt sentence into the generative AI model to generate advice. An example of the prompt sentence is as follows:

[0140] User spending data: {"2023-10-01": {"food": 5000, "transport": 2000, "entertainment": 3000}, "2023-10-02": {"food": 4500, "transport": 1500, "entertainment": 2500}, "2023-10-03": {"food": 4000, "transport": 1000, "entertainment": 2000}}

[0141] As a financial planner, you can provide advice based on this data.

[0142] Step 4:

[0143] The server provides the generated advice to the user in chat format. The input is the FP advice generated in step 3, and the output is the advice in chat format displayed on the user's device. Specifically, the server sends the generated advice to the user's device in the form of a chatbot so that the user can check it through the app.

[0144] Step 5:

[0145] When a user enters a question, the server uses a generative AI model to generate an answer in real time and provides it in chat format. The input is the question entered by the user, and the output is the generated answer. Specifically, the server inputs the user's question as a prompt sentence into the generative AI model and generates an answer. The generated answer is displayed on the user's device in chat format.

[0146] Example 2

[0147] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0148] Advice provided by traditional household accounting apps and financial planners (FPs) is temporary, making it difficult to provide ongoing support. In addition, there is a lack of systems that provide accurate advice by combining personal information and external information, making it difficult for users to receive personalized advice based on their lifestyle and asset status. Furthermore, there is a lack of automated creation and support for cumbersome tax returns.

[0149] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for combining personal information (attributes, household accounting application, portal site, etc.) with external information (tax system, asset management, real estate, financial products, local life information, etc.) to provide accurate advice and support, a means for generating personalized advice based on the user's lifestyle and asset status, a means for encrypting personal information input by the user and transmitting it to the server using a secure communication protocol, a means for the server to store the received personal information in a database, a means for the server to collect external information and store it in a database, a means for the server to perform data analysis using a generation AI model, a means for the server to generate advice based on the analysis results, a means for the server to transmit the advice generated by the server to the terminal, and a means for the terminal to display the advice to the user. This allows the user to receive continuous and personalized advice.

[0150] "Personal information" refers to a series of data about a user, such as user attribute information, data from a household accounting app, and information from a portal site.

[0151] "External information" refers to data collected from external sources related to the user's lifestyle and asset management, such as tax systems, asset management, real estate, financial products, and local lifestyle information.

[0152] A "server" is a computer system that receives, stores, and processes data submitted by users.

[0153] A "database" is a data management system for storing personal information and external information received by the server.

[0154] A "generative AI model" is an artificial intelligence model that performs data analysis based on a user's personal information and external information, and generates advice.

[0155] "Personalized advice" is advice that is individually customized based on a user's lifestyle and financial situation.

[0156] "Encryption" is a technique for converting data using a specific algorithm in order to transmit the data securely.

[0157] A "communications protocol" is a technology that defines the rules and procedures for sending and receiving data safely.

[0158] "Data analytics" is the process of using generative AI models to analyze a user's personal information and external information to extract meaningful information.

[0159] A "terminal" is a device used by a user, such as a smartphone or computer.

[0160] The "means for displaying advice" is a function for visually presenting to the user the advice that the terminal receives from the server.

[0161] The present invention is a system that combines personal information and external information to provide appropriate advice and support. A specific embodiment of this system will be described below.

[0162] Hardware and Software Configuration

[0163] Hardware:

[0164] Server: A high-performance computer system (e.g., a general-purpose server)

[0165] Device: The smartphone or computer used by the user

[0166] software:

[0167] Database Management System: Database software such as MySQL

[0168] Generative AI models: Artificial intelligence models such as OpenAI GPT-4

[0169] Communication Protocol: A secure communication protocol such as HTTPS

[0170] Data processing and calculation

[0171] Enter and submit your personal information:

[0172] The user uses the terminal to access the system's dedicated application or website and enters personal information such as attribute information (age, occupation, income, etc.), data from the household accounting application, and information from the portal site. The terminal encrypts the entered personal information and transmits it to the server using a secure communication protocol (e.g., HTTPS).

[0173] Data Retention:

[0174] The server stores the received personal information in a database management system (e.g. MySQL). When storing, checks are performed to ensure data integrity and security.

[0175] Collection of external information:

[0176] The server uses external APIs and web scraping technology to collect external information such as tax systems, asset management, real estate, financial products, and local life information. The collected information is stored in a database.

[0177] Data analysis and advice generation:

[0178] The server combines the stored personal information with external information and performs data analysis using a generative AI model (e.g., OpenAI GPT-4). Specifically, it analyzes the user's income and expenditure patterns and derives optimal asset management and savings methods. The server generates specific advice for the user based on the analysis results of the generative AI model.

[0179] Sending and viewing advice:

[0180] The server sends the generated advice to the device, using data encryption and secure communication protocols. The device displays the received advice to the user, who can then view the specific advice through an application or website.

[0181] Examples of concrete examples and prompts

[0182] Examples:

[0183] The user opens a dedicated application on their smartphone and enters their monthly income (300,000 yen) and expenses (250,000 yen). The device encrypts this information and sends it to the server using HTTPS. The server stores the received information in a MySQL database. The server then collects the latest tax information and asset management trends from an external API and stores them in the database.

[0184] The server uses OpenAI GPT-4 to analyze the user's income and spending patterns and generates advice such as "To reduce spending this month, it is effective to cut food expenses by 10%." The generated advice is encrypted again and sent to the terminal using HTTPS. The terminal displays the received advice to the user, and the user can check the specific ways to save money.

[0185] Example prompt:

[0186] "If a user's monthly income is 300,000 yen and expenses are 250,000 yen, what saving and investment methods would you suggest, taking into account the latest tax information and asset management trends?"

[0187] In this way, a system is realized in which the server, terminal, and user work together to provide personalized advice.

[0188] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0189] Step 1:

[0190] The user inputs personal information. The user uses the terminal to access the system's dedicated application or website and inputs personal information such as attribute information (age, occupation, income, etc.), data from a household accounting application, and information from a portal site. The input data is sent to the system through the terminal's input device (keyboard or touch screen).

[0191] Step 2:

[0192] The terminal sends the personal information entered by the user to the server. The terminal encrypts the personal information entered by the user and sends it to the server using a secure communication protocol (e.g. HTTPS). The input data is encrypted and sent to the server.

[0193] Step 3:

[0194] The server saves the personal information in a database. The server saves the received personal information in a database management system (e.g. MySQL). When saving, checks are performed to ensure data integrity and security. The input data is saved in the database and a consistency check is performed.

[0195] Step 4:

[0196] The server collects external information and stores it in a database. The server uses external APIs and web scraping technology to collect external information such as tax systems, asset management, real estate, financial products, and local lifestyle information. The collected information is stored in a database. External information is obtained through APIs and scraping technology and stored in a database.

[0197] Step 5:

[0198] The server performs data analysis using a generative AI model. The server combines the stored personal information with external information and performs data analysis using a generative AI model (e.g. OpenAI GPT-4). Specifically, it analyzes the user's income and expenditure patterns and determines optimal asset management and savings methods. Input data (personal information and external information) is input into the generative AI model, and the analysis results are output.

[0199] Step 6:

[0200] The server generates advice based on the analysis results. The server generates specific advice for the user based on the analysis results of the generative AI model. For example, it generates advice such as "To reduce expenses this month, it is effective to cut food expenses by 10%" or "It would be a good idea to invest surplus funds in stocks." The analysis results are output as advice.

[0201] Step 7:

[0202] The server transmits the generated advice to the terminal. The server transmits the generated advice to the terminal. When transmitting, data encryption and a secure communication protocol are used. The generated advice is encrypted and transmitted to the terminal.

[0203] Step 8:

[0204] The device displays the advice to the user. The device displays the received advice to the user. The user can check the specific advice through an application or website. The received advice is displayed on the device display.

[0205] (Application example 2)

[0206] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0207] Advice provided by traditional household accounting apps and financial planners is temporary and lacks ongoing support. In addition, there is no system that combines a user's personal information with external information to provide accurate advice, making it difficult for users to receive advice that is best suited to their lifestyle and asset situation. Furthermore, there is a lack of a centralized means of providing advice on the creation of complicated tax returns, asset management, tax-saving strategies, and ways to reduce living expenses.

[0208] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for providing a generative AI function to a household accounting application to make advice by a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and is similar to consulting a financial planner, not just temporarily, but continuously, and not temporarily, and is similar to consulting a financial planner, a means for realizing accurate advice and support by continuous learning of personal information (attributes, household accounting application, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local living information, etc.), a means for realizing automatic creation and support of complicated tax returns, etc., a means for combining the user's personal information and external information to advise on asset management, tax saving measures, and ways to save on living expenses, a means for calculating taxes on the user's income, a means for providing investment advice according to the user's asset situation, a means for reviewing the user's living expenses and proposing savings, and a means for generating a prompt sentence using a generative AI model. This allows the user to receive continuous and accurate advice.

[0209] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[0210] "Generative AI" is a system that uses artificial intelligence technology to analyze data and automatically generate new information and advice.

[0211] A financial planner is an expert who analyzes the financial situations of individuals and companies and provides advice on asset management and tax saving measures.

[0212] "Chat format" means that users communicate in real time via text messages.

[0213] "Personal information" refers to all data relating to individuals, such as user attribute information, data from household accounting apps, and My Number Portal information.

[0214] "External information" refers to data concerning the user's external environment, such as tax systems, asset management, real estate, financial products, and local living information.

[0215] "Continuous learning" is the process by which the system continually learns from user data and improves the accuracy of its advice.

[0216] A "tax return" is a document to be submitted to the tax office, etc., which lists income, expenses, asset status, etc.

[0217] "Asset management" refers to investment activities aimed at efficiently increasing users' assets.

[0218] "Tax avoidance strategies" refer to methods or means for legally reducing tax burdens.

[0219] "Saving on living expenses" refers to ways and means of reducing expenses in daily life.

[0220] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and generate new information and advice.

[0221] A "prompt" is an instruction to be input into a generative AI model, which serves as a trigger for generating specific information or advice.

[0222] The system for implementing this invention includes a server, a user terminal, and a generative AI model. The server collects personal information and external information of the user, and generates appropriate advice based on this data. The user terminal records the user's income and expenditure through a household accounting app, and communicates with the server to receive advice.

[0223] The server first obtains the user's personal information (attributes, data from the household accounting app, information from My Number Portal, etc.). It then collects external information (tax systems, asset management, real estate, financial products, local living information, etc.). This data is stored in a database within the server.

[0224] The server uses a generative AI model to analyze the user's personal information and external information, and generates advice on asset management, tax savings, ways to save on living expenses, etc. This generative AI model continuously learns from the user's data and improves the accuracy of its advice.

[0225] The user device receives advice from the server through the household accounting app and presents it to the user. The user can send questions to the server in chat format and receive answers in real time, allowing the user to receive continuous and accurate advice.

[0226] As a concrete example, consider a case where a user has an annual income of 6 million yen, annual living expenses of 3 million yen, and assets of 10 million yen. In this case, the server generates the following advice:

[0227] The annual tax is 1200000 yen.

[0228] Consider investing in stocks or real estate as a way to manage your assets.

[0229] Review your living expenses and try to save money.

[0230] Example of a prompt to be input to a generative AI model:

[0231] Please create a program that combines the user's personal information (attributes, household accounting app, My Number Portal, etc.) with external information (tax system, asset management, real estate, financial products, local living information, etc.) to give the user advice on optimal asset management, tax saving measures, ways to save on living expenses, etc. Please also include a concrete example where the user's annual income is 6 million yen, annual living expenses are 3 million yen, and assets are 10 million yen.

[0232] This system enables users to receive advice that is best suited to their lifestyle and asset situation, enabling them to effectively manage their assets, save on taxes, and reduce living expenses.

[0233] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0234] Step 1:

[0235] The user's device inputs the user's income and expenditure data through the household accounting app. This records the user's household financial situation. The input data includes the amount of income, expenditure items, and expenditure amounts. This data is sent from the user's device to the server.

[0236] Step 2:

[0237] The server receives the household data sent from the user's device and stores it in a database. The stored data is managed as the user's personal information (attributes, data from the household accounting app, My Number Portal information, etc.). This allows the user's household financial situation to be accumulated on the server.

[0238] Step 3:

[0239] The server collects external information (tax systems, asset management, real estate, financial products, local life information, etc.). The external information is obtained through API and stored in a database. This allows the latest external information to be accumulated on the server.

[0240] Step 4:

[0241] The server combines and analyzes the user's personal information and external information. Using a generative AI model, it generates advice based on the user's household situation. Specifically, this includes calculating taxes on the user's income, suggesting asset management, and ways to save on living expenses. The input data is the user's personal information and external information, and the output data is the generated advice.

[0242] Step 5:

[0243] The server transmits the generated advice to the user's device, which then presents the received advice to the user through the household accounting app, allowing the user to confirm and act on the advice.

[0244] Step 6:

[0245] Users send questions to the server through the home accounting app. The questions are entered in text format and sent to the server, allowing users to receive support in real time.

[0246] Step 7:

[0247] The server receives questions from users and generates answers in real time using a generative AI model. The input data is the user's question, and the output data is the generated answer. The generated answer is based on the user's household financial situation and external information.

[0248] Step 8:

[0249] The server sends the generated answer to the user's device, which then presents the received answer to the user through the household accounting app, allowing the user to receive accurate advice in real time.

[0250] In this way, users can receive continuous and accurate advice, enabling them to effectively manage their assets, save on taxes, and reduce living expenses.

[0251] Example 3

[0252] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0253] Conventional household accounting apps and systems that provide advice from financial planners have problems in that it takes a lot of time and effort for users to declare taxes, insurance, etc., and mistakes are likely to occur. In addition, the creation of tax returns is complicated, making it difficult for users to create tax returns accurately. Furthermore, there is also the problem that advice from financial planners is temporary and there is a lack of ongoing support.

[0254] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0255] In this invention, the server includes a means for automatically generating a tax return based on data input by the user to the household accounting application, a means for the terminal to send the input data to the server, a means for the server to receive the data and store it in a database, a means for the server to analyze the stored data and extract necessary information, a means for the server to input the extracted information to the generative AI model, a means for the generative AI model to automatically generate a tax return, a means for the server to output the generated tax return in PDF format, and a means for the user to download the PDF and submit it as a tax return. This allows the user to automate the creation of complicated tax returns and significantly reduce the effort required.

[0256] A "household accounting app" is software that allows users to input and manage household information such as income and expenses.

[0257] "Generative AI" is an artificial intelligence technology that automatically generates text and information based on input data.

[0258] A "financial planner" is a professional who provides financial planning and investment advice to individuals and businesses.

[0259] "Chat format" means that users communicate in real time via text messages.

[0260] "Personal information" is information that can be used to identify a specific individual, such as user attributes and household information.

[0261] "External information" refers to information obtained from external sources related to the user's household management and filing, such as tax systems, asset management, real estate, financial products, and local living information.

[0262] "Continuous learning" is the process by which a system continually learns new data and information to improve its accuracy and performance.

[0263] A "tax return" is a document required to declare taxes, insurance, etc.

[0264] A "terminal" is a device that a user uses to operate the household accounting app, including a smartphone or a PC.

[0265] A "server" is a computer system that receives, stores, analyzes, and runs generative AI models.

[0266] A "database" is a system for efficiently storing, managing, and searching data.

[0267] A "generative AI model" is an artificial intelligence model that automatically generates documents such as tax returns based on input data.

[0268] "PDF format" is an abbreviation for Portable Document Format, a file format for electronically storing and displaying documents.

[0269] This invention is a system that automatically generates tax returns based on data entered by a user into a household accounting application. The purpose of this system is to reduce the user's workload and prevent mistakes. A specific embodiment of this system will be described below.

[0270] First, the user uses the household accounting app to input data such as income, expenses, and deductions. For example, the user enters information such as income of 5 million yen, medical expenses of 100,000 yen, and mortgage deduction of 200,000 yen. This household accounting app works on devices such as smartphones and computers.

[0271] The terminal then transmits the entered data to the server, using the HTTPS protocol to ensure data security. The server receives the data sent from the terminal and stores it in a relational database such as MySQL or PostgreSQL.

[0272] The server uses Python scripts to analyze the data stored in the database. During the analysis, it extracts necessary information such as income, medical expenses, mortgage deductions, etc. The extracted information is then fed into a generative AI model (e.g. GPT-4).

[0273] The prompt for input to the generative AI model is as follows:

[0274] The user's income is 5 million yen, medical expenses are 100,000 yen, and the mortgage deduction is 200,000 yen. Please fill out your year-end tax return based on this information.

[0275] The generative AI model automatically generates the year-end tax return based on this prompt. The generated return is returned to the server in text format. The server converts the returned text to PDF format. For example, Python's ReportLab library is used for this conversion.

[0276] Finally, the user downloads the generated PDF form from the server, which can then be printed and submitted to the appropriate authorities.

[0277] This system enables users to automate the creation of complicated tax returns, significantly reducing the amount of work required. In addition, the use of generative AI models improves the accuracy of tax returns. The flow of the specific process in Example 3 is described with reference to FIG. 15.

[0278] Step 1:

[0279] The user enters data into a household accounting app.

[0280] The user uses the household accounting app to input data such as income, expenses, and deductions. For example, the user may input information such as income of 5 million yen, medical expenses of 100,000 yen, and mortgage deduction of 200,000 yen. The input data is temporarily stored in the household accounting app.

[0281] Step 2:

[0282] The terminal transmits the input data to the server.

[0283] The terminal (smartphone or PC) sends the data entered by the user to the server using the HTTPS protocol. The data sent includes information such as income, medical expenses, and mortgage deductions. The input data is encrypted and sent to the server through a secure communication channel.

[0284] Step 3:

[0285] The server receives the data and stores it in a database.

[0286] The server receives the data sent from the terminal. The received data is stored in a relational database such as MySQL or PostgreSQL. The data is organized and stored for each user in the database.

[0287] Step 4:

[0288] The server analyzes the stored data and extracts the necessary information.

[0289] The server uses Python scripts to analyze the data stored in the database. During the analysis, it extracts necessary information such as income, medical expenses, and mortgage deductions. Based on the input data (income of 5 million yen, medical expenses of 100,000 yen, and mortgage deduction of 200,000 yen), the analyzed information is extracted.

[0290] Step 5:

[0291] The server inputs the extracted information into a generative AI model.

[0292] The server inputs the extracted information into a generative AI model (e.g. GPT-4) with the following prompt:

[0293] The user's income is 5 million yen, medical expenses are 100,000 yen, and the mortgage deduction is 200,000 yen. Please fill out your year-end tax return based on this information.

[0294] Step 6:

[0295] A generative AI model automatically generates tax returns.

[0296] The generative AI model automatically generates the year-end tax return based on the input prompt text. The generated return is returned to the server in text format. The generative AI model analyzes the input data and generates the return in the appropriate format.

[0297] Step 7:

[0298] The server outputs the generated declaration in PDF format.

[0299] The server converts the text-based tax return returned by the generative AI model into a PDF file, for example using the Python ReportLab library, and converts the text data into a PDF file that users can download.

[0300] Step 8:

[0301] The user downloads the PDF and submits it as a tax return.

[0302] The user downloads the generated PDF tax return from the server. The downloaded PDF can be printed and submitted to the necessary authorities. The user can also check the contents of the tax return and make corrections if necessary.

[0303] (Application example 3)

[0304] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0305] In modern society, filing tax and insurance returns is extremely cumbersome, and many people spend a lot of time and effort preparing tax returns. In addition, preparing tax returns requires specialized knowledge and is prone to errors. Furthermore, consulting with an expert is often expensive, which is a heavy burden on ordinary people. There is a need for a system that can solve these problems and allow anyone to easily prepare accurate tax returns.

[0306] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means. In this invention, the server includes a means for providing a generative AI function to a household accounting application to make expert advice "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and is not temporary but continuous, as if consulting an expert, a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting application, portal site, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for realizing automatic creation and support of complicated tax returns, etc., a means for analyzing expenditure data and automatically generating tax and insurance returns, a means for checking whether there are any errors in the generated returns, and a means for providing support for electronically submitting the generated returns. This allows the user to create accurate returns without much effort and carry out the tax return procedure while receiving advice from an expert.

[0307] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[0308] "Generative AI" is a system that uses artificial intelligence technology to automatically generate text and information based on user input data.

[0309] An "expert" is a person who has advanced knowledge and experience in a particular field and can provide users with appropriate advice.

[0310] "Chat style" refers to a method of communication between the user and the system in real time via text messages.

[0311] "Personal information" refers to all data related to individuals, such as user attributes, data from household accounting apps, and information from portal sites.

[0312] "External information" refers to data obtained from external sources related to the user's household management and filing, such as tax systems, asset management, real estate, financial products, and local living information.

[0313] "Continuous learning" is the process by which the system continually learns from user data and external information in order to provide more accurate advice and support.

[0314] A "tax return" is a document required to declare taxes, insurance, etc.

[0315] "Expense data" refers to information regarding daily expenses that a user enters into the household accounting app.

[0316] "Error checking" is the process of checking whether the generated tax return is error-free.

[0317] "Electronic filing" refers to the filing of a completed tax return online via the Internet.

[0318] The system for implementing this invention includes a household accounting app, a generative AI, an expert advice function, a chat-style communication function, a personal information and external information management function, a continuous learning function, an automatic tax return generation function, an error checking function, and an electronic submission support function.

[0319] Hardware and Software Used

[0320] Hardware: Smartphone

[0321] Software: household accounting apps, electronic payment service apps, generative AI models (e.g. GPT-4)

[0322] Data processing and calculation flow

[0323] 1. Data Acquisition:

[0324] The server obtains the user's expenditure data from the household accounting app.

[0325] API used: Data acquisition API for household accounting app

[0326] Example: GET / api / v1 / expenses

[0327] 2. Data Analysis:

[0328] The server analyzes the acquired expenditure data and extracts information necessary for tax and insurance declarations.

[0329] Libraries used: pandas, numpy

[0330] Example: pandas.DataFrame(expenses).groupby('category').sum()

[0331] 3. Generate tax return:

[0332] The server automatically generates tax returns using a generative AI model based on the analysis results.

[0333] Model used: GPT-4

[0334] Example prompt:

[0335] Generate a tax return based on the user's expenditure data. Below is the user's expenditure data.

[0336] Food expenses: 50,000 yen

[0337] Transportation fee: 10,000 yen

[0338] Medical expenses: 20,000 yen

[0339] Other: 15,000 yen

[0340] 4. Error checking:

[0341] The server checks the generated return for errors.

[0342] Libraries used: regex, jsonschema

[0343] Example: jsonschema.validate(generated_form, schema)

[0344] 5. Submission Support:

[0345] The server provides support for electronic filing of generated returns.

[0346] API to be used: Electronic reporting system submission API

[0347] Example: POST / api / v1 / submit_form

[0348] Examples

[0349] When a user enters their daily expenses into the household accounting app, the data is sent to a server. The server analyzes the acquired expenditure data and extracts the information required for tax and insurance declarations. It then uses a generative AI model to automatically generate a declaration form and checks for errors. Finally, it provides support for electronically submitting the generated declaration form.

[0350] This system allows users to easily prepare accurate tax returns and complete the tax return procedures with the help of expert advice.

[0351] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0352] Step 1:

[0353] The server obtains the user's expenditure data from the household accounting app. The expenditure data entered by the user into the household accounting app is the input. The server obtains the expenditure data using the data acquisition API of the household accounting app. Specifically, the server sends an API request such as GET / api / v1 / expenses and receives the expenditure data. The output is the obtained expenditure data.

[0354] Step 2:

[0355] The server analyzes the acquired expense data and extracts information necessary for tax and insurance declarations. The input is the expense data acquired in step 1. The server aggregates the expense data by category using data analysis libraries such as pandas and numpy. Specifically, it performs operations such as pandas.DataFrame(expenses).groupby('category').sum(). The output is the expense data aggregated by category.

[0356] Step 3:

[0357] The server automatically generates a tax return using a generative AI model based on the analysis results. The input is the expenditure data collected in step 2. The server inputs a prompt sentence into the generative AI model (e.g., GPT-4) to generate the tax return. Specifically, the following prompt sentence is used:

[0358] Generate a tax return based on the user's expenditure data. Below is the user's expenditure data.

[0359] Food expenses: 50,000 yen

[0360] Transportation fee: 10,000 yen

[0361] Medical expenses: 20,000 yen

[0362] Other: 15,000 yen

[0363] The output is the generated tax return.

[0364] Step 4:

[0365] The server checks the generated form for errors. The input is the form generated in step 3. The server validates the form for errors in format and content using libraries such as regex and jsonschema. Specifically, it performs operations like jsonschema.validate(generated_form, schema). The output is the result of the error check.

[0366] Step 5:

[0367] The server supports the electronic submission of the generated tax return. The input is the tax return that passed the error check in step 4. The server submits the tax return online using the submission API of the electronic tax return system. Specifically, it sends an API request such as POST / api / v1 / submit_form. The output is the tax return submission result.

[0368] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[0369] "Example 1"

[0370] One embodiment of the present invention is a system that combines an emotion engine that recognizes the user's emotions. In this system, when a user inputs their own income and expenditure information into a household accounting app, a generative AI analyzes the user's input information and grasps the user's household financial situation. The emotion engine then recognizes the user's emotions, and the generative AI automatically generates FP advice based on those emotions. For example, if a user feels that they are in a financially difficult situation, the emotion engine recognizes those emotions, and the generative AI generates specific advice on saving based on that information.

[0371] "Example 2"

[0372] In another embodiment, the emotion engine adjusts the content and delivery of advice based on the user's emotion. In this system, if the user is feeling stressed, the emotion engine recognizes the emotion and the generative AI uses that information to generate advice to reduce stress. In addition, if the user is feeling joy, the emotion engine recognizes the emotion and the generative AI uses that information to generate advice to maintain joy.

[0373] "Example 3"

[0374] As yet another embodiment, there is a system in which an emotion engine learns changes in a user's emotions and successively improves the content of advice and the method of providing it based on the results of that learning. In this system, the emotion engine learns changes in a user's emotions and feeds back the results of that learning to the generative AI. The generative AI successively improves the content of advice and the method of providing it based on that feedback. For example, as a result of learning changes in emotions when a user faces financial difficulties, the generative AI uses that information to generate more specific and practical advice.

[0375] The process flow of each embodiment will be described below.

[0376] "Example 1"

[0377] Step 1: The user enters their income and expenditure information into the household accounting app.

[0378] Step 2: The generative AI analyzes the information entered by the user and understands the user's financial situation.

[0379] Step 3: The emotion engine recognizes the user's emotion.

[0380] Step 4: Based on those emotions, the generative AI automatically generates FP advice.

[0381] "Example 2"

[0382] Step 1: If the user is stressed, the emotion engine recognizes that emotion.

[0383] Step 2: The generative AI uses that information to generate advice to reduce stress.

[0384] Step 3: If the user is feeling happy, the emotion engine recognizes that emotion.

[0385] Step 4: The generative AI uses that information to generate advice on how to maintain that joy.

[0386] "Example 3"

[0387] Step 1: The emotion engine learns the user's emotional changes.

[0388] Step 2: The learning results are fed back to the generative AI.

[0389] Step 3: The generative AI uses the feedback to continually improve the content and delivery of advice.

[0390] Example 1

[0391] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal".

[0392] With conventional household accounting apps, even if users input their income and expenditure information, it is difficult to receive specific advice based on that information. Also, consulting a financial planner takes time and money, making it difficult to receive ongoing support. Furthermore, advice is not provided that takes into account the user's emotions, so there is a problem in that users cannot receive appropriate advice based on their situation.

[0393] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for the user to input household accounting data and the terminal to transmit the data to the server, a means for the server to transmit a prompt to the generative AI model and recognize the user's emotions using an emotion engine, and a means for the server to receive advice from the generative AI model, transmit it to the terminal, and display it to the user. This allows the user to receive specific advice based on income and expenditure information in real time, and to receive continuous support. In addition, since advice is provided that takes the user's emotions into consideration, more appropriate advice can be obtained.

[0394] A "household accounting app" is software that allows users to enter income and expenditure information and manage their household finances.

[0395] "Generative AI" is an artificial intelligence technology that generates advice and information in natural language based on data input by the user.

[0396] A financial planner is an expert who analyzes the financial situation of individuals and companies and suggests optimal asset management and savings methods.

[0397] "Chat style" refers to an interface in which the user and the system exchange information in a dialogue format.

[0398] "Personal information" is information that can identify a specific individual, such as user attributes, household accounting data, and portal site information.

[0399] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0400] "Continuous learning" is a function that enables the system to continually learn from user data and external information in order to provide more accurate advice.

[0401] An "emotion engine" is software that recognizes emotions from user input data and generates appropriate advice based on those emotions.

[0402] A "prompt" is an input sentence that inputs specific information or a question to a generative AI so that it can generate an appropriate response.

[0403] A "terminal" is a device through which a user inputs household accounting data and interacts with the system. This includes smartphones, tablets, and PCs.

[0404] A "server" is a computer system that stores and processes data and uses generative AI models and emotion engines to provide advice to users.

[0405] This invention is a system that adds generative AI functionality to a household accounting app and automatically generates advice from a financial planner. This system uses a combination of a generative AI model and an emotion engine to provide appropriate advice based on household accounting data entered by the user.

[0406] Hardware and Software Used

[0407] Server: Stores and processes data. Specifically, it uses cloud services (e.g., Amazon Web Services, Google (registered trademark) Cloud Platform).

[0408] Terminal: The device through which the user enters household accounting data. This includes smartphones, tablets, and PCs.

[0409] Generative AI model: Uses a natural language generation model (e.g. GPT-4).

[0410] Emotion engine: Uses software to recognize user emotions (e.g., Microsoft® Azure® Emotion API).

[0411] Data processing and data calculation

[0412] 1. User input: The user inputs income and expenditure information into the household accounting app. For example, the user enters, "This month's income is 200,000 yen, and expenses are 250,000 yen."

[0413] 2. Data transmission: The terminal transmits the input data to the server. Specifically, the data is transmitted using an HTTP request.

[0414] 3. Data Analysis: The server sends a prompt to the generative AI model to analyze the user's income and expenditure information. For example, it sends a prompt saying, "The user's income is 200,000 yen and his expenditure is 250,000 yen. Please generate advice based on this."

[0415] 4. Emotion recognition: The server uses the emotion engine to recognize the user's emotion. For example, if the user feels "troubled," the emotion engine recognizes that emotion.

[0416] 5. Advice generation: The server receives advice from the generative AI model. For example, it generates advice such as, "Your expenses are higher than your income this month. We recommend that you review your food expenses to save money."

[0417] 6. Providing advice: The server sends the generated advice to the terminal and displays it to the user. Specifically, the server sends data using an HTTP response.

[0418] Examples

[0419] User input: The user enters, "This month's income is 200,000 yen and expenses are 250,000 yen."

[0420] Emotion recognition: The emotion engine recognizes the emotion of "distress."

[0421] Generated advice: The generative AI model generates advice such as, "Your expenses are exceeding your income this month. To save money, we recommend that you review your food expenses."

[0422] Examples of prompt statements

[0423] "A user has entered their income and expenditure information. Their income is 200,000 yen and their expenses are 250,000 yen. The user feels they are in financial difficulty. Based on this, please generate specific advice on how to save money."

[0424] In this way, the system combines an emotion engine and a generative AI model to provide appropriate advice based on the information the user enters into the household accounting app.

[0425] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0426] Step 1:

[0427] The user inputs household accounting data. The user uses a device such as a smartphone or PC to input income and expenditure information into the household accounting app. For example, the user might input "This month's income is 200,000 yen, and expenses are 250,000 yen." The input data includes income and expenditure information.

[0428] Step 2:

[0429] The terminal sends the input data to the server. The terminal sends the balance information entered by the user to the server using an HTTP request. The input is the user's balance information, and the output is the data sent to the server.

[0430] Step 3:

[0431] The server receives the data and sends a prompt to the generative AI model. The server analyzes the received income and expenditure information and sends a prompt to the generative AI model. For example, it sends a prompt saying, "The user's income is 200,000 yen and his expenditure is 250,000 yen. Please generate advice based on this." The input is the income and expenditure information, and the output is the prompt sent to the generative AI model.

[0432] Step 4:

[0433] The server recognizes the user's emotions using the emotion engine. The server recognizes emotions from the user's input data using the emotion engine. For example, if the user feels "in trouble," the emotion engine recognizes that emotion. The input is the user's financial information and emotion information, and the output is the recognized emotion.

[0434] Step 5:

[0435] The server receives advice from the generative AI model. The server receives the advice from the generative AI model and generates advice based on the analysis results and the recognition results of the emotion engine. For example, the server receives advice such as "This month your expenses are higher than your income. To save money, we recommend that you review your food expenses." The input is the response from the generative AI model, and the output is the generated advice.

[0436] Step 6:

[0437] The server sends advice to the terminal. The server sends the generated advice to the terminal using an HTTP response. The input is the generated advice, and the output is the data sent to the terminal.

[0438] Step 7:

[0439] The terminal displays advice to the user. The terminal displays the advice received to the user. For example, it displays in chat format, "This month your expenses exceed your income. To save money, we recommend that you review your food expenses." The input is the advice received from the server, and the output is the advice displayed to the user.

[0440] In this way, the system provides appropriate advice to the user by performing specific actions at each step.

[0441] (Application example 1)

[0442] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0443] Conventional household accounting apps only manage income and expenditures based on data entered by the user, and are unable to provide specific advice based on the user's emotions or circumstances. Additionally, there were no systems that could link with electronic payment services to automatically record spending history, recognize the user's emotions, and provide appropriate advice. This made it difficult for users to accurately grasp their own financial situation and take appropriate measures.

[0444] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for providing a generative AI function to a household accounting application, making advice by a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and is similar to consulting a financial planner, not just temporarily, but continuously, and in an easy-to-understand manner, as if consulting a financial planner, a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting application, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for realizing automatic creation and support of complicated tax returns, etc., and a means for analyzing a user's spending history in an electronic payment service, recognizing the user's emotions using an emotion engine, and a generative AI providing advice by a financial planner. This allows the user to accurately grasp his or her own financial situation and receive appropriate advice according to his or her emotions.

[0445] A "household accounting app" is software that allows users to enter income and expenditure information and manage their household finances.

[0446] "Generative AI" is an artificial intelligence technology that automatically generates advice and information based on user input data.

[0447] "FP" stands for financial planner, a professional who provides appropriate advice based on an individual's financial situation.

[0448] "Chat style" refers to an interface style in which a user and a system exchange information in a dialogue format.

[0449] "Personal information" refers to user attribute information, data entered into a household accounting app, My Number Portal, etc.

[0450] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0451] "Continuous learning" is a feature that allows the system to continually learn from user data and provide more accurate advice.

[0452] "Automatic creation of complicated tax returns, etc." is a function that automatically creates tax returns and documents that users need to submit.

[0453] An "electronic payment service" is a service that enables users to make payments online.

[0454] "Spending History" means a record of payments made by a User.

[0455] An "emotion engine" is a technology for analyzing and recognizing user emotions.

[0456] "Means for providing advice" refers to methods or technologies for providing appropriate advice to users.

[0457] The system for implementing this invention is a combination of a household accounting application, a generative AI, an emotion engine, and an electronic payment service. A specific embodiment is described below.

[0458] System Configuration

[0459] 1. Household accounting app:

[0460] Hardware: Smartphone

[0461] Software: Household accounting application

[0462] Function: Users can enter income and expenditure information and manage their household finances.

[0463] 2. Generative AI:

[0464] Hardware: Server

[0465] Software: Generative AI models (e.g. GPT-4)

[0466] What it does: Automatically generate advice based on user-entered data.

[0467] 3. Emotion Engine:

[0468] Hardware: Smartphone

[0469] Software: Emotion recognition engine (e.g. Affectiva SDK)

[0470] Function: Analyze and recognize user emotions.

[0471] 4. Electronic payment services:

[0472] Hardware: Smartphone

[0473] Software: Electronic payment application

[0474] Function: User makes online payments.

[0475] Processing flow

[0476] 1. Data collection:

[0477] Every time a user makes an electronic payment, the spending history is automatically recorded in the household accounting app.

[0478] 2. Emotion recognition:

[0479] The emotion engine analyzes users' spending history and behavioral patterns to recognize their emotions.

[0480] 3. Advice Generation:

[0481] The generative AI generates FP advice based on the results of the emotion engine.

[0482] 4. Advice provided:

[0483] Provide advice to users in chat format.

[0484] Examples

[0485] For example, if a user is stressed about their increasing monthly expenses, the emotion engine will recognize that emotion and the generative AI will offer advice like:

[0486] "It seems like your expenses have been increasing lately. You may be feeling stressed, but why not start by reviewing the amount of coffee you spend each day? You could save about 5,000 yen a month."

[0487] Examples of prompt statements

[0488] User's spending history: [Expense data]

[0489] User sentiment: [emotion data]

[0490] Generate advice.

[0491] This prompt sentence is used to have the generative AI model generate advice.

[0492] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0493] Step 1:

[0494] Every time a user makes an electronic payment, the expenditure history is automatically recorded in the household accounting app. The input is expenditure data from the electronic payment service, and the output is the expenditure history stored in the household accounting app. In concrete terms, the electronic payment service sends expenditure information to the household accounting app, and the household accounting app stores the information in a database.

[0495] Step 2:

[0496] The device sends the expenditure history recorded in the household accounting app to the emotion engine. The input is the expenditure history stored in the household accounting app, and the output is the expenditure data sent to the emotion engine. In concrete terms, the household accounting app sends the expenditure history to the API of the emotion engine.

[0497] Step 3:

[0498] The emotion engine analyzes spending history and behavioral patterns to recognize user emotions. The input is spending history data, and the output is the recognized user emotion data. Specifically, the emotion engine analyzes spending history and identifies emotions such as stress and anxiety.

[0499] Step 4:

[0500] The server sends a prompt to the generative AI based on the results of the emotion engine. The input is emotion data and expenditure history data, and the output is the prompt to be sent to the generative AI. In concrete terms, the server combines emotion data and expenditure history data to generate a prompt and sends it to the generative AI.

[0501] Step 5:

[0502] The generative AI generates advice using FP based on the prompt sentence. The input is the prompt sentence, and the output is the generated advice. In concrete terms, the generative AI analyzes the prompt sentence and generates appropriate advice.

[0503] Step 6:

[0504] The server provides the generated advice to the user in a chat format. The input is the generated advice, and the output is a chat message provided to the user. In concrete terms, the server sends the generated advice to a chat app and displays it to the user.

[0505] Example 2

[0506] Next, a second embodiment of the second embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0507] In conventional household management systems, it was time-consuming and expensive for users to consult with a financial planner, and they often only received temporary advice. It was also difficult to provide advice that took into account the user's emotional state, and there was a lack of personalized support tailored to each individual's lifestyle and emotions. Furthermore, the hassle of creating complicated tax returns and obtaining external information placed a burden on users.

[0508] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for providing a function of a generation AI model to a household management application, making advice by a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in an easy-to-understand and interactive format as if consulting a financial planner, not temporarily but continuously, and in an easy-to-understand manner, as if consulting a financial planner, a means for combining personal information (attributes, household management application, government portal, etc.) with external information (tax system, asset management, real estate, financial products, local life information, etc.) to realize accurate advice and support, a means for analyzing the user's emotion data using an emotion analysis engine, and a means for the generation AI model to generate advice based on the information, and a means for realizing automatic creation and support of complicated tax returns, etc. This allows the user to receive continuous and personalized advice without spending time and money, and to obtain appropriate support according to the emotional state. In addition, the automatic acquisition of external information and automatic creation of tax returns can reduce the burden on the user.

[0509] A "household management application" is software that allows users to manage their income and expenses and grasp the state of their household finances.

[0510] A "generative AI model" is an artificial intelligence algorithm that generates advice and information in natural language based on user input data.

[0511] A "financial planner" is a professional who provides financial planning and investment advice to individuals and businesses.

[0512] "Interactive" means that the user and the system exchange questions and answers in real time.

[0513] "Personal information" refers to all information about users, such as user attribute information, data from household management applications, and data from government portals.

[0514] "External information" refers to information obtained from external sources that is used in combination with the user's personal information, such as information on tax systems, asset management, real estate, financial products, and local living information.

[0515] An "emotion analysis engine" is software that analyzes a user's emotional state and provides appropriate advice based on the results.

[0516] "Returns" means any tax returns or other official reports that you are required to submit.

[0517] "Automated generation" is the process by which a system automatically generates documents or reports based on user-entered data or external information.

[0518] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0519] This invention is a system that combines a user's personal information with external information to provide appropriate advice and support. Furthermore, it is possible to adjust the content and method of providing advice based on the user's emotions using a sentiment analysis engine. This system is implemented using the following hardware and software.

[0520] Hardware and Software Used

[0521] Server: Processes and stores data. For example, it uses a server of a cloud service provider (such as AWS (registered trademark) or Google Cloud Platform).

[0522] Terminal: A device through which a user accesses the system, such as a smartphone or personal computer.

[0523] Generative AI models: Generate advice based on user input data. For example, natural language processing models (such as GPT-4).

[0524] Sentiment analysis engine: Analyze user sentiment. For example, sentiment analysis API (such as Microsoft Azure's Emotion API).

[0525] Data processing and calculation

[0526] 1. Collection of User's Personal Information:

[0527] User: Uses a terminal to log in to the system and enter personal information, such as age, occupation, income, expenses, etc.

[0528] Terminal: Sends personal information entered by the user to the server.

[0529] Server: Stores the received personal information in a database.

[0530] 2. Obtaining external information:

[0531] Server: Uses external APIs to obtain the latest information on tax systems, asset management, real estate, financial products, local lifestyle information, etc.

[0532] Server: The external information obtained is stored in an internal database and associated with the user's personal information.

[0533] 3. Emotion data analysis:

[0534] User: Answers emotional questions while using the system, for example, "How are you feeling today?"

[0535] Terminal: Sends the user's answer to the server.

[0536] Server: Analyze user sentiment data using the sentiment analysis engine.

[0537] 4. Generate advice:

[0538] Server: Uses a generative AI model to generate advice based on the user's personal information, external information, and emotional data.

[0539] Server: Customize the generated advice for each user.

[0540] 5. Providing advice:

[0541] Server: Sends the generated advice to the user's device.

[0542] Terminal: Display received advice to the user.

[0543] User: View and act on advice via terminal.

[0544] Examples

[0545] Example prompt:

[0546] User demographic information: 30 years old, single, annual income of 5 million yen

[0547] Data from household accounting app: Monthly expenditure is 300,000 yen

[0548] My Number Portal data: Health insurance premiums, pension information

[0549] External information: Latest tax reforms, asset management trends

[0550] Emotional data: High stress levels

[0551] An example of the advice generated:

[0552] We recommend that you review your current expenses and increase your monthly savings. In particular, reducing food and entertainment expenses is effective. In addition, the latest tax reform allows certain investment trusts to receive tax benefits, so please consider them as part of your asset management. To reduce stress, we recommend that you take up a relaxing hobby on the weekends.

[0553] In this way, the system provides personalized advice tailored to the user's lifestyle and emotions.

[0554] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0555] Step 1: Entering user details

[0556] User: Uses a terminal to log in to the system and enter personal information, such as age, occupation, income, expenses, etc.

[0557] Terminal: Sends personal information entered by the user to the server.

[0558] Server: Stores the received personal information in a database.

[0559] Specific behavior:

[0560] Users open the app on their smartphone and enter their age and occupation on the profile screen.

[0561] The terminal transmits the input data to the server in real time.

[0562] The server saves the following information in the database: "User ID: 12345, Age: 30, Occupation: Engineer, Income: 5 million yen."

[0563] Input: User's personal information (age, occupation, income, expenses)

[0564] Output: Personal information stored in a database

[0565] Step 2: Obtaining external information

[0566] Server: Uses external APIs to obtain the latest information on tax systems, asset management, real estate, financial products, local lifestyle information, etc.

[0567] Server: The external information obtained is stored in an internal database and associated with the user's personal information.

[0568] Specific behavior:

[0569] The server periodically sends a request to an external API (e.g. a government tax information API).

[0570] Analyze the data returned from the external API and store the latest tax reform information in a database.

[0571] The server associates the user's income information with up-to-date tax information.

[0572] Input: Information obtained from external API (tax system, asset management, real estate, financial products, local living information)

[0573] Output: External information stored in a database

[0574] Step 3: Analyze the sentiment data

[0575] User: Answers emotional questions while using the system, for example, "How are you feeling today?"

[0576] Terminal: Sends the user's answer to the server.

[0577] Server: Analyze user sentiment data using the sentiment analysis engine.

[0578] Specific behavior:

[0579] The user answers a question in the app by saying "I am stressed."

[0580] The terminal sends this response to the server.

[0581] The server uses a sentiment analysis engine to obtain the analysis result "Stress level: High".

[0582] Input: User's emotional response

[0583] Output: Analyzed emotion data (e.g. stress level)

[0584] Step 4: Generate Advice

[0585] Server: Uses a generative AI model to generate advice based on the user's personal information, external information, and emotional data.

[0586] Server: Customize the generated advice for each user.

[0587] Specific behavior:

[0588] The server sends a prompt to the generative AI model (e.g., GPT-4): "User attribute information: 30 years old, single, annual income of 5 million yen. Emotional data: High stress level. External information: Latest tax reform."

[0589] The generative AI model generates the following advice: "We recommend that you review your current expenses and increase your monthly savings. Reducing food and entertainment expenses would be particularly effective. In addition, the latest tax reforms have made it possible for certain investment trusts to receive tax benefits, so please consider this as part of your asset management. To reduce stress, we recommend that you take up a relaxing hobby on the weekends."

[0590] Input: User personal information, external information, emotional data

[0591] Output: The generated advice.

[0592] Step 5: Providing advice

[0593] Server: Sends the generated advice to the user's device.

[0594] Terminal: Display received advice to the user.

[0595] User: View and act on advice via terminal.

[0596] Specific behavior:

[0597] The server sends the generated advice to the user's smartphone.

[0598] The device will display a message within the app saying, "We encourage you to review your current spending and increase your monthly savings..."

[0599] Users read the advice and take action to actually review their spending.

[0600] Input: Generated advice

[0601] Output: Advice displayed to the user

[0602] In this way, the system provides personalized advice tailored to the user's lifestyle and emotions.

[0603] (Application example 2)

[0604] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0605] In conventional household management applications, it was often time-consuming and expensive for users to consult with a financial planner, and the advice given was often only temporary. It was also difficult to provide personalized advice based on the user's emotions and lifestyle, which made it difficult to increase user satisfaction. Furthermore, the creation of complicated tax return forms and support was time-consuming and a burden on users.

[0606] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0607] In this invention, the server includes a means for providing a function of a generative AI model to a household management application, making advice from a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and that is similar to consulting a financial planner, not just temporarily, but continuously, not temporarily, and that realizes accurate advice and support by continuously learning about personal information (attributes, household management application, government portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically creating and supporting complicated tax returns, etc., a means for recognizing the user's emotions using an emotion engine and providing personalized advice based on the information by the generative AI model, and a means for adjusting the content and method of providing the advice based on the user's emotions. This allows the user to receive continuous and personalized advice while saving time and money.

[0608] A "household management application" is software that enables users to manage household information such as income, expenses, assets, and liabilities.

[0609] A "generative AI model" is an algorithm that uses artificial intelligence to automatically generate advice and information from data.

[0610] A "financial planner" is a professional who provides financial planning and asset management advice to individuals and businesses.

[0611] "Chat format" refers to real-time communication using text messages.

[0612] "Personal information" is information relating to an individual, such as user attributes, data from a household management application, or information from a government portal.

[0613] "External information" refers to information other than personal information, such as tax systems, asset management, real estate, financial products, and local living information.

[0614] "Continuous learning" is the process by which the system constantly learns from new data and improves the accuracy of its advice.

[0615] An "emotion engine" is a technology that recognizes the user's emotions and provides appropriate advice based on that information.

[0616] "Personalized advice" is advice that is customized to a user's individual situation and emotions.

[0617] A "tax return" is a document required for tax and other legal procedures.

[0618] The system for implementing the present invention includes a household management application, a generative AI model, an emotion engine, an external information acquisition module, and a chat interface. The following describes each component in detail and how they work together.

[0619] Household management application

[0620] Users install a household management application on their smartphones. The application provides functions for managing household information such as the user's income, expenses, assets, and liabilities. Users can input their daily income and expenditures and grasp the status of their household finances in real time.

[0621] Generative AI Models

[0622] The server uses a generative AI model to combine the user's household information with external information to generate personalized advice. This generative AI model is implemented in a programming language such as Python and provides optimal advice based on the user's household situation.

[0623] Emotion Engine

[0624] The emotion engine is a technology for recognizing emotions from user input and voice. The server uses the emotion engine to analyze the user's emotions and provides that information to the generative AI model, which can then tailor the content and delivery of advice based on the user's emotions.

[0625] External information acquisition module

[0626] The server uses an external information acquisition module to collect external information such as tax systems, asset management, real estate, financial products, and local living information. This information is acquired through an API and provided to the generative AI model.

[0627] Chat Interface

[0628] The user can receive advice to consult with a financial planner through a chat interface within the home finance management application. The server generates answers to the user's questions in real time and provides them in chat format.

[0629] Examples

[0630] For example, if a user types, "I've been feeling a bit tight on finances lately," the emotion engine will recognize "stress," and the generative AI model will provide advice on "how to review your spending and save money."

[0631] Examples of prompt statements

[0632] A user has an income of 5 million yen, expenses of 3 million yen, assets of 10 million yen, and liabilities of 2 million yen. Recently, he has been feeling a bit tight on finances. What advice would you give to a user who is feeling stressed?

[0633] In this way, a system can be created that provides personalized advice tailored to the user's emotions and lifestyle.

[0634] The flow of the specific process in the application example 2 will be described with reference to FIG.

[0635] Step 1:

[0636] A user installs a household management application on their smartphone and inputs household information such as income, expenses, assets, and liabilities. The input data is managed within the application and sent to the server. An example of input data is income of 5 million yen, expenses of 3 million yen, assets of 10 million yen, and liabilities of 2 million yen.

[0637] Step 2:

[0638] The server uses an external information acquisition module to collect external information such as tax systems, asset management, real estate, financial products, and local life information. The collected external information is obtained through an API and provided to the generative AI model. For example, the tax rate is 20%, and information on stocks, bonds, and real estate as investment options is included.

[0639] Step 3:

[0640] A user inputs a question or request for advice through a chat interface in the household finance management application. For example, the user inputs, "I've been feeling that my household finances are tight lately." This input data is sent to the server.

[0641] Step 4:

[0642] The server uses an emotion engine to recognize emotions from user input. For example, it recognizes "stress" from the input "I've been feeling that my finances are tight lately." The emotion engine performs text analysis and provides emotion data to the generative AI model.

[0643] Step 5:

[0644] The server uses a generative AI model to generate personalized advice by combining the user's household information, external information, and emotion data. For example, based on income of 5 million yen, expenses of 3 million yen, assets of 10 million yen, liabilities of 2 million yen, a tax rate of 20%, investment options, and the emotion "stress," the server generates advice on "how to review expenses and save money."

[0645] Step 6:

[0646] The server provides the generated advice to the user through a chat interface. The user can receive the advice in real time. For example, the advice may be, "To review your spending and save money, first consider ways to reduce your fixed expenses."

[0647] In this way, a system can be created that provides personalized advice tailored to the user's emotions and lifestyle.

[0648] Example 3

[0649] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0650] In conventional household accounting apps and systems that provide advice from financial planners, users have to manually input data and receive advice, which takes a lot of time and effort. In addition, when preparing tax and insurance returns, users must manually organize information and prepare the returns, which is prone to errors. Furthermore, it is difficult to provide advice that responds to changes in the user's emotions, making it difficult to meet individual needs. To solve these issues, a system that can process data and provide advice more efficiently and accurately is needed.

[0651] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[0652] In this invention, the server includes a means for providing a household accounting app with a generative AI function, making advice from a financial planner "easy to understand and affordable for anyone, anytime," a means for providing advice in a chat format that is easy to understand and similar to consulting a financial planner, not just temporarily, but continuously, and in a manner similar to consulting a financial planner, a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting app, government portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically generating tax and insurance declaration forms based on data entered by the user into the household accounting app, and a means for successively improving the content and method of advice by using an emotion engine that learns changes in the user's emotions and feeds back the learning results to the generative AI. This allows the user to create accurate declaration forms without much effort and receive advice according to their individual needs.

[0653] A "household accounting app" is software that allows users to enter daily income and expenditure data and manage and analyze their household finances.

[0654] "Generative AI" is an artificial intelligence technology that automatically generates information based on input data and provides it to users.

[0655] A financial planner is an expert who analyzes the financial situation of individuals and companies and proposes optimal asset management and tax-saving measures.

[0656] "Chat format" means that users communicate in real time via text messages.

[0657] "Personal information" is information that can identify a specific individual, such as user attributes, data entered into a household accounting app, or information obtained from a government portal.

[0658] "External information" refers to information other than personal information, such as tax systems, asset management, real estate, financial products, and local living information.

[0659] "Continuous learning" is the process by which the system continues to learn based on user data and feedback, gradually improving the accuracy and content of its advice.

[0660] The "emotion engine" is a technology that analyzes changes in a user's emotions and uses the results to improve the content and delivery method of advice.

[0661] A "tax return" is a document required for filing tax and insurance returns.

[0662] "Automatic generation" is the process whereby the system creates the necessary documents and information based on user input data, without manual intervention.

[0663] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0664] This invention is a system that automatically generates tax and insurance declaration forms based on the data entered by the user into a household accounting application, and furthermore, learns the changes in the user's emotions and successively improves the content and delivery method of advice. This system works in cooperation with the server, the terminal, and the user.

[0665] Hardware and Software Used

[0666] Server: A cloud server is used to process data analysis, tax return generation, and the emotion engine.

[0667] Terminal: The user uses their smartphone or PC to enter data, send data, and receive advice.

[0668] Household accounting app: Software that allows users to enter daily income and expenditure data.

[0669] Generative AI: Artificial intelligence technology that automatically generates information based on input data and provides it to users.

[0670] Emotion engine: Technology that analyzes changes in a user's emotions and uses the results to improve the content and delivery of advice.

[0671] Program Processing

[0672] 1. Data Entry

[0673] The user inputs daily income and expenditure data into the household accounting app. For example, the user inputs information such as "Salary income in December 2023: 300,000 yen" and "Medical expenses: 10,000 yen."

[0674] 2. Data transmission

[0675] The terminal transmits the input data to the cloud server, and the terminal uploads the data to the server via the Internet.

[0676] 3. Data Analysis

[0677] The server analyzes the received data and extracts the necessary information. The server categorizes the data into income, expenses, deductibles, etc., and performs calculations based on tax laws and insurance regulations.

[0678] 4. Generate tax return

[0679] The server automatically generates tax and insurance declaration forms based on the analysis results. The server creates the declaration forms using templates and fills in the necessary fields with data.

[0680] 5. Submit your tax return

[0681] The server sends the generated tax return to the user's terminal. The server generates a PDF format tax return and sends it to the user's email address.

[0682] 6. Check the tax return

[0683] The user checks the tax return on the terminal and makes corrections as necessary. The user opens the tax return, checks the contents, and corrects any errors.

[0684] 7. Filing of tax returns

[0685] User files the return. User prints the return and either mails it or files it online.

[0686] 8. Emotion data input

[0687] Users input their daily events and emotions into the app, such as "I'm tired today" or "I'm in financial difficulty."

[0688] 9. Emotional Data Transmission

[0689] The device sends the data to a cloud server, and the device uploads the emotion data to the server via the Internet.

[0690] 10. Emotion analysis

[0691] The server uses an emotion engine to analyze changes in the user's emotions. The server uses text analysis and emotion recognition algorithms to classify the user's emotions and detect changes.

[0692] 11. Feedback Generation

[0693] The server feeds back the analysis results to the generative AI, which then sends data on changes in emotions to the generative AI to improve its advice.

[0694] 12. Advice Generation

[0695] Based on the feedback, generative AI will improve the content and delivery of advice. Based on the user's emotional data, generative AI will generate more specific and actionable advice.

[0696] 13. Sending Advice

[0697] The server sends the generated advice to the user's device. The server sends the advice to the user's device as a text message or notification.

[0698] 14. Receiving Advice

[0699] The user receives and executes the advice on the device. The user checks the advice and takes action if necessary.

[0700] Examples of prompt statements

[0701] 1. Prompt text about a system that realizes automatic creation and support of complicated tax returns:

[0702] Automatically generate your year-end tax adjustment declaration form based on the income and expenditure data entered into the household accounting app.

[0703] 2. Prompt for advice system using emotion engine:

[0704] If a user types, "I've been having financial trouble lately," generate specific, actionable advice based on what the sentiment engine has learned.

[0705] The flow of the identification process in the third embodiment will be described with reference to FIG.

[0706] Step 1:

[0707] Data Entry

[0708] The user enters daily income and expenditure data into a household accounting app.

[0709] Input: The user enters information such as "Salary income for December 2023: 300,000 yen" and "Medical expenses: 10,000 yen."

[0710] Output: Income and expenditure data is saved in the household accounting app.

[0711] Step 2:

[0712] Data transmission

[0713] The terminal transmits the input data to the cloud server.

[0714] Input: Income and expenditure data stored in the household accounting app.

[0715] Output: The balance data is uploaded to a cloud server via the Internet.

[0716] Step 3:

[0717] 4. Data Analysis

[0718] The server analyzes the received data and extracts the necessary information.

[0719] Input: Income and expenditure data uploaded to the cloud server.

[0720] Data processing: The server classifies data such as income, expenses, and deductibles, and performs calculations based on tax laws and insurance regulations.

[0721] Output: The analysis results include classified balance data and calculation results.

[0722] Step 4:

[0723] Generate tax return

[0724] The server automatically generates tax and insurance declarations based on the analysis results.

[0725] Input: Classified balance data and calculation results obtained as analysis results.

[0726] Data processing: The server creates a declaration form using a template and fills in the required fields with data.

[0727] Output: Auto-generated tax return (PDF format).

[0728] Step 5:

[0729] Submit your tax return

[0730] The server sends the generated declaration to the user's terminal.

[0731] Input: Auto-generated tax return (PDF format).

[0732] Output: The declaration is sent to the user's email address.

[0733] Step 6:

[0734] Check the declaration

[0735] The user checks the tax return on the terminal and makes corrections if necessary.

[0736] Input: The declaration sent to the user's email address.

[0737] Output: Amended return (if necessary).

[0738] Step 7:

[0739] Filing tax return

[0740] The user submits the return.

[0741] Enter: amended return.

[0742] Output: The return is printed and mailed or submitted online.

[0743] Step 8:

[0744] Emotion data input

[0745] Users input their daily events and feelings into the app.

[0746] Input: The user enters a feeling, such as "I'm tired today" or "I'm in financial difficulty."

[0747] Output: The emotion data is stored in the app.

[0748] Step 9:

[0749] Emotion data transmission

[0750] The device sends the data to a cloud server.

[0751] Input: Emotion data stored in the app.

[0752] Output: The emotion data is uploaded to a cloud server via the Internet.

[0753] Step 10:

[0754] Emotion analysis

[0755] The server uses an emotion engine to analyze changes in the user's emotions.

[0756] Input: Emotion data uploaded to the cloud server.

[0757] Data processing: The server uses text analysis and emotion recognition algorithms to classify the user's emotions and detect changes.

[0758] Output: The analysis results in data on changes in user emotions.

[0759] Step 11:

[0760] Feedback Generation

[0761] The server feeds back the analysis results to the generative AI.

[0762] Input: Data about user sentiment changes.

[0763] Output: Feedback data sent to the generative AI.

[0764] Step 12:

[0765] Advice Generation

[0766] Based on the feedback, the generative AI will improve the content and delivery of advice.

[0767] Input: Feedback data.

[0768] Data processing: Generative AI generates more specific and practical advice based on the user's emotional data.

[0769] Output: The generated advice.

[0770] Step 13:

[0771] Send Advice

[0772] The server transmits the generated advice to the user's terminal.

[0773] Input: The generated advice.

[0774] Output: Advice is sent to the user's device as a text message or notification.

[0775] Step 14:

[0776] Receive advice

[0777] The user receives and implements the advice on their device.

[0778] Input: Advice sent to the terminal.

[0779] Output: User reviews the advice and takes action if necessary.

[0780] (Application example 3)

[0781] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0782] Conventional household accounting apps and advice systems by financial planners have the problem that users have to manually input data and receive advice, which requires a lot of effort and time. In addition, they cannot provide advice based on emotional changes, and they lack concrete and practical support for users' financial difficulties. In addition, preparing tax and insurance declarations is also cumbersome, and mistakes are likely to occur.

[0783] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[0784] In this invention, the server includes: a means for providing a household accounting app with generative AI functions, making advice from a financial planner "easy to understand and affordable for anyone, anytime," a means for providing advice in a chat format that is easy to understand and similar to consulting a financial planner, not just temporarily, but continuously, and in a manner similar to consulting a financial planner; a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting app, Mynaportal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.); a means for automatically creating and supporting complicated tax returns, etc.; a means for an emotion engine to learn changes in the user's emotions and successively improve the content and method of providing advice based on the learning results; a means for automatically generating tax and insurance returns based on data entered by the user into the household accounting app; a means for the emotion engine to learn changes in the user's emotions and feed back the information to the generative AI; and a means for the generative AI to generate more specific and practical advice based on the feedback. This significantly reduces the user's effort and makes it possible to provide specific and practical advice based on changes in emotions.

[0785] A "household accounting app" is software that allows users to input and manage household data such as income, expenses, and savings.

[0786] "Generative AI" is an artificial intelligence technology that automatically generates advice and information based on input data.

[0787] A "financial planner" is a professional who provides financial planning and investment advice to individuals and businesses.

[0788] "Chat format" means that users communicate in real time via text messages.

[0789] "Personal information" refers to individual information such as user attributes, household accounting data, and My Number Portal.

[0790] "External information" refers to external information related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0791] "Continuous learning" is the process by which the system continually learns from user data and behavior to improve the accuracy of its advice.

[0792] A "tax return" is an official document used to declare taxes, insurance, etc.

[0793] The "emotion engine" is a technology that analyzes changes in a user's emotions and uses the results to improve the content and delivery method of advice.

[0794] "Feedback" is the process of providing information for the next action or improvement based on the information or results obtained by the system.

[0795] The system for implementing this invention adds generative AI functionality to a household accounting app, providing financial planner advice "anytime, for anyone, in an easy-to-understand and affordable way." The system provides accurate advice and support through continuous learning based on the user's personal information and external information. It also automatically creates and supports complicated tax returns, and the emotion engine learns the user's emotional changes and, based on the learning results, continuously improves the content and delivery method of the advice.

[0796] Hardware and Software Used

[0797] Hardware: Smartphone

[0798] Software: Python, EmotionEngine library, AIAdvisor library, TaxFormGenerator library

[0799] Data processing and calculation

[0800] 1. Reading household accounting data: The server reads data such as income, expenses, and savings that the user has entered into the household accounting app on their smartphone in JSON format.

[0801] 2. Initializing emotion engine: The server initializes the emotion engine using the EmotionEngine library and analyzes changes in the user's emotions.

[0802] 3. Initialization of the generative AI: The server initializes the generative AI using the AIAdvisor library and automatically generates advice based on the user's household financial situation.

[0803] 4. Initializing the tax return generator: The server initializes the tax return generator using the TaxFormGenerator library, and automatically generates tax, insurance, and other tax returns based on the user's household accounting data.

[0804] 5. Learning changes in emotions: The server analyzes changes in the user's emotions based on household accounting data and feeds that information back to the generative AI.

[0805] 6. Advice generation: Generative AI uses feedback from the emotion engine to generate more specific and actionable advice.

[0806] Examples

[0807] For example, if a user enters "This month's income is 300,000 yen, and expenses are 250,000 yen" into a household accounting app, the server reads this data and uses an emotion engine to analyze changes in the user's emotions. Next, based on this information, generative AI generates specific advice such as "This month's savings are 50,000 yen. To reduce expenses next month, why not review your food expenses?" Tax and insurance declaration forms are also automatically generated, significantly reducing the user's workload.

[0808] Examples of prompt statements

[0809] Develop an application that automatically generates tax and insurance returns based on household accounting data, and learns changes in the user's emotions to provide financial advice. Specifically, create a Python program that includes the following functions:

[0810] 1. Importing household accounting data

[0811] 2. Initializing the emotion engine

[0812] 3. Initialization of generative AI

[0813] 4. Initializing the declaration generator

[0814] 5. Automatic generation of tax returns

[0815] 6. Learn emotional changes

[0816] 7. Generating Advice

[0817] In this way, a specific embodiment of the invention can be shown.

[0818] The flow of the specific process in the application example 3 will be described with reference to FIG.

[0819] Step 1:

[0820] The server reads data in JSON format, such as income, expenses, and savings, that the user has entered into the household accounting app on their smartphone. The input data is obtained from the household accounting app and sent to the server. The server analyzes this data and saves it in an internal database. This allows the user to understand their household financial situation.

[0821] Step 2:

[0822] The server initializes the emotion engine using the EmotionEngine library. The emotion engine analyzes changes in the user's emotions based on the user's household accounting data. The input data is the household accounting data, and the output is the user's emotional state (e.g., stress, relief). The server feeds this emotion data back to the generative AI.

[0823] Step 3:

[0824] The server initializes the generative AI using the AIAdvisor library. The generative AI automatically generates advice based on the user's household finances. The input data are household finance data and emotion data, and the output is specific advice (e.g., how to review spending and increase savings). The server provides this advice to the user.

[0825] Step 4:

[0826] The server initializes the tax return generator using the TaxFormGenerator library. The tax return generator automatically generates tax, insurance, and other tax returns based on the user's household accounting data. The input data is the household accounting data, and the output is an automatically generated tax return. The server provides this tax return to the user.

[0827] Step 5:

[0828] The server learns the changes in the user's emotions based on the household accounting data and feeds that information back to the generative AI. The input data is the household accounting data and emotion data, and the output is the learning results. The server reflects these learning results in the generative AI.

[0829] Step 6:

[0830] The generative AI generates more specific and practical advice based on the feedback from the emotion engine. The input data is the feedback from the emotion engine, and the output is improved advice. The server provides this advice to the user.

[0831] In this way, the system can support users in managing their finances and provide specific, actionable advice based on emotional changes.

[0832] 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0833] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0834] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0835] In the above embodiment, an example was given in which the specific process was performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0836] [Second embodiment]

[0837] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0838] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0839] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[0840] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0841] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[0842] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[0843] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[0844] Fig. 4 shows an example of main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0845] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0846] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0847] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0848] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0849] "Example 1"

[0850] One embodiment of the present invention is a system that adds generative AI functions to a household accounting app. This system automatically generates advice from a financial planner based on household accounting data entered by the user. The generated advice is provided to the user in a format that is easy for the user to understand, such as a chat format.

[0851] "Example 2"

[0852] Furthermore, as another embodiment of the present invention, there is a system that provides accurate advice and support by combining personal information (attributes, household accounting apps, My Number Portal, etc.) with external information (tax systems, asset management, real estate, financial products, local life information, etc.). This system is capable of providing personalized advice tailored to the user's lifestyle and asset situation.

[0853] "Example 3"

[0854] As another embodiment of the present invention, there is a system that realizes automatic creation and support of complicated tax returns. This system can reduce the time and effort required for users to file tax and insurance returns and prevent mistakes. For example, when creating a tax return for year-end adjustment, the system can automatically generate the return based on the data entered by the user into a household accounting application.

[0855] The process flow of each embodiment will be described below.

[0856] "Example 1"

[0857] Step 1: The user enters their income and expenditure information into the household accounting app.

[0858] Step 2: The generative AI analyzes the information entered by the user and understands the user's financial situation.

[0859] Step 3: The generative AI automatically generates FP advice and provides it to the user.

[0860] "Example 2"

[0861] Step 1: The user enters their income and expenditure information into the household accounting app.

[0862] Step 2: The system combines personal information (attributes, household accounting apps, My Number Portal, etc.) with external information (tax systems, asset management, real estate, financial products, local lifestyle information, etc.) to provide accurate advice and support.

[0863] "Example 3"

[0864] Step 1: The user enters their income and expenditure information into the household accounting app.

[0865] Step 2: The system will automatically create and provide support for complicated tax returns and other documents based on the information entered by the user.

[0866] Step 3: For example, when preparing a year-end tax return, the system automatically generates the return based on the data the user entered into the household accounting app.

[0867] Example 1

[0868] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0869] Conventional household accounting apps allow users to understand their own household finances, but to get professional advice, they must consult a financial planner separately. In addition, the cost and effort required to get advice makes it difficult to receive ongoing support. Furthermore, users must themselves fill out complicated tax returns and gather external information, which places a heavy burden on them. To solve these issues, there is a need for a system that adds generative AI functionality to household accounting apps and automatically generates and continuously provides advice from financial planners.

[0870] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0871] In this invention, the server includes a means for generating a prompt sentence based on household accounting data input by the user and sending it to the generative AI model, a means for the generative AI model to generate advice based on the prompt sentence and for the server to receive the advice, and a means for the server to send the generated advice to the user's terminal. This allows the user to automatically and continuously receive expert advice, reducing the burden of household accounting management.

[0872] A "household accounting app" is software that allows users to input and manage household data such as income, expenses, and savings.

[0873] "Generative AI" is an artificial intelligence technology that automatically generates responses and advice in natural language based on input data.

[0874] A financial planner is an expert who analyzes the financial situation of individuals and families and suggests optimal asset management and savings methods.

[0875] A "prompt sentence" is an instruction sentence input to a generative AI, which contains the information that the AI ​​uses to generate responses and advice.

[0876] A "server" is a computer system whose role is to receive data from users, process it, and send it to the generative AI.

[0877] "Terminal" means the device through which a User enters household accounting data and receives generated advice.

[0878] "Database" refers to an information management system for storing household accounting data and generated advice.

[0879] "Chat format" refers to an interface format for interaction between a user and a system, in which messages are exchanged.

[0880] "Personal information" refers to individual information such as user attributes, household accounting data, portal sites, etc.

[0881] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0882] "Continuous learning" is the process by which generative AI continues to learn from user data and external information in order to provide more accurate advice.

[0883] "Returns" means any tax returns or other official reports that you are required to submit.

[0884] This invention is a system that adds generative AI functionality to a household accounting app, automatically generating advice from a financial planner based on household accounting data entered by the user, and providing it in chat format. This system enables users to efficiently manage their household finances and receive continuous expert advice.

[0885] Hardware and Software Used

[0886] Hardware

[0887] Server: Receives, stores, and analyzes data, sends prompts to the generative AI model, receives generated advice, and sends it to the user device.

[0888] Terminal: The device (smartphone, tablet, PC, etc.) where the user enters their household accounting data and receives the generated advice.

[0889] software

[0890] Financial accounting app: An application that allows users to enter data such as income, expenses, and savings goals.

[0891] Generative AI model: An artificial intelligence technology that generates advice based on an input prompt (e.g., OpenAI’s GPT-4).

[0892] Database: An information management system (e.g. MySQL, PostgreSQL) for storing the accounting data and the generated advice.

[0893] Data processing and calculation

[0894] Enter and send household accounting data

[0895] The user uses the household accounting app to input data such as income, expenses, and savings goals. For example, monthly income is 300,000 yen, rent is 100,000 yen, food expenses are 50,000 yen, transportation expenses are 20,000 yen, other expenses are 30,000 yen, and savings goal is 50,000 yen. The device then transmits this data to the server.

[0896] Data storage and analysis

[0897] The server saves the received household accounting data in the database. Next, the server generates a prompt based on the saved data. For example, it generates the following prompt:

[0898] The user's monthly income is 300,000 yen, and his expenses are as follows: rent 100,000 yen, food 50,000 yen, transportation 20,000 yen, other 30,000 yen. The user's savings goal is 50,000 yen per month. Based on this, please provide some advice as a financial planner.

[0899] Generating and serving advice

[0900] The server sends the generated prompt sentence to the generative AI model. The generative AI model generates advice based on the prompt sentence. For example, it generates advice like the following:

[0901] Your monthly income is 300,000 yen and your total expenses are 200,000 yen. To achieve your savings goal of 50,000 yen, you can save the remaining 50,000 yen. Review your food expenses and other expenses and see if there are any areas where you can save money. It would also be a good idea to think about ways to increase your income.

[0902] The server receives the generated advice and transmits it to the user's terminal, where the user can receive the advice in chat format.

[0903] Examples

[0904] For example, when a user opens a household accounting app and enters income and expenditure data, the app provides an input form. After the user finishes entering the data, he or she presses the "Submit" button. The device sends this data to the server, which then stores the data in a database. The server then sends a prompt to the generative AI model and receives the generated advice. Finally, the server sends the advice to the user's device, and the user checks the advice in the app.

[0905] In this way, users can automatically and continuously receive expert advice, easing the burden of managing their household finances.

[0906] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0907] Step 1:

[0908] The user enters household accounting data

[0909] Users use a household accounting app to input data such as income, expenses, and savings goals. For example, monthly income is 300,000 yen, rent is 100,000 yen, food expenses are 50,000 yen, transportation expenses are 20,000 yen, other expenses are 30,000 yen, and savings goal is 50,000 yen. The input data is temporarily stored on the device.

[0910] Step 2:

[0911] The terminal sends the input data to the server

[0912] The terminal transmits the household accounting data entered by the user to the server. This transmission is secure using the HTTPS protocol. The input data includes information such as income, expenses, and savings goals.

[0913] Step 3:

[0914] The server saves the data to a database

[0915] The server stores the received household accounting data in a database, using a relational database such as MySQL or PostgreSQL. The stored data includes information such as the user's income, expenses, and savings goals.

[0916] Step 4:

[0917] The server sends a prompt to the generative AI model.

[0918] The server generates a prompt sentence based on the saved household accounting data. For example, it generates a prompt sentence like, "The user's monthly income is 300,000 yen, and the expenses are as follows: rent 100,000 yen, food 50,000 yen, transportation 20,000 yen, other 30,000 yen. The user's savings goal is 50,000 yen per month. Based on this, please provide some advice as a financial planner." The generated prompt sentence is sent to the generative AI model.

[0919] Step 5:

[0920] Generative AI models generate advice

[0921] A generative AI model (for example, OpenAI's GPT-4) generates advice based on the prompt text sent from the server. The generative AI model analyzes the household accounting data included in the prompt text and generates appropriate advice. For example, it generates advice such as, "Your monthly income is 300,000 yen, and your total expenses are 200,000 yen. To achieve your savings goal of 50,000 yen, you can save the remaining 50,000 yen. Please review your food expenses and other expenses and consider whether there are any areas where you can save money. It would also be a good idea to think about ways to increase your income."

[0922] Step 6:

[0923] The server receives the generated advice

[0924] The server receives advice generated from the generative AI model in a format that is easy for the user to understand.

[0925] Step 7:

[0926] The server sends advice to the device

[0927] The server transmits the generated advice to the user's terminal, again securely using the HTTPS protocol. The transmitted data is the generated advice.

[0928] Step 8:

[0929] User receives advice

[0930] Users receive the generated advice via their device. The advice is displayed in chat format, and users can use it to review and improve their household finances.

[0931] (Application example 1)

[0932] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[0933] Conventional household accounting apps require users to manually input data, and require separate consultation with a financial planner (FP) to receive advice. This is time-consuming for users, making it difficult for them to continue using the apps. In addition, when using electronic payment services, expenditure data is not automatically reflected in the household accounting app, making expenditure management cumbersome.

[0934] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0935] In this invention, the server includes a means for providing a generative AI function to a household accounting app, making advice from a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in chat format that is easy to understand and similar to consulting a financial planner, not just one-time but continuous, not one-time, but continuous, and provides accurate advice and support through continuous learning of personal information (attributes, household accounting app, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically creating and supporting complicated tax returns, etc., and a means for automatically recording expenditure data in a household accounting book when using an electronic payment service, analyzing the data with a generative AI, and providing advice from a financial planner in chat format. This allows users to manage their expenditure data hassle-free and receive accurate advice on an ongoing basis.

[0936] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[0937] "Generative AI" is an artificial intelligence technology that automatically generates responses and suggestions for specific tasks based on data entered by the user.

[0938] "FP" stands for financial planner, a professional who provides financial planning and investment advice to individuals and companies.

[0939] "Chat style" refers to an interface style in which a user and a system exchange information in a dialogue format.

[0940] "Personal information" refers to information about individuals contained in user attributes, data from household accounting apps, My Number Portal, etc.

[0941] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[0942] "Continuous learning" is a function that enables the system to continually learn from user data and external information in order to provide more accurate advice.

[0943] An "electronic payment service" is an online payment system that enables users to pay for goods and services via the Internet.

[0944] "Expense data" refers to information such as the amount, date, and category when a user purchases a product or service.

[0945] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[0946] In order to implement this invention, it is necessary to build a system in which a household accounting app is given generative AI functionality, expenditure data is automatically recorded in the household accounting book when using electronic payment services, and the generative AI analyzes the data and provides advice from a financial planner in chat format.

[0947] The server collects the user's spending data and analyzes it using a generative AI model. Specifically, the server automatically obtains spending data from the user's electronic payment service and records it in the household accounting app. At this time, the spending data is organized by category and displayed so that the user's household financial situation can be seen at a glance.

[0948] Next, the server uses a generative AI model to generate FP advice based on the user's spending data. This generative AI model uses OpenAI's GPT-3 and other models. The generated advice is provided to the user in a chat format that is easy for the user to understand. For example, the following prompt sentences are used:

[0949] User spending data: {"2023-10-01": {"food": 5000, "transport": 2000, "entertainment": 3000}, "2023-10-02": {"food": 4500, "transport": 1500, "entertainment": 2500}, "2023-10-03": {"food": 4000, "transport": 1000, "entertainment": 2000}}

[0950] As a financial planner, you can provide advice based on this data.

[0951] The generated advice may look something like this:

[0952] FP Tip: Food costs make up a large portion of your total expenses. You can save by buying in bulk once a week and eating out less. You should also reassess your transportation costs. Using a commuter pass for public transportation can help you save even more.

[0953] Users can access the household accounting app using a smartphone, tablet, or other device and check the generated advice. When users input a question, the generative AI model generates an answer in real time and provides it in chat format.

[0954] The system allows users to effortlessly manage their spending data and receive accurate advice on an ongoing basis. The hardware required is a smartphone or tablet with an internet connection, and a server. The software uses Python, OpenAI API, and JSON files.

[0955] The flow of the specific process in the application example 1 will be described with reference to FIG.

[0956] Step 1:

[0957] The server automatically obtains spending data from the user's electronic payment service. The input is the transaction data of the user's electronic payment service, and the output is spending data organized by category. Specifically, the server accesses the electronic payment service through an API to obtain the user's spending information. This data is stored in the form of dates, categories, amounts, etc.

[0958] Step 2:

[0959] The server records the acquired expenditure data in the household accounting app. The input is the expenditure data organized by category acquired in step 1, and the output is the expenditure data saved in the household accounting app. Specifically, the server writes the expenditure data to the database of the household accounting app so that the user can check it through the app.

[0960] Step 3:

[0961] The server uses a generative AI model to generate FP advice based on the expenditure data recorded in the household accounting app. The input is the expenditure data stored in the household accounting app, and the output is the generated FP advice. Specifically, the server inputs the expenditure data as a prompt sentence into the generative AI model to generate advice. An example of the prompt sentence is as follows:

[0962] User spending data: {"2023-10-01": {"food": 5000, "transport": 2000, "entertainment": 3000}, "2023-10-02": {"food": 4500, "transport": 1500, "entertainment": 2500}, "2023-10-03": {"food": 4000, "transport": 1000, "entertainment": 2000}}

[0963] As a financial planner, you can provide advice based on this data.

[0964] Step 4:

[0965] The server provides the generated advice to the user in chat format. The input is the FP advice generated in step 3, and the output is the advice in chat format displayed on the user's device. Specifically, the server sends the generated advice to the user's device in the form of a chatbot so that the user can check it through the app.

[0966] Step 5:

[0967] When a user enters a question, the server uses a generative AI model to generate an answer in real time and provides it in chat format. The input is the question entered by the user, and the output is the generated answer. Specifically, the server inputs the user's question as a prompt sentence into the generative AI model and generates an answer. The generated answer is displayed on the user's device in chat format.

[0968] Example 2

[0969] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[0970] Advice provided by traditional household accounting apps and financial planners (FPs) is temporary, making it difficult to provide ongoing support. In addition, there is a lack of systems that provide accurate advice by combining personal information and external information, making it difficult for users to receive personalized advice based on their lifestyle and asset status. Furthermore, there is a lack of automated creation and support for cumbersome tax returns.

[0971] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for combining personal information (attributes, household accounting application, portal site, etc.) with external information (tax system, asset management, real estate, financial products, local life information, etc.) to provide accurate advice and support, a means for generating personalized advice based on the user's lifestyle and asset status, a means for encrypting personal information input by the user and transmitting it to the server using a secure communication protocol, a means for the server to store the received personal information in a database, a means for the server to collect external information and store it in a database, a means for the server to perform data analysis using a generation AI model, a means for the server to generate advice based on the analysis results, a means for the server to transmit the advice generated by the server to the terminal, and a means for the terminal to display the advice to the user. This allows the user to receive continuous and personalized advice.

[0972] "Personal information" refers to a series of data about a user, such as user attribute information, data from a household accounting app, and information from a portal site.

[0973] "External information" refers to data collected from external sources related to the user's lifestyle and asset management, such as tax systems, asset management, real estate, financial products, and local lifestyle information.

[0974] A "server" is a computer system that receives, stores, and processes data submitted by users.

[0975] A "database" is a data management system for storing personal information and external information received by the server.

[0976] A "generative AI model" is an artificial intelligence model that performs data analysis based on a user's personal information and external information, and generates advice.

[0977] "Personalized advice" is advice that is individually customized based on a user's lifestyle and financial situation.

[0978] "Encryption" is a technique for converting data using a specific algorithm in order to transmit the data securely.

[0979] A "communications protocol" is a technology that defines the rules and procedures for sending and receiving data safely.

[0980] "Data analytics" is the process of using generative AI models to analyze a user's personal information and external information to extract meaningful information.

[0981] A "terminal" is a device used by a user, such as a smartphone or computer.

[0982] The "means for displaying advice" is a function for visually presenting to the user the advice that the terminal receives from the server.

[0983] The present invention is a system that combines personal information and external information to provide appropriate advice and support. A specific embodiment of this system will be described below.

[0984] Hardware and Software Configuration

[0985] Hardware:

[0986] Server: A high-performance computer system (e.g., a general-purpose server)

[0987] Device: The smartphone or computer used by the user

[0988] software:

[0989] Database Management System: Database software such as MySQL

[0990] Generative AI models: Artificial intelligence models such as OpenAI GPT-4

[0991] Communication Protocol: A secure communication protocol such as HTTPS

[0992] Data processing and calculation

[0993] Enter and submit your personal information:

[0994] The user uses the terminal to access the system's dedicated application or website and enters personal information such as attribute information (age, occupation, income, etc.), data from the household accounting application, and information from the portal site. The terminal encrypts the entered personal information and transmits it to the server using a secure communication protocol (e.g., HTTPS).

[0995] Data Retention:

[0996] The server stores the received personal information in a database management system (e.g. MySQL). When storing, checks are performed to ensure data integrity and security.

[0997] Collection of external information:

[0998] The server uses external APIs and web scraping technology to collect external information such as tax systems, asset management, real estate, financial products, and local life information. The collected information is stored in a database.

[0999] Data analysis and advice generation:

[1000] The server combines the stored personal information with external information and performs data analysis using a generative AI model (e.g., OpenAI GPT-4). Specifically, it analyzes the user's income and expenditure patterns and derives optimal asset management and savings methods. The server generates specific advice for the user based on the analysis results of the generative AI model.

[1001] Sending and viewing advice:

[1002] The server sends the generated advice to the device, using data encryption and secure communication protocols. The device displays the received advice to the user, who can then view the specific advice through an application or website.

[1003] Examples of concrete examples and prompts

[1004] Examples:

[1005] The user opens a dedicated application on their smartphone and enters their monthly income (300,000 yen) and expenses (250,000 yen). The device encrypts this information and sends it to the server using HTTPS. The server stores the received information in a MySQL database. The server then collects the latest tax information and asset management trends from an external API and stores them in the database.

[1006] The server uses OpenAI GPT-4 to analyze the user's income and spending patterns and generates advice such as "To reduce spending this month, it is effective to cut food expenses by 10%." The generated advice is encrypted again and sent to the terminal using HTTPS. The terminal displays the received advice to the user, and the user can check the specific ways to save money.

[1007] Example prompt:

[1008] "If a user's monthly income is 300,000 yen and expenses are 250,000 yen, what saving and investment methods would you suggest, taking into account the latest tax information and asset management trends?"

[1009] In this way, a system is realized in which the server, terminal, and user work together to provide personalized advice.

[1010] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1011] Step 1:

[1012] The user inputs personal information. The user uses the terminal to access the system's dedicated application or website and inputs personal information such as attribute information (age, occupation, income, etc.), data from a household accounting application, and information from a portal site. The input data is sent to the system through the terminal's input device (keyboard or touch screen).

[1013] Step 2:

[1014] The terminal sends the personal information entered by the user to the server. The terminal encrypts the personal information entered by the user and sends it to the server using a secure communication protocol (e.g. HTTPS). The input data is encrypted and sent to the server.

[1015] Step 3:

[1016] The server saves the personal information in a database. The server saves the received personal information in a database management system (e.g. MySQL). When saving, checks are performed to ensure data integrity and security. The input data is saved in the database and a consistency check is performed.

[1017] Step 4:

[1018] The server collects external information and stores it in a database. The server uses external APIs and web scraping technology to collect external information such as tax systems, asset management, real estate, financial products, and local lifestyle information. The collected information is stored in a database. External information is obtained through APIs and scraping technology and stored in a database.

[1019] Step 5:

[1020] The server performs data analysis using a generative AI model. The server combines the stored personal information with external information and performs data analysis using a generative AI model (e.g. OpenAI GPT-4). Specifically, it analyzes the user's income and expenditure patterns and determines optimal asset management and savings methods. Input data (personal information and external information) is input into the generative AI model, and the analysis results are output.

[1021] Step 6:

[1022] The server generates advice based on the analysis results. The server generates specific advice for the user based on the analysis results of the generative AI model. For example, it generates advice such as "To reduce expenses this month, it is effective to cut food expenses by 10%" or "It would be a good idea to invest surplus funds in stocks." The analysis results are output as advice.

[1023] Step 7:

[1024] The server transmits the generated advice to the terminal. The server transmits the generated advice to the terminal. When transmitting, data encryption and a secure communication protocol are used. The generated advice is encrypted and transmitted to the terminal.

[1025] Step 8:

[1026] The device displays the advice to the user. The device displays the received advice to the user. The user can check the specific advice through an application or website. The received advice is displayed on the device display.

[1027] (Application example 2)

[1028] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1029] Advice provided by traditional household accounting apps and financial planners is temporary and lacks ongoing support. In addition, there is no system that combines a user's personal information with external information to provide accurate advice, making it difficult for users to receive advice that is best suited to their lifestyle and asset situation. Furthermore, there is a lack of a centralized means of providing advice on the creation of complicated tax returns, asset management, tax-saving strategies, and ways to reduce living expenses.

[1030] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means. In this invention, the server includes a means for providing a generative AI function to a household accounting application to make advice by a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and is similar to consulting a financial planner, not just temporarily, but continuously, and not temporarily, and is similar to consulting a financial planner, a means for realizing accurate advice and support by continuous learning of personal information (attributes, household accounting application, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local living information, etc.), a means for realizing automatic creation and support of complicated tax returns, etc., a means for combining the user's personal information and external information to advise on asset management, tax saving measures, and ways to save on living expenses, a means for calculating taxes on the user's income, a means for providing investment advice according to the user's asset situation, a means for reviewing the user's living expenses and proposing savings, and a means for generating a prompt sentence using a generative AI model. This allows the user to receive continuous and accurate advice.

[1031] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[1032] "Generative AI" is a system that uses artificial intelligence technology to analyze data and automatically generate new information and advice.

[1033] A financial planner is an expert who analyzes the financial situations of individuals and companies and provides advice on asset management and tax saving measures.

[1034] "Chat format" means that users communicate in real time via text messages.

[1035] "Personal information" refers to all data relating to individuals, such as user attribute information, data from household accounting apps, and My Number Portal information.

[1036] "External information" refers to data concerning the user's external environment, such as tax systems, asset management, real estate, financial products, and local living information.

[1037] "Continuous learning" is the process by which the system continually learns from user data and improves the accuracy of its advice.

[1038] A "tax return" is a document to be submitted to the tax office, etc., which lists income, expenses, asset status, etc.

[1039] "Asset management" refers to investment activities aimed at efficiently increasing users' assets.

[1040] "Tax avoidance strategies" refer to methods or means for legally reducing tax burdens.

[1041] "Saving on living expenses" refers to ways and means of reducing expenses in daily life.

[1042] A "generative AI model" is a model that uses artificial intelligence technology to analyze data and generate new information and advice.

[1043] A "prompt" is an instruction to be input into a generative AI model, which serves as a trigger for generating specific information or advice.

[1044] The system for implementing this invention includes a server, a user terminal, and a generative AI model. The server collects personal information and external information of the user, and generates appropriate advice based on this data. The user terminal records the user's income and expenditure through a household accounting app, and communicates with the server to receive advice.

[1045] The server first obtains the user's personal information (attributes, data from the household accounting app, My Number Portal information, etc.). It then collects external information (tax systems, asset management, real estate, financial products, local living information, etc.). This data is stored in a database within the server.

[1046] The server uses a generative AI model to analyze the user's personal information and external information, and generates advice on asset management, tax savings, ways to save on living expenses, etc. This generative AI model continuously learns from the user's data and improves the accuracy of its advice.

[1047] The user device receives advice from the server through the household accounting app and presents it to the user. The user can send questions to the server in chat format and receive answers in real time, allowing the user to receive continuous and accurate advice.

[1048] As a concrete example, consider a case where a user has an annual income of 6 million yen, annual living expenses of 3 million yen, and assets of 10 million yen. In this case, the server generates the following advice:

[1049] The annual tax is 1200000 yen.

[1050] Consider investing in stocks or real estate as a way to manage your assets.

[1051] Review your living expenses and try to save money.

[1052] Example of a prompt to be input to a generative AI model:

[1053] Please create a program that combines the user's personal information (attributes, household accounting app, My Number Portal, etc.) with external information (tax system, asset management, real estate, financial products, local living information, etc.) to give the user advice on optimal asset management, tax saving measures, ways to save on living expenses, etc. Please also include a concrete example where the user's annual income is 6 million yen, annual living expenses are 3 million yen, and assets are 10 million yen.

[1054] This system enables users to receive advice that is best suited to their lifestyle and asset situation, enabling them to effectively manage their assets, save on taxes, and reduce living expenses.

[1055] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1056] Step 1:

[1057] The user's device inputs the user's income and expenditure data through the household accounting app. This records the user's household financial situation. The input data includes the amount of income, expenditure items, and expenditure amounts. This data is sent from the user's device to the server.

[1058] Step 2:

[1059] The server receives the household data sent from the user's device and stores it in a database. The stored data is managed as the user's personal information (attributes, data from the household accounting app, My Number Portal information, etc.). This allows the user's household financial situation to be accumulated on the server.

[1060] Step 3:

[1061] The server collects external information (tax systems, asset management, real estate, financial products, local life information, etc.). The external information is obtained through API and stored in a database. This allows the latest external information to be accumulated on the server.

[1062] Step 4:

[1063] The server combines and analyzes the user's personal information and external information. Using a generative AI model, it generates advice based on the user's household situation. Specifically, this includes calculating taxes on the user's income, suggesting asset management, and ways to save on living expenses. The input data is the user's personal information and external information, and the output data is the generated advice.

[1064] Step 5:

[1065] The server transmits the generated advice to the user's device, which then presents the received advice to the user through the household accounting app, allowing the user to confirm and act on the advice.

[1066] Step 6:

[1067] Users send questions to the server through the home accounting app. The questions are entered in text format and sent to the server, allowing users to receive support in real time.

[1068] Step 7:

[1069] The server receives questions from users and generates answers in real time using a generative AI model. The input data is the user's question, and the output data is the generated answer. The generated answer is based on the user's household financial situation and external information.

[1070] Step 8:

[1071] The server sends the generated answer to the user's device, which then presents the received answer to the user through the household accounting app, allowing the user to receive accurate advice in real time.

[1072] In this way, users can receive continuous and accurate advice, enabling them to effectively manage their assets, save on taxes, and reduce living expenses.

[1073] Example 3

[1074] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1075] Conventional household accounting apps and systems that provide advice from financial planners have problems in that it takes a lot of time and effort for users to declare taxes, insurance, etc., and mistakes are likely to occur. In addition, the creation of tax returns is complicated, making it difficult for users to create tax returns accurately. Furthermore, there is also the problem that advice from financial planners is temporary and there is a lack of ongoing support.

[1076] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1077] In this invention, the server includes a means for automatically generating a tax return based on data input by the user to the household accounting application, a means for the terminal to send the input data to the server, a means for the server to receive the data and store it in a database, a means for the server to analyze the stored data and extract necessary information, a means for the server to input the extracted information to the generative AI model, a means for the generative AI model to automatically generate a tax return, a means for the server to output the generated tax return in PDF format, and a means for the user to download the PDF and submit it as a tax return. This allows the user to automate the creation of complicated tax returns and significantly reduce the effort required.

[1078] A "household accounting app" is software that allows users to input and manage household information such as income and expenses.

[1079] "Generative AI" is an artificial intelligence technology that automatically generates text and information based on input data.

[1080] A "financial planner" is a professional who provides financial planning and investment advice to individuals and businesses.

[1081] "Chat format" means that users communicate in real time via text messages.

[1082] "Personal information" is information that can be used to identify a specific individual, such as user attributes and household information.

[1083] "External information" refers to information obtained from external sources related to the user's household management and filing, such as tax systems, asset management, real estate, financial products, and local living information.

[1084] "Continuous learning" is the process by which a system continually learns new data and information to improve its accuracy and performance.

[1085] A "tax return" is a document required to declare taxes, insurance, etc.

[1086] A "terminal" is a device that a user uses to operate the household accounting app, including a smartphone or a PC.

[1087] A "server" is a computer system that receives, stores, analyzes, and runs generative AI models.

[1088] A "database" is a system for efficiently storing, managing, and searching data.

[1089] A "generative AI model" is an artificial intelligence model that automatically generates documents such as tax returns based on input data.

[1090] "PDF format" is an abbreviation for Portable Document Format, a file format for electronically storing and displaying documents.

[1091] This invention is a system that automatically generates tax returns based on data entered by a user into a household accounting application. The purpose of this system is to reduce the user's workload and prevent mistakes. A specific embodiment of this system will be described below.

[1092] First, the user uses the household accounting app to input data such as income, expenses, and deductions. For example, the user enters information such as income of 5 million yen, medical expenses of 100,000 yen, and mortgage deduction of 200,000 yen. This household accounting app works on devices such as smartphones and computers.

[1093] The terminal then transmits the entered data to the server, using the HTTPS protocol to ensure data security. The server receives the data sent from the terminal and stores it in a relational database such as MySQL or PostgreSQL.

[1094] The server uses Python scripts to analyze the data stored in the database. During the analysis, it extracts necessary information such as income, medical expenses, mortgage deductions, etc. The extracted information is then fed into a generative AI model (e.g. GPT-4).

[1095] The prompt for input to the generative AI model is as follows:

[1096] The user's income is 5 million yen, medical expenses are 100,000 yen, and the mortgage deduction is 200,000 yen. Please fill out your year-end tax return based on this information.

[1097] The generative AI model automatically generates the year-end tax return based on this prompt. The generated return is returned to the server in text format. The server converts the returned text to PDF format. For example, Python's ReportLab library is used for this conversion.

[1098] Finally, the user downloads the generated PDF form from the server, which can then be printed and submitted to the appropriate authorities.

[1099] This system enables users to automate the creation of complicated tax returns, significantly reducing the amount of work required. In addition, the use of generative AI models improves the accuracy of tax returns. The flow of the specific process in Example 3 is described with reference to FIG. 15.

[1100] Step 1:

[1101] The user enters data into a household accounting app.

[1102] The user uses the household accounting app to input data such as income, expenses, and deductions. For example, the user may input information such as income of 5 million yen, medical expenses of 100,000 yen, and mortgage deduction of 200,000 yen. The input data is temporarily stored in the household accounting app.

[1103] Step 2:

[1104] The terminal transmits the input data to the server.

[1105] The terminal (smartphone or PC) sends the data entered by the user to the server using the HTTPS protocol. The data sent includes information such as income, medical expenses, and mortgage deductions. The input data is encrypted and sent to the server through a secure communication channel.

[1106] Step 3:

[1107] The server receives the data and stores it in a database.

[1108] The server receives the data sent from the terminal. The received data is stored in a relational database such as MySQL or PostgreSQL. The data is organized and stored for each user in the database.

[1109] Step 4:

[1110] The server analyzes the stored data and extracts the necessary information.

[1111] The server uses Python scripts to analyze the data stored in the database. During the analysis, it extracts necessary information such as income, medical expenses, and mortgage deductions. Based on the input data (income of 5 million yen, medical expenses of 100,000 yen, and mortgage deduction of 200,000 yen), the analyzed information is extracted.

[1112] Step 5:

[1113] The server inputs the extracted information into a generative AI model.

[1114] The server inputs the extracted information into a generative AI model (e.g. GPT-4) with the following prompt:

[1115] The user's income is 5 million yen, medical expenses are 100,000 yen, and the mortgage deduction is 200,000 yen. Please fill out your year-end tax return based on this information.

[1116] Step 6:

[1117] A generative AI model automatically generates tax returns.

[1118] The generative AI model automatically generates the year-end tax return based on the input prompt text. The generated return is returned to the server in text format. The generative AI model analyzes the input data and generates the return in the appropriate format.

[1119] Step 7:

[1120] The server outputs the generated declaration in PDF format.

[1121] The server converts the text-based tax return returned by the generative AI model into a PDF file, for example using the Python ReportLab library, and converts the text data into a PDF file that users can download.

[1122] Step 8:

[1123] The user downloads the PDF and submits it as a tax return.

[1124] The user downloads the generated PDF tax return from the server. The downloaded PDF can be printed and submitted to the necessary authorities. The user can also check the contents of the tax return and make corrections if necessary.

[1125] (Application example 3)

[1126] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1127] In modern society, filing tax and insurance returns is extremely cumbersome, and many people spend a lot of time and effort preparing tax returns. In addition, preparing tax returns requires specialized knowledge and is prone to errors. Furthermore, consulting with an expert is often expensive, which is a heavy burden on ordinary people. There is a need for a system that can solve these problems and allow anyone to easily prepare accurate tax returns.

[1128] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means. In this invention, the server includes a means for providing a generative AI function to a household accounting application to make expert advice "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and is not temporary but continuous, as if consulting an expert, a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting application, portal site, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for realizing automatic creation and support of complicated tax returns, etc., a means for analyzing expenditure data and automatically generating tax and insurance returns, a means for checking whether there are any errors in the generated returns, and a means for providing support for electronically submitting the generated returns. This allows the user to create accurate returns without much effort and carry out the tax return procedure while receiving advice from an expert.

[1129] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[1130] "Generative AI" is a system that uses artificial intelligence technology to automatically generate text and information based on user input data.

[1131] An "expert" is a person who has advanced knowledge and experience in a particular field and can provide users with appropriate advice.

[1132] "Chat style" refers to a method of communication between the user and the system in real time via text messages.

[1133] "Personal information" refers to all data related to individuals, such as user attributes, data from household accounting apps, and information from portal sites.

[1134] "External information" refers to data obtained from external sources related to the user's household management and filing, such as tax systems, asset management, real estate, financial products, and local living information.

[1135] "Continuous learning" is the process by which the system continually learns from user data and external information in order to provide more accurate advice and support.

[1136] A "tax return" is a document required to declare taxes, insurance, etc.

[1137] "Expense data" refers to information regarding daily expenses that a user enters into the household accounting app.

[1138] "Error checking" is the process of checking whether the generated tax return is error-free.

[1139] "Electronic filing" refers to the filing of a completed tax return online via the Internet.

[1140] The system for implementing this invention includes a household accounting app, a generative AI, an expert advice function, a chat-style communication function, a personal information and external information management function, a continuous learning function, an automatic tax return generation function, an error checking function, and an electronic submission support function.

[1141] Hardware and Software Used

[1142] Hardware: Smartphone

[1143] Software: household accounting apps, electronic payment service apps, generative AI models (e.g. GPT-4)

[1144] Data processing and calculation flow

[1145] 1. Data Acquisition:

[1146] The server obtains the user's expenditure data from the household accounting app.

[1147] API used: Data acquisition API for household accounting app

[1148] Example: GET / api / v1 / expenses

[1149] 2. Data Analysis:

[1150] The server analyzes the acquired expenditure data and extracts information necessary for tax and insurance declarations.

[1151] Libraries used: pandas, numpy

[1152] Example: pandas.DataFrame(expenses).groupby('category').sum()

[1153] 3. Generate tax return:

[1154] The server automatically generates tax returns using a generative AI model based on the analysis results.

[1155] Model used: GPT-4

[1156] Example prompt:

[1157] Generate a tax return based on the user's expenditure data. Below is the user's expenditure data.

[1158] Food expenses: 50,000 yen

[1159] Transportation fee: 10,000 yen

[1160] Medical expenses: 20,000 yen

[1161] Other: 15,000 yen

[1162] 4. Error checking:

[1163] The server checks the generated return for errors.

[1164] Libraries used: regex, jsonschema

[1165] Example: jsonschema.validate(generated_form, schema)

[1166] 5. Submission Support:

[1167] The server provides support for electronic filing of generated returns.

[1168] API to be used: Electronic reporting system submission API

[1169] Example: POST / api / v1 / submit_form

[1170] Examples

[1171] When a user enters their daily expenses into the household accounting app, the data is sent to a server. The server analyzes the acquired expenditure data and extracts the information required for tax and insurance declarations. It then uses a generative AI model to automatically generate a declaration form and checks for errors. Finally, it provides support for electronically submitting the generated declaration form.

[1172] This system allows users to easily prepare accurate tax returns and complete the tax return procedures with the help of expert advice.

[1173] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1174] Step 1:

[1175] The server obtains the user's expenditure data from the household accounting app. The expenditure data entered by the user into the household accounting app is the input. The server obtains the expenditure data using the data acquisition API of the household accounting app. Specifically, the server sends an API request such as GET / api / v1 / expenses and receives the expenditure data. The output is the obtained expenditure data.

[1176] Step 2:

[1177] The server analyzes the acquired expense data and extracts information necessary for tax and insurance declarations. The input is the expense data acquired in step 1. The server aggregates the expense data by category using data analysis libraries such as pandas and numpy. Specifically, it performs operations such as pandas.DataFrame(expenses).groupby('category').sum(). The output is the expense data aggregated by category.

[1178] Step 3:

[1179] The server automatically generates a tax return using a generative AI model based on the analysis results. The input is the expenditure data collected in step 2. The server inputs a prompt sentence into the generative AI model (e.g., GPT-4) to generate the tax return. Specifically, the following prompt sentence is used:

[1180] Generate a tax return based on the user's expenditure data. Below is the user's expenditure data.

[1181] Food expenses: 50,000 yen

[1182] Transportation fee: 10,000 yen

[1183] Medical expenses: 20,000 yen

[1184] Other: 15,000 yen

[1185] The output is the generated tax return.

[1186] Step 4:

[1187] The server checks the generated form for errors. The input is the form generated in step 3. The server validates the form for errors in format and content using libraries such as regex and jsonschema. Specifically, it performs operations like jsonschema.validate(generated_form, schema). The output is the result of the error check.

[1188] Step 5:

[1189] The server supports the electronic submission of the generated tax return. The input is the tax return that passed the error check in step 4. The server submits the tax return online using the submission API of the electronic tax return system. Specifically, it sends an API request such as POST / api / v1 / submit_form. The output is the tax return submission result.

[1190] Furthermore, an emotion engine that estimates the emotion of the user may be combined. That is, the identification processing unit 290 may estimate the emotion of the user using the emotion identification model 59, and perform identification processing using the emotion of the user.

[1191] "Example 1"

[1192] One embodiment of the present invention is a system that combines an emotion engine that recognizes the user's emotions. In this system, when a user inputs their own income and expenditure information into a household accounting app, a generative AI analyzes the user's input information and grasps the user's household financial situation. The emotion engine then recognizes the user's emotions, and the generative AI automatically generates FP advice based on those emotions. For example, if a user feels that they are in a financially difficult situation, the emotion engine recognizes those emotions, and the generative AI generates specific advice on saving based on that information.

[1193] "Example 2"

[1194] In another embodiment, the emotion engine adjusts the content and delivery of advice based on the user's emotion. In this system, if the user is feeling stressed, the emotion engine recognizes the emotion and the generative AI uses that information to generate advice to reduce stress. In addition, if the user is feeling joy, the emotion engine recognizes the emotion and the generative AI uses that information to generate advice to maintain joy.

[1195] "Example 3"

[1196] As yet another embodiment, there is a system in which an emotion engine learns changes in a user's emotions and successively improves the content of advice and the method of providing it based on the results of that learning. In this system, the emotion engine learns changes in a user's emotions and feeds back the results of that learning to the generative AI. The generative AI successively improves the content of advice and the method of providing it based on that feedback. For example, as a result of learning changes in emotions when a user faces financial difficulties, the generative AI uses that information to generate more specific and practical advice.

[1197] The process flow of each embodiment will be described below.

[1198] "Example 1"

[1199] Step 1: The user enters their income and expenditure information into the household accounting app.

[1200] Step 2: The generative AI analyzes the information entered by the user and understands the user's financial situation.

[1201] Step 3: The emotion engine recognizes the user's emotion.

[1202] Step 4: Based on those emotions, the generative AI automatically generates FP advice.

[1203] "Example 2"

[1204] Step 1: If the user is stressed, the emotion engine recognizes that emotion.

[1205] Step 2: The generative AI uses that information to generate advice to reduce stress.

[1206] Step 3: If the user is feeling happy, the emotion engine recognizes that emotion.

[1207] Step 4: The generative AI uses that information to generate advice on how to maintain that joy.

[1208] "Example 3"

[1209] Step 1: The emotion engine learns the user's emotional changes.

[1210] Step 2: The learning results are fed back to the generative AI.

[1211] Step 3: The generative AI uses the feedback to continually improve the content and delivery of advice.

[1212] Example 1

[1213] Next, a description will be given of Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1214] With conventional household accounting apps, even if users input their income and expenditure information, it is difficult to receive specific advice based on that information. Also, consulting a financial planner takes time and money, making it difficult to receive ongoing support. Furthermore, advice is not provided that takes into account the user's emotions, so there is a problem in that users cannot receive appropriate advice based on their situation.

[1215] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means. In this invention, the server includes a means for the user to input household accounting data and the terminal to transmit the data to the server, a means for the server to transmit a prompt to the generative AI model and recognize the user's emotions using an emotion engine, and a means for the server to receive advice from the generative AI model, transmit it to the terminal, and display it to the user. This allows the user to receive specific advice based on income and expenditure information in real time, and to receive continuous support. In addition, since advice is provided that takes the user's emotions into consideration, more appropriate advice can be obtained.

[1216] A "household accounting app" is software that allows users to enter income and expenditure information and manage their household finances.

[1217] "Generative AI" is an artificial intelligence technology that generates advice and information in natural language based on data input by the user.

[1218] A financial planner is an expert who analyzes the financial situation of individuals and companies and suggests optimal asset management and savings methods.

[1219] "Chat style" refers to an interface in which the user and the system exchange information in a dialogue format.

[1220] "Personal information" is information that can identify a specific individual, such as user attributes, household accounting data, and portal site information.

[1221] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[1222] "Continuous learning" is a function that enables the system to continually learn from user data and external information in order to provide more accurate advice.

[1223] An "emotion engine" is software that recognizes emotions from user input data and generates appropriate advice based on those emotions.

[1224] A "prompt" is an input sentence that inputs specific information or a question to a generative AI so that it can generate an appropriate response.

[1225] A "terminal" is a device through which a user inputs household accounting data and interacts with the system. This includes smartphones, tablets, and PCs.

[1226] A "server" is a computer system that stores and processes data and uses generative AI models and emotion engines to provide advice to users.

[1227] This invention is a system that adds generative AI functionality to a household accounting app and automatically generates advice from a financial planner. This system uses a combination of a generative AI model and an emotion engine to provide appropriate advice based on household accounting data entered by the user.

[1228] Hardware and Software Used

[1229] Server: Stores and processes data. Specifically, it uses cloud services (e.g. Amazon Web Services, Google Cloud Platform).

[1230] Terminal: The device through which the user enters household accounting data. This includes smartphones, tablets, and PCs.

[1231] Generative AI model: Uses a natural language generation model (e.g. GPT-4).

[1232] Emotion engine: Uses software to recognize user emotions (e.g. Microsoft Azure's Emotion API).

[1233] Data processing and data calculation

[1234] 1. User input: The user inputs income and expenditure information into the household accounting app. For example, the user enters, "This month's income is 200,000 yen, and expenses are 250,000 yen."

[1235] 2. Data transmission: The terminal transmits the input data to the server. Specifically, the data is transmitted using an HTTP request.

[1236] 3. Data Analysis: The server sends a prompt to the generative AI model to analyze the user's income and expenditure information. For example, it sends a prompt saying, "The user's income is 200,000 yen and his expenditure is 250,000 yen. Please generate advice based on this."

[1237] 4. Emotion recognition: The server uses the emotion engine to recognize the user's emotion. For example, if the user feels "troubled," the emotion engine recognizes that emotion.

[1238] 5. Advice generation: The server receives advice from the generative AI model. For example, it generates advice such as, "Your expenses are higher than your income this month. We recommend that you review your food expenses to save money."

[1239] 6. Providing advice: The server sends the generated advice to the terminal and displays it to the user. Specifically, the server sends data using an HTTP response.

[1240] Examples

[1241] User input: The user enters, "This month's income is 200,000 yen and expenses are 250,000 yen."

[1242] Emotion recognition: The emotion engine recognizes the emotion of "distress."

[1243] Generated advice: The generative AI model generates advice such as, "Your expenses are exceeding your income this month. To save money, we recommend that you review your food expenses."

[1244] Examples of prompt statements

[1245] "A user has entered their income and expenditure information. Their income is 200,000 yen and their expenses are 250,000 yen. The user feels they are in financial difficulty. Based on this, please generate specific advice on how to save money."

[1246] In this way, the system combines an emotion engine and a generative AI model to provide appropriate advice based on the information the user enters into the household accounting app.

[1247] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1248] Step 1:

[1249] The user inputs household accounting data. The user uses a device such as a smartphone or PC to input income and expenditure information into the household accounting app. For example, the user might input "This month's income is 200,000 yen, and expenses are 250,000 yen." The input data includes income and expenditure information.

[1250] Step 2:

[1251] The terminal sends the input data to the server. The terminal sends the balance information entered by the user to the server using an HTTP request. The input is the user's balance information, and the output is the data sent to the server.

[1252] Step 3:

[1253] The server receives the data and sends a prompt to the generative AI model. The server analyzes the received income and expenditure information and sends a prompt to the generative AI model. For example, it sends a prompt saying, "The user's income is 200,000 yen and his expenditure is 250,000 yen. Please generate advice based on this." The input is the income and expenditure information, and the output is the prompt sent to the generative AI model.

[1254] Step 4:

[1255] The server recognizes the user's emotions using the emotion engine. The server recognizes emotions from the user's input data using the emotion engine. For example, if the user feels "in trouble," the emotion engine recognizes that emotion. The input is the user's financial information and emotion information, and the output is the recognized emotion.

[1256] Step 5:

[1257] The server receives advice from the generative AI model. The server receives the advice from the generative AI model and generates advice based on the analysis results and the recognition results of the emotion engine. For example, the server receives advice such as "This month your expenses are higher than your income. To save money, we recommend that you review your food expenses." The input is the response from the generative AI model, and the output is the generated advice.

[1258] Step 6:

[1259] The server sends advice to the terminal. The server sends the generated advice to the terminal using an HTTP response. The input is the generated advice, and the output is the data sent to the terminal.

[1260] Step 7:

[1261] The terminal displays advice to the user. The terminal displays the advice received to the user. For example, it displays in chat format, "This month your expenses exceed your income. To save money, we recommend that you review your food expenses." The input is the advice received from the server, and the output is the advice displayed to the user.

[1262] In this way, the system provides appropriate advice to the user by performing specific actions at each step.

[1263] (Application example 1)

[1264] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1265] Conventional household accounting apps only manage income and expenditures based on data entered by the user, and are unable to provide specific advice based on the user's emotions or circumstances. Additionally, there were no systems that could link with electronic payment services to automatically record spending history, recognize the user's emotions, and provide appropriate advice. This made it difficult for users to accurately grasp their own financial situation and take appropriate measures.

[1266] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means. In this invention, the server includes a means for providing a generative AI function to a household accounting application, making advice by a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and is similar to consulting a financial planner, not just temporarily, but continuously, and in an easy-to-understand manner, as if consulting a financial planner, a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting application, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for realizing automatic creation and support of complicated tax returns, etc., and a means for analyzing a user's spending history in an electronic payment service, recognizing the user's emotions using an emotion engine, and a generative AI providing advice by a financial planner. This allows the user to accurately grasp his or her own financial situation and receive appropriate advice according to his or her emotions.

[1267] A "household accounting app" is software that allows users to enter income and expenditure information and manage their household finances.

[1268] "Generative AI" is an artificial intelligence technology that automatically generates advice and information based on user input data.

[1269] "FP" stands for financial planner, a professional who provides appropriate advice based on an individual's financial situation.

[1270] "Chat style" refers to an interface style in which a user and a system exchange information in a dialogue format.

[1271] "Personal information" refers to user attribute information, data entered into a household accounting app, My Number Portal, etc.

[1272] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[1273] "Continuous learning" is a feature that allows the system to continually learn from user data and provide more accurate advice.

[1274] "Automatic creation of complicated tax returns, etc." is a function that automatically creates tax returns and documents that users need to submit.

[1275] An "electronic payment service" is a service that enables users to make payments online.

[1276] "Spending History" means a record of payments made by a User.

[1277] An "emotion engine" is a technology for analyzing and recognizing user emotions.

[1278] "Means for providing advice" refers to methods or technologies for providing appropriate advice to users.

[1279] The system for implementing this invention is a combination of a household accounting application, a generative AI, an emotion engine, and an electronic payment service. A specific embodiment is described below.

[1280] System Configuration

[1281] 1. Household accounting app:

[1282] Hardware: Smartphone

[1283] Software: Household accounting application

[1284] Function: Users can enter income and expenditure information and manage their household finances.

[1285] 2. Generative AI:

[1286] Hardware: Server

[1287] Software: Generative AI models (e.g. GPT-4)

[1288] What it does: Automatically generate advice based on user-entered data.

[1289] 3. Emotion Engine:

[1290] Hardware: Smartphone

[1291] Software: Emotion recognition engine (e.g. Affectiva SDK)

[1292] Function: Analyze and recognize user emotions.

[1293] 4. Electronic payment services:

[1294] Hardware: Smartphone

[1295] Software: Electronic payment application

[1296] Function: User makes online payments.

[1297] Processing flow

[1298] 1. Data collection:

[1299] Every time a user makes an electronic payment, the spending history is automatically recorded in the household accounting app.

[1300] 2. Emotion recognition:

[1301] The emotion engine analyzes users' spending history and behavioral patterns to recognize their emotions.

[1302] 3. Advice Generation:

[1303] The generative AI generates FP advice based on the results of the emotion engine.

[1304] 4. Advice provided:

[1305] Provide advice to users in chat format.

[1306] Examples

[1307] For example, if a user is stressed about their increasing monthly expenses, the emotion engine will recognize that emotion and the generative AI will offer advice like:

[1308] "It seems like your expenses have been increasing lately. You may be feeling stressed, but why not start by reviewing the amount of coffee you spend each day? You could save about 5,000 yen a month."

[1309] Examples of prompt statements

[1310] User's spending history: [Expense data]

[1311] User sentiment: [emotion data]

[1312] Generate advice.

[1313] This prompt sentence is used to have the generative AI model generate advice.

[1314] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1315] Step 1:

[1316] Every time a user makes an electronic payment, the expenditure history is automatically recorded in the household accounting app. The input is expenditure data from the electronic payment service, and the output is the expenditure history stored in the household accounting app. In concrete terms, the electronic payment service sends expenditure information to the household accounting app, and the household accounting app stores the information in a database.

[1317] Step 2:

[1318] The device sends the expenditure history recorded in the household accounting app to the emotion engine. The input is the expenditure history stored in the household accounting app, and the output is the expenditure data sent to the emotion engine. In concrete terms, the household accounting app sends the expenditure history to the API of the emotion engine.

[1319] Step 3:

[1320] The emotion engine analyzes spending history and behavioral patterns to recognize user emotions. The input is spending history data, and the output is the recognized user emotion data. Specifically, the emotion engine analyzes spending history and identifies emotions such as stress and anxiety.

[1321] Step 4:

[1322] The server sends a prompt to the generative AI based on the results of the emotion engine. The input is emotion data and expenditure history data, and the output is the prompt to be sent to the generative AI. In concrete terms, the server combines emotion data and expenditure history data to generate a prompt and sends it to the generative AI.

[1323] Step 5:

[1324] The generative AI generates advice using FP based on the prompt sentence. The input is the prompt sentence, and the output is the generated advice. In concrete terms, the generative AI analyzes the prompt sentence and generates appropriate advice.

[1325] Step 6:

[1326] The server provides the generated advice to the user in a chat format. The input is the generated advice, and the output is a chat message provided to the user. In concrete terms, the server sends the generated advice to a chat app and displays it to the user.

[1327] Example 2

[1328] Next, a description will be given of Example 2 of the embodiment 2. In the following description, the data processing device 12 is referred to as a "server" and the smart glasses 214 are referred to as a "terminal".

[1329] In conventional household management systems, it was time-consuming and expensive for users to consult with a financial planner, and they often only received temporary advice. It was also difficult to provide advice that took into account the user's emotional state, and there was a lack of personalized support tailored to each individual's lifestyle and emotions. Furthermore, the hassle of creating complicated tax returns and obtaining external information placed a burden on users.

[1330] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for providing a function of a generation AI model to a household management application, making advice by a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in an easy-to-understand and interactive format as if consulting a financial planner, not temporarily but continuously, and in an easy-to-understand manner, as if consulting a financial planner, a means for combining personal information (attributes, household management application, government portal, etc.) with external information (tax system, asset management, real estate, financial products, local life information, etc.) to realize accurate advice and support, a means for analyzing the user's emotion data using an emotion analysis engine, and a means for the generation AI model to generate advice based on the information, and a means for realizing automatic creation and support of complicated tax returns, etc. This allows the user to receive continuous and personalized advice without spending time and money, and to obtain appropriate support according to the emotional state. In addition, the automatic acquisition of external information and automatic creation of tax returns can reduce the burden on the user.

[1331] A "household management application" is software that allows users to manage their income and expenses and grasp the state of their household finances.

[1332] A "generative AI model" is an artificial intelligence algorithm that generates advice and information in natural language based on user input data.

[1333] A "financial planner" is a professional who provides financial planning and investment advice to individuals and businesses.

[1334] "Interactive" means that the user and the system exchange questions and answers in real time.

[1335] "Personal information" refers to all information about users, such as user attribute information, data from household management applications, and data from government portals.

[1336] "External information" refers to information obtained from external sources that is used in combination with the user's personal information, such as information on tax systems, asset management, real estate, financial products, and local living information.

[1337] An "emotion analysis engine" is software that analyzes a user's emotional state and provides appropriate advice based on the results.

[1338] "Returns" means any tax returns or other official reports that you are required to submit.

[1339] "Automated generation" is the process by which a system automatically generates documents or reports based on user-entered data or external information.

[1340] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1341] This invention is a system that combines a user's personal information with external information to provide appropriate advice and support. Furthermore, it is possible to adjust the content and method of providing advice based on the user's emotions using a sentiment analysis engine. This system is implemented using the following hardware and software.

[1342] Hardware and Software Used

[1343] Server: Processes and stores data, for example using a cloud service provider's server (such as AWS or Google Cloud Platform).

[1344] Terminal: A device through which a user accesses the system, such as a smartphone or personal computer.

[1345] Generative AI models: Generate advice based on user input data. For example, natural language processing models (such as GPT-4).

[1346] Sentiment analysis engine: Analyze user sentiment. For example, sentiment analysis API (such as Microsoft Azure's Emotion API).

[1347] Data processing and calculation

[1348] 1. Collection of User's Personal Information:

[1349] User: Uses a terminal to log in to the system and enter personal information, such as age, occupation, income, expenses, etc.

[1350] Terminal: Sends personal information entered by the user to the server.

[1351] Server: Stores the received personal information in a database.

[1352] 2. Obtaining external information:

[1353] Server: Uses external APIs to obtain the latest information on tax systems, asset management, real estate, financial products, local lifestyle information, etc.

[1354] Server: The external information obtained is stored in an internal database and associated with the user's personal information.

[1355] 3. Emotion data analysis:

[1356] User: Answers emotional questions while using the system, for example, "How are you feeling today?"

[1357] Terminal: Sends the user's answer to the server.

[1358] Server: Analyze user sentiment data using the sentiment analysis engine.

[1359] 4. Generate advice:

[1360] Server: Uses a generative AI model to generate advice based on the user's personal information, external information, and emotional data.

[1361] Server: Customize the generated advice for each user.

[1362] 5. Providing advice:

[1363] Server: Sends the generated advice to the user's device.

[1364] Terminal: Display received advice to the user.

[1365] User: View and act on advice via terminal.

[1366] Examples

[1367] Example prompt:

[1368] User demographic information: 30 years old, single, annual income of 5 million yen

[1369] Data from household accounting app: Monthly expenditure is 300,000 yen

[1370] My Number Portal data: Health insurance premiums, pension information

[1371] External information: Latest tax reforms, asset management trends

[1372] Emotional data: High stress levels

[1373] An example of the advice generated:

[1374] We recommend that you review your current expenses and increase your monthly savings. In particular, reducing food and entertainment expenses is effective. In addition, the latest tax reform allows certain investment trusts to receive tax benefits, so please consider them as part of your asset management. To reduce stress, we recommend that you take up a relaxing hobby on the weekends.

[1375] In this way, the system provides personalized advice tailored to the user's lifestyle and emotions.

[1376] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1377] Step 1: Entering user details

[1378] User: Uses a terminal to log in to the system and enter personal information, such as age, occupation, income, expenses, etc.

[1379] Terminal: Sends personal information entered by the user to the server.

[1380] Server: Stores the received personal information in a database.

[1381] Specific behavior:

[1382] Users open the app on their smartphone and enter their age and occupation on the profile screen.

[1383] The terminal transmits the input data to the server in real time.

[1384] The server saves the following information in the database: "User ID: 12345, Age: 30, Occupation: Engineer, Income: 5 million yen."

[1385] Input: User's personal information (age, occupation, income, expenses)

[1386] Output: Personal information stored in a database

[1387] Step 2: Obtaining external information

[1388] Server: Uses external APIs to obtain the latest information on tax systems, asset management, real estate, financial products, local lifestyle information, etc.

[1389] Server: The external information obtained is stored in an internal database and associated with the user's personal information.

[1390] Specific behavior:

[1391] The server periodically sends a request to an external API (e.g. a government tax information API).

[1392] Analyze the data returned from the external API and store the latest tax reform information in a database.

[1393] The server associates the user's income information with up-to-date tax information.

[1394] Input: Information obtained from external API (tax system, asset management, real estate, financial products, local living information)

[1395] Output: External information stored in a database

[1396] Step 3: Analyze the sentiment data

[1397] User: Answers emotional questions while using the system, for example, "How are you feeling today?"

[1398] Terminal: Sends the user's answer to the server.

[1399] Server: Analyze user sentiment data using the sentiment analysis engine.

[1400] Specific behavior:

[1401] The user answers a question in the app by saying "I am stressed."

[1402] The terminal sends this response to the server.

[1403] The server uses a sentiment analysis engine to obtain the analysis result "Stress level: High".

[1404] Input: User's emotional response

[1405] Output: Analyzed emotion data (e.g. stress level)

[1406] Step 4: Generate Advice

[1407] Server: Uses a generative AI model to generate advice based on the user's personal information, external information, and emotional data.

[1408] Server: Customize the generated advice for each user.

[1409] Specific behavior:

[1410] The server sends a prompt to the generative AI model (e.g., GPT-4): "User attribute information: 30 years old, single, annual income of 5 million yen. Emotional data: High stress level. External information: Latest tax reform."

[1411] The generative AI model generates the following advice: "We recommend that you review your current expenses and increase your monthly savings. Reducing food and entertainment expenses would be particularly effective. In addition, the latest tax reforms have made it possible for certain investment trusts to receive tax benefits, so please consider this as part of your asset management. To reduce stress, we recommend that you take up a relaxing hobby on the weekends."

[1412] Input: User personal information, external information, emotional data

[1413] Output: The generated advice.

[1414] Step 5: Providing advice

[1415] Server: Sends the generated advice to the user's device.

[1416] Terminal: Display received advice to the user.

[1417] User: View and act on advice via terminal.

[1418] Specific behavior:

[1419] The server sends the generated advice to the user's smartphone.

[1420] The device will display a message within the app saying, "We encourage you to review your current spending and increase your monthly savings..."

[1421] Users read the advice and take action to actually review their spending.

[1422] Input: Generated advice

[1423] Output: Advice displayed to the user

[1424] In this way, the system provides personalized advice tailored to the user's lifestyle and emotions.

[1425] (Application example 2)

[1426] Next, a description will be given of Application Example 2 of Form Example 2. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1427] In conventional household management applications, it often takes time and money for a user to consult with a financial planner, and the advice is often only temporary. In addition, it is difficult to provide personalized advice according to the user's emotions and lifestyle, and it is not possible to increase user satisfaction. Furthermore, creating and supporting complicated tax returns is time-consuming and burdensome for users. The specific processing by the specific processing unit 290 of the data processing device 12 in application example 2 is realized by the following means.

[1428] In this invention, the server includes a means for providing a function of a generative AI model to a household management application, making advice from a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in a chat format that is easy to understand and that is similar to consulting a financial planner, not just temporarily, but continuously, not temporarily, and that realizes accurate advice and support by continuously learning about personal information (attributes, household management application, government portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically creating and supporting complicated tax returns, etc., a means for recognizing the user's emotions using an emotion engine and providing personalized advice based on the information by the generative AI model, and a means for adjusting the content and method of providing the advice based on the user's emotions. This allows the user to receive continuous and personalized advice while saving time and money.

[1429] A "household management application" is software that enables users to manage household information such as income, expenses, assets, and liabilities.

[1430] A "generative AI model" is an algorithm that uses artificial intelligence to automatically generate advice and information from data.

[1431] A "financial planner" is a professional who provides financial planning and asset management advice to individuals and businesses.

[1432] "Chat format" refers to real-time communication using text messages.

[1433] "Personal information" is information relating to an individual, such as user attributes, data from a household management application, or information from a government portal.

[1434] "External information" refers to information other than personal information, such as tax systems, asset management, real estate, financial products, and local living information.

[1435] "Continuous learning" is the process by which the system constantly learns from new data and improves the accuracy of its advice.

[1436] An "emotion engine" is a technology that recognizes the user's emotions and provides appropriate advice based on that information.

[1437] "Personalized advice" is advice that is customized to a user's individual situation and emotions.

[1438] A "tax return" is a document required for tax and other legal procedures.

[1439] The system for implementing the present invention includes a household management application, a generative AI model, an emotion engine, an external information acquisition module, and a chat interface. The following describes each component in detail and how they work together.

[1440] Household management application

[1441] Users install a household management application on their smartphones. The application provides functions for managing household information such as the user's income, expenses, assets, and liabilities. Users can input their daily income and expenditures and grasp the status of their household finances in real time.

[1442] Generative AI Models

[1443] The server uses a generative AI model to combine the user's household information with external information to generate personalized advice. This generative AI model is implemented in a programming language such as Python and provides optimal advice based on the user's household situation.

[1444] Emotion Engine

[1445] The emotion engine is a technology for recognizing emotions from user input and voice. The server uses the emotion engine to analyze the user's emotions and provides that information to the generative AI model, which can then tailor the content and delivery of advice based on the user's emotions.

[1446] External information acquisition module

[1447] The server uses an external information acquisition module to collect external information such as tax systems, asset management, real estate, financial products, and local living information. This information is acquired through an API and provided to the generative AI model.

[1448] Chat Interface

[1449] The user can receive advice to consult with a financial planner through a chat interface within the home finance management application. The server generates answers to the user's questions in real time and provides them in chat format.

[1450] Examples

[1451] For example, if a user types, "I've been feeling a bit tight on finances lately," the emotion engine will recognize "stress," and the generative AI model will provide advice on "how to review your spending and save money."

[1452] Examples of prompt statements

[1453] A user has an income of 5 million yen, expenses of 3 million yen, assets of 10 million yen, and liabilities of 2 million yen. Recently, he has been feeling a bit tight on finances. What advice would you give to a user who is feeling stressed?

[1454] In this way, a system can be created that provides personalized advice tailored to the user's emotions and lifestyle.

[1455] The flow of the specific process in the application example 2 will be described with reference to FIG.

[1456] Step 1:

[1457] A user installs a household management application on their smartphone and inputs household information such as income, expenses, assets, and liabilities. The input data is managed within the application and sent to the server. An example of input data is income of 5 million yen, expenses of 3 million yen, assets of 10 million yen, and liabilities of 2 million yen.

[1458] Step 2:

[1459] The server uses an external information acquisition module to collect external information such as tax systems, asset management, real estate, financial products, and local life information. The collected external information is obtained through an API and provided to the generative AI model. For example, the tax rate is 20%, and information on stocks, bonds, and real estate as investment options is included.

[1460] Step 3:

[1461] A user inputs a question or request for advice through a chat interface in the household finance management application. For example, the user inputs, "I've been feeling that my household finances are tight lately." This input data is sent to the server.

[1462] Step 4:

[1463] The server uses an emotion engine to recognize emotions from user input. For example, it recognizes "stress" from the input "I've been feeling that my finances are tight lately." The emotion engine performs text analysis and provides emotion data to the generative AI model.

[1464] Step 5:

[1465] The server uses a generative AI model to generate personalized advice by combining the user's household information, external information, and emotion data. For example, based on income of 5 million yen, expenses of 3 million yen, assets of 10 million yen, liabilities of 2 million yen, a tax rate of 20%, investment options, and the emotion "stress," the server generates advice on "how to review expenses and save money."

[1466] Step 6:

[1467] The server provides the generated advice to the user through a chat interface. The user can receive the advice in real time. For example, the advice may be, "Review your spending and consider ways to reduce fixed expenses in order to save money."

[1468] In this way, a system can be created that provides personalized advice tailored to the user's emotions and lifestyle.

[1469] Example 3

[1470] Next, a third embodiment of the third embodiment will be described. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal".

[1471] In conventional household accounting apps and systems that provide advice from financial planners, users have to manually input data and receive advice, which takes a lot of time and effort. In addition, when preparing tax and insurance returns, users must manually organize information and prepare the returns, which is prone to errors. Furthermore, it is difficult to provide advice that responds to changes in the user's emotions, making it difficult to meet individual needs. To solve these issues, a system that can process data and provide advice more efficiently and accurately is needed.

[1472] The specific processing by the specific processing unit 290 of the data processing device 12 in the third embodiment is realized by the following means.

[1473] In this invention, the server includes a means for providing a household accounting app with a generative AI function, making advice from a financial planner "easy to understand and affordable for anyone, anytime," a means for providing advice in a chat format that is easy to understand and similar to consulting a financial planner, not just temporarily, but continuously, and in a manner similar to consulting a financial planner, a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting app, government portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically generating tax and insurance declaration forms based on data entered by the user into the household accounting app, and a means for successively improving the content and method of advice by using an emotion engine that learns changes in the user's emotions and feeds back the learning results to the generative AI. This allows the user to create accurate declaration forms without much effort and receive advice according to their individual needs.

[1474] A "household accounting app" is software that allows users to enter daily income and expenditure data and manage and analyze their household finances.

[1475] "Generative AI" is an artificial intelligence technology that automatically generates information based on input data and provides it to users.

[1476] A financial planner is an expert who analyzes the financial situation of individuals and companies and proposes optimal asset management and tax-saving measures.

[1477] "Chat format" means that users communicate in real time via text messages.

[1478] "Personal information" is information that can identify a specific individual, such as user attributes, data entered into a household accounting app, or information obtained from a government portal.

[1479] "External information" refers to information other than personal information, such as tax systems, asset management, real estate, financial products, and local living information.

[1480] "Continuous learning" is the process by which the system continues to learn based on user data and feedback, gradually improving the accuracy and content of its advice.

[1481] The "emotion engine" is a technology that analyzes changes in a user's emotions and uses the results to improve the content and delivery method of advice.

[1482] A "tax return" is a document required for filing tax and insurance returns.

[1483] "Automatic generation" is the process whereby the system creates the necessary documents and information based on user input data, without manual intervention.

[1484] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[1485] This invention is a system that automatically generates tax and insurance declaration forms based on the data entered by the user into a household accounting application, and furthermore, learns the changes in the user's emotions and successively improves the content and delivery method of advice. This system works in cooperation with the server, the terminal, and the user.

[1486] Hardware and Software Used

[1487] Server: A cloud server is used to process data analysis, tax return generation, and the emotion engine.

[1488] Terminal: The user uses their smartphone or PC to enter data, send data, and receive advice.

[1489] Household accounting app: Software that allows users to enter daily income and expenditure data.

[1490] Generative AI: Artificial intelligence technology that automatically generates information based on input data and provides it to users.

[1491] Emotion engine: Technology that analyzes changes in a user's emotions and uses the results to improve the content and delivery of advice.

[1492] Program Processing

[1493] 1. Data Entry

[1494] The user inputs daily income and expenditure data into the household accounting app. For example, the user inputs information such as "Salary income in December 2023: 300,000 yen" and "Medical expenses: 10,000 yen."

[1495] 2. Data transmission

[1496] The terminal transmits the input data to the cloud server, and the terminal uploads the data to the server via the Internet.

[1497] 3. Data Analysis

[1498] The server analyzes the received data and extracts the necessary information. The server categorizes the data into income, expenses, deductibles, etc., and performs calculations based on tax laws and insurance regulations.

[1499] 4. Generate tax return

[1500] The server automatically generates tax and insurance declaration forms based on the analysis results. The server creates the declaration forms using templates and fills in the necessary fields with data.

[1501] 5. Submit your tax return

[1502] The server sends the generated tax return to the user's terminal. The server generates a PDF format tax return and sends it to the user's email address.

[1503] 6. Check the tax return

[1504] The user checks the tax return on the terminal and makes corrections as necessary. The user opens the tax return, checks the contents, and corrects any errors.

[1505] 7. Filing of tax returns

[1506] User files the return. User prints the return and either mails it or files it online.

[1507] 8. Emotion data input

[1508] Users input their daily events and emotions into the app, such as "I'm tired today" or "I'm in financial difficulty."

[1509] 9. Emotional Data Transmission

[1510] The device sends the data to a cloud server, and the device uploads the emotion data to the server via the Internet.

[1511] 10. Emotion analysis

[1512] The server uses an emotion engine to analyze changes in the user's emotions. The server uses text analysis and emotion recognition algorithms to classify the user's emotions and detect changes.

[1513] 11. Feedback Generation

[1514] The server feeds back the analysis results to the generative AI, which then sends data on changes in emotions to the generative AI to improve its advice.

[1515] 12. Advice Generation

[1516] Based on the feedback, generative AI will improve the content and delivery of advice. Based on the user's emotional data, generative AI will generate more specific and actionable advice.

[1517] 13. Sending Advice

[1518] The server sends the generated advice to the user's device. The server sends the advice to the user's device as a text message or notification.

[1519] 14. Receiving Advice

[1520] The user receives and executes the advice on the device. The user checks the advice and takes action if necessary.

[1521] Examples of prompt statements

[1522] 1. Prompt text about a system that realizes automatic creation and support of complicated tax returns:

[1523] Automatically generate your year-end tax adjustment declaration form based on the income and expenditure data entered into the household accounting app.

[1524] 2. Prompt for advice system using emotion engine:

[1525] If a user types, "I've been having financial trouble lately," generate specific, actionable advice based on what the sentiment engine has learned.

[1526] The flow of the identification process in the third embodiment will be described with reference to FIG.

[1527] Step 1:

[1528] Data Entry

[1529] The user enters daily income and expenditure data into a household accounting app.

[1530] Input: The user enters information such as "Salary income for December 2023: 300,000 yen" and "Medical expenses: 10,000 yen."

[1531] Output: Income and expenditure data is saved in the household accounting app.

[1532] Step 2:

[1533] Data transmission

[1534] The terminal transmits the input data to the cloud server.

[1535] Input: Income and expenditure data stored in the household accounting app.

[1536] Output: The balance data is uploaded to a cloud server via the Internet.

[1537] Step 3:

[1538] 4. Data Analysis

[1539] The server analyzes the received data and extracts the necessary information.

[1540] Input: Income and expenditure data uploaded to the cloud server.

[1541] Data processing: The server classifies data such as income, expenses, and deductibles, and performs calculations based on tax laws and insurance regulations.

[1542] Output: The analysis results include classified balance data and calculation results.

[1543] Step 4:

[1544] Generate tax return

[1545] The server automatically generates tax and insurance declarations based on the analysis results.

[1546] Input: Classified balance data and calculation results obtained as analysis results.

[1547] Data processing: The server creates a declaration form using a template and fills in the required fields with data.

[1548] Output: Auto-generated tax return (PDF format).

[1549] Step 5:

[1550] Submit your tax return

[1551] The server sends the generated declaration to the user's terminal.

[1552] Input: Auto-generated tax return (PDF format).

[1553] Output: The declaration is sent to the user's email address.

[1554] Step 6:

[1555] Check the declaration

[1556] The user checks the tax return on the terminal and makes corrections if necessary.

[1557] Input: The declaration sent to the user's email address.

[1558] Output: Amended return (if necessary).

[1559] Step 7:

[1560] Filing tax return

[1561] The user submits the return.

[1562] Enter: amended return.

[1563] Output: The return is printed and mailed or submitted online.

[1564] Step 8:

[1565] Emotion data input

[1566] Users input their daily events and feelings into the app.

[1567] Input: The user enters a feeling, such as "I'm tired today" or "I'm in financial difficulty."

[1568] Output: The emotion data is stored in the app.

[1569] Step 9:

[1570] Emotion data transmission

[1571] The device sends the data to a cloud server.

[1572] Input: Emotion data stored in the app.

[1573] Output: The emotion data is uploaded to a cloud server via the Internet.

[1574] Step 10:

[1575] Emotion analysis

[1576] The server uses an emotion engine to analyze changes in the user's emotions.

[1577] Input: Emotion data uploaded to the cloud server.

[1578] Data processing: The server uses text analysis and emotion recognition algorithms to classify the user's emotions and detect changes.

[1579] Output: The analysis results in data on changes in user emotions.

[1580] Step 11:

[1581] Feedback Generation

[1582] The server feeds back the analysis results to the generative AI.

[1583] Input: Data about user sentiment changes.

[1584] Output: Feedback data sent to the generative AI.

[1585] Step 12:

[1586] Advice Generation

[1587] Based on the feedback, the generative AI will improve the content and delivery of advice.

[1588] Input: Feedback data.

[1589] Data processing: Generative AI generates more specific and practical advice based on the user's emotional data.

[1590] Output: The generated advice.

[1591] Step 13:

[1592] Send Advice

[1593] The server transmits the generated advice to the user's terminal.

[1594] Input: The generated advice.

[1595] Output: Advice is sent to the user's device as a text message or notification.

[1596] Step 14:

[1597] Receive advice

[1598] The user receives and implements the advice on their device.

[1599] Input: Advice sent to the terminal.

[1600] Output: User reviews the advice and takes action if necessary.

[1601] (Application example 3)

[1602] Next, a description will be given of Application Example 3 of Form Example 3. In the following description, the data processing device 12 will be referred to as a "server", and the smart glasses 214 will be referred to as a "terminal".

[1603] Conventional household accounting apps and advice systems by financial planners have the problem that users have to manually input data and receive advice, which requires a lot of effort and time. In addition, they cannot provide advice based on emotional changes, and they lack concrete and practical support for users' financial difficulties. In addition, preparing tax and insurance declarations is also cumbersome, and mistakes are likely to occur.

[1604] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 3 is realized by the following means.

[1605] In this invention, the server includes: a means for providing a household accounting app with generative AI functions, making advice from a financial planner "easy to understand and affordable for anyone, anytime," a means for providing advice in a chat format that is easy to understand and similar to consulting a financial planner, not just temporarily, but continuously, and in a manner similar to consulting a financial planner; a means for realizing accurate advice and support by continuously learning about personal information (attributes, household accounting app, Mynaportal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.); a means for automatically creating and supporting complicated tax returns, etc.; a means for an emotion engine to learn changes in the user's emotions and successively improve the content and method of providing advice based on the learning results; a means for automatically generating tax and insurance returns based on data entered by the user into the household accounting app; a means for the emotion engine to learn changes in the user's emotions and feed back the information to the generative AI; and a means for the generative AI to generate more specific and practical advice based on the feedback. This significantly reduces the user's effort and makes it possible to provide specific and practical advice based on changes in emotions.

[1606] A "household accounting app" is software that allows users to input and manage household data such as income, expenses, and savings.

[1607] "Generative AI" is an artificial intelligence technology that automatically generates advice and information based on input data.

[1608] A "financial planner" is a professional who provides financial planning and investment advice to individuals and businesses.

[1609] "Chat format" means that users communicate in real time via text messages.

[1610] "Personal information" refers to individual information such as user attributes, household accounting data, and My Number Portal.

[1611] "External information" refers to external information related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[1612] "Continuous learning" is the process by which the system continually learns from user data and behavior to improve the accuracy of its advice.

[1613] A "tax return" is an official document used to declare taxes, insurance, etc.

[1614] The "emotion engine" is a technology that analyzes changes in a user's emotions and uses the results to improve the content and delivery method of advice.

[1615] "Feedback" is the process of providing information for the next action or improvement based on the information or results obtained by the system.

[1616] The system for implementing this invention adds generative AI functionality to a household accounting app, providing financial planner advice "anytime, for anyone, in an easy-to-understand and affordable way." The system provides accurate advice and support through continuous learning based on the user's personal information and external information. It also automatically creates and supports complicated tax returns, and the emotion engine learns the user's emotional changes and, based on the learning results, continuously improves the content and delivery method of the advice.

[1617] Hardware and Software Used

[1618] Hardware: Smartphone

[1619] Software: Python, EmotionEngine library, AIAdvisor library, TaxFormGenerator library

[1620] Data processing and calculation

[1621] 1. Reading household accounting data: The server reads data such as income, expenses, and savings that the user has entered into the household accounting app on their smartphone in JSON format.

[1622] 2. Initializing emotion engine: The server initializes the emotion engine using the EmotionEngine library and analyzes changes in the user's emotions.

[1623] 3. Initialization of the generative AI: The server initializes the generative AI using the AIAdvisor library and automatically generates advice based on the user's household financial situation.

[1624] 4. Initializing the tax return generator: The server initializes the tax return generator using the TaxFormGenerator library, and automatically generates tax, insurance, and other tax returns based on the user's household accounting data.

[1625] 5. Learning changes in emotions: The server analyzes changes in the user's emotions based on household accounting data and feeds that information back to the generative AI.

[1626] 6. Advice generation: Generative AI uses feedback from the emotion engine to generate more specific and actionable advice.

[1627] Examples

[1628] For example, if a user enters "This month's income is 300,000 yen, and expenses are 250,000 yen" into a household accounting app, the server reads this data and uses an emotion engine to analyze changes in the user's emotions. Next, based on this information, generative AI generates specific advice such as "This month's savings are 50,000 yen. To reduce expenses next month, why not review your food expenses?" Tax and insurance declaration forms are also automatically generated, significantly reducing the user's workload.

[1629] Examples of prompt statements

[1630] Develop an application that automatically generates tax and insurance returns based on household accounting data, and learns changes in the user's emotions to provide financial advice. Specifically, create a Python program that includes the following functions:

[1631] 1. Importing household accounting data

[1632] 2. Initializing the emotion engine

[1633] 3. Initialization of generative AI

[1634] 4. Initializing the declaration generator

[1635] 5. Automatic generation of tax returns

[1636] 6. Learn emotional changes

[1637] 7. Generating Advice

[1638] In this way, a specific embodiment of the invention can be shown.

[1639] The flow of the specific process in the application example 3 will be described with reference to FIG.

[1640] Step 1:

[1641] The server reads data in JSON format, such as income, expenses, and savings, that the user has entered into the household accounting app on their smartphone. The input data is obtained from the household accounting app and sent to the server. The server analyzes this data and saves it in an internal database. This allows the user to understand their household financial situation.

[1642] Step 2:

[1643] The server initializes the emotion engine using the EmotionEngine library. The emotion engine analyzes changes in the user's emotions based on the user's household accounting data. The input data is the household accounting data, and the output is the user's emotional state (e.g., stress, relief). The server feeds this emotion data back to the generative AI.

[1644] Step 3:

[1645] The server initializes the generative AI using the AIAdvisor library. The generative AI automatically generates advice based on the user's household finances. The input data are household finance data and emotion data, and the output is specific advice (e.g., how to review spending and increase savings). The server provides this advice to the user.

[1646] Step 4:

[1647] The server initializes the tax return generator using the TaxFormGenerator library. The tax return generator automatically generates tax, insurance, and other tax returns based on the user's household accounting data. The input data is the household accounting data, and the output is an automatically generated tax return. The server provides this tax return to the user.

[1648] Step 5:

[1649] The server learns the changes in the user's emotions based on the household accounting data and feeds that information back to the generative AI. The input data is the household accounting data and emotion data, and the output is the learning results. The server reflects these learning results in the generative AI.

[1650] Step 6:

[1651] The generative AI generates more specific and practical advice based on the feedback from the emotion engine. The input data is the feedback from the emotion engine, and the output is improved advice. The server provides this advice to the user.

[1652] In this way, the system can support users in managing their finances and provide specific, actionable advice based on emotional changes.

[1653] The specific processing unit 290 transmits a 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 a voice indicating a user input for the result of the specific processing. The control unit 46A transmits the voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1654] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search<URL: https: / / openai.com / blog / chatgpt> ) and other generation AIs. The data generation model 58 is obtained by making a neural network perform deep learning. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating a voice, text data indicating a text, and image data indicating an image is input. The data generation model 58 performs inference on the input inference data according to the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1655] Another example of generative AI is Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1656] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1657] [Third embodiment]

[1658] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1659] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1660] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a wide area network (WAN) and / or a local area network (LAN).

[1661] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1662] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs the voice according to instructions from the processor 46.

[1663] Camera 42 is a small digital camera equipped with an optical system including a lens, an aperture, and a shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (e.g., an imaging range defined by an angle of view equivalent to the width of the field of vision of an average healthy person).

[1664] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for transmitting and receiving various types of information between the processor 46 and the processor 28 via the network 54. The transmission and reception of various types of information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is performed in a secure state.

[1665] Fig. 6 shows an example of main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1666] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32, and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1667] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1668] In the headset type terminal 314, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50, and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1669] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1670] "Example 1"

[1671] One embodiment of the present invention is a system that adds generative AI functions to a household accounting app. This system automatically generates advice from a financial planner based on household accounting data entered by the user. The generated advice is provided to the user in a format that is easy for the user to understand, such as a chat format.

[1672] "Example 2"

[1673] Furthermore, as another embodiment of the present invention, there is a system that provides accurate advice and support by combining personal information (attributes, household accounting apps, My Number Portal, etc.) with external information (tax systems, asset management, real estate, financial products, local life information, etc.). This system is capable of providing personalized advice tailored to the user's lifestyle and asset situation.

[1674] "Example 3"

[1675] As another embodiment of the present invention, there is a system that realizes automatic creation and support of complicated tax returns. This system can reduce the time and effort required for users to file tax and insurance returns and prevent mistakes. For example, when creating a tax return for year-end adjustment, the system can automatically generate the return based on the data entered by the user into a household accounting application.

[1676] The process flow of each embodiment will be described below.

[1677] "Example 1"

[1678] Step 1: The user enters their income and expenditure information into the household accounting app.

[1679] Step 2: The generative AI analyzes the information entered by the user and understands the user's financial situation.

[1680] Step 3: The generative AI automatically generates FP advice and provides it to the user.

[1681] "Example 2"

[1682] Step 1: The user enters their income and expenditure information into the household accounting app.

[1683] Step 2: The system combines personal information (attributes, household accounting apps, My Number Portal, etc.) with external information (tax systems, asset management, real estate, financial products, local lifestyle information, etc.) to provide accurate advice and support.

[1684] "Example 3"

[1685] Step 1: The user enters their income and expenditure information into the household accounting app.

[1686] Step 2: The system will automatically create and provide support for complicated tax returns and other documents based on the information entered by the user.

[1687] Step 3: For example, when preparing a year-end tax return, the system automatically generates the return based on the data the user entered into the household accounting app.

[1688] Example 1

[1689] Next, a description will be given of Example 1 of the embodiment 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1690] Conventional household accounting apps allow users to understand their own household finances, but to get professional advice, they must consult a financial planner separately. In addition, the cost and effort required to get advice makes it difficult to receive ongoing support. Furthermore, users must themselves fill out complicated tax returns and gather external information, which places a heavy burden on them. To solve these issues, there is a need for a system that adds generative AI functionality to household accounting apps and automatically generates and continuously provides advice from financial planners.

[1691] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1692] In this invention, the server includes a means for generating a prompt sentence based on household accounting data input by the user and sending it to the generative AI model, a means for the generative AI model to generate advice based on the prompt sentence and for the server to receive the advice, and a means for the server to send the generated advice to the user's terminal. This allows the user to automatically and continuously receive expert advice, reducing the burden of household accounting management.

[1693] A "household accounting app" is software that allows users to input and manage household data such as income, expenses, and savings.

[1694] "Generative AI" is an artificial intelligence technology that automatically generates responses and advice in natural language based on input data.

[1695] A financial planner is an expert who analyzes the financial situation of individuals and families and suggests optimal asset management and savings methods.

[1696] A "prompt sentence" is an instruction sentence input to a generative AI, which contains the information that the AI ​​uses to generate responses and advice.

[1697] A "server" is a computer system whose role is to receive data from users, process it, and send it to the generative AI.

[1698] "Terminal" means the device through which a User enters household accounting data and receives generated advice.

[1699] "Database" refers to an information management system for storing household accounting data and generated advice.

[1700] "Chat format" refers to an interface format for interaction between a user and a system, in which messages are exchanged.

[1701] "Personal information" refers to individual information such as user attributes, household accounting data, portal sites, etc.

[1702] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[1703] "Continuous learning" is the process by which generative AI continues to learn from user data and external information in order to provide more accurate advice.

[1704] "Returns" means any tax returns or other official reports that you are required to submit.

[1705] This invention is a system that adds generative AI functionality to a household accounting app, automatically generating advice from a financial planner based on household accounting data entered by the user, and providing it in chat format. This system enables users to efficiently manage their household finances and receive continuous expert advice.

[1706] Hardware and Software Used

[1707] Hardware

[1708] Server: Receives, stores, and analyzes data, sends prompts to the generative AI model, receives generated advice, and sends it to the user device.

[1709] Terminal: The device (smartphone, tablet, PC, etc.) where the user enters their household accounting data and receives the generated advice.

[1710] software

[1711] Financial accounting app: An application that allows users to enter data such as income, expenses, and savings goals.

[1712] Generative AI model: An artificial intelligence technology that generates advice based on an input prompt (e.g., OpenAI’s GPT-4).

[1713] Database: An information management system (e.g. MySQL, PostgreSQL) for storing the accounting data and the generated advice.

[1714] Data processing and calculation

[1715] Enter and send household accounting data

[1716] The user uses the household accounting app to input data such as income, expenses, and savings goals. For example, monthly income is 300,000 yen, rent is 100,000 yen, food expenses are 50,000 yen, transportation expenses are 20,000 yen, other expenses are 30,000 yen, and savings goal is 50,000 yen. The device then transmits this data to the server.

[1717] Data storage and analysis

[1718] The server saves the received household accounting data in the database. Next, the server generates a prompt based on the saved data. For example, it generates the following prompt:

[1719] The user's monthly income is 300,000 yen, and his expenses are as follows: rent 100,000 yen, food 50,000 yen, transportation 20,000 yen, other 30,000 yen. The user's savings goal is 50,000 yen per month. Based on this, please provide some advice as a financial planner.

[1720] Generating and serving advice

[1721] The server sends the generated prompt sentence to the generative AI model. The generative AI model generates advice based on the prompt sentence. For example, it generates advice like the following:

[1722] Your monthly income is 300,000 yen and your total expenses are 200,000 yen. To achieve your savings goal of 50,000 yen, you can save the remaining 50,000 yen. Review your food expenses and other expenses and see if there are any areas where you can save money. It would also be a good idea to think about ways to increase your income.

[1723] The server receives the generated advice and transmits it to the user's terminal, where the user can receive the advice in chat format.

[1724] Examples

[1725] For example, when a user opens a household accounting app and enters income and expenditure data, the app provides an input form. After the user finishes entering the data, he or she presses the "Submit" button. The device sends this data to the server, which then stores the data in a database. The server then sends a prompt to the generative AI model and receives the generated advice. Finally, the server sends the advice to the user's device, and the user checks the advice in the app.

[1726] In this way, users can automatically and continuously receive expert advice, easing the burden of managing their household finances.

[1727] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1728] Step 1:

[1729] The user inputs household accounting data

[1730] The user uses the household accounting app to input data such as income, expenses, and savings goals. For example, the user can input information such as monthly income of 300,000 yen, rent of 100,000 yen, food expenses of 50,000 yen, transportation expenses of 20,000 yen, other expenses of 30,000 yen, and savings goal of 50,000 yen. The input data is temporarily stored on the device.

[1731] Step 2:

[1732] The terminal sends the input data to the server

[1733] The terminal transmits the household accounting data entered by the user to the server. This transmission is secure using the HTTPS protocol. The input data includes information such as income, expenses, and savings goals.

[1734] Step 3:

[1735] The server saves the data to a database

[1736] The server stores the received household accounting data in a database. A relational database such as MySQL or PostgreSQL is used as the database. The stored data includes information such as the user's income, expenses, and savings goals.

[1737] Step 4:

[1738] The server sends a prompt to the generative AI model.

[1739] The server generates a prompt sentence based on the saved household accounting data. For example, it generates a prompt sentence like, "The user's monthly income is 300,000 yen, and the expenses are as follows: rent 100,000 yen, food 50,000 yen, transportation 20,000 yen, other 30,000 yen. The user's savings goal is 50,000 yen per month. Based on this, please provide some advice as a financial planner." The generated prompt sentence is sent to the generative AI model.

[1740] Step 5:

[1741] Generative AI models generate advice

[1742] A generative AI model (for example, OpenAI's GPT-4) generates advice based on the prompt text sent from the server. The generative AI model analyzes the household accounting data included in the prompt text and generates appropriate advice. For example, it generates advice such as, "Your monthly income is 300,000 yen, and your total expenses are 200,000 yen. To achieve your savings goal of 50,000 yen, you can save the remaining 50,000 yen. Please review your food expenses and other expenses and consider whether there are any areas where you can save money. It would also be a good idea to think about ways to increase your income."

[1743] Step 6:

[1744] The server receives the generated advice

[1745] The server receives advice generated from the generative AI model in a format that is easy for the user to understand.

[1746] Step 7:

[1747] The server sends advice to the device

[1748] The server transmits the generated advice to the user's terminal, again securely using the HTTPS protocol. The transmitted data is the generated advice.

[1749] Step 8:

[1750] User receives advice

[1751] The user receives the generated advice via their device. The advice is displayed in chat format, and the user can use it to review and improve their household finances.

[1752] (Application example 1)

[1753] Next, a description will be given of Application Example 1 of Form Example 1. In the following description, the data processing device 12 will be referred to as a "server", and the headset type terminal 314 will be referred to as a "terminal".

[1754] Conventional household accounting apps require users to manually input data, and require separate consultation with a financial planner (FP) to receive advice. This is time-consuming for users, making it difficult for them to continue using the apps. In addition, when using electronic payment services, expenditure data is not automatically reflected in the household accounting app, making expenditure management cumbersome.

[1755] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1756] In this invention, the server includes a means for providing a generative AI function to a household accounting app, making advice from a financial planner "easy to understand and affordable for anyone at any time," a means for providing advice in chat format that is easy to understand and similar to consulting a financial planner, not just one-time but continuous, not one-time, but continuous, and provides accurate advice and support through continuous learning of personal information (attributes, household accounting app, My Number Portal, etc.) and external information (tax system, asset management, real estate, financial products, local life information, etc.), a means for automatically creating and supporting complicated tax returns, etc., and a means for automatically recording expenditure data in a household accounting book when using an electronic payment service, analyzing the data with a generative AI, and providing advice from a financial planner in chat format. This allows users to manage their expenditure data hassle-free and receive accurate advice on an ongoing basis.

[1757] A "household accounting app" is software that allows users to record their daily income and expenses and manage their household finances.

[1758] "Generative AI" is an artificial intelligence technology that automatically generates responses and suggestions for specific tasks based on data entered by the user.

[1759] "FP" stands for financial planner, a professional who provides financial planning and investment advice to individuals and companies.

[1760] "Chat style" refers to an interface style in which a user and a system exchange information in a dialogue format.

[1761] "Personal information" refers to information about individuals contained in user attributes, data from household accounting apps, My Number Portal, etc.

[1762] "External information" refers to information obtained from external sources related to the user's household management, such as tax systems, asset management, real estate, financial products, and local living information.

[1763] "Continuous learning" is a function that enables the system to continually learn from user data and external information in order to provide more accurate advice.

[1764] An "electronic payment service" is an online payment system that enables users to pay for goods and services via the Internet.

[1765] "Expense data" refers to information such as the amount, date, and category when a user purchases a product or service.

[1766] "Analysis" is the process of analyzing collected data and extracting meaningful information and patterns.

[1767] In order to implement this invention, it is necessary to build a system in which a household accounting app is given generative AI functionality, expenditure data is automatically recorded in the household accounting book when using electronic payment services, and the generative AI analyzes the data and provides advice from a financial planner in chat format.

[1768] The server collects the user's spending data and analyzes it using a generative AI model. Specifically, the server automatically obtains spending data from the user's electronic payment service and records it in the household accounting app. At this time, the spending data is organized by category and displayed so that the user's household financial situation can be seen at a glance.

[1769] Next, the server uses a generative AI model to generate FP advice based on the user's spending data. This generative AI model uses OpenAI's GPT-3 and other models. The generated advice is provided to the user in a chat format that is easy for the user to understand. For example, the following prompt sentences are used:

[1770] User spending data: {"2023-10-01": {"food": 5000, "transport": 2000, "entertainment": 3000}, "2023-10-02": {"food": 4500, "transport": 1500, "entertainment": 2500}, "2023-10-03": {"food": 4000, "transport": 1000, "entertainment": 2000}}

[1771] As a financial planner, you can provide advice based on this data.

[1772] The generated advice may look something like this:

[1773] FP Tip: Food costs make up a large portion of your total expenses. You can save by buying in bulk once a week and eating out less. You should also reassess your transportation costs. Using a commuter pass for public transportation can help you save even more.

[1774] Users can access the household accounting app using a smartphone, tablet, or other device and check the generated advice. When users input a question, the generative AI model generates an answer in real time and provides it in chat format.

[1775] The system allows users to effortlessly manage their spending data and receive accurate advice on an ongoing basis. The hardware required is a smartphone or tablet with an internet connection, and a server. The software uses Python, OpenAI API, and JSON files.

[1776] The flow of the specific process in the application example 1 will be described with reference to FIG.

[1777] Step 1:

[1778] The server automatically obtains spending data from the user's electronic payment service. The input is the transaction data of the user's electronic payment service, and the output is spending data organized by category. Specifically, the server accesses the electronic payment service through an API to obtain the user's spending information. This data is stored in the form of dates, categories, amounts, etc.

[1779] Step 2:

[1780] The server records the acquired expenditure data in the household accounting app. The input is the expenditure data organized by category acquired in step 1, and the output is the expenditure data saved in the household accounting app. Specifically, the server writes the expenditure data to the database of the household accounting app so that the user can check it through the app.

[1781] Step 3:

[1782] The server uses a generative AI model to generate FP advice based on the expenditure data recorded in the household accounting app. The input is the expenditure data stored in the household accounting app, and the output is the generated FP advice. Specifically, the server inputs the expenditure data as a prompt sentence into the generative AI model to generate advice. An example of the prompt sentence is as follows:

[1783] User spending data: {"2023-10-01": {"food": 5000, "transport": 2000, "entertainment": 3000}, "2023-10-02": {"food": 4500, "transport": 1500, "entertainment": 2500}, "2023-10-03": {"food": 4000, "transport": 1000, "entertainment": 2000}}

[1784] As a financial planner, you can provide advice based on this data.

[1785] Step 4:

[1786] The server provides the generated advice to the user in chat format. The input is the FP advice generated in step 3, and the output is the advice in chat format displayed on the user's device. Specifically, the server sends the generated advice to the user's device in the form of a chatbot so that the user can check it through the app.

[1787] Step 5:

[1788] When a user enters a question, the server uses a generative AI model to generate an answer in real time and provides it in chat format. The input is the question entered by the user, and the output is the generated answer. Specifically, the server inputs the user's question as a prompt sentence into the generative AI model and generates an answer. The generated answer is displayed on the user's device in chat format.

[1789] Example 2

[1790] Next, a second embodiment of the second form will be described. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal".

[1791] Advice provided by traditional household accounting apps and financial planners (FPs) is temporary, making it difficult to provide ongoing support. In addition, there is a lack of systems that provide accurate advice by combining personal information and external information, making it difficult for users to receive personalized advice based on their lifestyle and asset status. Furthermore, there is a lack of automated creation and support for cumbersome tax returns.

[1792] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for combining personal information (attributes, household accounting application, portal site, etc.) with external information (tax system, asset management, real estate, financial products, local life information, etc.) to provide accurate advice and support, a means for generating personalized advice based on the user's lifestyle and asset status, a means for encrypting personal information input by the user and transmitting it to the server using a secure communication protocol, a means for the server to store the received personal information in a database, a means for the server to collect external information and store it in a database, a means for the server to perform data analysis using a generation AI model, a means for the server to generate advice based on the analysis results, a means for the server to transmit the advice generated by the server to the terminal, and a means for the terminal to display the advice to the user. This allows the user to receive continuous and personalized advice.

[1793] "Personal information" refers to a series of data about a user, such as user attribute information, data from a household accounting app, and information from a portal site.

[1794] "External information" refers to data collected from external sources related to the user's lifestyle and asset management, such as tax systems, asset management, real estate, financial products, and local lifestyle information.

[1795] A "server" is a computer system that receives, stores, and processes data submitted by users.

[1796] A "database" is a data management system for storing personal information and external information received by the server.

[1797] A "generative AI model" is an artificial intelligence model that performs data analysis based on a user's personal information and external information, and generates advice.

[1798] "Personalized advice" is advice that is individually customized based on a user's lifestyle and financial situation.

[1799] "Encryption" is a technique for converting data using a specific algorithm in order to transmit the data securely.

[1800] A "communications protocol" is a technology that defines the rules and procedures for sending and receiving data safely.

[1801] "Data analytics" is the process of using generative AI models to analyze a user's personal information and external information to extract meaningful information.

[1802] A "terminal" is a device used by a user, such as a smartphone or computer.

[1803] The "means for displaying advice" is a function for visually presenting to the user the advice that the terminal receives from the server.

[1804] The present invention is a system that combines personal information and external information to provide appropriate advice and support. A specific embodiment of this system will be described below.

[1805] Hardware and Software Configuration

[1806] Hardware:

[1807] Server: A high-performance computer system (e.g., a general-purpose server)

[1808] Device: The smartphone or computer used by the user

[1809] software:

[1810] Database Management System: Database software such as MySQL

[1811] Generative AI models: Artificial intelligence models such as OpenAI GPT-4

[1812] Communication Protocol: A secure communication protocol such as HTTPS

[1813] Data processing and calculation

[1814] Enter and submit your personal information:

[1815] The user uses the terminal to access the system's dedicated application or website and inputs personal information such as attribute information (age, occupation, income, etc.), data from the household accounting application, information from the portal site, etc. The terminal encrypts the input personal information and transmits it to the server using a secure communication protocol (e.g. HTTPS).

[1816] Data Retention:

[1817] The server stores the received personal information in a database management system (e.g. MySQL). When storing, checks are performed to ensure data integrity and security.

[1818] Collection of external information:

[1819] The server uses external APIs and web scraping technology to collect external information such as tax systems, asset management, real estate, financial products, and local life information. The collected information is stored in a database.

[1820] Data analysis and advice generation:

[1821] The server combines the stored personal information with external information and performs data analysis using a generative AI model (e.g., OpenAI GPT-4). Specifically, it analyzes the user's income and expenditure patterns and derives optimal asset management and savings methods. The server generates specific advice for the user based on the analysis results of the generative AI model.

[1822] Sending and viewing advice:

[1823] The server sends the generated advice to the terminal. During transmission, data encryption and a secure communication protocol are used. The terminal displays the received advice to the user. The user can check the specific advice through an application or a website.

[1824] Examples of concrete examples and prompts

[1825] Examples:

[1826] The user opens a dedicated application on their smartphone and enters their monthly income (300,000 yen) and expenses (250,000 yen). The device encrypts this information and sends it to the server using HTTPS. The server stores the received information in a MySQL database. The server then collects the latest tax information and asset management trends from an external API and stores them in the database.

[1827] The server uses OpenAI GPT-4 to analyze the user's income and spending patterns and generates advice such as "To reduce spending this month, it is effective to cut food expenses by 10%." ...

Claims

1. A means for generating a prompt sentence that instructs a generation AI model to prepare advice as a financial planner based on household accounting data input by a user; A means for generating advice using the generative AI model based on the household accounting data and the prompt sentence; means for providing the generated advice to the user; A system having

2. means for recognizing an emotion of the user using an emotion engine; generating advice using the generative AI model based on the user's emotion, the household accounting data, and the prompt sentence; The system of claim 1 .

3. Providing said advice in a chat format; A system according to claim 1 or claim 2.

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