system

Abstract

システムを提供する。【解決手段】ユーザーの入力情報を受信する手段と、前記ユーザーの入力情報に基づき金融情報をインターネットから収集する手段と、前記収集された金融情報を基に資産形成の計画を生成する手段と、前記生成された資産形成の計画を可視化する手段と、前記可視化された資産形成の計画に対するユーザーのフィードバックを受ける手段と、前記ユーザーのフィードバックに応じて前記資産形成の計画を調整する手段と、外部の金融情報の変化をモニタリングし、前記資産形成の計画を更新する手段と、経済的取引データを統合し、前記資産形成の計画とリアルタイムで連動させる手段と、を含むシステム。

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 recent years, due to the lack of financial education in Japan, many individuals do not understand effective ways of asset formation. As a result, the number of cases where it is difficult to secure assets for old-age life has been increasing, threatening the economic security of individuals. In addition, it is not easy for individuals to conduct advanced information analysis and asset planning with limited counselors having specialized knowledge. Therefore, there is a need for a means by which users can obtain a realistic asset formation plan with less knowledge and effort.

Means for Solving the Problems

[0005] The system of this invention automatically collects relevant financial information from the internet, starting with input information provided by the user, and generates an asset formation plan based on this information. Furthermore, the generated plan is visualized using graphs and other methods, allowing the user to intuitively understand its contents. The system also provides a function to dynamically adjust the plan based on user feedback and maintains the up-to-dateness of the plan by constantly monitoring changes in financial information. In this way, the system supports users in obtaining appropriate and timely asset formation plans.

[0006] "User" refers to an individual who wishes to create an asset building plan using this system.

[0007] "Input information" refers to various types of data that users enter into their devices as goals or wishes related to asset building.

[0008] "Financial information" refers to relevant information necessary for wealth building, such as data on tax systems, interest rates, and investment products, collected via the internet.

[0009] "Means of collection" refers to the technical processes that servers use to obtain financial information via the internet.

[0010] A "wealth building plan" refers to a plan that includes specific asset management and investment scenarios, generated based on the user's goals.

[0011] "Means of visualization" refers to technologies that convert the generated asset formation plan into graphs, charts, etc., and present it to users in an easy-to-understand format.

[0012] "Means of receiving feedback" refers to the process by which the system receives user opinions and requests as input again and uses them to adjust plans.

[0013] "Means of updating" refers to technologies that monitor changes in collected financial information and, accordingly, revise and regenerate asset building plans with the latest information. [Brief explanation of the drawing]

[0014] [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] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, a processor with a reference number (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one 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.

[0018] In the following embodiments, a RAM (Random Access Memory) with a reference number is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, a storage with a reference number is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0020] 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).

[0021] 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."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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".

[0035] This invention is a system for providing users with a means to easily create and implement asset formation plans. This system is mainly implemented with the following configuration.

[0036] First, the user enters their wishes and goals regarding wealth building into the terminal. Based on this, the server retrieves the necessary information from the internet. This information includes the latest data on tax laws, interest rates, and investment products. Based on the collected information, the server generates a wealth building plan to help the user achieve their goals. At this stage, an algorithm is used to consider different investment scenarios and select the optimal plan.

[0037] The generated plan is displayed visually in a way that users can intuitively understand. Specifically, the server creates graphs and charts based on the plan's content and provides them to the user via their device. This allows users to easily grasp the progress of their asset building and the actions that need to be taken.

[0038] Furthermore, when a user provides specific feedback on the displayed plan, the server adjusts the plan based on that feedback. For example, if a user wishes to lower their risk tolerance, the investment scenario is recalculated and the plan is modified to match that objective.

[0039] Furthermore, the system has a function to continuously update information in response to changes in the external environment. The server regularly monitors market trends and changes in legal systems, revises plans as needed, and delivers the latest information to users.

[0040] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will collect necessary economic data from the internet and generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented by a line graph showing the expected flow of funds and displayed on the terminal. In this way, the system functions as a powerful tool to support the user's asset building.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] Users input their asset building goals and aspirations into the terminal's interface. At this time, they can also specify concrete amounts, timeframes, and risk tolerance.

[0044] Step 2:

[0045] The terminal sends the information entered by the user to the server as initial data. This information includes the user's asset building goals.

[0046] Step 3:

[0047] The server automatically collects relevant financial information from the internet based on user input. Specifically, it uses public databases and financial institution APIs to obtain the latest information on tax laws, interest rates, and investment products.

[0048] Step 4:

[0049] The server analyzes the collected financial information and generates an optimal asset building plan to help the user achieve their goals. At this stage, simulations are performed using different investment strategies and risk scenarios to select the plan with the highest expected value.

[0050] Step 5:

[0051] The server visualizes the generated asset building plan in an easy-to-understand format. Specifically, it creates line graphs showing the progress of the plan and bubble charts showing the relationship between risk and return.

[0052] Step 6:

[0053] The terminal displays visualization data sent from the server, presenting the user with an overview of the plan. This allows the user to visually confirm the details of the plan.

[0054] Step 7:

[0055] Users review the presented asset building plan and provide feedback as needed. This feedback may include changes to risk tolerance or adjustments to investment amounts.

[0056] Step 8:

[0057] The server recalculates and adjusts the asset building plan based on user feedback. If necessary, it generates new investment scenarios, visualizes them again, and presents them to the user.

[0058] Step 9:

[0059] The server constantly monitors financial information and changes in economic trends, and updates plans based on the latest information it acquires. In the event of significant changes, users will be notified.

[0060] (Example 1)

[0061] 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."

[0062] For individuals to achieve their wealth-building goals, proper information gathering and planning are essential. However, this generally requires advanced knowledge and analytical skills, making it a difficult and time-consuming task for many. Furthermore, keeping up with rapidly changing market trends and legal systems is not easy. Therefore, there is a need to develop a system that provides individual investors with an intuitively usable wealth-building plan that always reflects the latest information.

[0063] 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.

[0064] In this invention, the server includes means for receiving user input information, means for collecting economic information from a communication network, and means for generating asset management plans. This makes it possible for users to easily formulate plans based on their own asset formation goals and to always execute optimal asset management based on the latest information, even without specialized knowledge.

[0065] A "user" is an individual or organization that uses the system to set asset building goals and create plans.

[0066] "Input information" refers to the data that users send to the system, including the requirements and preferences necessary to achieve their goals.

[0067] "Economic information" refers to external data on tax systems, interest rates, and investment products necessary for creating an asset formation plan.

[0068] A "wealth management plan" is a long-term investment strategy formulated based on economic information collected to help the user achieve their goals.

[0069] "Visualization" is the process of visually representing the generated asset management plan in a way that is easy for the user to understand.

[0070] "Opinions" refer to evaluations and requests made by users regarding the asset management plan presented, and these are reflected in adjustments to the plan.

[0071] "Monitoring" refers to the activity of a server continuously checking for changes in the market and legal systems, and updating asset management plans as needed.

[0072] This invention is a system for users to set asset formation goals and develop actionable plans. Specific embodiments are shown below.

[0073] First, the user enters their goals and aspirations regarding wealth creation into their device. The device used here is a common computing device such as a personal computer or smartphone.

[0074] Next, the server begins operating based on the user's input. The server collects necessary economic information from the internet via the communication network. This process utilizes APIs from financial data providers and web crawling technologies. Based on this collected information, the server performs data analysis to develop an investment plan. It conducts simulations based on historical market data and generates an optimal investment scenario that takes into account the user's risk tolerance.

[0075] The generated asset management plan is presented to the user in an easy-to-understand format. Specifically, the server visualizes the plan data and sends it to the terminal as graphs and charts. This allows the user to visually grasp the progress of their asset building and the actions that need to be taken.

[0076] Users can provide feedback on the displayed plan. For example, they can input comments such as "I want to reduce the risk further" from their device. Based on this feedback, the server recalculates the investment scenario and adjusts the plan.

[0077] Furthermore, the servers monitor changes in the market and legal systems, and update asset management plans as needed. This allows users to access plans based on the latest information.

[0078] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will gather the necessary economic data from the internet to generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented in graphs showing the expected flow of funds and displayed on the terminal.

[0079] An example of a prompt would be, "My goal is to save 30 million yen in 10 years. Can you suggest the best investment plan considering annual interest rates and risks?"

[0080] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0081] Step 1:

[0082] Users input their asset-building goals and desired conditions into the terminal. Specifically, users enter a goal into a form, such as "I want to accumulate 30 million yen in assets in 10 years." This input information is then used in the next step of processing.

[0083] Step 2:

[0084] The server collects necessary economic information from the internet based on the input information received from the user. Based on the input information, the server sends requests to financial data provider APIs to obtain the latest tax, interest rate, and investment product data. This collected dataset forms the basis for the next planning step.

[0085] Step 3:

[0086] The server generates an asset management plan based on collected economic information and the user's goals. In this step, the server uses a generating AI model to perform simulations based on historical market data. Specifically, it considers different investment scenarios and derives the optimal plan for the user's risk tolerance and goal achievement. The generated plan is output in a digital format and moves on to the next visualization step.

[0087] Step 4:

[0088] The server visualizes the generated asset management plan and sends it to the terminal. Based on the plan data, the server launches software to create graphs and charts, generating visual materials. This allows users to receive information about their asset building progress in an intuitively easy-to-understand format.

[0089] Step 5:

[0090] Users provide feedback on the displayed plan. For example, they might input a comment like, "I want to reduce the risks further." This feedback is sent to the server and used as input for the next plan adjustment step.

[0091] Step 6:

[0092] The server adjusts the asset management plan based on feedback received from the user. The server re-evaluates previously generated simulation results and recalculates an adjusted investment plan that reflects the user's new opinions. This updated plan is visualized again and sent to the terminal.

[0093] Step 7:

[0094] The server regularly monitors market trends and changes in legal systems. It uses APIs and web crawling technologies to retrieve the latest information and automatically updates asset management plans as needed. This real-time update information is notified to the user to ensure continued optimal wealth creation.

[0095] (Application Example 1)

[0096] 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."

[0097] In personal wealth building, there is a problem with the insufficient linkage between real-time management of expenses and income and asset planning that reflects that information. This is particularly evident with the spread of electronic payments, and the lack of means for users to quickly and accurately adjust their asset plans is a challenge.

[0098] 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.

[0099] In this invention, the server includes means for receiving user input information, means for collecting financial information, means for generating an asset formation plan, means for visualizing the plan, means for receiving feedback, means for adjusting the plan, means for monitoring data, and means for integrating economic transaction data and linking it with the plan. This allows for the immediate reflection of the user's spending and income data from electronic payments into the asset plan, enabling more appropriate asset management.

[0100] "User input information" refers to the individual financial goals and risk tolerance that users provide in order to create an asset building plan.

[0101] "Financial information" includes the latest data on tax systems, interest rates, and investment products related to wealth building.

[0102] A "wealth building plan" refers to an investment strategy or plan generated based on the user's financial goals.

[0103] "Visualization" means presenting the generated asset building plan in a format that is easy for the user to understand, such as graphs or charts.

[0104] "Feedback" refers to the act of users providing opinions and suggestions regarding plans and proposals.

[0105] "Adjustment" is the process of re-evaluating and modifying asset building plans based on user feedback and external information.

[0106] "Monitoring" refers to the continuous observation of market trends, changes in legal systems, and other factors, and the collection of necessary information.

[0107] "Integrating economic transaction data and linking it to planning" means incorporating expenditure and income information from electronic payments into asset planning in real time, enabling dynamic plan adjustments.

[0108] A description of embodiments for carrying out this invention will be given.

[0109] Users enter their personal wealth-building goals using a smartphone or other device. This information is sent to a server. Based on the user's input, the server collects financial information via the internet. This financial information includes tax laws, interest rates, and investment products.

[0110] Based on the collected financial information, the server calculates multiple asset building scenarios tailored to the user's goals and generates an optimal plan. The plan is visualized using visual means such as graphs and charts and displayed on the user's device. Through this visualized information, the user can monitor their asset building progress and provide feedback.

[0111] The server dynamically adjusts the plan based on user feedback. During this process, the server monitors changes in the external environment and updates the plan based on real-time market trends and legal revisions. Furthermore, it integrates economic transaction data, reflecting daily expenses and income in the plan in real time, enabling more accurate adjustments to asset planning. These functionalities are achieved by utilizing electronic payment APIs and financial data APIs.

[0112] As a concrete example, consider a case where user A sets a goal of "saving 2 million yen within 5 years." The server analyzes the user's spending patterns from their electronic payment history and builds a plan to achieve the goal. The generating AI model can then suggest appropriate actions to the user using prompts such as, "Please suggest the latest tax information needed to improve my investment plan."

[0113] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0114] Step 1:

[0115] Users input their asset building goals via a device such as a smartphone. This input information includes target amounts for savings and investments, timeframes, and risk tolerance. The device receives this input information and transmits it to the server.

[0116] Step 2:

[0117] The server collects up-to-date financial information, such as tax laws, interest rates, and investment products, via the internet based on user input. This collection is performed in real time using a financial data API, and the acquired data forms the basis for generating asset plans. The input is user information, and the output is financial information.

[0118] Step 3:

[0119] The server uses collected financial information and user input to calculate different asset building scenarios and generate an optimal plan. This calculation includes multiple investment strategies, and a generative AI model is used to select the best plan. The input is financial information and user information, and the output is an asset building plan.

[0120] Step 4:

[0121] The server visualizes the generated asset building plan as graphs and charts and displays them on the terminal. This visualization allows the user to intuitively understand the progress and details of the plan. The input is the asset building plan, and the output is the visualized data.

[0122] Step 5:

[0123] Users can review the displayed plan and provide feedback. This feedback may include changes to risk tolerance or adjustments to the target amount. The device sends the feedback to the server.

[0124] Step 6:

[0125] The server dynamically adjusts the asset building plan based on user feedback. It also integrates economic transaction data to reflect the latest income and expenditure information. Inputs are feedback and economic transaction data, and output is the adjusted plan.

[0126] Step 7:

[0127] The server monitors market trends and changes in legal systems, and updates the plan as needed. This ensures that the plan always reflects the latest information. The input is monitoring data, and the output is the updated plan.

[0128] 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.

[0129] This invention is a system that combines an emotional engine with an asset formation system to understand the user's emotional state and provide a individually customized asset formation plan. Specific embodiments are described below.

[0130] First, the user enters their asset-building goals and aspirations into the terminal's interface. This information includes specific amounts, desired asset types, investment timeframe, and risk tolerance. The entered information is then sent to the server as initial data.

[0131] The server automatically collects relevant financial information from the internet based on the information entered by the user. At this stage, it utilizes public databases and financial institution APIs to obtain the latest data on tax laws, interest rates, and investment products. The collected information is also recorded in a database.

[0132] During the asset building plan generation stage, the server uses collected financial information to create asset building scenarios tailored to the user's goals. The plan includes different investment strategies evaluated through simulations, and the most suitable plan is selected.

[0133] The generated plan is visualized by the server and presented to the user via the terminal. The visualization methods used include line graphs showing the progress of the plan and bubble charts showing scenario analysis, allowing the user to intuitively grasp the overall picture of the plan.

[0134] The emotion engine, a key feature of this invention, is incorporated at the stage where user feedback on the plan is received. The server uses the emotion engine to analyze and recognize emotions from the user's voice or input text. This emotional information is used to further customize the asset building plan. For example, if the user is feeling anxious, responses such as presenting a lower-risk scenario are taken.

[0135] Furthermore, the server monitors changes in financial markets and regularly updates the asset building plan provided by the system. When the user's emotional state changes or new information becomes available, the plan is restructured and the user is notified at the appropriate time.

[0136] For example, if a user sets their goal to "maximize investment returns within five years" and the emotion engine detects "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy will be presented. In this way, the system provides a dynamic and personalized asset building plan that responds to the user's needs and emotions.

[0137] The following describes the processing flow.

[0138] Step 1:

[0139] Users input their wealth-building goals and aspirations into the device's interface. Specific inputs include target asset amount, timeframe, and investment risk tolerance.

[0140] Step 2:

[0141] The terminal sends user input information to the server. This information is used as initial system data and therefore needs to be transmitted accurately.

[0142] Step 3:

[0143] The server collects relevant financial information from the internet based on the goals and preferences received from the user. It primarily obtains the latest tax, interest rate, and investment product information from APIs of trusted financial institutions and databases of public institutions.

[0144] Step 4:

[0145] The server analyzes the collected data and generates an asset building plan to help the user achieve their goals. It simulates various investment scenarios and selects the plan with the optimal balance of risk and return. The user's risk tolerance is also taken into consideration during this process.

[0146] Step 5:

[0147] The server visualizes the generated asset building plan and converts the data into a format that can be displayed as graphs and charts. This visualization allows users to intuitively understand the overall picture and details of the plan.

[0148] Step 6:

[0149] The device presents the user with visualized plan data. Based on this, the user can review the plan and deepen their understanding.

[0150] Step 7:

[0151] The user reviews the plan and then provides voice or text input for emotion recognition by the emotion engine. It is expected that emotions such as joy and anxiety will be extracted from the input.

[0152] Step 8:

[0153] The server analyzes the user's emotions using an emotion engine and incorporates the results into the asset building plan. For example, if the user expresses anxiety, the plan may be adjusted to be more conservative.

[0154] Step 9:

[0155] The server monitors market changes and fluctuations in economic conditions, and updates the asset building plan based on the latest information it obtains. It also restructures the plan if the user's emotions change, and is configured to notify the user as needed.

[0156] (Example 2)

[0157] 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".

[0158] Traditional asset building systems often provide uniform asset building plans without considering the user's emotional state, which is problematic as it fails to adequately address individual needs. Furthermore, they struggle to respond immediately to changes in financial markets and lack the flexibility to propose the optimal asset building plan for each user.

[0159] 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.

[0160] In this invention, the server includes means for receiving user goal information, means for collecting data from a network, and means for recognizing the user's emotions using sentiment analysis and adjusting the asset building scenario. This makes it possible to provide a flexible and customized asset building plan that responds to the user's individual emotional state and market changes.

[0161] A "user" is an entity that uses the system to set asset building goals and provides feedback.

[0162] "Target information" refers to information entered by users, such as specific target amounts and timeframes for asset building, and risk tolerance.

[0163] "Data" refers to a collection of information, including laws, regulations, interest rates, and financial products, that is gathered through networks to support wealth building plans.

[0164] A "network" is a communication infrastructure for exchanging data, and includes wide-area communication lines such as the internet.

[0165] A "wealth building scenario" is a proposed structure of a wealth expansion plan generated based on the user's goal information and external data.

[0166] "Visual representation" refers to a method of making information intuitively understandable to users using computational diagrams, representational diagrams, and other visual aids.

[0167] "Response" refers to user feedback and comments on asset building scenarios.

[0168] "Emotion analysis" is a technology that analyzes a user's voice and text data to identify their emotional state.

[0169] "Market information" refers to a collection of information about trends in the external environment, such as fluctuations in financial markets and trading data.

[0170] "Monitoring" refers to the act of continuously checking changes in market information and evaluating the potential impact on users.

[0171] This invention is a system that utilizes user information to provide individually optimized asset building plans. This system is particularly characterized by its provision of dynamic plans that reflect the user's emotional state.

[0172] Users input their asset-building goals into the terminal's interface. These goals include specific target amounts, timeframes, and risk tolerance. The entered information is then sent to the server as initial data.

[0173] The server automatically collects relevant data via the network based on information entered by the user. This data includes legal and regulatory information, interest rates, and information on financial products. The server uses APIs and data schemas as protocols to efficiently retrieve information and store it in a database. Data analysis software is used in this process to enable high-speed data processing.

[0174] Based on the collected data, the server generates multiple asset building scenarios. Simulation software and numerical analysis tools are used for this generation. For example, it compares the profitability of different investment strategies to determine the strategy best suited to the user's risk tolerance. The generated scenarios are visualized using visualization tools as line graphs and bubble charts. This allows the scenarios to be presented visually to the user through their device, enabling intuitive understanding.

[0175] Next, the server uses an emotion analysis engine to identify the user's emotional state. It analyzes voice data and input text from the user to determine whether the emotion is "security," "anxiety," etc. Based on this emotional information, it further adjusts the asset building plan. For example, if the user indicates anxiety, a more conservative scenario will be included in the plan.

[0176] Furthermore, the server has the function of continuously monitoring market information and updating plans in response to changes in the external environment. This ensures that users always have an asset building plan based on the latest information.

[0177] For example, if a user sets a goal of "maximizing investment returns within 5 years," and the emotion analysis engine detects "security," the server will suggest a higher-risk investment strategy. Conversely, if "anxiety" is detected, a lower-risk strategy will be suggested. An example of a prompt would be, "If the user indicates security, please suggest an investment strategy with a high risk tolerance." This prompt instructs the generative AI model to generate plans based on emotion.

[0178] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0179] Step 1:

[0180] The user enters their asset-building goal information into the terminal interface. This includes the target amount, investment period, desired investment products, and risk tolerance. The entered information is sent to the server and used as initial data for the program. This information forms the basis for all subsequent processing steps.

[0181] Step 2:

[0182] The server collects data from the network based on the target information entered by the user. Specifically, it uses APIs to obtain the latest legal regulations, interest rates, and investment product information from public and financial institutions. This collected data is stored in a database and used as material for subsequent scenario generation. Real-time updated data analysis tools are used for data collection.

[0183] Step 3:

[0184] The server generates asset building scenarios based on collected data and user goal information. This process uses simulation software to perform numerical analysis on different investment strategies. The output consists of multiple investment scenarios, from which the most appropriate one is selected. The generated scenario is output as a detailed analysis, including the profitability and risk of the strategy.

[0185] Step 4:

[0186] The server visually represents the generated asset formation scenario. A graph generation tool is used for visualization, creating line graphs and bubble charts. The input for this process is the scenario data from step 3, and the output is visually organized information. The resulting visuals are presented to the user via a terminal, allowing the user to intuitively understand the information.

[0187] Step 5:

[0188] The server analyzes user feedback using an emotion analysis engine. It identifies emotional states from the user's voice and input text, generating emotional data such as "sense of security" and "anxiety." Based on this emotional information, the server adjusts the asset building scenario accordingly. The risk level of the scenario is dynamically changed according to the results of the emotional information analysis.

[0189] Step 6:

[0190] The server monitors fluctuations in financial markets and updates the asset building plan. New external information is acquired, and the plan is restructured, taking into account the user's sentiment data and market trends. In this process, visualized information based on feedback is generated again and notified to the user via the terminal. The user is able to always have a plan based on the latest information.

[0191] (Application Example 2)

[0192] 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".

[0193] In modern society, it is a challenging task for individual users to create appropriate asset building plans based on their emotions. Conventional systems fail to adequately provide asset building plans that take into account users' emotional states, and the anxieties and stresses users experience hinder the execution of these plans. Particularly in electronic payments, there is a need to optimize spending and risk in accordance with users' emotional states.

[0194] 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.

[0195] In this invention, the server includes means for receiving user input information, means for collecting financial information from a communication network based on the user input information, means for generating an asset building plan based on the collected financial information, means for visually representing the generated asset building plan, means for receiving the user's response to the visually represented asset building plan, and means for analyzing the user's emotional state, further individualizing the asset building plan based on the emotional state, and assisting the user in optimizing spending and risk. This makes it possible to provide an individualized asset building plan that reflects the user's emotional state.

[0196] "User input information" refers to data in which users specifically express their goals and aspirations for asset building.

[0197] "Financial information" refers to general data related to wealth creation, such as legal systems, interest rates, and investment products.

[0198] A "communication network" is a network that allows data to be transmitted bidirectionally, such as the internet.

[0199] A "wealth building plan" is a set of investment strategies and their implementation plan formulated to achieve a user's wealth building goals.

[0200] "Visual representation" refers to techniques that use graphs, charts, and other visual tools to make data and information easier to understand.

[0201] "User response" refers to the user's reaction and feedback to the generated plan.

[0202] "Emotional state" refers to a user's psychological condition and emotional tendencies, and is a factor that influences decision-making when executing a plan.

[0203] The system for implementing this invention consists of a server and a user terminal. First, the user's terminal transmits data about the user's asset building goals and desires to the server. This includes specific amounts, desired asset types, investment periods, and risk tolerance.

[0204] Based on the user's input, the server collects relevant financial information using public databases and communication networks such as financial institution APIs. This financial information includes legal systems, interest rates, and investment products. Subsequently, based on the collected financial information, it generates an asset building plan tailored to the user's goals. In this process, the server simulates various investment strategies and selects the optimal plan.

[0205] The asset building plan generated by the server is visually represented and presented to the user's terminal. The user can provide feedback on the visually represented plan. The server uses the user's responses to adjust the asset building plan. In this adjustment process, the user's emotional state is considered a crucial factor. Using an emotion engine, the server analyzes and recognizes the user's emotions from their voice and input text, and further customizes the plan according to that emotional state.

[0206] For example, if a user sets their goal to maximize investment returns within a limited timeframe, and the emotion engine detects a sense of "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy can be presented. This allows users to obtain the optimal asset building plan according to their emotions at any given time.

[0207] Furthermore, changes in financial markets are monitored by the server, and asset building plans are regularly updated based on the results. This ensures that the plan is always up-to-date, and is restructured when the user's emotional state changes or new information becomes available.

[0208] An example of a prompt to a generative AI model is, "Perform a sentiment analysis on the product the user is about to purchase, and provide the risks and benefits of purchasing this product." This prompt allows the AI ​​to appropriately assess the user's emotional state and provide personalized advice.

[0209] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0210] Step 1:

[0211] The user uses a terminal to input their asset building goals and aspirations. This input includes specific amounts, desired asset types, investment timeframe, and risk tolerance. This information is sent to the server as initial data.

[0212] Step 2:

[0213] The server collects financial information from public databases and financial institution APIs based on user input. This includes data on legal systems, interest rates, and investment products. At this stage, the input consists of the user's desired conditions, and the output is relevant financial information.

[0214] Step 3:

[0215] The server generates an asset building plan tailored to the user's goals based on the collected financial information. Here, the server simulates various investment strategies and selects the most suitable plan. The input is the financial information from step 2, and the output is the proposed plan. Data calculations include risk assessment and yield forecasting.

[0216] Step 4:

[0217] The generated plan is visually represented by the server and sent to the user terminal. Graphs and charts are used for visualization, with the generated plan information as input and the visualized information as output.

[0218] Step 5:

[0219] Users review the plan on their devices and provide feedback. This feedback is received by the server and used to adjust the plan. The input is the user's feedback, and the output is the adjusted plan.

[0220] Step 6:

[0221] The server uses an emotion engine to analyze the user's emotional state from their input and voice data. Input consists of feedback information and voice data, while output is the result of the emotion evaluation. The prompt text from the generative AI model is used here.

[0222] Step 7:

[0223] Based on the results of the emotional assessment, the asset building plan is personalized and adjusted to better suit the user's emotions. The input is the result of the emotional assessment, and the output is the final asset plan.

[0224] Step 8:

[0225] The server monitors changes in financial markets and regularly updates asset building plans based on new information. Input is the latest financial data, and output is the updated plan. This ensures the plan is always up-to-date.

[0226] 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.

[0227] 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.

[0228] 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.

[0229] [Second Embodiment]

[0230] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0231] 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.

[0232] 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).

[0233] 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.

[0234] 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.

[0235] 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).

[0236] 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.

[0237] 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.

[0238] 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.

[0239] 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.

[0240] 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.

[0241] 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".

[0242] This invention is a system for providing users with a means to easily create and implement asset formation plans. This system is mainly implemented with the following configuration.

[0243] First, the user enters their wishes and goals regarding wealth building into the terminal. Based on this, the server retrieves the necessary information from the internet. This information includes the latest data on tax laws, interest rates, and investment products. Based on the collected information, the server generates a wealth building plan to help the user achieve their goals. At this stage, an algorithm is used to consider different investment scenarios and select the optimal plan.

[0244] The generated plan is displayed visually in a way that users can intuitively understand. Specifically, the server creates graphs and charts based on the plan's content and provides them to the user via their device. This allows users to easily grasp the progress of their asset building and the actions that need to be taken.

[0245] Furthermore, when a user provides specific feedback on the displayed plan, the server adjusts the plan based on that feedback. For example, if a user wishes to lower their risk tolerance, the investment scenario is recalculated and the plan is modified to match that objective.

[0246] Furthermore, the system has a function to continuously update information in response to changes in the external environment. The server regularly monitors market trends and changes in legal systems, revises plans as needed, and delivers the latest information to users.

[0247] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will collect necessary economic data from the internet and generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented by a line graph showing the expected flow of funds and displayed on the terminal. In this way, the system functions as a powerful tool to support the user's asset building.

[0248] The following describes the processing flow.

[0249] Step 1:

[0250] Users input their asset building goals and aspirations into the terminal's interface. At this time, they can also specify concrete amounts, timeframes, and risk tolerance.

[0251] Step 2:

[0252] The terminal sends the information entered by the user to the server as initial data. This information includes the user's asset building goals.

[0253] Step 3:

[0254] The server automatically collects relevant financial information from the internet based on user input. Specifically, it uses public databases and financial institution APIs to obtain the latest information on tax laws, interest rates, and investment products.

[0255] Step 4:

[0256] The server analyzes the collected financial information and generates an optimal asset building plan to help the user achieve their goals. At this stage, simulations are performed using different investment strategies and risk scenarios to select the plan with the highest expected value.

[0257] Step 5:

[0258] The server visualizes the generated asset building plan in an easy-to-understand format. Specifically, it creates line graphs showing the progress of the plan and bubble charts showing the relationship between risk and return.

[0259] Step 6:

[0260] The terminal displays visualization data sent from the server, presenting the user with an overview of the plan. This allows the user to visually confirm the details of the plan.

[0261] Step 7:

[0262] Users review the presented asset building plan and provide feedback as needed. This feedback may include changes to risk tolerance or adjustments to investment amounts.

[0263] Step 8:

[0264] The server recalculates and adjusts the asset building plan based on user feedback. If necessary, it generates new investment scenarios, visualizes them again, and presents them to the user.

[0265] Step 9:

[0266] The server constantly monitors financial information and changes in economic trends, and updates plans based on the latest information it acquires. In the event of significant changes, users will be notified.

[0267] (Example 1)

[0268] 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."

[0269] For individuals to achieve their wealth-building goals, proper information gathering and planning are essential. However, this generally requires advanced knowledge and analytical skills, making it a difficult and time-consuming task for many. Furthermore, keeping up with rapidly changing market trends and legal systems is not easy. Therefore, there is a need to develop a system that provides individual investors with an intuitively usable wealth-building plan that always reflects the latest information.

[0270] 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.

[0271] In this invention, the server includes means for receiving user input information, means for collecting economic information from a communication network, and means for generating asset management plans. This makes it possible for users to easily formulate plans based on their own asset formation goals and to always execute optimal asset management based on the latest information, even without specialized knowledge.

[0272] A "user" is an individual or organization that uses the system to set asset building goals and create plans.

[0273] "Input information" refers to the data that users send to the system, including the requirements and preferences necessary to achieve their goals.

[0274] "Economic information" refers to external data on tax systems, interest rates, and investment products necessary for creating an asset formation plan.

[0275] A "wealth management plan" is a long-term investment strategy formulated based on economic information collected to help the user achieve their goals.

[0276] "Visualization" is the process of visually representing the generated asset management plan in a way that is easy for the user to understand.

[0277] "Opinions" refer to evaluations and requests made by users regarding the asset management plan presented, and these are reflected in adjustments to the plan.

[0278] "Monitoring" refers to the activity of a server continuously checking for changes in the market and legal systems, and updating asset management plans as needed.

[0279] This invention is a system for users to set asset formation goals and develop actionable plans. Specific embodiments are shown below.

[0280] First, the user enters their goals and aspirations regarding wealth creation into their device. The device used here is a common computing device such as a personal computer or smartphone.

[0281] Next, the server begins operating based on the user's input. The server collects necessary economic information from the internet via the communication network. This process utilizes APIs from financial data providers and web crawling technologies. Based on this collected information, the server performs data analysis to develop an investment plan. It conducts simulations based on historical market data and generates an optimal investment scenario that takes into account the user's risk tolerance.

[0282] The generated wealth management plan is provided in a form that is easy for users to understand. Specifically, the server visualizes the plan data and transmits it to the terminal as graphs and charts. As a result, users can visually grasp the progress of asset formation and the necessary actions.

[0283] Users can provide feedback on the displayed plan. For example, they can input opinions such as "I want to reduce risks more" from the terminal. Based on this feedback, the server recalculates the investment scenario and adjusts the plan.

[0284] Furthermore, the server monitors changes in the market and legal systems and updates the wealth management plan as needed. As a result, users can access a plan based on the latest information.

[0285] As a specific example, when a user sets a goal of "wanting to form assets of 30 million yen in 10 years," the server collects the necessary economic data from the Internet to meet this requirement and generates an optimal investment plan considering annual interest and risk levels. This plan is presented in the form of a graph showing the expected flow of funds accumulation and is displayed on the terminal.

[0286] An example of a prompt sentence is "My goal is to save 30 million yen in 10 years. Can you propose an optimal investment plan considering annual interest and risk?"

[0287] The flow of the specific process in Example 1 will be described using FIG. 11.

[0288] Step 1:

[0289] The user inputs their asset formation goals and desired conditions into the terminal. As a specific operation, the user inputs into a form for setting a goal such as "wanting to form assets of 30 million yen in 10 years." This input information is utilized in the processing of the next step.

[0290] Step 2:

[0291] The server collects necessary economic information from the internet based on the input information received from the user. Based on the input information, the server sends requests to financial data provider APIs to obtain the latest tax, interest rate, and investment product data. This collected dataset forms the basis for the next planning step.

[0292] Step 3:

[0293] The server generates an asset management plan based on collected economic information and the user's goals. In this step, the server uses a generating AI model to perform simulations based on historical market data. Specifically, it considers different investment scenarios and derives the optimal plan for the user's risk tolerance and goal achievement. The generated plan is output in a digital format and moves on to the next visualization step.

[0294] Step 4:

[0295] The server visualizes the generated asset management plan and sends it to the terminal. Based on the plan data, the server launches software to create graphs and charts, generating visual materials. This allows users to receive information about their asset building progress in an intuitively easy-to-understand format.

[0296] Step 5:

[0297] Users provide feedback on the displayed plan. For example, they might input a comment like, "I want to reduce the risks further." This feedback is sent to the server and used as input for the next plan adjustment step.

[0298] Step 6:

[0299] The server adjusts the asset management plan based on feedback received from the user. The server re-evaluates previously generated simulation results and recalculates an adjusted investment plan that reflects the user's new opinions. This updated plan is visualized again and sent to the terminal.

[0300] Step 7:

[0301] The server regularly monitors market trends and changes in legal systems. It uses APIs and web crawling technologies to retrieve the latest information and automatically updates asset management plans as needed. This real-time update information is notified to the user to ensure continued optimal wealth creation.

[0302] (Application Example 1)

[0303] 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."

[0304] In personal wealth building, there is a problem with the insufficient linkage between real-time management of expenses and income and asset planning that reflects that information. This is particularly evident with the spread of electronic payments, and the lack of means for users to quickly and accurately adjust their asset plans is a challenge.

[0305] 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.

[0306] In this invention, the server includes means for receiving user input information, means for collecting financial information, means for generating an asset formation plan, means for visualizing the plan, means for receiving feedback, means for adjusting the plan, means for monitoring data, and means for integrating economic transaction data and linking it with the plan. This allows for the immediate reflection of the user's spending and income data from electronic payments into the asset plan, enabling more appropriate asset management.

[0307] "User input information" refers to the individual financial goals and risk tolerances provided by the user to create an asset formation plan.

[0308] "Financial information" includes the latest data on tax systems, interest rates, and investment products related to asset formation.

[0309] "Asset formation plan" refers to the investment strategies and plans generated based on the user's financial goals.

[0310] "Visualization" means presenting the generated asset formation plan in a user-friendly format, such as graphs or charts.

[0311] "Feedback" refers to the act of the user returning opinions and wishes regarding the plan or proposal.

[0312] "Adjustment" is the process of re-evaluating and changing the asset formation plan based on the user's feedback and external information.

[0313] "Monitoring" means continuously observing market trends, changes in legal systems, etc., and collecting necessary information.

[0314] "Integrating economic transaction data and linking it with the plan" means capturing expenditure and income information in electronic payments in real time into the asset plan, enabling dynamic plan adjustment.

[0315] The embodiments for implementing this invention will be described.

[0316] The user uses a smartphone or other terminal to input their goals related to asset formation. This information is sent to the server. The server collects financial information via the Internet based on the received user input information. This financial information includes tax systems, interest rates, investment products, etc.

[0317] Based on the collected financial information, the server calculates multiple asset building scenarios tailored to the user's goals and generates an optimal plan. The plan is visualized using visual means such as graphs and charts and displayed on the user's device. Through this visualized information, the user can monitor their asset building progress and provide feedback.

[0318] The server dynamically adjusts the plan based on user feedback. During this process, the server monitors changes in the external environment and updates the plan based on real-time market trends and legal revisions. Furthermore, it integrates economic transaction data, reflecting daily expenses and income in the plan in real time, enabling more accurate adjustments to asset planning. These functionalities are achieved by utilizing electronic payment APIs and financial data APIs.

[0319] As a concrete example, consider a case where user A sets a goal of "saving 2 million yen within 5 years." The server analyzes the user's spending patterns from their electronic payment history and builds a plan to achieve the goal. The generating AI model can then suggest appropriate actions to the user using prompts such as, "Please suggest the latest tax information needed to improve my investment plan."

[0320] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0321] Step 1:

[0322] Users input their asset building goals via a device such as a smartphone. This input information includes target amounts for savings and investments, timeframes, and risk tolerance. The device receives this input information and transmits it to the server.

[0323] Step 2:

[0324] The server collects up-to-date financial information, such as tax laws, interest rates, and investment products, via the internet based on user input. This collection is performed in real time using a financial data API, and the acquired data forms the basis for generating asset plans. The input is user information, and the output is financial information.

[0325] Step 3:

[0326] The server uses collected financial information and user input to calculate different asset building scenarios and generate an optimal plan. This calculation includes multiple investment strategies, and a generative AI model is used to select the best plan. The input is financial information and user information, and the output is an asset building plan.

[0327] Step 4:

[0328] The server visualizes the generated asset building plan as graphs and charts and displays them on the terminal. This visualization allows the user to intuitively understand the progress and details of the plan. The input is the asset building plan, and the output is the visualized data.

[0329] Step 5:

[0330] Users can review the displayed plan and provide feedback. This feedback may include changes to risk tolerance or adjustments to the target amount. The device sends the feedback to the server.

[0331] Step 6:

[0332] The server dynamically adjusts the asset building plan based on user feedback. It also integrates economic transaction data to reflect the latest income and expenditure information. Inputs are feedback and economic transaction data, and output is the adjusted plan.

[0333] Step 7:

[0334] The server monitors market trends and changes in legal systems, and updates the plan as needed. This ensures that the plan always reflects the latest information. The input is monitoring data, and the output is the updated plan.

[0335] 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.

[0336] This invention is a system that combines an emotional engine with an asset formation system to understand the user's emotional state and provide a individually customized asset formation plan. Specific embodiments are described below.

[0337] First, the user enters their asset-building goals and aspirations into the terminal's interface. This information includes specific amounts, desired asset types, investment timeframe, and risk tolerance. The entered information is then sent to the server as initial data.

[0338] The server automatically collects relevant financial information from the internet based on the information entered by the user. At this stage, it utilizes public databases and financial institution APIs to obtain the latest data on tax laws, interest rates, and investment products. The collected information is also recorded in a database.

[0339] During the asset building plan generation stage, the server uses collected financial information to create asset building scenarios tailored to the user's goals. The plan includes different investment strategies evaluated through simulations, and the most suitable plan is selected.

[0340] The generated plan is visualized by the server and presented to the user via the terminal. The visualization methods used include line graphs showing the progress of the plan and bubble charts showing scenario analysis, allowing the user to intuitively grasp the overall picture of the plan.

[0341] The emotion engine, a key feature of this invention, is incorporated at the stage where user feedback on the plan is received. The server uses the emotion engine to analyze and recognize emotions from the user's voice or input text. This emotional information is used to further customize the asset building plan. For example, if the user is feeling anxious, responses such as presenting a lower-risk scenario are taken.

[0342] Furthermore, the server monitors changes in financial markets and regularly updates the asset building plan provided by the system. When the user's emotional state changes or new information becomes available, the plan is restructured and the user is notified at the appropriate time.

[0343] For example, if a user sets their goal to "maximize investment returns within five years" and the emotion engine detects "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy will be presented. In this way, the system provides a dynamic and personalized asset building plan that responds to the user's needs and emotions.

[0344] The following describes the processing flow.

[0345] Step 1:

[0346] Users input their wealth-building goals and aspirations into the device's interface. Specific inputs include target asset amount, timeframe, and investment risk tolerance.

[0347] Step 2:

[0348] The terminal sends user input information to the server. This information is used as initial system data and therefore needs to be transmitted accurately.

[0349] Step 3:

[0350] The server collects relevant financial information from the internet based on the goals and preferences received from the user. It primarily obtains the latest tax, interest rate, and investment product information from APIs of trusted financial institutions and databases of public institutions.

[0351] Step 4:

[0352] The server analyzes the collected data and generates an asset building plan to help the user achieve their goals. It simulates various investment scenarios and selects the plan with the optimal balance of risk and return. The user's risk tolerance is also taken into consideration during this process.

[0353] Step 5:

[0354] The server visualizes the generated asset building plan and converts the data into a format that can be displayed as graphs and charts. This visualization allows users to intuitively understand the overall picture and details of the plan.

[0355] Step 6:

[0356] The device presents the user with visualized plan data. Based on this, the user can review the plan and deepen their understanding.

[0357] Step 7:

[0358] The user reviews the plan and then provides voice or text input for emotion recognition by the emotion engine. It is expected that emotions such as joy and anxiety will be extracted from the input.

[0359] Step 8:

[0360] The server analyzes the user's emotions using an emotion engine and incorporates the results into the asset building plan. For example, if the user expresses anxiety, the plan may be adjusted to be more conservative.

[0361] Step 9:

[0362] The server monitors market changes and fluctuations in economic conditions, and updates the asset building plan based on the latest information it obtains. It also restructures the plan if the user's emotions change, and is configured to notify the user as needed.

[0363] (Example 2)

[0364] 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".

[0365] Traditional asset building systems often provide uniform asset building plans without considering the user's emotional state, which is problematic as it fails to adequately address individual needs. Furthermore, they struggle to respond immediately to changes in financial markets and lack the flexibility to propose the optimal asset building plan for each user.

[0366] 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.

[0367] In this invention, the server includes means for receiving user goal information, means for collecting data from a network, and means for recognizing the user's emotions using sentiment analysis and adjusting the asset building scenario. This makes it possible to provide a flexible and customized asset building plan that responds to the user's individual emotional state and market changes.

[0368] A "user" is an entity that uses the system to set asset building goals and provides feedback.

[0369] "Target information" refers to information entered by users, such as specific target amounts and timeframes for asset building, and risk tolerance.

[0370] "Data" refers to a collection of information, including laws, regulations, interest rates, and financial products, that is gathered through networks to support wealth building plans.

[0371] A "network" is a communication infrastructure for exchanging data, and includes wide-area communication lines such as the internet.

[0372] A "wealth building scenario" is a proposed structure of a wealth expansion plan generated based on the user's goal information and external data.

[0373] "Visual representation" refers to a method of making information intuitively understandable to users using computational diagrams, representational diagrams, and other visual aids.

[0374] "Response" refers to user feedback and comments on asset building scenarios.

[0375] "Emotion analysis" is a technology that analyzes a user's voice and text data to identify their emotional state.

[0376] "Market information" refers to a collection of information about trends in the external environment, such as fluctuations in financial markets and trading data.

[0377] "Monitoring" refers to the act of continuously checking changes in market information and evaluating the potential impact on users.

[0378] This invention is a system that utilizes user information to provide individually optimized asset building plans. This system is particularly characterized by its provision of dynamic plans that reflect the user's emotional state.

[0379] Users input their asset-building goals into the terminal's interface. These goals include specific target amounts, timeframes, and risk tolerance. The entered information is then sent to the server as initial data.

[0380] The server automatically collects relevant data via the network based on information entered by the user. This data includes legal and regulatory information, interest rates, and information on financial products. The server uses APIs and data schemas as protocols to efficiently retrieve information and store it in a database. Data analysis software is used in this process to enable high-speed data processing.

[0381] Based on the collected data, the server generates multiple asset building scenarios. Simulation software and numerical analysis tools are used for this generation. For example, it compares the profitability of different investment strategies to determine the strategy best suited to the user's risk tolerance. The generated scenarios are visualized using visualization tools as line graphs and bubble charts. This allows the scenarios to be presented visually to the user through their device, enabling intuitive understanding.

[0382] Next, the server uses an emotion analysis engine to identify the user's emotional state. It analyzes voice data and input text from the user to determine whether the emotion is "security," "anxiety," etc. Based on this emotional information, it further adjusts the asset building plan. For example, if the user indicates anxiety, a more conservative scenario will be included in the plan.

[0383] Furthermore, the server has the function of continuously monitoring market information and updating plans in response to changes in the external environment. This ensures that users always have an asset building plan based on the latest information.

[0384] For example, if a user sets a goal of "maximizing investment returns within 5 years," and the emotion analysis engine detects "security," the server will suggest a higher-risk investment strategy. Conversely, if "anxiety" is detected, a lower-risk strategy will be suggested. An example of a prompt would be, "If the user indicates security, please suggest an investment strategy with a high risk tolerance." This prompt instructs the generative AI model to generate plans based on emotion.

[0385] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0386] Step 1:

[0387] The user enters their asset-building goal information into the terminal interface. This includes the target amount, investment period, desired investment products, and risk tolerance. The entered information is sent to the server and used as initial data for the program. This information forms the basis for all subsequent processing steps.

[0388] Step 2:

[0389] The server collects data from the network based on the target information entered by the user. Specifically, it uses APIs to obtain the latest legal regulations, interest rates, and investment product information from public and financial institutions. This collected data is stored in a database and used as material for subsequent scenario generation. Real-time updated data analysis tools are used for data collection.

[0390] Step 3:

[0391] The server generates asset building scenarios based on collected data and user goal information. This process uses simulation software to perform numerical analysis on different investment strategies. The output consists of multiple investment scenarios, from which the most appropriate one is selected. The generated scenario is output as a detailed analysis, including the profitability and risk of the strategy.

[0392] Step 4:

[0393] The server visually represents the generated asset formation scenario. A graph generation tool is used for visualization, creating line graphs and bubble charts. The input for this process is the scenario data from step 3, and the output is visually organized information. The resulting visuals are presented to the user via a terminal, allowing the user to intuitively understand the information.

[0394] Step 5:

[0395] The server analyzes user feedback using an emotion analysis engine. It identifies emotional states from the user's voice and input text, generating emotional data such as "sense of security" and "anxiety." Based on this emotional information, the server adjusts the asset building scenario accordingly. The risk level of the scenario is dynamically changed according to the results of the emotional information analysis.

[0396] Step 6:

[0397] The server monitors fluctuations in financial markets and updates the asset building plan. New external information is acquired, and the plan is restructured, taking into account the user's sentiment data and market trends. In this process, visualized information based on feedback is generated again and notified to the user via the terminal. The user is able to always have a plan based on the latest information.

[0398] (Application Example 2)

[0399] 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."

[0400] In modern society, it is a challenging task for individual users to create appropriate asset building plans based on their emotions. Conventional systems fail to adequately provide asset building plans that take into account users' emotional states, and the anxieties and stresses users experience hinder the execution of these plans. Particularly in electronic payments, there is a need to optimize spending and risk in accordance with users' emotional states.

[0401] 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.

[0402] In this invention, the server includes means for receiving user input information, means for collecting financial information from a communication network based on the user input information, means for generating an asset building plan based on the collected financial information, means for visually representing the generated asset building plan, means for receiving the user's response to the visually represented asset building plan, and means for analyzing the user's emotional state, further individualizing the asset building plan based on the emotional state, and assisting the user in optimizing spending and risk. This makes it possible to provide an individualized asset building plan that reflects the user's emotional state.

[0403] "User input information" refers to data in which users specifically express their goals and aspirations for asset building.

[0404] "Financial information" refers to general data related to wealth creation, such as legal systems, interest rates, and investment products.

[0405] A "communication network" is a network that allows data to be transmitted bidirectionally, such as the internet.

[0406] A "wealth building plan" is a set of investment strategies and their implementation plan formulated to achieve a user's wealth building goals.

[0407] "Visual representation" refers to techniques that use graphs, charts, and other visual tools to make data and information easier to understand.

[0408] "User response" refers to the user's reaction and feedback to the generated plan.

[0409] "Emotional state" refers to a user's psychological condition and emotional tendencies, and is a factor that influences decision-making when executing a plan.

[0410] The system for implementing this invention consists of a server and a user terminal. First, the user's terminal transmits data about the user's asset building goals and desires to the server. This includes specific amounts, desired asset types, investment periods, and risk tolerance.

[0411] Based on the user's input, the server collects relevant financial information using public databases and communication networks such as financial institution APIs. This financial information includes legal systems, interest rates, and investment products. Subsequently, based on the collected financial information, it generates an asset building plan tailored to the user's goals. In this process, the server simulates various investment strategies and selects the optimal plan.

[0412] The asset building plan generated by the server is visually represented and presented to the user's terminal. The user can provide feedback on the visually represented plan. The server uses the user's responses to adjust the asset building plan. In this adjustment process, the user's emotional state is considered a crucial factor. Using an emotion engine, the server analyzes and recognizes the user's emotions from their voice and input text, and further customizes the plan according to that emotional state.

[0413] For example, if a user sets their goal to maximize investment returns within a limited timeframe, and the emotion engine detects a sense of "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy can be presented. This allows users to obtain the optimal asset building plan according to their emotions at any given time.

[0414] Furthermore, changes in financial markets are monitored by the server, and asset building plans are regularly updated based on the results. This ensures that the plan is always up-to-date, and is restructured when the user's emotional state changes or new information becomes available.

[0415] An example of a prompt to a generative AI model is, "Perform a sentiment analysis on the product the user is about to purchase, and provide the risks and benefits of purchasing this product." This prompt allows the AI ​​to appropriately assess the user's emotional state and provide personalized advice.

[0416] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0417] Step 1:

[0418] The user uses a terminal to input their asset building goals and aspirations. This input includes specific amounts, desired asset types, investment timeframe, and risk tolerance. This information is sent to the server as initial data.

[0419] Step 2:

[0420] The server collects financial information from public databases and financial institution APIs based on user input. This includes data on legal systems, interest rates, and investment products. At this stage, the input consists of the user's desired conditions, and the output is relevant financial information.

[0421] Step 3:

[0422] The server generates an asset building plan tailored to the user's goals based on the collected financial information. Here, the server simulates various investment strategies and selects the most suitable plan. The input is the financial information from step 2, and the output is the proposed plan. Data calculations include risk assessment and yield forecasting.

[0423] Step 4:

[0424] The generated plan is visually represented by the server and sent to the user terminal. Graphs and charts are used for visualization, with the generated plan information as input and the visualized information as output.

[0425] Step 5:

[0426] Users review the plan on their devices and provide feedback. This feedback is received by the server and used to adjust the plan. The input is the user's feedback, and the output is the adjusted plan.

[0427] Step 6:

[0428] The server uses an emotion engine to analyze the user's emotional state from their input and voice data. Input consists of feedback information and voice data, while output is the result of the emotion evaluation. The prompt text from the generative AI model is used here.

[0429] Step 7:

[0430] Based on the results of the emotional assessment, the asset building plan is personalized and adjusted to better suit the user's emotions. The input is the result of the emotional assessment, and the output is the final asset plan.

[0431] Step 8:

[0432] The server monitors changes in financial markets and regularly updates asset building plans based on new information. Input is the latest financial data, and output is the updated plan. This ensures the plan is always up-to-date.

[0433] 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.

[0434] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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.

[0435] 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.

[0436] [Third Embodiment]

[0437] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0438] 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.

[0439] 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).

[0440] 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.

[0441] 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.

[0442] 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).

[0443] 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.

[0444] 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.

[0445] 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.

[0446] 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.

[0447] 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.

[0448] 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".

[0449] This invention is a system for providing users with a means to easily create and implement asset formation plans. This system is mainly implemented with the following configuration.

[0450] First, the user enters their wishes and goals regarding wealth building into the terminal. Based on this, the server retrieves the necessary information from the internet. This information includes the latest data on tax laws, interest rates, and investment products. Based on the collected information, the server generates a wealth building plan to help the user achieve their goals. At this stage, an algorithm is used to consider different investment scenarios and select the optimal plan.

[0451] The generated plan is displayed visually in a way that users can intuitively understand. Specifically, the server creates graphs and charts based on the plan's content and provides them to the user via their device. This allows users to easily grasp the progress of their asset building and the actions that need to be taken.

[0452] Furthermore, when a user provides specific feedback on the displayed plan, the server adjusts the plan based on that feedback. For example, if a user wishes to lower their risk tolerance, the investment scenario is recalculated and the plan is modified to match that objective.

[0453] Furthermore, the system has a function to continuously update information in response to changes in the external environment. The server regularly monitors market trends and changes in legal systems, revises plans as needed, and delivers the latest information to users.

[0454] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will collect necessary economic data from the internet and generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented by a line graph showing the expected flow of funds and displayed on the terminal. In this way, the system functions as a powerful tool to support the user's asset building.

[0455] The following describes the processing flow.

[0456] Step 1:

[0457] Users input their asset building goals and aspirations into the terminal's interface. At this time, they can also specify concrete amounts, timeframes, and risk tolerance.

[0458] Step 2:

[0459] The terminal sends the information entered by the user to the server as initial data. This information includes the user's asset building goals.

[0460] Step 3:

[0461] The server automatically collects relevant financial information from the internet based on user input. Specifically, it uses public databases and financial institution APIs to obtain the latest information on tax laws, interest rates, and investment products.

[0462] Step 4:

[0463] The server analyzes the collected financial information and generates an optimal asset building plan to help the user achieve their goals. At this stage, simulations are performed using different investment strategies and risk scenarios to select the plan with the highest expected value.

[0464] Step 5:

[0465] The server visualizes the generated asset building plan in an easy-to-understand format. Specifically, it creates line graphs showing the progress of the plan and bubble charts showing the relationship between risk and return.

[0466] Step 6:

[0467] The terminal displays visualization data sent from the server, presenting the user with an overview of the plan. This allows the user to visually confirm the details of the plan.

[0468] Step 7:

[0469] Users review the presented asset building plan and provide feedback as needed. This feedback may include changes to risk tolerance or adjustments to investment amounts.

[0470] Step 8:

[0471] The server recalculates and adjusts the asset building plan based on user feedback. If necessary, it generates new investment scenarios, visualizes them again, and presents them to the user.

[0472] Step 9:

[0473] The server constantly monitors financial information and changes in economic trends, and updates plans based on the latest information it acquires. In the event of significant changes, users will be notified.

[0474] (Example 1)

[0475] 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."

[0476] For individuals to achieve their wealth-building goals, proper information gathering and planning are essential. However, this generally requires advanced knowledge and analytical skills, making it a difficult and time-consuming task for many. Furthermore, keeping up with rapidly changing market trends and legal systems is not easy. Therefore, there is a need to develop a system that provides individual investors with an intuitively usable wealth-building plan that always reflects the latest information.

[0477] 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.

[0478] In this invention, the server includes means for receiving user input information, means for collecting economic information from a communication network, and means for generating asset management plans. This makes it possible for users to easily formulate plans based on their own asset formation goals and to always execute optimal asset management based on the latest information, even without specialized knowledge.

[0479] A "user" is an individual or organization that uses the system to set asset building goals and create plans.

[0480] "Input information" refers to the data that users send to the system, including the requirements and preferences necessary to achieve their goals.

[0481] "Economic information" refers to external data on tax systems, interest rates, and investment products necessary for creating an asset formation plan.

[0482] A "wealth management plan" is a long-term investment strategy formulated based on economic information collected to help the user achieve their goals.

[0483] "Visualization" is the process of visually representing the generated asset management plan in a way that is easy for the user to understand.

[0484] "Opinions" refer to evaluations and requests made by users regarding the asset management plan presented, and these are reflected in adjustments to the plan.

[0485] "Monitoring" refers to the activity of a server continuously checking for changes in the market and legal systems, and updating asset management plans as needed.

[0486] This invention is a system for users to set asset formation goals and develop actionable plans. Specific embodiments are shown below.

[0487] First, the user enters their goals and aspirations regarding wealth creation into their device. The device used here is a common computing device such as a personal computer or smartphone.

[0488] Next, the server begins operating based on the user's input. The server collects necessary economic information from the internet via the communication network. This process utilizes APIs from financial data providers and web crawling technologies. Based on this collected information, the server performs data analysis to develop an investment plan. It conducts simulations based on historical market data and generates an optimal investment scenario that takes into account the user's risk tolerance.

[0489] The generated asset management plan is presented to the user in an easy-to-understand format. Specifically, the server visualizes the plan data and sends it to the terminal as graphs and charts. This allows the user to visually grasp the progress of their asset building and the actions that need to be taken.

[0490] Users can provide feedback on the displayed plan. For example, they can input comments such as "I want to reduce the risk further" from their device. Based on this feedback, the server recalculates the investment scenario and adjusts the plan.

[0491] Furthermore, the servers monitor changes in the market and legal systems, and update asset management plans as needed. This allows users to access plans based on the latest information.

[0492] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will gather the necessary economic data from the internet to generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented in graphs showing the expected flow of funds and displayed on the terminal.

[0493] An example of a prompt would be, "My goal is to save 30 million yen in 10 years. Can you suggest the best investment plan considering annual interest rates and risks?"

[0494] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0495] Step 1:

[0496] Users input their asset-building goals and desired conditions into the terminal. Specifically, users enter a goal into a form, such as "I want to accumulate 30 million yen in assets in 10 years." This input information is then used in the next step of processing.

[0497] Step 2:

[0498] The server collects necessary economic information from the internet based on the input information received from the user. Based on the input information, the server sends requests to financial data provider APIs to obtain the latest tax, interest rate, and investment product data. This collected dataset forms the basis for the next planning step.

[0499] Step 3:

[0500] The server generates an asset management plan based on collected economic information and the user's goals. In this step, the server uses a generating AI model to perform simulations based on historical market data. Specifically, it considers different investment scenarios and derives the optimal plan for the user's risk tolerance and goal achievement. The generated plan is output in a digital format and moves on to the next visualization step.

[0501] Step 4:

[0502] The server visualizes the generated asset management plan and sends it to the terminal. Based on the plan data, the server launches software to create graphs and charts, generating visual materials. This allows users to receive information about their asset building progress in an intuitively easy-to-understand format.

[0503] Step 5:

[0504] Users provide feedback on the displayed plan. For example, they might input a comment like, "I want to reduce the risks further." This feedback is sent to the server and used as input for the next plan adjustment step.

[0505] Step 6:

[0506] The server adjusts the asset management plan based on feedback received from the user. The server re-evaluates previously generated simulation results and recalculates an adjusted investment plan that reflects the user's new opinions. This updated plan is visualized again and sent to the terminal.

[0507] Step 7:

[0508] The server regularly monitors market trends and changes in legal systems. It uses APIs and web crawling technologies to retrieve the latest information and automatically updates asset management plans as needed. This real-time update information is notified to the user to ensure continued optimal wealth creation.

[0509] (Application Example 1)

[0510] 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."

[0511] In personal wealth building, there is a problem with the insufficient linkage between real-time management of expenses and income and asset planning that reflects that information. This is particularly evident with the spread of electronic payments, and the lack of means for users to quickly and accurately adjust their asset plans is a challenge.

[0512] 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.

[0513] In this invention, the server includes means for receiving user input information, means for collecting financial information, means for generating an asset formation plan, means for visualizing the plan, means for receiving feedback, means for adjusting the plan, means for monitoring data, and means for integrating economic transaction data and linking it with the plan. This allows for the immediate reflection of the user's spending and income data from electronic payments into the asset plan, enabling more appropriate asset management.

[0514] "User input information" refers to the individual financial goals and risk tolerance that users provide in order to create an asset building plan.

[0515] "Financial information" includes the latest data on tax systems, interest rates, and investment products related to wealth building.

[0516] A "wealth building plan" refers to an investment strategy or plan generated based on the user's financial goals.

[0517] "Visualization" means presenting the generated asset building plan in a format that is easy for the user to understand, such as graphs or charts.

[0518] "Feedback" refers to the act of users providing opinions and suggestions regarding plans and proposals.

[0519] "Adjustment" is the process of re-evaluating and modifying asset building plans based on user feedback and external information.

[0520] "Monitoring" refers to the continuous observation of market trends, changes in legal systems, and other factors, and the collection of necessary information.

[0521] "Integrating economic transaction data and linking it to planning" means incorporating expenditure and income information from electronic payments into asset planning in real time, enabling dynamic plan adjustments.

[0522] A description of embodiments for carrying out this invention will be given.

[0523] Users enter their personal wealth-building goals using a smartphone or other device. This information is sent to a server. Based on the user's input, the server collects financial information via the internet. This financial information includes tax laws, interest rates, and investment products.

[0524] Based on the collected financial information, the server calculates multiple asset building scenarios tailored to the user's goals and generates an optimal plan. The plan is visualized using visual means such as graphs and charts and displayed on the user's device. Through this visualized information, the user can monitor their asset building progress and provide feedback.

[0525] The server dynamically adjusts the plan based on user feedback. During this process, the server monitors changes in the external environment and updates the plan based on real-time market trends and legal revisions. Furthermore, it integrates economic transaction data, reflecting daily expenses and income in the plan in real time, enabling more accurate adjustments to asset planning. These functionalities are achieved by utilizing electronic payment APIs and financial data APIs.

[0526] As a concrete example, consider a case where user A sets a goal of "saving 2 million yen within 5 years." The server analyzes the user's spending patterns from their electronic payment history and builds a plan to achieve the goal. The generating AI model can then suggest appropriate actions to the user using prompts such as, "Please suggest the latest tax information needed to improve my investment plan."

[0527] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0528] Step 1:

[0529] Users input their asset building goals via a device such as a smartphone. This input information includes target amounts for savings and investments, timeframes, and risk tolerance. The device receives this input information and transmits it to the server.

[0530] Step 2:

[0531] The server collects up-to-date financial information, such as tax laws, interest rates, and investment products, via the internet based on user input. This collection is performed in real time using a financial data API, and the acquired data forms the basis for generating asset plans. The input is user information, and the output is financial information.

[0532] Step 3:

[0533] The server uses collected financial information and user input to calculate different asset building scenarios and generate an optimal plan. This calculation includes multiple investment strategies, and a generative AI model is used to select the best plan. The input is financial information and user information, and the output is an asset building plan.

[0534] Step 4:

[0535] The server visualizes the generated asset building plan as graphs and charts and displays them on the terminal. This visualization allows the user to intuitively understand the progress and details of the plan. The input is the asset building plan, and the output is the visualized data.

[0536] Step 5:

[0537] Users can review the displayed plan and provide feedback. This feedback may include changes to risk tolerance or adjustments to the target amount. The device sends the feedback to the server.

[0538] Step 6:

[0539] The server dynamically adjusts the asset building plan based on user feedback. It also integrates economic transaction data to reflect the latest income and expenditure information. Inputs are feedback and economic transaction data, and output is the adjusted plan.

[0540] Step 7:

[0541] The server monitors market trends and changes in legal systems, and updates the plan as needed. This ensures that the plan always reflects the latest information. The input is monitoring data, and the output is the updated plan.

[0542] 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.

[0543] This invention is a system that combines an emotional engine with an asset formation system to understand the user's emotional state and provide a individually customized asset formation plan. Specific embodiments are described below.

[0544] First, the user enters their asset-building goals and aspirations into the terminal's interface. This information includes specific amounts, desired asset types, investment timeframe, and risk tolerance. The entered information is then sent to the server as initial data.

[0545] The server automatically collects relevant financial information from the internet based on the information entered by the user. At this stage, it utilizes public databases and financial institution APIs to obtain the latest data on tax laws, interest rates, and investment products. The collected information is also recorded in a database.

[0546] During the asset building plan generation stage, the server uses collected financial information to create asset building scenarios tailored to the user's goals. The plan includes different investment strategies evaluated through simulations, and the most suitable plan is selected.

[0547] The generated plan is visualized by the server and presented to the user via the terminal. The visualization methods used include line graphs showing the progress of the plan and bubble charts showing scenario analysis, allowing the user to intuitively grasp the overall picture of the plan.

[0548] The emotion engine, a key feature of this invention, is incorporated at the stage where user feedback on the plan is received. The server uses the emotion engine to analyze and recognize emotions from the user's voice or input text. This emotional information is used to further customize the asset building plan. For example, if the user is feeling anxious, responses such as presenting a lower-risk scenario are taken.

[0549] Furthermore, the server monitors changes in financial markets and regularly updates the asset building plan provided by the system. When the user's emotional state changes or new information becomes available, the plan is restructured and the user is notified at the appropriate time.

[0550] For example, if a user sets their goal to "maximize investment returns within five years" and the emotion engine detects "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy will be presented. In this way, the system provides a dynamic and personalized asset building plan that responds to the user's needs and emotions.

[0551] The following describes the processing flow.

[0552] Step 1:

[0553] Users input their wealth-building goals and aspirations into the device's interface. Specific inputs include target asset amount, timeframe, and investment risk tolerance.

[0554] Step 2:

[0555] The terminal sends user input information to the server. This information is used as initial system data and therefore needs to be transmitted accurately.

[0556] Step 3:

[0557] The server collects relevant financial information from the internet based on the goals and preferences received from the user. It primarily obtains the latest tax, interest rate, and investment product information from APIs of trusted financial institutions and databases of public institutions.

[0558] Step 4:

[0559] The server analyzes the collected data and generates an asset building plan to help the user achieve their goals. It simulates various investment scenarios and selects the plan with the optimal balance of risk and return. The user's risk tolerance is also taken into consideration during this process.

[0560] Step 5:

[0561] The server visualizes the generated asset building plan and converts the data into a format that can be displayed as graphs and charts. This visualization allows users to intuitively understand the overall picture and details of the plan.

[0562] Step 6:

[0563] The device presents the user with visualized plan data. Based on this, the user can review the plan and deepen their understanding.

[0564] Step 7:

[0565] The user reviews the plan and then provides voice or text input for emotion recognition by the emotion engine. It is expected that emotions such as joy and anxiety will be extracted from the input.

[0566] Step 8:

[0567] The server analyzes the user's emotions using an emotion engine and incorporates the results into the asset building plan. For example, if the user expresses anxiety, the plan may be adjusted to be more conservative.

[0568] Step 9:

[0569] The server monitors market changes and fluctuations in economic conditions, and updates the asset building plan based on the latest information it obtains. It also restructures the plan if the user's emotions change, and is configured to notify the user as needed.

[0570] (Example 2)

[0571] 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."

[0572] Traditional asset building systems often provide uniform asset building plans without considering the user's emotional state, which is problematic as it fails to adequately address individual needs. Furthermore, they struggle to respond immediately to changes in financial markets and lack the flexibility to propose the optimal asset building plan for each user.

[0573] 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.

[0574] In this invention, the server includes means for receiving user goal information, means for collecting data from a network, and means for recognizing the user's emotions using sentiment analysis and adjusting the asset building scenario. This makes it possible to provide a flexible and customized asset building plan that responds to the user's individual emotional state and market changes.

[0575] A "user" is an entity that uses the system to set asset building goals and provides feedback.

[0576] "Target information" refers to information entered by users, such as specific target amounts and timeframes for asset building, and risk tolerance.

[0577] "Data" refers to a collection of information, including laws, regulations, interest rates, and financial products, that is gathered through networks to support wealth building plans.

[0578] A "network" is a communication infrastructure for exchanging data, and includes wide-area communication lines such as the internet.

[0579] A "wealth building scenario" is a proposed structure of a wealth expansion plan generated based on the user's goal information and external data.

[0580] "Visual representation" refers to a method of making information intuitively understandable to users using computational diagrams, representational diagrams, and other visual aids.

[0581] "Response" refers to user feedback and comments on asset building scenarios.

[0582] "Emotion analysis" is a technology that analyzes a user's voice and text data to identify their emotional state.

[0583] "Market information" refers to a collection of information about trends in the external environment, such as fluctuations in financial markets and trading data.

[0584] "Monitoring" refers to the act of continuously checking changes in market information and evaluating the potential impact on users.

[0585] This invention is a system that utilizes user information to provide individually optimized asset building plans. This system is particularly characterized by its provision of dynamic plans that reflect the user's emotional state.

[0586] Users input their asset-building goals into the terminal's interface. These goals include specific target amounts, timeframes, and risk tolerance. The entered information is then sent to the server as initial data.

[0587] The server automatically collects relevant data via the network based on information entered by the user. This data includes legal and regulatory information, interest rates, and information on financial products. The server uses APIs and data schemas as protocols to efficiently retrieve information and store it in a database. Data analysis software is used in this process to enable high-speed data processing.

[0588] Based on the collected data, the server generates multiple asset building scenarios. Simulation software and numerical analysis tools are used for this generation. For example, it compares the profitability of different investment strategies to determine the strategy best suited to the user's risk tolerance. The generated scenarios are visualized using visualization tools as line graphs and bubble charts. This allows the scenarios to be presented visually to the user through their device, enabling intuitive understanding.

[0589] Next, the server uses an emotion analysis engine to identify the user's emotional state. It analyzes voice data and input text from the user to determine whether the emotion is "security," "anxiety," etc. Based on this emotional information, it further adjusts the asset building plan. For example, if the user indicates anxiety, a more conservative scenario will be included in the plan.

[0590] Furthermore, the server has the function of continuously monitoring market information and updating plans in response to changes in the external environment. This ensures that users always have an asset building plan based on the latest information.

[0591] For example, if a user sets a goal of "maximizing investment returns within 5 years," and the emotion analysis engine detects "security," the server will suggest a higher-risk investment strategy. Conversely, if "anxiety" is detected, a lower-risk strategy will be suggested. An example of a prompt would be, "If the user indicates security, please suggest an investment strategy with a high risk tolerance." This prompt instructs the generative AI model to generate plans based on emotion.

[0592] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0593] Step 1:

[0594] The user enters their asset-building goal information into the terminal interface. This includes the target amount, investment period, desired investment products, and risk tolerance. The entered information is sent to the server and used as initial data for the program. This information forms the basis for all subsequent processing steps.

[0595] Step 2:

[0596] The server collects data from the network based on the target information entered by the user. Specifically, it uses APIs to obtain the latest legal regulations, interest rates, and investment product information from public and financial institutions. This collected data is stored in a database and used as material for subsequent scenario generation. Real-time updated data analysis tools are used for data collection.

[0597] Step 3:

[0598] The server generates asset building scenarios based on collected data and user goal information. This process uses simulation software to perform numerical analysis on different investment strategies. The output consists of multiple investment scenarios, from which the most appropriate one is selected. The generated scenario is output as a detailed analysis, including the profitability and risk of the strategy.

[0599] Step 4:

[0600] The server visually represents the generated asset formation scenario. A graph generation tool is used for visualization, creating line graphs and bubble charts. The input for this process is the scenario data from step 3, and the output is visually organized information. The resulting visuals are presented to the user via a terminal, allowing the user to intuitively understand the information.

[0601] Step 5:

[0602] The server analyzes user feedback using an emotion analysis engine. It identifies emotional states from the user's voice and input text, generating emotional data such as "sense of security" and "anxiety." Based on this emotional information, the server adjusts the asset building scenario accordingly. The risk level of the scenario is dynamically changed according to the results of the emotional information analysis.

[0603] Step 6:

[0604] The server monitors fluctuations in financial markets and updates the asset building plan. New external information is acquired, and the plan is restructured, taking into account the user's sentiment data and market trends. In this process, visualized information based on feedback is generated again and notified to the user via the terminal. The user is able to always have a plan based on the latest information.

[0605] (Application Example 2)

[0606] 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."

[0607] In modern society, it is a challenging task for individual users to create appropriate asset building plans based on their emotions. Conventional systems fail to adequately provide asset building plans that take into account users' emotional states, and the anxieties and stresses users experience hinder the execution of these plans. Particularly in electronic payments, there is a need to optimize spending and risk in accordance with users' emotional states.

[0608] 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.

[0609] In this invention, the server includes means for receiving user input information, means for collecting financial information from a communication network based on the user input information, means for generating an asset building plan based on the collected financial information, means for visually representing the generated asset building plan, means for receiving the user's response to the visually represented asset building plan, and means for analyzing the user's emotional state, further individualizing the asset building plan based on the emotional state, and assisting the user in optimizing spending and risk. This makes it possible to provide an individualized asset building plan that reflects the user's emotional state.

[0610] "User input information" refers to data in which users specifically express their goals and aspirations for asset building.

[0611] "Financial information" refers to general data related to wealth creation, such as legal systems, interest rates, and investment products.

[0612] A "communication network" is a network that allows data to be transmitted bidirectionally, such as the internet.

[0613] A "wealth building plan" is a set of investment strategies and their implementation plan formulated to achieve a user's wealth building goals.

[0614] "Visual representation" refers to techniques that use graphs, charts, and other visual tools to make data and information easier to understand.

[0615] "User response" refers to the user's reaction and feedback to the generated plan.

[0616] "Emotional state" refers to a user's psychological condition and emotional tendencies, and is a factor that influences decision-making when executing a plan.

[0617] The system for implementing this invention consists of a server and a user terminal. First, the user's terminal transmits data about the user's asset building goals and desires to the server. This includes specific amounts, desired asset types, investment periods, and risk tolerance.

[0618] Based on the user's input, the server collects relevant financial information using public databases and communication networks such as financial institution APIs. This financial information includes legal systems, interest rates, and investment products. Subsequently, based on the collected financial information, it generates an asset building plan tailored to the user's goals. In this process, the server simulates various investment strategies and selects the optimal plan.

[0619] The asset building plan generated by the server is visually represented and presented to the user's terminal. The user can provide feedback on the visually represented plan. The server uses the user's responses to adjust the asset building plan. In this adjustment process, the user's emotional state is considered a crucial factor. Using an emotion engine, the server analyzes and recognizes the user's emotions from their voice and input text, and further customizes the plan according to that emotional state.

[0620] For example, if a user sets their goal to maximize investment returns within a limited timeframe, and the emotion engine detects a sense of "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy can be presented. This allows users to obtain the optimal asset building plan according to their emotions at any given time.

[0621] Furthermore, changes in financial markets are monitored by the server, and asset building plans are regularly updated based on the results. This ensures that the plan is always up-to-date, and is restructured when the user's emotional state changes or new information becomes available.

[0622] An example of a prompt to a generative AI model is, "Perform a sentiment analysis on the product the user is about to purchase, and provide the risks and benefits of purchasing this product." This prompt allows the AI ​​to appropriately assess the user's emotional state and provide personalized advice.

[0623] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0624] Step 1:

[0625] The user uses a terminal to input their asset building goals and aspirations. This input includes specific amounts, desired asset types, investment timeframe, and risk tolerance. This information is sent to the server as initial data.

[0626] Step 2:

[0627] The server collects financial information from public databases and financial institution APIs based on user input. This includes data on legal systems, interest rates, and investment products. At this stage, the input consists of the user's desired conditions, and the output is relevant financial information.

[0628] Step 3:

[0629] The server generates an asset building plan tailored to the user's goals based on the collected financial information. Here, the server simulates various investment strategies and selects the most suitable plan. The input is the financial information from step 2, and the output is the proposed plan. Data calculations include risk assessment and yield forecasting.

[0630] Step 4:

[0631] The generated plan is visually represented by the server and sent to the user terminal. Graphs and charts are used for visualization, with the generated plan information as input and the visualized information as output.

[0632] Step 5:

[0633] Users review the plan on their devices and provide feedback. This feedback is received by the server and used to adjust the plan. The input is the user's feedback, and the output is the adjusted plan.

[0634] Step 6:

[0635] The server uses an emotion engine to analyze the user's emotional state from their input and voice data. Input consists of feedback information and voice data, while output is the result of the emotion evaluation. The prompt text from the generative AI model is used here.

[0636] Step 7:

[0637] Based on the results of the emotional assessment, the asset building plan is personalized and adjusted to better suit the user's emotions. The input is the result of the emotional assessment, and the output is the final asset plan.

[0638] Step 8:

[0639] The server monitors changes in financial markets and regularly updates asset building plans based on new information. Input is the latest financial data, and output is the updated plan. This ensures the plan is always up-to-date.

[0640] 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.

[0641] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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.

[0642] 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.

[0643] [Fourth Embodiment]

[0644] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0645] 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.

[0646] 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).

[0647] 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.

[0648] 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.

[0649] 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).

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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.

[0656] 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".

[0657] This invention is a system for providing users with a means to easily create and implement asset formation plans. This system is mainly implemented with the following configuration.

[0658] First, the user enters their wishes and goals regarding wealth building into the terminal. Based on this, the server retrieves the necessary information from the internet. This information includes the latest data on tax laws, interest rates, and investment products. Based on the collected information, the server generates a wealth building plan to help the user achieve their goals. At this stage, an algorithm is used to consider different investment scenarios and select the optimal plan.

[0659] The generated plan is displayed visually in a way that users can intuitively understand. Specifically, the server creates graphs and charts based on the plan's content and provides them to the user via their device. This allows users to easily grasp the progress of their asset building and the actions that need to be taken.

[0660] Furthermore, when a user provides specific feedback on the displayed plan, the server adjusts the plan based on that feedback. For example, if a user wishes to lower their risk tolerance, the investment scenario is recalculated and the plan is modified to match that objective.

[0661] Furthermore, the system has a function to continuously update information in response to changes in the external environment. The server regularly monitors market trends and changes in legal systems, revises plans as needed, and delivers the latest information to users.

[0662] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will collect necessary economic data from the internet and generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented by a line graph showing the expected flow of funds and displayed on the terminal. In this way, the system functions as a powerful tool to support the user's asset building.

[0663] The following describes the processing flow.

[0664] Step 1:

[0665] Users input their asset building goals and aspirations into the terminal's interface. At this time, they can also specify concrete amounts, timeframes, and risk tolerance.

[0666] Step 2:

[0667] The terminal sends the information entered by the user to the server as initial data. This information includes the user's asset building goals.

[0668] Step 3:

[0669] The server automatically collects relevant financial information from the internet based on user input. Specifically, it uses public databases and financial institution APIs to obtain the latest information on tax laws, interest rates, and investment products.

[0670] Step 4:

[0671] The server analyzes the collected financial information and generates an optimal asset building plan to help the user achieve their goals. At this stage, simulations are performed using different investment strategies and risk scenarios to select the plan with the highest expected value.

[0672] Step 5:

[0673] The server visualizes the generated asset building plan in an easy-to-understand format. Specifically, it creates line graphs showing the progress of the plan and bubble charts showing the relationship between risk and return.

[0674] Step 6:

[0675] The terminal displays visualization data sent from the server, presenting the user with an overview of the plan. This allows the user to visually confirm the details of the plan.

[0676] Step 7:

[0677] Users review the presented asset building plan and provide feedback as needed. This feedback may include changes to risk tolerance or adjustments to investment amounts.

[0678] Step 8:

[0679] The server recalculates and adjusts the asset building plan based on user feedback. If necessary, it generates new investment scenarios, visualizes them again, and presents them to the user.

[0680] Step 9:

[0681] The server constantly monitors financial information and changes in economic trends, and updates plans based on the latest information it acquires. In the event of significant changes, users will be notified.

[0682] (Example 1)

[0683] 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".

[0684] For individuals to achieve their wealth-building goals, proper information gathering and planning are essential. However, this generally requires advanced knowledge and analytical skills, making it a difficult and time-consuming task for many. Furthermore, keeping up with rapidly changing market trends and legal systems is not easy. Therefore, there is a need to develop a system that provides individual investors with an intuitively usable wealth-building plan that always reflects the latest information.

[0685] 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.

[0686] In this invention, the server includes means for receiving user input information, means for collecting economic information from a communication network, and means for generating asset management plans. This makes it possible for users to easily formulate plans based on their own asset formation goals and to always execute optimal asset management based on the latest information, even without specialized knowledge.

[0687] A "user" is an individual or organization that uses the system to set asset building goals and create plans.

[0688] "Input information" refers to the data that users send to the system, including the requirements and preferences necessary to achieve their goals.

[0689] "Economic information" refers to external data on tax systems, interest rates, and investment products necessary for creating an asset formation plan.

[0690] A "wealth management plan" is a long-term investment strategy formulated based on economic information collected to help the user achieve their goals.

[0691] "Visualization" is the process of visually representing the generated asset management plan in a way that is easy for the user to understand.

[0692] "Opinions" refer to evaluations and requests made by users regarding the asset management plan presented, and these are reflected in adjustments to the plan.

[0693] "Monitoring" refers to the activity of a server continuously checking for changes in the market and legal systems, and updating asset management plans as needed.

[0694] This invention is a system for users to set asset formation goals and develop actionable plans. Specific embodiments are shown below.

[0695] First, the user enters their goals and aspirations regarding wealth creation into their device. The device used here is a common computing device such as a personal computer or smartphone.

[0696] Next, the server begins operating based on the user's input. The server collects necessary economic information from the internet via the communication network. This process utilizes APIs from financial data providers and web crawling technologies. Based on this collected information, the server performs data analysis to develop an investment plan. It conducts simulations based on historical market data and generates an optimal investment scenario that takes into account the user's risk tolerance.

[0697] The generated asset management plan is presented to the user in an easy-to-understand format. Specifically, the server visualizes the plan data and sends it to the terminal as graphs and charts. This allows the user to visually grasp the progress of their asset building and the actions that need to be taken.

[0698] Users can provide feedback on the displayed plan. For example, they can input comments such as "I want to reduce the risk further" from their device. Based on this feedback, the server recalculates the investment scenario and adjusts the plan.

[0699] Furthermore, the servers monitor changes in the market and legal systems, and update asset management plans as needed. This allows users to access plans based on the latest information.

[0700] For example, if a user sets a goal of "accumulating 30 million yen in assets in 10 years," the server will gather the necessary economic data from the internet to generate an optimal investment plan that takes into account annual interest rates and risk levels. This plan is represented in graphs showing the expected flow of funds and displayed on the terminal.

[0701] An example of a prompt would be, "My goal is to save 30 million yen in 10 years. Can you suggest the best investment plan considering annual interest rates and risks?"

[0702] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0703] Step 1:

[0704] Users input their asset-building goals and desired conditions into the terminal. Specifically, users enter a goal into a form, such as "I want to accumulate 30 million yen in assets in 10 years." This input information is then used in the next step of processing.

[0705] Step 2:

[0706] The server collects necessary economic information from the internet based on the input information received from the user. Based on the input information, the server sends requests to financial data provider APIs to obtain the latest tax, interest rate, and investment product data. This collected dataset forms the basis for the next planning step.

[0707] Step 3:

[0708] The server generates an asset management plan based on collected economic information and the user's goals. In this step, the server uses a generating AI model to perform simulations based on historical market data. Specifically, it considers different investment scenarios and derives the optimal plan for the user's risk tolerance and goal achievement. The generated plan is output in a digital format and moves on to the next visualization step.

[0709] Step 4:

[0710] The server visualizes the generated asset management plan and sends it to the terminal. Based on the plan data, the server launches software to create graphs and charts, generating visual materials. This allows users to receive information about their asset building progress in an intuitively easy-to-understand format.

[0711] Step 5:

[0712] Users provide feedback on the displayed plan. For example, they might input a comment like, "I want to reduce the risks further." This feedback is sent to the server and used as input for the next plan adjustment step.

[0713] Step 6:

[0714] The server adjusts the asset management plan based on feedback received from the user. The server re-evaluates previously generated simulation results and recalculates an adjusted investment plan that reflects the user's new opinions. This updated plan is visualized again and sent to the terminal.

[0715] Step 7:

[0716] The server regularly monitors market trends and changes in legal systems. It uses APIs and web crawling technologies to retrieve the latest information and automatically updates asset management plans as needed. This real-time update information is notified to the user to ensure continued optimal wealth creation.

[0717] (Application Example 1)

[0718] 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".

[0719] In personal wealth building, there is a problem with the insufficient linkage between real-time management of expenses and income and asset planning that reflects that information. This is particularly evident with the spread of electronic payments, and the lack of means for users to quickly and accurately adjust their asset plans is a challenge.

[0720] 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.

[0721] In this invention, the server includes means for receiving user input information, means for collecting financial information, means for generating an asset formation plan, means for visualizing the plan, means for receiving feedback, means for adjusting the plan, means for monitoring data, and means for integrating economic transaction data and linking it with the plan. This allows for the immediate reflection of the user's spending and income data from electronic payments into the asset plan, enabling more appropriate asset management.

[0722] "User input information" refers to the individual financial goals and risk tolerance that users provide in order to create an asset building plan.

[0723] "Financial information" includes the latest data on tax systems, interest rates, and investment products related to wealth building.

[0724] A "wealth building plan" refers to an investment strategy or plan generated based on the user's financial goals.

[0725] "Visualization" means presenting the generated asset building plan in a format that is easy for the user to understand, such as graphs or charts.

[0726] "Feedback" refers to the act of users providing opinions and suggestions regarding plans and proposals.

[0727] "Adjustment" is the process of re-evaluating and modifying asset building plans based on user feedback and external information.

[0728] "Monitoring" refers to the continuous observation of market trends, changes in legal systems, and other factors, and the collection of necessary information.

[0729] "Integrating economic transaction data and linking it to planning" means incorporating expenditure and income information from electronic payments into asset planning in real time, enabling dynamic plan adjustments.

[0730] A description of embodiments for carrying out this invention will be given.

[0731] Users enter their personal wealth-building goals using a smartphone or other device. This information is sent to a server. Based on the user's input, the server collects financial information via the internet. This financial information includes tax laws, interest rates, and investment products.

[0732] Based on the collected financial information, the server calculates multiple asset building scenarios tailored to the user's goals and generates an optimal plan. The plan is visualized using visual means such as graphs and charts and displayed on the user's device. Through this visualized information, the user can monitor their asset building progress and provide feedback.

[0733] The server dynamically adjusts the plan based on user feedback. During this process, the server monitors changes in the external environment and updates the plan based on real-time market trends and legal revisions. Furthermore, it integrates economic transaction data, reflecting daily expenses and income in the plan in real time, enabling more accurate adjustments to asset planning. These functionalities are achieved by utilizing electronic payment APIs and financial data APIs.

[0734] As a concrete example, consider a case where user A sets a goal of "saving 2 million yen within 5 years." The server analyzes the user's spending patterns from their electronic payment history and builds a plan to achieve the goal. The generating AI model can then suggest appropriate actions to the user using prompts such as, "Please suggest the latest tax information needed to improve my investment plan."

[0735] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0736] Step 1:

[0737] Users input their asset building goals via a device such as a smartphone. This input information includes target amounts for savings and investments, timeframes, and risk tolerance. The device receives this input information and transmits it to the server.

[0738] Step 2:

[0739] The server collects up-to-date financial information, such as tax laws, interest rates, and investment products, via the internet based on user input. This collection is performed in real time using a financial data API, and the acquired data forms the basis for generating asset plans. The input is user information, and the output is financial information.

[0740] Step 3:

[0741] The server uses collected financial information and user input to calculate different asset building scenarios and generate an optimal plan. This calculation includes multiple investment strategies, and a generative AI model is used to select the best plan. The input is financial information and user information, and the output is an asset building plan.

[0742] Step 4:

[0743] The server visualizes the generated asset building plan as graphs and charts and displays them on the terminal. This visualization allows the user to intuitively understand the progress and details of the plan. The input is the asset building plan, and the output is the visualized data.

[0744] Step 5:

[0745] Users can review the displayed plan and provide feedback. This feedback may include changes to risk tolerance or adjustments to the target amount. The device sends the feedback to the server.

[0746] Step 6:

[0747] The server dynamically adjusts the asset building plan based on user feedback. It also integrates economic transaction data to reflect the latest income and expenditure information. Inputs are feedback and economic transaction data, and output is the adjusted plan.

[0748] Step 7:

[0749] The server monitors market trends and changes in legal systems, and updates the plan as needed. This ensures that the plan always reflects the latest information. The input is monitoring data, and the output is the updated plan.

[0750] 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.

[0751] This invention is a system that combines an emotional engine with an asset formation system to understand the user's emotional state and provide a individually customized asset formation plan. Specific embodiments are described below.

[0752] First, the user enters their asset-building goals and aspirations into the terminal's interface. This information includes specific amounts, desired asset types, investment timeframe, and risk tolerance. The entered information is then sent to the server as initial data.

[0753] The server automatically collects relevant financial information from the internet based on the information entered by the user. At this stage, it utilizes public databases and financial institution APIs to obtain the latest data on tax laws, interest rates, and investment products. The collected information is also recorded in a database.

[0754] During the asset building plan generation stage, the server uses collected financial information to create asset building scenarios tailored to the user's goals. The plan includes different investment strategies evaluated through simulations, and the most suitable plan is selected.

[0755] The generated plan is visualized by the server and presented to the user via the terminal. The visualization methods used include line graphs showing the progress of the plan and bubble charts showing scenario analysis, allowing the user to intuitively grasp the overall picture of the plan.

[0756] The emotion engine, a key feature of this invention, is incorporated at the stage where user feedback on the plan is received. The server uses the emotion engine to analyze and recognize emotions from the user's voice or input text. This emotional information is used to further customize the asset building plan. For example, if the user is feeling anxious, responses such as presenting a lower-risk scenario are taken.

[0757] Furthermore, the server monitors changes in financial markets and regularly updates the asset building plan provided by the system. When the user's emotional state changes or new information becomes available, the plan is restructured and the user is notified at the appropriate time.

[0758] For example, if a user sets their goal to "maximize investment returns within five years" and the emotion engine detects "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy will be presented. In this way, the system provides a dynamic and personalized asset building plan that responds to the user's needs and emotions.

[0759] The following describes the processing flow.

[0760] Step 1:

[0761] Users input their wealth-building goals and aspirations into the device's interface. Specific inputs include target asset amount, timeframe, and investment risk tolerance.

[0762] Step 2:

[0763] The terminal sends user input information to the server. This information is used as initial system data and therefore needs to be transmitted accurately.

[0764] Step 3:

[0765] The server collects relevant financial information from the internet based on the goals and preferences received from the user. It primarily obtains the latest tax, interest rate, and investment product information from APIs of trusted financial institutions and databases of public institutions.

[0766] Step 4:

[0767] The server analyzes the collected data and generates an asset building plan to help the user achieve their goals. It simulates various investment scenarios and selects the plan with the optimal balance of risk and return. The user's risk tolerance is also taken into consideration during this process.

[0768] Step 5:

[0769] The server visualizes the generated asset building plan and converts the data into a format that can be displayed as graphs and charts. This visualization allows users to intuitively understand the overall picture and details of the plan.

[0770] Step 6:

[0771] The device presents the user with visualized plan data. Based on this, the user can review the plan and deepen their understanding.

[0772] Step 7:

[0773] The user reviews the plan and then provides voice or text input for emotion recognition by the emotion engine. It is expected that emotions such as joy and anxiety will be extracted from the input.

[0774] Step 8:

[0775] The server analyzes the user's emotions using an emotion engine and incorporates the results into the asset building plan. For example, if the user expresses anxiety, the plan may be adjusted to be more conservative.

[0776] Step 9:

[0777] The server monitors market changes and fluctuations in economic conditions, and updates the asset building plan based on the latest information it obtains. It also restructures the plan if the user's emotions change, and is configured to notify the user as needed.

[0778] (Example 2)

[0779] 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".

[0780] Traditional asset building systems often provide uniform asset building plans without considering the user's emotional state, which is problematic as it fails to adequately address individual needs. Furthermore, they struggle to respond immediately to changes in financial markets and lack the flexibility to propose the optimal asset building plan for each user.

[0781] 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.

[0782] In this invention, the server includes means for receiving user goal information, means for collecting data from a network, and means for recognizing the user's emotions using sentiment analysis and adjusting the asset building scenario. This makes it possible to provide a flexible and customized asset building plan that responds to the user's individual emotional state and market changes.

[0783] A "user" is an entity that uses the system to set asset building goals and provides feedback.

[0784] "Target information" refers to information entered by users, such as specific target amounts and timeframes for asset building, and risk tolerance.

[0785] "Data" refers to a collection of information, including laws, regulations, interest rates, and financial products, that is gathered through networks to support wealth building plans.

[0786] A "network" is a communication infrastructure for exchanging data, and includes wide-area communication lines such as the internet.

[0787] A "wealth building scenario" is a proposed structure of a wealth expansion plan generated based on the user's goal information and external data.

[0788] "Visual representation" refers to a method of making information intuitively understandable to users using computational diagrams, representational diagrams, and other visual aids.

[0789] "Response" refers to user feedback and comments on asset building scenarios.

[0790] "Emotion analysis" is a technology that analyzes a user's voice and text data to identify their emotional state.

[0791] "Market information" refers to a collection of information about trends in the external environment, such as fluctuations in financial markets and trading data.

[0792] "Monitoring" refers to the act of continuously checking changes in market information and evaluating the potential impact on users.

[0793] This invention is a system that utilizes user information to provide individually optimized asset building plans. This system is particularly characterized by its provision of dynamic plans that reflect the user's emotional state.

[0794] Users input their asset-building goals into the terminal's interface. These goals include specific target amounts, timeframes, and risk tolerance. The entered information is then sent to the server as initial data.

[0795] The server automatically collects relevant data via the network based on information entered by the user. This data includes legal and regulatory information, interest rates, and information on financial products. The server uses APIs and data schemas as protocols to efficiently retrieve information and store it in a database. Data analysis software is used in this process to enable high-speed data processing.

[0796] Based on the collected data, the server generates multiple asset building scenarios. Simulation software and numerical analysis tools are used for this generation. For example, it compares the profitability of different investment strategies to determine the strategy best suited to the user's risk tolerance. The generated scenarios are visualized using visualization tools as line graphs and bubble charts. This allows the scenarios to be presented visually to the user through their device, enabling intuitive understanding.

[0797] Next, the server uses an emotion analysis engine to identify the user's emotional state. It analyzes voice data and input text from the user to determine whether the emotion is "security," "anxiety," etc. Based on this emotional information, it further adjusts the asset building plan. For example, if the user indicates anxiety, a more conservative scenario will be included in the plan.

[0798] Furthermore, the server has the function of continuously monitoring market information and updating plans in response to changes in the external environment. This ensures that users always have an asset building plan based on the latest information.

[0799] For example, if a user sets a goal of "maximizing investment returns within 5 years," and the emotion analysis engine detects "security," the server will suggest a higher-risk investment strategy. Conversely, if "anxiety" is detected, a lower-risk strategy will be suggested. An example of a prompt would be, "If the user indicates security, please suggest an investment strategy with a high risk tolerance." This prompt instructs the generative AI model to generate plans based on emotion.

[0800] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0801] Step 1:

[0802] The user enters their asset-building goal information into the terminal interface. This includes the target amount, investment period, desired investment products, and risk tolerance. The entered information is sent to the server and used as initial data for the program. This information forms the basis for all subsequent processing steps.

[0803] Step 2:

[0804] The server collects data from the network based on the target information entered by the user. Specifically, it uses APIs to obtain the latest legal regulations, interest rates, and investment product information from public and financial institutions. This collected data is stored in a database and used as material for subsequent scenario generation. Real-time updated data analysis tools are used for data collection.

[0805] Step 3:

[0806] The server generates asset building scenarios based on collected data and user goal information. This process uses simulation software to perform numerical analysis on different investment strategies. The output consists of multiple investment scenarios, from which the most appropriate one is selected. The generated scenario is output as a detailed analysis, including the profitability and risk of the strategy.

[0807] Step 4:

[0808] The server visually represents the generated asset formation scenario. A graph generation tool is used for visualization, creating line graphs and bubble charts. The input for this process is the scenario data from step 3, and the output is visually organized information. The resulting visuals are presented to the user via a terminal, allowing the user to intuitively understand the information.

[0809] Step 5:

[0810] The server analyzes user feedback using an emotion analysis engine. It identifies emotional states from the user's voice and input text, generating emotional data such as "sense of security" and "anxiety." Based on this emotional information, the server adjusts the asset building scenario accordingly. The risk level of the scenario is dynamically changed according to the results of the emotional information analysis.

[0811] Step 6:

[0812] The server monitors fluctuations in financial markets and updates the asset building plan. New external information is acquired, and the plan is restructured, taking into account the user's sentiment data and market trends. In this process, visualized information based on feedback is generated again and notified to the user via the terminal. The user is able to always have a plan based on the latest information.

[0813] (Application Example 2)

[0814] 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".

[0815] In modern society, it is a challenging task for individual users to create appropriate asset building plans based on their emotions. Conventional systems fail to adequately provide asset building plans that take into account users' emotional states, and the anxieties and stresses users experience hinder the execution of these plans. Particularly in electronic payments, there is a need to optimize spending and risk in accordance with users' emotional states.

[0816] 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.

[0817] In this invention, the server includes means for receiving user input information, means for collecting financial information from a communication network based on the user input information, means for generating an asset building plan based on the collected financial information, means for visually representing the generated asset building plan, means for receiving the user's response to the visually represented asset building plan, and means for analyzing the user's emotional state, further individualizing the asset building plan based on the emotional state, and assisting the user in optimizing spending and risk. This makes it possible to provide an individualized asset building plan that reflects the user's emotional state.

[0818] "User input information" refers to data in which users specifically express their goals and aspirations for asset building.

[0819] "Financial information" refers to general data related to wealth creation, such as legal systems, interest rates, and investment products.

[0820] A "communication network" is a network that allows data to be transmitted bidirectionally, such as the internet.

[0821] A "wealth building plan" is a set of investment strategies and their implementation plan formulated to achieve a user's wealth building goals.

[0822] "Visual representation" refers to techniques that use graphs, charts, and other visual tools to make data and information easier to understand.

[0823] "User response" refers to the user's reaction and feedback to the generated plan.

[0824] "Emotional state" refers to a user's psychological condition and emotional tendencies, and is a factor that influences decision-making when executing a plan.

[0825] The system for implementing this invention consists of a server and a user terminal. First, the user's terminal transmits data about the user's asset building goals and desires to the server. This includes specific amounts, desired asset types, investment periods, and risk tolerance.

[0826] Based on the user's input, the server collects relevant financial information using public databases and communication networks such as financial institution APIs. This financial information includes legal systems, interest rates, and investment products. Subsequently, based on the collected financial information, it generates an asset building plan tailored to the user's goals. In this process, the server simulates various investment strategies and selects the optimal plan.

[0827] The asset building plan generated by the server is visually represented and presented to the user's terminal. The user can provide feedback on the visually represented plan. The server uses the user's responses to adjust the asset building plan. In this adjustment process, the user's emotional state is considered a crucial factor. Using an emotion engine, the server analyzes and recognizes the user's emotions from their voice and input text, and further customizes the plan according to that emotional state.

[0828] For example, if a user sets their goal to maximize investment returns within a limited timeframe, and the emotion engine detects a sense of "security," the server will recommend a more aggressive investment strategy. Conversely, if "anxiety" is detected, a more conservative investment strategy can be presented. This allows users to obtain the optimal asset building plan according to their emotions at any given time.

[0829] Furthermore, changes in financial markets are monitored by the server, and asset building plans are regularly updated based on the results. This ensures that the plan is always up-to-date, and is restructured when the user's emotional state changes or new information becomes available.

[0830] An example of a prompt to a generative AI model is, "Perform a sentiment analysis on the product the user is about to purchase, and provide the risks and benefits of purchasing this product." This prompt allows the AI ​​to appropriately assess the user's emotional state and provide personalized advice.

[0831] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0832] Step 1:

[0833] The user uses a terminal to input their asset building goals and aspirations. This input includes specific amounts, desired asset types, investment timeframe, and risk tolerance. This information is sent to the server as initial data.

[0834] Step 2:

[0835] The server collects financial information from public databases and financial institution APIs based on user input. This includes data on legal systems, interest rates, and investment products. At this stage, the input consists of the user's desired conditions, and the output is relevant financial information.

[0836] Step 3:

[0837] The server generates an asset building plan tailored to the user's goals based on the collected financial information. Here, the server simulates various investment strategies and selects the most suitable plan. The input is the financial information from step 2, and the output is the proposed plan. Data calculations include risk assessment and yield forecasting.

[0838] Step 4:

[0839] The generated plan is visually represented by the server and sent to the user terminal. Graphs and charts are used for visualization, with the generated plan information as input and the visualized information as output.

[0840] Step 5:

[0841] Users review the plan on their devices and provide feedback. This feedback is received by the server and used to adjust the plan. The input is the user's feedback, and the output is the adjusted plan.

[0842] Step 6:

[0843] The server uses an emotion engine to analyze the user's emotional state from their input and voice data. Input consists of feedback information and voice data, while output is the result of the emotion evaluation. The prompt text from the generative AI model is used here.

[0844] Step 7:

[0845] Based on the results of the emotional assessment, the asset building plan is personalized and adjusted to better suit the user's emotions. The input is the result of the emotional assessment, and the output is the final asset plan.

[0846] Step 8:

[0847] The server monitors changes in financial markets and regularly updates asset building plans based on new information. Input is the latest financial data, and output is the updated plan. This ensures the plan is always up-to-date.

[0848] 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.

[0849] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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.

[0850] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0851] 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.

[0852] 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.

[0853] 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.

[0854] 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.

[0855] 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.

[0856] 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."

[0857] 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.

[0858] 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.

[0859] 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.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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.

[0869] The following is further disclosed regarding the embodiments described above.

[0870] (Claim 1)

[0871] A means for receiving user input information,

[0872] A means for collecting financial information from the internet based on the user's input information,

[0873] A means for generating an asset formation plan based on the aforementioned collected financial information,

[0874] A means for visualizing the generated asset formation plan,

[0875] A means for receiving user feedback on the visualized asset formation plan,

[0876] Means for adjusting the asset formation plan in response to user feedback,

[0877] A means for monitoring changes in external financial information and updating the asset formation plan,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, wherein the financial information includes information on tax systems, interest rates, and investment products.

[0881] (Claim 3)

[0882] The system according to claim 1, wherein a graph or chart is used to visualize the asset formation plan.

[0883] "Example 1"

[0884] (Claim 1)

[0885] A means for receiving user input information,

[0886] A means for collecting economic information from a communication network based on the user's input information,

[0887] A means for generating a plan for asset management based on the aforementioned collected economic information,

[0888] A means for visualizing the generated asset management plan,

[0889] A means of receiving user feedback on the visualized asset management plan,

[0890] Means for adjusting the asset management plan in accordance with the opinions of the user,

[0891] Means for monitoring changes in external economic information and updating the asset management plan,

[0892] A system that includes this.

[0893] (Claim 2)

[0894] The system according to claim 1, wherein the economic information includes information on tax systems, interest rates, and investment products.

[0895] (Claim 3)

[0896] The system according to claim 1, wherein a chart or graph is used to visualize the asset management plan.

[0897] "Application Example 1"

[0898] (Claim 1)

[0899] A means for receiving user input information,

[0900] A means for collecting financial information from the internet based on the user's input information,

[0901] A means for generating an asset formation plan based on the aforementioned collected financial information,

[0902] A means for visualizing the generated asset formation plan,

[0903] A means for receiving user feedback on the visualized asset formation plan,

[0904] Means for adjusting the asset formation plan in response to user feedback,

[0905] A means for monitoring changes in external financial information and updating the asset formation plan,

[0906] A means for integrating economic transaction data and linking it in real time with the asset formation plan,

[0907] A system that includes this.

[0908] (Claim 2)

[0909] The system according to claim 1, wherein the financial information includes information on tax systems, interest rates, and investment products.

[0910] (Claim 3)

[0911] The system according to claim 1, wherein a graph or chart is used to visualize the asset formation plan.

[0912] "Example 2 of combining an emotion engine"

[0913] (Claim 1)

[0914] A means of receiving user goal information,

[0915] A means for collecting data from the network based on the aforementioned user's target information,

[0916] A means for generating asset formation scenarios based on the aforementioned collected data,

[0917] A means for visually displaying the generated asset formation scenario,

[0918] Means for receiving user responses to the asset formation scenario displayed above,

[0919] A means for recognizing the user's emotions using emotion analysis and adjusting the asset formation scenario according to the user's emotions,

[0920] A means for monitoring changes in external market information and updating the asset formation scenario,

[0921] A system that includes this.

[0922] (Claim 2)

[0923] The system according to claim 1, wherein the data includes legal and regulatory information, interest rates, and financial product information.

[0924] (Claim 3)

[0925] The system according to claim 1, wherein a calculation diagram or representation diagram is used to visualize the asset formation scenario.

[0926] "Application example 2 when combining with an emotional engine"

[0927] (Claim 1)

[0928] A means for receiving user input information,

[0929] A means for collecting financial information from a communication network based on the user's input information,

[0930] A means for generating an asset formation plan based on the aforementioned collected financial information,

[0931] A means for visually representing the generated asset formation plan,

[0932] Means for receiving the user's response to the visually represented asset formation plan,

[0933] Means for adjusting the asset formation plan in response to the user's response,

[0934] Means for monitoring changes in external financial information and updating the asset formation plan,

[0935] A means to analyze the emotional state of a user, to further personalize asset building plans based on said emotional state, and to help users optimize their spending and risk,

[0936] A system that includes this.

[0937] (Claim 2)

[0938] The system according to claim 1, wherein the financial information includes information on legal systems, interest rates, and investment products.

[0939] (Claim 3)

[0940] The system according to claim 1, wherein diagrams and charts are used for the visual representation of the asset formation plan. [Explanation of Symbols]

[0941] 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 means for receiving user input information, A means for collecting financial information from the internet based on the user's input information, A means for generating an asset formation plan based on the aforementioned collected financial information, A means for visualizing the generated asset formation plan, A means for receiving user feedback on the visualized asset formation plan, Means for adjusting the asset formation plan in response to user feedback, A means for monitoring changes in external financial information and updating the asset formation plan, A means for integrating economic transaction data and linking it in real time with the asset formation plan, A system that includes this.

2. The system according to claim 1, wherein the financial information includes information on tax systems, interest rates, and investment products.

3. The system according to claim 1, wherein a graph or chart is used to visualize the asset formation plan.

Images