system

Abstract

Provide a system. A means for inputting or linking financial data; a means for storing the entered financial data; A means of transmitting the stored financial data to an AI engine for analysis; a means for generating reports based on the analysis results; a means for providing the generated report to a user; A system including:

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] Conventional financial advisory systems place a heavy burden on users, requiring them to organize and analyze their own financial data, making it difficult to efficiently grasp their financial situation and manage risks. Furthermore, receiving expert advice requires a cumbersome process, making it difficult to obtain appropriate advice in situations where a quick response is required. For these reasons, there was a need for a system that could optimize users' financial decision-making and provide expert advice safely and quickly. [Means for solving the problem]

[0005] The present invention provides a system including a means for inputting or linking financial data, a means for saving the input financial data, a means for transmitting the saved financial data to an AI engine for analysis, a means for generating a report based on the analysis results, and a means for providing the generated report to a user. Furthermore, by providing a means for consulting with an expert based on the analysis results and a means for providing the expert with advice, it is possible to provide expert financial advice quickly and efficiently. Furthermore, by providing an API linking means for linking with external services and storing acquired financial data for use in analysis, the system centralizes the user's financial management and improves convenience. This solves existing problems and makes it possible to support users' economic decision-making.

[0006] "Financial Data" means your bank account, investment account, credit card information, and other data about your income, expenses, and assets.

[0007] "Means of input or integration" refers to a method by which a user manually inputs financial data into the system or automatically retrieves data using an API of an external service.

[0008] "Means for storage" refers to a method for securely recording and storing input or linked financial data in a database.

[0009] "AI engine" refers to artificial intelligence used to analyze collected financial data and predict users' financial situations and risks.

[0010] "Means of analysis" refers to how the AI ​​engine evaluates financial data and analyzes the user's income, expenses, investment patterns, etc.

[0011] "Means for generating a report" refers to a method for creating a report that is organized as useful information for the user based on the analysis results of the AI ​​engine.

[0012] "Means for providing to the user" refers to a method for displaying the generated report and advice from the expert on the user's terminal.

[0013] "Means for consulting with an expert" refers to a method for requesting consultation from an appropriate expert based on the user's financial data and the results of AI analysis.

[0014] The term "means for providing expert advice" refers to a method for providing advice provided by an expert to a user.

[0015] "API integration means" refers to a method of automatically obtaining financial data using the API of an external service and making it available within the system. [Brief explanation of the drawings]

[0016] [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 illustrating 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

[0017] 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.

[0018] First, the terms used in the following description will be explained.

[0019] 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).

[0020] 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.

[0021] 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.

[0022] 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.

[0023] 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."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 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.

[0027] 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).

[0028] 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.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] 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."

[0037] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' economic decision-making. Specific embodiments of this system are described in detail below.

[0038] Overall system configuration

[0039] The system basically consists of a user's device, a server, an AI engine, and an expert. The user's device provides the interface that the user operates, while the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the expert provides final advice.

[0040] User registration and authentication

[0041] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[0042] Terminal: The user's terminal sends the entered information to the server.

[0043] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[0044] Financial data input and integration

[0045] Users: Users enter their bank account, investment account, and credit card information into the system, with the option to automatically retrieve financial data through API integration with external services.

[0046] Terminal: The user's terminal sends the entered or acquired data to the server.

[0047] Server: The server receives the financial data and stores it in a secure database.

[0048] AI analysis and report generation

[0049] Server: The server sends the stored financial data to the AI ​​engine.

[0050] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[0051] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0052] Providing expert advice

[0053] User: The user submits a request for expert advice based on the analysis results.

[0054] Terminal: The user's terminal sends the request to the server.

[0055] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[0056] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[0057] Server: The server displays expert advice on the user's dashboard.

[0058] Specific examples

[0059] For example, consider a case where a user connects their bank account and investment account to the system. The user first enters their account information or sets up API connection. The system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[0060] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[0061] The processing flow will be explained below.

[0062] Step 1:

[0063] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[0064] Step 2:

[0065] The terminal transmits the input user information to the server.

[0066] Step 3:

[0067] The server stores the received user information in a database and sends a confirmation email to the user.

[0068] Step 4:

[0069] The user clicks on the link contained in the confirmation email to verify their email address.

[0070] Step 5:

[0071] The server verifies that the user clicked on the link and completes the account authentication.

[0072] Step 6:

[0073] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[0074] Step 7:

[0075] The terminal transmits the entered financial information and data obtained from the external service to the server.

[0076] Step 8:

[0077] The server stores the received financial data in a secure database.

[0078] Step 9:

[0079] The server sends the stored financial data to the AI ​​engine.

[0080] Step 10:

[0081] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[0082] Step 11:

[0083] The server receives the analysis results from the AI ​​engine and generates a report.

[0084] Step 12:

[0085] The terminal displays the generated report on the user's dashboard.

[0086] Step 13:

[0087] The user reviews the report and submits a request for further expert advice.

[0088] Step 14:

[0089] The terminal transmits the user's request to the server.

[0090] Step 15:

[0091] The server selects the appropriate expert based on the user's financial data and the results of AI analysis.

[0092] Step 16:

[0093] The server transmits the user's financial data and analysis results to the selected expert.

[0094] Step 17:

[0095] The expert creates specific advice based on the received data and sends the advice to the server.

[0096] Step 18:

[0097] The server receives the advice from the experts and displays it on the user's dashboard.

[0098] Step 19:

[0099] Users can view expert advice on the dashboard and take appropriate action.

[0100] Example 1

[0101] 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."

[0102] Conventional financial data management systems lack analytical functions and specific advice from experts to effectively support users' financial decision-making. Furthermore, they lack sufficient automation of data integration and analysis processes, making them difficult for users to use. Furthermore, it is difficult to integrate with external services, making it difficult to centrally manage multiple pieces of financial information.

[0103] 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.

[0104] In this invention, the server includes a means for inputting or linking financial data, a means for saving the input financial data, and a means for sending the saved financial data to an AI engine for analysis. This includes a means for a user to create a new account, a means for the server to send a confirmation email and authenticate the account, a means for providing the generated report to the user, a means for the user to send a request for expert advice, a means for the server to select an appropriate expert and provide the user's financial data and AI analysis results, a means for the expert to provide advice, a means for the server to display the advice on the user's dashboard, an API integration means for linking with external services, a means for saving financial data obtained from external services and using it for analysis, and a means for the user's device to send input information to the server via an HTTP POST request. This configuration allows users to easily create accounts, efficiently manage and analyze their financial data, and further enables them to make appropriate economic decisions by receiving specific advice from experts.

[0105] "Financial data" refers to data such as income, expenditure, and investment information obtained by a user from financial institutions, investment institutions, and the like.

[0106] "Means for input or linking" refers to means by which a user manually inputs data or automatically obtains data from an external service via an API.

[0107] "Means of storage" refers to a database for securely storing received data and the associated security mechanisms.

[0108] An "AI engine" is an artificial intelligence model that analyzes a user's financial data and predicts income, expenses, investment patterns, etc.

[0109] The "means for generating a report" refers to a means for visually displaying the analysis results by the AI ​​engine in a format that is easy for the user to understand.

[0110] The "means for creating an account" is a mechanism that allows a new user to create an account by entering their name, email address, password, etc.

[0111] The "means for sending a confirmation email" is a mechanism for sending a confirmation email to the email address entered during user registration and providing an authentication link.

[0112] The "account authentication method" is a mechanism by which a user activates their account by clicking a link in a confirmation email.

[0113] "Means for consulting with experts" refers to a system in which users can send requests for advice to experts based on the results of AI analysis.

[0114] The "means for providing advice from experts" is a mechanism for displaying advice provided by experts to the user.

[0115] "API integration means" is a mechanism that uses APIs to automatically obtain data by linking with external financial services and investment services.

[0116] An "HTTP POST request" is a request format that uses the HTTP protocol to send data from a terminal to a server.

[0117] The "dashboard" is a user interface that centrally displays the user's financial situation, AI analysis results, and advice from experts.

[0118] The system of the present invention efficiently manages users' financial data and supports their economic decision-making by providing AI analysis results and expert advice. This system consists of a user's terminal, a server, an AI engine, and experts.

[0119] User registration and authentication

[0120] Submit account creation request

[0121] The user accesses the system's registration page through a web browser, enters their name, email address, and password, and clicks the "Register" button.

[0122] The device constructs the input data in JSON format and sends an HTTP POST request to the server.

[0123] Save user data and send confirmation email

[0124] The server stores the received user data in an SQL database and uses the Python smtplib library to send a confirmation email containing an authentication link to the user.

[0125] Account authentication completed

[0126] The user clicks on the verification link in the email.

[0127] The server validates the token contained in the link and activates the corresponding user's account.

[0128] Financial data input and integration

[0129] Financial data entry request submission

[0130] A user enters bank account, investment account, and credit card information in a web browser and clicks the submit button.

[0131] The device sends the input data to the server via an HTTP POST request.

[0132] Financial Data Storage

[0133] The server stores the received financial data in a secure SQL database.

[0134] AI analysis and report generation

[0135] Data analysis request submission

[0136] The server periodically sends the stored financial data to the AI ​​engine.

[0137] Data analysis

[0138] The AI ​​engine analyzes the user's income, expenditure, and investment patterns and generates predictions.

[0139] Report Generation

[0140] The server receives the analysis results from the AI ​​engine, generates a user-friendly report using HTML and JavaScript (registered trademark), and displays it on the user's dashboard.

[0141] Providing expert advice

[0142] Submit an advice request

[0143] The user clicks a button on the dashboard to send a request for expert advice.

[0144] The device sends the request to the server via an HTTP POST request.

[0145] Selection of experts and provision of data

[0146] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel.

[0147] Creating and providing advice

[0148] Experts create specific advice based on the information provided and send it to the server via a dedicated management interface.

[0149] The server displays the received advice on the user's dashboard.

[0150] Example operation

[0151] For example, consider a case where a user connects their bank account and investment account to the system. After the user enters their account information or sets up API connection, the system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[0152] Prompt Sentence Examples

[0153] By inputting prompt statements into the generative AI model as shown below, specific advice and analysis results can be obtained.

[0154] Sample prompt 1: "Please tell me the breakdown of your income and expenses this month."

[0155] Sample prompt 2: "Predict your investment performance over the next six months."

[0156] Sample prompt 3: "I'd like some advice on effective ways to save money."

[0157] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[0158] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0159] Step 1:

[0160] A user accesses the system's registration page, enters their name, email address, and password, and clicks the "Register" button. The input data includes their name, email address, and password. This generates a request to create a new account.

[0161] Step 2:

[0162] The device constructs the input data in JSON format and sends an HTTP POST request to the server, which includes the user's name, email address, and password, and sends the new user information to the server.

[0163] Step 3:

[0164] The server receives the HTTP POST request, extracts user information from the request body, stores the extracted data in an SQL database by executing an insert query, and sends a confirmation email to the user's email address using the SMTP protocol. The confirmation email contains a link to verify the account.

[0165] Step 4:

[0166] The user opens the confirmation email they received and clicks on the authentication link in the email, which sends an account authentication request to the server.

[0167] Step 5:

[0168] The server verifies the token in the authentication link and updates the status of the corresponding user account to enabled, which means the user account is authenticated and ready for use.

[0169] Step 6:

[0170] After logging in, users enter their bank account, investment account, and credit card information, or use this information as input data to set up API integration with external services. After entering the information, they click the "Submit" button.

[0171] Step 7:

[0172] The terminal constructs the entered financial data in JSON format and sends an HTTP POST request to the server, containing the user's bank account, investment account, and credit card information.

[0173] Step 8:

[0174] The server receives the HTTP POST request, extracts financial data from the request body, and stores the extracted data securely in an SQL database for analysis.

[0175] Step 9:

[0176] The server periodically sends the stored financial data to the AI ​​engine, including the user's income, expenditure, and investment patterns.

[0177] Step 10:

[0178] The AI ​​engine analyzes the received financial data and generates forecasts for income, expenditure, and investment patterns. It uses machine learning algorithms to analyze the data and applies predictive models. The forecasts are then output as a report.

[0179] Step 11:

[0180] The server receives the analysis results from the AI ​​engine and generates a report using HTML and JavaScript. The generated report is displayed on the user's dashboard, allowing the user to check their financial status based on the analysis results.

[0181] Step 12:

[0182] A user clicks a button on the dashboard to send a request for expert advice, which includes the analysis results.

[0183] Step 13:

[0184] The device sends a request to the server via an HTTP POST request, which includes the user's financial data and the analysis results.

[0185] Step 14:

[0186] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel. The data provided to the expert includes the user's income, expenses, and investment patterns.

[0187] Step 15:

[0188] Experts create specific advice based on the information provided, and the advice is sent to the server via a dedicated management interface.

[0189] Step 16:

[0190] The server receives the advice provided by the experts and displays it on the user's dashboard, allowing the user to make appropriate financial decisions based on the expert advice.

[0191] (Application example 1)

[0192] 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."

[0193] Today's consumers make many of their daily payments and transactions electronically, resulting in a vast and complex amount of financial data. It is difficult to manually manage this vast amount of data and develop appropriate financial management and investment strategies. There is also a lack of ways to analyze financial data in real time or quickly obtain appropriate prescriptions from experts. This makes it difficult for consumers to make optimal financial decisions.

[0194] 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.

[0195] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to the user, means for automatically synchronizing payment information, and means for performing AI analysis in real time, thereby enabling users to analyze massive amounts of financial data in real time and receive prompt and appropriate advice from experts.

[0196] "Financial Data" means information about the economic activities of an individual or entity, including information about income, expenses, investments, assets, and liabilities.

[0197] An "AI engine" is a system that uses artificial intelligence algorithms to analyze data and make predictions.

[0198] A "report" is information such as detailed documents and graphs that are generated based on financial data and the results of that analysis and are provided to users.

[0199] "Payment information" is detailed data about payments made by a user, including information such as date, amount, and category.

[0200] "Synchronization" is the process of updating and matching data between different systems or devices in real time or periodically.

[0201] An "expert" is someone with advanced knowledge and experience in a particular field, in this case, an expert in the fields of finance and economics.

[0202] "Auto-email" is a feature that allows the system to automatically send emails based on specific conditions.

[0203] "API integration" refers to different software systems exchanging information and working together via an application programming interface (API).

[0204] "Real-time analysis" is the process of analyzing the latest data immediately and providing the results almost instantly.

[0205] An embodiment of the present invention includes a system for efficiently managing financial data and providing AI analysis results and expert advice. This system is composed of a user terminal, a server, an AI engine, and experts.

[0206] User registration and authentication

[0207] A user accesses the system to create a new account. They enter the required information (name, email address, password) and submit the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[0208] Financial data input and integration

[0209] Users enter their bank account, investment account, and credit card information into the system. Optionally, financial data can be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[0210] Automatic payment synchronization

[0211] Each time a user makes an electronic payment, payment information is automatically sent by the user's terminal to the server, which stores this data in a real-time database and keeps the financial data up to date.

[0212] AI analysis and report generation

[0213] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0214] Providing expert advice

[0215] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results using an automatic email sending function. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[0216] Hardware and software used

[0217] 1. Hardware: The server uses cloud infrastructure (e.g., AWS (registered trademark) or GCP).

[0218] 2. Software:

[0219] Django (Web framework)

[0220] SciKit-Learn (machine learning library)

[0221] Specific examples of processing

[0222] For example, when a user connects their bank account and investment account to the system, they first enter their account information or set up API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request advice from an expert based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[0223] Prompt Sentence Examples

[0224] The following transaction was entered for user "example_user". A transaction of 150 yen for food was made on 2023-10-10. Please make a prediction based on the next transaction. The next transaction date is assumed to be 10 days later.

[0225] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0226] Step 1:

[0227] A user accesses the system and creates a new account. The user enters their name, email address, and password, and submits the registration form. This information is sent from the user's device to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[0228] Input: User's name, email address, and password

[0229] Output: Sends a confirmation email, saves user information to the database

[0230] Step 2:

[0231] Users log in to the system and enter their bank account, investment account, and credit card information. Optionally, they can set up API integration with external services to automatically retrieve financial data. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[0232] Input: Bank account, investment account, credit card information, API connection settings

[0233] Output: Saving financial data to a database

[0234] Step 3:

[0235] Every time a user makes an electronic payment, payment information is automatically sent from the user's device to the server, which stores this data in a real-time database, keeping financial data up to date.

[0236] Input: Payment information (date, time, amount, category)

[0237] Output: Real-time updated financial data storage

[0238] Step 4:

[0239] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. This analysis can use, for example, a linear regression model from SciKit-Learn. Once the analysis is complete, the results are sent to the server.

[0240] Input: Stored financial data

[0241] Output: Prediction results

[0242] Step 5:

[0243] The server receives the analysis results from the AI ​​engine and generates an easy-to-understand report, which is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0244] Input: Analysis results from the AI ​​engine

[0245] Output: Report, display on user dashboard

[0246] Step 6:

[0247] The user sends a request for advice from an expert based on the analysis results. The user's device then sends the request to the server. The server then selects an appropriate expert and provides the user's financial data and the AI ​​analysis results using an automatic email sending function.

[0248] Input: User advice request

[0249] Output: Automatic email to the expert

[0250] Step 7:

[0251] The expert creates specific advice based on the provided information and sends it to the server, which then displays the advice on the user's dashboard, allowing the user to receive specific guidance on appropriate investment strategies and savings methods.

[0252] Input: Expert advice

[0253] Output: Display on user dashboard

[0254] 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.

[0255] The system of the present invention efficiently manages a user's financial data and provides AI-based analysis results and expert advice to support the user's financial decision-making. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized advice and services. Specific embodiments of this system are described in detail below.

[0256] Overall system configuration

[0257] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotions. The expert provides final advice.

[0258] User registration and authentication

[0259] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[0260] Terminal: The user's terminal sends the entered information to the server.

[0261] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[0262] Financial data input and integration

[0263] Users: Users enter their bank account, investment account, and credit card information into the system, and can also use API integration with external services to automatically retrieve financial data.

[0264] Terminal: The user's terminal sends the entered or acquired data to the server.

[0265] Server: The server receives the financial data and stores it in a secure database.

[0266] AI analysis and report generation

[0267] Server: The server sends the stored financial data to the AI ​​engine.

[0268] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[0269] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0270] Providing expert advice

[0271] User: The user submits a request for expert advice based on the analysis results.

[0272] Terminal: The user's terminal sends the request to the server.

[0273] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[0274] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[0275] Server: The server displays expert advice on the user's dashboard.

[0276] Emotion Engine Functions

[0277] User: As the user uses the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time.

[0278] Emotion Engine: The emotion engine recognizes the user's emotional state and sends the result to the server.

[0279] Server: The server adjusts financial reports and expert advice based on information from the sentiment engine.

[0280] Specific examples

[0281] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0282] Furthermore, the emotion engine can recognize a user's emotional state and adjust the report display to be simple and easy to understand if the user is stressed. Expert advice can also be tailored to the user's emotions, suggesting a low-risk investment strategy if the user is excited, or offering a detailed investment plan if the user is calm.

[0283] As described above, the present invention is a system that supports users' economic decision-making through efficient management and analysis of financial data, and by combining it with an emotion engine, it is possible to provide more personalized advice and services.

[0284] The processing flow will be explained below.

[0285] Step 1:

[0286] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[0287] Step 2:

[0288] The terminal transmits the input user information to the server.

[0289] Step 3:

[0290] The server stores the received user information in a database and sends a confirmation email to the user.

[0291] Step 4:

[0292] The user clicks on the link contained in the confirmation email to verify their email address.

[0293] Step 5:

[0294] The server verifies that the user clicked on the link and completes the account authentication.

[0295] Step 6:

[0296] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[0297] Step 7:

[0298] The terminal transmits the entered financial information and data obtained from the external service to the server.

[0299] Step 8:

[0300] The server stores the received financial data in a secure database.

[0301] Step 9:

[0302] The server sends the stored financial data to the AI ​​engine.

[0303] Step 10:

[0304] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[0305] Step 11:

[0306] The server receives the analysis results from the AI ​​engine and generates a report.

[0307] Step 12:

[0308] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[0309] Step 13:

[0310] The emotion engine sends the recognized emotional state to the server.

[0311] Step 14:

[0312] The server adjusts the display of the financial report based on the information from the emotion engine.

[0313] Step 15:

[0314] The terminal displays the generated report on the user's dashboard, reflecting the adjusted display content.

[0315] Step 16:

[0316] The user reviews the report and submits a request for further expert advice.

[0317] Step 17:

[0318] The terminal transmits the user's request to the server.

[0319] Step 18:

[0320] The server selects the appropriate expert and provides the user's financial data and AI analysis results.

[0321] Step 19:

[0322] The expert creates specific advice based on the provided information and sends it to the server.

[0323] Step 20:

[0324] The server receives expert advice and tailors it to the user.

[0325] Step 21:

[0326] The server adjusts the expert advice based on the information from the emotion engine and displays it on the user's dashboard.

[0327] Step 22:

[0328] The device displays the expert advice on the user's dashboard.

[0329] Step 23:

[0330] Users can view expert advice on the dashboard and take appropriate action.

[0331] Example 2

[0332] 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."

[0333] Conventional financial management systems are unable to consider the user's emotional state when inputting and analyzing financial data, making it difficult to provide optimal advice and reports. Furthermore, expert advice is provided without regard to the user's emotional state, making it difficult to say that it provides optimal support for user decision-making. There is a need to solve these problems and provide more personalized services to users.

[0334] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0335] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, an emotion engine for recognizing the emotional state of the user, and means for adjusting the report content based on the emotional state recognized by the emotion engine. This makes it possible to provide personalized reports and advice that take the user's emotions into consideration.

[0336] "Financial Data" refers to information related to a user's economic activities, such as income, expenses, investment accounts, and credit card information.

[0337] "Means for input or integration" refers to API integration that allows users to manually input financial data or automatically obtain data from external services.

[0338] "Means for storing" means a database or storage system for securely storing received financial data.

[0339] "AI engine" refers to software that uses artificial intelligence technology to analyze financial data and predict a user's financial situation.

[0340] "Means of analysis" refers to the process of sending financial data to an AI engine to analyze income, expenses, investment patterns, etc.

[0341] "Means for generating a report" refers to the process of creating a report in a visually easy-to-understand format for the user based on the analysis results of the AI ​​engine.

[0342] "Means for providing to user" refers to the process of displaying the generated report on the user's dashboard so that the user can easily access it.

[0343] An "emotion engine" refers to a software system that analyzes a user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[0344] "Means for adjusting report content based on emotional state" refers to a process for optimizing the presentation method and content of a report according to the emotional state of the user recognized by the emotion engine.

[0345] "Means for consulting an expert" refers to the process by which a user submits a request for advice from an expert based on the results of AI analysis.

[0346] "Means for providing expert advice to users" refers to the process by which the server receives the advice prepared by the expert and displays it on the user's dashboard.

[0347] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' financial decision-making. In addition, by combining it with an emotion engine that recognizes users' emotions, it is possible to provide more personalized advice and services.

[0348] Overall system configuration

[0349] This system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine is responsible for recognizing the user's emotions. The expert is responsible for providing final advice.

[0350] User registration and authentication

[0351] A user accesses the system and opens the new account creation page. They enter the required information, such as their name, email address, and password, and click the submit button. The user's device sends the entered information to the server. The server stores the received information in a database, generates a confirmation email, and sends it to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[0352] Financial data input and integration

[0353] Users open a page to enter their bank account, investment account, and credit card information. They enter the required information and click the submit button. Financial data can also be automatically retrieved from external services using API integration. The user's device sends the entered or retrieved data to the server. The server stores the financial data in a database in a secure manner.

[0354] AI analysis and report generation

[0355] The server sends the stored financial data to the AI ​​engine, which analyzes income, expenses, investment patterns, etc. and generates predictions. Based on the analysis results received from the AI ​​engine, the server generates reports in an easy-to-understand format and displays them on the user's dashboard.

[0356] Providing expert advice

[0357] Based on the analysis results, the user clicks the "Request Expert Advice" button. The user's device sends the request to the server. The server automatically selects an appropriate expert and sends the user's financial data and the AI ​​analysis results to the expert. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[0358] Emotion Engine Functions

[0359] As users use the system, the emotion engine analyzes their facial expressions, voice, and input in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[0360] Specific examples

[0361] For example, when a user connects their bank and investment accounts to the system, they first enter their account information or set up API integration. The user's device then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, spending, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0362] Furthermore, the emotion engine recognizes the user's emotional state and adjusts the report display to be simple and easy to understand if the user is feeling stressed. Expert advice is also tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, while if the user is calm, it will provide a detailed investment plan.

[0363] Prompt Sentence Examples

[0364] "Analyze my bank and investment account data and create reports based on my income, expenses, and investment trends. Optimize the display based on my current emotional state."

[0365] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0366] Step 1:

[0367] User registration and authentication

[0368] User: Accesses the system, enters their name, email address, and password on the new account creation page, and clicks the "Submit" button.

[0369] Input: Name, Email Address, Password.

[0370] Output: Form submission data.

[0371] Terminal: Sends the entered information to the server.

[0372] Input: Form submission data.

[0373] Output: The request to the server.

[0374] Server: Stores the received information in a database and generates a confirmation email to send to the user.

[0375] Input: User information.

[0376] Output: A confirmation email.

[0377] User: Clicks on the link in the confirmation email.

[0378] Enter: Confirmation email.

[0379] Output: The authentication request.

[0380] Server: Detects that the link was clicked and updates the user's account to an authenticated state.

[0381] Input: Authentication request.

[0382] Output: Account authentication successful.

[0383] Step 2:

[0384] Financial data input and integration

[0385] User: Visits a page to enter bank account, investment account, or credit card information, enters the required information, and clicks the "Submit" button. Users can also set up API integrations to automatically retrieve financial data from external services.

[0386] Input: Bank account information, investment account information, credit card information.

[0387] Output: Form submission data, API setting information.

[0388] Terminal: Sends input or acquired data to the server.

[0389] Input: Form submission data, API setting information.

[0390] Output: The request to the server.

[0391] Server: Receives financial data and stores it in a database in a secure manner.

[0392] Input: Financial data.

[0393] Output: Stored financial data.

[0394] Step 3:

[0395] AI analysis and report generation

[0396] Server: Sends the stored financial data to the AI ​​engine.

[0397] Input: Stored financial data.

[0398] Output: The request to the AI ​​Engine.

[0399] AI Engine: Analyzes financial data and generates predictions based on users' income, expenses, and investment patterns.

[0400] Input: Financial data.

[0401] Output: Analysis results.

[0402] Server: Based on the analysis results received from the AI ​​engine, it generates reports in an easy-to-understand format and displays them on the user's dashboard.

[0403] Input: Analysis results.

[0404] Output: Report.

[0405] Step 4:

[0406] Providing expert advice

[0407] User: Based on the analysis results, clicks the "Seek Expert Advice" button.

[0408] Input: Analysis results.

[0409] Output: Advice request.

[0410] Terminal: Sends the request to the server.

[0411] Input: Advice request.

[0412] Output: The request to the server.

[0413] Server: Automatically selects the appropriate expert and sends the user's financial data and the results of AI analysis to the expert.

[0414] Input: Advice request, financial data, AI analysis results.

[0415] Output: Request for expert.

[0416] Expert: Creates specific advice based on the information provided and sends it to the server.

[0417] Input: Financial data, AI analysis results.

[0418] Output: Advice.

[0419] Server: Provides expert advice to users on their dashboard.

[0420] Enter: Advice.

[0421] Output: Dashboard update.

[0422] Step 5:

[0423] Emotion Engine Functions

[0424] User: While using the system, the emotion engine analyzes facial expressions, voice, and input in real time.

[0425] Input: facial expressions, voice, input content.

[0426] Output: Emotion data.

[0427] Emotion engine: Recognizes the user's emotional state and sends the results to the server.

[0428] Input: Emotion data.

[0429] Output: Emotional state.

[0430] Server: Tailors financial reports and expert advice based on information from the sentiment engine.

[0431] Input: Emotional state.

[0432] Output: Tailored reports and advice.

[0433] (Application example 2)

[0434] 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."

[0435] Conventional financial data management systems can efficiently manage users' financial data and provide predictions and expert advice based on AI analysis, but they have difficulty taking the user's emotional state into account. As a result, they are unable to provide appropriate advice based on the user's emotions, and are unable to provide effective support in situations where the user feels stressed or anxious. Therefore, there is a growing need for a system that can recognize the user's emotional state in real time and provide personalized financial advice accordingly.

[0436] 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.

[0437] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to a user, means for acquiring the user's emotional state, means for adjusting the report based on the acquired emotional state, and means for customizing expert advice based on the emotional state, thereby making it possible to provide personalized advice and services according to the user's emotional state.

[0438] "Financial Data" means information about your income, expenses, investments and assets.

[0439] "Input means" refers to interfaces and devices through which users input financial data.

[0440] "Storage means" refers to a database or storage system for securely storing input financial data.

[0441] The "AI engine" is an artificial intelligence program that analyzes stored financial data and makes predictions about the user's financial status and future prospects.

[0442] "Analysis means" refers to the functions and programs that enable the AI ​​engine to process financial data and derive analytical results.

[0443] "Report generation means" refers to a device or function that creates a report to be provided to the user based on the results of AI analysis.

[0444] "Providing means" refers to a means for displaying or notifying the user of the generated report or expert advice.

[0445] "Emotional state" refers to a psychological state that is inferred based on the user's facial expression, voice, and input content.

[0446] "Acquisition means" refers to sensors and software for acquiring the user's emotional state.

[0447] The "adjustment means" is a function for changing the content of reports and advice based on the acquired emotional state.

[0448] "Expert advice" means guidance or recommendations provided by a professional with financial or investment knowledge.

[0449] "Means for customization" refers to a function that allows the content of expert advice to be appropriately adjusted according to the user's emotional state.

[0450] The system of the present invention aims to support users in making economic decisions by allowing them to efficiently manage their financial data and receive AI analysis results and expert advice. In addition, by combining it with an emotion engine, it is possible to provide personalized advice and services according to the user's emotional state.

[0451] Overall system configuration

[0452] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotional state. The expert provides final advice.

[0453] User registration and authentication

[0454] A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[0455] Financial data input and integration

[0456] Users enter bank account, investment account, and credit card information into the system. Financial data can also be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server. The server receives the financial data and stores it in a database in a secure manner.

[0457] AI analysis and report generation

[0458] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0459] Providing expert advice

[0460] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[0461] Emotion Engine Functions

[0462] While a user is using the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[0463] Specific examples

[0464] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0465] Furthermore, the emotion engine recognizes the user's emotional state, and if the user is stressed, for example, the report display will be adjusted to be simple and easy to understand. Expert advice will also be tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, and if the user is calm, it will provide a detailed investment plan.

[0466] Example prompts to be input to the generative AI model

[0467] The system uses a camera to capture the user's facial expressions and performs emotion recognition to determine the user's emotional state. Based on the acquired emotional state, an AI engine analyzes financial data and generates financial advice that takes into account the user's recent spending patterns and income situation. The expert advice is also customized according to the user's emotional state, such as encouraging conservative spending when the user is nervous, or providing a detailed investment plan when the user is relaxed.

[0468] The above is an embodiment of the present invention, which provides personalized financial advice based on the user's emotional state, enabling more effective financial decision-making.

[0469] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0470] Step 1:

[0471] A user creates a new account, enters the required information (name, email address, password) and submits the registration form. The input is made through the user's terminal, and this information is sent as output to the server.

[0472] Step 2:

[0473] The server stores the received user information in a database and sends a confirmation email to the user, which includes an authentication link. Data processing involves storing the information, generating and sending the confirmation email.

[0474] Step 3:

[0475] The user clicks on the link in the confirmation email and the server completes the account authentication. The input is the user's click, and the output is the authenticated account being enabled.

[0476] Step 4:

[0477] Users enter their bank account, investment account, and credit card information into the system. This information is sent from the user's device to the server. Financial data can also be automatically retrieved from external services via API integration.

[0478] Step 5:

[0479] The server receives and securely stores the user's financial data, which is a combination of data entered and data from external services.

[0480] Step 6:

[0481] The server sends the stored financial data to the AI ​​engine. The input is the stored financial data, and the output is the analysis results by the AI ​​engine.

[0482] Step 7:

[0483] The AI ​​engine analyzes users' income, expenditure, and investment patterns to generate predictions. Data processing uses pattern recognition, statistical analysis, and predictive algorithms.

[0484] Step 8:

[0485] The server receives the analysis results from the AI ​​engine and generates reports for display on the user's dashboard, including visualizations and summaries of the analysis results.

[0486] Step 9:

[0487] The user sends a request for expert advice based on the analysis results from the terminal to the server. The input is the user's request, and the request information is saved on the server as the output.

[0488] Step 10:

[0489] The server selects an appropriate expert and provides the user's financial data and the AI ​​analysis results. The input is the user's request and the analysis results, and the output is information provided to the expert.

[0490] Step 11:

[0491] The expert creates advice based on the provided information and sends it to the server. The input is the information received by the expert, and the output is specific advice.

[0492] Step 12:

[0493] The server provides the expert advice for display on the user's dashboard, where the advice is displayed on the user's device.

[0494] Step 13:

[0495] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time and sends the emotional state to the server. The input is the user's emotional data, and the output is the recognized emotional state.

[0496] Step 14:

[0497] The server adjusts the financial reports and expert advice based on the information from the emotion engine, adjusting the display and advice accordingly depending on the emotional state.

[0498] Step 15:

[0499] Users receive tailored reports and advice, enabling them to make more effective financial decisions. The output is personalized financial advice.

[0500] 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.

[0501] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0502] 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.

[0503] [Second embodiment]

[0504] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0505] 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.

[0506] 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).

[0507] 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.

[0508] 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.

[0509] 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).

[0510] 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.

[0511] 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.

[0512] 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.

[0513] 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.

[0514] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0515] 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."

[0516] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' economic decision-making. Specific embodiments of this system are described in detail below.

[0517] Overall system configuration

[0518] The system basically consists of a user's device, a server, an AI engine, and an expert. The user's device provides the interface that the user operates, while the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the expert provides final advice.

[0519] User registration and authentication

[0520] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[0521] Terminal: The user's terminal sends the entered information to the server.

[0522] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[0523] Financial data input and integration

[0524] Users: Users enter their bank account, investment account, and credit card information into the system, with the option to automatically retrieve financial data through API integration with external services.

[0525] Terminal: The user's terminal sends the entered or acquired data to the server.

[0526] Server: The server receives the financial data and stores it in a secure database.

[0527] AI analysis and report generation

[0528] Server: The server sends the stored financial data to the AI ​​engine.

[0529] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[0530] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0531] Providing expert advice

[0532] User: The user submits a request for expert advice based on the analysis results.

[0533] Terminal: The user's terminal sends the request to the server.

[0534] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[0535] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[0536] Server: The server displays expert advice on the user's dashboard.

[0537] Specific examples

[0538] For example, consider a case where a user connects their bank account and investment account to the system. The user first enters their account information or sets up API connection. The system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[0539] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[0540] The processing flow will be explained below.

[0541] Step 1:

[0542] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[0543] Step 2:

[0544] The terminal transmits the input user information to the server.

[0545] Step 3:

[0546] The server stores the received user information in a database and sends a confirmation email to the user.

[0547] Step 4:

[0548] The user clicks on the link contained in the confirmation email to verify their email address.

[0549] Step 5:

[0550] The server verifies that the user clicked on the link and completes the account authentication.

[0551] Step 6:

[0552] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[0553] Step 7:

[0554] The terminal transmits the entered financial information and data obtained from the external service to the server.

[0555] Step 8:

[0556] The server stores the received financial data in a secure database.

[0557] Step 9:

[0558] The server sends the stored financial data to the AI ​​engine.

[0559] Step 10:

[0560] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[0561] Step 11:

[0562] The server receives the analysis results from the AI ​​engine and generates a report.

[0563] Step 12:

[0564] The terminal displays the generated report on the user's dashboard.

[0565] Step 13:

[0566] The user reviews the report and submits a request for further expert advice.

[0567] Step 14:

[0568] The terminal transmits the user's request to the server.

[0569] Step 15:

[0570] The server selects the appropriate expert based on the user's financial data and the results of AI analysis.

[0571] Step 16:

[0572] The server transmits the user's financial data and analysis results to the selected expert.

[0573] Step 17:

[0574] The expert creates specific advice based on the received data and sends the advice to the server.

[0575] Step 18:

[0576] The server receives the advice from the experts and displays it on the user's dashboard.

[0577] Step 19:

[0578] Users can view expert advice on the dashboard and take appropriate action.

[0579] Example 1

[0580] 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."

[0581] Conventional financial data management systems lack analytical functions and specific advice from experts to effectively support users' financial decision-making. Furthermore, they lack sufficient automation of data integration and analysis processes, making them difficult for users to use. Furthermore, it is difficult to integrate with external services, making it difficult to centrally manage multiple pieces of financial information.

[0582] 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.

[0583] In this invention, the server includes a means for inputting or linking financial data, a means for saving the input financial data, and a means for sending the saved financial data to an AI engine for analysis. This includes a means for a user to create a new account, a means for the server to send a confirmation email and authenticate the account, a means for providing the generated report to the user, a means for the user to send a request for expert advice, a means for the server to select an appropriate expert and provide the user's financial data and AI analysis results, a means for the expert to provide advice, a means for the server to display the advice on the user's dashboard, an API integration means for linking with external services, a means for saving financial data obtained from external services and using it for analysis, and a means for the user's device to send input information to the server via an HTTP POST request. This configuration allows users to easily create accounts, efficiently manage and analyze their financial data, and further enables them to make appropriate economic decisions by receiving specific advice from experts.

[0584] "Financial data" refers to data such as income, expenditure, and investment information obtained by a user from financial institutions, investment institutions, and the like.

[0585] "Means for input or linking" refers to means by which a user manually inputs data or automatically obtains data from an external service via an API.

[0586] "Means of storage" refers to a database for securely storing received data and the associated security mechanisms.

[0587] An "AI engine" is an artificial intelligence model that analyzes a user's financial data and predicts income, expenses, investment patterns, etc.

[0588] The "means for generating a report" refers to a means for visually displaying the analysis results by the AI ​​engine in a format that is easy for the user to understand.

[0589] The "means for creating an account" is a mechanism that allows a new user to create an account by entering their name, email address, password, etc.

[0590] The "means for sending a confirmation email" is a mechanism for sending a confirmation email to the email address entered during user registration and providing an authentication link.

[0591] The "account authentication method" is a mechanism by which a user activates their account by clicking a link in a confirmation email.

[0592] "Means for consulting with experts" refers to a system in which users can send requests for advice to experts based on the results of AI analysis.

[0593] The "means for providing advice from experts" is a mechanism for displaying advice provided by experts to the user.

[0594] "API integration means" is a mechanism that uses APIs to automatically obtain data by linking with external financial services and investment services.

[0595] An "HTTP POST request" is a request format that uses the HTTP protocol to send data from a terminal to a server.

[0596] The "dashboard" is a user interface that centrally displays the user's financial situation, AI analysis results, and advice from experts.

[0597] The system of the present invention efficiently manages users' financial data and supports their economic decision-making by providing AI analysis results and expert advice. This system consists of a user's terminal, a server, an AI engine, and experts.

[0598] User registration and authentication

[0599] Submit account creation request

[0600] The user accesses the system's registration page through a web browser, enters their name, email address, and password, and clicks the "Register" button.

[0601] The device constructs the input data in JSON format and sends an HTTP POST request to the server.

[0602] Save user data and send confirmation email

[0603] The server stores the received user data in an SQL database and uses the Python smtplib library to send a confirmation email containing an authentication link to the user.

[0604] Account authentication completed

[0605] The user clicks on the verification link in the email.

[0606] The server validates the token contained in the link and activates the corresponding user's account.

[0607] Financial data input and integration

[0608] Financial data entry request submission

[0609] A user enters bank account, investment account, and credit card information in a web browser and clicks the submit button.

[0610] The device sends the input data to the server via an HTTP POST request.

[0611] Financial Data Storage

[0612] The server stores the received financial data in a secure SQL database.

[0613] AI analysis and report generation

[0614] Data analysis request submission

[0615] The server periodically sends the stored financial data to the AI ​​engine.

[0616] Data analysis

[0617] The AI ​​engine analyzes the user's income, expenditure, and investment patterns and generates predictions.

[0618] Report Generation

[0619] The server receives the analysis results from the AI ​​engine, generates user-friendly reports using HTML and JavaScript, and displays them on the user's dashboard.

[0620] Providing expert advice

[0621] Submit an advice request

[0622] The user clicks a button on the dashboard to send a request for expert advice.

[0623] The device sends the request to the server via an HTTP POST request.

[0624] Selection of experts and provision of data

[0625] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel.

[0626] Creating and providing advice

[0627] Experts create specific advice based on the information provided and send it to the server via a dedicated management interface.

[0628] The server displays the received advice on the user's dashboard.

[0629] Example operation

[0630] For example, consider a case where a user connects their bank account and investment account to the system. After the user enters their account information or sets up API connection, the system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[0631] Prompt Sentence Examples

[0632] By inputting prompt statements into the generative AI model as shown below, specific advice and analysis results can be obtained.

[0633] Sample prompt 1: "Please tell me the breakdown of your income and expenses this month."

[0634] Sample prompt 2: "Predict your investment performance over the next six months."

[0635] Sample prompt 3: "I'd like some advice on effective ways to save money."

[0636] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[0637] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0638] Step 1:

[0639] A user accesses the system's registration page, enters their name, email address, and password, and clicks the "Register" button. The input data includes their name, email address, and password. This generates a request to create a new account.

[0640] Step 2:

[0641] The device constructs the input data in JSON format and sends an HTTP POST request to the server, which includes the user's name, email address, and password, and sends the new user information to the server.

[0642] Step 3:

[0643] The server receives the HTTP POST request, extracts user information from the request body, stores the extracted data in an SQL database by executing an insert query, and sends a confirmation email to the user's email address using the SMTP protocol. The confirmation email contains a link to verify the account.

[0644] Step 4:

[0645] The user opens the confirmation email they received and clicks on the authentication link in the email, which sends an account authentication request to the server.

[0646] Step 5:

[0647] The server verifies the token in the authentication link and updates the status of the corresponding user account to enabled, which means the user account is authenticated and ready for use.

[0648] Step 6:

[0649] After logging in, users enter their bank account, investment account, and credit card information, or use this information as input data to set up API integration with external services. After entering the information, they click the "Submit" button.

[0650] Step 7:

[0651] The terminal constructs the entered financial data in JSON format and sends an HTTP POST request to the server, containing the user's bank account, investment account, and credit card information.

[0652] Step 8:

[0653] The server receives the HTTP POST request, extracts financial data from the request body, and stores the extracted data securely in an SQL database for analysis.

[0654] Step 9:

[0655] The server periodically sends the stored financial data to the AI ​​engine, including the user's income, expenditure, and investment patterns.

[0656] Step 10:

[0657] The AI ​​engine analyzes the received financial data and generates forecasts for income, expenditure, and investment patterns. It uses machine learning algorithms to analyze the data and applies predictive models. The forecasts are then output as a report.

[0658] Step 11:

[0659] The server receives the analysis results from the AI ​​engine and generates a report using HTML and JavaScript. The generated report is displayed on the user's dashboard, allowing the user to check their financial status based on the analysis results.

[0660] Step 12:

[0661] A user clicks a button on the dashboard to send a request for expert advice, which includes the analysis results.

[0662] Step 13:

[0663] The device sends a request to the server via an HTTP POST request, which includes the user's financial data and the analysis results.

[0664] Step 14:

[0665] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel. The data provided to the expert includes the user's income, expenses, and investment patterns.

[0666] Step 15:

[0667] Experts create specific advice based on the information provided, and the advice is sent to the server via a dedicated management interface.

[0668] Step 16:

[0669] The server receives the advice provided by the experts and displays it on the user's dashboard, allowing the user to make appropriate financial decisions based on the expert advice.

[0670] (Application example 1)

[0671] 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."

[0672] Today's consumers make many of their daily payments and transactions electronically, resulting in a vast and complex amount of financial data. It is difficult to manually manage this vast amount of data and develop appropriate financial management and investment strategies. There is also a lack of ways to analyze financial data in real time or quickly obtain appropriate prescriptions from experts. This makes it difficult for consumers to make optimal financial decisions.

[0673] 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.

[0674] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to the user, means for automatically synchronizing payment information, and means for performing AI analysis in real time, thereby enabling users to analyze massive amounts of financial data in real time and receive prompt and appropriate advice from experts.

[0675] "Financial Data" means information about the economic activities of an individual or entity, including information about income, expenses, investments, assets, and liabilities.

[0676] An "AI engine" is a system that uses artificial intelligence algorithms to analyze data and make predictions.

[0677] A "report" is information such as detailed documents and graphs that are generated based on financial data and the results of that analysis and are provided to users.

[0678] "Payment information" is detailed data about payments made by a user, including information such as date, amount, and category.

[0679] "Synchronization" is the process of updating and matching data between different systems or devices in real time or periodically.

[0680] An "expert" is someone with advanced knowledge and experience in a particular field, in this case, an expert in the fields of finance and economics.

[0681] "Auto-email" is a feature that allows the system to automatically send emails based on specific conditions.

[0682] "API integration" refers to different software systems exchanging information and working together via an application programming interface (API).

[0683] "Real-time analysis" is the process of analyzing the latest data immediately and providing the results almost instantly.

[0684] An embodiment of the present invention includes a system for efficiently managing financial data and providing AI analysis results and expert advice. This system is composed of a user terminal, a server, an AI engine, and experts.

[0685] User registration and authentication

[0686] A user accesses the system to create a new account. They enter the required information (name, email address, password) and submit the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[0687] Financial data input and integration

[0688] Users enter their bank account, investment account, and credit card information into the system. Optionally, financial data can be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[0689] Automatic payment synchronization

[0690] Each time a user makes an electronic payment, payment information is automatically sent by the user's terminal to the server, which stores this data in a real-time database and keeps the financial data up to date.

[0691] AI analysis and report generation

[0692] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0693] Providing expert advice

[0694] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results using an automatic email sending function. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[0695] Hardware and software used

[0696] 1. Hardware: The server uses cloud infrastructure (e.g., AWS or GCP).

[0697] 2. Software:

[0698] Django (Web framework)

[0699] SciKit-Learn (machine learning library)

[0700] Specific examples of processing

[0701] For example, when a user connects their bank account and investment account to the system, they first enter their account information or set up API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request advice from an expert based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[0702] Prompt Sentence Examples

[0703] The following transaction was entered for user "example_user". A transaction of 150 yen for food was made on 2023-10-10. Please make a prediction based on the next transaction. The next transaction date is assumed to be 10 days later.

[0704] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0705] Step 1:

[0706] A user accesses the system and creates a new account. The user enters their name, email address, and password, and submits the registration form. This information is sent from the user's device to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[0707] Input: User's name, email address, and password

[0708] Output: Sends a confirmation email, saves user information to the database

[0709] Step 2:

[0710] Users log in to the system and enter their bank account, investment account, and credit card information. Optionally, they can set up API integration with external services to automatically retrieve financial data. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[0711] Input: Bank account, investment account, credit card information, API connection settings

[0712] Output: Saving financial data to a database

[0713] Step 3:

[0714] Every time a user makes an electronic payment, payment information is automatically sent from the user's device to the server, which stores this data in a real-time database, keeping financial data up to date.

[0715] Input: Payment information (date, time, amount, category)

[0716] Output: Real-time updated financial data storage

[0717] Step 4:

[0718] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. This analysis can use, for example, a linear regression model from SciKit-Learn. Once the analysis is complete, the results are sent to the server.

[0719] Input: Stored financial data

[0720] Output: Prediction results

[0721] Step 5:

[0722] The server receives the analysis results from the AI ​​engine and generates an easy-to-understand report, which is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0723] Input: Analysis results from the AI ​​engine

[0724] Output: Report, display on user dashboard

[0725] Step 6:

[0726] The user sends a request for advice from an expert based on the analysis results. The user's device then sends the request to the server. The server then selects an appropriate expert and provides the user's financial data and the AI ​​analysis results using an automatic email sending function.

[0727] Input: User advice request

[0728] Output: Automatic email to the expert

[0729] Step 7:

[0730] The expert creates specific advice based on the provided information and sends it to the server, which then displays the advice on the user's dashboard, allowing the user to receive specific guidance on appropriate investment strategies and savings methods.

[0731] Input: Expert advice

[0732] Output: Display on user dashboard

[0733] 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.

[0734] The system of the present invention efficiently manages a user's financial data and provides AI-based analysis results and expert advice to support the user's financial decision-making. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized advice and services. Specific embodiments of this system are described in detail below.

[0735] Overall system configuration

[0736] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotions. The expert provides final advice.

[0737] User registration and authentication

[0738] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[0739] Terminal: The user's terminal sends the entered information to the server.

[0740] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[0741] Financial data input and integration

[0742] Users: Users enter their bank account, investment account, and credit card information into the system, and can also use API integration with external services to automatically retrieve financial data.

[0743] Terminal: The user's terminal sends the entered or acquired data to the server.

[0744] Server: The server receives the financial data and stores it in a secure database.

[0745] AI analysis and report generation

[0746] Server: The server sends the stored financial data to the AI ​​engine.

[0747] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[0748] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0749] Providing expert advice

[0750] User: The user submits a request for expert advice based on the analysis results.

[0751] Terminal: The user's terminal sends the request to the server.

[0752] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[0753] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[0754] Server: The server displays expert advice on the user's dashboard.

[0755] Emotion Engine Functions

[0756] User: As the user uses the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time.

[0757] Emotion Engine: The emotion engine recognizes the user's emotional state and sends the result to the server.

[0758] Server: The server adjusts financial reports and expert advice based on information from the sentiment engine.

[0759] Specific examples

[0760] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0761] Furthermore, the emotion engine can recognize a user's emotional state and adjust the report display to be simple and easy to understand if the user is stressed. Expert advice can also be tailored to the user's emotions, suggesting a low-risk investment strategy if the user is excited, or offering a detailed investment plan if the user is calm.

[0762] As described above, the present invention is a system that supports users' economic decision-making through efficient management and analysis of financial data, and by combining it with an emotion engine, it is possible to provide more personalized advice and services.

[0763] The processing flow will be explained below.

[0764] Step 1:

[0765] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[0766] Step 2:

[0767] The terminal transmits the input user information to the server.

[0768] Step 3:

[0769] The server stores the received user information in a database and sends a confirmation email to the user.

[0770] Step 4:

[0771] The user clicks on the link contained in the confirmation email to verify their email address.

[0772] Step 5:

[0773] The server verifies that the user clicked on the link and completes the account authentication.

[0774] Step 6:

[0775] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[0776] Step 7:

[0777] The terminal transmits the entered financial information and data obtained from the external service to the server.

[0778] Step 8:

[0779] The server stores the received financial data in a secure database.

[0780] Step 9:

[0781] The server sends the stored financial data to the AI ​​engine.

[0782] Step 10:

[0783] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[0784] Step 11:

[0785] The server receives the analysis results from the AI ​​engine and generates a report.

[0786] Step 12:

[0787] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[0788] Step 13:

[0789] The emotion engine sends the recognized emotional state to the server.

[0790] Step 14:

[0791] The server adjusts the display of the financial report based on the information from the emotion engine.

[0792] Step 15:

[0793] The terminal displays the generated report on the user's dashboard, reflecting the adjusted display content.

[0794] Step 16:

[0795] The user reviews the report and submits a request for further expert advice.

[0796] Step 17:

[0797] The terminal transmits the user's request to the server.

[0798] Step 18:

[0799] The server selects the appropriate expert and provides the user's financial data and AI analysis results.

[0800] Step 19:

[0801] The expert creates specific advice based on the provided information and sends it to the server.

[0802] Step 20:

[0803] The server receives expert advice and tailors it to the user.

[0804] Step 21:

[0805] The server adjusts the expert advice based on the information from the emotion engine and displays it on the user's dashboard.

[0806] Step 22:

[0807] The device displays the expert advice on the user's dashboard.

[0808] Step 23:

[0809] Users can view expert advice on the dashboard and take appropriate action.

[0810] Example 2

[0811] 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."

[0812] Conventional financial management systems are unable to consider the user's emotional state when inputting and analyzing financial data, making it difficult to provide optimal advice and reports. Furthermore, expert advice is provided without regard to the user's emotional state, making it difficult to say that it provides optimal support for user decision-making. There is a need to solve these problems and provide more personalized services to users.

[0813] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0814] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, an emotion engine for recognizing the emotional state of the user, and means for adjusting the report content based on the emotional state recognized by the emotion engine. This makes it possible to provide personalized reports and advice that take the user's emotions into consideration.

[0815] "Financial Data" refers to information related to a user's economic activities, such as income, expenses, investment accounts, and credit card information.

[0816] "Means for input or integration" refers to API integration that allows users to manually input financial data or automatically obtain data from external services.

[0817] "Means for storing" means a database or storage system for securely storing received financial data.

[0818] "AI engine" refers to software that uses artificial intelligence technology to analyze financial data and predict a user's financial situation.

[0819] "Means of analysis" refers to the process of sending financial data to an AI engine to analyze income, expenses, investment patterns, etc.

[0820] "Means for generating a report" refers to the process of creating a report in a visually easy-to-understand format for the user based on the analysis results of the AI ​​engine.

[0821] "Means for providing to user" refers to the process of displaying the generated report on the user's dashboard so that the user can easily access it.

[0822] An "emotion engine" refers to a software system that analyzes a user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[0823] "Means for adjusting report content based on emotional state" refers to a process for optimizing the presentation method and content of a report according to the emotional state of the user recognized by the emotion engine.

[0824] "Means for consulting an expert" refers to the process by which a user submits a request for advice from an expert based on the results of AI analysis.

[0825] "Means for providing expert advice to users" refers to the process by which the server receives the advice prepared by the expert and displays it on the user's dashboard.

[0826] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' financial decision-making. In addition, by combining it with an emotion engine that recognizes users' emotions, it is possible to provide more personalized advice and services.

[0827] Overall system configuration

[0828] This system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine is responsible for recognizing the user's emotions. The expert is responsible for providing final advice.

[0829] User registration and authentication

[0830] A user accesses the system and opens the new account creation page. They enter the required information, such as their name, email address, and password, and click the submit button. The user's device sends the entered information to the server. The server stores the received information in a database, generates a confirmation email, and sends it to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[0831] Financial data input and integration

[0832] Users open a page to enter their bank account, investment account, and credit card information. They enter the required information and click the submit button. Financial data can also be automatically retrieved from external services using API integration. The user's device sends the entered or retrieved data to the server. The server stores the financial data in a database in a secure manner.

[0833] AI analysis and report generation

[0834] The server sends the stored financial data to the AI ​​engine, which analyzes income, expenses, investment patterns, etc. and generates predictions. Based on the analysis results received from the AI ​​engine, the server generates reports in an easy-to-understand format and displays them on the user's dashboard.

[0835] Providing expert advice

[0836] Based on the analysis results, the user clicks the "Request Expert Advice" button. The user's device sends the request to the server. The server automatically selects an appropriate expert and sends the user's financial data and the AI ​​analysis results to the expert. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[0837] Emotion Engine Functions

[0838] As users use the system, the emotion engine analyzes their facial expressions, voice, and input in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[0839] Specific examples

[0840] For example, when a user connects their bank and investment accounts to the system, they first enter their account information or set up API integration. The user's device then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, spending, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0841] Furthermore, the emotion engine recognizes the user's emotional state and adjusts the report display to be simple and easy to understand if the user is feeling stressed. Expert advice is also tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, while if the user is calm, it will provide a detailed investment plan.

[0842] Prompt Sentence Examples

[0843] "Analyze my bank and investment account data and create reports based on my income, expenses, and investment trends. Optimize the display based on my current emotional state."

[0844] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0845] Step 1:

[0846] User registration and authentication

[0847] User: Accesses the system, enters their name, email address, and password on the new account creation page, and clicks the "Submit" button.

[0848] Input: Name, Email Address, Password.

[0849] Output: Form submission data.

[0850] Terminal: Sends the entered information to the server.

[0851] Input: Form submission data.

[0852] Output: The request to the server.

[0853] Server: Stores the received information in a database and generates a confirmation email to send to the user.

[0854] Input: User information.

[0855] Output: A confirmation email.

[0856] User: Clicks on the link in the confirmation email.

[0857] Enter: Confirmation email.

[0858] Output: The authentication request.

[0859] Server: Detects that the link was clicked and updates the user's account to an authenticated state.

[0860] Input: Authentication request.

[0861] Output: Account authentication successful.

[0862] Step 2:

[0863] Financial data input and integration

[0864] User: Visits a page to enter bank account, investment account, or credit card information, enters the required information, and clicks the "Submit" button. Users can also set up API integrations to automatically retrieve financial data from external services.

[0865] Input: Bank account information, investment account information, credit card information.

[0866] Output: Form submission data, API setting information.

[0867] Terminal: Sends input or acquired data to the server.

[0868] Input: Form submission data, API setting information.

[0869] Output: The request to the server.

[0870] Server: Receives financial data and stores it in a database in a secure manner.

[0871] Input: Financial data.

[0872] Output: Stored financial data.

[0873] Step 3:

[0874] AI analysis and report generation

[0875] Server: Sends the stored financial data to the AI ​​engine.

[0876] Input: Stored financial data.

[0877] Output: The request to the AI ​​Engine.

[0878] AI Engine: Analyzes financial data and generates predictions based on users' income, expenses, and investment patterns.

[0879] Input: Financial data.

[0880] Output: Analysis results.

[0881] Server: Based on the analysis results received from the AI ​​engine, it generates reports in an easy-to-understand format and displays them on the user's dashboard.

[0882] Input: Analysis results.

[0883] Output: Report.

[0884] Step 4:

[0885] Providing expert advice

[0886] User: Based on the analysis results, clicks the "Seek Expert Advice" button.

[0887] Input: Analysis results.

[0888] Output: Advice request.

[0889] Terminal: Sends the request to the server.

[0890] Input: Advice request.

[0891] Output: The request to the server.

[0892] Server: Automatically selects the appropriate expert and sends the user's financial data and the results of AI analysis to the expert.

[0893] Input: Advice request, financial data, AI analysis results.

[0894] Output: Request for expert.

[0895] Expert: Creates specific advice based on the information provided and sends it to the server.

[0896] Input: Financial data, AI analysis results.

[0897] Output: Advice.

[0898] Server: Provides expert advice to users on their dashboard.

[0899] Enter: Advice.

[0900] Output: Dashboard update.

[0901] Step 5:

[0902] Emotion Engine Functions

[0903] User: While using the system, the emotion engine analyzes facial expressions, voice, and input in real time.

[0904] Input: facial expressions, voice, input content.

[0905] Output: Emotion data.

[0906] Emotion engine: Recognizes the user's emotional state and sends the results to the server.

[0907] Input: Emotion data.

[0908] Output: Emotional state.

[0909] Server: Tailors financial reports and expert advice based on information from the sentiment engine.

[0910] Input: Emotional state.

[0911] Output: Tailored reports and advice.

[0912] (Application example 2)

[0913] 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."

[0914] Conventional financial data management systems can efficiently manage users' financial data and provide predictions and expert advice based on AI analysis, but they have difficulty taking the user's emotional state into account. As a result, they are unable to provide appropriate advice based on the user's emotions, and are unable to provide effective support in situations where the user feels stressed or anxious. Therefore, there is a growing need for a system that can recognize the user's emotional state in real time and provide personalized financial advice accordingly.

[0915] 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.

[0916] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to a user, means for acquiring the user's emotional state, means for adjusting the report based on the acquired emotional state, and means for customizing expert advice based on the emotional state, thereby making it possible to provide personalized advice and services according to the user's emotional state.

[0917] "Financial Data" means information about your income, expenses, investments and assets.

[0918] "Input means" refers to interfaces and devices through which users input financial data.

[0919] "Storage means" refers to a database or storage system for securely storing input financial data.

[0920] The "AI engine" is an artificial intelligence program that analyzes stored financial data and makes predictions about the user's financial status and future prospects.

[0921] "Analysis means" refers to the functions and programs that enable the AI ​​engine to process financial data and derive analytical results.

[0922] "Report generation means" refers to a device or function that creates a report to be provided to the user based on the results of AI analysis.

[0923] "Providing means" refers to a means for displaying or notifying the user of the generated report or expert advice.

[0924] "Emotional state" refers to a psychological state that is inferred based on the user's facial expression, voice, and input content.

[0925] "Acquisition means" refers to sensors and software for acquiring the user's emotional state.

[0926] The "adjustment means" is a function for changing the content of reports and advice based on the acquired emotional state.

[0927] "Expert advice" means guidance or recommendations provided by a professional with financial or investment knowledge.

[0928] "Means for customization" refers to a function that allows the content of expert advice to be appropriately adjusted according to the user's emotional state.

[0929] The system of the present invention aims to support users in making economic decisions by allowing them to efficiently manage their financial data and receive AI analysis results and expert advice. In addition, by combining it with an emotion engine, it is possible to provide personalized advice and services according to the user's emotional state.

[0930] Overall system configuration

[0931] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotional state. The expert provides final advice.

[0932] User registration and authentication

[0933] A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[0934] Financial data input and integration

[0935] Users enter bank account, investment account, and credit card information into the system. Financial data can also be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server. The server receives the financial data and stores it in a database in a secure manner.

[0936] AI analysis and report generation

[0937] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[0938] Providing expert advice

[0939] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[0940] Emotion Engine Functions

[0941] While a user is using the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[0942] Specific examples

[0943] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[0944] Furthermore, the emotion engine recognizes the user's emotional state, and if the user is stressed, for example, the report display will be adjusted to be simple and easy to understand. Expert advice will also be tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, and if the user is calm, it will provide a detailed investment plan.

[0945] Example prompts to be input to the generative AI model

[0946] The system uses a camera to capture the user's facial expressions and performs emotion recognition to determine the user's emotional state. Based on the acquired emotional state, an AI engine analyzes financial data and generates financial advice that takes into account the user's recent spending patterns and income situation. The expert advice is also customized according to the user's emotional state, such as encouraging conservative spending when the user is nervous, or providing a detailed investment plan when the user is relaxed.

[0947] The above is an embodiment of the present invention, which provides personalized financial advice based on the user's emotional state, enabling more effective financial decision-making.

[0948] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0949] Step 1:

[0950] A user creates a new account, enters the required information (name, email address, password) and submits the registration form. The input is made through the user's terminal, and this information is sent as output to the server.

[0951] Step 2:

[0952] The server stores the received user information in a database and sends a confirmation email to the user, which includes an authentication link. Data processing involves storing the information, generating and sending the confirmation email.

[0953] Step 3:

[0954] The user clicks on the link in the confirmation email and the server completes the account authentication. The input is the user's click, and the output is the authenticated account being enabled.

[0955] Step 4:

[0956] Users enter their bank account, investment account, and credit card information into the system. This information is sent from the user's device to the server. Financial data can also be automatically retrieved from external services via API integration.

[0957] Step 5:

[0958] The server receives and securely stores the user's financial data, which is a combination of data entered and data from external services.

[0959] Step 6:

[0960] The server sends the stored financial data to the AI ​​engine. The input is the stored financial data, and the output is the analysis results by the AI ​​engine.

[0961] Step 7:

[0962] The AI ​​engine analyzes users' income, expenditure, and investment patterns to generate predictions. Data processing uses pattern recognition, statistical analysis, and predictive algorithms.

[0963] Step 8:

[0964] The server receives the analysis results from the AI ​​engine and generates reports for display on the user's dashboard, including visualizations and summaries of the analysis results.

[0965] Step 9:

[0966] The user sends a request for expert advice based on the analysis results from the terminal to the server. The input is the user's request, and the request information is saved on the server as the output.

[0967] Step 10:

[0968] The server selects an appropriate expert and provides the user's financial data and the AI ​​analysis results. The input is the user's request and the analysis results, and the output is information provided to the expert.

[0969] Step 11:

[0970] The expert creates advice based on the provided information and sends it to the server. The input is the information received by the expert, and the output is specific advice.

[0971] Step 12:

[0972] The server provides the expert advice for display on the user's dashboard, where the advice is displayed on the user's device.

[0973] Step 13:

[0974] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time and sends the emotional state to the server. The input is the user's emotional data, and the output is the recognized emotional state.

[0975] Step 14:

[0976] The server adjusts the financial reports and expert advice based on the information from the emotion engine, adjusting the display and advice accordingly depending on the emotional state.

[0977] Step 15:

[0978] Users receive tailored reports and advice, enabling them to make more effective financial decisions. The output is personalized financial advice.

[0979] 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.

[0980] 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.

[0981] 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.

[0982] [Third embodiment]

[0983] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0984] 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.

[0985] 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).

[0986] 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.

[0987] 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.

[0988] 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).

[0989] 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.

[0990] 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.

[0991] 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.

[0992] 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.

[0993] 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.

[0994] 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."

[0995] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' economic decision-making. Specific embodiments of this system are described in detail below.

[0996] Overall system configuration

[0997] The system basically consists of a user's device, a server, an AI engine, and an expert. The user's device provides the interface that the user operates, while the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the expert provides final advice.

[0998] User registration and authentication

[0999] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[1000] Terminal: The user's terminal sends the entered information to the server.

[1001] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[1002] Financial data input and integration

[1003] Users: Users enter their bank account, investment account, and credit card information into the system, with the option to automatically retrieve financial data through API integration with external services.

[1004] Terminal: The user's terminal sends the entered or acquired data to the server.

[1005] Server: The server receives the financial data and stores it in a secure database.

[1006] AI analysis and report generation

[1007] Server: The server sends the stored financial data to the AI ​​engine.

[1008] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[1009] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1010] Providing expert advice

[1011] User: The user submits a request for expert advice based on the analysis results.

[1012] Terminal: The user's terminal sends the request to the server.

[1013] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[1014] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[1015] Server: The server displays expert advice on the user's dashboard.

[1016] Specific examples

[1017] For example, consider a case where a user connects their bank account and investment account to the system. The user first enters their account information or sets up API connection. The system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[1018] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[1019] The processing flow will be explained below.

[1020] Step 1:

[1021] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[1022] Step 2:

[1023] The terminal transmits the input user information to the server.

[1024] Step 3:

[1025] The server stores the received user information in a database and sends a confirmation email to the user.

[1026] Step 4:

[1027] The user clicks on the link contained in the confirmation email to verify their email address.

[1028] Step 5:

[1029] The server verifies that the user clicked on the link and completes the account authentication.

[1030] Step 6:

[1031] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[1032] Step 7:

[1033] The terminal transmits the entered financial information and data obtained from the external service to the server.

[1034] Step 8:

[1035] The server stores the received financial data in a secure database.

[1036] Step 9:

[1037] The server sends the stored financial data to the AI ​​engine.

[1038] Step 10:

[1039] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[1040] Step 11:

[1041] The server receives the analysis results from the AI ​​engine and generates a report.

[1042] Step 12:

[1043] The terminal displays the generated report on the user's dashboard.

[1044] Step 13:

[1045] The user reviews the report and submits a request for further expert advice.

[1046] Step 14:

[1047] The terminal transmits the user's request to the server.

[1048] Step 15:

[1049] The server selects the appropriate expert based on the user's financial data and the results of AI analysis.

[1050] Step 16:

[1051] The server transmits the user's financial data and analysis results to the selected expert.

[1052] Step 17:

[1053] The expert creates specific advice based on the received data and sends the advice to the server.

[1054] Step 18:

[1055] The server receives the advice from the experts and displays it on the user's dashboard.

[1056] Step 19:

[1057] Users can view expert advice on the dashboard and take appropriate action.

[1058] Example 1

[1059] 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."

[1060] Conventional financial data management systems lack analytical functions and specific advice from experts to effectively support users' financial decision-making. Furthermore, they lack sufficient automation of data integration and analysis processes, making them difficult for users to use. Furthermore, it is difficult to integrate with external services, making it difficult to centrally manage multiple pieces of financial information.

[1061] 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.

[1062] In this invention, the server includes a means for inputting or linking financial data, a means for saving the input financial data, and a means for sending the saved financial data to an AI engine for analysis. This includes a means for a user to create a new account, a means for the server to send a confirmation email and authenticate the account, a means for providing the generated report to the user, a means for the user to send a request for expert advice, a means for the server to select an appropriate expert and provide the user's financial data and AI analysis results, a means for the expert to provide advice, a means for the server to display the advice on the user's dashboard, an API integration means for linking with external services, a means for saving financial data obtained from external services and using it for analysis, and a means for the user's device to send input information to the server via an HTTP POST request. This configuration allows users to easily create accounts, efficiently manage and analyze their financial data, and further enables them to make appropriate economic decisions by receiving specific advice from experts.

[1063] "Financial data" refers to data such as income, expenditure, and investment information obtained by a user from financial institutions, investment institutions, and the like.

[1064] "Means for input or linking" refers to means by which a user manually inputs data or automatically obtains data from an external service via an API.

[1065] "Means of storage" refers to a database for securely storing received data and the associated security mechanisms.

[1066] An "AI engine" is an artificial intelligence model that analyzes a user's financial data and predicts income, expenses, investment patterns, etc.

[1067] The "means for generating a report" refers to a means for visually displaying the analysis results by the AI ​​engine in a format that is easy for the user to understand.

[1068] The "means for creating an account" is a mechanism that allows a new user to create an account by entering their name, email address, password, etc.

[1069] The "means for sending a confirmation email" is a mechanism for sending a confirmation email to the email address entered during user registration and providing an authentication link.

[1070] The "account authentication method" is a mechanism by which a user activates their account by clicking a link in a confirmation email.

[1071] "Means for consulting with experts" refers to a system in which users can send requests for advice to experts based on the results of AI analysis.

[1072] The "means for providing advice from experts" is a mechanism for displaying advice provided by experts to the user.

[1073] "API integration means" is a mechanism that uses APIs to automatically obtain data by linking with external financial services and investment services.

[1074] An "HTTP POST request" is a request format that uses the HTTP protocol to send data from a terminal to a server.

[1075] The "dashboard" is a user interface that centrally displays the user's financial situation, AI analysis results, and advice from experts.

[1076] The system of the present invention efficiently manages users' financial data and supports their economic decision-making by providing AI analysis results and expert advice. This system consists of a user's terminal, a server, an AI engine, and experts.

[1077] User registration and authentication

[1078] Submit account creation request

[1079] The user accesses the system's registration page through a web browser, enters their name, email address, and password, and clicks the "Register" button.

[1080] The device constructs the input data in JSON format and sends an HTTP POST request to the server.

[1081] Save user data and send confirmation email

[1082] The server stores the received user data in an SQL database and uses the Python smtplib library to send a confirmation email containing an authentication link to the user.

[1083] Account authentication completed

[1084] The user clicks on the verification link in the email.

[1085] The server validates the token contained in the link and activates the corresponding user's account.

[1086] Financial data input and integration

[1087] Financial data entry request submission

[1088] A user enters bank account, investment account, and credit card information in a web browser and clicks the submit button.

[1089] The device sends the input data to the server via an HTTP POST request.

[1090] Financial Data Storage

[1091] The server stores the received financial data in a secure SQL database.

[1092] AI analysis and report generation

[1093] Data analysis request submission

[1094] The server periodically sends the stored financial data to the AI ​​engine.

[1095] Data analysis

[1096] The AI ​​engine analyzes the user's income, expenditure, and investment patterns and generates predictions.

[1097] Report Generation

[1098] The server receives the analysis results from the AI ​​engine, generates user-friendly reports using HTML and JavaScript, and displays them on the user's dashboard.

[1099] Providing expert advice

[1100] Submit an advice request

[1101] The user clicks a button on the dashboard to send a request for expert advice.

[1102] The device sends the request to the server via an HTTP POST request.

[1103] Selection of experts and provision of data

[1104] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel.

[1105] Creating and providing advice

[1106] Experts create specific advice based on the information provided and send it to the server via a dedicated management interface.

[1107] The server displays the received advice on the user's dashboard.

[1108] Example operation

[1109] For example, consider a case where a user connects their bank account and investment account to the system. After the user enters their account information or sets up API connection, the system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[1110] Prompt Sentence Examples

[1111] By inputting prompt statements into the generative AI model as shown below, specific advice and analysis results can be obtained.

[1112] Sample prompt 1: "Please tell me the breakdown of your income and expenses this month."

[1113] Sample prompt 2: "Predict your investment performance over the next six months."

[1114] Sample prompt 3: "I'd like some advice on effective ways to save money."

[1115] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[1116] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1117] Step 1:

[1118] A user accesses the system's registration page, enters their name, email address, and password, and clicks the "Register" button. The input data includes their name, email address, and password. This generates a request to create a new account.

[1119] Step 2:

[1120] The device constructs the input data in JSON format and sends an HTTP POST request to the server, which includes the user's name, email address, and password, and sends the new user information to the server.

[1121] Step 3:

[1122] The server receives the HTTP POST request, extracts user information from the request body, stores the extracted data in an SQL database by executing an insert query, and sends a confirmation email to the user's email address using the SMTP protocol. The confirmation email contains a link to verify the account.

[1123] Step 4:

[1124] The user opens the confirmation email they received and clicks on the authentication link in the email, which sends an account authentication request to the server.

[1125] Step 5:

[1126] The server verifies the token in the authentication link and updates the status of the corresponding user account to enabled, which means the user account is authenticated and ready for use.

[1127] Step 6:

[1128] After logging in, users enter their bank account, investment account, and credit card information, or use this information as input data to set up API integration with external services. After entering the information, they click the "Submit" button.

[1129] Step 7:

[1130] The terminal constructs the entered financial data in JSON format and sends an HTTP POST request to the server, containing the user's bank account, investment account, and credit card information.

[1131] Step 8:

[1132] The server receives the HTTP POST request, extracts financial data from the request body, and stores the extracted data securely in an SQL database for analysis.

[1133] Step 9:

[1134] The server periodically sends the stored financial data to the AI ​​engine, including the user's income, expenditure, and investment patterns.

[1135] Step 10:

[1136] The AI ​​engine analyzes the received financial data and generates forecasts for income, expenditure, and investment patterns. It uses machine learning algorithms to analyze the data and applies predictive models. The forecasts are then output as a report.

[1137] Step 11:

[1138] The server receives the analysis results from the AI ​​engine and generates a report using HTML and JavaScript. The generated report is displayed on the user's dashboard, allowing the user to check their financial status based on the analysis results.

[1139] Step 12:

[1140] A user clicks a button on the dashboard to send a request for expert advice, which includes the analysis results.

[1141] Step 13:

[1142] The device sends a request to the server via an HTTP POST request, which includes the user's financial data and the analysis results.

[1143] Step 14:

[1144] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel. The data provided to the expert includes the user's income, expenses, and investment patterns.

[1145] Step 15:

[1146] Experts create specific advice based on the information provided, and the advice is sent to the server via a dedicated management interface.

[1147] Step 16:

[1148] The server receives the advice provided by the experts and displays it on the user's dashboard, allowing the user to make appropriate financial decisions based on the expert advice.

[1149] (Application example 1)

[1150] 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."

[1151] Today's consumers make many of their daily payments and transactions electronically, resulting in a vast and complex amount of financial data. It is difficult to manually manage this vast amount of data and develop appropriate financial management and investment strategies. There is also a lack of ways to analyze financial data in real time or quickly obtain appropriate prescriptions from experts. This makes it difficult for consumers to make optimal financial decisions.

[1152] 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.

[1153] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to the user, means for automatically synchronizing payment information, and means for performing AI analysis in real time, thereby enabling users to analyze massive amounts of financial data in real time and receive prompt and appropriate advice from experts.

[1154] "Financial Data" means information about the economic activities of an individual or entity, including information about income, expenses, investments, assets, and liabilities.

[1155] An "AI engine" is a system that uses artificial intelligence algorithms to analyze data and make predictions.

[1156] A "report" is information such as detailed documents and graphs that are generated based on financial data and the results of that analysis and are provided to users.

[1157] "Payment information" is detailed data about payments made by a user, including information such as date, amount, and category.

[1158] "Synchronization" is the process of updating and matching data between different systems or devices in real time or periodically.

[1159] An "expert" is someone with advanced knowledge and experience in a particular field, in this case, an expert in the fields of finance and economics.

[1160] "Auto-email" is a feature that allows the system to automatically send emails based on specific conditions.

[1161] "API integration" refers to different software systems exchanging information and working together via an application programming interface (API).

[1162] "Real-time analysis" is the process of analyzing the latest data immediately and providing the results almost instantly.

[1163] An embodiment of the present invention includes a system for efficiently managing financial data and providing AI analysis results and expert advice. This system is composed of a user terminal, a server, an AI engine, and experts.

[1164] User registration and authentication

[1165] A user accesses the system to create a new account. They enter the required information (name, email address, password) and submit the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[1166] Financial data input and integration

[1167] Users enter their bank account, investment account, and credit card information into the system. Optionally, financial data can be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[1168] Automatic payment synchronization

[1169] Each time a user makes an electronic payment, payment information is automatically sent by the user's terminal to the server, which stores this data in a real-time database and keeps the financial data up to date.

[1170] AI analysis and report generation

[1171] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1172] Providing expert advice

[1173] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results using an automatic email sending function. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[1174] Hardware and software used

[1175] 1. Hardware: The server uses cloud infrastructure (e.g., AWS or GCP).

[1176] 2. Software:

[1177] Django (Web framework)

[1178] SciKit-Learn (machine learning library)

[1179] Specific examples of processing

[1180] For example, when a user connects their bank account and investment account to the system, they first enter their account information or set up API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request advice from an expert based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[1181] Prompt Sentence Examples

[1182] The following transaction was entered for user "example_user". A transaction of 150 yen for food was made on 2023-10-10. Please make a prediction based on the next transaction. The next transaction date is assumed to be 10 days later.

[1183] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1184] Step 1:

[1185] A user accesses the system and creates a new account. The user enters their name, email address, and password, and submits the registration form. This information is sent from the user's device to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[1186] Input: User's name, email address, and password

[1187] Output: Sends a confirmation email, saves user information to the database

[1188] Step 2:

[1189] Users log in to the system and enter their bank account, investment account, and credit card information. Optionally, they can set up API integration with external services to automatically retrieve financial data. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[1190] Input: Bank account, investment account, credit card information, API connection settings

[1191] Output: Saving financial data to a database

[1192] Step 3:

[1193] Every time a user makes an electronic payment, payment information is automatically sent from the user's device to the server, which stores this data in a real-time database, keeping financial data up to date.

[1194] Input: Payment information (date, time, amount, category)

[1195] Output: Real-time updated financial data storage

[1196] Step 4:

[1197] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. This analysis can use, for example, a linear regression model from SciKit-Learn. Once the analysis is complete, the results are sent to the server.

[1198] Input: Stored financial data

[1199] Output: Prediction results

[1200] Step 5:

[1201] The server receives the analysis results from the AI ​​engine and generates an easy-to-understand report, which is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1202] Input: Analysis results from the AI ​​engine

[1203] Output: Report, display on user dashboard

[1204] Step 6:

[1205] The user sends a request for advice from an expert based on the analysis results. The user's device then sends the request to the server. The server then selects an appropriate expert and provides the user's financial data and the AI ​​analysis results using an automatic email sending function.

[1206] Input: User advice request

[1207] Output: Automatic email to the expert

[1208] Step 7:

[1209] The expert creates specific advice based on the provided information and sends it to the server, which then displays the advice on the user's dashboard, allowing the user to receive specific guidance on appropriate investment strategies and savings methods.

[1210] Input: Expert advice

[1211] Output: Display on user dashboard

[1212] 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.

[1213] The system of the present invention efficiently manages a user's financial data and provides AI-based analysis results and expert advice to support the user's financial decision-making. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized advice and services. Specific embodiments of this system are described in detail below.

[1214] Overall system configuration

[1215] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotions. The expert provides final advice.

[1216] User registration and authentication

[1217] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[1218] Terminal: The user's terminal sends the entered information to the server.

[1219] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[1220] Financial data input and integration

[1221] Users: Users enter their bank account, investment account, and credit card information into the system, and can also use API integration with external services to automatically retrieve financial data.

[1222] Terminal: The user's terminal sends the entered or acquired data to the server.

[1223] Server: The server receives the financial data and stores it in a secure database.

[1224] AI analysis and report generation

[1225] Server: The server sends the stored financial data to the AI ​​engine.

[1226] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[1227] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1228] Providing expert advice

[1229] User: The user submits a request for expert advice based on the analysis results.

[1230] Terminal: The user's terminal sends the request to the server.

[1231] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[1232] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[1233] Server: The server displays expert advice on the user's dashboard.

[1234] Emotion Engine Functions

[1235] User: As the user uses the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time.

[1236] Emotion Engine: The emotion engine recognizes the user's emotional state and sends the result to the server.

[1237] Server: The server adjusts financial reports and expert advice based on information from the sentiment engine.

[1238] Specific examples

[1239] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1240] Furthermore, the emotion engine can recognize a user's emotional state and adjust the report display to be simple and easy to understand if the user is stressed. Expert advice can also be tailored to the user's emotions, suggesting a low-risk investment strategy if the user is excited, or offering a detailed investment plan if the user is calm.

[1241] As described above, the present invention is a system that supports users' economic decision-making through efficient management and analysis of financial data, and by combining it with an emotion engine, it is possible to provide more personalized advice and services.

[1242] The processing flow will be explained below.

[1243] Step 1:

[1244] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[1245] Step 2:

[1246] The terminal transmits the input user information to the server.

[1247] Step 3:

[1248] The server stores the received user information in a database and sends a confirmation email to the user.

[1249] Step 4:

[1250] The user clicks on the link contained in the confirmation email to verify their email address.

[1251] Step 5:

[1252] The server verifies that the user clicked on the link and completes the account authentication.

[1253] Step 6:

[1254] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[1255] Step 7:

[1256] The terminal transmits the entered financial information and data obtained from the external service to the server.

[1257] Step 8:

[1258] The server stores the received financial data in a secure database.

[1259] Step 9:

[1260] The server sends the stored financial data to the AI ​​engine.

[1261] Step 10:

[1262] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[1263] Step 11:

[1264] The server receives the analysis results from the AI ​​engine and generates a report.

[1265] Step 12:

[1266] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[1267] Step 13:

[1268] The emotion engine sends the recognized emotional state to the server.

[1269] Step 14:

[1270] The server adjusts the display of the financial report based on the information from the emotion engine.

[1271] Step 15:

[1272] The terminal displays the generated report on the user's dashboard, reflecting the adjusted display content.

[1273] Step 16:

[1274] The user reviews the report and submits a request for further expert advice.

[1275] Step 17:

[1276] The terminal transmits the user's request to the server.

[1277] Step 18:

[1278] The server selects the appropriate expert and provides the user's financial data and AI analysis results.

[1279] Step 19:

[1280] The expert creates specific advice based on the provided information and sends it to the server.

[1281] Step 20:

[1282] The server receives expert advice and tailors it to the user.

[1283] Step 21:

[1284] The server adjusts the expert advice based on the information from the emotion engine and displays it on the user's dashboard.

[1285] Step 22:

[1286] The device displays the expert advice on the user's dashboard.

[1287] Step 23:

[1288] Users can view expert advice on the dashboard and take appropriate action.

[1289] Example 2

[1290] 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."

[1291] Conventional financial management systems are unable to consider the user's emotional state when inputting and analyzing financial data, making it difficult to provide optimal advice and reports. Furthermore, expert advice is provided without regard to the user's emotional state, making it difficult to say that it provides optimal support for user decision-making. There is a need to solve these problems and provide more personalized services to users.

[1292] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1293] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, an emotion engine for recognizing the emotional state of the user, and means for adjusting the report content based on the emotional state recognized by the emotion engine. This makes it possible to provide personalized reports and advice that take the user's emotions into consideration.

[1294] "Financial Data" refers to information related to a user's economic activities, such as income, expenses, investment accounts, and credit card information.

[1295] "Means for input or integration" refers to API integration that allows users to manually input financial data or automatically obtain data from external services.

[1296] "Means for storing" means a database or storage system for securely storing received financial data.

[1297] "AI engine" refers to software that uses artificial intelligence technology to analyze financial data and predict a user's financial situation.

[1298] "Means of analysis" refers to the process of sending financial data to an AI engine to analyze income, expenses, investment patterns, etc.

[1299] "Means for generating a report" refers to the process of creating a report in a visually easy-to-understand format for the user based on the analysis results of the AI ​​engine.

[1300] "Means for providing to user" refers to the process of displaying the generated report on the user's dashboard so that the user can easily access it.

[1301] An "emotion engine" refers to a software system that analyzes a user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[1302] "Means for adjusting report content based on emotional state" refers to a process for optimizing the presentation method and content of a report according to the emotional state of the user recognized by the emotion engine.

[1303] "Means for consulting an expert" refers to the process by which a user submits a request for advice from an expert based on the results of AI analysis.

[1304] "Means for providing expert advice to users" refers to the process by which the server receives the advice prepared by the expert and displays it on the user's dashboard.

[1305] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' financial decision-making. In addition, by combining it with an emotion engine that recognizes users' emotions, it is possible to provide more personalized advice and services.

[1306] Overall system configuration

[1307] This system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine is responsible for recognizing the user's emotions. The expert is responsible for providing final advice.

[1308] User registration and authentication

[1309] A user accesses the system and opens the new account creation page. They enter the required information, such as their name, email address, and password, and click the submit button. The user's device sends the entered information to the server. The server stores the received information in a database, generates a confirmation email, and sends it to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[1310] Financial data input and integration

[1311] Users open a page to enter their bank account, investment account, and credit card information. They enter the required information and click the submit button. Financial data can also be automatically retrieved from external services using API integration. The user's device sends the entered or retrieved data to the server. The server stores the financial data in a database in a secure manner.

[1312] AI analysis and report generation

[1313] The server sends the stored financial data to the AI ​​engine, which analyzes income, expenses, investment patterns, etc. and generates predictions. Based on the analysis results received from the AI ​​engine, the server generates reports in an easy-to-understand format and displays them on the user's dashboard.

[1314] Providing expert advice

[1315] Based on the analysis results, the user clicks the "Request Expert Advice" button. The user's device sends the request to the server. The server automatically selects an appropriate expert and sends the user's financial data and the AI ​​analysis results to the expert. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[1316] Emotion Engine Functions

[1317] As users use the system, the emotion engine analyzes their facial expressions, voice, and input in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[1318] Specific examples

[1319] For example, when a user connects their bank and investment accounts to the system, they first enter their account information or set up API integration. The user's device then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, spending, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1320] Furthermore, the emotion engine recognizes the user's emotional state and adjusts the report display to be simple and easy to understand if the user is feeling stressed. Expert advice is also tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, while if the user is calm, it will provide a detailed investment plan.

[1321] Prompt Sentence Examples

[1322] "Analyze my bank and investment account data and create reports based on my income, expenses, and investment trends. Optimize the display based on my current emotional state."

[1323] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1324] Step 1:

[1325] User registration and authentication

[1326] User: Accesses the system, enters their name, email address, and password on the new account creation page, and clicks the "Submit" button.

[1327] Input: Name, Email Address, Password.

[1328] Output: Form submission data.

[1329] Terminal: Sends the entered information to the server.

[1330] Input: Form submission data.

[1331] Output: The request to the server.

[1332] Server: Stores the received information in a database and generates a confirmation email to send to the user.

[1333] Input: User information.

[1334] Output: A confirmation email.

[1335] User: Clicks on the link in the confirmation email.

[1336] Enter: Confirmation email.

[1337] Output: The authentication request.

[1338] Server: Detects that the link was clicked and updates the user's account to an authenticated state.

[1339] Input: Authentication request.

[1340] Output: Account authentication successful.

[1341] Step 2:

[1342] Financial data input and integration

[1343] User: Visits a page to enter bank account, investment account, or credit card information, enters the required information, and clicks the "Submit" button. Users can also set up API integrations to automatically retrieve financial data from external services.

[1344] Input: Bank account information, investment account information, credit card information.

[1345] Output: Form submission data, API setting information.

[1346] Terminal: Sends input or acquired data to the server.

[1347] Input: Form submission data, API setting information.

[1348] Output: The request to the server.

[1349] Server: Receives financial data and stores it in a database in a secure manner.

[1350] Input: Financial data.

[1351] Output: Stored financial data.

[1352] Step 3:

[1353] AI analysis and report generation

[1354] Server: Sends the stored financial data to the AI ​​engine.

[1355] Input: Stored financial data.

[1356] Output: The request to the AI ​​Engine.

[1357] AI Engine: Analyzes financial data and generates predictions based on users' income, expenses, and investment patterns.

[1358] Input: Financial data.

[1359] Output: Analysis results.

[1360] Server: Based on the analysis results received from the AI ​​engine, it generates reports in an easy-to-understand format and displays them on the user's dashboard.

[1361] Input: Analysis results.

[1362] Output: Report.

[1363] Step 4:

[1364] Providing expert advice

[1365] User: Based on the analysis results, clicks the "Seek Expert Advice" button.

[1366] Input: Analysis results.

[1367] Output: Advice request.

[1368] Terminal: Sends the request to the server.

[1369] Input: Advice request.

[1370] Output: The request to the server.

[1371] Server: Automatically selects the appropriate expert and sends the user's financial data and the results of AI analysis to the expert.

[1372] Input: Advice request, financial data, AI analysis results.

[1373] Output: Request for expert.

[1374] Expert: Creates specific advice based on the information provided and sends it to the server.

[1375] Input: Financial data, AI analysis results.

[1376] Output: Advice.

[1377] Server: Provides expert advice to users on their dashboard.

[1378] Enter: Advice.

[1379] Output: Dashboard update.

[1380] Step 5:

[1381] Emotion Engine Functions

[1382] User: While using the system, the emotion engine analyzes facial expressions, voice, and input in real time.

[1383] Input: facial expressions, voice, input content.

[1384] Output: Emotion data.

[1385] Emotion engine: Recognizes the user's emotional state and sends the results to the server.

[1386] Input: Emotion data.

[1387] Output: Emotional state.

[1388] Server: Tailors financial reports and expert advice based on information from the sentiment engine.

[1389] Input: Emotional state.

[1390] Output: Tailored reports and advice.

[1391] (Application example 2)

[1392] 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."

[1393] Conventional financial data management systems can efficiently manage users' financial data and provide predictions and expert advice based on AI analysis, but they have difficulty taking the user's emotional state into account. As a result, they are unable to provide appropriate advice based on the user's emotions, and are unable to provide effective support in situations where the user feels stressed or anxious. Therefore, there is a growing need for a system that can recognize the user's emotional state in real time and provide personalized financial advice accordingly.

[1394] 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.

[1395] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to a user, means for acquiring the user's emotional state, means for adjusting the report based on the acquired emotional state, and means for customizing expert advice based on the emotional state, thereby making it possible to provide personalized advice and services according to the user's emotional state.

[1396] "Financial Data" means information about your income, expenses, investments and assets.

[1397] "Input means" refers to interfaces and devices through which users input financial data.

[1398] "Storage means" refers to a database or storage system for securely storing input financial data.

[1399] The "AI engine" is an artificial intelligence program that analyzes stored financial data and makes predictions about the user's financial status and future prospects.

[1400] "Analysis means" refers to the functions and programs that enable the AI ​​engine to process financial data and derive analytical results.

[1401] "Report generation means" refers to a device or function that creates a report to be provided to the user based on the results of AI analysis.

[1402] "Providing means" refers to a means for displaying or notifying the user of the generated report or expert advice.

[1403] "Emotional state" refers to a psychological state that is inferred based on the user's facial expression, voice, and input content.

[1404] "Acquisition means" refers to sensors and software for acquiring the user's emotional state.

[1405] The "adjustment means" is a function for changing the content of reports and advice based on the acquired emotional state.

[1406] "Expert advice" means guidance or recommendations provided by a professional with financial or investment knowledge.

[1407] "Means for customization" refers to a function that allows the content of expert advice to be appropriately adjusted according to the user's emotional state.

[1408] The system of the present invention aims to support users in making economic decisions by allowing them to efficiently manage their financial data and receive AI analysis results and expert advice. In addition, by combining it with an emotion engine, it is possible to provide personalized advice and services according to the user's emotional state.

[1409] Overall system configuration

[1410] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotional state. The expert provides final advice.

[1411] User registration and authentication

[1412] A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[1413] Financial data input and integration

[1414] Users enter bank account, investment account, and credit card information into the system. Financial data can also be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server. The server receives the financial data and stores it in a database in a secure manner.

[1415] AI analysis and report generation

[1416] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1417] Providing expert advice

[1418] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[1419] Emotion Engine Functions

[1420] While a user is using the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[1421] Specific examples

[1422] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1423] Furthermore, the emotion engine recognizes the user's emotional state, and if the user is stressed, for example, the report display will be adjusted to be simple and easy to understand. Expert advice will also be tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, and if the user is calm, it will provide a detailed investment plan.

[1424] Example prompts to be input to the generative AI model

[1425] The system uses a camera to capture the user's facial expressions and performs emotion recognition to determine the user's emotional state. Based on the acquired emotional state, an AI engine analyzes financial data and generates financial advice that takes into account the user's recent spending patterns and income situation. The expert advice is also customized according to the user's emotional state, such as encouraging conservative spending when the user is nervous, or providing a detailed investment plan when the user is relaxed.

[1426] The above is an embodiment of the present invention, which provides personalized financial advice based on the user's emotional state, enabling more effective financial decision-making.

[1427] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1428] Step 1:

[1429] A user creates a new account, enters the required information (name, email address, password) and submits the registration form. The input is made through the user's terminal, and this information is sent as output to the server.

[1430] Step 2:

[1431] The server stores the received user information in a database and sends a confirmation email to the user, which includes an authentication link. Data processing involves storing the information, generating and sending the confirmation email.

[1432] Step 3:

[1433] The user clicks on the link in the confirmation email and the server completes the account authentication. The input is the user's click, and the output is the authenticated account being enabled.

[1434] Step 4:

[1435] Users enter their bank account, investment account, and credit card information into the system. This information is sent from the user's device to the server. Financial data can also be automatically retrieved from external services via API integration.

[1436] Step 5:

[1437] The server receives and securely stores the user's financial data, which is a combination of data entered and data from external services.

[1438] Step 6:

[1439] The server sends the stored financial data to the AI ​​engine. The input is the stored financial data, and the output is the analysis results by the AI ​​engine.

[1440] Step 7:

[1441] The AI ​​engine analyzes users' income, expenditure, and investment patterns to generate predictions. Data processing uses pattern recognition, statistical analysis, and predictive algorithms.

[1442] Step 8:

[1443] The server receives the analysis results from the AI ​​engine and generates reports for display on the user's dashboard, including visualizations and summaries of the analysis results.

[1444] Step 9:

[1445] The user sends a request for expert advice based on the analysis results from the terminal to the server. The input is the user's request, and the request information is saved on the server as the output.

[1446] Step 10:

[1447] The server selects an appropriate expert and provides the user's financial data and the AI ​​analysis results. The input is the user's request and the analysis results, and the output is information provided to the expert.

[1448] Step 11:

[1449] The expert creates advice based on the provided information and sends it to the server. The input is the information received by the expert, and the output is specific advice.

[1450] Step 12:

[1451] The server provides the expert advice for display on the user's dashboard, where the advice is displayed on the user's device.

[1452] Step 13:

[1453] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time and sends the emotional state to the server. The input is the user's emotional data, and the output is the recognized emotional state.

[1454] Step 14:

[1455] The server adjusts the financial reports and expert advice based on the information from the emotion engine, adjusting the display and advice accordingly depending on the emotional state.

[1456] Step 15:

[1457] Users receive tailored reports and advice, enabling them to make more effective financial decisions. The output is personalized financial advice.

[1458] 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.

[1459] 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.

[1460] 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.

[1461] [Fourth embodiment]

[1462] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1463] 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.

[1464] 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).

[1465] 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.

[1466] 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.

[1467] 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).

[1468] 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.

[1469] 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.

[1470] 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.

[1471] 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.

[1472] 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.

[1473] 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.

[1474] 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."

[1475] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' economic decision-making. Specific embodiments of this system are described in detail below.

[1476] Overall system configuration

[1477] The system basically consists of a user's device, a server, an AI engine, and an expert. The user's device provides the interface that the user operates, while the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the expert provides final advice.

[1478] User registration and authentication

[1479] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[1480] Terminal: The user's terminal sends the entered information to the server.

[1481] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[1482] Financial data input and integration

[1483] Users: Users enter their bank account, investment account, and credit card information into the system, with the option to automatically retrieve financial data through API integration with external services.

[1484] Terminal: The user's terminal sends the entered or acquired data to the server.

[1485] Server: The server receives the financial data and stores it in a secure database.

[1486] AI analysis and report generation

[1487] Server: The server sends the stored financial data to the AI ​​engine.

[1488] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[1489] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1490] Providing expert advice

[1491] User: The user submits a request for expert advice based on the analysis results.

[1492] Terminal: The user's terminal sends the request to the server.

[1493] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[1494] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[1495] Server: The server displays expert advice on the user's dashboard.

[1496] Specific examples

[1497] For example, consider a case where a user connects their bank account and investment account to the system. The user first enters their account information or sets up API connection. The system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[1498] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[1499] The processing flow will be explained below.

[1500] Step 1:

[1501] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[1502] Step 2:

[1503] The terminal transmits the input user information to the server.

[1504] Step 3:

[1505] The server stores the received user information in a database and sends a confirmation email to the user.

[1506] Step 4:

[1507] The user clicks on the link contained in the confirmation email to verify their email address.

[1508] Step 5:

[1509] The server verifies that the user clicked on the link and completes the account authentication.

[1510] Step 6:

[1511] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[1512] Step 7:

[1513] The terminal transmits the entered financial information and data obtained from the external service to the server.

[1514] Step 8:

[1515] The server stores the received financial data in a secure database.

[1516] Step 9:

[1517] The server sends the stored financial data to the AI ​​engine.

[1518] Step 10:

[1519] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[1520] Step 11:

[1521] The server receives the analysis results from the AI ​​engine and generates a report.

[1522] Step 12:

[1523] The terminal displays the generated report on the user's dashboard.

[1524] Step 13:

[1525] The user reviews the report and submits a request for further expert advice.

[1526] Step 14:

[1527] The terminal transmits the user's request to the server.

[1528] Step 15:

[1529] The server selects the appropriate expert based on the user's financial data and the results of AI analysis.

[1530] Step 16:

[1531] The server transmits the user's financial data and analysis results to the selected expert.

[1532] Step 17:

[1533] The expert creates specific advice based on the received data and sends the advice to the server.

[1534] Step 18:

[1535] The server receives the advice from the experts and displays it on the user's dashboard.

[1536] Step 19:

[1537] Users can view expert advice on the dashboard and take appropriate action.

[1538] Example 1

[1539] 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."

[1540] Conventional financial data management systems lack analytical functions and specific advice from experts to effectively support users' financial decision-making. Furthermore, they lack sufficient automation of data integration and analysis processes, making them difficult for users to use. Furthermore, it is difficult to integrate with external services, making it difficult to centrally manage multiple pieces of financial information.

[1541] 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.

[1542] In this invention, the server includes a means for inputting or linking financial data, a means for saving the input financial data, and a means for sending the saved financial data to an AI engine for analysis. This includes a means for a user to create a new account, a means for the server to send a confirmation email and authenticate the account, a means for providing the generated report to the user, a means for the user to send a request for expert advice, a means for the server to select an appropriate expert and provide the user's financial data and AI analysis results, a means for the expert to provide advice, a means for the server to display the advice on the user's dashboard, an API integration means for linking with external services, a means for saving financial data obtained from external services and using it for analysis, and a means for the user's device to send input information to the server via an HTTP POST request. This configuration allows users to easily create accounts, efficiently manage and analyze their financial data, and further enables them to make appropriate economic decisions by receiving specific advice from experts.

[1543] "Financial data" refers to data such as income, expenditure, and investment information obtained by a user from financial institutions, investment institutions, and the like.

[1544] "Means for input or linking" refers to means by which a user manually inputs data or automatically obtains data from an external service via an API.

[1545] "Means of storage" refers to a database for securely storing received data and the associated security mechanisms.

[1546] An "AI engine" is an artificial intelligence model that analyzes a user's financial data and predicts income, expenses, investment patterns, etc.

[1547] The "means for generating a report" refers to a means for visually displaying the analysis results by the AI ​​engine in a format that is easy for the user to understand.

[1548] The "means for creating an account" is a mechanism that allows a new user to create an account by entering their name, email address, password, etc.

[1549] The "means for sending a confirmation email" is a mechanism for sending a confirmation email to the email address entered during user registration and providing an authentication link.

[1550] The "account authentication method" is a mechanism by which a user activates their account by clicking a link in a confirmation email.

[1551] "Means for consulting with experts" refers to a system in which users can send requests for advice to experts based on the results of AI analysis.

[1552] The "means for providing advice from experts" is a mechanism for displaying advice provided by experts to the user.

[1553] "API integration means" is a mechanism that uses APIs to automatically obtain data by linking with external financial services and investment services.

[1554] An "HTTP POST request" is a request format that uses the HTTP protocol to send data from a terminal to a server.

[1555] The "dashboard" is a user interface that centrally displays the user's financial situation, AI analysis results, and advice from experts.

[1556] The system of the present invention efficiently manages users' financial data and supports their economic decision-making by providing AI analysis results and expert advice. This system consists of a user's terminal, a server, an AI engine, and experts.

[1557] User registration and authentication

[1558] Submit account creation request

[1559] The user accesses the system's registration page through a web browser, enters their name, email address, and password, and clicks the "Register" button.

[1560] The device constructs the input data in JSON format and sends an HTTP POST request to the server.

[1561] Save user data and send confirmation email

[1562] The server stores the received user data in an SQL database and uses the Python smtplib library to send a confirmation email containing an authentication link to the user.

[1563] Account authentication completed

[1564] The user clicks on the verification link in the email.

[1565] The server validates the token contained in the link and activates the corresponding user's account.

[1566] Financial data input and integration

[1567] Financial data entry request submission

[1568] A user enters bank account, investment account, and credit card information in a web browser and clicks the submit button.

[1569] The device sends the input data to the server via an HTTP POST request.

[1570] Financial Data Storage

[1571] The server stores the received financial data in a secure SQL database.

[1572] AI analysis and report generation

[1573] Data analysis request submission

[1574] The server periodically sends the stored financial data to the AI ​​engine.

[1575] Data analysis

[1576] The AI ​​engine analyzes the user's income, expenditure, and investment patterns and generates predictions.

[1577] Report Generation

[1578] The server receives the analysis results from the AI ​​engine, generates user-friendly reports using HTML and JavaScript, and displays them on the user's dashboard.

[1579] Providing expert advice

[1580] Submit an advice request

[1581] The user clicks a button on the dashboard to send a request for expert advice.

[1582] The device sends the request to the server via an HTTP POST request.

[1583] Selection of experts and provision of data

[1584] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel.

[1585] Creating and providing advice

[1586] Experts create specific advice based on the information provided and send it to the server via a dedicated management interface.

[1587] The server displays the received advice on the user's dashboard.

[1588] Example operation

[1589] For example, consider a case where a user connects their bank account and investment account to the system. After the user enters their account information or sets up API connection, the system sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request expert advice based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[1590] Prompt Sentence Examples

[1591] By inputting prompt statements into the generative AI model as shown below, specific advice and analysis results can be obtained.

[1592] Sample prompt 1: "Please tell me the breakdown of your income and expenses this month."

[1593] Sample prompt 2: "Predict your investment performance over the next six months."

[1594] Sample prompt 3: "I'd like some advice on effective ways to save money."

[1595] As described above, the present invention is a system that supports users in making economic decisions through efficient management and analysis of financial data.

[1596] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1597] Step 1:

[1598] A user accesses the system's registration page, enters their name, email address, and password, and clicks the "Register" button. The input data includes their name, email address, and password. This generates a request to create a new account.

[1599] Step 2:

[1600] The device constructs the input data in JSON format and sends an HTTP POST request to the server, which includes the user's name, email address, and password, and sends the new user information to the server.

[1601] Step 3:

[1602] The server receives the HTTP POST request, extracts user information from the request body, stores the extracted data in an SQL database by executing an insert query, and sends a confirmation email to the user's email address using the SMTP protocol. The confirmation email contains a link to verify the account.

[1603] Step 4:

[1604] The user opens the confirmation email they received and clicks on the authentication link in the email, which sends an account authentication request to the server.

[1605] Step 5:

[1606] The server verifies the token in the authentication link and updates the status of the corresponding user account to enabled, which means the user account is authenticated and ready for use.

[1607] Step 6:

[1608] After logging in, users enter their bank account, investment account, and credit card information, or use this information as input data to set up API integration with external services. After entering the information, they click the "Submit" button.

[1609] Step 7:

[1610] The terminal constructs the entered financial data in JSON format and sends an HTTP POST request to the server, containing the user's bank account, investment account, and credit card information.

[1611] Step 8:

[1612] The server receives the HTTP POST request, extracts financial data from the request body, and stores the extracted data securely in an SQL database for analysis.

[1613] Step 9:

[1614] The server periodically sends the stored financial data to the AI ​​engine, including the user's income, expenditure, and investment patterns.

[1615] Step 10:

[1616] The AI ​​engine analyzes the received financial data and generates forecasts for income, expenditure, and investment patterns. It uses machine learning algorithms to analyze the data and applies predictive models. The forecasts are then output as a report.

[1617] Step 11:

[1618] The server receives the analysis results from the AI ​​engine and generates a report using HTML and JavaScript. The generated report is displayed on the user's dashboard, allowing the user to check their financial status based on the analysis results.

[1619] Step 12:

[1620] A user clicks a button on the dashboard to send a request for expert advice, which includes the analysis results.

[1621] Step 13:

[1622] The device sends a request to the server via an HTTP POST request, which includes the user's financial data and the analysis results.

[1623] Step 14:

[1624] The server selects an appropriate expert and provides the user's financial data and AI analysis results to the expert via a secure channel. The data provided to the expert includes the user's income, expenses, and investment patterns.

[1625] Step 15:

[1626] Experts create specific advice based on the information provided, and the advice is sent to the server via a dedicated management interface.

[1627] Step 16:

[1628] The server receives the advice provided by the experts and displays it on the user's dashboard, allowing the user to make appropriate financial decisions based on the expert advice.

[1629] (Application example 1)

[1630] 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."

[1631] Today's consumers make many of their daily payments and transactions electronically, resulting in a vast and complex amount of financial data. It is difficult to manually manage this vast amount of data and develop appropriate financial management and investment strategies. There is also a lack of ways to analyze financial data in real time or quickly obtain appropriate prescriptions from experts. This makes it difficult for consumers to make optimal financial decisions.

[1632] 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.

[1633] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to the user, means for automatically synchronizing payment information, and means for performing AI analysis in real time, thereby enabling users to analyze massive amounts of financial data in real time and receive prompt and appropriate advice from experts.

[1634] "Financial Data" means information about the economic activities of an individual or entity, including information about income, expenses, investments, assets, and liabilities.

[1635] An "AI engine" is a system that uses artificial intelligence algorithms to analyze data and make predictions.

[1636] A "report" is information such as detailed documents and graphs that are generated based on financial data and the results of that analysis and are provided to users.

[1637] "Payment information" is detailed data about payments made by a user, including information such as date, amount, and category.

[1638] "Synchronization" is the process of updating and matching data between different systems or devices in real time or periodically.

[1639] An "expert" is someone with advanced knowledge and experience in a particular field, in this case, an expert in the fields of finance and economics.

[1640] "Auto-email" is a feature that allows the system to automatically send emails based on specific conditions.

[1641] "API integration" refers to different software systems exchanging information and working together via an application programming interface (API).

[1642] "Real-time analysis" is the process of analyzing the latest data immediately and providing the results almost instantly.

[1643] An embodiment of the present invention includes a system for efficiently managing financial data and providing AI analysis results and expert advice. This system is composed of a user terminal, a server, an AI engine, and experts.

[1644] User registration and authentication

[1645] A user accesses the system to create a new account. They enter the required information (name, email address, password) and submit the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[1646] Financial data input and integration

[1647] Users enter their bank account, investment account, and credit card information into the system. Optionally, financial data can be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[1648] Automatic payment synchronization

[1649] Each time a user makes an electronic payment, payment information is automatically sent by the user's terminal to the server, which stores this data in a real-time database and keeps the financial data up to date.

[1650] AI analysis and report generation

[1651] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1652] Providing expert advice

[1653] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results using an automatic email sending function. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[1654] Hardware and software used

[1655] 1. Hardware: The server uses cloud infrastructure (e.g., AWS or GCP).

[1656] 2. Software:

[1657] Django (Web framework)

[1658] SciKit-Learn (machine learning library)

[1659] Specific examples of processing

[1660] For example, when a user connects their bank account and investment account to the system, they first enter their account information or set up API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance. Furthermore, the user can request advice from an expert based on the analysis results, resulting in specific guidance on appropriate investment strategies and savings methods.

[1661] Prompt Sentence Examples

[1662] The following transaction was entered for user "example_user". A transaction of 150 yen for food was made on 2023-10-10. Please make a prediction based on the next transaction. The next transaction date is assumed to be 10 days later.

[1663] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1664] Step 1:

[1665] A user accesses the system and creates a new account. The user enters their name, email address, and password, and submits the registration form. This information is sent from the user's device to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes account authentication.

[1666] Input: User's name, email address, and password

[1667] Output: Sends a confirmation email, saves user information to the database

[1668] Step 2:

[1669] Users log in to the system and enter their bank account, investment account, and credit card information. Optionally, they can set up API integration with external services to automatically retrieve financial data. The user's device sends the entered or retrieved data to the server, which receives the financial data and stores it in a database in a secure manner.

[1670] Input: Bank account, investment account, credit card information, API connection settings

[1671] Output: Saving financial data to a database

[1672] Step 3:

[1673] Every time a user makes an electronic payment, payment information is automatically sent from the user's device to the server, which stores this data in a real-time database, keeping financial data up to date.

[1674] Input: Payment information (date, time, amount, category)

[1675] Output: Real-time updated financial data storage

[1676] Step 4:

[1677] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. This analysis can use, for example, a linear regression model from SciKit-Learn. Once the analysis is complete, the results are sent to the server.

[1678] Input: Stored financial data

[1679] Output: Prediction results

[1680] Step 5:

[1681] The server receives the analysis results from the AI ​​engine and generates an easy-to-understand report, which is displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1682] Input: Analysis results from the AI ​​engine

[1683] Output: Report, display on user dashboard

[1684] Step 6:

[1685] The user sends a request for advice from an expert based on the analysis results. The user's device then sends the request to the server. The server then selects an appropriate expert and provides the user's financial data and the AI ​​analysis results using an automatic email sending function.

[1686] Input: User advice request

[1687] Output: Automatic email to the expert

[1688] Step 7:

[1689] The expert creates specific advice based on the provided information and sends it to the server, which then displays the advice on the user's dashboard, allowing the user to receive specific guidance on appropriate investment strategies and savings methods.

[1690] Input: Expert advice

[1691] Output: Display on user dashboard

[1692] 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.

[1693] The system of the present invention efficiently manages a user's financial data and provides AI-based analysis results and expert advice to support the user's financial decision-making. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, it is possible to provide more personalized advice and services. Specific embodiments of this system are described in detail below.

[1694] Overall system configuration

[1695] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotions. The expert provides final advice.

[1696] User registration and authentication

[1697] User: A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form.

[1698] Terminal: The user's terminal sends the entered information to the server.

[1699] Server: The server stores the received information in a database and sends a confirmation email to the user. When the user clicks on the link in the confirmation email, the server completes the account authentication.

[1700] Financial data input and integration

[1701] Users: Users enter their bank account, investment account, and credit card information into the system, and can also use API integration with external services to automatically retrieve financial data.

[1702] Terminal: The user's terminal sends the entered or acquired data to the server.

[1703] Server: The server receives the financial data and stores it in a secure database.

[1704] AI analysis and report generation

[1705] Server: The server sends the stored financial data to the AI ​​engine.

[1706] AI Engine: The AI ​​engine analyzes the user's income, expenses, investment patterns, etc. and generates predictions.

[1707] Server: The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1708] Providing expert advice

[1709] User: The user submits a request for expert advice based on the analysis results.

[1710] Terminal: The user's terminal sends the request to the server.

[1711] Server: The server selects appropriate experts and provides the user's financial data and AI analysis results.

[1712] Expert: The expert creates specific advice based on the information provided and sends it to the server.

[1713] Server: The server displays expert advice on the user's dashboard.

[1714] Emotion Engine Functions

[1715] User: As the user uses the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time.

[1716] Emotion Engine: The emotion engine recognizes the user's emotional state and sends the result to the server.

[1717] Server: The server adjusts financial reports and expert advice based on information from the sentiment engine.

[1718] Specific examples

[1719] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1720] Furthermore, the emotion engine can recognize a user's emotional state and adjust the report display to be simple and easy to understand if the user is stressed. Expert advice can also be tailored to the user's emotions, suggesting a low-risk investment strategy if the user is excited, or offering a detailed investment plan if the user is calm.

[1721] As described above, the present invention is a system that supports users' economic decision-making through efficient management and analysis of financial data, and by combining it with an emotion engine, it is possible to provide more personalized advice and services.

[1722] The processing flow will be explained below.

[1723] Step 1:

[1724] A user enters their name, email address, and password into a registration form to access the system and create a new account.

[1725] Step 2:

[1726] The terminal transmits the input user information to the server.

[1727] Step 3:

[1728] The server stores the received user information in a database and sends a confirmation email to the user.

[1729] Step 4:

[1730] The user clicks on the link contained in the confirmation email to verify their email address.

[1731] Step 5:

[1732] The server verifies that the user clicked on the link and completes the account authentication.

[1733] Step 6:

[1734] Users enter their bank account, investment account, and credit card information into the system, and can also choose to set up API integration with external services.

[1735] Step 7:

[1736] The terminal transmits the entered financial information and data obtained from the external service to the server.

[1737] Step 8:

[1738] The server stores the received financial data in a secure database.

[1739] Step 9:

[1740] The server sends the stored financial data to the AI ​​engine.

[1741] Step 10:

[1742] The AI ​​engine analyzes the received financial data and predicts the user's income, expenditure, and investment patterns.

[1743] Step 11:

[1744] The server receives the analysis results from the AI ​​engine and generates a report.

[1745] Step 12:

[1746] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[1747] Step 13:

[1748] The emotion engine sends the recognized emotional state to the server.

[1749] Step 14:

[1750] The server adjusts the display of the financial report based on the information from the emotion engine.

[1751] Step 15:

[1752] The terminal displays the generated report on the user's dashboard, reflecting the adjusted display content.

[1753] Step 16:

[1754] The user reviews the report and submits a request for further expert advice.

[1755] Step 17:

[1756] The terminal transmits the user's request to the server.

[1757] Step 18:

[1758] The server selects the appropriate expert and provides the user's financial data and AI analysis results.

[1759] Step 19:

[1760] The expert creates specific advice based on the provided information and sends it to the server.

[1761] Step 20:

[1762] The server receives expert advice and tailors it to the user.

[1763] Step 21:

[1764] The server adjusts the expert advice based on the information from the emotion engine and displays it on the user's dashboard.

[1765] Step 22:

[1766] The device displays the expert advice on the user's dashboard.

[1767] Step 23:

[1768] Users can view expert advice on the dashboard and take appropriate action.

[1769] Example 2

[1770] 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."

[1771] Conventional financial management systems are unable to consider the user's emotional state when inputting and analyzing financial data, making it difficult to provide optimal advice and reports. Furthermore, expert advice is provided without regard to the user's emotional state, making it difficult to say that it provides optimal support for user decision-making. There is a need to solve these problems and provide more personalized services to users.

[1772] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1773] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, an emotion engine for recognizing the emotional state of the user, and means for adjusting the report content based on the emotional state recognized by the emotion engine. This makes it possible to provide personalized reports and advice that take the user's emotions into consideration.

[1774] "Financial Data" refers to information related to a user's economic activities, such as income, expenses, investment accounts, and credit card information.

[1775] "Means for input or integration" refers to API integration that allows users to manually input financial data or automatically obtain data from external services.

[1776] "Means for storing" means a database or storage system for securely storing received financial data.

[1777] "AI engine" refers to software that uses artificial intelligence technology to analyze financial data and predict a user's financial situation.

[1778] "Means of analysis" refers to the process of sending financial data to an AI engine to analyze income, expenses, investment patterns, etc.

[1779] "Means for generating a report" refers to the process of creating a report in a visually easy-to-understand format for the user based on the analysis results of the AI ​​engine.

[1780] "Means for providing to user" refers to the process of displaying the generated report on the user's dashboard so that the user can easily access it.

[1781] An "emotion engine" refers to a software system that analyzes a user's facial expressions, voice, input content, etc. in real time to recognize the user's emotional state.

[1782] "Means for adjusting report content based on emotional state" refers to a process for optimizing the presentation method and content of a report according to the emotional state of the user recognized by the emotion engine.

[1783] "Means for consulting an expert" refers to the process by which a user submits a request for advice from an expert based on the results of AI analysis.

[1784] "Means for providing expert advice to users" refers to the process by which the server receives the advice prepared by the expert and displays it on the user's dashboard.

[1785] The system of the present invention efficiently manages users' financial data and provides AI-based analysis results and expert advice to support users' financial decision-making. In addition, by combining it with an emotion engine that recognizes users' emotions, it is possible to provide more personalized advice and services.

[1786] Overall system configuration

[1787] This system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine is responsible for recognizing the user's emotions. The expert is responsible for providing final advice.

[1788] User registration and authentication

[1789] A user accesses the system and opens the new account creation page. They enter the required information, such as their name, email address, and password, and click the submit button. The user's device sends the entered information to the server. The server stores the received information in a database, generates a confirmation email, and sends it to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[1790] Financial data input and integration

[1791] Users open a page to enter their bank account, investment account, and credit card information. They enter the required information and click the submit button. Financial data can also be automatically retrieved from external services using API integration. The user's device sends the entered or retrieved data to the server. The server stores the financial data in a database in a secure manner.

[1792] AI analysis and report generation

[1793] The server sends the stored financial data to the AI ​​engine, which analyzes income, expenses, investment patterns, etc. and generates predictions. Based on the analysis results received from the AI ​​engine, the server generates reports in an easy-to-understand format and displays them on the user's dashboard.

[1794] Providing expert advice

[1795] Based on the analysis results, the user clicks the "Request Expert Advice" button. The user's device sends the request to the server. The server automatically selects an appropriate expert and sends the user's financial data and the AI ​​analysis results to the expert. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[1796] Emotion Engine Functions

[1797] As users use the system, the emotion engine analyzes their facial expressions, voice, and input in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[1798] Specific examples

[1799] For example, when a user connects their bank and investment accounts to the system, they first enter their account information or set up API integration. The user's device then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, spending, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1800] Furthermore, the emotion engine recognizes the user's emotional state and adjusts the report display to be simple and easy to understand if the user is feeling stressed. Expert advice is also tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, while if the user is calm, it will provide a detailed investment plan.

[1801] Prompt Sentence Examples

[1802] "Analyze my bank and investment account data and create reports based on my income, expenses, and investment trends. Optimize the display based on my current emotional state."

[1803] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1804] Step 1:

[1805] User registration and authentication

[1806] User: Accesses the system, enters their name, email address, and password on the new account creation page, and clicks the "Submit" button.

[1807] Input: Name, Email Address, Password.

[1808] Output: Form submission data.

[1809] Terminal: Sends the entered information to the server.

[1810] Input: Form submission data.

[1811] Output: The request to the server.

[1812] Server: Stores the received information in a database and generates a confirmation email to send to the user.

[1813] Input: User information.

[1814] Output: A confirmation email.

[1815] User: Clicks on the link in the confirmation email.

[1816] Enter: Confirmation email.

[1817] Output: The authentication request.

[1818] Server: Detects that the link was clicked and updates the user's account to an authenticated state.

[1819] Input: Authentication request.

[1820] Output: Account authentication successful.

[1821] Step 2:

[1822] Financial data input and integration

[1823] User: Visits a page to enter bank account, investment account, or credit card information, enters the required information, and clicks the "Submit" button. Users can also set up API integrations to automatically retrieve financial data from external services.

[1824] Input: Bank account information, investment account information, credit card information.

[1825] Output: Form submission data, API setting information.

[1826] Terminal: Sends input or acquired data to the server.

[1827] Input: Form submission data, API setting information.

[1828] Output: The request to the server.

[1829] Server: Receives financial data and stores it in a database in a secure manner.

[1830] Input: Financial data.

[1831] Output: Stored financial data.

[1832] Step 3:

[1833] AI analysis and report generation

[1834] Server: Sends the stored financial data to the AI ​​engine.

[1835] Input: Stored financial data.

[1836] Output: The request to the AI ​​Engine.

[1837] AI Engine: Analyzes financial data and generates predictions based on users' income, expenses, and investment patterns.

[1838] Input: Financial data.

[1839] Output: Analysis results.

[1840] Server: Based on the analysis results received from the AI ​​engine, it generates reports in an easy-to-understand format and displays them on the user's dashboard.

[1841] Input: Analysis results.

[1842] Output: Report.

[1843] Step 4:

[1844] Providing expert advice

[1845] User: Based on the analysis results, clicks the "Seek Expert Advice" button.

[1846] Input: Analysis results.

[1847] Output: Advice request.

[1848] Terminal: Sends the request to the server.

[1849] Input: Advice request.

[1850] Output: The request to the server.

[1851] Server: Automatically selects the appropriate expert and sends the user's financial data and the results of AI analysis to the expert.

[1852] Input: Advice request, financial data, AI analysis results.

[1853] Output: Request for expert.

[1854] Expert: Creates specific advice based on the information provided and sends it to the server.

[1855] Input: Financial data, AI analysis results.

[1856] Output: Advice.

[1857] Server: Provides expert advice to users on their dashboard.

[1858] Enter: Advice.

[1859] Output: Dashboard update.

[1860] Step 5:

[1861] Emotion Engine Functions

[1862] User: While using the system, the emotion engine analyzes facial expressions, voice, and input in real time.

[1863] Input: facial expressions, voice, input content.

[1864] Output: Emotion data.

[1865] Emotion engine: Recognizes the user's emotional state and sends the results to the server.

[1866] Input: Emotion data.

[1867] Output: Emotional state.

[1868] Server: Tailors financial reports and expert advice based on information from the sentiment engine.

[1869] Input: Emotional state.

[1870] Output: Tailored reports and advice.

[1871] (Application example 2)

[1872] 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."

[1873] Conventional financial data management systems can efficiently manage users' financial data and provide predictions and expert advice based on AI analysis, but they have difficulty taking the user's emotional state into account. As a result, they are unable to provide appropriate advice based on the user's emotions, and are unable to provide effective support in situations where the user feels stressed or anxious. Therefore, there is a growing need for a system that can recognize the user's emotional state in real time and provide personalized financial advice accordingly.

[1874] 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.

[1875] In this invention, the server includes means for inputting or linking financial data, means for saving the input financial data, means for sending the saved financial data to an AI engine for analysis, means for generating a report based on the analysis results, means for providing the generated report to a user, means for acquiring the user's emotional state, means for adjusting the report based on the acquired emotional state, and means for customizing expert advice based on the emotional state, thereby making it possible to provide personalized advice and services according to the user's emotional state.

[1876] "Financial Data" means information about your income, expenses, investments and assets.

[1877] "Input means" refers to interfaces and devices through which users input financial data.

[1878] "Storage means" refers to a database or storage system for securely storing input financial data.

[1879] The "AI engine" is an artificial intelligence program that analyzes stored financial data and makes predictions about the user's financial status and future prospects.

[1880] "Analysis means" refers to the functions and programs that enable the AI ​​engine to process financial data and derive analytical results.

[1881] "Report generation means" refers to a device or function that creates a report to be provided to the user based on the results of AI analysis.

[1882] "Providing means" refers to a means for displaying or notifying the user of the generated report or expert advice.

[1883] "Emotional state" refers to a psychological state that is inferred based on the user's facial expression, voice, and input content.

[1884] "Acquisition means" refers to sensors and software for acquiring the user's emotional state.

[1885] The "adjustment means" is a function for changing the content of reports and advice based on the acquired emotional state.

[1886] "Expert advice" means guidance or recommendations provided by a professional with financial or investment knowledge.

[1887] "Means for customization" refers to a function that allows the content of expert advice to be appropriately adjusted according to the user's emotional state.

[1888] The system of the present invention aims to support users in making economic decisions by allowing them to efficiently manage their financial data and receive AI analysis results and expert advice. In addition, by combining it with an emotion engine, it is possible to provide personalized advice and services according to the user's emotional state.

[1889] Overall system configuration

[1890] The system consists of a user's device, a server, an AI engine, an emotion engine, and an expert. The user's device provides the interface that the user operates, and the server is responsible for storing, processing, and analyzing data. The AI ​​engine is responsible for analyzing the user's financial data, and the emotion engine recognizes the user's emotional state. The expert provides final advice.

[1891] User registration and authentication

[1892] A user accesses the system to create a new account, enters the required information (name, email address, password) and submits the registration form. The user's device sends the entered information to the server. The server stores the received information in a database and sends a confirmation email to the user. When the user clicks the link in the confirmation email, the server completes account authentication.

[1893] Financial data input and integration

[1894] Users enter bank account, investment account, and credit card information into the system. Financial data can also be automatically retrieved using API integration with external services. The user's device sends the entered or retrieved data to the server. The server receives the financial data and stores it in a database in a secure manner.

[1895] AI analysis and report generation

[1896] The server sends the stored financial data to the AI ​​engine, which analyzes the user's income, expenses, investment patterns, etc. and generates predictions. The server receives the analysis results from the AI ​​engine, generates easy-to-understand reports, and displays them on the user's dashboard.

[1897] Providing expert advice

[1898] The user sends a request for advice from an expert based on the analysis results. The user's device sends the request to the server. The server selects an appropriate expert and provides the user's financial data and AI analysis results. The expert creates specific advice based on the provided information and sends it to the server. The server displays the expert's advice on the user's dashboard.

[1899] Emotion Engine Functions

[1900] While a user is using the system, the emotion engine analyzes the user's facial expressions, voice, input, etc. in real time. The emotion engine recognizes the user's emotional state and sends the results to the server. The server then adjusts financial reports and expert advice based on the information from the emotion engine.

[1901] Specific examples

[1902] For example, consider a user who connects their bank and investment accounts to the system. The user first enters their account information or sets up an API connection. The system then sends this data to the server, which securely stores it. The AI ​​engine then analyzes this data and generates a report predicting the user's income, expenses, and investment trends. This report is then displayed on the user's dashboard, allowing the user to understand their financial situation at a glance.

[1903] Furthermore, the emotion engine recognizes the user's emotional state, and if the user is stressed, for example, the report display will be adjusted to be simple and easy to understand. Expert advice will also be tailored to the user's emotions. For example, if the user is excited, it will suggest a low-risk investment strategy, and if the user is calm, it will provide a detailed investment plan.

[1904] Example prompts to be input to the generative AI model

[1905] The system uses a camera to capture the user's facial expressions and performs emotion recognition to determine the user's emotional state. Based on the acquired emotional state, an AI engine analyzes financial data and generates financial advice that takes into account the user's recent spending patterns and income situation. The expert advice is also customized according to the user's emotional state, such as encouraging conservative spending when the user is nervous, or providing a detailed investment plan when the user is relaxed.

[1906] The above is an embodiment of the present invention, which provides personalized financial advice based on the user's emotional state, enabling more effective financial decision-making.

[1907] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1908] Step 1:

[1909] A user creates a new account, enters the required information (name, email address, password) and submits the registration form. The input is made through the user's terminal, and this information is sent as output to the server.

[1910] Step 2:

[1911] The server stores the received user information in a database and sends a confirmation email to the user, which includes an authentication link. Data processing involves storing the information, generating and sending the confirmation email.

[1912] Step 3:

[1913] The user clicks on the link in the confirmation email and the server completes the account authentication. The input is the user's click, and the output is the authenticated account being enabled.

[1914] Step 4:

[1915] Users enter their bank account, investment account, and credit card information into the system. This information is sent from the user's device to the server. Financial data can also be automatically retrieved from external services via API integration.

[1916] Step 5:

[1917] The server receives and securely stores the user's financial data, which is a combination of data entered and data from external services.

[1918] Step 6:

[1919] The server sends the stored financial data to the AI ​​engine. The input is the stored financial data, and the output is the analysis results by the AI ​​engine.

[1920] Step 7:

[1921] The AI ​​engine analyzes users' income, expenditure, and investment patterns to generate predictions. Data processing uses pattern recognition, statistical analysis, and predictive algorithms.

[1922] Step 8:

[1923] The server receives the analysis results from the AI ​​engine and generates reports for display on the user's dashboard, including visualizations and summaries of the analysis results.

[1924] Step 9:

[1925] The user sends a request for expert advice based on the analysis results from the terminal to the server. The input is the user's request, and the request information is saved on the server as the output.

[1926] Step 10:

[1927] The server selects an appropriate expert and provides the user's financial data and the AI ​​analysis results. The input is the user's request and the analysis results, and the output is information provided to the expert.

[1928] Step 11:

[1929] The expert creates advice based on the provided information and sends it to the server. The input is the information received by the expert, and the output is specific advice.

[1930] Step 12:

[1931] The server provides the expert advice for display on the user's dashboard, where the advice is displayed on the user's device.

[1932] Step 13:

[1933] The emotion engine analyzes the user's facial expressions, voice, input content, etc. in real time and sends the emotional state to the server. The input is the user's emotional data, and the output is the recognized emotional state.

[1934] Step 14:

[1935] The server adjusts the financial reports and expert advice based on the information from the emotion engine, adjusting the display and advice accordingly depending on the emotional state.

[1936] Step 15:

[1937] Users receive tailored reports and advice, enabling them to make more effective financial decisions. The output is personalized financial advice.

[1938] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1939] 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.

[1940] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1941] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1942] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1943] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1944] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1945] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1946] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1947] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1948] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1949] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1950] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1951] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1952] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1953] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1954] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1955] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1956] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1957] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1958] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1959] The following is further disclosed regarding the above embodiment.

[1960] (Claim 1)

[1961] A means for inputting or linking financial data;

[1962] a means for storing the entered financial data;

[1963] A means of transmitting the stored financial data to an AI engine for analysis;

[1964] a means for generating reports based on the analysis results;

[1965] a means for providing the generated report to a user;

[1966] A system including:

[1967] (Claim 2)

[1968] A means for consulting with experts based on the results of the analysis of financial data;

[1969] a means for providing expert advice to users;

[1970] The system of claim 1 further comprising:

[1971] (Claim 3)

[1972] API integration means for linking with external services,

[1973] A means to store and analyze financial data obtained from external services;

[1974] The system of claim 1 further comprising:

[1975] "Example 1"

[1976] (Claim 1)

[1977] A means for inputting or linking financial data;

[1978] a means for storing the entered financial data;

[1979] A means of transmitting the stored financial data to an AI engine for analysis;

[1980] a means for generating reports based on the analysis results;

[1981] a means for providing the generated report to a user;

[1982] A means for a user to create a new account and for the server to send a confirmation email and authenticate the account;

[1983] A system including:

[1984] (Claim 2)

[1985] A means for consulting with experts based on the results of the analysis of financial data;

[1986] a means for providing expert advice to users;

[1987] means for a user to submit a request for advice from a specialist;

[1988] The server selects appropriate experts and provides users with financial data and AI analysis results.

[1989] a means for experts to provide advice;

[1990] a means for the server to display the advice on the user's dashboard;

[1991] The system of claim 1 further comprising:

[1992] (Claim 3)

[1993] API integration means for linking with external services,

[1994] A means to store and analyze financial data obtained from external services;

[1995] A means for the user's device to send input information to the server via an HTTP POST request;

[1996] The system of claim 1 further comprising:

[1997] "Application Example 1"

[1998] (Claim 1)

[1999] A means of inputting or linking financial data;

[2000] a means for storing the entered financial data;

[2001] A means of transmitting the stored financial data to an AI engine for analysis;

[2002] a means for generating reports based on the analysis results;

[2003] a means for providing the generated report to a user;

[2004] A means of automatically synchronizing payment information;

[2005] A means of performing AI analysis in real time,

[2006] A system including:

[2007] (Claim 2)

[2008] A means for consulting with experts based on the results of the analysis of financial data;

[2009] a means for providing expert advice to users;

[2010] A means of sending automated emails when requesting expert advice;

[2011] The system of claim 1 further comprising:

[2012] (Claim 3)

[2013] API integration means for linking with external services,

[2014] A means to store and analyze financial data obtained from external services;

[2015] a means for displaying real-time prediction results to a user;

[2016] The system of claim 1 further comprising:

[2017] "Example 2: Combining Emotion Engines"

[2018] (Claim 1)

[2019] A means for inputting or linking financial data;

[2020] a means for storing the entered financial data;

[2021] A means of transmitting the stored financial data to an AI engine for analysis;

[2022] a means for generating reports based on the analysis results;

[2023] a means for providing the generated report to a user;

[2024] an emotion engine that recognizes the user's emotions;

[2025] means for adjusting report content based on the emotional state recognized by the emotion engine;

[2026] A system including:

[2027] (Claim 2)

[2028] A means for consulting with experts based on the results of the analysis of financial data;

[2029] a means for providing expert advice to users;

[2030] means for adjusting advice content based on the emotional state recognized by the emotion engine;

[2031] The system of claim 1 further comprising:

[2032] (Claim 3)

[2033] API integration means for linking with external services,

[2034] A means to store and analyze financial data obtained from external services;

[2035] The system of claim 1 further comprising:

[2036] "Application example 2 when combining emotion engines"

[2037] (Claim 1)

[2038] A means of inputting or linking financial data;

[2039] a means for storing the entered financial data;

[2040] A means of transmitting the stored financial data to an AI engine for analysis;

[2041] a means for generating reports based on the analysis results;

[2042] a means for providing the generated report to a user;

[2043] means for capturing an emotional state of a user;

[2044] a means for adjusting the report based on the captured emotional state;

[2045] a means to customize expert advice based on emotional state;

[2046] A system including:

[2047] (Claim 2)

[2048] A means for consulting with experts based on the results of the analysis of financial data;

[2049] a means for providing expert advice to users;

[2050] means for adjusting the generated reports and expert advice according to the emotional state of the user;

[2051] The system of claim 1 further comprising:

[2052] (Claim 3)

[2053] API integration means for linking with external services,

[2054] A means to store and analyze financial data obtained from external services;

[2055] input means for recognizing the emotional state of a user;

[2056] The system of claim 1 further comprising: [Explanation of symbols]

[2057] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for inputting or linking financial data; a means for storing the entered financial data; A means of transmitting the stored financial data to an AI engine for analysis; a means for generating reports based on the analysis results; a means for providing the generated report to a user; A system including:

2. A means for consulting with experts based on the results of the analysis of financial data; a means for providing expert advice to users; The system of claim 1 further comprising:

3. API integration means for linking with external services, A means to store and analyze financial data obtained from external services; The system of claim 1 further comprising:

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