System

Abstract

A system is provided.SOLUTION: A system comprising means for a user to input basic information, means for transmitting the inputted data to a server, means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal, means for returning the generated proposal to the user's terminal and displaying it, and means for generating an answer to a detailed question of the user depending on an AI model or a human expert and returning it to the user's terminal.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] With traditional financial consultation services, users often felt a strong psychological resistance to discussing financial and household details with others, and were hesitant to use them due to privacy concerns. Furthermore, while these services were advertised as free consultations, they often involved aggressive sales tactics and repeated contact, which led to lower user satisfaction. Furthermore, traditional services required financial planners to provide one-on-one consultations, which was time-consuming and costly, making it difficult to provide services to many users. It is necessary to solve these issues and provide a financial consultation service that more people can easily use. [Means for solving the problem]

[0005] This invention provides a financial consultation system that utilizes AI to solve the above-mentioned problems. This system includes a means for a user to input basic information, a means for transmitting the input data to a server, a means for analyzing the received data based on an AI model and generating a financial plan or insurance proposal, a means for returning and displaying the generated proposal to the user's device, and a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's device. This system allows users to receive financial consultations without any psychological resistance and obtains prompt and appropriate proposals from the AI. Furthermore, by handing over to a human expert as needed, users can also receive professional support. As a result, it is possible to solve the problems of the past and provide users with a reliable financial consultation service.

[0006] "User" refers to an individual or corporate customer who uses the financial advice service.

[0007] "Basic information" refers to information including data such as the user's name, age, income, fixed expenses, and family composition.

[0008] "Device" refers to the electronic device used by a User to access the Financial Advice Service, including a PC, tablet, smartphone, etc.

[0009] "Server" refers to a central management system for receiving and processing data sent from terminals.

[0010] An "AI model" is an analytical engine that uses artificial intelligence and refers to technology that analyzes user data and generates appropriate household plans and insurance proposals.

[0011] "Household Plan" means a plan for managing and optimizing a User's income and expenses.

[0012] "Insurance proposal" refers to information that proposes the most suitable insurance products and services for the user.

[0013] A "detailed question" refers to a question in which the user seeks more specific information about a suggestion provided by the system.

[0014] "Human experts" refer to individuals with specialized knowledge of household finance, such as financial planners, who will be responsible for responding to advanced questions and inquiries that are difficult for AI models to handle.

[0015] "Format check" refers to the process of checking whether the basic information entered by the user is accurate.

[0016] "Error detection" refers to the system's ability to identify errors in basic information entered by a user.

[0017] "Database" means the digital storage system that stores and manages User information and related financial plans and insurance offers. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] This invention is a financial consultation system that uses AI to provide prompt and appropriate advice when users seek financial advice. The program processing of this system is explained in natural language below. A user usage scenario is also shown with specific examples.

[0040] Overall system overview

[0041] This household financial consultation system mainly consists of the following elements:

[0042] 1. Terminal

[0043] 2. Server

[0044] 3. AI Model

[0045] 4. Human Experts

[0046] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and human experts providing support as needed.

[0047] Program processing flow

[0048] The specific processing flow of the system is as follows:

[0049] 1. The user starts a financial consultation

[0050] The user accesses an online or in-store terminal and is taken to the login screen.

[0051] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[0052] The terminal transmits the user's input information to the server for authentication.

[0053] 2. Enter your user information

[0054] The terminal displays a basic information input form to the user.

[0055] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[0056] The terminal checks the format of the entered data and checks for input errors.

[0057] 3. Sending input data

[0058] The terminal transmits the data whose format has been confirmed to the server.

[0059] The server analyzes the received data and stores it in a database.

[0060] 4. Analysis using AI models

[0061] The server passes the stored data to the AI ​​model.

[0062] The AI ​​model analyzes the received data and generates optimal household budget review points and insurance plans.

[0063] The AI ​​model sends the generated suggestions back to the server.

[0064] 5. Display of Suggestions

[0065] The server sends the suggestions received from the AI ​​model to the user's device.

[0066] The terminal displays household plans and insurance proposals suitable for the user.

[0067] 6. Response to detailed questions

[0068] The user enters detailed questions and customization requests regarding the proposed content.

[0069] The terminal sends these detailed questions to the server.

[0070] The server asks questions to AI or human experts and generates answers.

[0071] The server returns the generated answer to the user's terminal.

[0072] The terminal displays the detailed answer to the user.

[0073] 7. Handover to experts

[0074] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[0075] The server notifies the experts and shares the user's data.

[0076] A human expert will contact the user for a detailed consultation.

[0077] Specific examples

[0078] Example: Maria is discussing her financial plan.

[0079] 1. Maria starts financial counseling

[0080] Maria accesses the system online from her home computer and is taken to the login screen.

[0081] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[0082] The terminal transmits Maria's input information to the server for authentication.

[0083] 2. Enter your user information

[0084] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[0085] The terminal checks the format of the entered data and checks for input errors.

[0086] 3. Sending input data

[0087] The terminal transmits the verified data to the server.

[0088] The server receives and analyzes the data and then stores it in a database.

[0089] 4. Analysis using AI models

[0090] The server passes the stored data to the AI ​​model.

[0091] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[0092] The AI ​​model sends the generated suggestions back to the server.

[0093] 5. Display of Suggestions

[0094] The server sends the suggestions received from the AI ​​model to Maria's device.

[0095] The terminal displays the proposal to Maria.

[0096] 6. Response to detailed questions

[0097] Maria enters detailed questions about the proposal and requests further customization.

[0098] The device then sends the question to a server and asks either an AI or human expert for an answer.

[0099] The server generates a response and sends it back to Maria's terminal.

[0100] The terminal presents Maria with a detailed response.

[0101] 7. Handover to experts

[0102] The server determines that Maria's question is advanced and hands it over to a human expert.

[0103] The expert will contact Maria and provide further advice.

[0104] In this way, this invention allows users to use the household finance consultation service without any psychological hesitation and receive prompt and appropriate suggestions from AI. Furthermore, since human experts are available to provide support as needed, it is possible to provide a highly reliable service to users.

[0105] The processing flow will be explained below.

[0106] Step 1:

[0107] A user accesses an online or in-store terminal and arrives at the login screen.

[0108] The terminal displays a login authentication screen to the user.

[0109] The user enters the user ID and password and clicks the login button.

[0110] Step 2:

[0111] The terminal sends the user's login information to the server.

[0112] The server receives the login information and authenticates it against a database.

[0113] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[0114] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[0115] Step 3:

[0116] The terminal displays a basic information input form to the user.

[0117] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[0118] Step 4:

[0119] The terminal checks the format of the input data.

[0120] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[0121] Step 5:

[0122] The server analyzes the received data and stores it in a database.

[0123] Step 6:

[0124] The server passes the stored data to the AI ​​model.

[0125] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[0126] Step 7:

[0127] The AI ​​model sends the generated suggestions back to the server.

[0128] The server sends the proposal to the user's terminal.

[0129] Step 8:

[0130] The device displays household plans and insurance proposals that are suitable for the user.

[0131] The user enters detailed questions and customization requests for the displayed plan.

[0132] Step 9:

[0133] The terminal transmits the user's questions and requests to the server.

[0134] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[0135] Step 10:

[0136] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[0137] The server sends the generated answer to the user's terminal.

[0138] Step 11:

[0139] The terminal displays the detailed answer to the user.

[0140] If the user wants further advice, the server hands over to a human expert.

[0141] A human expert will contact the user and provide detailed advice.

[0142] The above is the flow of specific processing steps in the household finance consultation system.

[0143] Example 1

[0144] 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."

[0145] Traditionally, household financial consultation services have been time-consuming and expensive, making them difficult for ordinary users to use. Furthermore, specialized knowledge is often required, making it difficult to obtain appropriate advice. Furthermore, online consultations are prone to input errors and misunderstandings, resulting in the risk of incorrect recommendations. Furthermore, analysis results using AI alone can sometimes lack reliability, requiring final confirmation by a human expert, but there has been a lack of a system for smoothly carrying out this adjustment.

[0146] 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.

[0147] In this invention, the server includes means for a user to input basic information, means for transmitting the input data, means for analyzing the received data based on a generative AI model and generating a household plan or insurance proposal, means for returning the generated proposal to the user's information processing device and displaying it, means for generating answers to the user's detailed questions using the generative AI model or a human expert and returning them to the user's information processing device, and means for handing over to a human expert if the user's question is determined to be of advanced or specialized content. This allows the user to easily receive highly accurate household consultation and, if necessary, to receive detailed support from a human expert.

[0148] "User" refers to an individual or corporation that uses this system to provide financial advice.

[0149] "Basic information" refers to information entered by the user, such as name, age, income, fixed expenses, and family composition.

[0150] "Server" refers to a computer system for receiving and processing data sent by users.

[0151] A "generative AI model" refers to an artificial intelligence model that analyzes user data to generate household plans and insurance proposals.

[0152] The term "information processing device" refers to a terminal that a user accesses to input data and view the results.

[0153] "Format validation" refers to the process of checking whether the format and content of the data entered by the user are correct.

[0154] A "detailed question" refers to a question that a user enters when they want to know more about the content of a proposal.

[0155] "Human experts" refer to experts who review the results generated by the AI ​​model and provide additional advice to users as needed.

[0156] "Database" refers to a data management system for storing and managing basic user information and AI analysis results.

[0157] "Handing over" refers to the process of transferring the response from the AI ​​model to a human expert when the user's question is deemed to be advanced or specialized.

[0158] This invention is a financial consultation system that utilizes a generative AI model to provide prompt and appropriate advice when a user seeks financial advice. This system is primarily composed of a user, a terminal, a server, a generative AI model, and a human expert. The system's processing is carried out in the following specific steps.

[0159] Hardware and Software Use

[0160] Device:

[0161] A terminal is an information processing device that allows a user to access the system, and includes a personal computer, smartphone, tablet, etc. A terminal has an input interface and a display interface.

[0162] server:

[0163] A computer system for receiving and processing data sent by users. The server manages the database and works in conjunction with the generative AI model. It is generally installed on a cloud platform (e.g., Amazon Web Services, Microsoft Azure).

[0164] Generative AI models:

[0165] It is an artificial intelligence model that analyzes user data and generates household plans and insurance proposals. It uses machine learning and deep learning libraries such as Python, TensorFlow, and Scikit-learn.

[0166] Data processing and calculation

[0167] Collecting input data:

[0168] The terminal displays a basic information input form to the user, who then enters information such as name, age, income, fixed expenses, and family composition. The input data is checked for formatting on the terminal, and if no errors are detected, it is sent to the server.

[0169] Analyzing data and generating recommendations:

[0170] The server passes the received user data to the generative AI model, which analyzes the collected data and generates recommendations for household budget revisions and optimal insurance plans. The generated proposals are then sent back to the server.

[0171] View suggestions:

[0172] The server sends the proposals received from the generative AI model to the user's device, which then displays the household plan and insurance proposals that are suitable for the user.

[0173] Response to detailed questions:

[0174] The user enters detailed questions or customization requests regarding the suggestions into the device. The device then sends the user's question data to the server. The server then asks the question to a generative AI model or a human expert and generates an answer. The generated answer is then sent back to the user's device and displayed.

[0175] Expert support:

[0176] If the server determines that the user's question is too advanced or technical, it will hand over to a human expert, who will contact the user for a detailed consultation.

[0177] Specific examples

[0178] Example 1: Financial advice prompt

[0179] Example financial advice prompt: "How can I reduce my monthly fixed expenses?"

[0180] The generative AI model then responds to this prompt by generating multiple pieces of energy-saving advice, such as "switch to eco-friendly appliances to reduce your electricity bill" or "cancel your magazine subscription."

[0181] Example 2: Insurance consultation prompt

[0182] Example insurance consultation prompt: "What is the best life insurance plan for me?"

[0183] The generative AI model proposes cost-effective life insurance plans based on the user's age, income, family structure, etc. For example, it will suggest specific plans such as "a comprehensive plan that covers the entire family for a user in their 30s with a family."

[0184] In this way, the present invention allows users to easily receive highly accurate financial advice and, if necessary, receive detailed support from human experts. Specific proposals are generated for various usage scenarios, allowing users to efficiently manage their financial affairs in an optimal manner.

[0185] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0186] Step 1:

[0187] A user accesses the system.

[0188] Input: The user accesses the system URL from their home computer or smartphone and is redirected to the login screen.

[0189] Output: A login authentication screen is displayed.

[0190] Specific operation: The terminal prompts the user to enter their user ID and password.

[0191] Step 2:

[0192] The user performs login authentication.

[0193] Input: The user enters their user ID and password and clicks the "Login" button.

[0194] Output: The input information is sent to the server.

[0195] Specific operation: The terminal sends the entered user ID and password to the server.

[0196] Step 3:

[0197] The server performs login authentication.

[0198] Input: User ID and password sent from the device.

[0199] Output: Session information if authentication is successful, error message if authentication is unsuccessful.

[0200] Specific operation: The server checks the user ID and password against the information in the database. If authentication is successful, it generates session information and returns it to the terminal. If authentication fails, it returns an error message.

[0201] Step 4:

[0202] The user enters basic information.

[0203] Input: The user enters name, age, income, fixed expenses, family composition, etc.

[0204] Output: Basic information input data.

[0205] Specific operation: After successful authentication, the terminal displays a basic information input form, and the user enters the required information in each field.

[0206] Step 5:

[0207] The terminal checks the format of the data.

[0208] Input: Basic information entered by the user.

[0209] Output: Format check result.

[0210] What happens: The terminal checks whether the entered data is in the correct format and detects errors, for example, whether the age is a number.

[0211] Step 6:

[0212] The device sends the verified data to the server.

[0213] Input: Basic information data with formatting checked.

[0214] Output: Sending data to the server.

[0215] Specific operation: The terminal sends the data to the server after checking the format.

[0216] Step 7:

[0217] The server receives and analyzes the data.

[0218] Input: Basic information data sent from the device.

[0219] Output: Save to database.

[0220] What happens: The server parses the data it receives, converts it into a structured format, and then stores it in a database.

[0221] Step 8:

[0222] The server passes the data to the generative AI model.

[0223] Input: Basic information data stored in the database.

[0224] Output: Passing data to a generative AI model.

[0225] Specific operation: The server transmits the stored data to the generative AI model.

[0226] Step 9:

[0227] A generative AI model analyzes the data and generates suggestions.

[0228] Input: Basic information data passed to the generative AI model.

[0229] Output: Household plan and insurance proposals.

[0230] Specific operation: The generative AI model analyzes basic information and generates points to review for household finances and optimal insurance plans.

[0231] Step 10:

[0232] The server sends the generated proposal to the terminal.

[0233] Input: Proposals generated from a generative AI model.

[0234] Output: Sends the proposal data to the user's device.

[0235] Specific operation: The server sends the generated proposal to the user's device.

[0236] Step 11:

[0237] The device will display suggestions.

[0238] Input: Proposal data sent by the server.

[0239] Output: Display of proposal.

[0240] Specific operation: The device displays household plans and insurance proposals suitable for the user on the screen.

[0241] Step 12:

[0242] The user enters a detailed question.

[0243] Input: Detailed questions or customization requests for the proposal.

[0244] Output: Question data.

[0245] Specific operation: The user enters a detailed question about the proposal, and the device sends it to the server.

[0246] Step 13:

[0247] The server generates questions and asks them to AI models or human experts.

[0248] Input: Question data from the user.

[0249] Output: Response data.

[0250] What it does: The server passes the user's question to a generative AI model or human expert to generate an appropriate answer.

[0251] Step 14:

[0252] The server generates a response and sends it back to the terminal.

[0253] Input: Answer data from a generative AI model or human experts.

[0254] Output: Send the answer data to the user's device.

[0255] Specific operation: The server sends the generated answer to the user's terminal.

[0256] Step 15:

[0257] The device will display a detailed response.

[0258] Input: The response data sent from the server.

[0259] Output: Show detailed answer.

[0260] Specific Actions: The device displays a detailed answer to the user.

[0261] Step 16:

[0262] The server will hand over to the expert.

[0263] Input: Advanced or specialized question data.

[0264] Output: Expert handover notification and data sharing.

[0265] Specific operation: If the server determines that the user's question is advanced, it notifies a human expert and shares the necessary data.

[0266] (Application example 1)

[0267] 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."

[0268] Conventional household finance consultation systems only required users to input household finance-related information and receive AI analysis results, which limited user interaction and resulted in an insufficient consultation experience. Furthermore, when providing specific advice, it was difficult to provide real-time feedback, making it difficult for users to receive prompt and appropriate suggestions.

[0269] Furthermore, when users seek financial advice from home, the environment is limited, and the consultation process with the expert may not proceed smoothly.

[0270] 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.

[0271] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on a generative AI model to generate a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's information terminal; a means for generating answers to the user's detailed questions based on the generative AI model or a human expert and returning them to the user's information terminal; a means for displaying the household budget plan in a virtual environment using augmented reality; and a natural language processing means for voice interaction with the user. This allows the user to receive prompt and appropriate proposals in real time during a household budget consultation from the comfort of their own home. Furthermore, combining augmented reality technology with natural language processing improves interaction with the user and allows for more specific and friendly advice to be provided.

[0272] The "means for the user to input basic information" is an interface that allows the user to input basic information about the household, such as name, age, income, fixed expenses, and family composition.

[0273] "Means for sending input data to a server" refers to a mechanism for transferring basic information input by a user to a remote server via a network.

[0274] "Means for analyzing received data based on a generation AI model and generating a household plan or insurance proposal" refers to the process of analyzing data sent by a user using AI technology and generating an optimal household plan or insurance proposal.

[0275] "Means for returning and displaying the generated proposals to the user's information terminal" refers to a mechanism for sending household plans and insurance proposals generated by AI to the device used by the user and displaying them visually.

[0276] "Means for generating answers to detailed user questions using a generative AI model or a human expert and sending them back to the user's information device" refers to the process by which an AI or expert creates an answer to a detailed user question and sends that answer to the user's device.

[0277] "Means for displaying a household plan in a virtual environment using augmented reality" refers to a mechanism that uses AR technology to visually overlay a household plan on the user's real-world environment.

[0278] "Natural language processing means for voice interaction with a user" is a system that includes technology for understanding a user's voice input and generating an appropriate response.

[0279] "Means for format validation and error detection" refers to a mechanism that has a validation process to ensure that data entered by the user conforms to a predetermined format and has the ability to detect incorrect input.

[0280] "Means for a human expert to finalize the analysis results of the generated AI model and contact the user as necessary" refers to a process in which experts review the analysis results generated by AI and, if necessary, provide direct feedback to the user.

[0281] "Means for managing the database used by the AI ​​model" refers to a system for storing data necessary for AI analysis and maintaining and operating the database that manages it.

[0282] "Natural language processing means for voice interaction" is a system that uses technology to analyze a user's voice input, understand the content of the question, and automatically generate an appropriate response.

[0283] This invention is a system that allows users to receive financial advice from the comfort of their own home, and is composed of the following elements: A device such as a smartphone, smart glasses, or head-mounted display is used as a means for users to input basic information. This device provides an interface for users to input basic information about their household finances, such as name, age, income, fixed expenses, and family composition.

[0284] The data entered by the user is sent via a network to a remote server. The server analyzes the received data based on a generative AI model and generates a household plan or insurance proposal. The generative AI model is an analysis system that uses machine learning algorithms and is built into the server.

[0285] The generated proposals are then sent back to the user's information device and displayed visually. In this process, the AI ​​model generates household plans and proposals for the user in real time. Answers to detailed questions from the user are also generated by the AI ​​model or human experts and sent back to the user's information device.

[0286] The system includes a means to display a household plan in a virtual environment using augmented reality (AR) technology. Users can visually experience a virtual household planner in their living room or other location using smart glasses or a head-mounted display. The system also uses voice recognition and natural language processing technology to interact with the user, allowing them to input household information and ask questions by voice.

[0287] As a specific example, there is a scenario in which a user can say, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people," and the system will collect basic information and perform analysis. The user's voice input is converted into text using the Google Speech-to-Text API, and the Google Natural Language API is used for natural language processing.

[0288] If a user wants to ask a more detailed question about the proposed household budget plan, for example, they can say, "How can I revise my household budget plan?" This question is also analyzed using natural language processing, and a generative AI model or expert generates an answer. This answer is also displayed on the information terminal, providing visual and audio feedback.

[0289] An example of a prompt is as follows:

[0290] Please enter household information such as the user's name, age, income, fixed expenses, and family composition. For example, please enter something like, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people."

[0291] In this way, users can use an interactive household finance consultation system that combines augmented reality technology and natural language processing from the comfort of their own home. This invention enables users to receive prompt and accurate household finance advice, which is expected to improve their quality of life.

[0292] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0293] Step 1:

[0294] The user enters basic information.

[0295] Users launch the household finance advisor app using their smartphone, smart glasses, or head-mounted display, and an input screen appears, prompting them to enter basic information such as their name, age, income, fixed expenses, and family composition by voice or text.

[0296] Input: User's household information

[0297] Output: Input household information data

[0298] Step 2:

[0299] The terminal transmits the input data to the server.

[0300] The terminal checks the format of the household information entered by the user and performs error detection before transmitting the data to a remote server via a network.

[0301] Input: Entered household information data

[0302] Output: Household information data sent to the server

[0303] Step 3:

[0304] The server analyzes the data using the generative AI model.

[0305] The server analyzes the received data based on the generative AI model and generates a household plan or insurance proposal, using machine learning algorithms to evaluate the user's household situation and make optimal proposals.

[0306] Input: Household information data sent to the server

[0307] Output: A household budget or insurance proposal from a generative AI model

[0308] Step 4:

[0309] The server sends the generated proposal back to the user's terminal.

[0310] The household plan and insurance proposals generated by the server are sent back to the user's terminal via the network.

[0311] Input: household budget or insurance proposals from a generative AI model

[0312] Output: Proposal data returned to the user device

[0313] Step 5:

[0314] The terminal displays the suggestions to the user.

[0315] The device visually displays the returned household plan or insurance proposal and presents it to the user in an easy-to-view format, where the household plan is displayed in a virtual environment using augmented reality (AR) technology.

[0316] Input: Returned proposal data

[0317] Output: A household plan or insurance proposal displayed to the user

[0318] Step 6:

[0319] The user enters a detailed question.

[0320] The user can then enter additional or detailed questions about the suggestions by voice or text.

[0321] Input: Detailed question from user

[0322] Output: Question data entered

[0323] Step 7:

[0324] The terminal transmits the question data to the server.

[0325] The terminal sends detailed questions from the user to the server.

[0326] Input: The entered question data

[0327] Output: The query data sent to the server

[0328] Step 8:

[0329] The server asks questions to generative AI models or human experts and generates answers.

[0330] The server analyzes the user's detailed question and generates an answer relying on generative AI models or human experts.

[0331] Input: Query data sent to the server

[0332] Output: Generated response data

[0333] Step 9:

[0334] The server sends the generated answer back to the user's terminal.

[0335] The generated answer is sent back to the user's terminal via the network.

[0336] Input: Generated response data

[0337] Output: Answer data returned to the user's device

[0338] Step 10:

[0339] The terminal displays the answer to the user.

[0340] The terminal visually displays the returned answer data and provides the user with audio or text feedback.

[0341] Input: Returned response data

[0342] Output: The answer displayed to the user

[0343] 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.

[0344] This invention is a financial advice system that utilizes AI and an emotion engine to provide more accurate and emotionally sensitive advice to users when they seek financial advice. Below, we explain the program processing of this system in natural language. We also provide a user usage scenario with concrete examples.

[0345] Overall system overview

[0346] This household financial consultation system mainly consists of the following elements:

[0347] 1. Terminal

[0348] 2. Server

[0349] 3. AI Model

[0350] 4. Emotion Engine

[0351] 5. Human Experts

[0352] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and the emotion engine recognizing the user's emotional state, with human experts providing support as needed.

[0353] Program processing flow

[0354] The specific processing flow of the system is as follows:

[0355] 1. The user starts a financial consultation

[0356] A user accesses an online or in-store terminal and arrives at the login screen.

[0357] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[0358] The terminal transmits the user's input information to the server for authentication.

[0359] 2. Enter your user information

[0360] The terminal displays a basic information input form to the user.

[0361] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[0362] The terminal checks the format of the entered data and checks for input errors.

[0363] 3. Sending input data

[0364] The terminal transmits the data whose format has been confirmed to the server.

[0365] The server analyzes the received data and stores it in a database.

[0366] 4. Analysis using AI models

[0367] The server passes the stored data to the AI ​​model.

[0368] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[0369] 5. Emotion Recognition by Emotion Engine

[0370] The terminal activates an emotion engine during interaction with the user to recognize the user's emotional state.

[0371] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate their emotional state.

[0372] 6. Customize your suggestions

[0373] The emotional state recognized by the emotion engine is sent to the server.

[0374] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[0375] The server sends the customized offer to the user's terminal.

[0376] 7. Display of Suggestions

[0377] The device displays household plans and insurance proposals that are suitable for the user.

[0378] The user enters detailed questions and customization requests for the displayed plan.

[0379] 8. Response to detailed questions

[0380] The terminal transmits the user's questions and requests to the server.

[0381] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[0382] 9. Generating and Displaying Answers

[0383] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[0384] The server sends the generated answer to the user's terminal.

[0385] The terminal displays the detailed answer to the user.

[0386] 10. Handover to an expert

[0387] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[0388] The server notifies the experts and shares the user's data.

[0389] A human expert will contact the user for a detailed consultation.

[0390] Specific examples

[0391] Example: Maria is discussing her financial plan.

[0392] 1. Maria starts financial counseling

[0393] Maria accesses the system online from her home computer and reaches the login screen.

[0394] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[0395] The terminal transmits Maria's input information to the server for authentication.

[0396] 2. Enter your user information

[0397] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[0398] The terminal checks the format of the entered data and checks for input errors.

[0399] 3. Sending input data

[0400] The terminal transmits the verified data to the server.

[0401] The server receives and analyzes the data and then stores it in a database.

[0402] 4. Analysis using AI models

[0403] The server passes the stored data to the AI ​​model.

[0404] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[0405] 5. Emotion Recognition by Emotion Engine

[0406] The device activates an emotion engine during interaction with Maria to recognize her emotional state.

[0407] The emotion engine analyzes Maria's facial expressions, voice, and text data to assess her emotional state.

[0408] 6. Customize your suggestions

[0409] The emotional state recognized by the emotion engine is sent to the server.

[0410] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[0411] The server sends the customized offer to Maria's terminal.

[0412] 7. Display of Suggestions

[0413] The device displays the suggestions to Maria and provides appropriate advice that takes her emotions into consideration.

[0414] 8. Response to detailed questions

[0415] Maria enters detailed questions and customization requests for the displayed plan.

[0416] The device sends these questions to a server, which then asks an AI model or a human expert.

[0417] 9. Generating and Displaying Answers

[0418] An AI model or human expert generates answers to Maria's questions and sends them back to the server.

[0419] The server sends the generated response to Maria's terminal.

[0420] The terminal displays a detailed response to Maria.

[0421] 10. Handover to an expert

[0422] The server determines that Maria's question is advanced and hands it over to a human expert.

[0423] The expert will contact Maria and provide further advice.

[0424] In this way, this invention allows users to use a household finance consultation service that also takes their emotional state into consideration. In addition to fast and appropriate suggestions from AI, the emotion engine recognizes the user's emotional state and human experts provide support as needed, making it possible to provide a highly reliable service to users.

[0425] The processing flow will be explained below.

[0426] Step 1:

[0427] A user accesses an online or in-store terminal and arrives at the login screen.

[0428] The terminal displays a login authentication screen to the user.

[0429] The user enters the user ID and password and clicks the login button.

[0430] Step 2:

[0431] The terminal sends the user's login information to the server.

[0432] The server receives the login information and authenticates it against a database.

[0433] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[0434] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[0435] Step 3:

[0436] The terminal displays a basic information input form to the user.

[0437] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[0438] Step 4:

[0439] The terminal checks the format of the input data.

[0440] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[0441] Step 5:

[0442] The server analyzes the received data and stores it in a database.

[0443] Step 6:

[0444] The server passes the stored data to the AI ​​model.

[0445] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[0446] Step 7:

[0447] The terminal activates the emotion engine during interaction with the user.

[0448] The emotion engine analyzes the user's facial expressions, voice, and text data to assess their emotional state.

[0449] Step 8:

[0450] The emotion engine transmits the recognized emotional state to the server.

[0451] The server uses this emotional data to customize the suggestions generated by the AI ​​model.

[0452] Step 9:

[0453] The server sends the customized offer to the user's terminal.

[0454] The terminal displays the suggestions to the user.

[0455] Step 10:

[0456] The user then inputs detailed questions and customization requests in response to the displayed suggestions.

[0457] The terminal sends these questions and requests to the server.

[0458] Step 11:

[0459] The server receives detailed questions or requests and refers them to an AI model or a human expert.

[0460] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[0461] Step 12:

[0462] The server sends the generated answer to the user's terminal.

[0463] The terminal displays the detailed answer to the user.

[0464] Step 13:

[0465] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[0466] The server notifies the experts and shares the user's data.

[0467] A human expert will contact the user for further consultation.

[0468] The above is the flow of specific processing steps in the household finance consultation system.

[0469] Example 2

[0470] 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."

[0471] Conventional financial consultation systems make suggestions based on the user's basic information, but they are unable to consider the user's emotional state and often make one-sided suggestions, making it difficult for users to achieve satisfactory results. Furthermore, there is insufficient formatting and error checking of input data, which can result in incorrect information being sent to the system. Furthermore, when answers to detailed questions are automatically generated, they can sometimes lack professional judgment.

[0472] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's terminal; a means for recognizing an emotional state during interaction with the user; a means for customizing the proposal content based on the recognized emotional state; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's terminal; a means for checking the data format and performing error checks; and a means for a human expert to finally check the AI ​​analysis results and contact the user as necessary. This enables the provision of an accurate household budget plan that reflects the user's emotional state, high reliability of input data, and response to detailed questions from a professional perspective.

[0473] "User" refers to a person who uses the system to receive financial advice.

[0474] "Terminal" refers to an electronic device (PC, smartphone, tablet, etc.) that a user uses to access and use the system.

[0475] "Server" refers to the central computer device that manages the entire system and performs processes such as data storage, analysis, and proposal generation.

[0476] "Artificial intelligence model" refers to the algorithms and machine learning models that analyze user data and generate household plans and insurance proposals.

[0477] An "emotion engine" refers to a system that recognizes a user's emotional state from data collected during interactions with the user and customizes suggestions based on the results.

[0478] A "household plan" refers to a financial plan created taking into account the user's income, expenses, family composition, etc.

[0479] "Insurance proposal" refers to information that suggests the most suitable insurance plan based on the user's household data, etc.

[0480] "Interaction" refers to the dialogue and exchange of information between a user and a system.

[0481] "Error checking" refers to the process of checking and correcting input data for errors.

[0482] This invention is a financial advice system that provides users with more accurate and emotionally sensitive advice when they seek financial advice. The system collects basic information about the user and generates financial plans and insurance proposals using an artificial intelligence model and an emotion engine. Furthermore, the system recognizes the user's emotional state and customizes proposals based on that state. A specific embodiment of the system is described below.

[0483] The system mainly consists of the following elements:

[0484] 1. Terminal

[0485] This refers to devices that users use to access systems, such as PCs, smartphones, and tablets. Examples include Apple's MacBook, Microsoft's Surface, and Google's Pixel.

[0486] 2. Server

[0487] This refers to the central computer device that manages the entire system and stores data, analyzes it, and generates proposals. It can be a general cloud server, such as an EC2 instance from Amazon Web Services (AWS) or a Compute Engine from Google Cloud Platform (GCP).

[0488] 3. Artificial Intelligence Model

[0489] This refers to algorithms and machine learning models that analyze user data and generate household plans and insurance proposals. Examples include OpenAI's GPT-3 and BERT.

[0490] 4. Emotion Engine

[0491] This refers to systems that recognize a user's emotional state from data collected during user interactions and customize suggestions based on the results. Examples include Affectiva and Microsoft's Emotion API.

[0492] 5. Human Experts

[0493] This refers to financial planners and insurance advisors who, if necessary, provide final confirmation of the analysis results of the AI ​​model and contact users directly.

[0494] Specific examples

[0495] In a scenario where a user is consulting about a household budget, the system operates in the following steps.

[0496] 1. The user starts a financial consultation

[0497] A user accesses the system from their home PC and reaches the login screen. The terminal displays the login authentication screen, and the user logs in by entering their user ID and password. This information is sent from the terminal to the server and authenticated.

[0498] 2. Enter your user information

[0499] The terminal displays a basic information input form, and the user inputs name, age, income, fixed expenses, family composition, etc. The terminal checks the format of the input data and performs error checks.

[0500] 3. Analysis of input data

[0501] The server receives the data after checking the format and stores it in a database. The stored data is then passed to an AI model, which analyzes the user's data and generates budget adjustments and optimal insurance plans.

[0502] 4. Emotion Recognition and Customized Suggestions

[0503] The device activates an emotion engine during interaction with the user to recognize the user's emotional state. The emotion engine then sends the recognized emotional data to the server, which then customizes suggestions based on this data. As a result, the device provides appropriate advice that takes the user's emotions into consideration.

[0504] Prompt Sentence Examples

[0505] Below is an example of a prompt sentence to input to the generative AI model.

[0506] "The user is 30 years old and earns 300,000 yen a month. I have entered detailed information about my monthly fixed expenses and family structure. Please suggest the best household budget plan for this user."

[0507] The detailed operation of this system allows users to receive accurate and prompt financial advice that takes their emotions into consideration. Each element works in tandem to provide a highly reliable service to users.

[0508] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0509] Step 1:

[0510] User starts household finance consultation

[0511] A user accesses the system using a PC or smartphone and reaches the login screen.

[0512] Input: User ID, Password

[0513] The terminal displays a login authentication screen, and the user enters their user ID and password.

[0514] Output: Authentication result

[0515] The device sends the entered authentication information to the server. The server verifies the authentication information and checks whether the user is registered. If authentication is successful, the device displays the home screen to proceed to the next step.

[0516] Step 2:

[0517] Entering user information

[0518] The terminal displays a basic information input form to the user.

[0519] Input: Basic information such as name, age, income, fixed expenses, family composition, etc.

[0520] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[0521] Output: Basic information entered

[0522] The terminal checks the format of the entered data and ensures that all required fields are filled in. If there is a problem with the format, the terminal displays an error message and prompts the user to re-enter the data.

[0523] Step 3:

[0524] Sending input data

[0525] The terminal transmits the data after format confirmation to the server.

[0526] Input: Verified data

[0527] The server analyzes the received data and stores it in a database.

[0528] Output: Save results to database

[0529] The server returns a confirmation of data storage to the terminal and instructs it to proceed to the next step.

[0530] Step 4:

[0531] Analysis using AI models

[0532] The server passes the stored user data to an artificial intelligence model.

[0533] Input: Saved user data

[0534] The artificial intelligence model generates budget review points and optimal insurance plans based on data such as the user's income, expenses, and family composition.

[0535] Output: Household budget plan and insurance proposals

[0536] The AI ​​model generates a proposal that is sent back to the server, which uses it in the next step.

[0537] Step 5:

[0538] Emotion recognition by emotion engine

[0539] The terminal activates the emotion engine during interaction with the user.

[0540] Input: User's facial expressions, voice, and text data

[0541] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate the user's emotional state.

[0542] Output: Emotional evaluation data

[0543] The evaluated emotion data is sent to the server via the terminal.

[0544] Step 6:

[0545] Customize suggestions

[0546] The server customizes the suggestions generated by the artificial intelligence model based on the emotional data received from the emotion engine.

[0547] Input: Emotion data, suggested data from AI model

[0548] The server adjusts the content of the suggestions appropriately depending on the user's emotional state, and constructs the most appropriate advice for the user.

[0549] Output: Customized proposal

[0550] Send customized offers to your device.

[0551] Step 7:

[0552] View Suggestions

[0553] The device displays customized household plans and insurance offers to the user.

[0554] Input:Customized Proposal

[0555] Output: Displayed proposal

[0556] Users can then enter detailed questions and customization requests for the plans displayed, allowing them to receive advice that best suits their situation.

[0557] Step 8:

[0558] Response to detailed questions

[0559] The terminal sends user questions and requests to the server.

[0560] Input: User questions or requests

[0561] Based on the question, the server asks an AI model or a human expert to respond to the question.

[0562] Output: Request details

[0563] This allows for appropriate answers to be prepared for detailed questions from the user.

[0564] Step 9:

[0565] Generate and display answers

[0566] An artificial intelligence model or human expert generates answers to the user's questions and sends them back to the server.

[0567] Input: Question response request, expert answer

[0568] Output: The generated answer

[0569] The server sends the generated answer to the user's device, which displays the detailed answer to the user, allowing the user to resolve their question and obtain further information.

[0570] Step 10:

[0571] Handover to experts

[0572] If the server determines that the user's question is difficult, it will hand it off to a human expert.

[0573] Input: User question, expert handover instructions

[0574] Output: Handover notification to expert

[0575] The server notifies the expert and shares the user's data, and the human expert contacts the user for a detailed consultation, allowing the user to receive further expert advice.

[0576] (Application example 2)

[0577] 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."

[0578] Conventional household budget consultation systems provide analysis results and advice without considering the user's emotions, making it difficult to reduce the user's psychological burden and stress. In addition, centralized management of expenditure data was insufficient, making it difficult to provide appropriate advice that takes emotions into consideration in real time.

[0579] 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.

[0580] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's device; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's device; an emotion recognition means for analyzing the user's facial expressions and voice using the device's built-in camera and microphone to recognize the user's emotional state; a means for adjusting the proposal content based on the emotional state; a means for transmitting emotion-sensitive notifications and advice to the user's device; a format verification and error detection means; a means for inputting and analyzing the user's expenditure data and providing a household budget improvement plan that takes the user's emotional state into account; and a means for managing the generative AI model and emotion engine to provide advice and plans based on the user's emotional state. This allows for the provision of appropriate advice that takes the user's emotions into account, improving the efficiency of household budget management and reducing the user's psychological burden.

[0581] "Basic information" refers to personal information necessary for financial consultation, such as the user's name, age, income, fixed expenses, and family composition.

[0582] "Server" refers to a device that receives data entered by a user, analyzes it, and returns the results to the user.

[0583] "AI model" refers to an algorithm that uses machine learning technology to generate household budget review points and insurance proposals.

[0584] "Emotion recognition means" refers to a device that uses a camera and microphone to analyze the user's facial expressions and voice and evaluate their emotional state.

[0585] "Emotional state" refers to the psychological state obtained from the user's facial expressions, voice, and text data.

[0586] "Proposal content" refers to advice and plans generated by the AI ​​model, such as points to review in household finances and insurance proposals.

[0587] "Notifications and advice" refers to information about improving household finances and notifications encouraging specific actions that are sent to the user's device.

[0588] "Terminal" refers to the device on which the user inputs information and receives and displays suggestions from the server.

[0589] "Format checking and error detection means" refers to a function that checks whether there are any errors in the format or content of the data entered by the user.

[0590] "Input and analysis of expenditure data" refers to the function that allows users to input daily expenditure amounts and breakdowns and analyze them.

[0591] "Finance Improvement Plan" refers to savings and investment plans created based on the user's spending data and emotional state.

[0592] A "generative AI model" refers to an algorithm that uses AI technology to generate suggestions suited to a user's financial situation and emotional state.

[0593] An "emotion engine" refers to software that assesses a user's emotional state and adjusts suggestions accordingly.

[0594] MODE FOR CARRYING OUT THE INVENTION

[0595] System configuration overview

[0596] This invention is a system that provides financial advice to users while they manage their daily expenses. The system aims to provide advice that takes into account the user's emotional state. The main components of the system include a terminal, a server, an AI model, and an emotion engine.

[0597] Hardware and software used

[0598] Hardware: Smartphone (built-in camera, microphone)

[0599] Software: TensorFlow, Emotion API, Expense Database

[0600] Program processing

[0601] overview

[0602] The server performs the following processes: It analyzes the expenditure data entered by the user and generates a household budget plan and insurance proposals based on that data. It also recognizes the user's emotional state in real time using a camera and microphone and provides advice that takes their emotions into consideration. It also responds to detailed questions from the user and provides appropriate feedback tailored to the user's emotions.

[0603] The server operates as follows:

[0604] 1. Data Acquisition

[0605] Users enter basic information and expenditure data into their smartphones and send it to the server, which receives the data and stores it in a database.

[0606] 2. Data analysis and proposal generation

[0607] The saved data is passed to an AI model that generates budget review points and insurance proposals. The AI ​​model uses TensorFlow to calculate optimal advice based on past data and statistical information.

[0608] 3. Recognizing emotional states

[0609] It uses the smartphone's camera and microphone to analyze the user's facial expressions and voice in real time, and uses the Emotion API to evaluate the user's emotional state at that time.

[0610] 4. Adjusting the proposal

[0611] The emotion engine analyzes the user's emotional state and customizes the generated household budget plan and advice based on that. For example, if the user is feeling stressed, it will prioritize specific and easy-to-implement plans.

[0612] 5. Sending Notices and Advice

[0613] The adjusted suggestions are sent to the user via push notifications on their smartphone, etc. The notification content takes into consideration emotions and provides advice in gentle language.

[0614] Specific scenarios

[0615] Situation: User enters expenditure data and conducts financial consultation

[0616] 1. Entering expenditure data

[0617] User: Enters "My recent expenses are 5,000 yen" into the app.

[0618] 2. Recognizing emotional states

[0619] The app's camera captures the user's facial expression and recognizes that they are confused.

[0620] 3. Proposal generation and refinement

[0621] The AI ​​model analyzes users' spending patterns and identifies points where they should adjust their finances, while the Emotion API notifies the server when a user is under stress.

[0622] 4. Submitting Advice

[0623] The server sends emotion-sensitive suggestions to the smartphone and notifies the user.

[0624] "It seems like you haven't been managing your expenses well lately. I'd like to suggest some easy and simple ways to save money. How about setting aside some time on the weekends to relax with your family and do your hobbies?"

[0625] The above is an embodiment of the invention.

[0626] Prompt Sentence Examples

[0627] Below is an example of a prompt that an application might pass to a generative AI model.

[0628] A user enters their recent spending data. The camera detects a confused state in their facial expression. Reflect their emotional state, provide situational financial improvement advice, and suggest emotionally sensitive recommendations.

[0629] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0630] Step 1:

[0631] The user enters basic information and expenditure data into their smartphone device and sends it to the server.

[0632] Input: The user enters basic information such as "name, age, income, fixed expenses, family composition" and "expense data" into the app.

[0633] Output: The app sends input data and the server receives it.

[0634] Specific operation: The user presses the submit button on the smartphone app to submit the information entered in the form. The server receives this information and stores it in the database.

[0635] Step 2:

[0636] The server stores the received data and passes it to the AI ​​model.

[0637] Input: Basic information and spending data sent from your device.

[0638] Output: Stored data and input to the AI ​​model.

[0639] What it does: The server immediately stores the received data in a database and prepares it to be passed to the AI ​​model for analysis.

[0640] Step 3:

[0641] The AI ​​model analyzes the stored spending data and generates household plans and insurance proposals.

[0642] Input: User spending data retrieved from the database.

[0643] Output: Generation of household plans and insurance proposals.

[0644] How it works: An AI model (powered by TensorFlow) pulls user data from a database, compares it with statistics and historical data, and generates appropriate financial plans and insurance proposals.

[0645] Step 4:

[0646] Using the smartphone's camera and microphone, the system analyzes the user's facial expressions and voice to recognize their emotional state.

[0647] Input: User's facial expression data captured by the smartphone camera and voice data captured by the microphone.

[0648] Output: Evaluation of the user's emotional state.

[0649] Specific operation: The device sends the user's facial expressions and voice to the Emotion API in real time for emotion recognition, and the emotional state is sent to the server.

[0650] Step 5:

[0651] The emotion engine adjusts the suggestions based on the emotional state it recognizes.

[0652] Input: Emotional state data from emotion recognition instruments, and financial plan and insurance proposal data from AI models.

[0653] Output: Emotionally sensitive household budget plans and insurance proposals.

[0654] How it works: The server adjusts the generated household plan based on the data obtained from the emotion engine. For example, it will prioritize plans that are easy to implement for users who are under stress.

[0655] Step 6:

[0656] The user is notified of emotionally sensitive suggestions via their device.

[0657] Input: Tailored household plans and insurance proposals.

[0658] Output: The suggestions displayed on the user's smartphone.

[0659] Specific operation: The server sends the adjusted proposal to the user's device and notifies them via push notification or on-screen display.

[0660] Step 7:

[0661] The user inputs detailed questions and feedback about the generated plan and sends them to the server.

[0662] Input: Questions or feedback that users enter into the app.

[0663] Output: Detailed question and feedback sent to the server.

[0664] Specific operation: The user reviews the proposal, enters questions or feedback through the app interface, and presses the send button to send it to the server.

[0665] Step 8:

[0666] The server generates answers based on detailed questions, either through AI models or human experts.

[0667] Input: User's detailed question.

[0668] Output: The generated answer.

[0669] What it does: The server passes the user's question to an AI model or designated expert to generate an answer, which is then sent back to the server.

[0670] Step 9:

[0671] The generated answer is returned to the user's terminal and displayed.

[0672] Input: The generated answer.

[0673] Output: The answer displayed on the user's device.

[0674] Specific behavior: The server sends the generated answer to the user's device, and the app displays the answer.

[0675] Step 10:

[0676] If the server determines that the user's question is more advanced, it hands it off to a human expert.

[0677] Input: User's advanced question.

[0678] Output: Detailed answers from experts.

[0679] What it does: The server evaluates the question and, if it determines that the question is advanced, notifies an expert and shares the user's data. The expert then contacts the user directly and provides detailed advice.

[0680] The above is the specific processing flow of the system that realizes the application example.

[0681] 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.

[0682] 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.

[0683] 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.

[0684] [Second embodiment]

[0685] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0686] 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.

[0687] 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).

[0688] 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.

[0689] 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.

[0690] 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).

[0691] 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.

[0692] 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.

[0693] 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.

[0694] 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.

[0695] In the smart glasses 214, 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.

[0696] 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."

[0697] This invention is a financial consultation system that uses AI to provide prompt and appropriate advice when users seek financial advice. The program processing of this system is explained in natural language below. A user usage scenario is also shown with specific examples.

[0698] Overall system overview

[0699] This household financial consultation system mainly consists of the following elements:

[0700] 1. Terminal

[0701] 2. Server

[0702] 3. AI Model

[0703] 4. Human Experts

[0704] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and human experts providing support as needed.

[0705] Program processing flow

[0706] The specific processing flow of the system is as follows:

[0707] 1. The user starts a financial consultation

[0708] The user accesses an online or in-store terminal and is taken to the login screen.

[0709] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[0710] The terminal transmits the user's input information to the server for authentication.

[0711] 2. Enter your user information

[0712] The terminal displays a basic information input form to the user.

[0713] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[0714] The terminal checks the format of the entered data and checks for input errors.

[0715] 3. Sending input data

[0716] The terminal transmits the data whose format has been confirmed to the server.

[0717] The server analyzes the received data and stores it in a database.

[0718] 4. Analysis using AI models

[0719] The server passes the stored data to the AI ​​model.

[0720] The AI ​​model analyzes the received data and generates optimal household budget review points and insurance plans.

[0721] The AI ​​model sends the generated suggestions back to the server.

[0722] 5. Display of Suggestions

[0723] The server sends the suggestions received from the AI ​​model to the user's device.

[0724] The terminal displays household plans and insurance proposals suitable for the user.

[0725] 6. Response to detailed questions

[0726] The user enters detailed questions and customization requests regarding the proposed content.

[0727] The terminal sends these detailed questions to the server.

[0728] The server asks questions to AI or human experts and generates answers.

[0729] The server returns the generated answer to the user's terminal.

[0730] The terminal displays the detailed answer to the user.

[0731] 7. Handover to experts

[0732] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[0733] The server notifies the experts and shares the user's data.

[0734] A human expert will contact the user for a detailed consultation.

[0735] Specific examples

[0736] Example: Maria is discussing her financial plan.

[0737] 1. Maria starts financial counseling

[0738] Maria accesses the system online from her home computer and is taken to the login screen.

[0739] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[0740] The terminal transmits Maria's input information to the server for authentication.

[0741] 2. Enter your user information

[0742] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[0743] The terminal checks the format of the entered data and checks for input errors.

[0744] 3. Sending input data

[0745] The terminal transmits the verified data to the server.

[0746] The server receives and analyzes the data and then stores it in a database.

[0747] 4. Analysis using AI models

[0748] The server passes the stored data to the AI ​​model.

[0749] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[0750] The AI ​​model sends the generated suggestions back to the server.

[0751] 5. Display of Suggestions

[0752] The server sends the suggestions received from the AI ​​model to Maria's device.

[0753] The terminal displays the proposal to Maria.

[0754] 6. Response to detailed questions

[0755] Maria enters detailed questions about the proposal and requests further customization.

[0756] The device then sends the question to a server and asks either an AI or human expert for an answer.

[0757] The server generates a response and sends it back to Maria's terminal.

[0758] The terminal presents Maria with a detailed response.

[0759] 7. Handover to experts

[0760] The server determines that Maria's question is advanced and hands it over to a human expert.

[0761] The expert will contact Maria and provide further advice.

[0762] In this way, this invention allows users to use the household finance consultation service without any psychological hesitation and receive prompt and appropriate suggestions from AI. Furthermore, since human experts are available to provide support as needed, it is possible to provide a highly reliable service to users.

[0763] The processing flow will be explained below.

[0764] Step 1:

[0765] A user accesses an online or in-store terminal and arrives at the login screen.

[0766] The terminal displays a login authentication screen to the user.

[0767] The user enters the user ID and password and clicks the login button.

[0768] Step 2:

[0769] The terminal sends the user's login information to the server.

[0770] The server receives the login information and authenticates it against a database.

[0771] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[0772] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[0773] Step 3:

[0774] The terminal displays a basic information input form to the user.

[0775] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[0776] Step 4:

[0777] The terminal checks the format of the input data.

[0778] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[0779] Step 5:

[0780] The server analyzes the received data and stores it in a database.

[0781] Step 6:

[0782] The server passes the stored data to the AI ​​model.

[0783] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[0784] Step 7:

[0785] The AI ​​model sends the generated suggestions back to the server.

[0786] The server sends the proposal to the user's terminal.

[0787] Step 8:

[0788] The device displays household plans and insurance proposals that are suitable for the user.

[0789] The user enters detailed questions and customization requests for the displayed plan.

[0790] Step 9:

[0791] The terminal transmits the user's questions and requests to the server.

[0792] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[0793] Step 10:

[0794] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[0795] The server sends the generated answer to the user's terminal.

[0796] Step 11:

[0797] The terminal displays the detailed answer to the user.

[0798] If the user wants further advice, the server hands over to a human expert.

[0799] A human expert will contact the user and provide detailed advice.

[0800] The above is the flow of specific processing steps in the household finance consultation system.

[0801] Example 1

[0802] 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."

[0803] Traditionally, household financial consultation services have been time-consuming and expensive, making them difficult for ordinary users to use. Furthermore, specialized knowledge is often required, making it difficult to obtain appropriate advice. Furthermore, online consultations are prone to input errors and misunderstandings, resulting in the risk of incorrect recommendations. Furthermore, analysis results using AI alone can sometimes lack reliability, requiring final confirmation by a human expert, but there has been a lack of a system for smoothly carrying out this adjustment.

[0804] 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.

[0805] In this invention, the server includes means for a user to input basic information, means for transmitting the input data, means for analyzing the received data based on a generative AI model and generating a household plan or insurance proposal, means for returning the generated proposal to the user's information processing device and displaying it, means for generating answers to the user's detailed questions using the generative AI model or a human expert and returning them to the user's information processing device, and means for handing over to a human expert if the user's question is determined to be of advanced or specialized content. This allows the user to easily receive highly accurate household consultation and, if necessary, to receive detailed support from a human expert.

[0806] "User" refers to an individual or corporation that uses this system to provide financial advice.

[0807] "Basic information" refers to information entered by the user, such as name, age, income, fixed expenses, and family composition.

[0808] "Server" refers to a computer system for receiving and processing data sent by users.

[0809] A "generative AI model" refers to an artificial intelligence model that analyzes user data to generate household plans and insurance proposals.

[0810] The term "information processing device" refers to a terminal that a user accesses to input data and view the results.

[0811] "Format validation" refers to the process of checking whether the format and content of the data entered by the user are correct.

[0812] A "detailed question" refers to a question that a user enters when they want to know more about the content of a proposal.

[0813] "Human experts" refer to experts who review the results generated by the AI ​​model and provide additional advice to users as needed.

[0814] "Database" refers to a data management system for storing and managing basic user information and AI analysis results.

[0815] "Handing over" refers to the process of transferring the response from the AI ​​model to a human expert when the user's question is deemed to be advanced or specialized.

[0816] This invention is a financial consultation system that utilizes a generative AI model to provide prompt and appropriate advice when a user seeks financial advice. This system is primarily composed of a user, a terminal, a server, a generative AI model, and a human expert. The system's processing is carried out in the following specific steps.

[0817] Hardware and Software Use

[0818] Device:

[0819] A terminal is an information processing device that allows a user to access the system, and includes a personal computer, smartphone, tablet, etc. A terminal has an input interface and a display interface.

[0820] server:

[0821] A computer system for receiving and processing data sent by users. The server manages the database and works in conjunction with the generative AI model. It is generally installed on a cloud platform (e.g., Amazon Web Services, Microsoft Azure).

[0822] Generative AI models:

[0823] It is an artificial intelligence model that analyzes user data and generates household plans and insurance proposals. It uses machine learning and deep learning libraries such as Python, TensorFlow, and Scikit-learn.

[0824] Data processing and calculation

[0825] Collecting input data:

[0826] The terminal displays a basic information input form to the user, who then enters information such as name, age, income, fixed expenses, and family composition. The input data is checked for formatting on the terminal, and if no errors are detected, it is sent to the server.

[0827] Analyzing data and generating recommendations:

[0828] The server passes the received user data to the generative AI model, which analyzes the collected data and generates recommendations for household budget revisions and optimal insurance plans. The generated proposals are then sent back to the server.

[0829] View suggestions:

[0830] The server sends the proposals received from the generative AI model to the user's device, which then displays the household plan and insurance proposals that are suitable for the user.

[0831] Response to detailed questions:

[0832] The user enters detailed questions or customization requests regarding the suggestions into the device. The device then sends the user's question data to the server. The server then asks the question to a generative AI model or a human expert and generates an answer. The generated answer is then sent back to the user's device and displayed.

[0833] Expert support:

[0834] If the server determines that the user's question is too advanced or technical, it will hand over to a human expert, who will contact the user for a detailed consultation.

[0835] Specific examples

[0836] Example 1: Financial advice prompt

[0837] Example financial advice prompt: "How can I reduce my monthly fixed expenses?"

[0838] The generative AI model then responds to this prompt by generating multiple pieces of energy-saving advice, such as "switch to eco-friendly appliances to reduce your electricity bill" or "cancel your magazine subscription."

[0839] Example 2: Insurance consultation prompt

[0840] Example insurance consultation prompt: "What is the best life insurance plan for me?"

[0841] The generative AI model proposes cost-effective life insurance plans based on the user's age, income, family structure, etc. For example, it will suggest specific plans such as "a comprehensive plan that covers the entire family for a user in their 30s with a family."

[0842] In this way, the present invention allows users to easily receive highly accurate financial advice and, if necessary, receive detailed support from human experts. Specific proposals are generated for various usage scenarios, allowing users to efficiently manage their financial affairs in an optimal manner.

[0843] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0844] Step 1:

[0845] A user accesses the system.

[0846] Input: The user accesses the system URL from their home computer or smartphone and is redirected to the login screen.

[0847] Output: A login authentication screen is displayed.

[0848] Specific operation: The terminal prompts the user to enter their user ID and password.

[0849] Step 2:

[0850] The user performs login authentication.

[0851] Input: The user enters their user ID and password and clicks the "Login" button.

[0852] Output: The input information is sent to the server.

[0853] Specific operation: The terminal sends the entered user ID and password to the server.

[0854] Step 3:

[0855] The server performs login authentication.

[0856] Input: User ID and password sent from the device.

[0857] Output: Session information if authentication is successful, error message if authentication is unsuccessful.

[0858] Specific operation: The server checks the user ID and password against the information in the database. If authentication is successful, it generates session information and returns it to the terminal. If authentication fails, it returns an error message.

[0859] Step 4:

[0860] The user enters basic information.

[0861] Input: The user enters name, age, income, fixed expenses, family composition, etc.

[0862] Output: Basic information input data.

[0863] Specific operation: After successful authentication, the terminal displays a basic information input form, and the user enters the required information in each field.

[0864] Step 5:

[0865] The terminal checks the format of the data.

[0866] Input: Basic information entered by the user.

[0867] Output: Format check result.

[0868] What happens: The terminal checks whether the entered data is in the correct format and detects errors, for example, whether the age is a number.

[0869] Step 6:

[0870] The device sends the verified data to the server.

[0871] Input: Basic information data with formatting checked.

[0872] Output: Sending data to the server.

[0873] Specific operation: The terminal sends the data to the server after checking the format.

[0874] Step 7:

[0875] The server receives and analyzes the data.

[0876] Input: Basic information data sent from the device.

[0877] Output: Save to database.

[0878] What happens: The server parses the data it receives, converts it into a structured format, and then stores it in a database.

[0879] Step 8:

[0880] The server passes the data to the generative AI model.

[0881] Input: Basic information data stored in the database.

[0882] Output: Passing data to a generative AI model.

[0883] Specific operation: The server transmits the stored data to the generative AI model.

[0884] Step 9:

[0885] A generative AI model analyzes the data and generates suggestions.

[0886] Input: Basic information data passed to the generative AI model.

[0887] Output: Household plan and insurance proposals.

[0888] Specific operation: The generative AI model analyzes basic information and generates points to review for household finances and optimal insurance plans.

[0889] Step 10:

[0890] The server sends the generated proposal to the terminal.

[0891] Input: Proposals generated from a generative AI model.

[0892] Output: Sends the proposal data to the user's device.

[0893] Specific operation: The server sends the generated proposal to the user's device.

[0894] Step 11:

[0895] The device will display suggestions.

[0896] Input: Proposal data sent by the server.

[0897] Output: Display of proposal.

[0898] Specific operation: The device displays household plans and insurance proposals suitable for the user on the screen.

[0899] Step 12:

[0900] The user enters a detailed question.

[0901] Input: Detailed questions or customization requests for the proposal.

[0902] Output: Question data.

[0903] Specific operation: The user enters a detailed question about the proposal, and the device sends it to the server.

[0904] Step 13:

[0905] The server generates questions and asks them to AI models or human experts.

[0906] Input: Question data from the user.

[0907] Output: Response data.

[0908] What it does: The server passes the user's question to a generative AI model or human expert to generate an appropriate answer.

[0909] Step 14:

[0910] The server generates a response and sends it back to the terminal.

[0911] Input: Answer data from a generative AI model or human experts.

[0912] Output: Send the answer data to the user's device.

[0913] Specific operation: The server sends the generated answer to the user's terminal.

[0914] Step 15:

[0915] The device will display a detailed response.

[0916] Input: The response data sent from the server.

[0917] Output: Show detailed answer.

[0918] Specific Actions: The device displays a detailed answer to the user.

[0919] Step 16:

[0920] The server will hand over to the expert.

[0921] Input: Advanced or specialized question data.

[0922] Output: Expert handover notification and data sharing.

[0923] Specific operation: If the server determines that the user's question is advanced, it notifies a human expert and shares the necessary data.

[0924] (Application example 1)

[0925] 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."

[0926] Conventional household finance consultation systems only required users to input household finance-related information and receive AI analysis results, which limited user interaction and resulted in an insufficient consultation experience. Furthermore, when providing specific advice, it was difficult to provide real-time feedback, making it difficult for users to receive prompt and appropriate suggestions.

[0927] Furthermore, when users seek financial advice from home, the environment is limited, and the consultation process with the expert may not proceed smoothly.

[0928] 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.

[0929] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on a generative AI model to generate a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's information terminal; a means for generating answers to the user's detailed questions based on the generative AI model or a human expert and returning them to the user's information terminal; a means for displaying the household budget plan in a virtual environment using augmented reality; and a natural language processing means for voice interaction with the user. This allows the user to receive prompt and appropriate proposals in real time during a household budget consultation from the comfort of their own home. Furthermore, combining augmented reality technology with natural language processing improves interaction with the user and allows for more specific and friendly advice to be provided.

[0930] The "means for the user to input basic information" is an interface that allows the user to input basic information about the household, such as name, age, income, fixed expenses, and family composition.

[0931] "Means for sending input data to a server" refers to a mechanism for transferring basic information input by a user to a remote server via a network.

[0932] "Means for analyzing received data based on a generation AI model and generating a household plan or insurance proposal" refers to the process of analyzing data sent by a user using AI technology and generating an optimal household plan or insurance proposal.

[0933] "Means for returning and displaying the generated proposals to the user's information terminal" refers to a mechanism for sending household plans and insurance proposals generated by AI to the device used by the user and displaying them visually.

[0934] "Means for generating answers to detailed user questions using a generative AI model or a human expert and sending them back to the user's information device" refers to the process by which an AI or expert creates an answer to a detailed user question and sends that answer to the user's device.

[0935] "Means for displaying a household plan in a virtual environment using augmented reality" refers to a mechanism that uses AR technology to visually overlay a household plan on the user's real-world environment.

[0936] "Natural language processing means for voice interaction with a user" is a system that includes technology for understanding a user's voice input and generating an appropriate response.

[0937] "Means for format validation and error detection" refers to a mechanism that has a validation process to ensure that data entered by the user conforms to a predetermined format and has the ability to detect incorrect input.

[0938] "Means for a human expert to finalize the analysis results of the generated AI model and contact the user as necessary" refers to a process in which experts review the analysis results generated by AI and, if necessary, provide direct feedback to the user.

[0939] "Means for managing the database used by the AI ​​model" refers to a system for storing data necessary for AI analysis and maintaining and operating the database that manages it.

[0940] "Natural language processing means for voice interaction" is a system that uses technology to analyze a user's voice input, understand the content of the question, and automatically generate an appropriate response.

[0941] This invention is a system that allows users to receive financial advice from the comfort of their own home, and is composed of the following elements: A device such as a smartphone, smart glasses, or head-mounted display is used as a means for users to input basic information. This device provides an interface for users to input basic information about their household finances, such as name, age, income, fixed expenses, and family composition.

[0942] The data entered by the user is sent via a network to a remote server. The server analyzes the received data based on a generative AI model and generates a household plan or insurance proposal. The generative AI model is an analysis system that uses machine learning algorithms and is built into the server.

[0943] The generated proposals are then sent back to the user's information device and displayed visually. In this process, the AI ​​model generates household plans and proposals for the user in real time. Answers to detailed questions from the user are also generated by the AI ​​model or human experts and sent back to the user's information device.

[0944] The system includes a means to display a household plan in a virtual environment using augmented reality (AR) technology. Users can visually experience a virtual household planner in their living room or other location using smart glasses or a head-mounted display. The system also uses voice recognition and natural language processing technology to interact with the user, allowing them to input household information and ask questions by voice.

[0945] As a specific example, there is a scenario in which a user can say, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people," and the system will collect basic information and perform analysis. The user's voice input is converted into text using the Google Speech-to-Text API, and the Google Natural Language API is used for natural language processing.

[0946] If a user wants to ask a more detailed question about the proposed household budget plan, for example, they can say, "How can I revise my household budget plan?" This question is also analyzed using natural language processing, and a generative AI model or expert generates an answer. This answer is also displayed on the information terminal, providing visual and audio feedback.

[0947] An example of a prompt is as follows:

[0948] Please enter household information such as the user's name, age, income, fixed expenses, and family composition. For example, please enter something like, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people."

[0949] In this way, users can use an interactive household finance consultation system that combines augmented reality technology and natural language processing from the comfort of their own home. This invention enables users to receive prompt and accurate household finance advice, which is expected to improve their quality of life.

[0950] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0951] Step 1:

[0952] The user enters basic information.

[0953] Users launch the household finance advisor app using their smartphone, smart glasses, or head-mounted display, and an input screen appears, prompting them to enter basic information such as their name, age, income, fixed expenses, and family composition by voice or text.

[0954] Input: User's household information

[0955] Output: Input household information data

[0956] Step 2:

[0957] The terminal transmits the input data to the server.

[0958] The terminal checks the format of the household information entered by the user and performs error detection before transmitting the data to a remote server via a network.

[0959] Input: Entered household information data

[0960] Output: Household information data sent to the server

[0961] Step 3:

[0962] The server analyzes the data using the generative AI model.

[0963] The server analyzes the received data based on the generative AI model and generates a household plan or insurance proposal, using machine learning algorithms to evaluate the user's household situation and make optimal proposals.

[0964] Input: Household information data sent to the server

[0965] Output: A household budget or insurance proposal from a generative AI model

[0966] Step 4:

[0967] The server sends the generated proposal back to the user's terminal.

[0968] The household plan and insurance proposals generated by the server are sent back to the user's terminal via the network.

[0969] Input: household budget or insurance proposals from a generative AI model

[0970] Output: Proposal data returned to the user device

[0971] Step 5:

[0972] The terminal displays the suggestions to the user.

[0973] The device visually displays the returned household plan or insurance proposal and presents it to the user in an easy-to-view format, where the household plan is displayed in a virtual environment using augmented reality (AR) technology.

[0974] Input: Returned proposal data

[0975] Output: A household plan or insurance proposal displayed to the user

[0976] Step 6:

[0977] The user enters a detailed question.

[0978] The user can then enter additional or detailed questions about the suggestions by voice or text.

[0979] Input: Detailed question from user

[0980] Output: Question data entered

[0981] Step 7:

[0982] The terminal transmits the question data to the server.

[0983] The terminal sends detailed questions from the user to the server.

[0984] Input: The entered question data

[0985] Output: The query data sent to the server

[0986] Step 8:

[0987] The server asks questions to generative AI models or human experts and generates answers.

[0988] The server analyzes the user's detailed question and generates an answer relying on generative AI models or human experts.

[0989] Input: Query data sent to the server

[0990] Output: Generated response data

[0991] Step 9:

[0992] The server sends the generated answer back to the user's terminal.

[0993] The generated answer is sent back to the user's terminal via the network.

[0994] Input: Generated response data

[0995] Output: Answer data returned to the user's device

[0996] Step 10:

[0997] The terminal displays the answer to the user.

[0998] The terminal visually displays the returned answer data and provides the user with audio or text feedback.

[0999] Input: Returned response data

[1000] Output: The answer displayed to the user

[1001] 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.

[1002] This invention is a financial advice system that utilizes AI and an emotion engine to provide more accurate and emotionally sensitive advice to users when they seek financial advice. Below, we explain the program processing of this system in natural language. We also provide a user usage scenario with concrete examples.

[1003] Overall system overview

[1004] This household financial consultation system mainly consists of the following elements:

[1005] 1. Terminal

[1006] 2. Server

[1007] 3. AI Model

[1008] 4. Emotion Engine

[1009] 5. Human Experts

[1010] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and the emotion engine recognizing the user's emotional state, with human experts providing support as needed.

[1011] Program processing flow

[1012] The specific processing flow of the system is as follows:

[1013] 1. The user starts a financial consultation

[1014] A user accesses an online or in-store terminal and arrives at the login screen.

[1015] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[1016] The terminal transmits the user's input information to the server for authentication.

[1017] 2. Enter your user information

[1018] The terminal displays a basic information input form to the user.

[1019] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[1020] The terminal checks the format of the entered data and checks for input errors.

[1021] 3. Sending input data

[1022] The terminal transmits the data whose format has been confirmed to the server.

[1023] The server analyzes the received data and stores it in a database.

[1024] 4. Analysis using AI models

[1025] The server passes the stored data to the AI ​​model.

[1026] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[1027] 5. Emotion Recognition by Emotion Engine

[1028] The terminal activates an emotion engine during interaction with the user to recognize the user's emotional state.

[1029] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate their emotional state.

[1030] 6. Customize your suggestions

[1031] The emotional state recognized by the emotion engine is sent to the server.

[1032] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[1033] The server sends the customized offer to the user's terminal.

[1034] 7. Display of Suggestions

[1035] The device displays household plans and insurance proposals that are suitable for the user.

[1036] The user enters detailed questions and customization requests for the displayed plan.

[1037] 8. Response to detailed questions

[1038] The terminal transmits the user's questions and requests to the server.

[1039] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[1040] 9. Generating and Displaying Answers

[1041] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[1042] The server sends the generated answer to the user's terminal.

[1043] The terminal displays the detailed answer to the user.

[1044] 10. Handover to an expert

[1045] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[1046] The server notifies the experts and shares the user's data.

[1047] A human expert will contact the user for a detailed consultation.

[1048] Specific examples

[1049] Example: Maria is discussing her financial plan.

[1050] 1. Maria starts financial counseling

[1051] Maria accesses the system online from her home computer and reaches the login screen.

[1052] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[1053] The terminal transmits Maria's input information to the server for authentication.

[1054] 2. Enter your user information

[1055] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[1056] The terminal checks the format of the entered data and checks for input errors.

[1057] 3. Sending input data

[1058] The terminal transmits the verified data to the server.

[1059] The server receives and analyzes the data and then stores it in a database.

[1060] 4. Analysis using AI models

[1061] The server passes the stored data to the AI ​​model.

[1062] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[1063] 5. Emotion Recognition by Emotion Engine

[1064] The device activates an emotion engine during interaction with Maria to recognize her emotional state.

[1065] The emotion engine analyzes Maria's facial expressions, voice, and text data to assess her emotional state.

[1066] 6. Customize your suggestions

[1067] The emotional state recognized by the emotion engine is sent to the server.

[1068] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[1069] The server sends the customized offer to Maria's terminal.

[1070] 7. Display of Suggestions

[1071] The device displays the suggestions to Maria and provides appropriate advice that takes her emotions into consideration.

[1072] 8. Response to detailed questions

[1073] Maria enters detailed questions and customization requests for the displayed plan.

[1074] The device sends these questions to a server, which then asks an AI model or a human expert.

[1075] 9. Generating and Displaying Answers

[1076] An AI model or human expert generates answers to Maria's questions and sends them back to the server.

[1077] The server sends the generated response to Maria's terminal.

[1078] The terminal displays a detailed response to Maria.

[1079] 10. Handover to an expert

[1080] The server determines that Maria's question is advanced and hands it over to a human expert.

[1081] The expert will contact Maria and provide further advice.

[1082] In this way, this invention allows users to use a household finance consultation service that also takes their emotional state into consideration. In addition to fast and appropriate suggestions from AI, the emotion engine recognizes the user's emotional state and human experts provide support as needed, making it possible to provide a highly reliable service to users.

[1083] The processing flow will be explained below.

[1084] Step 1:

[1085] A user accesses an online or in-store terminal and arrives at the login screen.

[1086] The terminal displays a login authentication screen to the user.

[1087] The user enters the user ID and password and clicks the login button.

[1088] Step 2:

[1089] The terminal sends the user's login information to the server.

[1090] The server receives the login information and authenticates it against a database.

[1091] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[1092] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[1093] Step 3:

[1094] The terminal displays a basic information input form to the user.

[1095] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[1096] Step 4:

[1097] The terminal checks the format of the input data.

[1098] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[1099] Step 5:

[1100] The server analyzes the received data and stores it in a database.

[1101] Step 6:

[1102] The server passes the stored data to the AI ​​model.

[1103] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[1104] Step 7:

[1105] The terminal activates the emotion engine during interaction with the user.

[1106] The emotion engine analyzes the user's facial expressions, voice, and text data to assess their emotional state.

[1107] Step 8:

[1108] The emotion engine transmits the recognized emotional state to the server.

[1109] The server uses this emotional data to customize the suggestions generated by the AI ​​model.

[1110] Step 9:

[1111] The server sends the customized offer to the user's terminal.

[1112] The terminal displays the suggestions to the user.

[1113] Step 10:

[1114] The user then inputs detailed questions and customization requests in response to the displayed suggestions.

[1115] The terminal sends these questions and requests to the server.

[1116] Step 11:

[1117] The server receives detailed questions or requests and refers them to an AI model or a human expert.

[1118] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[1119] Step 12:

[1120] The server sends the generated answer to the user's terminal.

[1121] The terminal displays the detailed answer to the user.

[1122] Step 13:

[1123] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[1124] The server notifies the experts and shares the user's data.

[1125] A human expert will contact the user for further consultation.

[1126] The above is the flow of specific processing steps in the household finance consultation system.

[1127] Example 2

[1128] 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."

[1129] Conventional financial consultation systems make suggestions based on basic user information, but they fail to consider the user's emotional state and often make one-sided suggestions, making it difficult for users to achieve satisfactory results. Furthermore, input data formatting and error checking are often insufficient, resulting in incorrect information being sent to the system. Furthermore, when answers to detailed questions are automatically generated, they often lack professional judgment.

[1130] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's terminal; a means for recognizing an emotional state during interaction with the user; a means for customizing the proposal content based on the recognized emotional state; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's terminal; a means for checking the data format and performing error checks; and a means for a human expert to finally check the AI ​​analysis results and contact the user as necessary. This enables the provision of an accurate household budget plan that reflects the user's emotional state, high reliability of input data, and response to detailed questions from a professional perspective.

[1131] "User" refers to a person who uses the system to receive financial advice.

[1132] "Terminal" refers to an electronic device (PC, smartphone, tablet, etc.) that a user uses to access and use the system.

[1133] "Server" refers to the central computer device that manages the entire system and performs processes such as data storage, analysis, and proposal generation.

[1134] "Artificial intelligence model" refers to the algorithms and machine learning models that analyze user data and generate household plans and insurance proposals.

[1135] An "emotion engine" refers to a system that recognizes a user's emotional state from data collected during interactions with the user and customizes suggestions based on the results.

[1136] A "household plan" refers to a financial plan created taking into account the user's income, expenses, family composition, etc.

[1137] "Insurance proposal" refers to information that suggests the most suitable insurance plan based on the user's household data, etc.

[1138] "Interaction" refers to the dialogue and exchange of information between a user and a system.

[1139] "Error checking" refers to the process of checking and correcting input data for errors.

[1140] This invention is a financial advice system that provides users with more accurate and emotionally sensitive advice when they seek financial advice. The system collects basic information about the user and generates financial plans and insurance proposals using an artificial intelligence model and an emotion engine. Furthermore, the system recognizes the user's emotional state and customizes proposals based on that state. A specific embodiment of the system is described below.

[1141] The system mainly consists of the following elements:

[1142] 1. Terminal

[1143] This refers to devices that users use to access systems, such as PCs, smartphones, and tablets. Examples include Apple's MacBook, Microsoft's Surface, and Google's Pixel.

[1144] 2. Server

[1145] This refers to the central computer device that manages the entire system and stores data, analyzes it, and generates proposals. It can be a general cloud server, such as an EC2 instance from Amazon Web Services (AWS) or a Compute Engine from Google Cloud Platform (GCP).

[1146] 3. Artificial Intelligence Model

[1147] This refers to algorithms and machine learning models that analyze user data and generate household plans and insurance proposals. Examples include OpenAI's GPT-3 and BERT.

[1148] 4. Emotion Engine

[1149] This refers to systems that recognize a user's emotional state from data collected during user interactions and customize suggestions based on the results. Examples include Affectiva and Microsoft's Emotion API.

[1150] 5. Human Experts

[1151] This refers to financial planners and insurance advisors who, if necessary, provide final confirmation of the analysis results of the AI ​​model and contact users directly.

[1152] Specific examples

[1153] In a scenario where a user is consulting about a household budget, the system operates in the following steps.

[1154] 1. The user starts a financial consultation

[1155] A user accesses the system from their home PC and reaches the login screen. The terminal displays the login authentication screen, and the user logs in by entering their user ID and password. This information is sent from the terminal to the server and authenticated.

[1156] 2. Enter your user information

[1157] The terminal displays a basic information input form, and the user inputs name, age, income, fixed expenses, family composition, etc. The terminal checks the format of the input data and performs error checks.

[1158] 3. Analysis of input data

[1159] The server receives the data after checking the format and stores it in a database. The stored data is then passed to an AI model, which analyzes the user's data and generates budget adjustments and optimal insurance plans.

[1160] 4. Emotion Recognition and Customized Suggestions

[1161] The device activates an emotion engine during interaction with the user to recognize the user's emotional state. The emotion engine then sends the recognized emotional data to the server, which then customizes suggestions based on this data. As a result, the device provides appropriate advice that takes the user's emotions into consideration.

[1162] Prompt Sentence Examples

[1163] Below is an example of a prompt sentence to input to the generative AI model.

[1164] "The user is 30 years old and earns 300,000 yen a month. I have entered detailed information about my monthly fixed expenses and family structure. Please suggest the best household budget plan for this user."

[1165] The detailed operation of this system allows users to receive accurate and prompt financial advice that takes their emotions into consideration. Each element works in tandem to provide a highly reliable service to users.

[1166] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1167] Step 1:

[1168] User starts household finance consultation

[1169] A user accesses the system using a PC or smartphone and reaches the login screen.

[1170] Input: User ID, Password

[1171] The terminal displays a login authentication screen, and the user enters their user ID and password.

[1172] Output: Authentication result

[1173] The device sends the entered authentication information to the server. The server verifies the authentication information and checks whether the user is registered. If authentication is successful, the device displays the home screen to proceed to the next step.

[1174] Step 2:

[1175] Entering user information

[1176] The terminal displays a basic information input form to the user.

[1177] Input: Basic information such as name, age, income, fixed expenses, family composition, etc.

[1178] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[1179] Output: Basic information entered

[1180] The terminal checks the format of the entered data and ensures that all required fields are filled in. If there is a problem with the format, the terminal displays an error message and prompts the user to re-enter the data.

[1181] Step 3:

[1182] Sending input data

[1183] The terminal transmits the data after format confirmation to the server.

[1184] Input: Verified data

[1185] The server analyzes the received data and stores it in a database.

[1186] Output: Save results to database

[1187] The server returns a confirmation of data storage to the terminal and instructs it to proceed to the next step.

[1188] Step 4:

[1189] Analysis using AI models

[1190] The server passes the stored user data to an artificial intelligence model.

[1191] Input: Saved user data

[1192] The artificial intelligence model generates budget review points and optimal insurance plans based on data such as the user's income, expenses, and family composition.

[1193] Output: Household budget plan and insurance proposals

[1194] The AI ​​model generates a proposal that is sent back to the server, which uses it in the next step.

[1195] Step 5:

[1196] Emotion recognition by emotion engine

[1197] The terminal activates the emotion engine during interaction with the user.

[1198] Input: User's facial expressions, voice, and text data

[1199] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate the user's emotional state.

[1200] Output: Emotional evaluation data

[1201] The evaluated emotion data is sent to the server via the terminal.

[1202] Step 6:

[1203] Customize suggestions

[1204] The server customizes the suggestions generated by the artificial intelligence model based on the emotional data received from the emotion engine.

[1205] Input: Emotion data, suggested data from AI model

[1206] The server adjusts the content of the suggestions appropriately depending on the user's emotional state, and constructs the most appropriate advice for the user.

[1207] Output: Customized proposal

[1208] Send customized offers to your device.

[1209] Step 7:

[1210] View Suggestions

[1211] The device displays customized household plans and insurance offers to the user.

[1212] Input:Customized Proposal

[1213] Output: Displayed proposal

[1214] Users can then enter detailed questions and customization requests for the plans displayed, allowing them to receive advice that best suits their situation.

[1215] Step 8:

[1216] Response to detailed questions

[1217] The terminal sends user questions and requests to the server.

[1218] Input: User questions or requests

[1219] Based on the question, the server asks an AI model or a human expert to respond to the question.

[1220] Output: Request details

[1221] This allows for appropriate answers to be prepared for detailed questions from the user.

[1222] Step 9:

[1223] Generate and display answers

[1224] An artificial intelligence model or human expert generates answers to the user's questions and sends them back to the server.

[1225] Input: Question response request, expert answer

[1226] Output: The generated answer

[1227] The server sends the generated answer to the user's device, which displays the detailed answer to the user, allowing the user to resolve their question and obtain further information.

[1228] Step 10:

[1229] Handover to experts

[1230] If the server determines that the user's question is difficult, it will hand it off to a human expert.

[1231] Input: User question, expert handover instructions

[1232] Output: Handover notification to expert

[1233] The server notifies the expert and shares the user's data, and the human expert contacts the user for a detailed consultation, allowing the user to receive further expert advice.

[1234] (Application example 2)

[1235] 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."

[1236] Conventional household budget consultation systems provide analysis results and advice without considering the user's emotions, making it difficult to reduce the user's psychological burden and stress. In addition, centralized management of expenditure data was insufficient, making it difficult to provide appropriate advice that takes emotions into consideration in real time.

[1237] 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.

[1238] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's device; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's device; an emotion recognition means for analyzing the user's facial expressions and voice using the device's built-in camera and microphone to recognize the user's emotional state; a means for adjusting the proposal content based on the emotional state; a means for transmitting emotion-sensitive notifications and advice to the user's device; a format verification and error detection means; a means for inputting and analyzing the user's expenditure data and providing a household budget improvement plan that takes the user's emotional state into account; and a means for managing the generative AI model and emotion engine to provide advice and plans based on the user's emotional state. This allows for the provision of appropriate advice that takes the user's emotions into account, improving the efficiency of household budget management and reducing the user's psychological burden.

[1239] "Basic information" refers to personal information necessary for financial consultation, such as the user's name, age, income, fixed expenses, and family composition.

[1240] "Server" refers to a device that receives data entered by a user, analyzes it, and returns the results to the user.

[1241] "AI model" refers to an algorithm that uses machine learning technology to generate household budget review points and insurance proposals.

[1242] "Emotion recognition means" refers to a device that uses a camera and microphone to analyze the user's facial expressions and voice and evaluate their emotional state.

[1243] "Emotional state" refers to the psychological state obtained from the user's facial expressions, voice, and text data.

[1244] "Proposal content" refers to advice and plans generated by the AI ​​model, such as points to review in household finances and insurance proposals.

[1245] "Notifications and advice" refers to information about improving household finances and notifications encouraging specific actions that are sent to the user's device.

[1246] "Terminal" refers to the device on which the user inputs information and receives and displays suggestions from the server.

[1247] "Format checking and error detection means" refers to a function that checks whether there are any errors in the format or content of the data entered by the user.

[1248] "Input and analysis of expenditure data" refers to the function that allows users to input daily expenditure amounts and breakdowns and analyze them.

[1249] "Finance Improvement Plan" refers to savings and investment plans created based on the user's spending data and emotional state.

[1250] A "generative AI model" refers to an algorithm that uses AI technology to generate suggestions suited to a user's financial situation and emotional state.

[1251] An "emotion engine" refers to software that assesses a user's emotional state and adjusts suggestions accordingly.

[1252] MODE FOR CARRYING OUT THE INVENTION

[1253] System configuration overview

[1254] This invention is a system that provides financial advice to users while they manage their daily expenses. The system aims to provide advice that takes into account the user's emotional state. The main components of the system include a terminal, a server, an AI model, and an emotion engine.

[1255] Hardware and software used

[1256] Hardware: Smartphone (built-in camera, microphone)

[1257] Software: TensorFlow, Emotion API, Expense Database

[1258] Program processing

[1259] overview

[1260] The server performs the following processes: It analyzes the expenditure data entered by the user and generates a household budget plan and insurance proposals based on that data. It also recognizes the user's emotional state in real time using a camera and microphone and provides advice that takes their emotions into consideration. It also responds to detailed questions from the user and provides appropriate feedback tailored to the user's emotions.

[1261] The server operates as follows:

[1262] 1. Data Acquisition

[1263] Users enter basic information and expenditure data into their smartphones and send it to the server, which receives the data and stores it in a database.

[1264] 2. Data analysis and proposal generation

[1265] The saved data is passed to an AI model that generates budget review points and insurance proposals. The AI ​​model uses TensorFlow to calculate optimal advice based on past data and statistical information.

[1266] 3. Recognizing emotional states

[1267] It uses the smartphone's camera and microphone to analyze the user's facial expressions and voice in real time, and uses the Emotion API to evaluate the user's emotional state at that time.

[1268] 4. Adjusting the proposal

[1269] The emotion engine analyzes the user's emotional state and customizes the generated household budget plan and advice based on that. For example, if the user is feeling stressed, it will prioritize specific and easy-to-implement plans.

[1270] 5. Sending Notices and Advice

[1271] The adjusted suggestions are sent to the user via push notifications on their smartphone, etc. The notification content takes into consideration emotions and provides advice in gentle language.

[1272] Specific scenarios

[1273] Situation: User enters expenditure data and conducts financial consultation

[1274] 1. Entering expenditure data

[1275] User: Enters "My recent expenses are 5,000 yen" into the app.

[1276] 2. Recognizing emotional states

[1277] The app's camera captures the user's facial expression and recognizes that they are confused.

[1278] 3. Proposal generation and refinement

[1279] The AI ​​model analyzes users' spending patterns and identifies points where they should adjust their finances, while the Emotion API notifies the server when a user is under stress.

[1280] 4. Submitting Advice

[1281] The server sends emotion-sensitive suggestions to the smartphone and notifies the user.

[1282] "It seems like you haven't been managing your expenses well lately. I'd like to suggest some easy and simple ways to save money. How about setting aside some time on the weekends to relax with your family and do your hobbies?"

[1283] The above is an embodiment of the invention.

[1284] Prompt Sentence Examples

[1285] Below is an example of a prompt that an application might pass to a generative AI model.

[1286] A user enters their recent spending data. The camera detects a confused state in their facial expression. Reflect their emotional state, provide situational financial improvement advice, and suggest emotionally sensitive recommendations.

[1287] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1288] Step 1:

[1289] The user enters basic information and expenditure data into their smartphone device and sends it to the server.

[1290] Input: The user enters basic information such as "name, age, income, fixed expenses, family composition" and "expense data" into the app.

[1291] Output: The app sends input data and the server receives it.

[1292] Specific operation: The user presses the submit button on the smartphone app to submit the information entered in the form. The server receives this information and stores it in the database.

[1293] Step 2:

[1294] The server stores the received data and passes it to the AI ​​model.

[1295] Input: Basic information and spending data sent from your device.

[1296] Output: Stored data and input to the AI ​​model.

[1297] What it does: The server immediately stores the received data in a database and prepares it to be passed to the AI ​​model for analysis.

[1298] Step 3:

[1299] The AI ​​model analyzes the stored spending data and generates household plans and insurance proposals.

[1300] Input: User spending data retrieved from the database.

[1301] Output: Generation of household plans and insurance proposals.

[1302] How it works: An AI model (powered by TensorFlow) pulls user data from a database, compares it with statistics and historical data, and generates appropriate financial plans and insurance proposals.

[1303] Step 4:

[1304] Using the smartphone's camera and microphone, the system analyzes the user's facial expressions and voice to recognize their emotional state.

[1305] Input: User's facial expression data captured by the smartphone camera and voice data captured by the microphone.

[1306] Output: Evaluation of the user's emotional state.

[1307] Specific operation: The device sends the user's facial expressions and voice to the Emotion API in real time for emotion recognition, and the emotional state is sent to the server.

[1308] Step 5:

[1309] The emotion engine adjusts the suggestions based on the emotional state it recognizes.

[1310] Input: Emotional state data from emotion recognition instruments, and financial plan and insurance proposal data from AI models.

[1311] Output: Emotionally sensitive household budget plans and insurance proposals.

[1312] How it works: The server adjusts the generated household plan based on the data obtained from the emotion engine. For example, it will prioritize plans that are easy to implement for users who are under stress.

[1313] Step 6:

[1314] The user is notified of emotionally sensitive suggestions via their device.

[1315] Input: Tailored household plans and insurance proposals.

[1316] Output: The suggestions displayed on the user's smartphone.

[1317] Specific operation: The server sends the adjusted proposal to the user's device and notifies them via push notification or on-screen display.

[1318] Step 7:

[1319] The user inputs detailed questions and feedback about the generated plan and sends them to the server.

[1320] Input: Questions or feedback that users enter into the app.

[1321] Output: Detailed question and feedback sent to the server.

[1322] Specific operation: The user reviews the proposal, enters questions or feedback through the app interface, and presses the send button to send it to the server.

[1323] Step 8:

[1324] The server generates answers based on detailed questions, either through AI models or human experts.

[1325] Input: User's detailed question.

[1326] Output: The generated answer.

[1327] What it does: The server passes the user's question to an AI model or designated expert to generate an answer, which is then sent back to the server.

[1328] Step 9:

[1329] The generated answer is returned to the user's terminal and displayed.

[1330] Input: The generated answer.

[1331] Output: The answer displayed on the user's device.

[1332] Specific behavior: The server sends the generated answer to the user's device, and the app displays the answer.

[1333] Step 10:

[1334] If the server determines that the user's question is more advanced, it hands it off to a human expert.

[1335] Input: User's advanced question.

[1336] Output: Detailed answers from experts.

[1337] What it does: The server evaluates the question and, if it determines that the question is advanced, notifies an expert and shares the user's data. The expert then contacts the user directly and provides detailed advice.

[1338] The above is the specific processing flow of the system that realizes the application example.

[1339] 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.

[1340] 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.

[1341] 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.

[1342] [Third embodiment]

[1343] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1344] 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.

[1345] 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).

[1346] 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.

[1347] 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.

[1348] 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).

[1349] 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.

[1350] 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.

[1351] 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.

[1352] 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.

[1353] 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.

[1354] 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."

[1355] This invention is a financial consultation system that uses AI to provide prompt and appropriate advice when users seek financial advice. The program processing of this system is explained in natural language below. A user usage scenario is also shown with specific examples.

[1356] Overall system overview

[1357] This household financial consultation system mainly consists of the following elements:

[1358] 1. Terminal

[1359] 2. Server

[1360] 3. AI Model

[1361] 4. Human Experts

[1362] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and human experts providing support as needed.

[1363] Program processing flow

[1364] The specific processing flow of the system is as follows:

[1365] 1. The user starts a financial consultation

[1366] The user accesses an online or in-store terminal and is taken to the login screen.

[1367] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[1368] The terminal transmits the user's input information to the server for authentication.

[1369] 2. Enter your user information

[1370] The terminal displays a basic information input form to the user.

[1371] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[1372] The terminal checks the format of the entered data and checks for input errors.

[1373] 3. Sending input data

[1374] The terminal transmits the data whose format has been confirmed to the server.

[1375] The server analyzes the received data and stores it in a database.

[1376] 4. Analysis using AI models

[1377] The server passes the stored data to the AI ​​model.

[1378] The AI ​​model analyzes the received data and generates optimal household budget review points and insurance plans.

[1379] The AI ​​model sends the generated suggestions back to the server.

[1380] 5. Display of Suggestions

[1381] The server sends the suggestions received from the AI ​​model to the user's device.

[1382] The terminal displays household plans and insurance proposals suitable for the user.

[1383] 6. Response to detailed questions

[1384] The user enters detailed questions and customization requests regarding the proposed content.

[1385] The terminal sends these detailed questions to the server.

[1386] The server asks questions to AI or human experts and generates answers.

[1387] The server returns the generated answer to the user's terminal.

[1388] The terminal displays the detailed answer to the user.

[1389] 7. Handover to experts

[1390] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[1391] The server notifies the experts and shares the user's data.

[1392] A human expert will contact the user for a detailed consultation.

[1393] Specific examples

[1394] Example: Maria is discussing her financial plan.

[1395] 1. Maria starts financial counseling

[1396] Maria accesses the system online from her home computer and is taken to the login screen.

[1397] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[1398] The terminal transmits Maria's input information to the server for authentication.

[1399] 2. Enter your user information

[1400] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[1401] The terminal checks the format of the entered data and checks for input errors.

[1402] 3. Sending input data

[1403] The terminal transmits the verified data to the server.

[1404] The server receives and analyzes the data and then stores it in a database.

[1405] 4. Analysis using AI models

[1406] The server passes the stored data to the AI ​​model.

[1407] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[1408] The AI ​​model sends the generated suggestions back to the server.

[1409] 5. Display of Suggestions

[1410] The server sends the suggestions received from the AI ​​model to Maria's device.

[1411] The terminal displays the proposal to Maria.

[1412] 6. Response to detailed questions

[1413] Maria enters detailed questions about the proposal and requests further customization.

[1414] The device then sends the question to a server and asks either an AI or human expert for an answer.

[1415] The server generates a response and sends it back to Maria's terminal.

[1416] The terminal presents Maria with a detailed response.

[1417] 7. Handover to experts

[1418] The server determines that Maria's question is advanced and hands it over to a human expert.

[1419] The expert will contact Maria and provide further advice.

[1420] In this way, this invention allows users to use the household finance consultation service without any psychological hesitation and receive prompt and appropriate suggestions from AI. Furthermore, since human experts are available to provide support as needed, it is possible to provide a highly reliable service to users.

[1421] The processing flow will be explained below.

[1422] Step 1:

[1423] A user accesses an online or in-store terminal and arrives at the login screen.

[1424] The terminal displays a login authentication screen to the user.

[1425] The user enters the user ID and password and clicks the login button.

[1426] Step 2:

[1427] The terminal sends the user's login information to the server.

[1428] The server receives the login information and authenticates it against a database.

[1429] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[1430] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[1431] Step 3:

[1432] The terminal displays a basic information input form to the user.

[1433] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[1434] Step 4:

[1435] The terminal checks the format of the input data.

[1436] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[1437] Step 5:

[1438] The server analyzes the received data and stores it in a database.

[1439] Step 6:

[1440] The server passes the stored data to the AI ​​model.

[1441] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[1442] Step 7:

[1443] The AI ​​model sends the generated suggestions back to the server.

[1444] The server sends the proposal to the user's terminal.

[1445] Step 8:

[1446] The device displays household plans and insurance proposals that are suitable for the user.

[1447] The user enters detailed questions and customization requests for the displayed plan.

[1448] Step 9:

[1449] The terminal transmits the user's questions and requests to the server.

[1450] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[1451] Step 10:

[1452] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[1453] The server sends the generated answer to the user's terminal.

[1454] Step 11:

[1455] The terminal displays the detailed answer to the user.

[1456] If the user wants further advice, the server hands over to a human expert.

[1457] A human expert will contact the user and provide detailed advice.

[1458] The above is the flow of specific processing steps in the household finance consultation system.

[1459] Example 1

[1460] 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."

[1461] Traditionally, household financial consultation services have been time-consuming and expensive, making them difficult for ordinary users to use. Furthermore, specialized knowledge is often required, making it difficult to obtain appropriate advice. Furthermore, online consultations are prone to input errors and misunderstandings, resulting in the risk of incorrect recommendations. Furthermore, analysis results using AI alone can sometimes lack reliability, requiring final confirmation by a human expert, but there has been a lack of a system for smoothly carrying out this adjustment.

[1462] 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.

[1463] In this invention, the server includes means for a user to input basic information, means for transmitting the input data, means for analyzing the received data based on a generative AI model and generating a household plan or insurance proposal, means for returning the generated proposal to the user's information processing device and displaying it, means for generating answers to the user's detailed questions using the generative AI model or a human expert and returning them to the user's information processing device, and means for handing over to a human expert if the user's question is determined to be of advanced or specialized content. This allows the user to easily receive highly accurate household consultation and, if necessary, to receive detailed support from a human expert.

[1464] "User" refers to an individual or corporation that uses this system to provide financial advice.

[1465] "Basic information" refers to information entered by the user, such as name, age, income, fixed expenses, and family composition.

[1466] "Server" refers to a computer system for receiving and processing data sent by users.

[1467] A "generative AI model" refers to an artificial intelligence model that analyzes user data to generate household plans and insurance proposals.

[1468] The term "information processing device" refers to a terminal that a user accesses to input data and view the results.

[1469] "Format validation" refers to the process of checking whether the format and content of the data entered by the user are correct.

[1470] A "detailed question" refers to a question that a user enters when they want to know more about the content of a proposal.

[1471] "Human experts" refer to experts who review the results generated by the AI ​​model and provide additional advice to users as needed.

[1472] "Database" refers to a data management system for storing and managing basic user information and AI analysis results.

[1473] "Handing over" refers to the process of transferring the response from the AI ​​model to a human expert when the user's question is deemed to be advanced or specialized.

[1474] This invention is a financial consultation system that utilizes a generative AI model to provide prompt and appropriate advice when a user seeks financial advice. This system is primarily composed of a user, a terminal, a server, a generative AI model, and a human expert. The system's processing is carried out in the following specific steps.

[1475] Hardware and Software Use

[1476] Device:

[1477] A terminal is an information processing device that allows a user to access the system, and includes a personal computer, smartphone, tablet, etc. A terminal has an input interface and a display interface.

[1478] server:

[1479] A computer system for receiving and processing data sent by users. The server manages the database and works in conjunction with the generative AI model. It is generally installed on a cloud platform (e.g., Amazon Web Services, Microsoft Azure).

[1480] Generative AI models:

[1481] It is an artificial intelligence model that analyzes user data and generates household plans and insurance proposals. It uses machine learning and deep learning libraries such as Python, TensorFlow, and Scikit-learn.

[1482] Data processing and calculation

[1483] Collecting input data:

[1484] The terminal displays a basic information input form to the user, who then enters information such as name, age, income, fixed expenses, and family composition. The input data is checked for formatting on the terminal, and if no errors are detected, it is sent to the server.

[1485] Analyzing data and generating recommendations:

[1486] The server passes the received user data to the generative AI model, which analyzes the collected data and generates recommendations for household budget revisions and optimal insurance plans. The generated proposals are then sent back to the server.

[1487] View suggestions:

[1488] The server sends the proposals received from the generative AI model to the user's device, which then displays the household plan and insurance proposals that are suitable for the user.

[1489] Response to detailed questions:

[1490] The user enters detailed questions or customization requests regarding the suggestions into the device. The device then sends the user's question data to the server. The server then asks the question to a generative AI model or a human expert and generates an answer. The generated answer is then sent back to the user's device and displayed.

[1491] Expert support:

[1492] If the server determines that the user's question is too advanced or technical, it will hand over to a human expert, who will contact the user for a detailed consultation.

[1493] Specific examples

[1494] Example 1: Financial advice prompt

[1495] Example financial advice prompt: "How can I reduce my monthly fixed expenses?"

[1496] The generative AI model then responds to this prompt by generating multiple pieces of energy-saving advice, such as "switch to eco-friendly appliances to reduce your electricity bill" or "cancel your magazine subscription."

[1497] Example 2: Insurance consultation prompt

[1498] Example insurance consultation prompt: "What is the best life insurance plan for me?"

[1499] The generative AI model proposes cost-effective life insurance plans based on the user's age, income, family structure, etc. For example, it will suggest specific plans such as "a comprehensive plan that covers the entire family for a user in their 30s with a family."

[1500] In this way, the present invention allows users to easily receive highly accurate financial advice and, if necessary, receive detailed support from human experts. Specific proposals are generated for various usage scenarios, allowing users to efficiently manage their financial affairs in an optimal manner.

[1501] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1502] Step 1:

[1503] A user accesses the system.

[1504] Input: The user accesses the system URL from their home computer or smartphone and is redirected to the login screen.

[1505] Output: A login authentication screen is displayed.

[1506] Specific operation: The terminal prompts the user to enter their user ID and password.

[1507] Step 2:

[1508] The user performs login authentication.

[1509] Input: The user enters their user ID and password and clicks the "Login" button.

[1510] Output: The input information is sent to the server.

[1511] Specific operation: The terminal sends the entered user ID and password to the server.

[1512] Step 3:

[1513] The server performs login authentication.

[1514] Input: User ID and password sent from the device.

[1515] Output: Session information if authentication is successful, error message if authentication is unsuccessful.

[1516] Specific operation: The server checks the user ID and password against the information in the database. If authentication is successful, it generates session information and returns it to the terminal. If authentication fails, it returns an error message.

[1517] Step 4:

[1518] The user enters basic information.

[1519] Input: The user enters name, age, income, fixed expenses, family composition, etc.

[1520] Output: Basic information input data.

[1521] Specific operation: After successful authentication, the terminal displays a basic information input form, and the user enters the required information in each field.

[1522] Step 5:

[1523] The terminal checks the format of the data.

[1524] Input: Basic information entered by the user.

[1525] Output: Format check result.

[1526] What happens: The terminal checks whether the entered data is in the correct format and detects errors, for example, whether the age is a number.

[1527] Step 6:

[1528] The device sends the verified data to the server.

[1529] Input: Basic information data with formatting checked.

[1530] Output: Sending data to the server.

[1531] Specific operation: The terminal sends the data to the server after checking the format.

[1532] Step 7:

[1533] The server receives and analyzes the data.

[1534] Input: Basic information data sent from the device.

[1535] Output: Save to database.

[1536] What happens: The server parses the data it receives, converts it into a structured format, and then stores it in a database.

[1537] Step 8:

[1538] The server passes the data to the generative AI model.

[1539] Input: Basic information data stored in the database.

[1540] Output: Passing data to a generative AI model.

[1541] Specific operation: The server transmits the stored data to the generative AI model.

[1542] Step 9:

[1543] A generative AI model analyzes the data and generates suggestions.

[1544] Input: Basic information data passed to the generative AI model.

[1545] Output: Household plan and insurance proposals.

[1546] Specific operation: The generative AI model analyzes basic information and generates points to review for household finances and optimal insurance plans.

[1547] Step 10:

[1548] The server sends the generated proposal to the terminal.

[1549] Input: Proposals generated from a generative AI model.

[1550] Output: Sends the proposal data to the user's device.

[1551] Specific operation: The server sends the generated proposal to the user's device.

[1552] Step 11:

[1553] The device will display suggestions.

[1554] Input: Proposal data sent by the server.

[1555] Output: Display of proposal.

[1556] Specific operation: The device displays household plans and insurance proposals suitable for the user on the screen.

[1557] Step 12:

[1558] The user enters a detailed question.

[1559] Input: Detailed questions or customization requests for the proposal.

[1560] Output: Question data.

[1561] Specific operation: The user enters a detailed question about the proposal, and the device sends it to the server.

[1562] Step 13:

[1563] The server generates questions and asks them to AI models or human experts.

[1564] Input: Question data from the user.

[1565] Output: Response data.

[1566] What it does: The server passes the user's question to a generative AI model or human expert to generate an appropriate answer.

[1567] Step 14:

[1568] The server generates a response and sends it back to the terminal.

[1569] Input: Answer data from a generative AI model or human experts.

[1570] Output: Send the answer data to the user's device.

[1571] Specific operation: The server sends the generated answer to the user's terminal.

[1572] Step 15:

[1573] The device will display a detailed response.

[1574] Input: The response data sent from the server.

[1575] Output: Show detailed answer.

[1576] Specific Actions: The device displays a detailed answer to the user.

[1577] Step 16:

[1578] The server will hand over to the expert.

[1579] Input: Advanced or specialized question data.

[1580] Output: Expert handover notification and data sharing.

[1581] Specific operation: If the server determines that the user's question is advanced, it notifies a human expert and shares the necessary data.

[1582] (Application example 1)

[1583] 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."

[1584] Conventional household finance consultation systems only required users to input household finance-related information and receive AI analysis results, which limited user interaction and resulted in an insufficient consultation experience. Furthermore, when providing specific advice, it was difficult to provide real-time feedback, making it difficult for users to receive prompt and appropriate suggestions.

[1585] Furthermore, when users seek financial advice from home, the environment is limited, and the consultation process with the expert may not proceed smoothly.

[1586] 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.

[1587] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on a generative AI model to generate a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's information terminal; a means for generating answers to the user's detailed questions based on the generative AI model or a human expert and returning them to the user's information terminal; a means for displaying the household budget plan in a virtual environment using augmented reality; and a natural language processing means for voice interaction with the user. This allows the user to receive prompt and appropriate proposals in real time during a household budget consultation from the comfort of their own home. Furthermore, combining augmented reality technology with natural language processing improves interaction with the user and allows for more specific and friendly advice to be provided.

[1588] The "means for the user to input basic information" is an interface that allows the user to input basic information about the household, such as name, age, income, fixed expenses, and family composition.

[1589] "Means for sending input data to a server" refers to a mechanism for transferring basic information input by a user to a remote server via a network.

[1590] "Means for analyzing received data based on a generation AI model and generating a household plan or insurance proposal" refers to the process of analyzing data sent by a user using AI technology and generating an optimal household plan or insurance proposal.

[1591] "Means for returning and displaying the generated proposals to the user's information terminal" refers to a mechanism for sending household plans and insurance proposals generated by AI to the device used by the user and displaying them visually.

[1592] "Means for generating answers to detailed user questions using a generative AI model or a human expert and sending them back to the user's information device" refers to the process by which an AI or expert creates an answer to a detailed user question and sends that answer to the user's device.

[1593] "Means for displaying a household plan in a virtual environment using augmented reality" refers to a mechanism that uses AR technology to visually overlay a household plan on the user's real-world environment.

[1594] "Natural language processing means for voice interaction with a user" is a system that includes technology for understanding a user's voice input and generating an appropriate response.

[1595] "Means for format validation and error detection" refers to a mechanism that has a validation process to ensure that data entered by the user conforms to a predetermined format and has the ability to detect incorrect input.

[1596] "Means for a human expert to finalize the analysis results of the generated AI model and contact the user as necessary" refers to a process in which experts review the analysis results generated by AI and, if necessary, provide direct feedback to the user.

[1597] "Means for managing the database used by the AI ​​model" refers to a system for storing data necessary for AI analysis and maintaining and operating the database that manages it.

[1598] "Natural language processing means for voice interaction" is a system that uses technology to analyze a user's voice input, understand the content of the question, and automatically generate an appropriate response.

[1599] This invention is a system that allows users to receive financial advice from the comfort of their own home, and is composed of the following elements: A device such as a smartphone, smart glasses, or head-mounted display is used as a means for users to input basic information. This device provides an interface for users to input basic information about their household finances, such as name, age, income, fixed expenses, and family composition.

[1600] The data entered by the user is sent via a network to a remote server. The server analyzes the received data based on a generative AI model and generates a household plan or insurance proposal. The generative AI model is an analysis system that uses machine learning algorithms and is built into the server.

[1601] The generated proposals are then sent back to the user's information device and displayed visually. In this process, the AI ​​model generates household plans and proposals for the user in real time. Answers to detailed questions from the user are also generated by the AI ​​model or human experts and sent back to the user's information device.

[1602] The system includes a means to display a household plan in a virtual environment using augmented reality (AR) technology. Users can visually experience a virtual household planner in their living room or other location using smart glasses or a head-mounted display. The system also uses voice recognition and natural language processing technology to interact with the user, allowing them to input household information and ask questions by voice.

[1603] As a specific example, there is a scenario in which a user can say, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people," and the system will collect basic information and perform analysis. The user's voice input is converted into text using the Google Speech-to-Text API, and the Google Natural Language API is used for natural language processing.

[1604] If a user wants to ask a more detailed question about the proposed household budget plan, for example, they can say, "How can I revise my household budget plan?" This question is also analyzed using natural language processing, and a generative AI model or expert generates an answer. This answer is also displayed on the information terminal, providing visual and audio feedback.

[1605] An example of a prompt is as follows:

[1606] Please enter household information such as the user's name, age, income, fixed expenses, and family composition. For example, please enter something like, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people."

[1607] In this way, users can use an interactive household finance consultation system that combines augmented reality technology and natural language processing from the comfort of their own home. This invention enables users to receive prompt and accurate household finance advice, which is expected to improve their quality of life.

[1608] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1609] Step 1:

[1610] The user enters basic information.

[1611] Users launch the household finance advisor app using their smartphone, smart glasses, or head-mounted display, and an input screen appears, prompting them to enter basic information such as their name, age, income, fixed expenses, and family composition by voice or text.

[1612] Input: User's household information

[1613] Output: Input household information data

[1614] Step 2:

[1615] The terminal transmits the input data to the server.

[1616] The terminal checks the format of the household information entered by the user and performs error detection before transmitting the data to a remote server via a network.

[1617] Input: Entered household information data

[1618] Output: Household information data sent to the server

[1619] Step 3:

[1620] The server analyzes the data using the generative AI model.

[1621] The server analyzes the received data based on the generative AI model and generates a household plan or insurance proposal, using machine learning algorithms to evaluate the user's household situation and make optimal proposals.

[1622] Input: Household information data sent to the server

[1623] Output: A household budget or insurance proposal from a generative AI model

[1624] Step 4:

[1625] The server sends the generated proposal back to the user's terminal.

[1626] The household plan and insurance proposals generated by the server are sent back to the user's terminal via the network.

[1627] Input: household budget or insurance proposals from a generative AI model

[1628] Output: Proposal data returned to the user device

[1629] Step 5:

[1630] The terminal displays the suggestions to the user.

[1631] The device visually displays the returned household plan or insurance proposal and presents it to the user in an easy-to-view format, where the household plan is displayed in a virtual environment using augmented reality (AR) technology.

[1632] Input: Returned proposal data

[1633] Output: A household plan or insurance proposal displayed to the user

[1634] Step 6:

[1635] The user enters a detailed question.

[1636] The user can then enter additional or detailed questions about the suggestions by voice or text.

[1637] Input: Detailed question from user

[1638] Output: Question data entered

[1639] Step 7:

[1640] The terminal transmits the question data to the server.

[1641] The terminal sends detailed questions from the user to the server.

[1642] Input: The entered question data

[1643] Output: The query data sent to the server

[1644] Step 8:

[1645] The server asks questions to generative AI models or human experts and generates answers.

[1646] The server analyzes the user's detailed question and generates an answer relying on generative AI models or human experts.

[1647] Input: Query data sent to the server

[1648] Output: Generated response data

[1649] Step 9:

[1650] The server sends the generated answer back to the user's terminal.

[1651] The generated answer is sent back to the user's terminal via the network.

[1652] Input: Generated response data

[1653] Output: Answer data returned to the user's device

[1654] Step 10:

[1655] The terminal displays the answer to the user.

[1656] The terminal visually displays the returned answer data and provides the user with audio or text feedback.

[1657] Input: Returned response data

[1658] Output: The answer displayed to the user

[1659] 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.

[1660] This invention is a financial advice system that utilizes AI and an emotion engine to provide more accurate and emotionally sensitive advice to users when they seek financial advice. Below, we explain the program processing of this system in natural language. We also provide a user usage scenario with concrete examples.

[1661] Overall system overview

[1662] This household financial consultation system mainly consists of the following elements:

[1663] 1. Terminal

[1664] 2. Server

[1665] 3. AI Model

[1666] 4. Emotion Engine

[1667] 5. Human Experts

[1668] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and the emotion engine recognizing the user's emotional state, with human experts providing support as needed.

[1669] Program processing flow

[1670] The specific processing flow of the system is as follows:

[1671] 1. The user starts a financial consultation

[1672] A user accesses an online or in-store terminal and arrives at the login screen.

[1673] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[1674] The terminal transmits the user's input information to the server for authentication.

[1675] 2. Enter your user information

[1676] The terminal displays a basic information input form to the user.

[1677] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[1678] The terminal checks the format of the entered data and checks for input errors.

[1679] 3. Sending input data

[1680] The terminal transmits the data whose format has been confirmed to the server.

[1681] The server analyzes the received data and stores it in a database.

[1682] 4. Analysis using AI models

[1683] The server passes the stored data to the AI ​​model.

[1684] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[1685] 5. Emotion Recognition by Emotion Engine

[1686] The terminal activates an emotion engine during interaction with the user to recognize the user's emotional state.

[1687] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate their emotional state.

[1688] 6. Customize your suggestions

[1689] The emotional state recognized by the emotion engine is sent to the server.

[1690] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[1691] The server sends the customized offer to the user's terminal.

[1692] 7. Display of Suggestions

[1693] The device displays household plans and insurance proposals that are suitable for the user.

[1694] The user enters detailed questions and customization requests for the displayed plan.

[1695] 8. Response to detailed questions

[1696] The terminal transmits the user's questions and requests to the server.

[1697] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[1698] 9. Generating and Displaying Answers

[1699] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[1700] The server sends the generated answer to the user's terminal.

[1701] The terminal displays the detailed answer to the user.

[1702] 10. Handover to an expert

[1703] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[1704] The server notifies the experts and shares the user's data.

[1705] A human expert will contact the user for a detailed consultation.

[1706] Specific examples

[1707] Example: Maria is discussing her financial plan.

[1708] 1. Maria starts financial counseling

[1709] Maria accesses the system online from her home computer and reaches the login screen.

[1710] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[1711] The terminal transmits Maria's input information to the server for authentication.

[1712] 2. Enter your user information

[1713] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[1714] The terminal checks the format of the entered data and checks for input errors.

[1715] 3. Sending input data

[1716] The terminal transmits the verified data to the server.

[1717] The server receives and analyzes the data and then stores it in a database.

[1718] 4. Analysis using AI models

[1719] The server passes the stored data to the AI ​​model.

[1720] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[1721] 5. Emotion Recognition by Emotion Engine

[1722] The device activates an emotion engine during interaction with Maria to recognize her emotional state.

[1723] The emotion engine analyzes Maria's facial expressions, voice, and text data to assess her emotional state.

[1724] 6. Customize your suggestions

[1725] The emotional state recognized by the emotion engine is sent to the server.

[1726] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[1727] The server sends the customized offer to Maria's terminal.

[1728] 7. Display of Suggestions

[1729] The device displays the suggestions to Maria and provides appropriate advice that takes her emotions into consideration.

[1730] 8. Response to detailed questions

[1731] Maria enters detailed questions and customization requests for the displayed plan.

[1732] The device sends these questions to a server, which then asks an AI model or a human expert.

[1733] 9. Generating and Displaying Answers

[1734] An AI model or human expert generates answers to Maria's questions and sends them back to the server.

[1735] The server sends the generated response to Maria's terminal.

[1736] The terminal displays a detailed response to Maria.

[1737] 10. Handover to an expert

[1738] The server determines that Maria's question is advanced and hands it over to a human expert.

[1739] The expert will contact Maria and provide further advice.

[1740] In this way, this invention allows users to use a household finance consultation service that also takes their emotional state into consideration. In addition to fast and appropriate suggestions from AI, the emotion engine recognizes the user's emotional state and human experts provide support as needed, making it possible to provide a highly reliable service to users.

[1741] The processing flow will be explained below.

[1742] Step 1:

[1743] A user accesses an online or in-store terminal and arrives at the login screen.

[1744] The terminal displays a login authentication screen to the user.

[1745] The user enters the user ID and password and clicks the login button.

[1746] Step 2:

[1747] The terminal sends the user's login information to the server.

[1748] The server receives the login information and authenticates it against a database.

[1749] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[1750] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[1751] Step 3:

[1752] The terminal displays a basic information input form to the user.

[1753] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[1754] Step 4:

[1755] The terminal checks the format of the input data.

[1756] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[1757] Step 5:

[1758] The server analyzes the received data and stores it in a database.

[1759] Step 6:

[1760] The server passes the stored data to the AI ​​model.

[1761] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[1762] Step 7:

[1763] The terminal activates the emotion engine during interaction with the user.

[1764] The emotion engine analyzes the user's facial expressions, voice, and text data to assess their emotional state.

[1765] Step 8:

[1766] The emotion engine transmits the recognized emotional state to the server.

[1767] The server uses this emotional data to customize the suggestions generated by the AI ​​model.

[1768] Step 9:

[1769] The server sends the customized offer to the user's terminal.

[1770] The terminal displays the suggestions to the user.

[1771] Step 10:

[1772] The user then inputs detailed questions and customization requests in response to the displayed suggestions.

[1773] The terminal sends these questions and requests to the server.

[1774] Step 11:

[1775] The server receives detailed questions or requests and refers them to an AI model or a human expert.

[1776] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[1777] Step 12:

[1778] The server sends the generated answer to the user's terminal.

[1779] The terminal displays the detailed answer to the user.

[1780] Step 13:

[1781] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[1782] The server notifies the experts and shares the user's data.

[1783] A human expert will contact the user for further consultation.

[1784] The above is the flow of specific processing steps in the household finance consultation system.

[1785] Example 2

[1786] 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."

[1787] Conventional financial consultation systems make suggestions based on basic user information, but they fail to consider the user's emotional state and often make one-sided suggestions, making it difficult for users to achieve satisfactory results. Furthermore, input data formatting and error checking are often insufficient, resulting in incorrect information being sent to the system. Furthermore, when answers to detailed questions are automatically generated, they often lack professional judgment.

[1788] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's terminal; a means for recognizing an emotional state during interaction with the user; a means for customizing the proposal content based on the recognized emotional state; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's terminal; a means for checking the data format and performing error checks; and a means for a human expert to finally check the AI ​​analysis results and contact the user as necessary. This enables the provision of an accurate household budget plan that reflects the user's emotional state, high reliability of input data, and response to detailed questions from a professional perspective.

[1789] "User" refers to a person who uses the system to receive financial advice.

[1790] "Terminal" refers to an electronic device (PC, smartphone, tablet, etc.) that a user uses to access and use the system.

[1791] "Server" refers to the central computer device that manages the entire system and performs processes such as data storage, analysis, and proposal generation.

[1792] "Artificial intelligence model" refers to the algorithms and machine learning models that analyze user data and generate household plans and insurance proposals.

[1793] An "emotion engine" refers to a system that recognizes a user's emotional state from data collected during interactions with the user and customizes suggestions based on the results.

[1794] A "household plan" refers to a financial plan created taking into account the user's income, expenses, family composition, etc.

[1795] "Insurance proposal" refers to information that suggests the most suitable insurance plan based on the user's household data, etc.

[1796] "Interaction" refers to the dialogue and exchange of information between a user and a system.

[1797] "Error checking" refers to the process of checking and correcting input data for errors.

[1798] This invention is a financial advice system that provides users with more accurate and emotionally sensitive advice when they seek financial advice. The system collects basic information about the user and generates financial plans and insurance proposals using an artificial intelligence model and an emotion engine. Furthermore, the system recognizes the user's emotional state and customizes proposals based on that state. A specific embodiment of the system is described below.

[1799] The system mainly consists of the following elements:

[1800] 1. Terminal

[1801] This refers to devices that users use to access systems, such as PCs, smartphones, and tablets. Examples include Apple's MacBook, Microsoft's Surface, and Google's Pixel.

[1802] 2. Server

[1803] This refers to the central computer device that manages the entire system and stores data, analyzes it, and generates proposals. It can be a general cloud server, such as an EC2 instance from Amazon Web Services (AWS) or a Compute Engine from Google Cloud Platform (GCP).

[1804] 3. Artificial Intelligence Model

[1805] This refers to algorithms and machine learning models that analyze user data and generate household plans and insurance proposals. Examples include OpenAI's GPT-3 and BERT.

[1806] 4. Emotion Engine

[1807] This refers to systems that recognize a user's emotional state from data collected during user interactions and customize suggestions based on the results. Examples include Affectiva and Microsoft's Emotion API.

[1808] 5. Human Experts

[1809] This refers to financial planners and insurance advisors who, if necessary, provide final confirmation of the analysis results of the AI ​​model and contact users directly.

[1810] Specific examples

[1811] In a scenario where a user is consulting about a household budget, the system operates in the following steps.

[1812] 1. The user starts a financial consultation

[1813] A user accesses the system from their home PC and reaches the login screen. The terminal displays the login authentication screen, and the user logs in by entering their user ID and password. This information is sent from the terminal to the server and authenticated.

[1814] 2. Enter your user information

[1815] The terminal displays a basic information input form, and the user inputs name, age, income, fixed expenses, family composition, etc. The terminal checks the format of the input data and performs error checks.

[1816] 3. Analysis of input data

[1817] The server receives the data after checking the format and stores it in a database. The stored data is then passed to an AI model, which analyzes the user's data and generates budget adjustments and optimal insurance plans.

[1818] 4. Emotion Recognition and Customized Suggestions

[1819] The device activates an emotion engine during interaction with the user to recognize the user's emotional state. The emotion engine then sends the recognized emotional data to the server, which then customizes suggestions based on this data. As a result, the device provides appropriate advice that takes the user's emotions into consideration.

[1820] Prompt Sentence Examples

[1821] Below is an example of a prompt sentence to input to the generative AI model.

[1822] "The user is 30 years old and earns 300,000 yen a month. I have entered detailed information about my monthly fixed expenses and family structure. Please suggest the best household budget plan for this user."

[1823] The detailed operation of this system allows users to receive accurate and prompt financial advice that takes their emotions into consideration. Each element works in tandem to provide a highly reliable service to users.

[1824] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1825] Step 1:

[1826] User starts household finance consultation

[1827] A user accesses the system using a PC or smartphone and reaches the login screen.

[1828] Input: User ID, Password

[1829] The terminal displays a login authentication screen, and the user enters their user ID and password.

[1830] Output: Authentication result

[1831] The device sends the entered authentication information to the server. The server verifies the authentication information and checks whether the user is registered. If authentication is successful, the device displays the home screen to proceed to the next step.

[1832] Step 2:

[1833] Entering user information

[1834] The terminal displays a basic information input form to the user.

[1835] Input: Basic information such as name, age, income, fixed expenses, family composition, etc.

[1836] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[1837] Output: Basic information entered

[1838] The terminal checks the format of the entered data and ensures that all required fields are filled in. If there is a problem with the format, the terminal displays an error message and prompts the user to re-enter the data.

[1839] Step 3:

[1840] Sending input data

[1841] The terminal transmits the data after format confirmation to the server.

[1842] Input: Verified data

[1843] The server analyzes the received data and stores it in a database.

[1844] Output: Save results to database

[1845] The server returns a confirmation of data storage to the terminal and instructs it to proceed to the next step.

[1846] Step 4:

[1847] Analysis using AI models

[1848] The server passes the stored user data to an artificial intelligence model.

[1849] Input: Saved user data

[1850] The artificial intelligence model generates budget review points and optimal insurance plans based on data such as the user's income, expenses, and family composition.

[1851] Output: Household budget plan and insurance proposals

[1852] The AI ​​model generates a proposal that is sent back to the server, which uses it in the next step.

[1853] Step 5:

[1854] Emotion recognition by emotion engine

[1855] The terminal activates the emotion engine during interaction with the user.

[1856] Input: User's facial expressions, voice, and text data

[1857] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate the user's emotional state.

[1858] Output: Emotional evaluation data

[1859] The evaluated emotion data is sent to the server via the terminal.

[1860] Step 6:

[1861] Customize suggestions

[1862] The server customizes the suggestions generated by the artificial intelligence model based on the emotional data received from the emotion engine.

[1863] Input: Emotion data, suggested data from AI model

[1864] The server adjusts the content of the suggestions appropriately depending on the user's emotional state, and constructs the most appropriate advice for the user.

[1865] Output: Customized proposal

[1866] Send customized offers to your device.

[1867] Step 7:

[1868] View Suggestions

[1869] The device displays customized household plans and insurance offers to the user.

[1870] Input:Customized Proposal

[1871] Output: Displayed proposal

[1872] Users can then enter detailed questions and customization requests for the plans displayed, allowing them to receive advice that best suits their situation.

[1873] Step 8:

[1874] Response to detailed questions

[1875] The terminal sends user questions and requests to the server.

[1876] Input: User questions or requests

[1877] Based on the question, the server asks an AI model or a human expert to respond to the question.

[1878] Output: Request details

[1879] This allows for appropriate answers to be prepared for detailed questions from the user.

[1880] Step 9:

[1881] Generate and display answers

[1882] An artificial intelligence model or human expert generates answers to the user's questions and sends them back to the server.

[1883] Input: Question response request, expert answer

[1884] Output: The generated answer

[1885] The server sends the generated answer to the user's device, which displays the detailed answer to the user, allowing the user to resolve their question and obtain further information.

[1886] Step 10:

[1887] Handover to experts

[1888] If the server determines that the user's question is difficult, it will hand it off to a human expert.

[1889] Input: User question, expert handover instructions

[1890] Output: Handover notification to expert

[1891] The server notifies the expert and shares the user's data, and the human expert contacts the user for a detailed consultation, allowing the user to receive further expert advice.

[1892] (Application example 2)

[1893] 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."

[1894] Conventional household budget consultation systems provide analysis results and advice without considering the user's emotions, making it difficult to reduce the user's psychological burden and stress. In addition, centralized management of expenditure data was insufficient, making it difficult to provide appropriate advice that takes emotions into consideration in real time.

[1895] 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.

[1896] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's device; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's device; an emotion recognition means for analyzing the user's facial expressions and voice using the device's built-in camera and microphone to recognize the user's emotional state; a means for adjusting the proposal content based on the emotional state; a means for transmitting emotion-sensitive notifications and advice to the user's device; a format verification and error detection means; a means for inputting and analyzing the user's expenditure data and providing a household budget improvement plan that takes the user's emotional state into account; and a means for managing the generative AI model and emotion engine to provide advice and plans based on the user's emotional state. This allows for the provision of appropriate advice that takes the user's emotions into account, improving the efficiency of household budget management and reducing the user's psychological burden.

[1897] "Basic information" refers to personal information necessary for financial consultation, such as the user's name, age, income, fixed expenses, and family composition.

[1898] "Server" refers to a device that receives data entered by a user, analyzes it, and returns the results to the user.

[1899] "AI model" refers to an algorithm that uses machine learning technology to generate household budget review points and insurance proposals.

[1900] "Emotion recognition means" refers to a device that uses a camera and microphone to analyze the user's facial expressions and voice and evaluate their emotional state.

[1901] "Emotional state" refers to the psychological state obtained from the user's facial expressions, voice, and text data.

[1902] "Proposal content" refers to advice and plans generated by the AI ​​model, such as points to review in household finances and insurance proposals.

[1903] "Notifications and advice" refers to information about improving household finances and notifications encouraging specific actions that are sent to the user's device.

[1904] "Terminal" refers to the device on which the user inputs information and receives and displays suggestions from the server.

[1905] "Format checking and error detection means" refers to a function that checks whether there are any errors in the format or content of the data entered by the user.

[1906] "Input and analysis of expenditure data" refers to the function that allows users to input daily expenditure amounts and breakdowns and analyze them.

[1907] "Finance Improvement Plan" refers to savings and investment plans created based on the user's spending data and emotional state.

[1908] A "generative AI model" refers to an algorithm that uses AI technology to generate suggestions suited to a user's financial situation and emotional state.

[1909] An "emotion engine" refers to software that assesses a user's emotional state and adjusts suggestions accordingly.

[1910] MODE FOR CARRYING OUT THE INVENTION

[1911] System configuration overview

[1912] This invention is a system that provides financial advice to users while they manage their daily expenses. The system aims to provide advice that takes into account the user's emotional state. The main components of the system include a terminal, a server, an AI model, and an emotion engine.

[1913] Hardware and software used

[1914] Hardware: Smartphone (built-in camera, microphone)

[1915] Software: TensorFlow, Emotion API, Expense Database

[1916] Program processing

[1917] overview

[1918] The server performs the following processes: It analyzes the expenditure data entered by the user and generates a household budget plan and insurance proposals based on that data. It also recognizes the user's emotional state in real time using a camera and microphone and provides advice that takes their emotions into consideration. It also responds to detailed questions from the user and provides appropriate feedback tailored to the user's emotions.

[1919] The server operates as follows:

[1920] 1. Data Acquisition

[1921] Users enter basic information and expenditure data into their smartphones and send it to the server, which receives the data and stores it in a database.

[1922] 2. Data analysis and proposal generation

[1923] The saved data is passed to an AI model that generates budget review points and insurance proposals. The AI ​​model uses TensorFlow to calculate optimal advice based on past data and statistical information.

[1924] 3. Recognizing emotional states

[1925] It uses the smartphone's camera and microphone to analyze the user's facial expressions and voice in real time, and uses the Emotion API to evaluate the user's emotional state at that time.

[1926] 4. Adjusting the proposal

[1927] The emotion engine analyzes the user's emotional state and customizes the generated household budget plan and advice based on that. For example, if the user is feeling stressed, it will prioritize specific and easy-to-implement plans.

[1928] 5. Sending Notices and Advice

[1929] The adjusted suggestions are sent to the user via push notifications on their smartphone, etc. The notification content takes into consideration emotions and provides advice in gentle language.

[1930] Specific scenarios

[1931] Situation: User enters expenditure data and conducts financial consultation

[1932] 1. Entering expenditure data

[1933] User: Enters "My recent expenses are 5,000 yen" into the app.

[1934] 2. Recognizing emotional states

[1935] The app's camera captures the user's facial expression and recognizes that they are confused.

[1936] 3. Proposal generation and refinement

[1937] The AI ​​model analyzes users' spending patterns and identifies points where they should adjust their finances, while the Emotion API notifies the server when a user is under stress.

[1938] 4. Submitting Advice

[1939] The server sends emotion-sensitive suggestions to the smartphone and notifies the user.

[1940] "It seems like you haven't been managing your expenses well lately. I'd like to suggest some easy and simple ways to save money. How about setting aside some time on the weekends to relax with your family and do your hobbies?"

[1941] The above is an embodiment of the invention.

[1942] Prompt Sentence Examples

[1943] Below is an example of a prompt that an application might pass to a generative AI model.

[1944] A user enters their recent spending data. The camera detects a confused state in their facial expression. Reflect their emotional state, provide situational financial improvement advice, and suggest emotionally sensitive recommendations.

[1945] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1946] Step 1:

[1947] The user enters basic information and expenditure data into their smartphone device and sends it to the server.

[1948] Input: The user enters basic information such as "name, age, income, fixed expenses, family composition" and "expense data" into the app.

[1949] Output: The app sends input data and the server receives it.

[1950] Specific operation: The user presses the submit button on the smartphone app to submit the information entered in the form. The server receives this information and stores it in the database.

[1951] Step 2:

[1952] The server stores the received data and passes it to the AI ​​model.

[1953] Input: Basic information and spending data sent from your device.

[1954] Output: Stored data and input to the AI ​​model.

[1955] What it does: The server immediately stores the received data in a database and prepares it to be passed to the AI ​​model for analysis.

[1956] Step 3:

[1957] The AI ​​model analyzes the stored spending data and generates household plans and insurance proposals.

[1958] Input: User spending data retrieved from the database.

[1959] Output: Generation of household plans and insurance proposals.

[1960] How it works: An AI model (powered by TensorFlow) pulls user data from a database, compares it with statistics and historical data, and generates appropriate financial plans and insurance proposals.

[1961] Step 4:

[1962] Using the smartphone's camera and microphone, the system analyzes the user's facial expressions and voice to recognize their emotional state.

[1963] Input: User's facial expression data captured by the smartphone camera and voice data captured by the microphone.

[1964] Output: Evaluation of the user's emotional state.

[1965] Specific operation: The device sends the user's facial expressions and voice to the Emotion API in real time for emotion recognition, and the emotional state is sent to the server.

[1966] Step 5:

[1967] The emotion engine adjusts the suggestions based on the emotional state it recognizes.

[1968] Input: Emotional state data from emotion recognition instruments, and financial plan and insurance proposal data from AI models.

[1969] Output: Emotionally sensitive household budget plans and insurance proposals.

[1970] How it works: The server adjusts the generated household plan based on the data obtained from the emotion engine. For example, it will prioritize plans that are easy to implement for users who are under stress.

[1971] Step 6:

[1972] The user is notified of emotionally sensitive suggestions via their device.

[1973] Input: Tailored household plans and insurance proposals.

[1974] Output: The suggestions displayed on the user's smartphone.

[1975] Specific operation: The server sends the adjusted proposal to the user's device and notifies them via push notification or on-screen display.

[1976] Step 7:

[1977] The user inputs detailed questions and feedback about the generated plan and sends them to the server.

[1978] Input: Questions or feedback that users enter into the app.

[1979] Output: Detailed question and feedback sent to the server.

[1980] Specific operation: The user reviews the proposal, enters questions or feedback through the app interface, and presses the send button to send it to the server.

[1981] Step 8:

[1982] The server generates answers based on detailed questions, either through AI models or human experts.

[1983] Input: User's detailed question.

[1984] Output: The generated answer.

[1985] What it does: The server passes the user's question to an AI model or designated expert to generate an answer, which is then sent back to the server.

[1986] Step 9:

[1987] The generated answer is returned to the user's terminal and displayed.

[1988] Input: The generated answer.

[1989] Output: The answer displayed on the user's device.

[1990] Specific behavior: The server sends the generated answer to the user's device, and the app displays the answer.

[1991] Step 10:

[1992] If the server determines that the user's question is more advanced, it hands it off to a human expert.

[1993] Input: User's advanced question.

[1994] Output: Detailed answers from experts.

[1995] What it does: The server evaluates the question and, if it determines that the question is advanced, notifies an expert and shares the user's data. The expert then contacts the user directly and provides detailed advice.

[1996] The above is the specific processing flow of the system that realizes the application example.

[1997] 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.

[1998] 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.

[1999] 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.

[2000] [Fourth embodiment]

[2001] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2002] 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.

[2003] 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).

[2004] 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.

[2005] 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.

[2006] 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).

[2007] 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.

[2008] 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.

[2009] 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.

[2010] 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.

[2011] 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.

[2012] 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.

[2013] 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."

[2014] This invention is a financial consultation system that uses AI to provide prompt and appropriate advice when users seek financial advice. The program processing of this system is explained in natural language below. A user usage scenario is also shown with specific examples.

[2015] Overall system overview

[2016] This household financial consultation system mainly consists of the following elements:

[2017] 1. Terminal

[2018] 2. Server

[2019] 3. AI Model

[2020] 4. Human Experts

[2021] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and human experts providing support as needed.

[2022] Program processing flow

[2023] The specific processing flow of the system is as follows:

[2024] 1. The user starts a financial consultation

[2025] The user accesses an online or in-store terminal and is taken to the login screen.

[2026] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[2027] The terminal transmits the user's input information to the server for authentication.

[2028] 2. Enter your user information

[2029] The terminal displays a basic information input form to the user.

[2030] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[2031] The terminal checks the format of the entered data and checks for input errors.

[2032] 3. Sending input data

[2033] The terminal transmits the data whose format has been confirmed to the server.

[2034] The server analyzes the received data and stores it in a database.

[2035] 4. Analysis using AI models

[2036] The server passes the stored data to the AI ​​model.

[2037] The AI ​​model analyzes the received data and generates optimal household budget review points and insurance plans.

[2038] The AI ​​model sends the generated suggestions back to the server.

[2039] 5. Display of Suggestions

[2040] The server sends the suggestions received from the AI ​​model to the user's device.

[2041] The terminal displays household plans and insurance proposals suitable for the user.

[2042] 6. Response to detailed questions

[2043] The user enters detailed questions and customization requests regarding the proposed content.

[2044] The terminal sends these detailed questions to the server.

[2045] The server asks questions to AI or human experts and generates answers.

[2046] The server returns the generated answer to the user's terminal.

[2047] The terminal displays the detailed answer to the user.

[2048] 7. Handover to experts

[2049] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[2050] The server notifies the experts and shares the user's data.

[2051] A human expert will contact the user for a detailed consultation.

[2052] Specific examples

[2053] Example: Maria is discussing her financial plan.

[2054] 1. Maria starts financial counseling

[2055] Maria accesses the system online from her home computer and is taken to the login screen.

[2056] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[2057] The terminal transmits Maria's input information to the server for authentication.

[2058] 2. Enter your user information

[2059] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[2060] The terminal checks the format of the entered data and checks for input errors.

[2061] 3. Sending input data

[2062] The terminal transmits the verified data to the server.

[2063] The server receives and analyzes the data and then stores it in a database.

[2064] 4. Analysis using AI models

[2065] The server passes the stored data to the AI ​​model.

[2066] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[2067] The AI ​​model sends the generated suggestions back to the server.

[2068] 5. Display of Suggestions

[2069] The server sends the suggestions received from the AI ​​model to Maria's device.

[2070] The terminal displays the proposal to Maria.

[2071] 6. Response to detailed questions

[2072] Maria enters detailed questions about the proposal and requests further customization.

[2073] The device then sends the question to a server and asks either an AI or human expert for an answer.

[2074] The server generates a response and sends it back to Maria's terminal.

[2075] The terminal presents Maria with a detailed response.

[2076] 7. Handover to experts

[2077] The server determines that Maria's question is advanced and hands it over to a human expert.

[2078] The expert will contact Maria and provide further advice.

[2079] In this way, this invention allows users to use the household finance consultation service without any psychological hesitation and receive prompt and appropriate suggestions from AI. Furthermore, since human experts are available to provide support as needed, it is possible to provide a highly reliable service to users.

[2080] The processing flow will be explained below.

[2081] Step 1:

[2082] A user accesses an online or in-store terminal and arrives at the login screen.

[2083] The terminal displays a login authentication screen to the user.

[2084] The user enters the user ID and password and clicks the login button.

[2085] Step 2:

[2086] The terminal sends the user's login information to the server.

[2087] The server receives the login information and authenticates it against a database.

[2088] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[2089] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[2090] Step 3:

[2091] The terminal displays a basic information input form to the user.

[2092] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[2093] Step 4:

[2094] The terminal checks the format of the input data.

[2095] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[2096] Step 5:

[2097] The server analyzes the received data and stores it in a database.

[2098] Step 6:

[2099] The server passes the stored data to the AI ​​model.

[2100] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[2101] Step 7:

[2102] The AI ​​model sends the generated suggestions back to the server.

[2103] The server sends the proposal to the user's terminal.

[2104] Step 8:

[2105] The device displays household plans and insurance proposals that are suitable for the user.

[2106] The user enters detailed questions and customization requests for the displayed plan.

[2107] Step 9:

[2108] The terminal transmits the user's questions and requests to the server.

[2109] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[2110] Step 10:

[2111] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[2112] The server sends the generated answer to the user's terminal.

[2113] Step 11:

[2114] The terminal displays the detailed answer to the user.

[2115] If the user wants further advice, the server hands over to a human expert.

[2116] A human expert will contact the user and provide detailed advice.

[2117] The above is the flow of specific processing steps in the household finance consultation system.

[2118] Example 1

[2119] 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."

[2120] Traditionally, household financial consultation services have been time-consuming and expensive, making them difficult for ordinary users to use. Furthermore, specialized knowledge is often required, making it difficult to obtain appropriate advice. Furthermore, online consultations are prone to input errors and misunderstandings, resulting in the risk of incorrect recommendations. Furthermore, analysis results using AI alone can sometimes lack reliability, requiring final confirmation by a human expert, but there has been a lack of a system for smoothly carrying out this adjustment.

[2121] 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.

[2122] In this invention, the server includes means for a user to input basic information, means for transmitting the input data, means for analyzing the received data based on a generative AI model and generating a household plan or insurance proposal, means for returning the generated proposal to the user's information processing device and displaying it, means for generating answers to the user's detailed questions using the generative AI model or a human expert and returning them to the user's information processing device, and means for handing over to a human expert if the user's question is determined to be of advanced or specialized content. This allows the user to easily receive highly accurate household consultation and, if necessary, to receive detailed support from a human expert.

[2123] "User" refers to an individual or corporation that uses this system to provide financial advice.

[2124] "Basic information" refers to information entered by the user, such as name, age, income, fixed expenses, and family composition.

[2125] "Server" refers to a computer system for receiving and processing data sent by users.

[2126] A "generative AI model" refers to an artificial intelligence model that analyzes user data to generate household plans and insurance proposals.

[2127] The term "information processing device" refers to a terminal that a user accesses to input data and view the results.

[2128] "Format validation" refers to the process of checking whether the format and content of the data entered by the user are correct.

[2129] A "detailed question" refers to a question that a user enters when they want to know more about the content of a proposal.

[2130] "Human experts" refer to experts who review the results generated by the AI ​​model and provide additional advice to users as needed.

[2131] "Database" refers to a data management system for storing and managing basic user information and AI analysis results.

[2132] "Handing over" refers to the process of transferring the response from the AI ​​model to a human expert when the user's question is deemed to be advanced or specialized.

[2133] This invention is a financial consultation system that utilizes a generative AI model to provide prompt and appropriate advice when a user seeks financial advice. This system is primarily composed of a user, a terminal, a server, a generative AI model, and a human expert. The system's processing is carried out in the following specific steps.

[2134] Hardware and Software Use

[2135] Device:

[2136] A terminal is an information processing device that allows a user to access the system, and includes a personal computer, smartphone, tablet, etc. A terminal has an input interface and a display interface.

[2137] server:

[2138] A computer system for receiving and processing data sent by users. The server manages the database and works in conjunction with the generative AI model. It is generally installed on a cloud platform (e.g., Amazon Web Services, Microsoft Azure).

[2139] Generative AI models:

[2140] It is an artificial intelligence model that analyzes user data and generates household plans and insurance proposals. It uses machine learning and deep learning libraries such as Python, TensorFlow, and Scikit-learn.

[2141] Data processing and calculation

[2142] Collecting input data:

[2143] The terminal displays a basic information input form to the user, who then enters information such as name, age, income, fixed expenses, and family composition. The input data is checked for formatting on the terminal, and if no errors are detected, it is sent to the server.

[2144] Analyzing data and generating recommendations:

[2145] The server passes the received user data to the generative AI model, which analyzes the collected data and generates recommendations for household budget revisions and optimal insurance plans. The generated proposals are then sent back to the server.

[2146] View suggestions:

[2147] The server sends the proposals received from the generative AI model to the user's device, which then displays the household plan and insurance proposals that are suitable for the user.

[2148] Response to detailed questions:

[2149] The user enters detailed questions or customization requests regarding the suggestions into the device. The device then sends the user's question data to the server. The server then asks the question to a generative AI model or a human expert and generates an answer. The generated answer is then sent back to the user's device and displayed.

[2150] Expert support:

[2151] If the server determines that the user's question is too advanced or technical, it will hand over to a human expert, who will contact the user for a detailed consultation.

[2152] Specific examples

[2153] Example 1: Financial advice prompt

[2154] Example financial advice prompt: "How can I reduce my monthly fixed expenses?"

[2155] The generative AI model then responds to this prompt by generating multiple pieces of energy-saving advice, such as "switch to eco-friendly appliances to reduce your electricity bill" or "cancel your magazine subscription."

[2156] Example 2: Insurance consultation prompt

[2157] Example insurance consultation prompt: "What is the best life insurance plan for me?"

[2158] The generative AI model proposes cost-effective life insurance plans based on the user's age, income, family structure, etc. For example, it will suggest specific plans such as "a comprehensive plan that covers the entire family for a user in their 30s with a family."

[2159] In this way, the present invention allows users to easily receive highly accurate financial advice and, if necessary, receive detailed support from human experts. Specific proposals are generated for various usage scenarios, allowing users to efficiently manage their financial affairs in an optimal manner.

[2160] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2161] Step 1:

[2162] A user accesses the system.

[2163] Input: The user accesses the system URL from their home computer or smartphone and is redirected to the login screen.

[2164] Output: A login authentication screen is displayed.

[2165] Specific operation: The terminal prompts the user to enter their user ID and password.

[2166] Step 2:

[2167] The user performs login authentication.

[2168] Input: The user enters their user ID and password and clicks the "Login" button.

[2169] Output: The input information is sent to the server.

[2170] Specific operation: The terminal sends the entered user ID and password to the server.

[2171] Step 3:

[2172] The server performs login authentication.

[2173] Input: User ID and password sent from the device.

[2174] Output: Session information if authentication is successful, error message if authentication is unsuccessful.

[2175] Specific operation: The server checks the user ID and password against the information in the database. If authentication is successful, it generates session information and returns it to the terminal. If authentication fails, it returns an error message.

[2176] Step 4:

[2177] The user enters basic information.

[2178] Input: The user enters name, age, income, fixed expenses, family composition, etc.

[2179] Output: Basic information input data.

[2180] Specific operation: After successful authentication, the terminal displays a basic information input form, and the user enters the required information in each field.

[2181] Step 5:

[2182] The terminal checks the format of the data.

[2183] Input: Basic information entered by the user.

[2184] Output: Format check result.

[2185] What happens: The terminal checks whether the entered data is in the correct format and detects errors, for example, whether the age is a number.

[2186] Step 6:

[2187] The device sends the verified data to the server.

[2188] Input: Basic information data with formatting checked.

[2189] Output: Sending data to the server.

[2190] Specific operation: The terminal sends the data to the server after checking the format.

[2191] Step 7:

[2192] The server receives and analyzes the data.

[2193] Input: Basic information data sent from the device.

[2194] Output: Save to database.

[2195] What happens: The server parses the data it receives, converts it into a structured format, and then stores it in a database.

[2196] Step 8:

[2197] The server passes the data to the generative AI model.

[2198] Input: Basic information data stored in the database.

[2199] Output: Passing data to a generative AI model.

[2200] Specific operation: The server transmits the stored data to the generative AI model.

[2201] Step 9:

[2202] A generative AI model analyzes the data and generates suggestions.

[2203] Input: Basic information data passed to the generative AI model.

[2204] Output: Household plan and insurance proposals.

[2205] Specific operation: The generative AI model analyzes basic information and generates points to review for household finances and optimal insurance plans.

[2206] Step 10:

[2207] The server sends the generated proposal to the terminal.

[2208] Input: Proposals generated from a generative AI model.

[2209] Output: Sends the proposal data to the user's device.

[2210] Specific operation: The server sends the generated proposal to the user's device.

[2211] Step 11:

[2212] The device will display suggestions.

[2213] Input: Proposal data sent by the server.

[2214] Output: Display of proposal.

[2215] Specific operation: The device displays household plans and insurance proposals suitable for the user on the screen.

[2216] Step 12:

[2217] The user enters a detailed question.

[2218] Input: Detailed questions or customization requests for the proposal.

[2219] Output: Question data.

[2220] Specific operation: The user enters a detailed question about the proposal, and the device sends it to the server.

[2221] Step 13:

[2222] The server generates questions and asks them to AI models or human experts.

[2223] Input: Question data from the user.

[2224] Output: Response data.

[2225] What it does: The server passes the user's question to a generative AI model or human expert to generate an appropriate answer.

[2226] Step 14:

[2227] The server generates a response and sends it back to the terminal.

[2228] Input: Answer data from a generative AI model or human experts.

[2229] Output: Send the answer data to the user's device.

[2230] Specific operation: The server sends the generated answer to the user's terminal.

[2231] Step 15:

[2232] The device will display a detailed response.

[2233] Input: The response data sent from the server.

[2234] Output: Show detailed answer.

[2235] Specific Actions: The device displays a detailed answer to the user.

[2236] Step 16:

[2237] The server will hand over to the expert.

[2238] Input: Advanced or specialized question data.

[2239] Output: Expert handover notification and data sharing.

[2240] Specific operation: If the server determines that the user's question is advanced, it notifies a human expert and shares the necessary data.

[2241] (Application example 1)

[2242] 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."

[2243] Conventional household finance consultation systems only required users to input household finance-related information and receive AI analysis results, which limited user interaction and resulted in an insufficient consultation experience. Furthermore, when providing specific advice, it was difficult to provide real-time feedback, making it difficult for users to receive prompt and appropriate suggestions.

[2244] Furthermore, when users seek financial advice from home, the environment is limited, and the consultation process with the expert may not proceed smoothly.

[2245] 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.

[2246] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on a generative AI model to generate a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's information terminal; a means for generating answers to the user's detailed questions based on the generative AI model or a human expert and returning them to the user's information terminal; a means for displaying the household budget plan in a virtual environment using augmented reality; and a natural language processing means for voice interaction with the user. This allows the user to receive prompt and appropriate proposals in real time during a household budget consultation from the comfort of their own home. Furthermore, combining augmented reality technology with natural language processing improves interaction with the user and allows for more specific and friendly advice to be provided.

[2247] The "means for the user to input basic information" is an interface that allows the user to input basic information about the household, such as name, age, income, fixed expenses, and family composition.

[2248] "Means for sending input data to a server" refers to a mechanism for transferring basic information input by a user to a remote server via a network.

[2249] "Means for analyzing received data based on a generation AI model and generating a household plan or insurance proposal" refers to the process of analyzing data sent by a user using AI technology and generating an optimal household plan or insurance proposal.

[2250] "Means for returning and displaying the generated proposals to the user's information terminal" refers to a mechanism for sending household plans and insurance proposals generated by AI to the device used by the user and displaying them visually.

[2251] "Means for generating answers to detailed user questions using a generative AI model or a human expert and sending them back to the user's information device" refers to the process by which an AI or expert creates an answer to a detailed user question and sends that answer to the user's device.

[2252] "Means for displaying a household plan in a virtual environment using augmented reality" refers to a mechanism that uses AR technology to visually overlay a household plan on the user's real-world environment.

[2253] "Natural language processing means for voice interaction with a user" is a system that includes technology for understanding a user's voice input and generating an appropriate response.

[2254] "Means for format validation and error detection" refers to a mechanism that has a validation process to ensure that data entered by the user conforms to a predetermined format and has the ability to detect incorrect input.

[2255] "Means for a human expert to finalize the analysis results of the generated AI model and contact the user as necessary" refers to a process in which experts review the analysis results generated by AI and, if necessary, provide direct feedback to the user.

[2256] "Means for managing the database used by the AI ​​model" refers to a system for storing data necessary for AI analysis and maintaining and operating the database that manages it.

[2257] "Natural language processing means for voice interaction" is a system that uses technology to analyze a user's voice input, understand the content of the question, and automatically generate an appropriate response.

[2258] This invention is a system that allows users to receive financial advice from the comfort of their own home, and is composed of the following elements: A device such as a smartphone, smart glasses, or head-mounted display is used as a means for users to input basic information. This device provides an interface for users to input basic information about their household finances, such as name, age, income, fixed expenses, and family composition.

[2259] The data entered by the user is sent via a network to a remote server. The server analyzes the received data based on a generative AI model and generates a household plan or insurance proposal. The generative AI model is an analysis system that uses machine learning algorithms and is built into the server.

[2260] The generated proposals are then sent back to the user's information device and displayed visually. In this process, the AI ​​model generates household plans and proposals for the user in real time. Answers to detailed questions from the user are also generated by the AI ​​model or human experts and sent back to the user's information device.

[2261] The system includes a means to display a household plan in a virtual environment using augmented reality (AR) technology. Users can visually experience a virtual household planner in their living room or other location using smart glasses or a head-mounted display. The system also uses voice recognition and natural language processing technology to interact with the user, allowing them to input household information and ask questions by voice.

[2262] As a specific example, there is a scenario in which a user can say, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people," and the system will collect basic information and perform analysis. The user's voice input is converted into text using the Google Speech-to-Text API, and the Google Natural Language API is used for natural language processing.

[2263] If a user wants to ask a more detailed question about the proposed household budget plan, for example, they can say, "How can I revise my household budget plan?" This question is also analyzed using natural language processing, and a generative AI model or expert generates an answer. This answer is also displayed on the information terminal, providing visual and audio feedback.

[2264] An example of a prompt is as follows:

[2265] Please enter household information such as the user's name, age, income, fixed expenses, and family composition. For example, please enter something like, "My name is Ichiro Tanaka. I'm 40 years old, my monthly income is 250,000 yen, my monthly fixed expenses are 100,000 yen, and my family consists of four people."

[2266] In this way, users can use an interactive household finance consultation system that combines augmented reality technology and natural language processing from the comfort of their own home. This invention enables users to receive prompt and accurate household finance advice, which is expected to improve their quality of life.

[2267] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2268] Step 1:

[2269] The user enters basic information.

[2270] Users launch the household finance advisor app using their smartphone, smart glasses, or head-mounted display, and an input screen appears, prompting them to enter basic information such as their name, age, income, fixed expenses, and family composition by voice or text.

[2271] Input: User's household information

[2272] Output: Input household information data

[2273] Step 2:

[2274] The terminal transmits the input data to the server.

[2275] The terminal checks the format of the household information entered by the user and performs error detection before transmitting the data to a remote server via a network.

[2276] Input: Entered household information data

[2277] Output: Household information data sent to the server

[2278] Step 3:

[2279] The server analyzes the data using the generative AI model.

[2280] The server analyzes the received data based on the generative AI model and generates a household plan or insurance proposal, using machine learning algorithms to evaluate the user's household situation and make optimal proposals.

[2281] Input: Household information data sent to the server

[2282] Output: A household budget or insurance proposal from a generative AI model

[2283] Step 4:

[2284] The server sends the generated proposal back to the user's terminal.

[2285] The household plan and insurance proposals generated by the server are sent back to the user's terminal via the network.

[2286] Input: household budget or insurance proposals from a generative AI model

[2287] Output: Proposal data returned to the user device

[2288] Step 5:

[2289] The terminal displays the suggestions to the user.

[2290] The device visually displays the returned household plan or insurance proposal and presents it to the user in an easy-to-view format, where the household plan is displayed in a virtual environment using augmented reality (AR) technology.

[2291] Input: Returned proposal data

[2292] Output: A household plan or insurance proposal displayed to the user

[2293] Step 6:

[2294] The user enters a detailed question.

[2295] The user can then enter additional or detailed questions about the suggestions by voice or text.

[2296] Input: Detailed question from user

[2297] Output: Question data entered

[2298] Step 7:

[2299] The terminal transmits the question data to the server.

[2300] The terminal sends detailed questions from the user to the server.

[2301] Input: The entered question data

[2302] Output: The query data sent to the server

[2303] Step 8:

[2304] The server asks questions to generative AI models or human experts and generates answers.

[2305] The server analyzes the user's detailed question and generates an answer relying on generative AI models or human experts.

[2306] Input: Query data sent to the server

[2307] Output: Generated response data

[2308] Step 9:

[2309] The server sends the generated answer back to the user's terminal.

[2310] The generated answer is sent back to the user's terminal via the network.

[2311] Input: Generated response data

[2312] Output: Answer data returned to the user's device

[2313] Step 10:

[2314] The terminal displays the answer to the user.

[2315] The terminal visually displays the returned answer data and provides the user with audio or text feedback.

[2316] Input: Returned response data

[2317] Output: The answer displayed to the user

[2318] 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.

[2319] This invention is a financial advice system that utilizes AI and an emotion engine to provide more accurate and emotionally sensitive advice to users when they seek financial advice. Below, we explain the program processing of this system in natural language. We also provide a user usage scenario with concrete examples.

[2320] Overall system overview

[2321] This household financial consultation system mainly consists of the following elements:

[2322] 1. Terminal

[2323] 2. Server

[2324] 3. AI Model

[2325] 4. Emotion Engine

[2326] 5. Human Experts

[2327] These elements work together, with the AI ​​analyzing and making suggestions based on the household information entered by the user, and the emotion engine recognizing the user's emotional state, with human experts providing support as needed.

[2328] Program processing flow

[2329] The specific processing flow of the system is as follows:

[2330] 1. The user starts a financial consultation

[2331] A user accesses an online or in-store terminal and arrives at the login screen.

[2332] The terminal displays a login authentication screen to the user and prompts them to enter their user ID and password.

[2333] The terminal transmits the user's input information to the server for authentication.

[2334] 2. Enter your user information

[2335] The terminal displays a basic information input form to the user.

[2336] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[2337] The terminal checks the format of the entered data and checks for input errors.

[2338] 3. Sending input data

[2339] The terminal transmits the data whose format has been confirmed to the server.

[2340] The server analyzes the received data and stores it in a database.

[2341] 4. Analysis using AI models

[2342] The server passes the stored data to the AI ​​model.

[2343] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[2344] 5. Emotion Recognition by Emotion Engine

[2345] The terminal activates an emotion engine during interaction with the user to recognize the user's emotional state.

[2346] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate their emotional state.

[2347] 6. Customize your suggestions

[2348] The emotional state recognized by the emotion engine is sent to the server.

[2349] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[2350] The server sends the customized offer to the user's terminal.

[2351] 7. Display of Suggestions

[2352] The device displays household plans and insurance proposals that are suitable for the user.

[2353] The user enters detailed questions and customization requests for the displayed plan.

[2354] 8. Response to detailed questions

[2355] The terminal transmits the user's questions and requests to the server.

[2356] The server then asks the AI ​​model or a human expert for answers to detailed questions.

[2357] 9. Generating and Displaying Answers

[2358] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[2359] The server sends the generated answer to the user's terminal.

[2360] The terminal displays the detailed answer to the user.

[2361] 10. Handover to an expert

[2362] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[2363] The server notifies the experts and shares the user's data.

[2364] A human expert will contact the user for a detailed consultation.

[2365] Specific examples

[2366] Example: Maria is discussing her financial plan.

[2367] 1. Maria starts financial counseling

[2368] Maria accesses the system online from her home computer and reaches the login screen.

[2369] The terminal displays the login authentication screen, and Maria enters her user ID and password to log in.

[2370] The terminal transmits Maria's input information to the server for authentication.

[2371] 2. Enter your user information

[2372] The terminal displays a basic information input form, and Maria enters her name, age, income, fixed expenses, family composition, etc.

[2373] The terminal checks the format of the entered data and checks for input errors.

[2374] 3. Sending input data

[2375] The terminal transmits the verified data to the server.

[2376] The server receives and analyzes the data and then stores it in a database.

[2377] 4. Analysis using AI models

[2378] The server passes the stored data to the AI ​​model.

[2379] The AI ​​model analyzes Maria's data and generates optimal household budget review points and insurance plans.

[2380] 5. Emotion Recognition by Emotion Engine

[2381] The device activates an emotion engine during interaction with Maria to recognize her emotional state.

[2382] The emotion engine analyzes Maria's facial expressions, voice, and text data to assess her emotional state.

[2383] 6. Customize your suggestions

[2384] The emotional state recognized by the emotion engine is sent to the server.

[2385] The server customizes the suggestions generated by the AI ​​model based on the emotional data.

[2386] The server sends the customized offer to Maria's terminal.

[2387] 7. Display of Suggestions

[2388] The device displays the suggestions to Maria and provides appropriate advice that takes her emotions into consideration.

[2389] 8. Response to detailed questions

[2390] Maria enters detailed questions and customization requests for the displayed plan.

[2391] The device sends these questions to a server, which then asks an AI model or a human expert.

[2392] 9. Generating and Displaying Answers

[2393] An AI model or human expert generates answers to Maria's questions and sends them back to the server.

[2394] The server sends the generated response to Maria's terminal.

[2395] The terminal displays a detailed response to Maria.

[2396] 10. Handover to an expert

[2397] The server determines that Maria's question is advanced and hands it over to a human expert.

[2398] The expert will contact Maria and provide further advice.

[2399] In this way, this invention allows users to use a household finance consultation service that also takes their emotional state into consideration. In addition to fast and appropriate suggestions from AI, the emotion engine recognizes the user's emotional state and human experts provide support as needed, making it possible to provide a highly reliable service to users.

[2400] The processing flow will be explained below.

[2401] Step 1:

[2402] A user accesses an online or in-store terminal and arrives at the login screen.

[2403] The terminal displays a login authentication screen to the user.

[2404] The user enters the user ID and password and clicks the login button.

[2405] Step 2:

[2406] The terminal sends the user's login information to the server.

[2407] The server receives the login information and authenticates it against a database.

[2408] If the authentication is successful, the server returns a message indicating that the authentication is successful to the terminal.

[2409] The terminal displays a message to the user indicating that authentication was successful and moves to the next screen.

[2410] Step 3:

[2411] The terminal displays a basic information input form to the user.

[2412] Users enter basic information such as name, age, income, fixed expenses, and family composition.

[2413] Step 4:

[2414] The terminal checks the format of the input data.

[2415] Once the error check is complete and there is no problem with the data, the terminal sends the input data to the server.

[2416] Step 5:

[2417] The server analyzes the received data and stores it in a database.

[2418] Step 6:

[2419] The server passes the stored data to the AI ​​model.

[2420] The AI ​​model analyzes user data and generates optimal household budget review points and insurance plans.

[2421] Step 7:

[2422] The terminal activates the emotion engine during interaction with the user.

[2423] The emotion engine analyzes the user's facial expressions, voice, and text data to assess their emotional state.

[2424] Step 8:

[2425] The emotion engine transmits the recognized emotional state to the server.

[2426] The server uses this emotional data to customize the suggestions generated by the AI ​​model.

[2427] Step 9:

[2428] The server sends the customized offer to the user's terminal.

[2429] The terminal displays the suggestions to the user.

[2430] Step 10:

[2431] The user then inputs detailed questions and customization requests in response to the displayed suggestions.

[2432] The terminal sends these questions and requests to the server.

[2433] Step 11:

[2434] The server receives detailed questions or requests and refers them to an AI model or a human expert.

[2435] An AI model or human expert generates an answer to the user's question and sends it back to the server.

[2436] Step 12:

[2437] The server sends the generated answer to the user's terminal.

[2438] The terminal displays the detailed answer to the user.

[2439] Step 13:

[2440] If the server determines that the user's question is of advanced or specialized nature, it will transfer the case to a human financial planner.

[2441] The server notifies the experts and shares the user's data.

[2442] A human expert will contact the user for further consultation.

[2443] The above is the flow of specific processing steps in the household finance consultation system.

[2444] Example 2

[2445] 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."

[2446] Conventional financial consultation systems make suggestions based on basic user information, but they fail to consider the user's emotional state and often make one-sided suggestions, making it difficult for users to achieve satisfactory results. Furthermore, input data formatting and error checking are often insufficient, resulting in incorrect information being sent to the system. Furthermore, when answers to detailed questions are automatically generated, they often lack professional judgment.

[2447] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's terminal; a means for recognizing an emotional state during interaction with the user; a means for customizing the proposal content based on the recognized emotional state; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's terminal; a means for checking the data format and performing error checks; and a means for a human expert to finally check the AI ​​analysis results and contact the user as necessary. This enables the provision of an accurate household budget plan that reflects the user's emotional state, high reliability of input data, and response to detailed questions from a professional perspective.

[2448] "User" refers to a person who uses the system to receive financial advice.

[2449] "Terminal" refers to an electronic device (PC, smartphone, tablet, etc.) that a user uses to access and use the system.

[2450] "Server" refers to the central computer device that manages the entire system and performs processes such as data storage, analysis, and proposal generation.

[2451] "Artificial intelligence model" refers to the algorithms and machine learning models that analyze user data and generate household plans and insurance proposals.

[2452] An "emotion engine" refers to a system that recognizes a user's emotional state from data collected during interactions with the user and customizes suggestions based on the results.

[2453] A "household plan" refers to a financial plan created taking into account the user's income, expenses, family composition, etc.

[2454] "Insurance proposal" refers to information that suggests the most suitable insurance plan based on the user's household data, etc.

[2455] "Interaction" refers to the dialogue and exchange of information between a user and a system.

[2456] "Error checking" refers to the process of checking and correcting input data for errors.

[2457] This invention is a financial advice system that provides users with more accurate and emotionally sensitive advice when they seek financial advice. The system collects basic information about the user and generates financial plans and insurance proposals using an artificial intelligence model and an emotion engine. Furthermore, the system recognizes the user's emotional state and customizes proposals based on that state. A specific embodiment of the system is described below.

[2458] The system mainly consists of the following elements:

[2459] 1. Terminal

[2460] This refers to devices that users use to access systems, such as PCs, smartphones, and tablets. Examples include Apple's MacBook, Microsoft's Surface, and Google's Pixel.

[2461] 2. Server

[2462] This refers to the central computer device that manages the entire system and stores data, analyzes it, and generates proposals. It can be a general cloud server, such as an EC2 instance from Amazon Web Services (AWS) or a Compute Engine from Google Cloud Platform (GCP).

[2463] 3. Artificial Intelligence Model

[2464] This refers to algorithms and machine learning models that analyze user data and generate household plans and insurance proposals. Examples include OpenAI's GPT-3 and BERT.

[2465] 4. Emotion Engine

[2466] This refers to systems that recognize a user's emotional state from data collected during user interactions and customize suggestions based on the results. Examples include Affectiva and Microsoft's Emotion API.

[2467] 5. Human Experts

[2468] This refers to financial planners and insurance advisors who, if necessary, provide final confirmation of the analysis results of the AI ​​model and contact users directly.

[2469] Specific examples

[2470] In a scenario where a user is consulting about a household budget, the system operates in the following steps.

[2471] 1. The user starts a financial consultation

[2472] A user accesses the system from their home PC and reaches the login screen. The terminal displays the login authentication screen, and the user logs in by entering their user ID and password. This information is sent from the terminal to the server and authenticated.

[2473] 2. Enter your user information

[2474] The terminal displays a basic information input form, and the user inputs name, age, income, fixed expenses, family composition, etc. The terminal checks the format of the input data and performs error checks.

[2475] 3. Analysis of input data

[2476] The server receives the data after checking the format and stores it in a database. The stored data is then passed to an AI model, which analyzes the user's data and generates budget adjustments and optimal insurance plans.

[2477] 4. Emotion Recognition and Customized Suggestions

[2478] The device activates an emotion engine during interaction with the user to recognize the user's emotional state. The emotion engine then sends the recognized emotional data to the server, which then customizes suggestions based on this data. As a result, the device provides appropriate advice that takes the user's emotions into consideration.

[2479] Prompt Sentence Examples

[2480] Below is an example of a prompt sentence to input to the generative AI model.

[2481] "The user is 30 years old and earns 300,000 yen a month. I have entered detailed information about my monthly fixed expenses and family structure. Please suggest the best household budget plan for this user."

[2482] The detailed operation of this system allows users to receive accurate and prompt financial advice that takes their emotions into consideration. Each element works in tandem to provide a highly reliable service to users.

[2483] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2484] Step 1:

[2485] User starts household finance consultation

[2486] A user accesses the system using a PC or smartphone and reaches the login screen.

[2487] Input: User ID, Password

[2488] The terminal displays a login authentication screen, and the user enters their user ID and password.

[2489] Output: Authentication result

[2490] The device sends the entered authentication information to the server. The server verifies the authentication information and checks whether the user is registered. If authentication is successful, the device displays the home screen to proceed to the next step.

[2491] Step 2:

[2492] Entering user information

[2493] The terminal displays a basic information input form to the user.

[2494] Input: Basic information such as name, age, income, fixed expenses, family composition, etc.

[2495] The user enters basic information such as name, age, income, fixed expenses, and family composition.

[2496] Output: Basic information entered

[2497] The terminal checks the format of the entered data and ensures that all required fields are filled in. If there is a problem with the format, the terminal displays an error message and prompts the user to re-enter the data.

[2498] Step 3:

[2499] Sending input data

[2500] The terminal transmits the data after format confirmation to the server.

[2501] Input: Verified data

[2502] The server analyzes the received data and stores it in a database.

[2503] Output: Save results to database

[2504] The server returns a confirmation of data storage to the terminal and instructs it to proceed to the next step.

[2505] Step 4:

[2506] Analysis using AI models

[2507] The server passes the stored user data to an artificial intelligence model.

[2508] Input: Saved user data

[2509] The artificial intelligence model generates budget review points and optimal insurance plans based on data such as the user's income, expenses, and family composition.

[2510] Output: Household budget plan and insurance proposals

[2511] The AI ​​model generates a proposal that is sent back to the server, which uses it in the next step.

[2512] Step 5:

[2513] Emotion recognition by emotion engine

[2514] The terminal activates the emotion engine during interaction with the user.

[2515] Input: User's facial expressions, voice, and text data

[2516] The emotion engine analyzes the user's facial expressions, voice, text data, etc. to evaluate the user's emotional state.

[2517] Output: Emotional evaluation data

[2518] The evaluated emotion data is sent to the server via the terminal.

[2519] Step 6:

[2520] Customize suggestions

[2521] The server customizes the suggestions generated by the artificial intelligence model based on the emotional data received from the emotion engine.

[2522] Input: Emotion data, suggested data from AI model

[2523] The server adjusts the content of the suggestions appropriately depending on the user's emotional state, and constructs the most appropriate advice for the user.

[2524] Output: Customized proposal

[2525] Send customized offers to your device.

[2526] Step 7:

[2527] View Suggestions

[2528] The device displays customized household plans and insurance offers to the user.

[2529] Input:Customized Proposal

[2530] Output: Displayed proposal

[2531] Users can then enter detailed questions and customization requests for the plans displayed, allowing them to receive advice that best suits their situation.

[2532] Step 8:

[2533] Response to detailed questions

[2534] The terminal sends user questions and requests to the server.

[2535] Input: User questions or requests

[2536] Based on the question, the server asks an AI model or a human expert to respond to the question.

[2537] Output: Request details

[2538] This allows for appropriate answers to be prepared for detailed questions from the user.

[2539] Step 9:

[2540] Generate and display answers

[2541] An artificial intelligence model or human expert generates answers to the user's questions and sends them back to the server.

[2542] Input: Question response request, expert answer

[2543] Output: The generated answer

[2544] The server sends the generated answer to the user's device, which displays the detailed answer to the user, allowing the user to resolve their question and obtain further information.

[2545] Step 10:

[2546] Handover to experts

[2547] If the server determines that the user's question is difficult, it will hand it off to a human expert.

[2548] Input: User question, expert handover instructions

[2549] Output: Handover notification to expert

[2550] The server notifies the expert and shares the user's data, and the human expert contacts the user for a detailed consultation, allowing the user to receive further expert advice.

[2551] (Application example 2)

[2552] 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."

[2553] Conventional household budget consultation systems provide analysis results and advice without considering the user's emotions, making it difficult to reduce the user's psychological burden and stress. In addition, centralized management of expenditure data was insufficient, making it difficult to provide appropriate advice that takes emotions into consideration in real time.

[2554] 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.

[2555] In this invention, the server includes: a means for a user to input basic information; a means for transmitting the input data to the server; a means for analyzing the received data based on an AI model and generating a household budget plan or insurance proposal; a means for returning and displaying the generated proposal to the user's device; a means for generating answers to the user's detailed questions using an AI model or a human expert and returning them to the user's device; an emotion recognition means for analyzing the user's facial expressions and voice using the device's built-in camera and microphone to recognize the user's emotional state; a means for adjusting the proposal content based on the emotional state; a means for transmitting emotion-sensitive notifications and advice to the user's device; a format verification and error detection means; a means for inputting and analyzing the user's expenditure data and providing a household budget improvement plan that takes the user's emotional state into account; and a means for managing the generative AI model and emotion engine to provide advice and plans based on the user's emotional state. This allows for the provision of appropriate advice that takes the user's emotions into account, improving the efficiency of household budget management and reducing the user's psychological burden.

[2556] "Basic information" refers to personal information necessary for financial consultation, such as the user's name, age, income, fixed expenses, and family composition.

[2557] "Server" refers to a device that receives data entered by a user, analyzes it, and returns the results to the user.

[2558] "AI model" refers to an algorithm that uses machine learning technology to generate household budget review points and insurance proposals.

[2559] "Emotion recognition means" refers to a device that uses a camera and microphone to analyze the user's facial expressions and voice and evaluate their emotional state.

[2560] "Emotional state" refers to the psychological state obtained from the user's facial expressions, voice, and text data.

[2561] "Proposal content" refers to advice and plans generated by the AI ​​model, such as points to review in household finances and insurance proposals.

[2562] "Notifications and advice" refers to information about improving household finances and notifications encouraging specific actions that are sent to the user's device.

[2563] "Terminal" refers to the device on which the user inputs information and receives and displays suggestions from the server.

[2564] "Format checking and error detection means" refers to a function that checks whether there are any errors in the format or content of the data entered by the user.

[2565] "Input and analysis of expenditure data" refers to the function that allows users to input daily expenditure amounts and breakdowns and analyze them.

[2566] "Finance Improvement Plan" refers to savings and investment plans created based on the user's spending data and emotional state.

[2567] A "generative AI model" refers to an algorithm that uses AI technology to generate suggestions suited to a user's financial situation and emotional state.

[2568] An "emotion engine" refers to software that assesses a user's emotional state and adjusts suggestions accordingly.

[2569] MODE FOR CARRYING OUT THE INVENTION

[2570] System configuration overview

[2571] This invention is a system that provides financial advice to users while they manage their daily expenses. The system aims to provide advice that takes into account the user's emotional state. The main components of the system include a terminal, a server, an AI model, and an emotion engine.

[2572] Hardware and software used

[2573] Hardware: Smartphone (built-in camera, microphone)

[2574] Software: TensorFlow, Emotion API, Expense Database

[2575] Program processing

[2576] overview

[2577] The server performs the following processes: It analyzes the expenditure data entered by the user and generates a household...

Claims

1. a means for a user to input basic information; means for transmitting the input data to a server; means for analyzing the received data based on an AI model to generate a household plan or insurance proposal; means for returning and displaying the generated suggestions to the user's terminal; and a means for generating answers to the user's detailed questions using an AI model or a human expert and returning the answers to the user's device.

2. means for formatting and detecting errors in user information input; Further include a means for a human expert to finalize the AI ​​analysis results and communicate with the user as needed. The system of claim 1 .

3. A means for users to access the system online or through a terminal at a store and start a household finance consultation; and a means for managing a database used by the AI ​​model when generating household budget review points and optimal plans. The system of claim 1 .

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