system

Abstract

We provide the system. [Solution] A database means for receiving and storing users' financial information, A generation means for automatically generating an asset management plan based on the aforementioned financial information, A notification means for notifying the user of the asset management plan generated by the generation means, A monitoring system that monitors user spending in real time and issues alerts when the budget is exceeded, A proposal method that evaluates insurance information and suggests the most suitable insurance product, Educational methods for delivering educational content to users, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, many individuals are compelled to make financial plans for the future, but they have difficulties in managing complex financial information and formulating and implementing efficient asset management plans. In addition, there is a lack of appropriate risk management, review of insurance, and provision of financial education, which affect the individual's financial health. Conventionally, individual services are often provided separately, and there is a need for a method to solve these problems integratively.

Means for Solving the Problems

[0005] This invention provides a system for comprehensively managing users' financial information. Specifically, it securely stores financial information such as income, expenses, assets, and liabilities entered by the user in a database, and uses AI technology to automatically generate and notify users of an optimal asset management plan based on that data. It also monitors expenses in real time and issues alerts when budgets are exceeded, preventing users from wasting money. Furthermore, it periodically evaluates insurance information, proposes the most suitable insurance products, and provides users with financial education content, thereby realizing integrated financial management. In this way, it is possible to comprehensively support individual financial health and reduce anxiety about the future.

[0006] "Financial information" refers to financial data of an individual or corporation, such as income, expenses, assets, and liabilities.

[0007] A "database means" is a system or device that has the function of systematically storing information and enabling efficient access and management as needed.

[0008] A "generation means" is a mechanism or algorithm that has the function of automatically producing results suitable for a specific purpose or use based on input data or conditions.

[0009] A "notification means" is a technology or process that has the function of transmitting specified information to a specific recipient.

[0010] A "monitoring device" is a mechanism that has the function of continuously or periodically observing a specific object and recording or reporting its state or changes.

[0011] A "proposal mechanism" is a system or algorithm for recommending a particular action or choice based on analysis or evaluation.

[0012] "Educational tools" are methods, techniques, or devices designed to support learning and the transfer of knowledge.

[0013] "Evaluation methods" refer to devices or algorithms used to measure and judge the value or performance of an object based on specific criteria or indicators.

[0014] "Simulation" refers to techniques and methods for analyzing and evaluating the dynamics of a real-world situation by simulating it.

[0015] "Protective measures" are technologies, processes, or devices used to protect information or assets from unauthorized access or loss. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] <0000,101>First, the terms used in the following description will be explained.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

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

[0026] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

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

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0033] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system for supporting the financial management of individuals and corporations, providing a comprehensive platform that combines convenience and security. Specific embodiments are described below.

[0038] First, users can input their daily income, expenses, assets, and liabilities using a dedicated application or web portal. The entered data is encrypted by the device and securely transmitted to the server. The server stores this information in a database, ensuring it is readily accessible when needed.

[0039] Next, the server uses a generation algorithm to automatically generate an asset management plan tailored to the user's goals and lifestyle, based on the collected financial information. This plan is optimized by analyzing historical data and simulating multiple market trends. For example, if the user wants to buy a house in the future, the server will suggest monthly savings amounts and investment strategies.

[0040] The generated operational plan is provided to the user through a notification system. The user can then approve or request modifications to the presented plan. While the plan is in operation, the server monitors spending in real time and sends an alert to the terminal if spending is likely to exceed the set budget.

[0041] Furthermore, the server periodically evaluates the user's insurance policies and suggests the most suitable insurance products based on the latest information. For example, it can suggest a review of life insurance to a user who has recently had a child. In this way, the system manages risks according to the user's life events.

[0042] Furthermore, the device delivers educational content designed to improve users' financial skills. This content is customized and broadly covers topics ranging from basic investment knowledge to advanced strategies, tailored to user needs. This allows users to deepen their understanding of finance and build confidence through self-study.

[0043] Overall, this system helps simplify and effectively manage complex financial operations while ensuring the security of user data through regular audits and protective measures.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] Users enter their income, expenses, assets, and liabilities through a dedicated application or web portal.

[0047] Step 2:

[0048] The terminal receives the financial information entered by the user and securely transmits the data to the server using the latest encryption protocols.

[0049] Step 3:

[0050] The server stores the received financial information in a database and uses this information to perform a detailed analysis of the user's financial situation.

[0051] Step 4:

[0052] The server uses the analyzed data to generate an asset management plan using an AI algorithm. The plan is optimized considering the user's goals and market trends.

[0053] Step 5:

[0054] The server presents the generated asset management plan to the user via a notification system and awaits their approval or request for modification.

[0055] Step 6:

[0056] The user reviews the presented plan and makes modifications or approvals as needed.

[0057] Step 7:

[0058] The server monitors the user's spending in real time and sends an alert to the terminal if it is about to exceed the set budget.

[0059] Step 8:

[0060] The server periodically evaluates the user's insurance policy and, as appropriate, suggests the most suitable insurance product.

[0061] Step 9:

[0062] The device supports learning by delivering appropriate finance education materials based on the educational content selected by the user.

[0063] Step 10:

[0064] The server audits each process to protect user data and maintain overall system security.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] In today's world, personal and corporate financial management is becoming increasingly complex, making it difficult for many users to manage their assets and risks effectively. Furthermore, with the increasing emphasis on information security and privacy protection, there is a need to securely manage users' financial information while efficiently proposing optimal asset management plans. Providing learning opportunities to improve financial literacy is also a challenge.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes information management means for receiving and storing the user's financial information, protection means for encrypting and securely transmitting the financial information, and generation means for automatically generating an asset management plan based on the financial information. This allows the user to receive an appropriate and optimized asset management plan while securely managing their information. In addition, it can provide effective utilization of financial information and learning support.

[0070] "Information management means" refers to technical means for receiving and securely storing financial data provided by users.

[0071] "Protection measures" refer to technical means that encrypt users' financial information and ensure security during data transmission and reception.

[0072] "Generation means" refers to a technical function that analyzes collected financial data and automatically generates an optimal asset management plan for the user.

[0073] "Communication means" refers to information transmission functions used to notify users of the generated asset management plan.

[0074] "Monitoring measures" refer to technical means for tracking user spending in real time and detecting potential budget overruns.

[0075] A "proposal method" is a technical means that evaluates a user's insurance-related information and, based on that evaluation, presents the most suitable financial product.

[0076] "Learning support methods" refer to methods of providing users with educational materials to improve their financial knowledge.

[0077] "Evaluation means" refers to a technical function that simulates the generated asset management plan using multiple factors such as market trends and evaluates its validity.

[0078] "Analysis means" refers to technical means that analyze market trends and process the information necessary for optimizing asset management plans using AI models.

[0079] This invention is a complex system that supports the smooth financial management of individuals and corporations. This system allows users to input financial information using a dedicated application or web portal, and generates an optimal asset management plan based on that information. Detailed embodiments are described below.

[0080] First, users input information about their income, expenses, assets, and liabilities using a personal computing device or mobile terminal. This information is encrypted by the terminal and transmitted to the server via a security protocol. Data security is ensured by employing AES-256 encryption technology.

[0081] The server stores the received financial information in a relational database system. This step utilizes a MySQL® database to achieve high-speed data access and efficient management. The stored data is analyzed using Python and various data processing libraries (e.g., Pandas). An AI model is used to generate an asset management plan from the collected financial information. To consider market conditions, market trends are simulated using TENSORFLOW®, and various scenario analyses are performed. In this process, an optimized plan is generated using evaluation methods.

[0082] The generated investment plan is provided to the user via push notification or email. Through this, the user can review the proposed investment plan and request revisions as needed. Meanwhile, the server monitors income and expenses in real time and sends a special alert to the device if the budget is exceeded.

[0083] In addition, it includes a function to evaluate insurance information and suggest the most suitable products. This enables enhanced risk management tailored to the user's lifestyle. Furthermore, the device provides users with a wide range of educational content, from basic knowledge about asset management to specific strategies. This learning content is individually customized, allowing users to acquire knowledge that suits their individual needs.

[0084] For example, if a user has a goal such as "I want to save 300,000 yen to buy a car in three years," the server will use this to suggest the best savings plan and investment method. This suggestion is generated based on prompt statements like the following:

[0085] "A user wants to save 300,000 yen over the next three years. Considering their current income, expenses, and asset information, what savings plan and investment strategy would you propose?"

[0086] This allows the system to support users' daily financial activities and assist in promoting optimal asset building.

[0087] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0088] Step 1:

[0089] Users enter financial information using a dedicated application or web portal. Input fields include income, expenses, assets, and liabilities. Users specifically enter data such as, "This month's income is 500,000 yen, and expenses are 300,000 yen." This information is temporarily stored on the device.

[0090] Step 2:

[0091] The terminal encrypts the user's financial information entered. Encryption technologies such as AES-256 are used to ensure data security. The encrypted data is sent to the server using the HTTPS protocol. Input is unencrypted user data, and output is encrypted user data. Specifically, the terminal automatically performs the encryption process in the background.

[0092] Step 3:

[0093] The server decrypts the received encrypted data and stores it in a relational database system. The database system used is MySQL, which efficiently manages each user's information. The input is encrypted data, and the output is the decoded data stored in the database. After decryption, the information is written to the database very quickly.

[0094] Step 4:

[0095] The server uses a generative AI model to analyze the user's financial information and automatically generate an optimal asset management plan. It uses Python and the Pandas library to create a dataframe and simulate various market trends, including historical data. The input is stored user data, and the output is the optimal investment plan. Specifically, the server uses TensorFlow to rapidly execute hundreds of thousands of simulations and selects the plan best suited to each user.

[0096] Step 5:

[0097] The server sends the generated operational plan to the user via a notification system. The user can review the plan via smartphone or PC and request revisions if necessary. The input is the generated operational plan, and the output is the plan notification and user feedback. The server sends push notifications quickly to ensure the user can review the plan immediately.

[0098] Step 6:

[0099] The server monitors user spending in real time and sends a warning to the terminal if the budget is about to be exceeded. Real-time functionality is ensured by using WebSockets. The input is the user's current spending status, and the output is a warning notification. The server immediately monitors real-time data and issues alerts as needed.

[0100] Step 7:

[0101] The server evaluates the user's insurance information and suggests the latest financial products. It uses machine learning to perform analysis based on customer profiles. K-Means clustering is used to group user attributes and select appropriate insurance products. The input is the user's profile information, and the output is the suggested financial products. The server provides the user with the presented options via email or app notification as needed.

[0102] Step 8:

[0103] The device delivers educational content to improve users' financial skills. This content includes videos, quizzes, and articles. Input is the user's learning needs, and output is customized learning content. The device has the capability to deliver optimal content tailored to the user's level and goals.

[0104] (Application Example 1)

[0105] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0106] In modern times, managing finances efficiently and securely for individuals and corporations has become increasingly complex. While real-time tracking of expenses and planned asset management are crucial amidst diverse spending patterns, doing so manually is difficult. Furthermore, the widespread use of electronic transactions demands rapid expense management, yet there is a lack of systems that can automatically provide users with suitable asset management and savings suggestions. The objective of this invention is to solve these problems.

[0107] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0108] In this invention, the server includes an information management means for receiving and storing financial information, a transaction recording means for acquiring electronic transaction information in real time and automatically recording expenditures, and a monitoring means for monitoring the user's expenditures and issuing alerts when the budget is exceeded. This enables the user to manage their finances in real time, preventing budget overruns and automatically supporting planned asset management.

[0109] "Information management means" refers to a device or program that has the function of receiving a user's financial information and securely storing and managing it.

[0110] A "plan generation means" is a device or program that has the function of automatically generating an asset management plan suitable for the user based on the financial information received.

[0111] "Information provision means" refers to a device or program that has the function of notifying users of generated asset management plans and other related information and prompting them to take necessary actions.

[0112] A "monitoring device" is a device or program that has the function of monitoring a user's spending in real time and detecting the possibility of budget overruns.

[0113] A "transaction recording device" is a device or program that has the function of acquiring electronic transaction information in real time and automatically recording expenditures.

[0114] A "behavioral suggestion device" is a device or program that has the function of generating specific action suggestions to support users in achieving their savings goals.

[0115] A "proposal means" is a device or program that has the function of evaluating the user's insurance information and proposing the most suitable insurance product.

[0116] An "educational tool" is a device or program that has the function of delivering educational content to improve users' financial literacy.

[0117] The system for realizing this invention primarily functions through data communication between a server and a user's terminal. The server is programmed to implement information management means, plan generation means, information provision means, monitoring means, transaction recording means, action suggestion means, suggestion means, and education means. This set of programs provides a smooth and comprehensive financial management experience.

[0118] Specifically, the server manages the financial information received from users and securely stores the information using encryption technologies such as AES. The plan generation means utilizes machine learning algorithms to formulate an asset management plan based on the user's past transactions and goal setting. Next, the information provision means quickly notifies the user's terminal of the generated information. The monitoring means uses real-time data stream processing technology to continuously monitor whether the user's spending is within budget.

[0119] On the terminal, users actually use this system in their daily activities. For example, a smartphone app transmits electronic payment information to the server in real time via a transaction recording device, and expenditures are recorded and updated. The action suggestion device provides users with specific asset management advice to help them achieve their savings goals. In this way, the terminal and server work together to enhance the user's financial management.

[0120] As a concrete example, when a user makes a purchase using their mobile device, that information is immediately sent to the server. The user's asset management plan is then automatically updated, and comprehensive financial information becomes available on the user's device.

[0121] An example of a prompt message when using a generative AI model would be: "Design a user budget management and spending analysis algorithm based on electronic payment history. Include features for optimizing asset management plans based on user goals and providing real-time alerts."

[0122] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0123] Step 1:

[0124] The user makes an electronic payment using a terminal. The terminal retrieves this transaction information and transmits it to the server using a secure communication protocol. The input is electronic payment information, and the output is encrypted transaction data. The data is retrieved instantly, and security is ensured during communication.

[0125] Step 2:

[0126] The server decrypts the received transaction information and stores it in a database through an information management system. The input is encrypted transaction data, and the output is the decrypted transaction information stored in the database. The server uses encryption technology to decrypt the data and stores it in a data store for information management.

[0127] Step 3:

[0128] The server operates a plan generation system that updates the asset management plan based on the user's latest transaction information. Inputs are the latest transaction information and pre-stored financial data, and output is the updated asset management plan. The server uses machine learning algorithms to recalculate the asset management plan.

[0129] Step 4:

[0130] The monitoring system operates to check in real time whether the user's spending is within the set budget. The input is real-time spending data, and the output is a warning for exceeding the budget or a notification that there is no problem. The server sets spending thresholds and generates an alert if these are exceeded.

[0131] Step 5:

[0132] Through the action suggestion mechanism, the server generates optimal action suggestions for the user and notifies the terminal. The input is the updated asset management plan and budget status, and the output is a suggestion of specific savings actions. The server determines the need for plan changes and shows the user improvement measures.

[0133] Step 6:

[0134] Through educational methods, the server regularly delivers content designed to improve users' financial skills. The input is the user's learning history and interests, and the output is individually customized educational content. The server utilizes a generative AI model to provide a personalized educational program.

[0135] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0136] This invention combines an emotion engine with a system that supports personal financial management to provide optimal financial advice tailored to the user's emotional state. The operation of this system involves the combination of several key components and their respective functions.

[0137] First, users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal. The terminal receives this information, encrypts it, and securely transmits it to the server. The server stores the received data in a database and analyzes the user's financial situation.

[0138] Next, the server uses a generation algorithm to automatically generate an asset management plan that takes into account the user's goals and market trends. The emotion engine plays a crucial role here. It collects emotional data from the user's facial expressions, voice, and text feedback, and analyzes their stress level and psychological state. This information is reflected in the generated plan, providing a flexible plan tailored to the user's situation.

[0139] For example, if a user is experiencing high stress levels, the system will suggest a low-risk investment plan. The emotion engine also provides advice and educational content to help users overcome psychological barriers when making financial decisions. In this way, the emotion engine offers insights beyond mere financial data.

[0140] The server collects sentiment data and analyzes long-term trends based on it. This data is then fed back into operational planning and risk assessment. For example, if a user regularly expresses anxiety, the proposed plan will incorporate a more conservative operational approach than usual.

[0141] Furthermore, the real-time monitoring feature immediately sends an alert if a user's spending is likely to exceed their budget. This helps users prevent unnecessary spending and reduces their mental burden.

[0142] Finally, to advance the user's financial education, the system delivers educational content tailored to the user's interests and needs to their device. The emotion engine understands how effectively the user is learning the content and adjusts it as needed. In this way, a system is realized that provides comprehensive support while taking into account the user's emotional state.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] Users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal.

[0146] Step 2:

[0147] The terminal receives the financial information entered by the user and securely transmits the data to the server using an encryption protocol.

[0148] Step 3:

[0149] The server stores the received financial information in a database and uses an analysis algorithm to analyze the user's financial situation.

[0150] Step 4:

[0151] While the user is using the application, the device acquires emotional data through the camera, microphone, text input, etc. This information includes facial expressions, voice tone, and keyboard touch speed.

[0152] Step 5:

[0153] The server processes emotional data sent from the terminal to identify the user's emotional state. It uses emotion recognition algorithms to measure stress levels and psychological barriers.

[0154] Step 6:

[0155] The server automatically generates an asset management plan using an AI algorithm based on the user's financial information and emotional state. The generated plan takes the user's emotional state into consideration and appropriately adjusts the risk level.

[0156] Step 7:

[0157] The server notifies the terminal of the generated asset management plan and allows the user to review its contents. The user can then approve or request modifications to the plan.

[0158] Step 8:

[0159] The user reviews the plan and approves or modifies it as needed. The server waits for the response and applies the plan.

[0160] Step 9:

[0161] The server monitors user spending in real time and immediately sends an alert to the terminal if there is a possibility of budget overrun. This monitoring is also adjusted based on stress levels read from emotional data.

[0162] Step 10:

[0163] The server periodically evaluates the user's insurance information and suggests the most suitable insurance product. This process also takes emotional data into account, reflecting the user's anxieties about insurance.

[0164] Step 11:

[0165] The device delivers personalized finance education content based on emotional data and learning trends. This allows users to effectively acquire knowledge and gain confidence in financial management.

[0166] (Example 2)

[0167] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0168] Providing appropriate asset management plans that take into account the emotional state of users is a challenging task in financial management. Furthermore, it is necessary to reduce the psychological barriers users feel when making financial decisions and provide support that allows them to confidently follow the plan. In addition, monitoring users' spending in real time to prevent budget overruns, as well as providing educational content that meets users' learning needs, are also crucial challenges.

[0169] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0170] In this invention, the server includes a storage means for receiving and storing the user's financial information, a calculation means for automatically generating an asset management plan based on the financial information, and an analysis means for analyzing emotional data and reflecting it in the generated plan. This enables the generation of flexible asset management plans tailored to the user's emotional state and provides support for financial decisions.

[0171] A "storage device" is a device or function for storing financial information received from a user, and it is capable of storing and retrieving data.

[0172] A "calculation means" refers to a process or device for automatically creating an asset management plan based on received financial information.

[0173] "Communication means" refers to a device or function for notifying the user of the generated asset management plan.

[0174] "Monitoring measures" refer to devices or functions that monitor user spending in real time and issue warnings if there is a possibility of exceeding the budget.

[0175] "Analysis means" refers to a function or device that collects and analyzes user emotional data and reflects the results in an asset management plan.

[0176] "Support measures" refer to devices or functions that, based on emotional data, support users' financial decisions and reduce psychological barriers.

[0177] A "feedback mechanism" is a device or function that feeds back emotional trends, analyzed over a long period, into the revision of investment plans and risk assessments.

[0178] "Educational tools" refer to devices or functions that deliver learning content to users and track their progress.

[0179] This invention is a system that supports financial management while taking into account the emotional state of the user, and is configured as follows.

[0180] First, users enter financial information such as income, expenses, assets, and liabilities into their device via a dedicated application or web portal. This information is securely encrypted by the device and transmitted to the server using the SSL / TLS protocol.

[0181] The server stores the received information in a database and uses it as a storage device. During this process, data sanitization is performed to check for abnormal values ​​and errors. Next, the server uses a generative AI model, which is its computational tool, to automatically generate an asset management plan based on the user's financial data and market trend data. An example of a prompt message to the generative AI model would be, "Please create an optimal asset management plan based on current market trends."

[0182] The device collects user emotional data in real time through facial expressions, voice, and text data. This emotional data is then sent back to the server, where analysis tools are used to evaluate the user's stress level and psychological state, and this is reflected in the automatically generated operational plan. As a result, if a user is experiencing high stress, a lower-risk operational plan is adjusted and provided.

[0183] Furthermore, the server analyzes long-term sentiment trends as a feedback mechanism, and uses this information when reviewing operational plans and conducting risk assessments. In particular, if users regularly experience anxiety, the proposed plans will be adjusted to be more conservative.

[0184] Real-time spending monitoring is performed by server-based monitoring systems, and alerts are immediately sent to users when budget overruns are predicted. This helps prevent unnecessary spending and reduces mental stress.

[0185] Furthermore, the server acts as an educational tool, providing learning content based on the user's interests and needs. This content is adjusted as the system tracks how effectively the user is learning. This allows users to acquire deeper financial knowledge and gain a better understanding of their own financial situation.

[0186] In this way, a system is realized that supports safe and effective financial management while taking into account the user's emotional state.

[0187] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0188] Step 1:

[0189] Users input financial information such as income, expenses, assets, and liabilities into a terminal using a dedicated application or web portal. This input data is fundamental information for gaining a detailed understanding of the user's financial situation.

[0190] Step 2:

[0191] The terminal receives the entered financial information, encrypts the data using the SSL / TLS protocol, and sends it to the server. This process ensures the safety and security of the data. The output is encrypted financial data.

[0192] Step 3:

[0193] The server stores the received encrypted data in a database. Here, data sanitization is performed, and data processing is carried out to check for outliers and errors, resulting in clean financial data being output.

[0194] Step 4:

[0195] The server uses a generation AI model to automatically generate asset management plans based on clean financial and market trend data. This calculation process outputs an optimal plan tailored to the user's goals. The prompt message used is in the format of "Please create an optimal asset management plan based on current market trends."

[0196] Step 5:

[0197] The device collects the user's facial expressions, voice, and text data in real time and sends it to the server as user emotion data. Here, data collection and basic processing of the emotion data take place.

[0198] Step 6:

[0199] The server uses analytical tools to evaluate stress levels and psychological states based on the received emotional data. A report of the evaluated emotional state is then generated through data calculations.

[0200] Step 7:

[0201] The server adjusts the generated asset management plan based on emotional data. It flexibly adjusts the plan, for example, suggesting a low-risk plan in cases of high stress, and outputs a final plan tailored to the user.

[0202] Step 8:

[0203] The server sends notifications regarding the operational plan to the terminal, and information is presented to the user based on these notifications. The user can then make financial decisions based on this information.

[0204] Step 9:

[0205] The server monitors user spending in real time and sends an alert to the terminal if the budget is exceeded. This monitoring system issues warnings prompting immediate action.

[0206] Step 10:

[0207] The server delivers educational content to the user's device based on their interests and needs. This process tracks learning progress and adjusts content as required.

[0208] Step 11:

[0209] The server analyzes long-term sentiment trends and feeds this back into risk assessment. This analysis yields trend analysis results that contribute to further adjustments to the operational plan.

[0210] (Application Example 2)

[0211] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0212] Traditional financial management systems managed assets and expenses without considering the emotional state of users, making it difficult to adequately address situations where users were prone to psychological stress. Furthermore, the lack of real-time feedback based on user emotion analysis made it difficult to propose flexible asset management plans that were sensitive to these emotions. This resulted in a problem where users' financial plans were often inappropriate, especially during economically unstable periods.

[0213] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0214] In this invention, the server includes emotion analysis means for analyzing the user's emotional state and providing real-time advice on spending based on that emotion; information management means for receiving and storing the user's financial information; and plan generation means for automatically generating an asset management plan based on the financial information. This enables personalized asset management plan suggestions tailored to the user's psychological state and real-time spending management.

[0215] "Information management means" refers to a device or software that has the function of storing and managing financial information received from users and securely storing it in a database.

[0216] A "plan generation means" is a device or software that has the function of automatically generating an asset management plan based on received financial information and designing a strategy that is suitable for the user's financial goals.

[0217] "Information notification means" refers to a device or software equipped with the function of notifying users of generated asset management plans and other important information.

[0218] A "monitoring device" is a device or software that has the function of monitoring a user's spending in real time and immediately issuing a warning if the set budget is likely to be exceeded.

[0219] A "selection suggestion means" is a device or software that has the function of evaluating the user's insurance information and suggesting the most suitable insurance product based on that information.

[0220] "Content distribution means" refers to a device or software that has the function of distributing educational content to users and supporting financial education.

[0221] "Emotional analysis means" refers to a device or software that analyzes a user's emotional state and provides real-time advice on spending based on that data.

[0222] The system for implementing this invention consists of three main elements: a user, a server, and a terminal.

[0223] Users input their financial information (income, expenses, assets, liabilities, etc.) via a device such as a smartphone. This information is encrypted on the device and securely transmitted to the server. The server receives and stores this data using an information management device and stores it in a database.

[0224] The server further analyzes the received financial information using a plan generation device and automatically generates an asset management plan tailored to the user's financial goals. This plan is immediately notified to the user through an information notification device.

[0225] The role of the sentiment analysis device is to analyze the user's voice and text data to evaluate their emotional state in real time. The information obtained from sentiment analysis is linked to the user's spending patterns, and the monitoring device displays a warning when spending approaches the budget limit. It also provides personalized spending advice to the user based on the sentiment data.

[0226] For example, if a user is feeling stressed while shopping, a notification might appear on their smartphone screen saying, "Why not hold off on making a big purchase for now and reconsider?" This allows for flexible asset management based on the user's emotions.

[0227] Furthermore, the selection and suggestion device evaluates insurance information and proposes the most suitable insurance product to the user. In addition, the content distribution device provides users with financial education content to support their knowledge improvement.

[0228] An example of input to the prompt generation AI model might be, "Generate an appropriate warning message to display when the user's emotional state is assessed as high stress."

[0229] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0230] Step 1:

[0231] The user inputs and transmits financial information via a terminal. This input includes income, expenses, assets, and liabilities. The terminal encrypts this information and securely transmits it to the server. The input here is the user's financial information, and the output is encrypted data.

[0232] Step 2:

[0233] The server receives encrypted data transmitted from the terminal, decrypts the financial information using an information management device, and stores it. The input is encrypted data, and the output is decoded financial information. This process allows the server to store each user's financial information in a database.

[0234] Step 3:

[0235] The server uses a plan generation device to analyze stored financial information and automatically generate an asset management plan based on the user's financial goals. The input is decoded financial information, and the output is the generated asset management plan. The resulting plan is structured as an asset strategy suitable for the user.

[0236] Step 4:

[0237] The generated asset management plan is communicated to the user via an information notification device. The input here is the generated asset management plan, and the output is a notification message to the user. This notification allows the user to gain information about their own financial policy.

[0238] Step 5:

[0239] The server analyzes the user's voice and text data through an emotion analysis device and evaluates their emotional state in real time. The input is the user's voice and text data, and the output is the analyzed emotion data. This allows for an accurate evaluation of the user's emotional state.

[0240] Step 6:

[0241] Based on the sentiment analysis results, the monitoring device evaluates the user's spending in real time and issues warnings as needed. The input here is the analyzed sentiment data and spending information, and the output is a warning notification to the user. Specifically, a notification such as "Is this purchase important? Perhaps you should think about it again?" might be sent.

[0242] Step 7:

[0243] The selection suggestion device evaluates stored insurance information and proposes the most suitable insurance product to the user. The input is the user's insurance information, and the output is information on the proposed insurance product. This process provides the user with the insurance selection that is expected to be most beneficial.

[0244] Step 8:

[0245] The content delivery device delivers educational content to help users improve their financial knowledge. The input is the user's learning needs, and the output is personalized educational content. Through this approach, users can effectively strengthen their financial knowledge.

[0246] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0247] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0248] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0249] [Second Embodiment]

[0250] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0251] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0252] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0253] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0254] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0255] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0256] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0257] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0258] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0259] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0260] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0261] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0262] This invention is a system for supporting the financial management of individuals and corporations, providing a comprehensive platform that combines convenience and security. Specific embodiments are described below.

[0263] First, users can input their daily income, expenses, assets, and liabilities using a dedicated application or web portal. The entered data is encrypted by the device and securely transmitted to the server. The server stores this information in a database, ensuring it is readily accessible when needed.

[0264] Next, the server uses a generation algorithm to automatically generate an asset management plan tailored to the user's goals and lifestyle, based on the collected financial information. This plan is optimized by analyzing historical data and simulating multiple market trends. For example, if the user wants to buy a house in the future, the server will suggest monthly savings amounts and investment strategies.

[0265] The generated operational plan is provided to the user through a notification system. The user can then approve or request modifications to the presented plan. While the plan is in operation, the server monitors spending in real time and sends an alert to the terminal if spending is likely to exceed the set budget.

[0266] Furthermore, the server periodically evaluates the user's insurance policies and suggests the most suitable insurance products based on the latest information. For example, it can suggest a review of life insurance to a user who has recently had a child. In this way, the system manages risks according to the user's life events.

[0267] Furthermore, the device delivers educational content designed to improve users' financial skills. This content is customized and broadly covers topics ranging from basic investment knowledge to advanced strategies, tailored to user needs. This allows users to deepen their understanding of finance and build confidence through self-study.

[0268] Overall, this system helps simplify and effectively manage complex financial operations while ensuring the security of user data through regular audits and protective measures.

[0269] The following describes the processing flow.

[0270] Step 1:

[0271] Users enter their income, expenses, assets, and liabilities through a dedicated application or web portal.

[0272] Step 2:

[0273] The terminal receives the financial information input by the user and securely transmits the data to the server using the latest encryption protocol.

[0274] Step 3:

[0275] The server stores the received financial information in the database and analyzes the user's financial situation in detail based on this.

[0276] Step 4:

[0277] The server utilizes the analyzed data to generate an asset management plan using AI algorithms. The plan is optimized considering the user's goals and market trends.

[0278] Step 5:

[0279] The server presents the generated asset management plan to the user via the notification means and waits for their approval or request for modification.

[0280] Step 6:

[0281] L [[]END]]The user checks the presented plan and makes modifications or approvals as necessary.

[0282] Step 7:

[0283] The server monitors the user's expenses in real time and sends an alert to the terminal if it is likely to exceed the set budget range.

[0284] Step 8:

[0285] The server periodically evaluates the user's insurance contracts and makes proposals for the most suitable insurance products as appropriate.

[0286] Step 9:

[0287] The device supports learning by delivering appropriate finance education materials based on the educational content selected by the user.

[0288] Step 10:

[0289] The server audits each process to protect user data and maintain overall system security.

[0290] (Example 1)

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

[0292] In today's world, personal and corporate financial management is becoming increasingly complex, making it difficult for many users to manage their assets and risks effectively. Furthermore, with the increasing emphasis on information security and privacy protection, there is a need to securely manage users' financial information while efficiently proposing optimal asset management plans. Providing learning opportunities to improve financial literacy is also a challenge.

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

[0294] In this invention, the server includes information management means for receiving and storing the user's financial information, protection means for encrypting and securely transmitting the financial information, and generation means for automatically generating an asset management plan based on the financial information. This allows the user to receive an appropriate and optimized asset management plan while securely managing their information. In addition, it can provide effective utilization of financial information and learning support.

[0295] "Information management means" refers to technical means for receiving and securely storing financial data provided by users.

[0296] "Protection measures" refer to technical means that encrypt users' financial information and ensure security during data transmission and reception.

[0297] "Generation means" refers to a technical function that analyzes collected financial data and automatically generates an optimal asset management plan for the user.

[0298] "Communication means" refers to information transmission functions used to notify users of the generated asset management plan.

[0299] "Monitoring measures" refer to technical means for tracking user spending in real time and detecting potential budget overruns.

[0300] A "proposal method" is a technical means that evaluates a user's insurance-related information and, based on that evaluation, presents the most suitable financial product.

[0301] "Learning support methods" refer to methods of providing users with educational materials to improve their financial knowledge.

[0302] "Evaluation means" refers to a technical function that simulates the generated asset management plan using multiple factors such as market trends and evaluates its validity.

[0303] "Analysis means" refers to technical means that analyze market trends and process the information necessary for optimizing asset management plans using AI models.

[0304] This invention is a complex system that supports the smooth financial management of individuals and corporations. This system allows users to input financial information using a dedicated application or web portal, and generates an optimal asset management plan based on that information. Detailed embodiments are described below.

[0305] First, the user uses a personal computing device or a mobile terminal to input information regarding income, expenses, assets, and liabilities. This information is encrypted by the terminal and transmitted to the server via a security protocol. The encryption technology adopts AES-256 to ensure data security.

[0306] The server stores the received financial information in a relational database system. In this step, the MySQL database is utilized to achieve high-speed data access and efficient management. The stored data is analyzed using Python and various data processing libraries (e.g., Pandas). A generative AI model is employed to generate an asset management plan from the collected financial information. When considering market conditions, etc., TensorFlow is used to simulate market trends and conduct various scenario analyses. In this process, an optimized plan is generated by an evaluation means.

[0307] The generated management plan is provided to the user via push notification or email. Through this, the user can confirm the proposed asset management plan and request modifications if necessary. On the other hand, the server monitors income and expenses in real-time and sends a special warning to the terminal when the budget is exceeded.

[0308] In addition, a function for evaluating insurance information and proposing optimal products is also installed. This enables strengthening of risk management according to the user's living situation. Furthermore, a wide range of educational content, from basic knowledge to specific strategies regarding asset management, is provided to the user from the terminal. Since this learning content is customized individually, users can acquire knowledge suitable for their individual needs.

[0309] As a specific example, when the user has a goal such as "wanting to save 300,000 yen to buy a car in 3 years", the server proposes the best savings plan and investment method based on this. This proposal is generated based on the following prompt text:

[0310] "A user wants to save 300,000 yen over the next three years. Considering their current income, expenses, and asset information, what savings plan and investment strategy would you propose?"

[0311] This allows the system to support users' daily financial activities and assist in promoting optimal asset building.

[0312] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0313] Step 1:

[0314] Users enter financial information using a dedicated application or web portal. Input fields include income, expenses, assets, and liabilities. Users specifically enter data such as, "This month's income is 500,000 yen, and expenses are 300,000 yen." This information is temporarily stored on the device.

[0315] Step 2:

[0316] The terminal encrypts the user's financial information entered. Encryption technologies such as AES-256 are used to ensure data security. The encrypted data is sent to the server using the HTTPS protocol. Input is unencrypted user data, and output is encrypted user data. Specifically, the terminal automatically performs the encryption process in the background.

[0317] Step 3:

[0318] The server decrypts the received encrypted data and stores it in a relational database system. The database system used is MySQL, which efficiently manages each user's information. The input is encrypted data, and the output is the decoded data stored in the database. After decryption, the information is written to the database very quickly.

[0319] Step 4:

[0320] The server uses a generative AI model to analyze the user's financial information and automatically generate an optimal asset management plan. It uses Python and the Pandas library to create a dataframe and simulate various market trends, including historical data. The input is stored user data, and the output is the optimal investment plan. Specifically, the server uses TensorFlow to rapidly execute hundreds of thousands of simulations and selects the plan best suited to each user.

[0321] Step 5:

[0322] The server sends the generated operational plan to the user via a notification system. The user can review the plan via smartphone or PC and request revisions if necessary. The input is the generated operational plan, and the output is the plan notification and user feedback. The server sends push notifications quickly to ensure the user can review the plan immediately.

[0323] Step 6:

[0324] The server monitors user spending in real time and sends a warning to the terminal if the budget is about to be exceeded. Real-time functionality is ensured by using WebSockets. The input is the user's current spending status, and the output is a warning notification. The server immediately monitors real-time data and issues alerts as needed.

[0325] Step 7:

[0326] The server evaluates the user's insurance information and suggests the latest financial products. It uses machine learning to perform analysis based on customer profiles. K-Means clustering is used to group user attributes and select appropriate insurance products. The input is the user's profile information, and the output is the suggested financial products. The server provides the user with the presented options via email or app notification as needed.

[0327] Step 8:

[0328] The device delivers educational content to improve users' financial skills. This content includes videos, quizzes, and articles. Input is the user's learning needs, and output is customized learning content. The device has the capability to deliver optimal content tailored to the user's level and goals.

[0329] (Application Example 1)

[0330] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0331] In modern times, managing finances efficiently and securely for individuals and corporations has become increasingly complex. While real-time tracking of expenses and planned asset management are crucial amidst diverse spending patterns, doing so manually is difficult. Furthermore, the widespread use of electronic transactions demands rapid expense management, yet there is a lack of systems that can automatically provide users with suitable asset management and savings suggestions. The objective of this invention is to solve these problems.

[0332] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0333] In this invention, the server includes an information management means for receiving and storing financial information, a transaction recording means for acquiring electronic transaction information in real time and automatically recording expenditures, and a monitoring means for monitoring the user's expenditures and issuing alerts when the budget is exceeded. This enables the user to manage their finances in real time, preventing budget overruns and automatically supporting planned asset management.

[0334] "Information management means" refers to a device or program that has the function of receiving a user's financial information and securely storing and managing it.

[0335] A "plan generation means" is a device or program that has the function of automatically generating an asset management plan suitable for the user based on the financial information received.

[0336] "Information provision means" refers to a device or program that has the function of notifying users of generated asset management plans and other related information and prompting them to take necessary actions.

[0337] A "monitoring device" is a device or program that has the function of monitoring a user's spending in real time and detecting the possibility of budget overruns.

[0338] A "transaction recording device" is a device or program that has the function of acquiring electronic transaction information in real time and automatically recording expenditures.

[0339] A "behavioral suggestion device" is a device or program that has the function of generating specific action suggestions to support users in achieving their savings goals.

[0340] A "proposal means" is a device or program that has the function of evaluating the user's insurance information and proposing the most suitable insurance product.

[0341] An "educational tool" is a device or program that has the function of delivering educational content to improve users' financial literacy.

[0342] The system for realizing this invention primarily functions through data communication between a server and a user's terminal. The server is programmed to implement information management means, plan generation means, information provision means, monitoring means, transaction recording means, action suggestion means, suggestion means, and education means. This set of programs provides a smooth and comprehensive financial management experience.

[0343] Specifically, the server manages the financial information received from users and securely stores the information using encryption technologies such as AES. The plan generation means utilizes machine learning algorithms to formulate an asset management plan based on the user's past transactions and goal setting. Next, the information provision means quickly notifies the user's terminal of the generated information. The monitoring means uses real-time data stream processing technology to continuously monitor whether the user's spending is within budget.

[0344] On the terminal, users actually use this system in their daily activities. For example, a smartphone app transmits electronic payment information to the server in real time via a transaction recording device, and expenditures are recorded and updated. The action suggestion device provides users with specific asset management advice to help them achieve their savings goals. In this way, the terminal and server work together to enhance the user's financial management.

[0345] As a concrete example, when a user makes a purchase using their mobile device, that information is immediately sent to the server. The user's asset management plan is then automatically updated, and comprehensive financial information becomes available on the user's device.

[0346] An example of a prompt message when using a generative AI model would be: "Design a user budget management and spending analysis algorithm based on electronic payment history. Include features for optimizing asset management plans based on user goals and providing real-time alerts."

[0347] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0348] Step 1:

[0349] The user makes an electronic payment using a terminal. The terminal retrieves this transaction information and transmits it to the server using a secure communication protocol. The input is electronic payment information, and the output is encrypted transaction data. The data is retrieved instantly, and security is ensured during communication.

[0350] Step 2:

[0351] The server decrypts the received transaction information and stores it in a database through an information management system. The input is encrypted transaction data, and the output is the decrypted transaction information stored in the database. The server uses encryption technology to decrypt the data and stores it in a data store for information management.

[0352] Step 3:

[0353] The server operates a plan generation system that updates the asset management plan based on the user's latest transaction information. Inputs are the latest transaction information and pre-stored financial data, and output is the updated asset management plan. The server uses machine learning algorithms to recalculate the asset management plan.

[0354] Step 4:

[0355] The monitoring system operates to check in real time whether the user's spending is within the set budget. The input is real-time spending data, and the output is a warning for exceeding the budget or a notification that there is no problem. The server sets spending thresholds and generates an alert if these are exceeded.

[0356] Step 5:

[0357] Through the action suggestion mechanism, the server generates optimal action suggestions for the user and notifies the terminal. The input is the updated asset management plan and budget status, and the output is a suggestion of specific savings actions. The server determines the need for plan changes and shows the user improvement measures.

[0358] Step 6:

[0359] Through educational methods, the server regularly delivers content designed to improve users' financial skills. The input is the user's learning history and interests, and the output is individually customized educational content. The server utilizes a generative AI model to provide a personalized educational program.

[0360] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0361] This invention combines an emotion engine with a system that supports personal financial management to provide optimal financial advice tailored to the user's emotional state. The operation of this system involves the combination of several key components and their respective functions.

[0362] First, users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal. The terminal receives this information, encrypts it, and securely transmits it to the server. The server stores the received data in a database and analyzes the user's financial situation.

[0363] Next, the server uses a generation algorithm to automatically generate an asset management plan that takes into account the user's goals and market trends. The emotion engine plays a crucial role here. It collects emotional data from the user's facial expressions, voice, and text feedback, and analyzes their stress level and psychological state. This information is reflected in the generated plan, providing a flexible plan tailored to the user's situation.

[0364] For example, if a user is experiencing high stress levels, the system will suggest a low-risk investment plan. The emotion engine also provides advice and educational content to help users overcome psychological barriers when making financial decisions. In this way, the emotion engine offers insights beyond mere financial data.

[0365] The server collects sentiment data and analyzes long-term trends based on it. This data is then fed back into operational planning and risk assessment. For example, if a user regularly expresses anxiety, the proposed plan will incorporate a more conservative operational approach than usual.

[0366] Furthermore, the real-time monitoring feature immediately sends an alert if a user's spending is likely to exceed their budget. This helps users prevent unnecessary spending and reduces their mental burden.

[0367] Finally, to advance the user's financial education, the system delivers educational content tailored to the user's interests and needs to their device. The emotion engine understands how effectively the user is learning the content and adjusts it as needed. In this way, a system is realized that provides comprehensive support while taking into account the user's emotional state.

[0368] The following describes the processing flow.

[0369] Step 1:

[0370] Users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal.

[0371] Step 2:

[0372] The terminal receives the financial information entered by the user and securely transmits the data to the server using an encryption protocol.

[0373] Step 3:

[0374] The server stores the received financial information in a database and uses an analysis algorithm to analyze the user's financial situation.

[0375] Step 4:

[0376] While the user is using the application, the device acquires emotional data through the camera, microphone, text input, etc. This information includes facial expressions, voice tone, and keyboard touch speed.

[0377] Step 5:

[0378] The server processes emotional data sent from the terminal to identify the user's emotional state. It uses emotion recognition algorithms to measure stress levels and psychological barriers.

[0379] Step 6:

[0380] The server automatically generates an asset management plan using an AI algorithm based on the user's financial information and emotional state. The generated plan takes the user's emotional state into consideration and appropriately adjusts the risk level.

[0381] Step 7:

[0382] The server notifies the terminal of the generated asset management plan and allows the user to review its contents. The user can then approve or request modifications to the plan.

[0383] Step 8:

[0384] The user reviews the plan and approves or modifies it as needed. The server waits for the response and applies the plan.

[0385] Step 9:

[0386] The server monitors user spending in real time and immediately sends an alert to the terminal if there is a possibility of budget overrun. This monitoring is also adjusted based on stress levels read from emotional data.

[0387] Step 10:

[0388] The server periodically evaluates the user's insurance information and suggests the most suitable insurance product. This process also takes emotional data into account, reflecting the user's anxieties about insurance.

[0389] Step 11:

[0390] The device delivers personalized finance education content based on emotional data and learning trends. This allows users to effectively acquire knowledge and gain confidence in financial management.

[0391] (Example 2)

[0392] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0393] Providing appropriate asset management plans that take into account the emotional state of users is a challenging task in financial management. Furthermore, it is necessary to reduce the psychological barriers users feel when making financial decisions and provide support that allows them to confidently follow the plan. In addition, monitoring users' spending in real time to prevent budget overruns, as well as providing educational content that meets users' learning needs, are also crucial challenges.

[0394] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0395] In this invention, the server includes a storage means for receiving and storing the user's financial information, a calculation means for automatically generating an asset management plan based on the financial information, and an analysis means for analyzing emotional data and reflecting it in the generated plan. This enables the generation of flexible asset management plans tailored to the user's emotional state and provides support for financial decisions.

[0396] A "storage device" is a device or function for storing financial information received from a user, and it is capable of storing and retrieving data.

[0397] A "calculation means" refers to a process or device for automatically creating an asset management plan based on received financial information.

[0398] "Communication means" refers to a device or function for notifying the user of the generated asset management plan.

[0399] "Monitoring measures" refer to devices or functions that monitor user spending in real time and issue warnings if there is a possibility of exceeding the budget.

[0400] "Analysis means" refers to a function or device that collects and analyzes user emotional data and reflects the results in an asset management plan.

[0401] "Support measures" refer to devices or functions that, based on emotional data, support users' financial decisions and reduce psychological barriers.

[0402] A "feedback mechanism" is a device or function that feeds back emotional trends, analyzed over a long period, into the revision of investment plans and risk assessments.

[0403] "Educational tools" refer to devices or functions that deliver learning content to users and track their progress.

[0404] This invention is a system that supports financial management while taking into account the emotional state of the user, and is configured as follows.

[0405] First, users enter financial information such as income, expenses, assets, and liabilities into their device via a dedicated application or web portal. This information is securely encrypted by the device and transmitted to the server using the SSL / TLS protocol.

[0406] The server stores the received information in a database and uses it as a storage device. During this process, data sanitization is performed to check for abnormal values ​​and errors. Next, the server uses a generative AI model, which is its computational tool, to automatically generate an asset management plan based on the user's financial data and market trend data. An example of a prompt message to the generative AI model would be, "Please create an optimal asset management plan based on current market trends."

[0407] The device collects user emotional data in real time through facial expressions, voice, and text data. This emotional data is then sent back to the server, where analysis tools are used to evaluate the user's stress level and psychological state, and this is reflected in the automatically generated operational plan. As a result, if a user is experiencing high stress, a lower-risk operational plan is adjusted and provided.

[0408] Furthermore, the server analyzes long-term sentiment trends as a feedback mechanism, and uses this information when reviewing operational plans and conducting risk assessments. In particular, if users regularly experience anxiety, the proposed plans will be adjusted to be more conservative.

[0409] Real-time spending monitoring is performed by server-based monitoring systems, and alerts are immediately sent to users when budget overruns are predicted. This helps prevent unnecessary spending and reduces mental stress.

[0410] Furthermore, the server acts as an educational tool, providing learning content based on the user's interests and needs. This content is adjusted as the system tracks how effectively the user is learning. This allows users to acquire deeper financial knowledge and gain a better understanding of their own financial situation.

[0411] In this way, a system is realized that supports safe and effective financial management while taking into account the user's emotional state.

[0412] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0413] Step 1:

[0414] Users input financial information such as income, expenses, assets, and liabilities into a terminal using a dedicated application or web portal. This input data is fundamental information for gaining a detailed understanding of the user's financial situation.

[0415] Step 2:

[0416] The terminal receives the entered financial information, encrypts the data using the SSL / TLS protocol, and sends it to the server. This process ensures the safety and security of the data. The output is encrypted financial data.

[0417] Step 3:

[0418] The server stores the received encrypted data in a database. Here, data sanitization is performed, and data processing is carried out to check for outliers and errors, resulting in clean financial data being output.

[0419] Step 4:

[0420] The server uses a generation AI model to automatically generate asset management plans based on clean financial and market trend data. This calculation process outputs an optimal plan tailored to the user's goals. The prompt message used is in the format of "Please create an optimal asset management plan based on current market trends."

[0421] Step 5:

[0422] The device collects the user's facial expressions, voice, and text data in real time and sends it to the server as user emotion data. Here, data collection and basic processing of the emotion data take place.

[0423] Step 6:

[0424] The server uses analytical tools to evaluate stress levels and psychological states based on the received emotional data. A report of the evaluated emotional state is then generated through data calculations.

[0425] Step 7:

[0426] The server adjusts the generated asset management plan based on emotional data. It flexibly adjusts the plan, for example, suggesting a low-risk plan in cases of high stress, and outputs a final plan tailored to the user.

[0427] Step 8:

[0428] The server sends notifications regarding the operational plan to the terminal, and information is presented to the user based on these notifications. The user can then make financial decisions based on this information.

[0429] Step 9:

[0430] The server monitors user spending in real time and sends an alert to the terminal if the budget is exceeded. This monitoring system issues warnings prompting immediate action.

[0431] Step 10:

[0432] The server delivers educational content to the user's device based on their interests and needs. This process tracks learning progress and adjusts content as required.

[0433] Step 11:

[0434] The server analyzes long-term sentiment trends and feeds this back into risk assessment. This analysis yields trend analysis results that contribute to further adjustments to the operational plan.

[0435] (Application Example 2)

[0436] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0437] Traditional financial management systems managed assets and expenses without considering the emotional state of users, making it difficult to adequately address situations where users were prone to psychological stress. Furthermore, the lack of real-time feedback based on user emotion analysis made it difficult to propose flexible asset management plans that were sensitive to these emotions. This resulted in a problem where users' financial plans were often inappropriate, especially during economically unstable periods.

[0438] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0439] In this invention, the server includes emotion analysis means for analyzing the user's emotional state and providing real-time advice on spending based on that emotion; information management means for receiving and storing the user's financial information; and plan generation means for automatically generating an asset management plan based on the financial information. This enables personalized asset management plan suggestions tailored to the user's psychological state and real-time spending management.

[0440] "Information management means" refers to a device or software that has the function of storing and managing financial information received from users and securely storing it in a database.

[0441] A "plan generation means" is a device or software that has the function of automatically generating an asset management plan based on received financial information and designing a strategy that is suitable for the user's financial goals.

[0442] "Information notification means" refers to a device or software equipped with the function of notifying users of generated asset management plans and other important information.

[0443] A "monitoring device" is a device or software that has the function of monitoring a user's spending in real time and immediately issuing a warning if the set budget is likely to be exceeded.

[0444] A "selection suggestion means" is a device or software that has the function of evaluating the user's insurance information and suggesting the most suitable insurance product based on that information.

[0445] "Content distribution means" refers to a device or software that has the function of distributing educational content to users and supporting financial education.

[0446] "Emotional analysis means" refers to a device or software that analyzes a user's emotional state and provides real-time advice on spending based on that data.

[0447] The system for implementing this invention consists of three main elements: a user, a server, and a terminal.

[0448] Users input their financial information (income, expenses, assets, liabilities, etc.) via a device such as a smartphone. This information is encrypted on the device and securely transmitted to the server. The server receives and stores this data using an information management device and stores it in a database.

[0449] The server further analyzes the received financial information using a plan generation device and automatically generates an asset management plan tailored to the user's financial goals. This plan is immediately notified to the user through an information notification device.

[0450] The role of the sentiment analysis device is to analyze the user's voice and text data to evaluate their emotional state in real time. The information obtained from sentiment analysis is linked to the user's spending patterns, and the monitoring device displays a warning when spending approaches the budget limit. It also provides personalized spending advice to the user based on the sentiment data.

[0451] For example, if a user is feeling stressed while shopping, a notification might appear on their smartphone screen saying, "Why not hold off on making a big purchase for now and reconsider?" This allows for flexible asset management based on the user's emotions.

[0452] Furthermore, the selection and suggestion device evaluates insurance information and proposes the most suitable insurance product to the user. In addition, the content distribution device provides users with financial education content to support their knowledge improvement.

[0453] An example of input to the prompt generation AI model might be, "Generate an appropriate warning message to display when the user's emotional state is assessed as high stress."

[0454] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0455] Step 1:

[0456] The user inputs and transmits financial information via a terminal. This input includes income, expenses, assets, and liabilities. The terminal encrypts this information and securely transmits it to the server. The input here is the user's financial information, and the output is encrypted data.

[0457] Step 2:

[0458] The server receives encrypted data transmitted from the terminal, decrypts the financial information using an information management device, and stores it. The input is encrypted data, and the output is decoded financial information. This process allows the server to store each user's financial information in a database.

[0459] Step 3:

[0460] The server uses a plan generation device to analyze stored financial information and automatically generate an asset management plan based on the user's financial goals. The input is decoded financial information, and the output is the generated asset management plan. The resulting plan is structured as an asset strategy suitable for the user.

[0461] Step 4:

[0462] The generated asset management plan is communicated to the user via an information notification device. The input here is the generated asset management plan, and the output is a notification message to the user. This notification allows the user to gain information about their own financial policy.

[0463] Step 5:

[0464] The server analyzes the user's voice and text data through an emotion analysis device and evaluates their emotional state in real time. The input is the user's voice and text data, and the output is the analyzed emotion data. This allows for an accurate evaluation of the user's emotional state.

[0465] Step 6:

[0466] Based on the sentiment analysis results, the monitoring device evaluates the user's spending in real time and issues warnings as needed. The input here is the analyzed sentiment data and spending information, and the output is a warning notification to the user. Specifically, a notification such as "Is this purchase important? Perhaps you should think about it again?" might be sent.

[0467] Step 7:

[0468] The selection suggestion device evaluates stored insurance information and proposes the most suitable insurance product to the user. The input is the user's insurance information, and the output is information on the proposed insurance product. This process provides the user with the insurance selection that is expected to be most beneficial.

[0469] Step 8:

[0470] The content delivery device delivers educational content to help users improve their financial knowledge. The input is the user's learning needs, and the output is personalized educational content. Through this approach, users can effectively strengthen their financial knowledge.

[0471] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0472] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0473] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0474] [Third Embodiment]

[0475] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0476] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0477] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0478] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0479] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0480] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0481] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0482] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0483] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0484] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0485] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0486] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0487] This invention is a system for supporting the financial management of individuals and corporations, providing a comprehensive platform that combines convenience and security. Specific embodiments are described below.

[0488] First, users can input their daily income, expenses, assets, and liabilities using a dedicated application or web portal. The entered data is encrypted by the device and securely transmitted to the server. The server stores this information in a database, ensuring it is readily accessible when needed.

[0489] Next, the server uses a generation algorithm to automatically generate an asset management plan tailored to the user's goals and lifestyle, based on the collected financial information. This plan is optimized by analyzing historical data and simulating multiple market trends. For example, if the user wants to buy a house in the future, the server will suggest monthly savings amounts and investment strategies.

[0490] The generated operational plan is provided to the user through a notification system. The user can then approve or request modifications to the presented plan. While the plan is in operation, the server monitors spending in real time and sends an alert to the terminal if spending is likely to exceed the set budget.

[0491] Furthermore, the server periodically evaluates the user's insurance policies and suggests the most suitable insurance products based on the latest information. For example, it can suggest a review of life insurance to a user who has recently had a child. In this way, the system manages risks according to the user's life events.

[0492] Furthermore, the device delivers educational content designed to improve users' financial skills. This content is customized and broadly covers topics ranging from basic investment knowledge to advanced strategies, tailored to user needs. This allows users to deepen their understanding of finance and build confidence through self-study.

[0493] Overall, this system helps simplify and effectively manage complex financial operations while ensuring the security of user data through regular audits and protective measures.

[0494] The following describes the processing flow.

[0495] Step 1:

[0496] Users enter their income, expenses, assets, and liabilities through a dedicated application or web portal.

[0497] Step 2:

[0498] The terminal receives the financial information entered by the user and securely transmits the data to the server using the latest encryption protocols.

[0499] Step 3:

[0500] The server stores the received financial information in a database and uses this information to perform a detailed analysis of the user's financial situation.

[0501] Step 4:

[0502] The server uses the analyzed data to generate an asset management plan using an AI algorithm. The plan is optimized considering the user's goals and market trends.

[0503] Step 5:

[0504] The server presents the generated asset management plan to the user via a notification system and awaits their approval or request for modification.

[0505] Step 6:

[0506] The user reviews the presented plan and makes modifications or approvals as needed.

[0507] Step 7:

[0508] The server monitors the user's spending in real time and sends an alert to the terminal if it is about to exceed the set budget.

[0509] Step 8:

[0510] The server periodically evaluates the user's insurance policy and, as appropriate, suggests the most suitable insurance product.

[0511] Step 9:

[0512] The device supports learning by delivering appropriate finance education materials based on the educational content selected by the user.

[0513] Step 10:

[0514] The server audits each process to protect user data and maintain overall system security.

[0515] (Example 1)

[0516] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0517] In today's world, personal and corporate financial management is becoming increasingly complex, making it difficult for many users to manage their assets and risks effectively. Furthermore, with the increasing emphasis on information security and privacy protection, there is a need to securely manage users' financial information while efficiently proposing optimal asset management plans. Providing learning opportunities to improve financial literacy is also a challenge.

[0518] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0519] In this invention, the server includes information management means for receiving and storing the user's financial information, protection means for encrypting and securely transmitting the financial information, and generation means for automatically generating an asset management plan based on the financial information. This allows the user to receive an appropriate and optimized asset management plan while securely managing their information. In addition, it can provide effective utilization of financial information and learning support.

[0520] "Information management means" refers to technical means for receiving and securely storing financial data provided by users.

[0521] "Protection measures" refer to technical means that encrypt users' financial information and ensure security during data transmission and reception.

[0522] "Generation means" refers to a technical function that analyzes collected financial data and automatically generates an optimal asset management plan for the user.

[0523] "Communication means" refers to information transmission functions used to notify users of the generated asset management plan.

[0524] "Monitoring measures" refer to technical means for tracking user spending in real time and detecting potential budget overruns.

[0525] A "proposal method" is a technical means that evaluates a user's insurance-related information and, based on that evaluation, presents the most suitable financial product.

[0526] "Learning support methods" refer to methods of providing users with educational materials to improve their financial knowledge.

[0527] "Evaluation means" refers to a technical function that simulates the generated asset management plan using multiple factors such as market trends and evaluates its validity.

[0528] "Analysis means" refers to technical means that analyze market trends and process the information necessary for optimizing asset management plans using AI models.

[0529] This invention is a complex system that supports the smooth financial management of individuals and corporations. This system allows users to input financial information using a dedicated application or web portal, and generates an optimal asset management plan based on that information. Detailed embodiments are described below.

[0530] First, users input information about their income, expenses, assets, and liabilities using a personal computing device or mobile terminal. This information is encrypted by the terminal and transmitted to the server via a security protocol. Data security is ensured by employing AES-256 encryption technology.

[0531] The server stores the received financial information in a relational database system. This step utilizes a MySQL database to achieve high-speed data access and efficient management. The stored data is analyzed using Python and various data processing libraries (e.g., Pandas). A generative AI model is used to generate an asset management plan from the collected financial information. To consider market conditions, TensorFlow is used to simulate market trends and perform diverse scenario analyses. In this process, an optimized plan is generated based on evaluation methods.

[0532] The generated investment plan is provided to the user via push notification or email. Through this, the user can review the proposed investment plan and request revisions as needed. Meanwhile, the server monitors income and expenses in real time and sends a special alert to the device if the budget is exceeded.

[0533] In addition, it includes a function to evaluate insurance information and suggest the most suitable products. This enables enhanced risk management tailored to the user's lifestyle. Furthermore, the device provides users with a wide range of educational content, from basic knowledge about asset management to specific strategies. This learning content is individually customized, allowing users to acquire knowledge that suits their individual needs.

[0534] For example, if a user has a goal such as "I want to save 300,000 yen to buy a car in three years," the server will use this to suggest the best savings plan and investment method. This suggestion is generated based on prompt statements like the following:

[0535] "A user wants to save 300,000 yen over the next three years. Considering their current income, expenses, and asset information, what savings plan and investment strategy would you propose?"

[0536] This allows the system to support users' daily financial activities and assist in promoting optimal asset building.

[0537] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0538] Step 1:

[0539] Users enter financial information using a dedicated application or web portal. Input fields include income, expenses, assets, and liabilities. Users specifically enter data such as, "This month's income is 500,000 yen, and expenses are 300,000 yen." This information is temporarily stored on the device.

[0540] Step 2:

[0541] The terminal encrypts the user's financial information entered. Encryption technologies such as AES-256 are used to ensure data security. The encrypted data is sent to the server using the HTTPS protocol. Input is unencrypted user data, and output is encrypted user data. Specifically, the terminal automatically performs the encryption process in the background.

[0542] Step 3:

[0543] The server decrypts the received encrypted data and stores it in a relational database system. The database system used is MySQL, which efficiently manages each user's information. The input is encrypted data, and the output is the decoded data stored in the database. After decryption, the information is written to the database very quickly.

[0544] Step 4:

[0545] The server uses a generative AI model to analyze the user's financial information and automatically generate an optimal asset management plan. It uses Python and the Pandas library to create a dataframe and simulate various market trends, including historical data. The input is stored user data, and the output is the optimal investment plan. Specifically, the server uses TensorFlow to rapidly execute hundreds of thousands of simulations and selects the plan best suited to each user.

[0546] Step 5:

[0547] The server sends the generated operational plan to the user via a notification system. The user can review the plan via smartphone or PC and request revisions if necessary. The input is the generated operational plan, and the output is the plan notification and user feedback. The server sends push notifications quickly to ensure the user can review the plan immediately.

[0548] Step 6:

[0549] The server monitors user spending in real time and sends a warning to the terminal if the budget is about to be exceeded. Real-time functionality is ensured by using WebSockets. The input is the user's current spending status, and the output is a warning notification. The server immediately monitors real-time data and issues alerts as needed.

[0550] Step 7:

[0551] The server evaluates the user's insurance information and suggests the latest financial products. It uses machine learning to perform analysis based on customer profiles. K-Means clustering is used to group user attributes and select appropriate insurance products. The input is the user's profile information, and the output is the suggested financial products. The server provides the user with the presented options via email or app notification as needed.

[0552] Step 8:

[0553] The device delivers educational content to improve users' financial skills. This content includes videos, quizzes, and articles. Input is the user's learning needs, and output is customized learning content. The device has the capability to deliver optimal content tailored to the user's level and goals.

[0554] (Application Example 1)

[0555] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0556] In modern times, managing finances efficiently and securely for individuals and corporations has become increasingly complex. While real-time tracking of expenses and planned asset management are crucial amidst diverse spending patterns, doing so manually is difficult. Furthermore, the widespread use of electronic transactions demands rapid expense management, yet there is a lack of systems that can automatically provide users with suitable asset management and savings suggestions. The objective of this invention is to solve these problems.

[0557] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0558] In this invention, the server includes an information management means for receiving and storing financial information, a transaction recording means for acquiring electronic transaction information in real time and automatically recording expenditures, and a monitoring means for monitoring the user's expenditures and issuing alerts when the budget is exceeded. This enables the user to manage their finances in real time, preventing budget overruns and automatically supporting planned asset management.

[0559] "Information management means" refers to a device or program that has the function of receiving a user's financial information and securely storing and managing it.

[0560] A "plan generation means" is a device or program that has the function of automatically generating an asset management plan suitable for the user based on the financial information received.

[0561] "Information provision means" refers to a device or program that has the function of notifying users of generated asset management plans and other related information and prompting them to take necessary actions.

[0562] A "monitoring device" is a device or program that has the function of monitoring a user's spending in real time and detecting the possibility of budget overruns.

[0563] A "transaction recording device" is a device or program that has the function of acquiring electronic transaction information in real time and automatically recording expenditures.

[0564] A "behavioral suggestion device" is a device or program that has the function of generating specific action suggestions to support users in achieving their savings goals.

[0565] A "proposal means" is a device or program that has the function of evaluating the user's insurance information and proposing the most suitable insurance product.

[0566] An "educational tool" is a device or program that has the function of delivering educational content to improve users' financial literacy.

[0567] The system for realizing this invention primarily functions through data communication between a server and a user's terminal. The server is programmed to implement information management means, plan generation means, information provision means, monitoring means, transaction recording means, action suggestion means, suggestion means, and education means. This set of programs provides a smooth and comprehensive financial management experience.

[0568] Specifically, the server manages the financial information received from users and securely stores the information using encryption technologies such as AES. The plan generation means utilizes machine learning algorithms to formulate an asset management plan based on the user's past transactions and goal setting. Next, the information provision means quickly notifies the user's terminal of the generated information. The monitoring means uses real-time data stream processing technology to continuously monitor whether the user's spending is within budget.

[0569] On the terminal, users actually use this system in their daily activities. For example, a smartphone app transmits electronic payment information to the server in real time via a transaction recording device, and expenditures are recorded and updated. The action suggestion device provides users with specific asset management advice to help them achieve their savings goals. In this way, the terminal and server work together to enhance the user's financial management.

[0570] As a concrete example, when a user makes a purchase using their mobile device, that information is immediately sent to the server. The user's asset management plan is then automatically updated, and comprehensive financial information becomes available on the user's device.

[0571] An example of a prompt message when using a generative AI model would be: "Design a user budget management and spending analysis algorithm based on electronic payment history. Include features for optimizing asset management plans based on user goals and providing real-time alerts."

[0572] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0573] Step 1:

[0574] The user makes an electronic payment using a terminal. The terminal retrieves this transaction information and transmits it to the server using a secure communication protocol. The input is electronic payment information, and the output is encrypted transaction data. The data is retrieved instantly, and security is ensured during communication.

[0575] Step 2:

[0576] The server decrypts the received transaction information and stores it in a database through an information management system. The input is encrypted transaction data, and the output is the decrypted transaction information stored in the database. The server uses encryption technology to decrypt the data and stores it in a data store for information management.

[0577] Step 3:

[0578] The server operates a plan generation system that updates the asset management plan based on the user's latest transaction information. Inputs are the latest transaction information and pre-stored financial data, and output is the updated asset management plan. The server uses machine learning algorithms to recalculate the asset management plan.

[0579] Step 4:

[0580] The monitoring system operates to check in real time whether the user's spending is within the set budget. The input is real-time spending data, and the output is a warning for exceeding the budget or a notification that there is no problem. The server sets spending thresholds and generates an alert if these are exceeded.

[0581] Step 5:

[0582] Through the action suggestion mechanism, the server generates optimal action suggestions for the user and notifies the terminal. The input is the updated asset management plan and budget status, and the output is a suggestion of specific savings actions. The server determines the need for plan changes and shows the user improvement measures.

[0583] Step 6:

[0584] Through educational methods, the server regularly delivers content designed to improve users' financial skills. The input is the user's learning history and interests, and the output is individually customized educational content. The server utilizes a generative AI model to provide a personalized educational program.

[0585] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0586] This invention combines an emotion engine with a system that supports personal financial management to provide optimal financial advice tailored to the user's emotional state. The operation of this system involves the combination of several key components and their respective functions.

[0587] First, users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal. The terminal receives this information, encrypts it, and securely transmits it to the server. The server stores the received data in a database and analyzes the user's financial situation.

[0588] Next, the server uses a generation algorithm to automatically generate an asset management plan that takes into account the user's goals and market trends. The emotion engine plays a crucial role here. It collects emotional data from the user's facial expressions, voice, and text feedback, and analyzes their stress level and psychological state. This information is reflected in the generated plan, providing a flexible plan tailored to the user's situation.

[0589] For example, if a user is experiencing high stress levels, the system will suggest a low-risk investment plan. The emotion engine also provides advice and educational content to help users overcome psychological barriers when making financial decisions. In this way, the emotion engine offers insights beyond mere financial data.

[0590] The server collects sentiment data and analyzes long-term trends based on it. This data is then fed back into operational planning and risk assessment. For example, if a user regularly expresses anxiety, the proposed plan will incorporate a more conservative operational approach than usual.

[0591] Furthermore, the real-time monitoring feature immediately sends an alert if a user's spending is likely to exceed their budget. This helps users prevent unnecessary spending and reduces their mental burden.

[0592] Finally, to advance the user's financial education, the system delivers educational content tailored to the user's interests and needs to their device. The emotion engine understands how effectively the user is learning the content and adjusts it as needed. In this way, a system is realized that provides comprehensive support while taking into account the user's emotional state.

[0593] The following describes the processing flow.

[0594] Step 1:

[0595] Users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal.

[0596] Step 2:

[0597] The terminal receives the financial information entered by the user and securely transmits the data to the server using an encryption protocol.

[0598] Step 3:

[0599] The server stores the received financial information in a database and uses an analysis algorithm to analyze the user's financial situation.

[0600] Step 4:

[0601] While the user is using the application, the device acquires emotional data through the camera, microphone, text input, etc. This information includes facial expressions, voice tone, and keyboard touch speed.

[0602] Step 5:

[0603] The server processes emotional data sent from the terminal to identify the user's emotional state. It uses emotion recognition algorithms to measure stress levels and psychological barriers.

[0604] Step 6:

[0605] The server automatically generates an asset management plan using an AI algorithm based on the user's financial information and emotional state. The generated plan takes the user's emotional state into consideration and appropriately adjusts the risk level.

[0606] Step 7:

[0607] The server notifies the terminal of the generated asset management plan and allows the user to review its contents. The user can then approve or request modifications to the plan.

[0608] Step 8:

[0609] The user reviews the plan and approves or modifies it as needed. The server waits for the response and applies the plan.

[0610] Step 9:

[0611] The server monitors user spending in real time and immediately sends an alert to the terminal if there is a possibility of budget overrun. This monitoring is also adjusted based on stress levels read from emotional data.

[0612] Step 10:

[0613] The server periodically evaluates the user's insurance information and suggests the most suitable insurance product. This process also takes emotional data into account, reflecting the user's anxieties about insurance.

[0614] Step 11:

[0615] The device delivers personalized finance education content based on emotional data and learning trends. This allows users to effectively acquire knowledge and gain confidence in financial management.

[0616] (Example 2)

[0617] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0618] Providing appropriate asset management plans that take into account the emotional state of users is a challenging task in financial management. Furthermore, it is necessary to reduce the psychological barriers users feel when making financial decisions and provide support that allows them to confidently follow the plan. In addition, monitoring users' spending in real time to prevent budget overruns, as well as providing educational content that meets users' learning needs, are also crucial challenges.

[0619] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0620] In this invention, the server includes a storage means for receiving and storing the user's financial information, a calculation means for automatically generating an asset management plan based on the financial information, and an analysis means for analyzing emotional data and reflecting it in the generated plan. This enables the generation of flexible asset management plans tailored to the user's emotional state and provides support for financial decisions.

[0621] A "storage device" is a device or function for storing financial information received from a user, and it is capable of storing and retrieving data.

[0622] A "calculation means" refers to a process or device for automatically creating an asset management plan based on received financial information.

[0623] "Communication means" refers to a device or function for notifying the user of the generated asset management plan.

[0624] "Monitoring measures" refer to devices or functions that monitor user spending in real time and issue warnings if there is a possibility of exceeding the budget.

[0625] "Analysis means" refers to a function or device that collects and analyzes user emotional data and reflects the results in an asset management plan.

[0626] "Support measures" refer to devices or functions that, based on emotional data, support users' financial decisions and reduce psychological barriers.

[0627] A "feedback mechanism" is a device or function that feeds back emotional trends, analyzed over a long period, into the revision of investment plans and risk assessments.

[0628] "Educational tools" refer to devices or functions that deliver learning content to users and track their progress.

[0629] This invention is a system that supports financial management while taking into account the emotional state of the user, and is configured as follows.

[0630] First, users enter financial information such as income, expenses, assets, and liabilities into their device via a dedicated application or web portal. This information is securely encrypted by the device and transmitted to the server using the SSL / TLS protocol.

[0631] The server stores the received information in a database and uses it as a storage device. During this process, data sanitization is performed to check for abnormal values ​​and errors. Next, the server uses a generative AI model, which is its computational tool, to automatically generate an asset management plan based on the user's financial data and market trend data. An example of a prompt message to the generative AI model would be, "Please create an optimal asset management plan based on current market trends."

[0632] The device collects user emotional data in real time through facial expressions, voice, and text data. This emotional data is then sent back to the server, where analysis tools are used to evaluate the user's stress level and psychological state, and this is reflected in the automatically generated operational plan. As a result, if a user is experiencing high stress, a lower-risk operational plan is adjusted and provided.

[0633] Furthermore, the server analyzes long-term sentiment trends as a feedback mechanism, and uses this information when reviewing operational plans and conducting risk assessments. In particular, if users regularly experience anxiety, the proposed plans will be adjusted to be more conservative.

[0634] Real-time spending monitoring is performed by server-based monitoring systems, and alerts are immediately sent to users when budget overruns are predicted. This helps prevent unnecessary spending and reduces mental stress.

[0635] Furthermore, the server acts as an educational tool, providing learning content based on the user's interests and needs. This content is adjusted as the system tracks how effectively the user is learning. This allows users to acquire deeper financial knowledge and gain a better understanding of their own financial situation.

[0636] In this way, a system is realized that supports safe and effective financial management while taking into account the user's emotional state.

[0637] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0638] Step 1:

[0639] Users input financial information such as income, expenses, assets, and liabilities into a terminal using a dedicated application or web portal. This input data is fundamental information for gaining a detailed understanding of the user's financial situation.

[0640] Step 2:

[0641] The terminal receives the entered financial information, encrypts the data using the SSL / TLS protocol, and sends it to the server. This process ensures the safety and security of the data. The output is encrypted financial data.

[0642] Step 3:

[0643] The server stores the received encrypted data in a database. Here, data sanitization is performed, and data processing is carried out to check for outliers and errors, resulting in clean financial data being output.

[0644] Step 4:

[0645] The server uses a generation AI model to automatically generate asset management plans based on clean financial and market trend data. This calculation process outputs an optimal plan tailored to the user's goals. The prompt message used is in the format of "Please create an optimal asset management plan based on current market trends."

[0646] Step 5:

[0647] The device collects the user's facial expressions, voice, and text data in real time and sends it to the server as user emotion data. Here, data collection and basic processing of the emotion data take place.

[0648] Step 6:

[0649] The server uses analytical tools to evaluate stress levels and psychological states based on the received emotional data. A report of the evaluated emotional state is then generated through data calculations.

[0650] Step 7:

[0651] The server adjusts the generated asset management plan based on emotional data. It flexibly adjusts the plan, for example, suggesting a low-risk plan in cases of high stress, and outputs a final plan tailored to the user.

[0652] Step 8:

[0653] The server sends notifications regarding the operational plan to the terminal, and information is presented to the user based on these notifications. The user can then make financial decisions based on this information.

[0654] Step 9:

[0655] The server monitors user spending in real time and sends an alert to the terminal if the budget is exceeded. This monitoring system issues warnings prompting immediate action.

[0656] Step 10:

[0657] The server delivers educational content to the user's device based on their interests and needs. This process tracks learning progress and adjusts content as required.

[0658] Step 11:

[0659] The server analyzes long-term sentiment trends and feeds this back into risk assessment. This analysis yields trend analysis results that contribute to further adjustments to the operational plan.

[0660] (Application Example 2)

[0661] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0662] Traditional financial management systems managed assets and expenses without considering the emotional state of users, making it difficult to adequately address situations where users were prone to psychological stress. Furthermore, the lack of real-time feedback based on user emotion analysis made it difficult to propose flexible asset management plans that were sensitive to these emotions. This resulted in a problem where users' financial plans were often inappropriate, especially during economically unstable periods.

[0663] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0664] In this invention, the server includes emotion analysis means for analyzing the user's emotional state and providing real-time advice on spending based on that emotion; information management means for receiving and storing the user's financial information; and plan generation means for automatically generating an asset management plan based on the financial information. This enables personalized asset management plan suggestions tailored to the user's psychological state and real-time spending management.

[0665] "Information management means" refers to a device or software that has the function of storing and managing financial information received from users and securely storing it in a database.

[0666] A "plan generation means" is a device or software that has the function of automatically generating an asset management plan based on received financial information and designing a strategy that is suitable for the user's financial goals.

[0667] "Information notification means" refers to a device or software equipped with the function of notifying users of generated asset management plans and other important information.

[0668] A "monitoring device" is a device or software that has the function of monitoring a user's spending in real time and immediately issuing a warning if the set budget is likely to be exceeded.

[0669] A "selection suggestion means" is a device or software that has the function of evaluating the user's insurance information and suggesting the most suitable insurance product based on that information.

[0670] "Content distribution means" refers to a device or software that has the function of distributing educational content to users and supporting financial education.

[0671] "Emotional analysis means" refers to a device or software that analyzes a user's emotional state and provides real-time advice on spending based on that data.

[0672] The system for implementing this invention consists of three main elements: a user, a server, and a terminal.

[0673] Users input their financial information (income, expenses, assets, liabilities, etc.) via a device such as a smartphone. This information is encrypted on the device and securely transmitted to the server. The server receives and stores this data using an information management device and stores it in a database.

[0674] The server further analyzes the received financial information using a plan generation device and automatically generates an asset management plan tailored to the user's financial goals. This plan is immediately notified to the user through an information notification device.

[0675] The role of the sentiment analysis device is to analyze the user's voice and text data to evaluate their emotional state in real time. The information obtained from sentiment analysis is linked to the user's spending patterns, and the monitoring device displays a warning when spending approaches the budget limit. It also provides personalized spending advice to the user based on the sentiment data.

[0676] For example, if a user is feeling stressed while shopping, a notification might appear on their smartphone screen saying, "Why not hold off on making a big purchase for now and reconsider?" This allows for flexible asset management based on the user's emotions.

[0677] Furthermore, the selection and suggestion device evaluates insurance information and proposes the most suitable insurance product to the user. In addition, the content distribution device provides users with financial education content to support their knowledge improvement.

[0678] An example of input to the prompt generation AI model might be, "Generate an appropriate warning message to display when the user's emotional state is assessed as high stress."

[0679] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0680] Step 1:

[0681] The user inputs and transmits financial information via a terminal. This input includes income, expenses, assets, and liabilities. The terminal encrypts this information and securely transmits it to the server. The input here is the user's financial information, and the output is encrypted data.

[0682] Step 2:

[0683] The server receives encrypted data transmitted from the terminal, decrypts the financial information using an information management device, and stores it. The input is encrypted data, and the output is decoded financial information. This process allows the server to store each user's financial information in a database.

[0684] Step 3:

[0685] The server uses a plan generation device to analyze stored financial information and automatically generate an asset management plan based on the user's financial goals. The input is decoded financial information, and the output is the generated asset management plan. The resulting plan is structured as an asset strategy suitable for the user.

[0686] Step 4:

[0687] The generated asset management plan is communicated to the user via an information notification device. The input here is the generated asset management plan, and the output is a notification message to the user. This notification allows the user to gain information about their own financial policy.

[0688] Step 5:

[0689] The server analyzes the user's voice and text data through an emotion analysis device and evaluates their emotional state in real time. The input is the user's voice and text data, and the output is the analyzed emotion data. This allows for an accurate evaluation of the user's emotional state.

[0690] Step 6:

[0691] Based on the sentiment analysis results, the monitoring device evaluates the user's spending in real time and issues warnings as needed. The input here is the analyzed sentiment data and spending information, and the output is a warning notification to the user. Specifically, a notification such as "Is this purchase important? Perhaps you should think about it again?" might be sent.

[0692] Step 7:

[0693] The selection suggestion device evaluates stored insurance information and proposes the most suitable insurance product to the user. The input is the user's insurance information, and the output is information on the proposed insurance product. This process provides the user with the insurance selection that is expected to be most beneficial.

[0694] Step 8:

[0695] The content delivery device delivers educational content to help users improve their financial knowledge. The input is the user's learning needs, and the output is personalized educational content. Through this approach, users can effectively strengthen their financial knowledge.

[0696] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0697] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0698] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0699] [Fourth Embodiment]

[0700] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0701] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0702] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0703] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0704] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0705] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0706] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0707] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0708] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0709] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0710] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0711] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0712] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0713] This invention is a system for supporting the financial management of individuals and corporations, providing a comprehensive platform that combines convenience and security. Specific embodiments are described below.

[0714] First, users can input their daily income, expenses, assets, and liabilities using a dedicated application or web portal. The entered data is encrypted by the device and securely transmitted to the server. The server stores this information in a database, ensuring it is readily accessible when needed.

[0715] Next, the server uses a generation algorithm to automatically generate an asset management plan tailored to the user's goals and lifestyle, based on the collected financial information. This plan is optimized by analyzing historical data and simulating multiple market trends. For example, if the user wants to buy a house in the future, the server will suggest monthly savings amounts and investment strategies.

[0716] The generated operational plan is provided to the user through a notification system. The user can then approve or request modifications to the presented plan. While the plan is in operation, the server monitors spending in real time and sends an alert to the terminal if spending is likely to exceed the set budget.

[0717] Furthermore, the server periodically evaluates the user's insurance policies and suggests the most suitable insurance products based on the latest information. For example, it can suggest a review of life insurance to a user who has recently had a child. In this way, the system manages risks according to the user's life events.

[0718] Furthermore, the device delivers educational content designed to improve users' financial skills. This content is customized and broadly covers topics ranging from basic investment knowledge to advanced strategies, tailored to user needs. This allows users to deepen their understanding of finance and build confidence through self-study.

[0719] Overall, this system helps simplify and effectively manage complex financial operations while ensuring the security of user data through regular audits and protective measures.

[0720] The following describes the processing flow.

[0721] Step 1:

[0722] Users enter their income, expenses, assets, and liabilities through a dedicated application or web portal.

[0723] Step 2:

[0724] The terminal receives the financial information entered by the user and securely transmits the data to the server using the latest encryption protocols.

[0725] Step 3:

[0726] The server stores the received financial information in a database and uses this information to perform a detailed analysis of the user's financial situation.

[0727] Step 4:

[0728] The server uses the analyzed data to generate an asset management plan using an AI algorithm. The plan is optimized considering the user's goals and market trends.

[0729] Step 5:

[0730] The server presents the generated asset management plan to the user via a notification system and awaits their approval or request for modification.

[0731] Step 6:

[0732] The user reviews the presented plan and makes modifications or approvals as needed.

[0733] Step 7:

[0734] The server monitors the user's spending in real time and sends an alert to the terminal if it is about to exceed the set budget.

[0735] Step 8:

[0736] The server periodically evaluates the user's insurance policy and, as appropriate, suggests the most suitable insurance product.

[0737] Step 9:

[0738] The device supports learning by delivering appropriate finance education materials based on the educational content selected by the user.

[0739] Step 10:

[0740] The server audits each process to protect user data and maintain overall system security.

[0741] (Example 1)

[0742] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0743] In today's world, personal and corporate financial management is becoming increasingly complex, making it difficult for many users to manage their assets and risks effectively. Furthermore, with the increasing emphasis on information security and privacy protection, there is a need to securely manage users' financial information while efficiently proposing optimal asset management plans. Providing learning opportunities to improve financial literacy is also a challenge.

[0744] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0745] In this invention, the server includes information management means for receiving and storing the user's financial information, protection means for encrypting and securely transmitting the financial information, and generation means for automatically generating an asset management plan based on the financial information. This allows the user to receive an appropriate and optimized asset management plan while securely managing their information. In addition, it can provide effective utilization of financial information and learning support.

[0746] "Information management means" refers to technical means for receiving and securely storing financial data provided by users.

[0747] "Protection measures" refer to technical means that encrypt users' financial information and ensure security during data transmission and reception.

[0748] "Generation means" refers to a technical function that analyzes collected financial data and automatically generates an optimal asset management plan for the user.

[0749] "Communication means" refers to information transmission functions used to notify users of the generated asset management plan.

[0750] "Monitoring measures" refer to technical means for tracking user spending in real time and detecting potential budget overruns.

[0751] A "proposal method" is a technical means that evaluates a user's insurance-related information and, based on that evaluation, presents the most suitable financial product.

[0752] "Learning support methods" refer to methods of providing users with educational materials to improve their financial knowledge.

[0753] "Evaluation means" refers to a technical function that simulates the generated asset management plan using multiple factors such as market trends and evaluates its validity.

[0754] "Analysis means" refers to technical means that analyze market trends and process the information necessary for optimizing asset management plans using AI models.

[0755] This invention is a complex system that supports the smooth financial management of individuals and corporations. This system allows users to input financial information using a dedicated application or web portal, and generates an optimal asset management plan based on that information. Detailed embodiments are described below.

[0756] First, users input information about their income, expenses, assets, and liabilities using a personal computing device or mobile terminal. This information is encrypted by the terminal and transmitted to the server via a security protocol. Data security is ensured by employing AES-256 encryption technology.

[0757] The server stores the received financial information in a relational database system. This step utilizes a MySQL database to achieve high-speed data access and efficient management. The stored data is analyzed using Python and various data processing libraries (e.g., Pandas). A generative AI model is used to generate an asset management plan from the collected financial information. To consider market conditions, TensorFlow is used to simulate market trends and perform diverse scenario analyses. In this process, an optimized plan is generated based on evaluation methods.

[0758] The generated investment plan is provided to the user via push notification or email. Through this, the user can review the proposed investment plan and request revisions as needed. Meanwhile, the server monitors income and expenses in real time and sends a special alert to the device if the budget is exceeded.

[0759] In addition, it includes a function to evaluate insurance information and suggest the most suitable products. This enables enhanced risk management tailored to the user's lifestyle. Furthermore, the device provides users with a wide range of educational content, from basic knowledge about asset management to specific strategies. This learning content is individually customized, allowing users to acquire knowledge that suits their individual needs.

[0760] For example, if a user has a goal such as "I want to save 300,000 yen to buy a car in three years," the server will use this to suggest the best savings plan and investment method. This suggestion is generated based on prompt statements like the following:

[0761] "A user wants to save 300,000 yen over the next three years. Considering their current income, expenses, and asset information, what savings plan and investment strategy would you propose?"

[0762] This allows the system to support users' daily financial activities and assist in promoting optimal asset building.

[0763] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0764] Step 1:

[0765] Users enter financial information using a dedicated application or web portal. Input fields include income, expenses, assets, and liabilities. Users specifically enter data such as, "This month's income is 500,000 yen, and expenses are 300,000 yen." This information is temporarily stored on the device.

[0766] Step 2:

[0767] The terminal encrypts the user's financial information entered. Encryption technologies such as AES-256 are used to ensure data security. The encrypted data is sent to the server using the HTTPS protocol. Input is unencrypted user data, and output is encrypted user data. Specifically, the terminal automatically performs the encryption process in the background.

[0768] Step 3:

[0769] The server decrypts the received encrypted data and stores it in a relational database system. The database system used is MySQL, which efficiently manages each user's information. The input is encrypted data, and the output is the decoded data stored in the database. After decryption, the information is written to the database very quickly.

[0770] Step 4:

[0771] The server uses a generative AI model to analyze the user's financial information and automatically generate an optimal asset management plan. It uses Python and the Pandas library to create a dataframe and simulate various market trends, including historical data. The input is stored user data, and the output is the optimal investment plan. Specifically, the server uses TensorFlow to rapidly execute hundreds of thousands of simulations and selects the plan best suited to each user.

[0772] Step 5:

[0773] The server sends the generated operational plan to the user via a notification system. The user can review the plan via smartphone or PC and request revisions if necessary. The input is the generated operational plan, and the output is the plan notification and user feedback. The server sends push notifications quickly to ensure the user can review the plan immediately.

[0774] Step 6:

[0775] The server monitors user spending in real time and sends a warning to the terminal if the budget is about to be exceeded. Real-time functionality is ensured by using WebSockets. The input is the user's current spending status, and the output is a warning notification. The server immediately monitors real-time data and issues alerts as needed.

[0776] Step 7:

[0777] The server evaluates the user's insurance information and suggests the latest financial products. It uses machine learning to perform analysis based on customer profiles. K-Means clustering is used to group user attributes and select appropriate insurance products. The input is the user's profile information, and the output is the suggested financial products. The server provides the user with the presented options via email or app notification as needed.

[0778] Step 8:

[0779] The device delivers educational content to improve users' financial skills. This content includes videos, quizzes, and articles. Input is the user's learning needs, and output is customized learning content. The device has the capability to deliver optimal content tailored to the user's level and goals.

[0780] (Application Example 1)

[0781] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0782] In modern times, managing finances efficiently and securely for individuals and corporations has become increasingly complex. While real-time tracking of expenses and planned asset management are crucial amidst diverse spending patterns, doing so manually is difficult. Furthermore, the widespread use of electronic transactions demands rapid expense management, yet there is a lack of systems that can automatically provide users with suitable asset management and savings suggestions. The objective of this invention is to solve these problems.

[0783] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0784] In this invention, the server includes an information management means for receiving and storing financial information, a transaction recording means for acquiring electronic transaction information in real time and automatically recording expenditures, and a monitoring means for monitoring the user's expenditures and issuing alerts when the budget is exceeded. This enables the user to manage their finances in real time, preventing budget overruns and automatically supporting planned asset management.

[0785] "Information management means" refers to a device or program that has the function of receiving a user's financial information and securely storing and managing it.

[0786] A "plan generation means" is a device or program that has the function of automatically generating an asset management plan suitable for the user based on the financial information received.

[0787] "Information provision means" refers to a device or program that has the function of notifying users of generated asset management plans and other related information and prompting them to take necessary actions.

[0788] A "monitoring device" is a device or program that has the function of monitoring a user's spending in real time and detecting the possibility of budget overruns.

[0789] A "transaction recording device" is a device or program that has the function of acquiring electronic transaction information in real time and automatically recording expenditures.

[0790] A "behavioral suggestion device" is a device or program that has the function of generating specific action suggestions to support users in achieving their savings goals.

[0791] A "proposal means" is a device or program that has the function of evaluating the user's insurance information and proposing the most suitable insurance product.

[0792] An "educational tool" is a device or program that has the function of delivering educational content to improve users' financial literacy.

[0793] The system for realizing this invention primarily functions through data communication between a server and a user's terminal. The server is programmed to implement information management means, plan generation means, information provision means, monitoring means, transaction recording means, action suggestion means, suggestion means, and education means. This set of programs provides a smooth and comprehensive financial management experience.

[0794] Specifically, the server manages the financial information received from users and securely stores the information using encryption technologies such as AES. The plan generation means utilizes machine learning algorithms to formulate an asset management plan based on the user's past transactions and goal setting. Next, the information provision means quickly notifies the user's terminal of the generated information. The monitoring means uses real-time data stream processing technology to continuously monitor whether the user's spending is within budget.

[0795] On the terminal, users actually use this system in their daily activities. For example, a smartphone app transmits electronic payment information to the server in real time via a transaction recording device, and expenditures are recorded and updated. The action suggestion device provides users with specific asset management advice to help them achieve their savings goals. In this way, the terminal and server work together to enhance the user's financial management.

[0796] As a concrete example, when a user makes a purchase using their mobile device, that information is immediately sent to the server. The user's asset management plan is then automatically updated, and comprehensive financial information becomes available on the user's device.

[0797] An example of a prompt message when using a generative AI model would be: "Design a user budget management and spending analysis algorithm based on electronic payment history. Include features for optimizing asset management plans based on user goals and providing real-time alerts."

[0798] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0799] Step 1:

[0800] The user makes an electronic payment using a terminal. The terminal retrieves this transaction information and transmits it to the server using a secure communication protocol. The input is electronic payment information, and the output is encrypted transaction data. The data is retrieved instantly, and security is ensured during communication.

[0801] Step 2:

[0802] The server decrypts the received transaction information and stores it in a database through an information management system. The input is encrypted transaction data, and the output is the decrypted transaction information stored in the database. The server uses encryption technology to decrypt the data and stores it in a data store for information management.

[0803] Step 3:

[0804] The server operates a plan generation system that updates the asset management plan based on the user's latest transaction information. Inputs are the latest transaction information and pre-stored financial data, and output is the updated asset management plan. The server uses machine learning algorithms to recalculate the asset management plan.

[0805] Step 4:

[0806] The monitoring system operates to check in real time whether the user's spending is within the set budget. The input is real-time spending data, and the output is a warning for exceeding the budget or a notification that there is no problem. The server sets spending thresholds and generates an alert if these are exceeded.

[0807] Step 5:

[0808] Through the action suggestion mechanism, the server generates optimal action suggestions for the user and notifies the terminal. The input is the updated asset management plan and budget status, and the output is a suggestion of specific savings actions. The server determines the need for plan changes and shows the user improvement measures.

[0809] Step 6:

[0810] Through educational methods, the server regularly delivers content designed to improve users' financial skills. The input is the user's learning history and interests, and the output is individually customized educational content. The server utilizes a generative AI model to provide a personalized educational program.

[0811] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0812] This invention combines an emotion engine with a system that supports personal financial management to provide optimal financial advice tailored to the user's emotional state. The operation of this system involves the combination of several key components and their respective functions.

[0813] First, users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal. The terminal receives this information, encrypts it, and securely transmits it to the server. The server stores the received data in a database and analyzes the user's financial situation.

[0814] Next, the server uses a generation algorithm to automatically generate an asset management plan that takes into account the user's goals and market trends. The emotion engine plays a crucial role here. It collects emotional data from the user's facial expressions, voice, and text feedback, and analyzes their stress level and psychological state. This information is reflected in the generated plan, providing a flexible plan tailored to the user's situation.

[0815] For example, if a user is experiencing high stress levels, the system will suggest a low-risk investment plan. The emotion engine also provides advice and educational content to help users overcome psychological barriers when making financial decisions. In this way, the emotion engine offers insights beyond mere financial data.

[0816] The server collects sentiment data and analyzes long-term trends based on it. This data is then fed back into operational planning and risk assessment. For example, if a user regularly expresses anxiety, the proposed plan will incorporate a more conservative operational approach than usual.

[0817] Furthermore, the real-time monitoring feature immediately sends an alert if a user's spending is likely to exceed their budget. This helps users prevent unnecessary spending and reduces their mental burden.

[0818] Finally, to advance the user's financial education, the system delivers educational content tailored to the user's interests and needs to their device. The emotion engine understands how effectively the user is learning the content and adjusts it as needed. In this way, a system is realized that provides comprehensive support while taking into account the user's emotional state.

[0819] The following describes the processing flow.

[0820] Step 1:

[0821] Users input financial information such as income, expenses, assets, and liabilities through a dedicated application or web portal.

[0822] Step 2:

[0823] The terminal receives the financial information entered by the user and securely transmits the data to the server using an encryption protocol.

[0824] Step 3:

[0825] The server stores the received financial information in a database and uses an analysis algorithm to analyze the user's financial situation.

[0826] Step 4:

[0827] While the user is using the application, the device acquires emotional data through the camera, microphone, text input, etc. This information includes facial expressions, voice tone, and keyboard touch speed.

[0828] Step 5:

[0829] The server processes emotional data sent from the terminal to identify the user's emotional state. It uses emotion recognition algorithms to measure stress levels and psychological barriers.

[0830] Step 6:

[0831] The server automatically generates an asset management plan using an AI algorithm based on the user's financial information and emotional state. The generated plan takes the user's emotional state into consideration and appropriately adjusts the risk level.

[0832] Step 7:

[0833] The server notifies the terminal of the generated asset management plan and allows the user to review its contents. The user can then approve or request modifications to the plan.

[0834] Step 8:

[0835] The user reviews the plan and approves or modifies it as needed. The server waits for the response and applies the plan.

[0836] Step 9:

[0837] The server monitors user spending in real time and immediately sends an alert to the terminal if there is a possibility of budget overrun. This monitoring is also adjusted based on stress levels read from emotional data.

[0838] Step 10:

[0839] The server periodically evaluates the user's insurance information and suggests the most suitable insurance product. This process also takes emotional data into account, reflecting the user's anxieties about insurance.

[0840] Step 11:

[0841] The device delivers personalized finance education content based on emotional data and learning trends. This allows users to effectively acquire knowledge and gain confidence in financial management.

[0842] (Example 2)

[0843] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0844] Providing appropriate asset management plans that take into account the emotional state of users is a challenging task in financial management. Furthermore, it is necessary to reduce the psychological barriers users feel when making financial decisions and provide support that allows them to confidently follow the plan. In addition, monitoring users' spending in real time to prevent budget overruns, as well as providing educational content that meets users' learning needs, are also crucial challenges.

[0845] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0846] In this invention, the server includes a storage means for receiving and storing the user's financial information, a calculation means for automatically generating an asset management plan based on the financial information, and an analysis means for analyzing emotional data and reflecting it in the generated plan. This enables the generation of flexible asset management plans tailored to the user's emotional state and provides support for financial decisions.

[0847] A "storage device" is a device or function for storing financial information received from a user, and it is capable of storing and retrieving data.

[0848] A "calculation means" refers to a process or device for automatically creating an asset management plan based on received financial information.

[0849] "Communication means" refers to a device or function for notifying the user of the generated asset management plan.

[0850] "Monitoring measures" refer to devices or functions that monitor user spending in real time and issue warnings if there is a possibility of exceeding the budget.

[0851] "Analysis means" refers to a function or device that collects and analyzes user emotional data and reflects the results in an asset management plan.

[0852] "Support measures" refer to devices or functions that, based on emotional data, support users' financial decisions and reduce psychological barriers.

[0853] A "feedback mechanism" is a device or function that feeds back emotional trends, analyzed over a long period, into the revision of investment plans and risk assessments.

[0854] "Educational tools" refer to devices or functions that deliver learning content to users and track their progress.

[0855] This invention is a system that supports financial management while taking into account the emotional state of the user, and is configured as follows.

[0856] First, users enter financial information such as income, expenses, assets, and liabilities into their device via a dedicated application or web portal. This information is securely encrypted by the device and transmitted to the server using the SSL / TLS protocol.

[0857] The server stores the received information in a database and uses it as a storage device. During this process, data sanitization is performed to check for abnormal values ​​and errors. Next, the server uses a generative AI model, which is its computational tool, to automatically generate an asset management plan based on the user's financial data and market trend data. An example of a prompt message to the generative AI model would be, "Please create an optimal asset management plan based on current market trends."

[0858] The device collects user emotional data in real time through facial expressions, voice, and text data. This emotional data is then sent back to the server, where analysis tools are used to evaluate the user's stress level and psychological state, and this is reflected in the automatically generated operational plan. As a result, if a user is experiencing high stress, a lower-risk operational plan is adjusted and provided.

[0859] Furthermore, the server analyzes long-term sentiment trends as a feedback mechanism, and uses this information when reviewing operational plans and conducting risk assessments. In particular, if users regularly experience anxiety, the proposed plans will be adjusted to be more conservative.

[0860] Real-time spending monitoring is performed by server-based monitoring systems, and alerts are immediately sent to users when budget overruns are predicted. This helps prevent unnecessary spending and reduces mental stress.

[0861] Furthermore, the server acts as an educational tool, providing learning content based on the user's interests and needs. This content is adjusted as the system tracks how effectively the user is learning. This allows users to acquire deeper financial knowledge and gain a better understanding of their own financial situation.

[0862] In this way, a system is realized that supports safe and effective financial management while taking into account the user's emotional state.

[0863] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0864] Step 1:

[0865] Users input financial information such as income, expenses, assets, and liabilities into a terminal using a dedicated application or web portal. This input data is fundamental information for gaining a detailed understanding of the user's financial situation.

[0866] Step 2:

[0867] The terminal receives the entered financial information, encrypts the data using the SSL / TLS protocol, and sends it to the server. This process ensures the safety and security of the data. The output is encrypted financial data.

[0868] Step 3:

[0869] The server stores the received encrypted data in a database. Here, data sanitization is performed, and data processing is carried out to check for outliers and errors, resulting in clean financial data being output.

[0870] Step 4:

[0871] The server uses a generation AI model to automatically generate asset management plans based on clean financial and market trend data. This calculation process outputs an optimal plan tailored to the user's goals. The prompt message used is in the format of "Please create an optimal asset management plan based on current market trends."

[0872] Step 5:

[0873] The device collects the user's facial expressions, voice, and text data in real time and sends it to the server as user emotion data. Here, data collection and basic processing of the emotion data take place.

[0874] Step 6:

[0875] The server uses analytical tools to evaluate stress levels and psychological states based on the received emotional data. A report of the evaluated emotional state is then generated through data calculations.

[0876] Step 7:

[0877] The server adjusts the generated asset management plan based on emotional data. It flexibly adjusts the plan, for example, suggesting a low-risk plan in cases of high stress, and outputs a final plan tailored to the user.

[0878] Step 8:

[0879] The server sends notifications regarding the operational plan to the terminal, and information is presented to the user based on these notifications. The user can then make financial decisions based on this information.

[0880] Step 9:

[0881] The server monitors user spending in real time and sends an alert to the terminal if the budget is exceeded. This monitoring system issues warnings prompting immediate action.

[0882] Step 10:

[0883] The server delivers educational content to the user's device based on their interests and needs. This process tracks learning progress and adjusts content as required.

[0884] Step 11:

[0885] The server analyzes long-term sentiment trends and feeds this back into risk assessment. This analysis yields trend analysis results that contribute to further adjustments to the operational plan.

[0886] (Application Example 2)

[0887] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0888] Traditional financial management systems managed assets and expenses without considering the emotional state of users, making it difficult to adequately address situations where users were prone to psychological stress. Furthermore, the lack of real-time feedback based on user emotion analysis made it difficult to propose flexible asset management plans that were sensitive to these emotions. This resulted in a problem where users' financial plans were often inappropriate, especially during economically unstable periods.

[0889] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0890] In this invention, the server includes emotion analysis means for analyzing the user's emotional state and providing real-time advice on spending based on that emotion; information management means for receiving and storing the user's financial information; and plan generation means for automatically generating an asset management plan based on the financial information. This enables personalized asset management plan suggestions tailored to the user's psychological state and real-time spending management.

[0891] "Information management means" refers to a device or software that has the function of storing and managing financial information received from users and securely storing it in a database.

[0892] A "plan generation means" is a device or software that has the function of automatically generating an asset management plan based on received financial information and designing a strategy that is suitable for the user's financial goals.

[0893] "Information notification means" refers to a device or software equipped with the function of notifying users of generated asset management plans and other important information.

[0894] A "monitoring device" is a device or software that has the function of monitoring a user's spending in real time and immediately issuing a warning if the set budget is likely to be exceeded.

[0895] A "selection suggestion means" is a device or software that has the function of evaluating the user's insurance information and suggesting the most suitable insurance product based on that information.

[0896] "Content distribution means" refers to a device or software that has the function of distributing educational content to users and supporting financial education.

[0897] "Emotional analysis means" refers to a device or software that analyzes a user's emotional state and provides real-time advice on spending based on that data.

[0898] The system for implementing this invention consists of three main elements: a user, a server, and a terminal.

[0899] Users input their financial information (income, expenses, assets, liabilities, etc.) via a device such as a smartphone. This information is encrypted on the device and securely transmitted to the server. The server receives and stores this data using an information management device and stores it in a database.

[0900] The server further analyzes the received financial information using a plan generation device and automatically generates an asset management plan tailored to the user's financial goals. This plan is immediately notified to the user through an information notification device.

[0901] The role of the sentiment analysis device is to analyze the user's voice and text data to evaluate their emotional state in real time. The information obtained from sentiment analysis is linked to the user's spending patterns, and the monitoring device displays a warning when spending approaches the budget limit. It also provides personalized spending advice to the user based on the sentiment data.

[0902] For example, if a user is feeling stressed while shopping, a notification might appear on their smartphone screen saying, "Why not hold off on making a big purchase for now and reconsider?" This allows for flexible asset management based on the user's emotions.

[0903] Furthermore, the selection and suggestion device evaluates insurance information and proposes the most suitable insurance product to the user. In addition, the content distribution device provides users with financial education content to support their knowledge improvement.

[0904] An example of input to the prompt generation AI model might be, "Generate an appropriate warning message to display when the user's emotional state is assessed as high stress."

[0905] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0906] Step 1:

[0907] The user inputs and transmits financial information via a terminal. This input includes income, expenses, assets, and liabilities. The terminal encrypts this information and securely transmits it to the server. The input here is the user's financial information, and the output is encrypted data.

[0908] Step 2:

[0909] The server receives encrypted data transmitted from the terminal, decrypts the financial information using an information management device, and stores it. The input is encrypted data, and the output is decoded financial information. This process allows the server to store each user's financial information in a database.

[0910] Step 3:

[0911] The server uses a plan generation device to analyze stored financial information and automatically generate an asset management plan based on the user's financial goals. The input is decoded financial information, and the output is the generated asset management plan. The resulting plan is structured as an asset strategy suitable for the user.

[0912] Step 4:

[0913] The generated asset management plan is communicated to the user via an information notification device. The input here is the generated asset management plan, and the output is a notification message to the user. This notification allows the user to gain information about their own financial policy.

[0914] Step 5:

[0915] The server analyzes the user's voice and text data through an emotion analysis device and evaluates their emotional state in real time. The input is the user's voice and text data, and the output is the analyzed emotion data. This allows for an accurate evaluation of the user's emotional state.

[0916] Step 6:

[0917] Based on the sentiment analysis results, the monitoring device evaluates the user's spending in real time and issues warnings as needed. The input here is the analyzed sentiment data and spending information, and the output is a warning notification to the user. Specifically, a notification such as "Is this purchase important? Perhaps you should think about it again?" might be sent.

[0918] Step 7:

[0919] The selection suggestion device evaluates stored insurance information and proposes the most suitable insurance product to the user. The input is the user's insurance information, and the output is information on the proposed insurance product. This process provides the user with the insurance selection that is expected to be most beneficial.

[0920] Step 8:

[0921] The content delivery device delivers educational content to help users improve their financial knowledge. The input is the user's learning needs, and the output is personalized educational content. Through this approach, users can effectively strengthen their financial knowledge.

[0922] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0923] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0924] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0925] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0926] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0927] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0928] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0929] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0930] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0931] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0932] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0933] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0934] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0935] 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.

[0936] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0937] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0938] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0939] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0940] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0941] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0942] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0943] The following is further disclosed regarding the embodiments described above.

[0944] (Claim 1)

[0945] A database means for receiving and storing users' financial information,

[0946] A generation means for automatically generating an asset management plan based on the aforementioned financial information,

[0947] A notification means for notifying the user of the asset management plan generated by the generation means,

[0948] A monitoring system that monitors user spending in real time and issues alerts when the budget is exceeded,

[0949] A proposal method that evaluates insurance information and suggests the most suitable insurance product,

[0950] Educational methods for delivering educational content to users,

[0951] A system that includes this.

[0952] (Claim 2)

[0953] The system according to claim 1, further comprising an evaluation means for evaluating an asset management plan using multiple simulations based on the user's financial objectives.

[0954] (Claim 3)

[0955] The system according to claim 1, further comprising a protective means for encrypting and storing the financial information of a user that has been received.

[0956] "Example 1"

[0957] (Claim 1)

[0958] An information management system that receives and stores users' financial information,

[0959] A protective means for encrypting and securely transmitting the aforementioned financial information,

[0960] A generation means for automatically generating an asset management plan based on the aforementioned financial information,

[0961] A communication means for notifying the user of the asset management plan generated by the generation means,

[0962] A monitoring system that monitors user spending in real time and issues warnings when the budget is exceeded,

[0963] A proposal method that evaluates insurance-related information and suggests the most suitable financial products,

[0964] A learning support method that delivers learning content to users,

[0965] An evaluation method that evaluates an asset management plan based on the user's financial objectives using multiple simulations,

[0966] A system that includes this.

[0967] (Claim 2)

[0968] The system according to claim 1, further comprising a protection function for encrypting and storing the financial information of a user that has been received.

[0969] (Claim 3)

[0970] The system according to claim 1, further comprising analytical means for monitoring financial status in real time and analyzing market trends using a generated AI model.

[0971] "Application Example 1"

[0972] (Claim 1)

[0973] An information management system that receives and stores users' financial information,

[0974] A plan generation means that automatically generates an asset management plan based on the aforementioned financial information,

[0975] Information provision means for notifying the user of the asset management plan generated by the plan generation means,

[0976] A monitoring system that monitors user spending in real time and issues alerts when the budget is exceeded,

[0977] A transaction recording method that acquires electronic transaction information in real time and automatically records expenditures,

[0978] Action proposals to support users in achieving their savings goals,

[0979] A proposal method that evaluates insurance information and suggests the most suitable insurance product,

[0980] Educational methods for delivering educational content to users,

[0981] A system that includes this.

[0982] (Claim 2)

[0983] The system according to claim 1, further comprising an evaluation means for evaluating an asset management plan using multiple simulations based on the user's financial objectives.

[0984] (Claim 3)

[0985] The system according to claim 1, further comprising a protective means for encrypting and storing the financial information of a user that has been received.

[0986] "Example 2 of combining an emotion engine"

[0987] (Claim 1)

[0988] A storage means for receiving and storing the user's financial information,

[0989] A calculation means for automatically generating an asset management plan based on the aforementioned financial information,

[0990] A communication means for notifying the user of the asset management plan generated by the aforementioned calculation means,

[0991] A monitoring system that monitors user spending in real time and issues warnings when the budget is exceeded,

[0992] An analytical method that analyzes user emotional data and reflects it in the generated plan,

[0993] A support method that provides financial decision-making assistance based on emotional data and alleviates psychological barriers,

[0994] A feedback mechanism that analyzes long-term emotional trends and feeds them back into risk assessment,

[0995] Educational methods for delivering learning content to users,

[0996] A system that includes this.

[0997] (Claim 2)

[0998] The system according to claim 1, further comprising an evaluation means for evaluating an asset management plan using multiple simulations based on the user's financial objectives.

[0999] (Claim 3)

[1000] The system according to claim 1, further comprising a protective means for encrypting and storing the financial information of a user that has been received.

[1001] "Application example 2 when combining with an emotional engine"

[1002] (Claim 1)

[1003] An information management system that receives and stores users' financial information,

[1004] A plan generation means that automatically generates an asset management plan based on the aforementioned financial information,

[1005] Information notification means for notifying the user of the asset management plan generated by the plan generation means,

[1006] A monitoring system that monitors user spending in real time and issues warnings when the budget is exceeded,

[1007] A selection and proposal method that evaluates insurance information and suggests the most suitable insurance product,

[1008] A content distribution method for delivering educational content to users,

[1009] An emotion analysis tool that analyzes the user's emotional state and provides real-time advice on spending based on those emotions,

[1010] A system that includes this.

[1011] (Claim 2)

[1012] The system according to claim 1, further comprising a plan evaluation means for evaluating an asset management plan using multiple simulations based on the user's financial objectives.

[1013] (Claim 3)

[1014] The system according to claim 1, further comprising information protection means for encrypting and storing the financial information of a user that has been received. [Explanation of Symbols]

[1015] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A database means for receiving and storing users' financial information, A generation means for automatically generating an asset management plan based on the aforementioned financial information, A notification means for notifying the user of the asset management plan generated by the generation means, A monitoring system that monitors user spending in real time and issues alerts when the budget is exceeded, A proposal method that evaluates insurance information and suggests the most suitable insurance product, Educational methods for delivering educational content to users, A system that includes this.

2. The system according to claim 1, further comprising an evaluation means for evaluating an asset management plan using multiple simulations based on the user's financial objectives.

3. The system according to claim 1, further comprising a protective means for encrypting and storing the financial information of a user that has been received.

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