System

Abstract

A system is provided.SOLUTION: A system, comprising: means for collecting income data, expense data, and savings goals from a user; means for calculating a savings amount by subtracting expenses from income based on the collected income data, expense data, and savings goals; means for generating an alert message when the savings amount is less than the savings goals; means for generating advice regarding asset management and savings management using the calculated savings amount and the generated alert message; and means for displaying the generated advice and alert message 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 an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

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

[0004] Approximately 30% of single people have zero savings, yet they have a strong desire to save. Furthermore, many people face difficulties due to a lack of knowledge about asset management and tax procedures, as well as time constraints. This creates a challenge that makes it difficult to achieve effective and efficient asset management and savings. The purpose of this invention is to solve these challenges and provide a system that easily and effectively supports individual asset management. [Means for solving the problem]

[0005] The present invention provides a system including: means for collecting income data, expenditure data, and savings goals from a user; means for calculating a savings potential by subtracting expenditures from income based on the collected income data, expenditure data, and savings goals; means for generating an alert message when the savings potential falls below the savings target; means for generating advice on asset management and savings investment using the calculated savings potential and the generated alert message; and means for displaying the generated advice and alert message to the user. The system also includes means for transmitting the collected income data, expenditure data, and savings goals to a server and means for receiving analysis results from the server, and the generated advice includes specific advice on asset management, tax treatment, and expenditure management. In this way, users can easily receive services equivalent to those of a financial planner no matter where they are, enabling them to achieve sound asset management.

[0006] "User Data" is information about a user's income, expenses, and savings goals.

[0007] A "means for collecting" is a method including an interface and data acquisition process for inputting or acquiring the required data from a user.

[0008] A "server" is a computer system that analyzes data and generates advice.

[0009] The "analysis means" is a method including algorithms and processes for analyzing the collected data and calculating the user's financial situation and savings potential.

[0010] The "savings available amount" is the amount remaining after subtracting the expenditure data from the user's income data, and indicates the funds available for savings and investments.

[0011] An "alert message" is a warning message that is generated to alert the user when the amount of savings available falls below the user's savings goal.

[0012] The "means for generating advice" is a method including an algorithm and a process for creating specific advice for a user on asset management, savings management, tax treatment, etc. based on the analysis results.

[0013] "Means for displaying" refers to a method, including display technology and user interface, for presenting the generated advice or alert message to the user.

[0014] "Asset management" refers to activities that centrally manage and optimize a user's income, expenses, and savings.

[0015] "Savings management" refers to activities that include methods and means for efficiently increasing assets by utilizing the amount of savings that a user can make.

[0016] The above are definitions of important words included in the patent claims for the "AI Money Support" system. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0025] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0038] The present invention enables users to effectively and efficiently manage their assets and savings through the "AI Money Support" system, which collects, analyzes, and provides advice on income, expenditure, and savings goals provided by users.

[0039] Specifically, the system consists of the following steps:

[0040] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0041] Next, the device sends the collected data to the server. The server analyzes the received data and calculates the user's possible savings by subtracting expenses from their income. If the possible savings amount falls below the savings goal, the server generates a warning message. For example, if the user enters a monthly income of 300,000 yen and monthly expenses of 250,000 yen, the possible savings amount will be 50,000 yen. In this case, if the user's savings goal is 40,000 yen, there is no problem, but if it falls below 50,000 yen, a warning message will be generated.

[0042] The server then generates specific advice for the user based on the analysis results, including advice on daily spending management, tax advice for filing tax returns, and advice on investment methods such as hometown tax donations and NISA savings accounts, allowing users to understand specific and practical ways to manage their assets.

[0043] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0044] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's calculated savings potential is 50,000 yen, so no warning message will be displayed. The system will provide the user with advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses," as well as tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently," and investment advice such as "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[0045] This allows users to easily receive services equivalent to those of a financial planner wherever they are, enabling sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[0046] The processing flow will be explained below.

[0047] Step 1:

[0048] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[0049] Step 2:

[0050] The terminal then prompts the user to "Enter your monthly expenses," and the user enters their monthly expenses. The terminal then prompts the user to "Enter your monthly savings goal," and the user enters their savings goal.

[0051] Step 3:

[0052] The device sends the collected data (income data, expenditure data, savings goals) to the server.

[0053] Step 4:

[0054] The server analyzes the received data. The server subtracts the user's expenses from their income to calculate the amount they can save. For example, if their income is 300,000 yen and their expenses are 250,000 yen, their savings amount is 50,000 yen.

[0055] Step 5:

[0056] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[0057] Step 6:

[0058] The server then uses the analysis results to generate specific advice for the user, including information on spending management, tax treatment, and investment options.

[0059] Step 7:

[0060] The device displays advice and warning messages received from the server to the user. For example, it displays information such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures" or "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[0061] This is the specific flow of processing in the "AI Money Support" system. Users can implement effective asset management based on this advice.

[0062] Example 1

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

[0064] Currently, many people find it difficult to effectively manage their income and expenditures and manage their savings, especially because they have limited opportunities to receive specific advice on achieving their savings goals. Furthermore, there are insufficient systems that analyze income and expenditure data and automatically suggest appropriate measures based on the results. This makes it difficult for users to easily grasp their income and expenditure situation and implement improvement measures. Therefore, an objective of the present invention is to provide a system that allows users to effectively and efficiently manage their assets and manage their savings.

[0065] 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.

[0066] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings goals, means for generating a warning message when the savings potential falls below the savings target, means for generating advice on asset management and savings management using the calculated savings potential and the generated warning message, and means for displaying the generated advice and warning message to the user, thereby enabling the user to clearly understand the income and expenditure situation and to appropriately manage assets and savings.

[0067] "Income information" is data indicating the amount of regular income of the user.

[0068] "Expense information" is data indicating the amount of regular expenditures of a user.

[0069] A "savings goal" is a target value that indicates the amount of savings that a user wishes to achieve within a certain period of time.

[0070] "Means for collecting" refers to methods and devices for obtaining income information, expenditure information, and savings goals from a user.

[0071] The "means for calculating the savable amount by subtraction" refers to a method or device for calculating the savable amount calculated by subtracting expenditure information from income information.

[0072] The term "means for generating a warning message" refers to a method or device that generates a message to alert the user when the amount of savings available falls below the savings goal.

[0073] The "means for generating advice" refers to a method or device that provides a user with suggestions or recommendations regarding asset management and savings management based on the calculated savings potential and the generated warning message.

[0074] The "displaying means" refers to a method or device for displaying the generated advice and warning messages on a terminal used by a user.

[0075] "Means for transmitting to a server" refers to a method or device for transmitting the collected income information, expenditure information, and savings goals to a server via the Internet or other communications network.

[0076] "Means for receiving the analysis results" refers to a method or device for receiving the analyzed data and results sent from the server at the user's terminal.

[0077] "Wealth Management Advice" means specific suggestions and recommendations for effectively managing and growing your assets.

[0078] "Tax advice" refers to specific suggestions and recommendations for calculating and filing taxes efficiently.

[0079] "Expense Management Advice" refers to specific suggestions and recommendations for effectively managing a user's day-to-day expenses.

[0080] The present invention relates to an "AI Money Support" system that collects income information, expenditure information, and savings goals, and provides advice for effective asset management and savings management. The system operates using a server, a terminal, and a generative AI model.

[0081] Hardware and software used

[0082] Hardware: Devices used by users (e.g. smartphones, PCs), servers

[0083] Software: User interface software (e.g., web applications, mobile apps), data analysis software (e.g., Python + Pandas), advice translators (e.g., ChatGPT®), warning generation modules (e.g., JavaScript®)

[0084] Basic operation of the system

[0085] 1. Data Collection:

[0086] User: Enters income and expenditure information such as monthly income, monthly expenses, and savings goal into the device. For example, the user enters this information into a smartphone app: "Monthly income: 300,000 yen, monthly expenses: 250,000 yen, savings goal: 40,000 yen."

[0087] Device: Stores the provided data in local storage and keeps it temporarily in memory. For example, store the data as follows: localStorage.setItem('income', '300000').

[0088] 2. Data Transmission and Analysis:

[0089] On the device: Send the collected data to the server using the HTTPS protocol. For example, send it as axios.post('https: / / api.example.com / data', data).

[0090] Server: Analyzes the received data using Python's Pandas library and calculates the potential savings. Specifically, it calculates savings_capacity = income - expenses.

[0091] 3. Warning message generation and advice generation:

[0092] Server: If the savings potential is below the target, generate a warning message. Example: "Saving potential is below the target. Please review your spending."

[0093] Server: Using a generative AI model (e.g., ChatGPT), a prompt such as "Please provide asset management advice for a user with a monthly income of 300,000 yen, expenses of 250,000 yen, and a savings goal of 40,000 yen" is input, and specific advice is generated.

[0094] 4. Displaying the results:

[0095] Server: Sends generated advice and warning messages to the device in JSON format, for example: response.json = {"advice": "...", "warning": "..."}.

[0096] Terminal: Display the received data in a user interface. For example, the HTML ... Insert a message inside.

[0097] 5. User Behavior:

[0098] User: Based on the advice and warning messages provided, they manage their spending and make investments. For example, they take concrete actions such as starting to keep a household budget or making use of hometown tax donations.

[0099] As an example of how the system works, let's take the case where a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. In this case, the system calculates that the user's possible savings amount is 50,000 yen, so no warning message is generated. Based on this data, the server generates specific advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses." It also suggests tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently" and investment advice such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[0100] Example prompt: "Monthly income: ¥300,000, monthly expenses: ¥250,000, savings goal: ¥40,000. Please provide specific advice to the user in this situation."

[0101] As described above, the present invention is a system that supports effective asset management by providing users with specific and practical advice on asset management and savings management.

[0102] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0103] Step 1:

[0104] The user enters their monthly income, monthly expenses, and savings goal into the terminal.

[0105] Specifically, the user enters "monthly income 300,000 yen, monthly expenses 250,000 yen, savings goal 40,000 yen" into the input form of the smartphone app. This is the input data. The output is that the input data is saved on the device.

[0106] Step 2:

[0107] The device saves the input data in local storage.

[0108] Specifically, the device uses commands such as localStorage.setItem('income', '300000') to store income information, expenditure information, and savings goals. The input is the data entered by the user. The output is the data stored in local storage.

[0109] Step 3:

[0110] The terminal transmits the collected data to the server.

[0111] Specifically, the terminal sends data using the HTTPS protocol, such as axios.post('https: / / api.example.com / data', data). The input is the data stored in local storage. The output is the data sent to the server.

[0112] Step 4:

[0113] The server parses the received data.

[0114] Specifically, the server analyzes the data using Python's Pandas library. For example, the code savings_capacity = income - expenses is used to calculate the amount of savings that can be made. The input is the data sent from the terminal, and the output is the calculated amount of savings that can be made.

[0115] Step 5:

[0116] The server checks the savings amount and generates a warning message if necessary.

[0117] Specifically, the server uses conditional branching to execute the following process: if savings_capacity < target_savings: warning_message = "Your savings potential is below your target. Please review your spending." The inputs are the calculated savings potential and the savings target. The output is a warning message.

[0118] Step 6:

[0119] The server uses the generative AI model to generate specific advice.

[0120] Specifically, the server inputs the prompt statement "Please provide asset management advice for the user's monthly income of 300,000 yen, expenses of 250,000 yen, and savings goal of 40,000 yen" into the generative AI model and generates advice. The input is the prompt statement and the user's data. The output is the generated advice.

[0121] Step 7:

[0122] The server sends generated advisory and warning messages to the terminal.

[0123] Specifically, the server packages the data in JSON format and sends it to the terminal as response.json = {"advice": "Your savings goal is achievable. Manage your daily expenses and refer to the tax advice for your tax return.", "warning": "Your savings potential is below your goal. Please review your expenses"}. The input is the generated advice and warning message. The output is the message sent to the terminal.

[0124] Step 8:

[0125] The terminal displays the received data on the user interface.

[0126] Specifically, the device uses HTML, CSS, and JavaScript to Your savings goals are achievable - take control of your daily expenses and get tax advice for your tax return. The input is the data sent from the server. The output is the message displayed on the user interface.

[0127] Step 9:

[0128] The user takes action based on the displayed advice and warning messages.

[0129] Specific actions that users take include reviewing income and expenditures, keeping a household account book, processing taxes, and using hometown tax donations. The input is the displayed advice and warning messages. The output is the specific actions taken by the user.

[0130] (Application example 1)

[0131] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0132] In today's society, many individuals lack knowledge about asset management and savings investments and are time-constrained. As a result, it is difficult to achieve effective savings goals and properly manage their assets. To solve these challenges, a user-friendly system is needed. Furthermore, there is a need for systems that can manage expenses in real time through integration with electronic payment platforms and provide detailed asset management advice using generative AI models.

[0133] 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.

[0134] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income data, expenditure data, and savings goals, and means for generating a warning message when the savings potential falls below the savings target. This allows the user to collect expenditure and income data in real time and receive detailed asset management advice. Furthermore, by displaying the generated advice and warning message to the user, the user can quickly understand their current expenditure and savings situation and manage their assets effectively and efficiently.

[0135] A "user" is an individual who utilizes the system to provide income data, expenditure data, and savings goals.

[0136] "Income Data" is information about all income earned by a user.

[0137] "Expense Data" is information about all expenses made by a user.

[0138] A "savings goal" is the amount of savings a user wants to achieve within a specific time period.

[0139] "Savings potential" is the amount you can actually save, obtained by subtracting expenses from income.

[0140] A "warning message" is a message generated to alert the user when the amount of savings available falls below the savings goal.

[0141] "Asset management advice" is a proposal for specific asset management and savings methods formulated based on the user's income, expenses, and savings.

[0142] An "electronic payment platform" is an online system that provides users with payment methods they use on a daily basis.

[0143] "Real time" refers to the fact that processing is carried out almost simultaneously at the moment an event occurs.

[0144] A "generative AI model" is an artificial intelligence model used to analyze user data and generate advice on asset management.

[0145] A "server" is a computer system that analyzes data collected from users and generates results.

[0146] "Analysis results" are the results of calculations and analyses performed by the server based on data provided by the user.

[0147] The system for implementing this invention works in conjunction with the electronic payment platform that users use on a daily basis to collect and analyze income data, expenditure data, and savings goals in real time. Specifically, the system automatically collects data when users perform daily transactions via their smartphones and transmits it to a server.

[0148] Program Overview

[0149] The server calculates the user's potential savings based on the collected income data, expenditure data, and savings goals, and generates a warning message if the savings goal is not reached. This process is performed using programming languages ​​such as Python. It also uses a generative AI model to generate specific advice on asset management for the user. This advice includes reviewing spending, streamlining tax procedures, and suggesting investment methods such as hometown tax payments and NISA savings.

[0150] Users can check these generated advice and warning messages in real time through smartphone applications that run on iOS and Android platforms, and the user interface is often implemented using frameworks such as React Native.

[0151] Hardware and Software

[0152] The following hardware and software are used to implement this system:

[0153] Hardware: Smartphone (iOS device, Android device)

[0154] software:

[0155] Python: Used to calculate savings potential and run generative AI models

[0156] React Native: Used to develop smartphone applications

[0157] Server platform: Cloud services such as AWS (registered trademark) and Google (registered trademark) Cloud Platform

[0158] Data processing and calculation

[0159] The server calculates the amount of savings possible based on the user's income and expenditure data. The data processing for this calculation includes the following steps:

[0160] 1. Normalizing data collected from users

[0161] 2. Calculating the difference between income and expenses using normalized data

[0162] 3. Generate a warning message if the difference is below the savings goal

[0163] 4. Generative AI model generates detailed advice

[0164] Specific examples

[0165] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the server calculates that the amount they can save is 50,000 yen. In this case, the server gives the user advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures," tax advice such as "Make sure to record your expenses and save receipts in order to file your tax return efficiently," and investment suggestions such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[0166] Prompt Sentence Examples

[0167] As a concrete example, the following prompts can be input to a generative AI model:

[0168] "If my income is 300,000 yen, my expenses are 250,000 yen, and my savings goal is 40,000 yen, how should I manage my assets?"

[0169] In this way, users can receive specific and practical advice tailored to their own financial situation.

[0170] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0171] Step 1:

[0172] Data collection

[0173] The user inputs their monthly income, monthly expenses, and savings goals through the device, which then collects and temporarily stores this data.

[0174] Input: Monthly income, monthly expenses, savings goal

[0175] Output: Collected income data, expenditure data, and savings goals

[0176] Step 2:

[0177] Sending data

[0178] The device sends the collected data to the server, using a secure communication protocol such as HTTPS.

[0179] Inputs: Collected income data, expenditure data, savings goals

[0180] Output: Collected data is sent to the server

[0181] Step 3:

[0182] Data analysis

[0183] The server analyzes the collected data and calculates the amount of savings possible by subtracting expenses from income. This calculation is done using Python.

[0184] Input: Collected data (income data, expenditure data, savings goal)

[0185] Output: Savings

[0186] Step 4:

[0187] Warning message generation

[0188] The server compares the calculated savings potential with the savings target and generates a warning message if the savings potential is less than the savings target.

[0189] Input: Savings Amount, Savings Goal

[0190] Output: Warning message

[0191] Step 5:

[0192] Applying generative AI models

[0193] The server uses the generative AI model to generate detailed asset management advice based on input data and calculated savings potential, including recommendations for reviewing spending, streamlining tax procedures, and investment options such as hometown tax payments and NISA savings.

[0194] Input: Collected data, Savings amount

[0195] Output: Wealth management advice

[0196] Step 6:

[0197] Sending advice and warning messages

[0198] The server generates advice and warning messages and sends them to the device, allowing the user to understand the situation in real time.

[0199] Input: Asset management advice, warning message

[0200] Output: Advisory and warning messages are sent to the terminal.

[0201] Step 7:

[0202] Display of advice and warning messages

[0203] The device displays the received advice and warning messages to the user, who can then check them through the smartphone application.

[0204] Input: Advice, warning message

[0205] Output: Display of advice and warning messages

[0206] Through this process, users can receive specific and practical advice tailored to their financial situation, and receive timely alerts to help them achieve their savings goals as planned.

[0207] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0208] This invention aims to enable users to effectively and efficiently manage their assets and savings through the "AI Money Support" system. In particular, by combining it with an emotion engine that recognizes the user's emotions, it aims to provide more personalized advice to each individual user.

[0209] Specifically, the system consists of the following steps:

[0210] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0211] Next, the device's built-in emotion engine recognizes the user's emotions when inputting or using the device. The emotion engine uses facial recognition and voice analysis technologies to extract emotional information from the user's facial expressions and tone of voice.

[0212] The device sends the collected data (income data, expenditure data, savings goal, and emotional information) to the server. The server analyzes the received data and calculates the user's savings potential by subtracting expenditure from income. If the savings potential falls below the savings goal, the server generates a warning message.

[0213] Based on the analysis results, the server generates specific advice for the user. This advice includes advice on how to manage expenses, tax advice for filing tax returns, and investment methods such as hometown tax donations and NISA savings. The server also adjusts the content and presentation of the advice based on the user's emotional information. For example, if the user is feeling stressed, the server can provide advice that includes encouraging words.

[0214] Furthermore, based on the user's emotional information, the system generates additional advice to reduce stress and improve motivation. For example, if the user is feeling stressed, the system can display a message such as, "Thank you for your hard work. It's important to take time to relax."

[0215] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0216] For example, if a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's estimated savings potential is 50,000 yen, so no warning message is generated. If the emotion engine recognizes that the user is relaxed, the server will provide regular asset management advice. On the other hand, if the user is feeling stressed, the server will provide advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[0217] This allows users to receive more personalized advice, easily receive services equivalent to those of a financial planner wherever they are, and achieve sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[0218] The processing flow will be explained below.

[0219] Step 1:

[0220] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[0221] Step 2:

[0222] The terminal displays a prompt saying, "Please enter your total monthly expenses," and the user enters the total monthly expenses. Next, the terminal displays a prompt saying, "Please enter your monthly savings goal," and the user enters the savings goal.

[0223] Step 3:

[0224] The emotion engine recognizes the user's face and voice to identify their current emotional state (e.g., relaxed, stressed, happy), and the device adds this emotional information to the data.

[0225] Step 4:

[0226] The device sends the collected data (income data, expenditure data, savings goals, emotional information) to a server.

[0227] Step 5:

[0228] The server analyzes the received data. It calculates the amount of savings that can be made by subtracting expenses from the user's income. For example, if the income is 300,000 yen and the expenses are 250,000 yen, the amount of savings that can be made is 50,000 yen.

[0229] Step 6:

[0230] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[0231] Step 7:

[0232] The server then generates specific advice for the user based on the analysis results, including information on how to manage expenses, tax advice for filing tax returns, and investment options such as hometown tax donations and NISA savings accounts.

[0233] Step 8:

[0234] The server takes into account the user's emotional information and adjusts the content and presentation of the advice. For example, if the user is feeling stressed, the server will provide advice that includes encouraging words, such as, "It's important to keep a record of your monthly income and expenses, but you should also take time to relax."

[0235] Step 9:

[0236] Furthermore, the server generates additional advice based on the user's emotional information to reduce stress and increase motivation, such as a message like "Thank you for your hard work. It's important to take time to relax."

[0237] Step 10:

[0238] The terminal displays the advice and warning messages received from the server to the user, allowing the user to understand the current spending and savings situation and manage their assets effectively.

[0239] In this way, the "AI Money Support" system, which combines an emotion engine, provides personalized advice that takes into account the user's emotional state, helping them achieve sound asset management.

[0240] Example 2

[0241] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0242] Conventional asset management systems do not provide advice that takes into account the user's emotional state, making it difficult to provide personalized support that reflects the user's mental state and motivation. Furthermore, advice based solely on the user's income and expenditure data is uniform and cannot fully address individual needs, which is a problem. Therefore, the present invention aims to achieve more effective and efficient asset management and savings management by taking into account the user's emotional information.

[0243] 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.

[0244] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditures from income based on the collected income data, expenditure data, and savings target, means for generating an alert message when the savings potential falls below the savings target, means for generating advice on asset management and savings investment using the calculated savings potential and the generated alert message, means for displaying the generated advice and alert message to the user, means for recognizing the user's emotions and adjusting the content and presentation of the advice based on the emotional information, and means for generating additional advice to reduce stress and increase motivation based on the user's emotional information. This allows the user to receive optimal advice tailored to their emotional state, enabling efficient asset management while reducing mental stress.

[0245] "Income data" is information about the amount of income a user receives.

[0246] "Expense data" is information on the amount of money that a user spends.

[0247] A "savings goal" is the amount of savings that a user wants to achieve within a certain period of time.

[0248] The "savings amount" is the amount that can be saved, calculated by subtracting expenses from the user's income.

[0249] An "alert message" is a warning message that is generated when the amount of available savings falls below the savings goal.

[0250] "Wealth management" is the act of effectively managing a user's financial assets, such as income, expenses, and savings.

[0251] "Savings management" refers to the plans and methods for how a user manages and increases their savings.

[0252] "Advice" means specific suggestions or advice regarding asset management and savings investment.

[0253] "Emotion information" is information about the user's emotional state extracted from facial expressions, tone of voice, and the like.

[0254] "Stress reduction" refers to actions or means to reduce the mental burden on the user.

[0255] "Motivation improvement" refers to actions or means to increase a user's motivation and enthusiasm.

[0256] The present invention aims to enable users to effectively and efficiently manage their assets and savings through an "AI Money Support" system. In particular, it aims to provide more personalized advice by combining it with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0257] First, the terminal asks the user to input their monthly income, monthly expenses, and savings goal. After the user inputs this data, the terminal stores the input data in an internal database, which can be a commonly used database such as SQLite.

[0258] Next, the device's built-in emotion engine recognizes the user's emotions when they input or use the device. The emotion engine uses facial recognition and voice analysis technologies, such as Microsoft® Azure® Cognitive Services and Google Cloud Vision, to extract emotional information from the user's facial expressions and tone of voice.

[0259] The device then sends the collected income data, expenditure data, savings goals, and sentiment information to a server, typically using HTTP requests.

[0260] The server analyzes the received data using programming languages ​​such as Python and R. The server calculates the amount of savings that can be made by subtracting expenses from the user's income, and generates a warning message if the amount of savings that can be made falls short of the savings goal.

[0261] The server generates specific advice for the user based on the analysis results. This advice includes advice on asset management, tax advice, and investment options. Furthermore, the server adjusts the content and presentation of the advice based on the user's emotional information, and provides encouraging advice when the user is feeling stressed.

[0262] The server also generates additional advice based on the user's emotional information to reduce stress and improve motivation. For example, it generates a message such as, "Thank you for your hard work. Make sure you take time to relax," thereby reducing the user's mental burden.

[0263] Finally, the terminal displays the generated advice and warning messages to the user, allowing the user to understand the current income / expense and savings situation and manage their assets effectively.

[0264] As a concrete example, consider the case where a user enters the following data:

[0265] "Monthly income: 300,000 yen"

[0266] "Monthly expenses: 250,000 yen"

[0267] "Savings goal: 40,000 yen"

[0268] In this case, the system calculates the amount that can be saved as 50,000 yen, and no warning message is displayed. If the emotion engine recognizes that the user is relaxed, the server provides regular asset management advice. On the other hand, if the user is feeling stressed, the server provides advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[0269] An example of a prompt is as follows:

[0270] "I set my monthly income at 300,000 yen, my monthly expenses at 250,000 yen, and my monthly savings goal at 40,000 yen. The emotion engine recognized that the user was feeling stressed. Please generate the most appropriate advice."

[0271] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0272] Step 1:

[0273] The user inputs their monthly income, monthly expenses, and savings goal. The input data is sent to the device and saved. Specifically, if a user inputs a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, this data is stored in the device's internal database.

[0274] Input: Monthly income, monthly expenses, savings goal

[0275] Output: Input data stored in the database on the device

[0276] Step 2:

[0277] The device's built-in emotion engine recognizes the user's emotions. The emotion engine uses facial recognition and voice analysis technology to analyze the user's emotions when inputting or using the device. For example, Microsoft Azure Cognitive Services and Google Cloud Vision can be used to recognize emotions such as joy, sadness, and stress from the user's facial expressions and voice.

[0278] Input: User's face image, voice sample

[0279] Output: User's emotional information

[0280] Step 3:

[0281] The device sends the collected income data, expenditure data, savings goals, and emotional information to a server. The data is sent to the server using a protocol such as an HTTP request.

[0282] Input: Income data, expenditure data, savings goals, emotional information

[0283] Output: Data sent to the server

[0284] Step 4:

[0285] The server analyzes the received data using a programming language such as Python or R. For example, it calculates the amount of savings possible by subtracting expenses from the user's income and compares it with the savings goal.

[0286] Input: Income data, expenditure data, savings goals, emotional information

[0287] Output: Analysis results (savings potential, analysis results based on emotional information)

[0288] Step 5:

[0289] The server generates specific advice for the user based on the analysis results. The advice includes information on asset management, tax advice, and investment options. Furthermore, the content and presentation of the advice are adjusted based on the user's emotional information. For example, if the user's savings potential falls below their savings goal, a warning message is generated to reflect the user's emotional information.

[0290] Input: Analysis results (savings potential, analysis results based on emotional information)

[0291] Output: Generated advice and warning messages

[0292] Step 6:

[0293] The server generates additional advice to reduce stress and improve motivation based on the user's emotional information. For example, if the server detects that the user is feeling stressed, it generates a message such as, "Make sure to take time to relax."

[0294] Input: Emotion information

[0295] Output: Additional advice

[0296] Step 7:

[0297] The terminal displays the generated advice and warning messages to the user, who can then use this information to review their own asset management and savings practices, for example, by reviewing their spending or considering new investment options as needed.

[0298] Input: Generated advice, warning messages, additional advice

[0299] Output: Advice and warning messages displayed to the user

[0300] (Application example 2)

[0301] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0302] Conventional asset management systems provide advice based only on data such as income, expenses, and savings goals, and therefore are unable to provide personalized advice that takes into account the user's emotional state. As a result, even when users are feeling stressed or anxious, they are unable to receive support to relax or improve their motivation at the appropriate time, limiting the effectiveness of asset management. Therefore, there is a need for a system that supports more effective asset management and savings management while taking into account the user's emotions.

[0303] 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.

[0304] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings target, means for generating a warning message when the savings potential falls below the savings target, means for recognizing the user's emotions using an emotion recognition engine built into the terminal and extracting emotion information, means for generating advice on asset management and savings management using the calculated savings potential, the generated warning message, and the extracted emotion information, and means for displaying the generated advice and warning message to the user. This allows for the provision of personalized advice and messages that take the user's emotional state into consideration, enabling more effective and user-friendly asset management.

[0305] "Income information" refers to data on all income earned by a user, including salary, bonuses, income from side jobs, etc.

[0306] "Expense information" refers to data on all expenses consumed by a user, including rent, food, utilities, entertainment, etc.

[0307] A "savings goal" refers to the amount of savings a user aims to achieve within a particular time period.

[0308] "Savings available" refers to the funds remaining after subtracting expenses from income, and is the amount that a user can actually save.

[0309] "Warning Message" refers to a notification that is generated when the savings potential falls below the set savings goal.

[0310] An "emotion recognition engine" refers to a system that recognizes a user's emotions using facial recognition and voice analysis technology and extracts their emotional state.

[0311] "Emotion information" refers to data on the emotional state extracted by the emotion recognition engine from the user's facial expressions and tone of voice.

[0312] "Wealth management" refers to the process of properly managing your income, expenses, and savings to maintain financial well-being.

[0313] "Savings management" refers to the process of systematically managing and investing funds toward a user's savings goal.

[0314] "Advice" refers to advice or guidance provided based on a user's income information, expenditure information, savings goals, savings potential, and emotional information.

[0315] "Server" refers to a computer system for collecting, analyzing, and storing data, and providing information to users.

[0316] The present invention relates to a system that allows users to effectively manage their assets and savings by inputting their income information, expenditure information, and savings goals. This system provides more personalized advice by incorporating an emotion recognition engine that recognizes the user's emotions.

[0317] First, the user uses a device such as a smartphone or tablet to input their monthly income, monthly expenses, and savings goal. This data is stored on the device. The device's built-in emotion recognition engine then analyzes the user's facial expressions and tone of voice to extract emotional information. This emotion recognition engine utilizes face recognition technology and voice analysis technology using OpenCV.

[0318] The terminal then sends the collected income information, expenditure information, savings goal, and emotional information to the server. The server receives this data and calculates the amount of savings that can be made by subtracting expenditure from income. Based on this calculation result, if the amount of savings that can be made falls below the savings goal, a warning message is generated. The server also generates personalized advice that takes the emotional information into account.

[0319] For example, if a user sets their monthly income at 300,000 yen, their monthly expenses at 250,000 yen, and their savings goal at 40,000 yen, the server will calculate the amount they can save as 50,000 yen. The emotion recognition engine also detects that the user is relaxed. Based on this, the server will provide them with regular asset management advice, as well as a message encouraging them to make time to relax.

[0320] The generated advice and warning messages are displayed to the user via the device, allowing the user to understand their current income, expenditure, and savings situation and manage their assets more effectively.In addition, additional advice based on emotional information is provided to reduce stress and increase motivation, providing psychological support to the user.

[0321] Here are some example prompts to pass to a generative AI model:

[0322] The user has set a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. The user's emotion is recognized as relaxation. Based on this condition, generate advice to provide to the user. Additionally, add a message to reduce stress.

[0323] Thus, the present invention provides a wealth management system that takes into account the user's financial and emotional state, resulting in a more effective and user-friendly approach.

[0324] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0325] Step 1:

[0326] The terminal allows the user to input income information, expenditure information, and savings goals. The user inputs monthly income, monthly expenditure, and savings goals. The terminal stores this data in a consolidated manner. The input data becomes the basic data required for subsequent processing.

[0327] Step 2:

[0328] The device's built-in emotion recognition engine recognizes the user's emotions, capturing the user's facial expressions and tone of voice to extract emotional information. This processing is performed using OpenCV and voice analysis technology. The acquired emotional information is used to tailor advice based on the user's financial behavior.

[0329] Step 3:

[0330] The terminal transmits the collected income information, expenditure information, savings goal, and emotional information to the server, which receives and analyzes this data.

[0331] Step 4:

[0332] The server analyzes the received data and calculates the amount of savings that can be made by subtracting expenses from income. This calculation is based on income information and expenditure information. The calculated amount of savings that can be made is the amount that the user can actually save.

[0333] Step 5:

[0334] The server compares the available savings amount with the savings goal, and if the available savings amount is less than the savings goal, it generates a warning message to remind the user to achieve the savings goal.

[0335] Step 6:

[0336] The server takes emotional information into account to generate personalized advice on asset management and savings, including specific suggestions on how to manage income and expenses and investment options, as well as encouraging messages and additional advice to reduce stress depending on the user's emotional state.

[0337] Step 7:

[0338] The server generates advice and warning messages and sends them to the terminal, which receives them and displays them to the user, allowing the user to understand the current asset status and take action based on the advice.

[0339] Through these steps, users can receive specific and personalized advice based on their individual financial and emotional situations, leading to more effective asset management.

[0340] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0341] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0342] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0343] [Second embodiment]

[0344] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0345] 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.

[0346] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0347] 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.

[0348] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0349] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0350] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0351] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0352] 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.

[0353] 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.

[0354] 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.

[0355] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0356] The present invention enables users to effectively and efficiently manage their assets and savings through the "AI Money Support" system, which collects, analyzes, and provides advice on income, expenditure, and savings goals provided by users.

[0357] Specifically, the system consists of the following steps:

[0358] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0359] Next, the device sends the collected data to the server. The server analyzes the received data and calculates the user's possible savings by subtracting expenses from their income. If the possible savings amount falls below the savings goal, the server generates a warning message. For example, if the user enters a monthly income of 300,000 yen and monthly expenses of 250,000 yen, the possible savings amount will be 50,000 yen. In this case, if the user's savings goal is 40,000 yen, there is no problem, but if it falls below 50,000 yen, a warning message will be generated.

[0360] The server then generates specific advice for the user based on the analysis results, including advice on daily spending management, tax advice for filing tax returns, and advice on investment methods such as hometown tax donations and NISA savings accounts, allowing users to understand specific and practical ways to manage their assets.

[0361] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0362] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's calculated savings potential is 50,000 yen, so no warning message will be displayed. The system will provide the user with advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses," as well as tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently," and investment advice such as "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[0363] This allows users to easily receive services equivalent to those of a financial planner wherever they are, enabling sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[0364] The processing flow will be explained below.

[0365] Step 1:

[0366] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[0367] Step 2:

[0368] The terminal then prompts the user to "Enter your monthly expenses," and the user enters their monthly expenses. The terminal then prompts the user to "Enter your monthly savings goal," and the user enters their savings goal.

[0369] Step 3:

[0370] The device sends the collected data (income data, expenditure data, savings goals) to the server.

[0371] Step 4:

[0372] The server analyzes the received data. The server subtracts the user's expenses from their income to calculate the amount they can save. For example, if their income is 300,000 yen and their expenses are 250,000 yen, their savings amount is 50,000 yen.

[0373] Step 5:

[0374] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[0375] Step 6:

[0376] The server then uses the analysis results to generate specific advice for the user, including information on spending management, tax treatment, and investment options.

[0377] Step 7:

[0378] The device displays advice and warning messages received from the server to the user. For example, it displays information such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures" or "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[0379] This is the specific flow of processing in the "AI Money Support" system. Users can implement effective asset management based on this advice.

[0380] Example 1

[0381] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0382] Currently, many people find it difficult to effectively manage their income and expenditures and manage their savings, especially because they have limited opportunities to receive specific advice on achieving their savings goals. Furthermore, there are insufficient systems that analyze income and expenditure data and automatically suggest appropriate measures based on the results. This makes it difficult for users to easily grasp their income and expenditure situation and implement improvement measures. Therefore, an objective of the present invention is to provide a system that allows users to effectively and efficiently manage their assets and manage their savings.

[0383] 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.

[0384] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings goals, means for generating a warning message when the savings potential falls below the savings target, means for generating advice on asset management and savings management using the calculated savings potential and the generated warning message, and means for displaying the generated advice and warning message to the user, thereby enabling the user to clearly understand the income and expenditure situation and to appropriately manage assets and savings.

[0385] "Income information" is data indicating the amount of regular income of the user.

[0386] "Expense information" is data indicating the amount of regular expenditures of a user.

[0387] A "savings goal" is a target value that indicates the amount of savings that a user wishes to achieve within a certain period of time.

[0388] "Means for collecting" refers to methods and devices for obtaining income information, expenditure information, and savings goals from a user.

[0389] The "means for calculating the savable amount by subtraction" refers to a method or device for calculating the savable amount calculated by subtracting expenditure information from income information.

[0390] The term "means for generating a warning message" refers to a method or device that generates a message to alert the user when the amount of savings available falls below the savings goal.

[0391] The "means for generating advice" refers to a method or device that provides a user with suggestions or recommendations regarding asset management and savings management based on the calculated savings potential and the generated warning message.

[0392] The "displaying means" refers to a method or device for displaying the generated advice and warning messages on a terminal used by a user.

[0393] "Means for transmitting to a server" refers to a method or device for transmitting the collected income information, expenditure information, and savings goals to a server via the Internet or other communications network.

[0394] "Means for receiving the analysis results" refers to a method or device for receiving the analyzed data and results sent from the server at the user's terminal.

[0395] "Wealth Management Advice" means specific suggestions and recommendations for effectively managing and growing your assets.

[0396] "Tax advice" refers to specific suggestions and recommendations for calculating and filing taxes efficiently.

[0397] "Expense Management Advice" refers to specific suggestions and recommendations for effectively managing a user's day-to-day expenses.

[0398] The present invention relates to an "AI Money Support" system that collects income information, expenditure information, and savings goals, and provides advice for effective asset management and savings management. The system operates using a server, a terminal, and a generative AI model.

[0399] Hardware and software used

[0400] Hardware: Devices used by users (e.g. smartphones, PCs), servers

[0401] Software: User interface software (e.g., web application, mobile app), data analysis software (e.g., Python + Pandas), advice translator (e.g., ChatGPT), warning generation module (e.g., JavaScript)

[0402] Basic operation of the system

[0403] 1. Data Collection:

[0404] User: Enters income and expenditure information such as monthly income, monthly expenses, and savings goal into the device. For example, the user enters this information into a smartphone app: "Monthly income: 300,000 yen, monthly expenses: 250,000 yen, savings goal: 40,000 yen."

[0405] Device: Stores the provided data in local storage and keeps it temporarily in memory. For example, store the data as follows: localStorage.setItem('income', '300000').

[0406] 2. Data Transmission and Analysis:

[0407] On the device: Send the collected data to the server using the HTTPS protocol. For example, send it as axios.post('https: / / api.example.com / data', data).

[0408] Server: Analyzes the received data using Python's Pandas library and calculates the potential savings. Specifically, it calculates savings_capacity = income - expenses.

[0409] 3. Warning message generation and advice generation:

[0410] Server: If the savings potential is below the target, generate a warning message. Example: "Saving potential is below the target. Please review your spending."

[0411] Server: Using a generative AI model (e.g., ChatGPT), a prompt such as "Please provide asset management advice for a user with a monthly income of 300,000 yen, expenses of 250,000 yen, and a savings goal of 40,000 yen" is input, and specific advice is generated.

[0412] 4. Displaying the results:

[0413] Server: Sends generated advice and warning messages to the device in JSON format, for example: response.json = {"advice": "...", "warning": "..."}.

[0414] Terminal: Display the received data in a user interface. For example, the HTML ... Insert a message inside.

[0415] 5. User Behavior:

[0416] User: Based on the advice and warning messages provided, they manage their spending and make investments. For example, they take concrete actions such as starting to keep a household budget or making use of hometown tax donations.

[0417] As an example of how the system works, let's take the case where a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. In this case, the system calculates that the user's possible savings amount is 50,000 yen, so no warning message is generated. Based on this data, the server generates specific advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses." It also suggests tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently" and investment advice such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[0418] Example prompt: "Monthly income: ¥300,000, monthly expenses: ¥250,000, savings goal: ¥40,000. Please provide specific advice to the user in this situation."

[0419] As described above, the present invention is a system that supports effective asset management by providing users with specific and practical advice on asset management and savings management.

[0420] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0421] Step 1:

[0422] The user enters their monthly income, monthly expenses, and savings goal into the terminal.

[0423] Specifically, the user enters "monthly income 300,000 yen, monthly expenses 250,000 yen, savings goal 40,000 yen" into the input form of the smartphone app. This is the input data. The output is that the input data is saved on the device.

[0424] Step 2:

[0425] The device saves the input data in local storage.

[0426] Specifically, the device uses commands such as localStorage.setItem('income', '300000') to store income information, expenditure information, and savings goals. The input is the data entered by the user. The output is the data stored in local storage.

[0427] Step 3:

[0428] The terminal transmits the collected data to the server.

[0429] Specifically, the terminal sends data using the HTTPS protocol, such as axios.post('https: / / api.example.com / data', data). The input is the data stored in local storage. The output is the data sent to the server.

[0430] Step 4:

[0431] The server parses the received data.

[0432] Specifically, the server analyzes the data using Python's Pandas library. For example, the code savings_capacity = income - expenses is used to calculate the amount of savings that can be made. The input is the data sent from the terminal, and the output is the calculated amount of savings that can be made.

[0433] Step 5:

[0434] The server checks the savings amount and generates a warning message if necessary.

[0435] Specifically, the server uses conditional branching to execute the following process: if savings_capacity < target_savings: warning_message = "Your savings potential is below your target. Please review your spending." The inputs are the calculated savings potential and the savings target. The output is a warning message.

[0436] Step 6:

[0437] The server uses the generative AI model to generate specific advice.

[0438] Specifically, the server inputs the prompt statement "Please provide asset management advice for the user's monthly income of 300,000 yen, expenses of 250,000 yen, and savings goal of 40,000 yen" into the generative AI model and generates advice. The input is the prompt statement and the user's data. The output is the generated advice.

[0439] Step 7:

[0440] The server sends generated advisory and warning messages to the terminal.

[0441] Specifically, the server packages the data in JSON format and sends it to the terminal as response.json = {"advice": "Your savings goal is achievable. Manage your daily expenses and refer to the tax advice for your tax return.", "warning": "Your savings potential is below your goal. Please review your expenses"}. The input is the generated advice and warning message. The output is the message sent to the terminal.

[0442] Step 8:

[0443] The terminal displays the received data on the user interface.

[0444] Specifically, the device uses HTML, CSS, and JavaScript to Your savings goals are achievable - take control of your daily expenses and get tax advice for your tax return. The input is the data sent from the server. The output is the message displayed on the user interface.

[0445] Step 9:

[0446] The user takes action based on the displayed advice and warning messages.

[0447] Specific actions that users take include reviewing income and expenditures, keeping a household account book, processing taxes, and using hometown tax donations. The input is the displayed advice and warning messages. The output is the specific actions taken by the user.

[0448] (Application example 1)

[0449] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0450] In today's society, many individuals lack knowledge about asset management and savings investments and are time-constrained. As a result, it is difficult to achieve effective savings goals and properly manage their assets. To solve these challenges, a user-friendly system is needed. Furthermore, there is a need for systems that can manage expenses in real time through integration with electronic payment platforms and provide detailed asset management advice using generative AI models.

[0451] 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.

[0452] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income data, expenditure data, and savings goals, and means for generating a warning message when the savings potential falls below the savings target. This allows the user to collect expenditure and income data in real time and receive detailed asset management advice. Furthermore, by displaying the generated advice and warning message to the user, the user can quickly understand their current expenditure and savings situation and manage their assets effectively and efficiently.

[0453] A "user" is an individual who utilizes the system to provide income data, expenditure data, and savings goals.

[0454] "Income Data" is information about all income earned by a user.

[0455] "Expense Data" is information about all expenses made by a user.

[0456] A "savings goal" is the amount of savings a user wants to achieve within a specific time period.

[0457] "Savings potential" is the amount you can actually save, obtained by subtracting expenses from income.

[0458] A "warning message" is a message generated to alert the user when the amount of savings available falls below the savings goal.

[0459] "Asset management advice" is a proposal for specific asset management and savings methods formulated based on the user's income, expenses, and savings.

[0460] An "electronic payment platform" is an online system that provides users with payment methods they use on a daily basis.

[0461] "Real time" refers to the fact that processing is carried out almost simultaneously at the moment an event occurs.

[0462] A "generative AI model" is an artificial intelligence model used to analyze user data and generate advice on asset management.

[0463] A "server" is a computer system that analyzes data collected from users and generates results.

[0464] "Analysis results" are the results of calculations and analyses performed by the server based on data provided by the user.

[0465] The system for implementing this invention works in conjunction with the electronic payment platform that users use on a daily basis to collect and analyze income data, expenditure data, and savings goals in real time. Specifically, the system automatically collects data when users perform daily transactions via their smartphones and transmits it to a server.

[0466] Program Overview

[0467] The server calculates the user's potential savings based on the collected income data, expenditure data, and savings goals, and generates a warning message if the savings goal is not reached. This process is performed using programming languages ​​such as Python. It also uses a generative AI model to generate specific advice on asset management for the user. This advice includes reviewing spending, streamlining tax procedures, and suggesting investment methods such as hometown tax payments and NISA savings.

[0468] Users can check these generated advice and warning messages in real time through smartphone applications that run on iOS and Android platforms, and the user interface is often implemented using frameworks such as React Native.

[0469] Hardware and Software

[0470] The following hardware and software are used to implement this system:

[0471] Hardware: Smartphone (iOS device, Android device)

[0472] software:

[0473] Python: Used to calculate savings potential and run generative AI models

[0474] React Native: Used to develop smartphone applications

[0475] Server platform: Cloud services such as AWS or Google Cloud Platform

[0476] Data processing and calculation

[0477] The server calculates the amount of savings possible based on the user's income and expenditure data. The data processing for this calculation includes the following steps:

[0478] 1. Normalizing data collected from users

[0479] 2. Calculating the difference between income and expenses using normalized data

[0480] 3. Generate a warning message if the difference is below the savings goal

[0481] 4. Generative AI model generates detailed advice

[0482] Specific examples

[0483] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the server calculates that the amount they can save is 50,000 yen. In this case, the server gives the user advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures," tax advice such as "Make sure to record your expenses and save receipts in order to file your tax return efficiently," and investment suggestions such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[0484] Prompt Sentence Examples

[0485] As a concrete example, the following prompts can be input to a generative AI model:

[0486] "If my income is 300,000 yen, my expenses are 250,000 yen, and my savings goal is 40,000 yen, how should I manage my assets?"

[0487] In this way, users can receive specific and practical advice tailored to their own financial situation.

[0488] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0489] Step 1:

[0490] Data collection

[0491] The user inputs their monthly income, monthly expenses, and savings goals through the device, which then collects and temporarily stores this data.

[0492] Input: Monthly income, monthly expenses, savings goal

[0493] Output: Collected income data, expenditure data, and savings goals

[0494] Step 2:

[0495] Sending data

[0496] The device sends the collected data to the server, using a secure communication protocol such as HTTPS.

[0497] Inputs: Collected income data, expenditure data, savings goals

[0498] Output: Collected data is sent to the server

[0499] Step 3:

[0500] Data analysis

[0501] The server analyzes the collected data and calculates the amount of savings possible by subtracting expenses from income. This calculation is done using Python.

[0502] Input: Collected data (income data, expenditure data, savings goal)

[0503] Output: Savings

[0504] Step 4:

[0505] Warning message generation

[0506] The server compares the calculated savings potential with the savings target and generates a warning message if the savings potential is less than the savings target.

[0507] Input: Savings Amount, Savings Goal

[0508] Output: Warning message

[0509] Step 5:

[0510] Applying generative AI models

[0511] The server uses the generative AI model to generate detailed asset management advice based on input data and calculated savings potential, including recommendations for reviewing spending, streamlining tax procedures, and investment options such as hometown tax payments and NISA savings.

[0512] Input: Collected data, Savings amount

[0513] Output: Wealth management advice

[0514] Step 6:

[0515] Sending advice and warning messages

[0516] The server generates advice and warning messages and sends them to the device, allowing the user to understand the situation in real time.

[0517] Input: Asset management advice, warning message

[0518] Output: Advisory and warning messages are sent to the terminal.

[0519] Step 7:

[0520] Display of advice and warning messages

[0521] The device displays the received advice and warning messages to the user, who can then check them through the smartphone application.

[0522] Input: Advice, warning message

[0523] Output: Display of advice and warning messages

[0524] Through this process, users can receive specific and practical advice tailored to their financial situation, and receive timely alerts to help them achieve their savings goals as planned.

[0525] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0526] This invention aims to enable users to effectively and efficiently manage their assets and savings through the "AI Money Support" system. In particular, by combining it with an emotion engine that recognizes the user's emotions, it aims to provide more personalized advice to each individual user.

[0527] Specifically, the system consists of the following steps:

[0528] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0529] Next, the device's built-in emotion engine recognizes the user's emotions when inputting or using the device. The emotion engine uses facial recognition and voice analysis technologies to extract emotional information from the user's facial expressions and tone of voice.

[0530] The device sends the collected data (income data, expenditure data, savings goal, and emotional information) to the server. The server analyzes the received data and calculates the user's savings potential by subtracting expenditure from income. If the savings potential falls below the savings goal, the server generates a warning message.

[0531] Based on the analysis results, the server generates specific advice for the user. This advice includes advice on how to manage expenses, tax advice for filing tax returns, and investment methods such as hometown tax donations and NISA savings. The server also adjusts the content and presentation of the advice based on the user's emotional information. For example, if the user is feeling stressed, the server can provide advice that includes encouraging words.

[0532] Furthermore, based on the user's emotional information, the system generates additional advice to reduce stress and improve motivation. For example, if the user is feeling stressed, the system can display a message such as, "Thank you for your hard work. It's important to take time to relax."

[0533] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0534] For example, if a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's estimated savings potential is 50,000 yen, so no warning message is generated. If the emotion engine recognizes that the user is relaxed, the server will provide regular asset management advice. On the other hand, if the user is feeling stressed, the server will provide advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[0535] This allows users to receive more personalized advice, easily receive services equivalent to those of a financial planner wherever they are, and achieve sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[0536] The processing flow will be explained below.

[0537] Step 1:

[0538] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[0539] Step 2:

[0540] The terminal displays a prompt saying, "Please enter your total monthly expenses," and the user enters the total monthly expenses. Next, the terminal displays a prompt saying, "Please enter your monthly savings goal," and the user enters the savings goal.

[0541] Step 3:

[0542] The emotion engine recognizes the user's face and voice to identify their current emotional state (e.g., relaxed, stressed, happy), and the device adds this emotional information to the data.

[0543] Step 4:

[0544] The device sends the collected data (income data, expenditure data, savings goals, emotional information) to a server.

[0545] Step 5:

[0546] The server analyzes the received data. It calculates the amount of savings that can be made by subtracting expenses from the user's income. For example, if the income is 300,000 yen and the expenses are 250,000 yen, the amount of savings that can be made is 50,000 yen.

[0547] Step 6:

[0548] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[0549] Step 7:

[0550] The server then generates specific advice for the user based on the analysis results, including information on how to manage expenses, tax advice for filing tax returns, and investment options such as hometown tax donations and NISA savings accounts.

[0551] Step 8:

[0552] The server takes into account the user's emotional information and adjusts the content and presentation of the advice. For example, if the user is feeling stressed, the server will provide advice that includes encouraging words, such as, "It's important to keep a record of your monthly income and expenses, but you should also take time to relax."

[0553] Step 9:

[0554] Furthermore, the server generates additional advice based on the user's emotional information to reduce stress and increase motivation, such as a message like "Thank you for your hard work. It's important to take time to relax."

[0555] Step 10:

[0556] The terminal displays the advice and warning messages received from the server to the user, allowing the user to understand the current spending and savings situation and manage their assets effectively.

[0557] In this way, the "AI Money Support" system, which combines an emotion engine, provides personalized advice that takes into account the user's emotional state, helping them achieve sound asset management.

[0558] Example 2

[0559] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0560] Conventional asset management systems do not provide advice that takes into account the user's emotional state, making it difficult to provide personalized support that reflects the user's mental state and motivation. Furthermore, advice based solely on the user's income and expenditure data is uniform and cannot fully address individual needs, which is a problem. Therefore, the present invention aims to achieve more effective and efficient asset management and savings management by taking into account the user's emotional information.

[0561] 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.

[0562] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditures from income based on the collected income data, expenditure data, and savings target, means for generating an alert message when the savings potential falls below the savings target, means for generating advice on asset management and savings investment using the calculated savings potential and the generated alert message, means for displaying the generated advice and alert message to the user, means for recognizing the user's emotions and adjusting the content and presentation of the advice based on the emotional information, and means for generating additional advice to reduce stress and increase motivation based on the user's emotional information. This allows the user to receive optimal advice tailored to their emotional state, enabling efficient asset management while reducing mental stress.

[0563] "Income data" is information about the amount of income a user receives.

[0564] "Expense data" is information on the amount of money that a user spends.

[0565] A "savings goal" is the amount of savings that a user wants to achieve within a certain period of time.

[0566] The "savings amount" is the amount that can be saved, calculated by subtracting expenses from the user's income.

[0567] An "alert message" is a warning message that is generated when the amount of available savings falls below the savings goal.

[0568] "Wealth management" is the act of effectively managing a user's financial assets, such as income, expenses, and savings.

[0569] "Savings management" refers to the plans and methods for how a user manages and increases their savings.

[0570] "Advice" means specific suggestions or advice regarding asset management and savings investment.

[0571] "Emotion information" is information about the user's emotional state extracted from facial expressions, tone of voice, and the like.

[0572] "Stress reduction" refers to actions or means to reduce the mental burden on the user.

[0573] "Motivation improvement" refers to actions or means to increase a user's motivation and enthusiasm.

[0574] The present invention aims to enable users to effectively and efficiently manage their assets and savings through an "AI Money Support" system. In particular, it aims to provide more personalized advice by combining it with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0575] First, the terminal asks the user to input their monthly income, monthly expenses, and savings goal. After the user inputs this data, the terminal stores the input data in an internal database, which can be a commonly used database such as SQLite.

[0576] Next, the device's built-in emotion engine recognizes the user's emotions when typing or using the device. The emotion engine uses facial recognition and voice analysis technologies, such as Microsoft Azure Cognitive Services and Google Cloud Vision, to extract emotional information from the user's facial expressions and tone of voice.

[0577] The device then sends the collected income data, expenditure data, savings goals, and sentiment information to a server, typically using HTTP requests.

[0578] The server analyzes the received data using programming languages ​​such as Python and R. The server calculates the amount of savings that can be made by subtracting expenses from the user's income, and generates a warning message if the amount of savings that can be made falls short of the savings goal.

[0579] The server generates specific advice for the user based on the analysis results. This advice includes advice on asset management, tax advice, and investment options. Furthermore, the server adjusts the content and presentation of the advice based on the user's emotional information, and provides encouraging advice when the user is feeling stressed.

[0580] The server also generates additional advice based on the user's emotional information to reduce stress and improve motivation. For example, it generates a message such as, "Thank you for your hard work. Make sure you take time to relax," thereby reducing the user's mental burden.

[0581] Finally, the terminal displays the generated advice and warning messages to the user, allowing the user to understand the current income / expense and savings situation and manage their assets effectively.

[0582] As a concrete example, consider the case where a user enters the following data:

[0583] "Monthly income: 300,000 yen"

[0584] "Monthly expenses: 250,000 yen"

[0585] "Savings goal: 40,000 yen"

[0586] In this case, the system calculates the amount that can be saved as 50,000 yen, and no warning message is displayed. If the emotion engine recognizes that the user is relaxed, the server provides regular asset management advice. On the other hand, if the user is feeling stressed, the server provides advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[0587] An example of a prompt is as follows:

[0588] "I set my monthly income at 300,000 yen, my monthly expenses at 250,000 yen, and my monthly savings goal at 40,000 yen. The emotion engine recognized that the user was feeling stressed. Please generate the most appropriate advice."

[0589] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0590] Step 1:

[0591] The user inputs their monthly income, monthly expenses, and savings goal. The input data is sent to the device and saved. Specifically, if a user inputs a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, this data is stored in the device's internal database.

[0592] Input: Monthly income, monthly expenses, savings goal

[0593] Output: Input data stored in the database on the device

[0594] Step 2:

[0595] The device's built-in emotion engine recognizes the user's emotions. The emotion engine uses facial recognition and voice analysis technology to analyze the user's emotions when inputting or using the device. For example, Microsoft Azure Cognitive Services and Google Cloud Vision can be used to recognize emotions such as joy, sadness, and stress from the user's facial expressions and voice.

[0596] Input: User's face image, voice sample

[0597] Output: User's emotional information

[0598] Step 3:

[0599] The device sends the collected income data, expenditure data, savings goals, and emotional information to a server. The data is sent to the server using a protocol such as an HTTP request.

[0600] Input: Income data, expenditure data, savings goals, emotional information

[0601] Output: Data sent to the server

[0602] Step 4:

[0603] The server analyzes the received data using a programming language such as Python or R. For example, it calculates the amount of savings possible by subtracting expenses from the user's income and compares it with the savings goal.

[0604] Input: Income data, expenditure data, savings goals, emotional information

[0605] Output: Analysis results (savings potential, analysis results based on emotional information)

[0606] Step 5:

[0607] The server generates specific advice for the user based on the analysis results. The advice includes information on asset management, tax advice, and investment options. Furthermore, the content and presentation of the advice are adjusted based on the user's emotional information. For example, if the user's savings potential falls below their savings goal, a warning message is generated to reflect the user's emotional information.

[0608] Input: Analysis results (savings potential, analysis results based on emotional information)

[0609] Output: Generated advice and warning messages

[0610] Step 6:

[0611] The server generates additional advice to reduce stress and improve motivation based on the user's emotional information. For example, if the server detects that the user is feeling stressed, it generates a message such as, "Make sure to take time to relax."

[0612] Input: Emotion information

[0613] Output: Additional advice

[0614] Step 7:

[0615] The terminal displays the generated advice and warning messages to the user, who can then use this information to review their own asset management and savings practices, for example, by reviewing their spending or considering new investment options as needed.

[0616] Input: Generated advice, warning messages, additional advice

[0617] Output: Advice and warning messages displayed to the user

[0618] (Application example 2)

[0619] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0620] Conventional asset management systems provide advice based only on data such as income, expenses, and savings goals, and therefore are unable to provide personalized advice that takes into account the user's emotional state. As a result, even when users are feeling stressed or anxious, they are unable to receive support to relax or improve their motivation at the appropriate time, limiting the effectiveness of asset management. Therefore, there is a need for a system that supports more effective asset management and savings management while taking into account the user's emotions.

[0621] 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.

[0622] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings target, means for generating a warning message when the savings potential falls below the savings target, means for recognizing the user's emotions using an emotion recognition engine built into the terminal and extracting emotion information, means for generating advice on asset management and savings management using the calculated savings potential, the generated warning message, and the extracted emotion information, and means for displaying the generated advice and warning message to the user. This allows for the provision of personalized advice and messages that take the user's emotional state into consideration, enabling more effective and user-friendly asset management.

[0623] "Income information" refers to data on all income earned by a user, including salary, bonuses, income from side jobs, etc.

[0624] "Expense information" refers to data on all expenses consumed by a user, including rent, food, utilities, entertainment, etc.

[0625] A "savings goal" refers to the amount of savings a user aims to achieve within a particular time period.

[0626] "Savings available" refers to the funds remaining after subtracting expenses from income, and is the amount that a user can actually save.

[0627] "Warning Message" refers to a notification that is generated when the savings potential falls below the set savings goal.

[0628] An "emotion recognition engine" refers to a system that recognizes a user's emotions using facial recognition and voice analysis technology and extracts their emotional state.

[0629] "Emotion information" refers to data on the emotional state extracted by the emotion recognition engine from the user's facial expressions and tone of voice.

[0630] "Wealth management" refers to the process of properly managing your income, expenses, and savings to maintain financial well-being.

[0631] "Savings management" refers to the process of systematically managing and investing funds toward a user's savings goal.

[0632] "Advice" refers to advice or guidance provided based on a user's income information, expenditure information, savings goals, savings potential, and emotional information.

[0633] "Server" refers to a computer system for collecting, analyzing, and storing data, and providing information to users.

[0634] The present invention relates to a system that allows users to effectively manage their assets and savings by inputting their income information, expenditure information, and savings goals. This system provides more personalized advice by incorporating an emotion recognition engine that recognizes the user's emotions.

[0635] First, the user uses a device such as a smartphone or tablet to input their monthly income, monthly expenses, and savings goal. This data is stored on the device. The device's built-in emotion recognition engine then analyzes the user's facial expressions and tone of voice to extract emotional information. This emotion recognition engine utilizes face recognition technology and voice analysis technology using OpenCV.

[0636] The terminal then sends the collected income information, expenditure information, savings goal, and emotional information to the server. The server receives this data and calculates the amount of savings that can be made by subtracting expenditure from income. Based on this calculation result, if the amount of savings that can be made falls below the savings goal, a warning message is generated. The server also generates personalized advice that takes the emotional information into account.

[0637] For example, if a user sets their monthly income at 300,000 yen, their monthly expenses at 250,000 yen, and their savings goal at 40,000 yen, the server will calculate the amount they can save as 50,000 yen. The emotion recognition engine also detects that the user is relaxed. Based on this, the server will provide them with regular asset management advice, as well as a message encouraging them to make time to relax.

[0638] The generated advice and warning messages are displayed to the user via the device, allowing the user to understand their current income, expenditure, and savings situation and manage their assets more effectively.In addition, additional advice based on emotional information is provided to reduce stress and increase motivation, providing psychological support to the user.

[0639] Here are some example prompts to pass to a generative AI model:

[0640] The user has set a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. The user's emotion is recognized as relaxation. Based on this condition, generate advice to provide to the user. Additionally, add a message to reduce stress.

[0641] Thus, the present invention provides a wealth management system that takes into account the user's financial and emotional state, resulting in a more effective and user-friendly approach.

[0642] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0643] Step 1:

[0644] The terminal allows the user to input income information, expenditure information, and savings goals. The user inputs monthly income, monthly expenditure, and savings goals. The terminal stores this data in a consolidated manner. The input data becomes the basic data required for subsequent processing.

[0645] Step 2:

[0646] The device's built-in emotion recognition engine recognizes the user's emotions, capturing the user's facial expressions and tone of voice to extract emotional information. This processing is performed using OpenCV and voice analysis technology. The acquired emotional information is used to tailor advice based on the user's financial behavior.

[0647] Step 3:

[0648] The terminal transmits the collected income information, expenditure information, savings goal, and emotional information to the server, which receives and analyzes this data.

[0649] Step 4:

[0650] The server analyzes the received data and calculates the amount of savings that can be made by subtracting expenses from income. This calculation is based on income information and expenditure information. The calculated amount of savings that can be made is the amount that the user can actually save.

[0651] Step 5:

[0652] The server compares the available savings amount with the savings goal, and if the available savings amount is less than the savings goal, it generates a warning message to remind the user to achieve the savings goal.

[0653] Step 6:

[0654] The server takes emotional information into account to generate personalized advice on asset management and savings, including specific suggestions on how to manage income and expenses and investment options, as well as encouraging messages and additional advice to reduce stress depending on the user's emotional state.

[0655] Step 7:

[0656] The server generates advice and warning messages and sends them to the terminal, which receives them and displays them to the user, allowing the user to understand the current asset status and take action based on the advice.

[0657] Through these steps, users can receive specific and personalized advice based on their individual financial and emotional situations, leading to more effective asset management.

[0658] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0659] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0660] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0661] [Third embodiment]

[0662] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0663] 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.

[0664] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0665] 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.

[0666] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0667] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0668] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0669] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0670] 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.

[0671] 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.

[0672] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0673] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0674] The present invention enables users to effectively and efficiently manage their assets and savings through the "AI Money Support" system, which collects, analyzes, and provides advice on income, expenditure, and savings goals provided by users.

[0675] Specifically, the system consists of the following steps:

[0676] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0677] Next, the device sends the collected data to the server. The server analyzes the received data and calculates the user's possible savings by subtracting expenses from their income. If the possible savings amount falls below the savings goal, the server generates a warning message. For example, if the user enters a monthly income of 300,000 yen and monthly expenses of 250,000 yen, the possible savings amount will be 50,000 yen. In this case, if the user's savings goal is 40,000 yen, there is no problem, but if it falls below 50,000 yen, a warning message will be generated.

[0678] The server then generates specific advice for the user based on the analysis results, including advice on daily spending management, tax advice for filing tax returns, and advice on investment methods such as hometown tax donations and NISA savings accounts, allowing users to understand specific and practical ways to manage their assets.

[0679] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0680] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's calculated savings potential is 50,000 yen, so no warning message will be displayed. The system will provide the user with advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses," as well as tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently," and investment advice such as "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[0681] This allows users to easily receive services equivalent to those of a financial planner wherever they are, enabling sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[0682] The processing flow will be explained below.

[0683] Step 1:

[0684] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[0685] Step 2:

[0686] The terminal then prompts the user to "Enter your monthly expenses," and the user enters their monthly expenses. The terminal then prompts the user to "Enter your monthly savings goal," and the user enters their savings goal.

[0687] Step 3:

[0688] The device sends the collected data (income data, expenditure data, savings goals) to the server.

[0689] Step 4:

[0690] The server analyzes the received data. The server subtracts the user's expenses from their income to calculate the amount they can save. For example, if their income is 300,000 yen and their expenses are 250,000 yen, their savings amount is 50,000 yen.

[0691] Step 5:

[0692] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[0693] Step 6:

[0694] The server then uses the analysis results to generate specific advice for the user, including information on spending management, tax treatment, and investment options.

[0695] Step 7:

[0696] The device displays advice and warning messages received from the server to the user. For example, it displays information such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures" or "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[0697] This is the specific flow of processing in the "AI Money Support" system. Users can implement effective asset management based on this advice.

[0698] Example 1

[0699] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0700] Currently, many people find it difficult to effectively manage their income and expenditures and manage their savings, especially because they have limited opportunities to receive specific advice on achieving their savings goals. Furthermore, there are insufficient systems that analyze income and expenditure data and automatically suggest appropriate measures based on the results. This makes it difficult for users to easily grasp their income and expenditure situation and implement improvement measures. Therefore, an objective of the present invention is to provide a system that allows users to effectively and efficiently manage their assets and manage their savings.

[0701] 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.

[0702] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings goals, means for generating a warning message when the savings potential falls below the savings target, means for generating advice on asset management and savings management using the calculated savings potential and the generated warning message, and means for displaying the generated advice and warning message to the user, thereby enabling the user to clearly understand the income and expenditure situation and to appropriately manage assets and savings.

[0703] "Income information" is data indicating the amount of regular income of the user.

[0704] "Expense information" is data indicating the amount of regular expenditures of a user.

[0705] A "savings goal" is a target value that indicates the amount of savings that a user wishes to achieve within a certain period of time.

[0706] "Means for collecting" refers to methods and devices for obtaining income information, expenditure information, and savings goals from a user.

[0707] The "means for calculating the savable amount by subtraction" refers to a method or device for calculating the savable amount calculated by subtracting expenditure information from income information.

[0708] The term "means for generating a warning message" refers to a method or device that generates a message to alert the user when the amount of savings available falls below the savings goal.

[0709] The "means for generating advice" refers to a method or device that provides a user with suggestions or recommendations regarding asset management and savings management based on the calculated savings potential and the generated warning message.

[0710] The "displaying means" refers to a method or device for displaying the generated advice and warning messages on a terminal used by a user.

[0711] "Means for transmitting to a server" refers to a method or device for transmitting the collected income information, expenditure information, and savings goals to a server via the Internet or other communications network.

[0712] "Means for receiving the analysis results" refers to a method or device for receiving the analyzed data and results sent from the server at the user's terminal.

[0713] "Wealth Management Advice" means specific suggestions and recommendations for effectively managing and growing your assets.

[0714] "Tax advice" refers to specific suggestions and recommendations for calculating and filing taxes efficiently.

[0715] "Expense Management Advice" refers to specific suggestions and recommendations for effectively managing a user's day-to-day expenses.

[0716] The present invention relates to an "AI Money Support" system that collects income information, expenditure information, and savings goals, and provides advice for effective asset management and savings management. The system operates using a server, a terminal, and a generative AI model.

[0717] Hardware and software used

[0718] Hardware: Devices used by users (e.g. smartphones, PCs), servers

[0719] Software: User interface software (e.g., web application, mobile app), data analysis software (e.g., Python + Pandas), advice translator (e.g., ChatGPT), warning generation module (e.g., JavaScript)

[0720] Basic operation of the system

[0721] 1. Data Collection:

[0722] User: Enters income and expenditure information such as monthly income, monthly expenses, and savings goal into the device. For example, the user enters this information into a smartphone app: "Monthly income: 300,000 yen, monthly expenses: 250,000 yen, savings goal: 40,000 yen."

[0723] Device: Stores the provided data in local storage and keeps it temporarily in memory. For example, store the data as follows: localStorage.setItem('income', '300000').

[0724] 2. Data Transmission and Analysis:

[0725] On the device: Send the collected data to the server using the HTTPS protocol. For example, send it as axios.post('https: / / api.example.com / data', data).

[0726] Server: Analyzes the received data using Python's Pandas library and calculates the potential savings. Specifically, it calculates savings_capacity = income - expenses.

[0727] 3. Warning message generation and advice generation:

[0728] Server: If the savings potential is below the target, generate a warning message. Example: "Saving potential is below the target. Please review your spending."

[0729] Server: Using a generative AI model (e.g., ChatGPT), a prompt such as "Please provide asset management advice for a user with a monthly income of 300,000 yen, expenses of 250,000 yen, and a savings goal of 40,000 yen" is input, and specific advice is generated.

[0730] 4. Displaying the results:

[0731] Server: Sends generated advice and warning messages to the device in JSON format, for example: response.json = {"advice": "...", "warning": "..."}.

[0732] Terminal: Display the received data in a user interface. For example, the HTML ... Insert a message inside.

[0733] 5. User Behavior:

[0734] User: Based on the advice and warning messages provided, they manage their spending and make investments. For example, they take concrete actions such as starting to keep a household budget or making use of hometown tax donations.

[0735] As an example of how the system works, let's take the case where a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. In this case, the system calculates that the user's possible savings amount is 50,000 yen, so no warning message is generated. Based on this data, the server generates specific advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses." It also suggests tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently" and investment advice such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[0736] Example prompt: "Monthly income: ¥300,000, monthly expenses: ¥250,000, savings goal: ¥40,000. Please provide specific advice to the user in this situation."

[0737] As described above, the present invention is a system that supports effective asset management by providing users with specific and practical advice on asset management and savings management.

[0738] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0739] Step 1:

[0740] The user enters their monthly income, monthly expenses, and savings goal into the terminal.

[0741] Specifically, the user enters "monthly income 300,000 yen, monthly expenses 250,000 yen, savings goal 40,000 yen" into the input form of the smartphone app. This is the input data. The output is that the input data is saved on the device.

[0742] Step 2:

[0743] The device saves the input data in local storage.

[0744] Specifically, the device uses commands such as localStorage.setItem('income', '300000') to store income information, expenditure information, and savings goals. The input is the data entered by the user. The output is the data stored in local storage.

[0745] Step 3:

[0746] The terminal transmits the collected data to the server.

[0747] Specifically, the terminal sends data using the HTTPS protocol, such as axios.post('https: / / api.example.com / data', data). The input is the data stored in local storage. The output is the data sent to the server.

[0748] Step 4:

[0749] The server parses the received data.

[0750] Specifically, the server analyzes the data using Python's Pandas library. For example, the code savings_capacity = income - expenses is used to calculate the amount of savings that can be made. The input is the data sent from the terminal, and the output is the calculated amount of savings that can be made.

[0751] Step 5:

[0752] The server checks the savings amount and generates a warning message if necessary.

[0753] Specifically, the server uses conditional branching to execute the following process: if savings_capacity < target_savings: warning_message = "Your savings potential is below your target. Please review your spending." The inputs are the calculated savings potential and the savings target. The output is a warning message.

[0754] Step 6:

[0755] The server uses the generative AI model to generate specific advice.

[0756] Specifically, the server inputs the prompt statement "Please provide asset management advice for the user's monthly income of 300,000 yen, expenses of 250,000 yen, and savings goal of 40,000 yen" into the generative AI model and generates advice. The input is the prompt statement and the user's data. The output is the generated advice.

[0757] Step 7:

[0758] The server sends generated advisory and warning messages to the terminal.

[0759] Specifically, the server packages the data in JSON format and sends it to the terminal as response.json = {"advice": "Your savings goal is achievable. Manage your daily expenses and refer to the tax advice for your tax return.", "warning": "Your savings potential is below your goal. Please review your expenses"}. The input is the generated advice and warning message. The output is the message sent to the terminal.

[0760] Step 8:

[0761] The terminal displays the received data on the user interface.

[0762] Specifically, the device uses HTML, CSS, and JavaScript to Your savings goals are achievable - take control of your daily expenses and get tax advice for your tax return. The input is the data sent from the server. The output is the message displayed on the user interface.

[0763] Step 9:

[0764] The user takes action based on the displayed advice and warning messages.

[0765] Specific actions that users take include reviewing income and expenditures, keeping a household account book, processing taxes, and using hometown tax donations. The input is the displayed advice and warning messages. The output is the specific actions taken by the user.

[0766] (Application example 1)

[0767] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0768] In today's society, many individuals lack knowledge about asset management and savings investments and are time-constrained. As a result, it is difficult to achieve effective savings goals and properly manage their assets. To solve these challenges, a user-friendly system is needed. Furthermore, there is a need for systems that can manage expenses in real time through integration with electronic payment platforms and provide detailed asset management advice using generative AI models.

[0769] 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.

[0770] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income data, expenditure data, and savings goals, and means for generating a warning message when the savings potential falls below the savings target. This allows the user to collect expenditure and income data in real time and receive detailed asset management advice. Furthermore, by displaying the generated advice and warning message to the user, the user can quickly understand their current expenditure and savings situation and manage their assets effectively and efficiently.

[0771] A "user" is an individual who utilizes the system to provide income data, expenditure data, and savings goals.

[0772] "Income Data" is information about all income earned by a user.

[0773] "Expense Data" is information about all expenses made by a user.

[0774] A "savings goal" is the amount of savings a user wants to achieve within a specific time period.

[0775] "Savings potential" is the amount you can actually save, obtained by subtracting expenses from income.

[0776] A "warning message" is a message generated to alert the user when the amount of savings available falls below the savings goal.

[0777] "Asset management advice" is a proposal for specific asset management and savings methods formulated based on the user's income, expenses, and savings.

[0778] An "electronic payment platform" is an online system that provides users with payment methods they use on a daily basis.

[0779] "Real time" refers to the fact that processing is carried out almost simultaneously at the moment an event occurs.

[0780] A "generative AI model" is an artificial intelligence model used to analyze user data and generate advice on asset management.

[0781] A "server" is a computer system that analyzes data collected from users and generates results.

[0782] "Analysis results" are the results of calculations and analyses performed by the server based on data provided by the user.

[0783] The system for implementing this invention works in conjunction with the electronic payment platform that users use on a daily basis to collect and analyze income data, expenditure data, and savings goals in real time. Specifically, the system automatically collects data when users perform daily transactions via their smartphones and transmits it to a server.

[0784] Program Overview

[0785] The server calculates the user's potential savings based on the collected income data, expenditure data, and savings goals, and generates a warning message if the savings goal is not reached. This process is performed using programming languages ​​such as Python. It also uses a generative AI model to generate specific advice on asset management for the user. This advice includes reviewing spending, streamlining tax procedures, and suggesting investment methods such as hometown tax payments and NISA savings.

[0786] Users can check these generated advice and warning messages in real time through smartphone applications that run on iOS and Android platforms, and the user interface is often implemented using frameworks such as React Native.

[0787] Hardware and Software

[0788] The following hardware and software are used to implement this system:

[0789] Hardware: Smartphone (iOS device, Android device)

[0790] software:

[0791] Python: Used to calculate savings potential and run generative AI models

[0792] React Native: Used to develop smartphone applications

[0793] Server platform: Cloud services such as AWS or Google Cloud Platform

[0794] Data processing and calculation

[0795] The server calculates the amount of savings possible based on the user's income and expenditure data. The data processing for this calculation includes the following steps:

[0796] 1. Normalizing data collected from users

[0797] 2. Calculating the difference between income and expenses using normalized data

[0798] 3. Generate a warning message if the difference is below the savings goal

[0799] 4. Generative AI model generates detailed advice

[0800] Specific examples

[0801] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the server calculates that the amount they can save is 50,000 yen. In this case, the server gives the user advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures," tax advice such as "Make sure to record your expenses and save receipts in order to file your tax return efficiently," and investment suggestions such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[0802] Prompt Sentence Examples

[0803] As a concrete example, the following prompts can be input to a generative AI model:

[0804] "If my income is 300,000 yen, my expenses are 250,000 yen, and my savings goal is 40,000 yen, how should I manage my assets?"

[0805] In this way, users can receive specific and practical advice tailored to their own financial situation.

[0806] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0807] Step 1:

[0808] Data collection

[0809] The user inputs their monthly income, monthly expenses, and savings goals through the device, which then collects and temporarily stores this data.

[0810] Input: Monthly income, monthly expenses, savings goal

[0811] Output: Collected income data, expenditure data, and savings goals

[0812] Step 2:

[0813] Sending data

[0814] The device sends the collected data to the server, using a secure communication protocol such as HTTPS.

[0815] Inputs: Collected income data, expenditure data, savings goals

[0816] Output: Collected data is sent to the server

[0817] Step 3:

[0818] Data analysis

[0819] The server analyzes the collected data and calculates the amount of savings possible by subtracting expenses from income. This calculation is done using Python.

[0820] Input: Collected data (income data, expenditure data, savings goal)

[0821] Output: Savings

[0822] Step 4:

[0823] Warning message generation

[0824] The server compares the calculated savings potential with the savings target and generates a warning message if the savings potential is less than the savings target.

[0825] Input: Savings Amount, Savings Goal

[0826] Output: Warning message

[0827] Step 5:

[0828] Applying generative AI models

[0829] The server uses the generative AI model to generate detailed asset management advice based on input data and calculated savings potential, including recommendations for reviewing spending, streamlining tax procedures, and investment options such as hometown tax payments and NISA savings.

[0830] Input: Collected data, Savings amount

[0831] Output: Wealth management advice

[0832] Step 6:

[0833] Sending advice and warning messages

[0834] The server generates advice and warning messages and sends them to the device, allowing the user to understand the situation in real time.

[0835] Input: Asset management advice, warning message

[0836] Output: Advisory and warning messages are sent to the terminal.

[0837] Step 7:

[0838] Display of advice and warning messages

[0839] The device displays the received advice and warning messages to the user, who can then check them through the smartphone application.

[0840] Input: Advice, warning message

[0841] Output: Display of advice and warning messages

[0842] Through this process, users can receive specific and practical advice tailored to their financial situation, and receive timely alerts to help them achieve their savings goals as planned.

[0843] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0844] This invention aims to enable users to effectively and efficiently manage their assets and savings through the "AI Money Support" system. In particular, by combining it with an emotion engine that recognizes the user's emotions, it aims to provide more personalized advice to each individual user.

[0845] Specifically, the system consists of the following steps:

[0846] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0847] Next, the device's built-in emotion engine recognizes the user's emotions when inputting or using the device. The emotion engine uses facial recognition and voice analysis technologies to extract emotional information from the user's facial expressions and tone of voice.

[0848] The device sends the collected data (income data, expenditure data, savings goal, and emotional information) to the server. The server analyzes the received data and calculates the user's savings potential by subtracting expenditure from income. If the savings potential falls below the savings goal, the server generates a warning message.

[0849] Based on the analysis results, the server generates specific advice for the user. This advice includes advice on how to manage expenses, tax advice for filing tax returns, and investment methods such as hometown tax donations and NISA savings. The server also adjusts the content and presentation of the advice based on the user's emotional information. For example, if the user is feeling stressed, the server can provide advice that includes encouraging words.

[0850] Furthermore, based on the user's emotional information, the system generates additional advice to reduce stress and improve motivation. For example, if the user is feeling stressed, the system can display a message such as, "Thank you for your hard work. It's important to take time to relax."

[0851] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0852] For example, if a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's estimated savings potential is 50,000 yen, so no warning message is generated. If the emotion engine recognizes that the user is relaxed, the server will provide regular asset management advice. On the other hand, if the user is feeling stressed, the server will provide advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[0853] This allows users to receive more personalized advice, easily receive services equivalent to those of a financial planner wherever they are, and achieve sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[0854] The processing flow will be explained below.

[0855] Step 1:

[0856] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[0857] Step 2:

[0858] The terminal displays a prompt saying, "Please enter your total monthly expenses," and the user enters the total monthly expenses. Next, the terminal displays a prompt saying, "Please enter your monthly savings goal," and the user enters the savings goal.

[0859] Step 3:

[0860] The emotion engine recognizes the user's face and voice to identify their current emotional state (e.g., relaxed, stressed, happy), and the device adds this emotional information to the data.

[0861] Step 4:

[0862] The device sends the collected data (income data, expenditure data, savings goals, emotional information) to a server.

[0863] Step 5:

[0864] The server analyzes the received data. It calculates the amount of savings that can be made by subtracting expenses from the user's income. For example, if the income is 300,000 yen and the expenses are 250,000 yen, the amount of savings that can be made is 50,000 yen.

[0865] Step 6:

[0866] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[0867] Step 7:

[0868] The server then generates specific advice for the user based on the analysis results, including information on how to manage expenses, tax advice for filing tax returns, and investment options such as hometown tax donations and NISA savings accounts.

[0869] Step 8:

[0870] The server takes into account the user's emotional information and adjusts the content and presentation of the advice. For example, if the user is feeling stressed, the server will provide advice that includes encouraging words, such as, "It's important to keep a record of your monthly income and expenses, but you should also take time to relax."

[0871] Step 9:

[0872] Furthermore, the server generates additional advice based on the user's emotional information to reduce stress and increase motivation, such as a message like "Thank you for your hard work. It's important to take time to relax."

[0873] Step 10:

[0874] The terminal displays the advice and warning messages received from the server to the user, allowing the user to understand the current spending and savings situation and manage their assets effectively.

[0875] In this way, the "AI Money Support" system, which combines an emotion engine, provides personalized advice that takes into account the user's emotional state, helping them achieve sound asset management.

[0876] Example 2

[0877] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0878] Conventional asset management systems do not provide advice that takes into account the user's emotional state, making it difficult to provide personalized support that reflects the user's mental state and motivation. Furthermore, advice based solely on the user's income and expenditure data is uniform and cannot fully address individual needs, which is a problem. Therefore, the present invention aims to achieve more effective and efficient asset management and savings management by taking into account the user's emotional information.

[0879] 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.

[0880] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditures from income based on the collected income data, expenditure data, and savings target, means for generating an alert message when the savings potential falls below the savings target, means for generating advice on asset management and savings investment using the calculated savings potential and the generated alert message, means for displaying the generated advice and alert message to the user, means for recognizing the user's emotions and adjusting the content and presentation of the advice based on the emotional information, and means for generating additional advice to reduce stress and increase motivation based on the user's emotional information. This allows the user to receive optimal advice tailored to their emotional state, enabling efficient asset management while reducing mental stress.

[0881] "Income data" is information about the amount of income a user receives.

[0882] "Expense data" is information on the amount of money that a user spends.

[0883] A "savings goal" is the amount of savings that a user wants to achieve within a certain period of time.

[0884] The "savings amount" is the amount that can be saved, calculated by subtracting expenses from the user's income.

[0885] An "alert message" is a warning message that is generated when the amount of available savings falls below the savings goal.

[0886] "Wealth management" is the act of effectively managing a user's financial assets, such as income, expenses, and savings.

[0887] "Savings management" refers to the plans and methods for how a user manages and increases their savings.

[0888] "Advice" means specific suggestions or advice regarding asset management and savings investment.

[0889] "Emotion information" is information about the user's emotional state extracted from facial expressions, tone of voice, and the like.

[0890] "Stress reduction" refers to actions or means to reduce the mental burden on the user.

[0891] "Motivation improvement" refers to actions or means to increase a user's motivation and enthusiasm.

[0892] The present invention aims to enable users to effectively and efficiently manage their assets and savings through an "AI Money Support" system. In particular, it aims to provide more personalized advice by combining it with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[0893] First, the terminal asks the user to input their monthly income, monthly expenses, and savings goal. After the user inputs this data, the terminal stores the input data in an internal database, which can be a commonly used database such as SQLite.

[0894] Next, the device's built-in emotion engine recognizes the user's emotions when typing or using the device. The emotion engine uses facial recognition and voice analysis technologies, such as Microsoft Azure Cognitive Services and Google Cloud Vision, to extract emotional information from the user's facial expressions and tone of voice.

[0895] The device then sends the collected income data, expenditure data, savings goals, and sentiment information to a server, typically using HTTP requests.

[0896] The server analyzes the received data using programming languages ​​such as Python and R. The server calculates the amount of savings that can be made by subtracting expenses from the user's income, and generates a warning message if the amount of savings that can be made falls short of the savings goal.

[0897] The server generates specific advice for the user based on the analysis results. This advice includes advice on asset management, tax advice, and investment options. Furthermore, the server adjusts the content and presentation of the advice based on the user's emotional information, and provides encouraging advice when the user is feeling stressed.

[0898] The server also generates additional advice based on the user's emotional information to reduce stress and improve motivation. For example, it generates a message such as, "Thank you for your hard work. Make sure you take time to relax," thereby reducing the user's mental burden.

[0899] Finally, the terminal displays the generated advice and warning messages to the user, allowing the user to understand the current income / expense and savings situation and manage their assets effectively.

[0900] As a concrete example, consider the case where a user enters the following data:

[0901] "Monthly income: 300,000 yen"

[0902] "Monthly expenses: 250,000 yen"

[0903] "Savings goal: 40,000 yen"

[0904] In this case, the system calculates the amount that can be saved as 50,000 yen, and no warning message is displayed. If the emotion engine recognizes that the user is relaxed, the server provides regular asset management advice. On the other hand, if the user is feeling stressed, the server provides advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[0905] An example of a prompt is as follows:

[0906] "I set my monthly income at 300,000 yen, my monthly expenses at 250,000 yen, and my monthly savings goal at 40,000 yen. The emotion engine recognized that the user was feeling stressed. Please generate the most appropriate advice."

[0907] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0908] Step 1:

[0909] The user inputs their monthly income, monthly expenses, and savings goal. The input data is sent to the device and saved. Specifically, if a user inputs a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, this data is stored in the device's internal database.

[0910] Input: Monthly income, monthly expenses, savings goal

[0911] Output: Input data stored in the database on the device

[0912] Step 2:

[0913] The device's built-in emotion engine recognizes the user's emotions. The emotion engine uses facial recognition and voice analysis technology to analyze the user's emotions when inputting or using the device. For example, Microsoft Azure Cognitive Services and Google Cloud Vision can be used to recognize emotions such as joy, sadness, and stress from the user's facial expressions and voice.

[0914] Input: User's face image, voice sample

[0915] Output: User's emotional information

[0916] Step 3:

[0917] The device sends the collected income data, expenditure data, savings goals, and emotional information to a server. The data is sent to the server using a protocol such as an HTTP request.

[0918] Input: Income data, expenditure data, savings goals, emotional information

[0919] Output: Data sent to the server

[0920] Step 4:

[0921] The server analyzes the received data using a programming language such as Python or R. For example, it calculates the amount of savings possible by subtracting expenses from the user's income and compares it with the savings goal.

[0922] Input: Income data, expenditure data, savings goals, emotional information

[0923] Output: Analysis results (savings potential, analysis results based on emotional information)

[0924] Step 5:

[0925] The server generates specific advice for the user based on the analysis results. The advice includes information on asset management, tax advice, and investment options. Furthermore, the content and presentation of the advice are adjusted based on the user's emotional information. For example, if the user's savings potential falls below their savings goal, a warning message is generated to reflect the user's emotional information.

[0926] Input: Analysis results (savings potential, analysis results based on emotional information)

[0927] Output: Generated advice and warning messages

[0928] Step 6:

[0929] The server generates additional advice to reduce stress and improve motivation based on the user's emotional information. For example, if the server detects that the user is feeling stressed, it generates a message such as, "Make sure to take time to relax."

[0930] Input: Emotion information

[0931] Output: Additional advice

[0932] Step 7:

[0933] The terminal displays the generated advice and warning messages to the user, who can then use this information to review their own asset management and savings practices, for example, by reviewing their spending or considering new investment options as needed.

[0934] Input: Generated advice, warning messages, additional advice

[0935] Output: Advice and warning messages displayed to the user

[0936] (Application example 2)

[0937] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0938] Conventional asset management systems provide advice based only on data such as income, expenses, and savings goals, and therefore are unable to provide personalized advice that takes into account the user's emotional state. As a result, even when users are feeling stressed or anxious, they are unable to receive support to relax or improve their motivation at the appropriate time, limiting the effectiveness of asset management. Therefore, there is a need for a system that supports more effective asset management and savings management while taking into account the user's emotions.

[0939] 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.

[0940] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings target, means for generating a warning message when the savings potential falls below the savings target, means for recognizing the user's emotions using an emotion recognition engine built into the terminal and extracting emotion information, means for generating advice on asset management and savings management using the calculated savings potential, the generated warning message, and the extracted emotion information, and means for displaying the generated advice and warning message to the user. This allows for the provision of personalized advice and messages that take the user's emotional state into consideration, enabling more effective and user-friendly asset management.

[0941] "Income information" refers to data on all income earned by a user, including salary, bonuses, income from side jobs, etc.

[0942] "Expense information" refers to data on all expenses consumed by a user, including rent, food, utilities, entertainment, etc.

[0943] A "savings goal" refers to the amount of savings a user aims to achieve within a particular time period.

[0944] "Savings available" refers to the funds remaining after subtracting expenses from income, and is the amount that a user can actually save.

[0945] "Warning Message" refers to a notification that is generated when the savings potential falls below the set savings goal.

[0946] An "emotion recognition engine" refers to a system that recognizes a user's emotions using facial recognition and voice analysis technology and extracts their emotional state.

[0947] "Emotion information" refers to data on the emotional state extracted by the emotion recognition engine from the user's facial expressions and tone of voice.

[0948] "Wealth management" refers to the process of properly managing your income, expenses, and savings to maintain financial well-being.

[0949] "Savings management" refers to the process of systematically managing and investing funds toward a user's savings goal.

[0950] "Advice" refers to advice or guidance provided based on a user's income information, expenditure information, savings goals, savings potential, and emotional information.

[0951] "Server" refers to a computer system for collecting, analyzing, and storing data, and providing information to users.

[0952] The present invention relates to a system that allows users to effectively manage their assets and savings by inputting their income information, expenditure information, and savings goals. This system provides more personalized advice by incorporating an emotion recognition engine that recognizes the user's emotions.

[0953] First, the user uses a device such as a smartphone or tablet to input their monthly income, monthly expenses, and savings goal. This data is stored on the device. The device's built-in emotion recognition engine then analyzes the user's facial expressions and tone of voice to extract emotional information. This emotion recognition engine utilizes face recognition technology and voice analysis technology using OpenCV.

[0954] The terminal then sends the collected income information, expenditure information, savings goal, and emotional information to the server. The server receives this data and calculates the amount of savings that can be made by subtracting expenditure from income. Based on this calculation result, if the amount of savings that can be made falls below the savings goal, a warning message is generated. The server also generates personalized advice that takes the emotional information into account.

[0955] For example, if a user sets their monthly income at 300,000 yen, their monthly expenses at 250,000 yen, and their savings goal at 40,000 yen, the server will calculate the amount they can save as 50,000 yen. The emotion recognition engine also detects that the user is relaxed. Based on this, the server will provide them with regular asset management advice, as well as a message encouraging them to make time to relax.

[0956] The generated advice and warning messages are displayed to the user via the device, allowing the user to understand their current income, expenditure, and savings situation and manage their assets more effectively.In addition, additional advice based on emotional information is provided to reduce stress and increase motivation, providing psychological support to the user.

[0957] Here are some example prompts to pass to a generative AI model:

[0958] The user has set a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. The user's emotion is recognized as relaxation. Based on this condition, generate advice to provide to the user. Additionally, add a message to reduce stress.

[0959] Thus, the present invention provides a wealth management system that takes into account the user's financial and emotional state, resulting in a more effective and user-friendly approach.

[0960] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0961] Step 1:

[0962] The terminal allows the user to input income information, expenditure information, and savings goals. The user inputs monthly income, monthly expenditure, and savings goals. The terminal stores this data in a consolidated manner. The input data becomes the basic data required for subsequent processing.

[0963] Step 2:

[0964] The device's built-in emotion recognition engine recognizes the user's emotions, capturing the user's facial expressions and tone of voice to extract emotional information. This processing is performed using OpenCV and voice analysis technology. The acquired emotional information is used to tailor advice based on the user's financial behavior.

[0965] Step 3:

[0966] The terminal transmits the collected income information, expenditure information, savings goal, and emotional information to the server, which receives and analyzes this data.

[0967] Step 4:

[0968] The server analyzes the received data and calculates the amount of savings that can be made by subtracting expenses from income. This calculation is based on income information and expenditure information. The calculated amount of savings that can be made is the amount that the user can actually save.

[0969] Step 5:

[0970] The server compares the available savings amount with the savings goal, and if the available savings amount is less than the savings goal, it generates a warning message to remind the user to achieve the savings goal.

[0971] Step 6:

[0972] The server takes emotional information into account to generate personalized advice on asset management and savings, including specific suggestions on how to manage income and expenses and investment options, as well as encouraging messages and additional advice to reduce stress depending on the user's emotional state.

[0973] Step 7:

[0974] The server generates advice and warning messages and sends them to the terminal, which receives them and displays them to the user, allowing the user to understand the current asset status and take action based on the advice.

[0975] Through these steps, users can receive specific and personalized advice based on their individual financial and emotional situations, leading to more effective asset management.

[0976] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0977] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0978] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[0979] [Fourth embodiment]

[0980] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0981] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0982] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0983] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0984] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0985] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0986] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0987] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0988] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0989] 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.

[0990] 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.

[0991] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0992] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[0993] The present invention enables users to effectively and efficiently manage their assets and savings through the "AI Money Support" system, which collects, analyzes, and provides advice on income, expenditure, and savings goals provided by users.

[0994] Specifically, the system consists of the following steps:

[0995] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[0996] Next, the device sends the collected data to the server. The server analyzes the received data and calculates the user's possible savings by subtracting expenses from their income. If the possible savings amount falls below the savings goal, the server generates a warning message. For example, if the user enters a monthly income of 300,000 yen and monthly expenses of 250,000 yen, the possible savings amount will be 50,000 yen. In this case, if the user's savings goal is 40,000 yen, there is no problem, but if it falls below 50,000 yen, a warning message will be generated.

[0997] The server then generates specific advice for the user based on the analysis results, including advice on daily spending management, tax advice for filing tax returns, and advice on investment methods such as hometown tax donations and NISA savings accounts, allowing users to understand specific and practical ways to manage their assets.

[0998] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[0999] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's calculated savings potential is 50,000 yen, so no warning message will be displayed. The system will provide the user with advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses," as well as tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently," and investment advice such as "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[1000] This allows users to easily receive services equivalent to those of a financial planner wherever they are, enabling sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[1001] The processing flow will be explained below.

[1002] Step 1:

[1003] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[1004] Step 2:

[1005] The terminal then prompts the user to "Enter your monthly expenses," and the user enters their monthly expenses. The terminal then prompts the user to "Enter your monthly savings goal," and the user enters their savings goal.

[1006] Step 3:

[1007] The device sends the collected data (income data, expenditure data, savings goals) to the server.

[1008] Step 4:

[1009] The server analyzes the received data. The server subtracts the user's expenses from their income to calculate the amount they can save. For example, if their income is 300,000 yen and their expenses are 250,000 yen, their savings amount is 50,000 yen.

[1010] Step 5:

[1011] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[1012] Step 6:

[1013] The server then uses the analysis results to generate specific advice for the user, including information on spending management, tax treatment, and investment options.

[1014] Step 7:

[1015] The device displays advice and warning messages received from the server to the user. For example, it displays information such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures" or "You can save more efficiently by taking advantage of tax-advantaged systems such as hometown tax donations and NISA savings."

[1016] This is the specific flow of processing in the "AI Money Support" system. Users can implement effective asset management based on this advice.

[1017] Example 1

[1018] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1019] Currently, many people find it difficult to effectively manage their income and expenditures and manage their savings, especially because they have limited opportunities to receive specific advice on achieving their savings goals. Furthermore, there are insufficient systems that analyze income and expenditure data and automatically suggest appropriate measures based on the results. This makes it difficult for users to easily grasp their income and expenditure situation and implement improvement measures. Therefore, an objective of the present invention is to provide a system that allows users to effectively and efficiently manage their assets and manage their savings.

[1020] 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.

[1021] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings goals, means for generating a warning message when the savings potential falls below the savings target, means for generating advice on asset management and savings management using the calculated savings potential and the generated warning message, and means for displaying the generated advice and warning message to the user, thereby enabling the user to clearly understand the income and expenditure situation and to appropriately manage assets and savings.

[1022] "Income information" is data indicating the amount of regular income of the user.

[1023] "Expense information" is data indicating the amount of regular expenditures of a user.

[1024] A "savings goal" is a target value that indicates the amount of savings that a user wishes to achieve within a certain period of time.

[1025] "Means for collecting" refers to methods and devices for obtaining income information, expenditure information, and savings goals from a user.

[1026] The "means for calculating the savable amount by subtraction" refers to a method or device for calculating the savable amount calculated by subtracting expenditure information from income information.

[1027] The term "means for generating a warning message" refers to a method or device that generates a message to alert the user when the amount of savings available falls below the savings goal.

[1028] The "means for generating advice" refers to a method or device that provides a user with suggestions or recommendations regarding asset management and savings management based on the calculated savings potential and the generated warning message.

[1029] The "displaying means" refers to a method or device for displaying the generated advice and warning messages on a terminal used by a user.

[1030] "Means for transmitting to a server" refers to a method or device for transmitting the collected income information, expenditure information, and savings goals to a server via the Internet or other communications network.

[1031] "Means for receiving the analysis results" refers to a method or device for receiving the analyzed data and results sent from the server at the user's terminal.

[1032] "Wealth Management Advice" means specific suggestions and recommendations for effectively managing and growing your assets.

[1033] "Tax advice" refers to specific suggestions and recommendations for calculating and filing taxes efficiently.

[1034] "Expense Management Advice" refers to specific suggestions and recommendations for effectively managing a user's day-to-day expenses.

[1035] The present invention relates to an "AI Money Support" system that collects income information, expenditure information, and savings goals, and provides advice for effective asset management and savings management. The system operates using a server, a terminal, and a generative AI model.

[1036] Hardware and software used

[1037] Hardware: Devices used by users (e.g. smartphones, PCs), servers

[1038] Software: User interface software (e.g., web application, mobile app), data analysis software (e.g., Python + Pandas), advice translator (e.g., ChatGPT), warning generation module (e.g., JavaScript)

[1039] Basic operation of the system

[1040] 1. Data Collection:

[1041] User: Enters income and expenditure information such as monthly income, monthly expenses, and savings goal into the device. For example, the user enters this information into a smartphone app: "Monthly income: 300,000 yen, monthly expenses: 250,000 yen, savings goal: 40,000 yen."

[1042] Device: Stores the provided data in local storage and keeps it temporarily in memory. For example, store the data as follows: localStorage.setItem('income', '300000').

[1043] 2. Data Transmission and Analysis:

[1044] On the device: Send the collected data to the server using the HTTPS protocol. For example, send it as axios.post('https: / / api.example.com / data', data).

[1045] Server: Analyzes the received data using Python's Pandas library and calculates the potential savings. Specifically, it calculates savings_capacity = income - expenses.

[1046] 3. Warning message generation and advice generation:

[1047] Server: If the savings potential is below the target, generate a warning message. Example: "Saving potential is below the target. Please review your spending."

[1048] Server: Using a generative AI model (e.g., ChatGPT), a prompt such as "Please provide asset management advice for a user with a monthly income of 300,000 yen, expenses of 250,000 yen, and a savings goal of 40,000 yen" is input, and specific advice is generated.

[1049] 4. Displaying the results:

[1050] Server: Sends generated advice and warning messages to the device in JSON format, for example: response.json = {"advice": "...", "warning": "..."}.

[1051] Terminal: Display the received data in a user interface. For example, the HTML ... Insert a message inside.

[1052] 5. User Behavior:

[1053] User: Based on the advice and warning messages provided, they manage their spending and make investments. For example, they take concrete actions such as starting to keep a household budget or making use of hometown tax donations.

[1054] As an example of how the system works, let's take the case where a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. In this case, the system calculates that the user's possible savings amount is 50,000 yen, so no warning message is generated. Based on this data, the server generates specific advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenses." It also suggests tax advice such as "Make sure to record your expenses and save receipts to file your tax return efficiently" and investment advice such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[1055] Example prompt: "Monthly income: ¥300,000, monthly expenses: ¥250,000, savings goal: ¥40,000. Please provide specific advice to the user in this situation."

[1056] As described above, the present invention is a system that supports effective asset management by providing users with specific and practical advice on asset management and savings management.

[1057] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1058] Step 1:

[1059] The user enters their monthly income, monthly expenses, and savings goal into the terminal.

[1060] Specifically, the user enters "monthly income 300,000 yen, monthly expenses 250,000 yen, savings goal 40,000 yen" into the input form of the smartphone app. This is the input data. The output is that the input data is saved on the device.

[1061] Step 2:

[1062] The device saves the input data in local storage.

[1063] Specifically, the device uses commands such as localStorage.setItem('income', '300000') to store income information, expenditure information, and savings goals. The input is the data entered by the user. The output is the data stored in local storage.

[1064] Step 3:

[1065] The terminal transmits the collected data to the server.

[1066] Specifically, the terminal sends data using the HTTPS protocol, such as axios.post('https: / / api.example.com / data', data). The input is the data stored in local storage. The output is the data sent to the server.

[1067] Step 4:

[1068] The server parses the received data.

[1069] Specifically, the server analyzes the data using Python's Pandas library. For example, the code savings_capacity = income - expenses is used to calculate the amount of savings that can be made. The input is the data sent from the terminal, and the output is the calculated amount of savings that can be made.

[1070] Step 5:

[1071] The server checks the savings amount and generates a warning message if necessary.

[1072] Specifically, the server uses conditional branching to execute the following process: if savings_capacity < target_savings: warning_message = "Your savings potential is below your target. Please review your spending." The inputs are the calculated savings potential and the savings target. The output is a warning message.

[1073] Step 6:

[1074] The server uses the generative AI model to generate specific advice.

[1075] Specifically, the server inputs the prompt statement "Please provide asset management advice for the user's monthly income of 300,000 yen, expenses of 250,000 yen, and savings goal of 40,000 yen" into the generative AI model and generates advice. The input is the prompt statement and the user's data. The output is the generated advice.

[1076] Step 7:

[1077] The server sends generated advisory and warning messages to the terminal.

[1078] Specifically, the server packages the data in JSON format and sends it to the terminal as response.json = {"advice": "Your savings goal is achievable. Manage your daily expenses and refer to the tax advice for your tax return.", "warning": "Your savings potential is below your goal. Please review your expenses"}. The input is the generated advice and warning message. The output is the message sent to the terminal.

[1079] Step 8:

[1080] The terminal displays the received data on the user interface.

[1081] Specifically, the device uses HTML, CSS, and JavaScript to Your savings goals are achievable - take control of your daily expenses and get tax advice for your tax return. The input is the data sent from the server. The output is the message displayed on the user interface.

[1082] Step 9:

[1083] The user takes action based on the displayed advice and warning messages.

[1084] Specific actions that users take include reviewing income and expenditures, keeping a household account book, processing taxes, and using hometown tax donations. The input is the displayed advice and warning messages. The output is the specific actions taken by the user.

[1085] (Application example 1)

[1086] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1087] In today's society, many individuals lack knowledge about asset management and savings investments and are time-constrained. As a result, it is difficult to achieve effective savings goals and properly manage their assets. To solve these challenges, a user-friendly system is needed. Furthermore, there is a need for systems that can manage expenses in real time through integration with electronic payment platforms and provide detailed asset management advice using generative AI models.

[1088] 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.

[1089] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income data, expenditure data, and savings goals, and means for generating a warning message when the savings potential falls below the savings target. This allows the user to collect expenditure and income data in real time and receive detailed asset management advice. Furthermore, by displaying the generated advice and warning message to the user, the user can quickly understand their current expenditure and savings situation and manage their assets effectively and efficiently.

[1090] A "user" is an individual who utilizes the system to provide income data, expenditure data, and savings goals.

[1091] "Income Data" is information about all income earned by a user.

[1092] "Expense Data" is information about all expenses made by a user.

[1093] A "savings goal" is the amount of savings a user wants to achieve within a specific time period.

[1094] "Savings potential" is the amount you can actually save, obtained by subtracting expenses from income.

[1095] A "warning message" is a message generated to alert the user when the amount of savings available falls below the savings goal.

[1096] "Asset management advice" is a proposal for specific asset management and savings methods formulated based on the user's income, expenses, and savings.

[1097] An "electronic payment platform" is an online system that provides users with payment methods they use on a daily basis.

[1098] "Real time" refers to the fact that processing is carried out almost simultaneously at the moment an event occurs.

[1099] A "generative AI model" is an artificial intelligence model used to analyze user data and generate advice on asset management.

[1100] A "server" is a computer system that analyzes data collected from users and generates results.

[1101] "Analysis results" are the results of calculations and analyses performed by the server based on data provided by the user.

[1102] The system for implementing this invention works in conjunction with the electronic payment platform that users use on a daily basis to collect and analyze income data, expenditure data, and savings goals in real time. Specifically, the system automatically collects data when users perform daily transactions via their smartphones and transmits it to a server.

[1103] Program Overview

[1104] The server calculates the user's potential savings based on the collected income data, expenditure data, and savings goals, and generates a warning message if the savings goal is not reached. This process is performed using programming languages ​​such as Python. It also uses a generative AI model to generate specific advice on asset management for the user. This advice includes reviewing spending, streamlining tax procedures, and suggesting investment methods such as hometown tax payments and NISA savings.

[1105] Users can check these generated advice and warning messages in real time through smartphone applications that run on iOS and Android platforms, and the user interface is often implemented using frameworks such as React Native.

[1106] Hardware and Software

[1107] The following hardware and software are used to implement this system:

[1108] Hardware: Smartphone (iOS device, Android device)

[1109] software:

[1110] Python: Used to calculate savings potential and run generative AI models

[1111] React Native: Used to develop smartphone applications

[1112] Server platform: Cloud services such as AWS or Google Cloud Platform

[1113] Data processing and calculation

[1114] The server calculates the amount of savings possible based on the user's income and expenditure data. The data processing for this calculation includes the following steps:

[1115] 1. Normalizing data collected from users

[1116] 2. Calculating the difference between income and expenses using normalized data

[1117] 3. Generate a warning message if the difference is below the savings goal

[1118] 4. Generative AI model generates detailed advice

[1119] Specific examples

[1120] For example, if a user has a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the server calculates that the amount they can save is 50,000 yen. In this case, the server gives the user advice such as "It's a good idea to manage your daily expenses and record your monthly income and expenditures," tax advice such as "Make sure to record your expenses and save receipts in order to file your tax return efficiently," and investment suggestions such as "You can save more efficiently by taking advantage of tax-advantage systems such as hometown tax donations and NISA savings."

[1121] Prompt Sentence Examples

[1122] As a concrete example, the following prompts can be input to a generative AI model:

[1123] "If my income is 300,000 yen, my expenses are 250,000 yen, and my savings goal is 40,000 yen, how should I manage my assets?"

[1124] In this way, users can receive specific and practical advice tailored to their own financial situation.

[1125] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1126] Step 1:

[1127] Data collection

[1128] The user inputs their monthly income, monthly expenses, and savings goals through the device, which then collects and temporarily stores this data.

[1129] Input: Monthly income, monthly expenses, savings goal

[1130] Output: Collected income data, expenditure data, and savings goals

[1131] Step 2:

[1132] Sending data

[1133] The device sends the collected data to the server, using a secure communication protocol such as HTTPS.

[1134] Inputs: Collected income data, expenditure data, savings goals

[1135] Output: Collected data is sent to the server

[1136] Step 3:

[1137] Data analysis

[1138] The server analyzes the collected data and calculates the amount of savings possible by subtracting expenses from income. This calculation is done using Python.

[1139] Input: Collected data (income data, expenditure data, savings goal)

[1140] Output: Savings

[1141] Step 4:

[1142] Warning message generation

[1143] The server compares the calculated savings potential with the savings target and generates a warning message if the savings potential is less than the savings target.

[1144] Input: Savings Amount, Savings Goal

[1145] Output: Warning message

[1146] Step 5:

[1147] Applying generative AI models

[1148] The server uses the generative AI model to generate detailed asset management advice based on input data and calculated savings potential, including recommendations for reviewing spending, streamlining tax procedures, and investment options such as hometown tax payments and NISA savings.

[1149] Input: Collected data, Savings amount

[1150] Output: Wealth management advice

[1151] Step 6:

[1152] Sending advice and warning messages

[1153] The server generates advice and warning messages and sends them to the device, allowing the user to understand the situation in real time.

[1154] Input: Asset management advice, warning message

[1155] Output: Advisory and warning messages are sent to the terminal.

[1156] Step 7:

[1157] Display of advice and warning messages

[1158] The device displays the received advice and warning messages to the user, who can then check them through the smartphone application.

[1159] Input: Advice, warning message

[1160] Output: Display of advice and warning messages

[1161] Through this process, users can receive specific and practical advice tailored to their financial situation, and receive timely alerts to help them achieve their savings goals as planned.

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

[1163] This invention aims to enable users to effectively and efficiently manage their assets and savings through the "AI Money Support" system. In particular, by combining it with an emotion engine that recognizes the user's emotions, it aims to provide more personalized advice to each individual user.

[1164] Specifically, the system consists of the following steps:

[1165] First, the terminal allows the user to input income data, expenditure data, and savings goals. When the user inputs monthly income, monthly expenditure, and monthly savings goals, the terminal collectively stores these data.

[1166] Next, the device's built-in emotion engine recognizes the user's emotions when inputting or using the device. The emotion engine uses facial recognition and voice analysis technologies to extract emotional information from the user's facial expressions and tone of voice.

[1167] The device sends the collected data (income data, expenditure data, savings goal, and emotional information) to the server. The server analyzes the received data and calculates the user's savings potential by subtracting expenditure from income. If the savings potential falls below the savings goal, the server generates a warning message.

[1168] Based on the analysis results, the server generates specific advice for the user. This advice includes advice on how to manage expenses, tax advice for filing tax returns, and investment methods such as hometown tax donations and NISA savings. The server also adjusts the content and presentation of the advice based on the user's emotional information. For example, if the user is feeling stressed, the server can provide advice that includes encouraging words.

[1169] Furthermore, based on the user's emotional information, the system generates additional advice to reduce stress and improve motivation. For example, if the user is feeling stressed, the system can display a message such as, "Thank you for your hard work. It's important to take time to relax."

[1170] Finally, the terminal displays the generated advice and warning messages to the user, which allows the user to understand the current spending and savings situation and manage their assets effectively.

[1171] For example, if a user sets a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, the system's estimated savings potential is 50,000 yen, so no warning message is generated. If the emotion engine recognizes that the user is relaxed, the server will provide regular asset management advice. On the other hand, if the user is feeling stressed, the server will provide advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[1172] This allows users to receive more personalized advice, easily receive services equivalent to those of a financial planner wherever they are, and achieve sound asset management. This invention will be an extremely useful system for many people who lack knowledge about asset management or who are limited by time.

[1173] The processing flow will be explained below.

[1174] Step 1:

[1175] The user launches the application and accesses the data entry screen. The terminal prompts the user to "Enter your monthly income," and the user enters their monthly income.

[1176] Step 2:

[1177] The terminal displays a prompt saying, "Please enter your total monthly expenses," and the user enters the total monthly expenses. Next, the terminal displays a prompt saying, "Please enter your monthly savings goal," and the user enters the savings goal.

[1178] Step 3:

[1179] The emotion engine recognizes the user's face and voice to identify their current emotional state (e.g., relaxed, stressed, happy), and the device adds this emotional information to the data.

[1180] Step 4:

[1181] The device sends the collected data (income data, expenditure data, savings goals, emotional information) to a server.

[1182] Step 5:

[1183] The server analyzes the received data. It calculates the amount of savings that can be made by subtracting expenses from the user's income. For example, if the income is 300,000 yen and the expenses are 250,000 yen, the amount of savings that can be made is 50,000 yen.

[1184] Step 6:

[1185] If the amount of savings that can be saved is less than the user's savings goal, the server generates a warning message. For example, if the amount of savings that can be saved is 30,000 yen and the savings goal is 40,000 yen, the server generates a message saying, "Warning! Your current expenses are too high. To save 40,000 yen each month, you need to reduce your expenses."

[1186] Step 7:

[1187] The server then generates specific advice for the user based on the analysis results, including information on how to manage expenses, tax advice for filing tax returns, and investment options such as hometown tax donations and NISA savings accounts.

[1188] Step 8:

[1189] The server takes into account the user's emotional information and adjusts the content and presentation of the advice. For example, if the user is feeling stressed, the server will provide advice that includes encouraging words, such as, "It's important to keep a record of your monthly income and expenses, but you should also take time to relax."

[1190] Step 9:

[1191] Furthermore, the server generates additional advice based on the user's emotional information to reduce stress and increase motivation, such as a message like "Thank you for your hard work. It's important to take time to relax."

[1192] Step 10:

[1193] The terminal displays the advice and warning messages received from the server to the user, allowing the user to understand the current spending and savings situation and manage their assets effectively.

[1194] In this way, the "AI Money Support" system, which combines an emotion engine, provides personalized advice that takes into account the user's emotional state, helping them achieve sound asset management.

[1195] Example 2

[1196] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1197] Conventional asset management systems do not provide advice that takes into account the user's emotional state, making it difficult to provide personalized support that reflects the user's mental state and motivation. Furthermore, advice based solely on the user's income and expenditure data is uniform and cannot fully address individual needs, which is a problem. Therefore, the present invention aims to achieve more effective and efficient asset management and savings management by taking into account the user's emotional information.

[1198] 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.

[1199] In this invention, the server includes means for collecting income data, expenditure data, and savings goals from a user, means for calculating a savings potential by subtracting expenditures from income based on the collected income data, expenditure data, and savings target, means for generating an alert message when the savings potential falls below the savings target, means for generating advice on asset management and savings investment using the calculated savings potential and the generated alert message, means for displaying the generated advice and alert message to the user, means for recognizing the user's emotions and adjusting the content and presentation of the advice based on the emotional information, and means for generating additional advice to reduce stress and increase motivation based on the user's emotional information. This allows the user to receive optimal advice tailored to their emotional state, enabling efficient asset management while reducing mental stress.

[1200] "Income data" is information about the amount of income a user receives.

[1201] "Expense data" is information on the amount of money that a user spends.

[1202] A "savings goal" is the amount of savings that a user wants to achieve within a certain period of time.

[1203] The "savings amount" is the amount that can be saved, calculated by subtracting expenses from the user's income.

[1204] An "alert message" is a warning message that is generated when the amount of available savings falls below the savings goal.

[1205] "Wealth management" is the act of effectively managing a user's financial assets, such as income, expenses, and savings.

[1206] "Savings management" refers to the plans and methods for how a user manages and increases their savings.

[1207] "Advice" means specific suggestions or advice regarding asset management and savings investment.

[1208] "Emotion information" is information about the user's emotional state extracted from facial expressions, tone of voice, and the like.

[1209] "Stress reduction" refers to actions or means to reduce the mental burden on the user.

[1210] "Motivation improvement" refers to actions or means to increase a user's motivation and enthusiasm.

[1211] The present invention aims to enable users to effectively and efficiently manage their assets and savings through an "AI Money Support" system. In particular, it aims to provide more personalized advice by combining it with an emotion engine that recognizes the user's emotions. Specific embodiments of this system are described below.

[1212] First, the terminal asks the user to input their monthly income, monthly expenses, and savings goal. After the user inputs this data, the terminal stores the input data in an internal database, which can be a commonly used database such as SQLite.

[1213] Next, the device's built-in emotion engine recognizes the user's emotions when typing or using the device. The emotion engine uses facial recognition and voice analysis technologies, such as Microsoft Azure Cognitive Services and Google Cloud Vision, to extract emotional information from the user's facial expressions and tone of voice.

[1214] The device then sends the collected income data, expenditure data, savings goals, and sentiment information to a server, typically using HTTP requests.

[1215] The server analyzes the received data using programming languages ​​such as Python and R. The server calculates the amount of savings that can be made by subtracting expenses from the user's income, and generates a warning message if the amount of savings that can be made falls short of the savings goal.

[1216] The server generates specific advice for the user based on the analysis results. This advice includes advice on asset management, tax advice, and investment options. Furthermore, the server adjusts the content and presentation of the advice based on the user's emotional information, and provides encouraging advice when the user is feeling stressed.

[1217] The server also generates additional advice based on the user's emotional information to reduce stress and improve motivation. For example, it generates a message such as, "Thank you for your hard work. Make sure you take time to relax," thereby reducing the user's mental burden.

[1218] Finally, the terminal displays the generated advice and warning messages to the user, allowing the user to understand the current income / expense and savings situation and manage their assets effectively.

[1219] As a concrete example, consider the case where a user enters the following data:

[1220] "Monthly income: 300,000 yen"

[1221] "Monthly expenses: 250,000 yen"

[1222] "Savings goal: 40,000 yen"

[1223] In this case, the system calculates the amount that can be saved as 50,000 yen, and no warning message is displayed. If the emotion engine recognizes that the user is relaxed, the server provides regular asset management advice. On the other hand, if the user is feeling stressed, the server provides advice such as, "It's important to keep a record of your monthly income and expenses, but make sure you also take time to relax."

[1224] An example of a prompt is as follows:

[1225] "I set my monthly income at 300,000 yen, my monthly expenses at 250,000 yen, and my monthly savings goal at 40,000 yen. The emotion engine recognized that the user was feeling stressed. Please generate the most appropriate advice."

[1226] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1227] Step 1:

[1228] The user inputs their monthly income, monthly expenses, and savings goal. The input data is sent to the device and saved. Specifically, if a user inputs a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen, this data is stored in the device's internal database.

[1229] Input: Monthly income, monthly expenses, savings goal

[1230] Output: Input data stored in the database on the device

[1231] Step 2:

[1232] The device's built-in emotion engine recognizes the user's emotions. The emotion engine uses facial recognition and voice analysis technology to analyze the user's emotions when inputting or using the device. For example, Microsoft Azure Cognitive Services and Google Cloud Vision can be used to recognize emotions such as joy, sadness, and stress from the user's facial expressions and voice.

[1233] Input: User's face image, voice sample

[1234] Output: User's emotional information

[1235] Step 3:

[1236] The device sends the collected income data, expenditure data, savings goals, and emotional information to a server. The data is sent to the server using a protocol such as an HTTP request.

[1237] Input: Income data, expenditure data, savings goals, emotional information

[1238] Output: Data sent to the server

[1239] Step 4:

[1240] The server analyzes the received data using a programming language such as Python or R. For example, it calculates the amount of savings possible by subtracting expenses from the user's income and compares it with the savings goal.

[1241] Input: Income data, expenditure data, savings goals, emotional information

[1242] Output: Analysis results (savings potential, analysis results based on emotional information)

[1243] Step 5:

[1244] The server generates specific advice for the user based on the analysis results. The advice includes information on asset management, tax advice, and investment options. Furthermore, the content and presentation of the advice are adjusted based on the user's emotional information. For example, if the user's savings potential falls below their savings goal, a warning message is generated to reflect the user's emotional information.

[1245] Input: Analysis results (savings potential, analysis results based on emotional information)

[1246] Output: Generated advice and warning messages

[1247] Step 6:

[1248] The server generates additional advice to reduce stress and improve motivation based on the user's emotional information. For example, if the server detects that the user is feeling stressed, it generates a message such as, "Make sure to take time to relax."

[1249] Input: Emotion information

[1250] Output: Additional advice

[1251] Step 7:

[1252] The terminal displays the generated advice and warning messages to the user, who can then use this information to review their own asset management and savings practices, for example, by reviewing their spending or considering new investment options as needed.

[1253] Input: Generated advice, warning messages, additional advice

[1254] Output: Advice and warning messages displayed to the user

[1255] (Application example 2)

[1256] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1257] Conventional asset management systems provide advice based only on data such as income, expenses, and savings goals, and therefore are unable to provide personalized advice that takes into account the user's emotional state. As a result, even when users are feeling stressed or anxious, they are unable to receive support to relax or improve their motivation at the appropriate time, limiting the effectiveness of asset management. Therefore, there is a need for a system that supports more effective asset management and savings management while taking into account the user's emotions.

[1258] 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.

[1259] In this invention, the server includes means for collecting income information, expenditure information, and savings goals from a user, means for calculating a savings potential by subtracting expenditure from income based on the collected income information, expenditure information, and savings target, means for generating a warning message when the savings potential falls below the savings target, means for recognizing the user's emotions using an emotion recognition engine built into the terminal and extracting emotion information, means for generating advice on asset management and savings management using the calculated savings potential, the generated warning message, and the extracted emotion information, and means for displaying the generated advice and warning message to the user. This allows for the provision of personalized advice and messages that take the user's emotional state into consideration, enabling more effective and user-friendly asset management.

[1260] "Income information" refers to data on all income earned by a user, including salary, bonuses, income from side jobs, etc.

[1261] "Expense information" refers to data on all expenses consumed by a user, including rent, food, utilities, entertainment, etc.

[1262] A "savings goal" refers to the amount of savings a user aims to achieve within a particular time period.

[1263] "Savings available" refers to the funds remaining after subtracting expenses from income, and is the amount that a user can actually save.

[1264] "Warning Message" refers to a notification that is generated when the savings potential falls below the set savings goal.

[1265] An "emotion recognition engine" refers to a system that recognizes a user's emotions using facial recognition and voice analysis technology and extracts their emotional state.

[1266] "Emotion information" refers to data on the emotional state extracted by the emotion recognition engine from the user's facial expressions and tone of voice.

[1267] "Wealth management" refers to the process of properly managing your income, expenses, and savings to maintain financial well-being.

[1268] "Savings management" refers to the process of systematically managing and investing funds toward a user's savings goal.

[1269] "Advice" refers to advice or guidance provided based on a user's income information, expenditure information, savings goals, savings potential, and emotional information.

[1270] "Server" refers to a computer system for collecting, analyzing, and storing data, and providing information to users.

[1271] The present invention relates to a system that allows users to effectively manage their assets and savings by inputting their income information, expenditure information, and savings goals. This system provides more personalized advice by incorporating an emotion recognition engine that recognizes the user's emotions.

[1272] First, the user uses a device such as a smartphone or tablet to input their monthly income, monthly expenses, and savings goal. This data is stored on the device. The device's built-in emotion recognition engine then analyzes the user's facial expressions and tone of voice to extract emotional information. This emotion recognition engine utilizes face recognition technology and voice analysis technology using OpenCV.

[1273] The terminal then sends the collected income information, expenditure information, savings goal, and emotional information to the server. The server receives this data and calculates the amount of savings that can be made by subtracting expenditure from income. Based on this calculation result, if the amount of savings that can be made falls below the savings goal, a warning message is generated. The server also generates personalized advice that takes the emotional information into account.

[1274] For example, if a user sets their monthly income at 300,000 yen, their monthly expenses at 250,000 yen, and their savings goal at 40,000 yen, the server will calculate the amount they can save as 50,000 yen. The emotion recognition engine also detects that the user is relaxed. Based on this, the server will provide them with regular asset management advice, as well as a message encouraging them to make time to relax.

[1275] The generated advice and warning messages are displayed to the user via the device, allowing the user to understand their current income, expenditure, and savings situation and manage their assets more effectively.In addition, additional advice based on emotional information is provided to reduce stress and increase motivation, providing psychological support to the user.

[1276] Here are some example prompts to pass to a generative AI model:

[1277] The user has set a monthly income of 300,000 yen, monthly expenses of 250,000 yen, and a savings goal of 40,000 yen. The user's emotion is recognized as relaxation. Based on this condition, generate advice to provide to the user. Additionally, add a message to reduce stress.

[1278] Thus, the present invention provides a wealth management system that takes into account the user's financial and emotional state, resulting in a more effective and user-friendly approach.

[1279] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1280] Step 1:

[1281] The terminal allows the user to input income information, expenditure information, and savings goals. The user inputs monthly income, monthly expenditure, and savings goals. The terminal stores this data in a consolidated manner. The input data becomes the basic data required for subsequent processing.

[1282] Step 2:

[1283] The device's built-in emotion recognition engine recognizes the user's emotions, capturing the user's facial expressions and tone of voice to extract emotional information. This processing is performed using OpenCV and voice analysis technology. The acquired emotional information is used to tailor advice based on the user's financial behavior.

[1284] Step 3:

[1285] The terminal transmits the collected income information, expenditure information, savings goal, and emotional information to the server, which receives and analyzes this data.

[1286] Step 4:

[1287] The server analyzes the received data and calculates the amount of savings that can be made by subtracting expenses from income. This calculation is based on income information and expenditure information. The calculated amount of savings that can be made is the amount that the user can actually save.

[1288] Step 5:

[1289] The server compares the available savings amount with the savings goal, and if the available savings amount is less than the savings goal, it generates a warning message to remind the user to achieve the savings goal.

[1290] Step 6:

[1291] The server takes emotional information into account to generate personalized advice on asset management and savings, including specific suggestions on how to manage income and expenses and investment options, as well as encouraging messages and additional advice to reduce stress depending on the user's emotional state.

[1292] Step 7:

[1293] The server generates advice and warning messages and sends them to the terminal, which receives them and displays them to the user, allowing the user to understand the current asset status and take action based on the advice.

[1294] Through these steps, users can receive specific and personalized advice based on their individual financial and emotional situations, leading to more effective asset management.

[1295] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1296] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1297] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1298] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1299] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1300] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1301] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1302] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1303] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1304] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1305] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1306] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1307] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1308] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1309] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1310] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1311] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1312] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1313] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1314] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1315] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1316] The following is further disclosed regarding the above embodiment.

[1317] (Claim 1)

[1318] means for collecting income data, expenditure data, and savings goals from a user;

[1319] A means for calculating a savings potential amount by subtracting expenses from income based on the collected income data, expenditure data, and savings goal;

[1320] means for generating an alert message when the savings potential falls below the savings target;

[1321] a means for generating advice on asset management and savings management using the calculated savings amount and the generated alert message;

[1322] means for displaying the generated advice and alert messages to the user;

[1323] A system including:

[1324] (Claim 2)

[1325] means for transmitting the collected income data, expenditure data, and savings goals to a server;

[1326] 10. The system of claim 1, further comprising: means for receiving the analysis results from the server.

[1327] (Claim 3)

[1328] 10. The system of claim 1, wherein the generated advice includes advice regarding asset management, tax treatment, and expense management.

[1329] This is the draft of the patent claims for the "AI Money Support" system. This clearly defines each function of the system and allows us to limit the technical scope when filing a patent application.

[1330] "Example 1"

[1331] (Claim 1)

[1332] means for collecting income information, expenditure information, and savings goals from a user;

[1333] A means for calculating a savings potential amount by subtracting expenses from income based on the collected income information, expenditure information, and savings goal;

[1334] means for generating a warning message when the savings potential falls below the savings target;

[1335] a means for generating advice on asset management and savings management using the calculated savings amount and the generated warning message;

[1336] means for displaying generated advisory and warning messages to a user;

[1337] A system including:

[1338] (Claim 2)

[1339] means for transmitting the collected income information, expenditure information, and savings goals to a server;

[1340] 10. The system of claim 1, further comprising: means for receiving the analysis results from the server.

[1341] (Claim 3)

[1342] 10. The system of claim 1, wherein the generated advice includes advice regarding asset management, tax treatment, and expense management.

[1343] "Application Example 1"

[1344] (Claim 1)

[1345] means for collecting income data, expenditure data, and savings goals from a user;

[1346] A means for calculating a savings potential amount by subtracting expenses from income based on the collected income data, expenditure data, and savings goal;

[1347] means for generating a warning message when the savings potential falls below the savings target;

[1348] a means for generating advice on asset management and savings management using the calculated savings amount and the generated warning message;

[1349] A means to connect with electronic payment platforms and collect real-time expenditure and income data;

[1350] A means of utilizing generative AI models to generate detailed wealth management advice; and

[1351] means for displaying the generated advice and warning messages to the user;

[1352] A system including:

[1353] (Claim 2)

[1354] means for transmitting the collected income data, expenditure data, and savings goals to a server;

[1355] 10. The system of claim 1, further comprising: means for receiving the analysis results from the server.

[1356] (Claim 3)

[1357] 10. The system of claim 1, wherein the generated advice includes advice regarding asset management, tax treatment, expense management, and investment vehicles.

[1358] "Example 2: Combining Emotion Engines"

[1359] (Claim 1)

[1360] means for collecting income data, expenditure data, and savings goals from a user;

[1361] A means for calculating a savings potential amount by subtracting expenses from income based on the collected income data, expenditure data, and savings goal;

[1362] means for generating an alert message when the savings potential falls below the savings target;

[1363] a means for generating advice on asset management and savings management using the calculated savings amount and the generated alert message;

[1364] means for displaying the generated advice and alert messages to a user;

[1365] means for recognizing the user's emotions and adjusting the content and presentation of advice based on the emotion information;

[1366] A means for generating additional advice for reducing stress and improving motivation based on the user's emotional information;

[1367] A system including:

[1368] (Claim 2)

[1369] means for transmitting the collected income data, expenditure data, and savings goals and sentiment information to a server;

[1370] 10. The system of claim 1, further comprising: means for receiving the analysis results from the server.

[1371] (Claim 3)

[1372] 10. The system of claim 1, wherein the generated advice includes advice regarding asset management, tax treatment, and expense management.

[1373] "Application example 2 when combining emotion engines"

[1374] (Claim 1)

[1375] means for collecting income information, expenditure information, and savings goals from a user;

[1376] A means for calculating a savings potential amount by subtracting expenses from income based on the collected income information, expenditure information, and savings goal;

[1377] means for generating a warning message when the savings potential falls below the savings target;

[1378] means for recognizing a user's emotion using an emotion recognition engine built into the terminal and extracting emotion information;

[1379] a means for generating advice on asset management and savings management using the calculated savings amount, the generated warning message, and the extracted emotion information;

[1380] means for displaying the generated advice and warning messages to the user;

[1381] A system including:

[1382] (Claim 2)

[1383] 10. The system of claim 1, further comprising: means for transmitting the collected income information, expenditure information, and savings goals to a server; and means for receiving analysis results from the server.

[1384] (Claim 3)

[1385] 10. The system of claim 1, wherein the generated advice includes advice regarding asset management, tax treatment, and expense management, while including additional advice and messages tailored based on emotional information. [Explanation of symbols]

[1386] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for collecting income data, expenditure data, and savings goals from a user; A means for calculating a savings potential amount by subtracting expenses from income based on the collected income data, expenditure data, and savings goal; means for generating an alert message when the savings potential falls below the savings target; a means for generating advice on asset management and savings management using the calculated savings amount and the generated alert message; means for displaying the generated advice and alert messages to the user; A system including:

2. means for transmitting the collected income data, expenditure data, and savings goals to a server; The system of claim 1 further comprising means for receiving the analysis results from the server.

3. The system of claim 1 , wherein the generated advice includes advice regarding asset management, tax treatment, and expense management.

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