system

Abstract

Provide a system. 【Solution means】 Means for collecting, encrypting, and securely storing the user's financial data, Means for automatically generating an asset management plan based on the input economic goals, Means for monitoring the user's expenses in real time and warning of anomalies, Means for analyzing market data and making appropriate investment and savings proposals, Means for proposing a review of insurance based on the user's asset information, Means for providing financial education content, Means for notifying in real time when an abnormal expense is detected using a smart device, A system including the above.

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, the method including 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 as a 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] Many individuals have problems in financial management, and there is a current situation where it is difficult to achieve appropriate asset management and economic goals. In addition to this, there is a lack of grasp of daily expenses and effective risk management, resulting in unnecessary economic losses and uneasiness. Furthermore, the lack of self-improvement due to the lack of financial knowledge is also a factor hindering long-term asset formation. It is required to solve these problems.

Means for Solving the Problems

[0005] This invention provides a system that securely collects and stores users' financial data and automatically generates asset management plans based on individual economic goals. This allows users to monitor their spending in real time and receive warnings for anomalies. Furthermore, it offers investment and savings suggestions based on market data and proposes insurance reviews based on asset information. It also aims to improve users' financial literacy through the provision of financial education content. This comprehensive system effectively solves these challenges.

[0006] "User financial data" refers to all information about an individual's income, expenses, assets, and liabilities.

[0007] "Encryption" is a technology that enhances security by transforming data using a specific algorithm to prevent unauthorized access to information.

[0008] A "financial plan" includes a plan for asset management, investment, and savings necessary to achieve the user's financial goals.

[0009] "Real-time monitoring" refers to a method of observing or monitoring data immediately without any time delay.

[0010] "Market data" refers to all information related to financial markets, and typically includes stock prices, interest rates, and economic indicators.

[0011] "Investment and savings suggestions" refer to the act of recommending specific investment or savings methods to improve the user's long-term financial interests.

[0012] "Insurance review" is the process of reassessing whether the current insurance policy is appropriate for the user's current and future risks.

[0013] "Financial education content" refers to informational materials that provide users with financial knowledge and promote skill improvement and self-development. [Brief explanation of the drawing]

[0014] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It 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] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It 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. <于 [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It 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] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

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

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

[0019] In the following embodiments, the labeled storage 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 household financial management system that allows users to efficiently and securely manage their own financial data, and further automates the creation of optimal financial plans and asset management based on that data. The system is configured as follows:

[0036] First, the user enters their income, expenses, assets, and liabilities information via a terminal. This information is immediately transmitted to the server and stored securely in an encrypted state. Based on this data, the server understands the user's current situation and initiates operations to achieve specific financial goals.

[0037] The user then sets their financial goals. This goal setting is easily done through the UI (user interface), and they can enter specific goals such as "I want to buy a new car in three years." The device then sends this information to the server.

[0038] The server automatically generates an asset management plan based on the user's financial data and set goals. This plan shows the monthly savings amount and other necessary financial actions the user needs to take to achieve their planned goals.

[0039] Furthermore, the server monitors user spending in real time. The terminal issues alerts if spending exceeds the set budget or if any anomalies are detected. Users can check these alerts sent from the terminal at any time and review their spending as needed.

[0040] Furthermore, the server analyzes market data and provides investment and savings suggestions tailored to the user. This allows users to achieve efficient asset management at an appropriate risk level. For example, it may suggest long-term, systematic investment with reduced risk.

[0041] In addition, the server can re-evaluate the user's asset information and suggest insurance review options. Users can then better manage their risks by following these suggestions.

[0042] Finally, to improve financial literacy, the server selects financial education content according to the user's interests and skill level and delivers it to the device, providing an environment where users can learn independently.

[0043] Thus, the system of the present invention goes beyond mere financial data management and provides a comprehensive household management solution that supports users in achieving their long-term economic goals.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user uses a terminal to input individual pieces of information regarding income, expenses, assets, and liabilities. The terminal then formats this information and sends it to the server.

[0047] Step 2:

[0048] The server stores the received user's financial data in an encrypted format in its database. It also verifies the data's integrity and checks for any anomalies.

[0049] Step 3:

[0050] Users set their personal financial goals on their devices. For example, they might enter a specific goal such as, "I want to save 1 million yen in one year."

[0051] Step 4:

[0052] The device sends the configured target data to the server. Based on that target, the server analyzes the user's current financial situation and generates an optimal asset management plan.

[0053] Step 5:

[0054] The server returns the generated asset management plan to the terminal and presents it to the user. The plan includes monthly savings targets and recommended investment plans.

[0055] Step 6:

[0056] The device tracks the user's daily spending in real time and sends that data to a server. If the budget is exceeded or unusual spending occurs, the device displays a warning to the user.

[0057] Step 7:

[0058] The server continuously collects and analyzes market data to provide users with the latest investment and savings plans. The terminal notifies the user of the analysis results and displays the plan details.

[0059] Step 8:

[0060] The server determines whether an insurance review is necessary based on the user's asset information and makes suggestions accordingly. The terminal displays the suggestions to the user and provides information to aid understanding.

[0061] Step 9:

[0062] The server selects financial education content based on the user's interests and current level of understanding. It then delivers this content to the user via their device, providing them with learning opportunities.

[0063] In this way, the entire system works together at each step to support the user's financial management.

[0064] (Example 1)

[0065] 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."

[0066] In modern times, it is crucial for individuals to efficiently and safely manage their financial situation and develop optimal asset management plans based on that management. However, manual data entry and goal setting are time-consuming, and making appropriate investment and savings decisions is difficult. This invention aims to provide a means to solve these problems.

[0067] 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.

[0068] In this invention, the server includes means for collecting, encrypting, and securely storing the user's financial information; means for automatically generating an asset management plan based on input goals; and means for improving the asset management plan using a generated AI model. This enables the user to securely manage their financial situation and automatically plan efficient asset management.

[0069] A "user" refers to an individual or organization that uses a financial management system, and is the entity that inputs financial data and sets goals.

[0070] A "server" refers to a computer system that receives data from users, securely stores and manages it, and plays a central role in executing various processes.

[0071] "Economic information" is a general term for financial information held by users, such as income, expenses, assets, and liabilities.

[0072] In information technology, "encryption" refers to the process of securely converting data so that its content cannot be deciphered by a third party.

[0073] An "asset management plan" refers to a plan designed to provide the optimal savings and investment strategy based on the user's goals.

[0074] A "generative AI model" is a model that uses artificial intelligence technology to generate an optimal asset management plan based on the input data.

[0075] "Investment and accumulation proposals" refer to specific suggestions on how to manage assets based on the user's financial situation and market data.

[0076] "Financial education content" refers to educational content provided to users to deepen their knowledge of asset management and investment.

[0077] A description of embodiments for carrying out the present invention will be provided.

[0078] System Configuration

[0079] This system allows users to input their own financial information into a terminal, and based on that information, it provides an appropriate asset management plan. The server is responsible for data collection, storage, and analysis, and automatically generates the asset management plan using a generative AI model.

[0080] Hardware and software

[0081] Users utilize devices such as personal computers and smartphones. Dedicated application software runs on these devices to assist users in inputting economic information. The server consists of computers with high processing power, and secure protocols are used to encrypt stored data. The generative AI model is implemented on a software application running within the server.

[0082] Data processing and calculations

[0083] The server stores economic information entered by users in a structured data format and performs analysis of income, expenses, assets, and liabilities based on this data. The analyzed data is used to generate asset management plans to help users achieve their goals, and this is supported by a generative AI model.

[0084] Specific example

[0085] For example, if a user sets a financial goal of "buying a new car in three years," this goal is entered through the application on their device. The server receives this information and uses a generative AI model to generate and present an asset management plan, including an optimal savings plan and investment strategy. To achieve this process, the prompt given to the AI ​​model is, "Please suggest an investment portfolio suitable for the user's goal of buying a new car in three years." This specific plan serves as an important guide for the user to efficiently control their financial situation.

[0086] This allows users to clarify their financial goals and manage their assets systematically. The system utilizes advanced analytical techniques and generative AI models to enhance financial support for users.

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

[0088] Step 1:

[0089] Users input information about their income, expenses, assets, and liabilities using a terminal. This input data undergoes basic formatting checks on the terminal before being sent to the server. The economic information, as input, is transmitted in a structured data format and received as output on the server.

[0090] Step 2:

[0091] The server encrypts the received economic information and securely stores it in a database. The AES-256 encryption algorithm is used to protect the data. The input to this process is economic information from the user, and the output is recorded as encrypted data.

[0092] Step 3:

[0093] The server analyzes stored economic information and performs data processing to evaluate the user's financial situation. Based on statistical analysis, it checks income and expenditure patterns and the balance of assets and liabilities. In this process, the input is encrypted information in the database, and the output is a report of the analyzed financial situation.

[0094] Step 4:

[0095] Users set specific financial goals through their devices. For example, they might input a goal like "I want to buy a new car in three years." This goal is sent to the server and registered as input. Based on this information, the server uses a generated AI model to formulate an asset management plan.

[0096] Step 5:

[0097] The server runs a generation AI model to create an optimal asset management plan based on the user's financial information and goals. This uses the prompt "Please suggest an investment portfolio suitable for the user's goal of purchasing a new car in three years." The input is the user's financial information and goals, and the output is a detailed asset management plan including monthly savings plans and recommended investment strategies.

[0098] Step 6:

[0099] The server sends the generated asset management plan to the user's terminal and displays it on the terminal's UI. The output is provided as visual feedback to the user, allowing for further manipulation and adjustment of each item in the plan.

[0100] Step 7:

[0101] The server continues to monitor the user's spending patterns in real time and issues warnings for unusual or unplanned spending. If the budget is exceeded, a notification is sent to the device. The input to this process is the user's latest spending data, and the output is a warning message displayed on the device.

[0102] (Application Example 1)

[0103] 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."

[0104] Modern consumers need to manage diverse financial information and make sound financial decisions based on it, but they lack the means to do so efficiently and safely. Furthermore, there is a lack of tools for real-time spending management and creating appropriate asset management plans for future financial goals. This situation is an obstacle to consumers achieving financial freedom.

[0105] 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.

[0106] This invention includes a server that collects, encrypts, and securely stores the user's financial data; a server that automatically generates an asset management plan based on the user's financial goals; and a server that uses a smart device to notify the user in real time when unusual spending is detected. This enables consumers to manage their financial information safely and efficiently, monitor their spending in real time, and develop appropriate asset management plans.

[0107] "Financial data" refers to information about a user's income, expenses, assets, and liabilities, and is the data on which economic decisions are made.

[0108] "Encryption" is a method of securely transforming information using special algorithms and techniques to protect it from unauthorized access.

[0109] "Economic goals" refer to specific financial outcomes or targets that users wish to achieve, such as saving money or making large purchases.

[0110] An "asset management plan" refers to a plan or strategy for asset management and investment aimed at achieving a user's financial goals.

[0111] "Real-time monitoring" refers to the process of immediately observing and analyzing ongoing data and situations.

[0112] "Market data" refers to information about financial markets, such as prices, trends, and economic indicators, which are used as the basis for investment and economic decisions.

[0113] A "smart device" refers to a portable electronic device equipped with communication and computer functions, and generally includes smartphones and wearable devices.

[0114] "Real-time notification when abnormal spending is detected" is a feature that immediately provides information to the user when deviations from normal spending patterns are detected.

[0115] The system that implements this application example is provided as an application installed on the user's smart device, such as a smartphone. Through the application, the user inputs their financial data and sends it to the server using a secure encryption method. The server operates in a cloud environment, and databases such as MongoDB or Firebase are used.

[0116] The server receives this data and uses a generative AI model to automatically generate an asset management plan based on economic goals. Furthermore, it monitors spending through real-time data monitoring and immediately sends an alert to the user's smartphone if spending exceeds normal levels. The alert serves as a notification when an anomaly is detected, helping the user prevent wasteful spending.

[0117] The software used includes Python and R libraries for data analysis, and AES encryption technology for encryption. This ensures the security of the information and the accuracy of the analysis.

[0118] Furthermore, the server analyzes market data and provides users with appropriate investment recommendations. This is done using an advanced data analytics platform on the cloud, providing users with guidance for long-term asset management with reduced risk.

[0119] As a concrete example, suppose a user planning a short family trip during the holidays sets this goal in the app. The server monitors shopping and travel expenses that deviate from the user's usual spending patterns and prompts the user to review their spending as needed. This allows the user to proceed with their plan while avoiding unnecessary expenses.

[0120] An example of a prompt using a generative AI model is, "How can I save 2.5 million yen in three years and buy a new car?" In this way, the generative AI model generates specific advice to help the user achieve their specific financial goals.

[0121] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0122] Step 1:

[0123] The user launches an application on their smart device and enters their financial data. This data includes income, daily expenses, assets, and liability information. This data is immediately encrypted using AES by the device. The encrypted data is then sent to the server via a secure communication protocol.

[0124] Step 2:

[0125] The server decrypts the received encrypted data and securely stores it in a database. A database such as MongoDB is used to store data in a structured format. The server also uses a generative AI model to analyze user prompts (e.g., "How to save 2.5 million yen in 3 years") and generate an asset management plan to achieve the goal. The output includes monthly savings plans and investment recommendations.

[0126] Step 3:

[0127] The server monitors user spending in real time. It analyzes purchase history and spending data transmitted from smart devices, and if it determines that there is a deviation from normal spending patterns, it is confirmed by an anomaly detection algorithm. Information on detected anomaly spending is notified to the device as an alert.

[0128] Step 4:

[0129] The server analyzes market data and provides investment and savings recommendations tailored to the user's risk management needs. This analysis utilizes data analysis libraries in Python and R, outputting strategic suggestions based on risk profiles derived from past market trends and economic indicators.

[0130] Step 5:

[0131] Users review investment and savings suggestions provided from their terminal and adjust their asset management plan as needed. They can also provide prompts to receive further advice from the server. The output includes specific goal achievement scenarios and improvement plans for asset management.

[0132] 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.

[0133] This invention is a household financial management system that recognizes users' emotions and utilizes them in financial planning and asset management. This system manages financial data while also understanding users' emotions, and optimizes various suggestions based on that understanding.

[0134] First, the user enters their financial data via a terminal. This includes information on income, expenses, assets, and liabilities. The terminal sends the entered data to a server, which securely encrypts and stores the received data.

[0135] Next, users can set financial goals and budgets using the interface provided on their devices during their daily lives. These settings are immediately transmitted to the server for analysis.

[0136] An emotion engine is running to understand the user's feelings. The device infers emotions by drawing hints from the user's input data and actions on the interface. This emotion data is sent to the server in real time.

[0137] The server uses the user's financial and emotional data to generate personalized investment plans. For example, if a user is feeling stressed, the server may suggest a low-risk investment plan to provide reassurance.

[0138] Furthermore, it monitors users' spending behavior in real time and provides emotionally-driven warnings and suggestions. If budget overruns are predicted, it recommends actions that will help users reduce costs.

[0139] Market data analysis will also be performed in conjunction with an emotion engine. This will allow the server to generate investment and savings plans tailored to the user's current mental state and recommend them through the device.

[0140] In insurance reviews, the server provides suggestions that take into account the user's emotional information, supporting appropriate risk management.

[0141] Based on analysis by an emotion engine, the server delivers advice and content to the user to help reduce stress. The device then delivers this to the user, aiming to maintain not only a healthy financial state but also mental well-being.

[0142] Thus, the system of the present invention supports comprehensive household management that links financial management and emotion recognition, as well as the optimization of the user's life balance.

[0143] The following describes the processing flow.

[0144] Step 1:

[0145] The user uses a device to input financial data such as income, expenses, assets, and liabilities. The device sends this data to a server, which encrypts and securely stores the data.

[0146] Step 2:

[0147] Users set individual financial goals and budgets on their devices. For example, they might enter a goal such as "Save 500,000 yen in one year." The device then transmits these settings to the server.

[0148] Step 3:

[0149] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and behavioral patterns resulting from their interface interactions.

[0150] Step 4:

[0151] The server integrates emotional and financial data sent from the terminal to automatically generate the most suitable asset management plan for the user. For example, if the user is feeling anxious, it will suggest a low-risk savings plan.

[0152] Step 5:

[0153] The server sends the user's monthly savings and spending plan to their device based on the generated plan. The device then displays this information visually to the user, highlighting the gap between their current situation and the plan.

[0154] Step 6:

[0155] The device tracks the user's daily spending in real time and reports that data to the server. If spending that exceeds the budget is predicted, the device warns the user and suggests specific countermeasures.

[0156] Step 7:

[0157] The server collects market data and makes appropriate investment and savings suggestions tailored to the user's sentiment. The terminal receives these suggestions and clearly displays the risk-return relationship to the user.

[0158] Step 8:

[0159] Based on the user's sentiment analysis, the server suggests a review of their insurance. This presents an optimal risk management plan that provides emotional reassurance.

[0160] Step 9:

[0161] The server selects and delivers stress-reducing advice and relaxation-promoting content based on the user's emotional and financial information, through the terminal.

[0162] This series of steps allows the entire system to work together to provide support tailored to the user's financial situation and emotions.

[0163] (Example 2)

[0164] 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".

[0165] Traditional household financial management systems can only offer suggestions based on financial information, making it difficult to provide optimal asset management and spending control that takes into account the user's emotions and psychological state. This results in a challenge in providing effective support that addresses situations where users feel stressed or when their emotions change.

[0166] 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.

[0167] In this invention, the server includes means for recognizing the user's emotional state and integrating and analyzing emotional data and financial information, means for generating individual asset management plans, and means for providing content for relaxation and stress reduction based on the user's emotions. This enables flexible and appropriate financial management and support according to the user's emotional state.

[0168] "User financial information" refers to the collective economic data owned by a user, including income, expenses, assets, and liabilities.

[0169] "Encryption" is a technology that enhances information security by converting data into a format that cannot be understood by third parties.

[0170] A "financial plan" is a detailed plan for asset management, investment, and savings, based on the user's goals.

[0171] Real-time tracking means instantly monitoring current actions and situations and updating the data accordingly.

[0172] "Market information" refers to trends and data related to financial markets, including information on stocks, foreign exchange, and interest rates.

[0173] A "personalized asset management plan" is a customized investment and asset management proposal tailored to the user's individual circumstances, goals, and emotions.

[0174] "Emotional state" refers to the psychological situation and emotions experienced by the user, including the degree of stress and relaxation.

[0175] "Content" refers to data such as text, audio, and video that provides users with information, entertainment, and education.

[0176] This invention is a comprehensive household financial management system that manages users' financial information and provides asset management plans that take their emotional state into consideration. Users input monthly financial information such as income, expenses, assets, and liabilities using devices such as smartphones or personal computers. The device transmits this information to a server, which stores it securely using advanced encryption technology.

[0177] An emotion engine is built into the device, inferring emotions from the user's interface interactions. For example, input speed and click patterns are analyzed. The inferred emotion data is sent to a server in real time and integrated with financial information. The server uses a generative AI model to create an asset management plan that is suitable for the user's financial and emotional state. This model develops a financial strategy that prioritizes the user's peace of mind, such as suggesting low-risk investments based on the user's feelings.

[0178] For example, when a user sets a goal such as "I want to achieve my savings goal for next month's trip," the server provides advice on how to reduce related expenses. Also, if a user is feeling stressed, the server provides online yoga and meditation content via the device to help maintain mental and physical health.

[0179] An example of a prompt message would be: "Understand the user's emotional state and combine it with financial information to propose the optimal investment plan. If the user is feeling stressed, consider a low-risk investment plan; if they are feeling positive, consider a more aggressive investment plan."

[0180] The system implemented in this way provides comprehensive support for the user's financial situation and utilizes emotional data to optimize their lifestyle balance.

[0181] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0182] Step 1:

[0183] The user uses a terminal to input financial information regarding income, expenses, assets, and liabilities. The terminal sends this information as input data to the server. Specifically, the terminal receives the user's input, converts it to a digital format, and transmits it to the server over the network. The output is encrypted financial information stored on the server.

[0184] Step 2:

[0185] The server encrypts the received financial information using advanced encryption technology (e.g., AES-256). This ensures the confidentiality of the data and allows for secure storage. The input is raw data, and the output is securely stored encrypted data. Specifically, the process involves encrypting the data and securely storing it in the database.

[0186] Step 3:

[0187] The user sets financial targets and budgets through the terminal interface. The terminal sends these settings as input data to the server. The input is user configuration data, and the output is the configuration information incorporated into the latest financial plan on the server. The specific operation involves the immediate transfer and processing of the configuration data.

[0188] Step 4:

[0189] The device performs analysis to infer emotional data from the user's interface operations and input. Here, the input is the user's interaction data, and the output is emotional information inferred in real time. The emotional engine operates, meticulously analyzing input speed and operation patterns.

[0190] Step 5:

[0191] The server integrates and analyzes the user's financial data and inferred sentiment data. Using a generative AI model, it generates an optimal investment plan. The input is an integrated dataset, and the output is an investment plan optimized for the user. This specific operation includes the processes of data integration analysis and plan generation.

[0192] Step 6:

[0193] The server monitors users' spending in real time and generates alerts if anomalies are detected. The input is spending data, and the output is an alert message. The goal is to analyze spending trends and immediately notify users if any warning signs are detected.

[0194] Step 7:

[0195] The server analyzes market information and provides investment and savings suggestions that take into account the user's emotional state. Inputs are market data and emotional data, and output is a suggested plan. The specific operation involves using a generative AI model to integrate market information with emotional data and generate suggestions.

[0196] Step 8:

[0197] The server generates content for relaxation and stress reduction based on the user's emotional state and delivers it to the user via the terminal. The input is emotional data, and the output is content. Specifically, it is a mechanism that selects appropriate content according to the user's emotional state and provides it to the user.

[0198] (Application Example 2)

[0199] 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".

[0200] In modern society, users are required to make optimal financial decisions while considering complex financial data and their own emotional state. However, spending behavior is easily influenced by emotions, and selecting appropriate investment and savings strategies is difficult, often leading to anxiety and stress for users. These factors then become obstacles to maintaining a healthy financial state. This invention aims to optimize the user's economic and emotional balance by providing a financial management support system that takes these emotional factors into account.

[0201] 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.

[0202] In this invention, the server includes means for collecting the user's financial data and securely storing it through information processing, means for automatically generating a financial plan based on the entered goals, and means for inferring the user's emotions using emotion recognition technology and providing advice according to their spending. This allows the user to always be aware of their financial situation and make flexible financial decisions based on their emotions.

[0203] A "user" is an individual or organization that uses a financial management system to achieve their own financial goals.

[0204] "Economic data" refers to data that includes financial information such as income, expenses, assets, and liabilities.

[0205] "Information processing" is the process of analyzing and organizing collected data and taking necessary protective measures.

[0206] "Emotion recognition technology" is a technology that infers a user's emotional state from their input data and behavioral patterns.

[0207] A "financial plan" is a financial strategy that takes into account profitability, risks, and other factors based on the user's economic goals.

[0208] A "server" is an information technology infrastructure that receives and processes data from users and provides necessary information and services.

[0209] "Advice" refers to guidance and suggestions provided in accordance with the user's economic activities and emotional state.

[0210] The system of this invention is designed to integrate and manage a user's economic data and emotions, and to provide appropriate advice. This system mainly consists of the user's terminal, a server, and an emotion recognition engine.

[0211] Users input their financial data using devices such as smartphones and personal computers. This data includes income, expenses, assets, and liabilities. Upon receiving this information, the device encrypts the data and sends it to the server. Standard encryption technologies such as AES-256 are used to protect the information.

[0212] The server securely stores the received data and prepares it for subsequent processing. Cloud-based data processing platforms such as AWS® Lambda and Azure® Functions are used for this purpose. Based on the user's financial data, the server automatically generates a financial plan. This plan includes risk analysis, investment strategies, and insurance review proposals.

[0213] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state. This engine utilizes machine learning libraries such as TENSORFLOW® and PyTorch to infer emotions based on the user's input data and daily interactions. When the user is experiencing stress or anxiety, low-risk investment and savings strategies are suggested.

[0214] For example, if a user is feeling down due to bad weather, the system will suggest ways to save money on their budget for the day. Also, if planned spending is necessary on a particular day, the system will use emotional data to suggest adjusting the timing and type of spending.

[0215] An example of a prompt for a generative AI model might be: "How can I use the emotion recognition engine to determine if a user's stress level is high and then display cost-saving advice based on that?" This prompt clarifies how each component of the system works together and guides developers to more accurately execute application examples.

[0216] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0217] Step 1:

[0218] The user inputs economic data using a terminal. This data includes income, expenses, assets, and liabilities. The terminal combines this data and securely encrypts it using AES-256 encryption technology. After encrypting the input data, it is sent to the server, which then becomes the input for the next process.

[0219] Step 2:

[0220] The server decrypts the received encrypted data and stores it in a database. Based on the information stored in the database, the server uses a machine learning algorithm (e.g., TensorFlow) to automatically generate a financial plan for the user. This involves analyzing the user's financial situation and providing a financial plan that includes optimal investment and savings strategies as output.

[0221] Step 3:

[0222] The emotion recognition engine analyzes interactions and data sent from the device in response to a user request to infer the user's emotional state. The engine utilizes TensorFlow to process the input data and obtain inferred emotion information. The inference result is sent to the server and becomes input for the next step.

[0223] Step 4:

[0224] The server integrates the user's emotional and economic data to generate personalized advice. For example, if the user's emotions indicate stress, the server will create low-risk investment or savings plans and provide advice to alleviate their anxiety.

[0225] Step 5:

[0226] The user's device receives advice from the server and displays it to the user. At this time, the device renders the information in a format that is easy for the user to understand, providing specific suggestions and warnings. For example, a message such as "Let's try to stay within budget today" might be displayed.

[0227] Step 6:

[0228] Based on the advice provided, users adjust their economic activities. The user's actions and feedback are then fed back into the system as input for the next processing, leading to more personalized suggestions.

[0229] 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.

[0230] 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.

[0231] 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.

[0232] [Second Embodiment]

[0233] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0234] 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.

[0235] 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).

[0236] 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.

[0237] 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.

[0238] 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).

[0239] 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.

[0240] 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.

[0241] 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.

[0242] 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.

[0243] 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.

[0244] 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".

[0245] This invention is a household financial management system that allows users to efficiently and securely manage their own financial data, and further automates the creation of optimal financial plans and asset management based on that data. The system is configured as follows:

[0246] First, the user enters their income, expenses, assets, and liabilities information via a terminal. This information is immediately transmitted to the server and stored securely in an encrypted state. Based on this data, the server understands the user's current situation and initiates operations to achieve specific financial goals.

[0247] The user then sets their financial goals. This goal setting is easily done through the UI (user interface), and they can enter specific goals such as "I want to buy a new car in three years." The device then sends this information to the server.

[0248] The server automatically generates an asset management plan based on the user's financial data and set goals. This plan shows the monthly savings amount and other necessary financial actions the user needs to take to achieve their planned goals.

[0249] Furthermore, the server monitors user spending in real time. The terminal issues alerts if spending exceeds the set budget or if any anomalies are detected. Users can check these alerts sent from the terminal at any time and review their spending as needed.

[0250] Furthermore, the server analyzes market data and provides investment and savings suggestions tailored to the user. This allows users to achieve efficient asset management at an appropriate risk level. For example, it may suggest long-term, systematic investment with reduced risk.

[0251] In addition, the server can re-evaluate the user's asset information and suggest insurance review options. Users can then better manage their risks by following these suggestions.

[0252] Finally, to improve financial literacy, the server selects financial education content according to the user's interests and skill level and delivers it to the device, providing an environment where users can learn independently.

[0253] Thus, the system of the present invention goes beyond mere financial data management and provides a comprehensive household management solution that supports users in achieving their long-term economic goals.

[0254] The following describes the processing flow.

[0255] Step 1:

[0256] The user uses a terminal to input individual pieces of information regarding income, expenses, assets, and liabilities. The terminal then formats this information and sends it to the server.

[0257] Step 2:

[0258] The server stores the received user's financial data in an encrypted format in its database. It also verifies the data's integrity and checks for any anomalies.

[0259] Step 3:

[0260] Users set their personal financial goals on their devices. For example, they might enter a specific goal such as, "I want to save 1 million yen in one year."

[0261] Step 4:

[0262] The device sends the configured target data to the server. Based on that target, the server analyzes the user's current financial situation and generates an optimal asset management plan.

[0263] Step 5:

[0264] The server returns the generated asset management plan to the terminal and presents it to the user. The plan includes monthly savings targets and recommended investment plans.

[0265] Step 6:

[0266] The device tracks the user's daily spending in real time and sends that data to a server. If the budget is exceeded or unusual spending occurs, the device displays a warning to the user.

[0267] Step 7:

[0268] The server continuously collects and analyzes market data to provide users with the latest investment and savings plans. The terminal notifies the user of the analysis results and displays the plan details.

[0269] Step 8:

[0270] The server determines whether an insurance review is necessary based on the user's asset information and makes suggestions accordingly. The terminal displays these suggestions to the user and provides information to aid understanding.

[0271] Step 9:

[0272] The server selects financial education content based on the user's interests and current level of understanding. It then delivers this content to the user via their device, providing them with learning opportunities.

[0273] In this way, the entire system works together at each step to support the user's financial management.

[0274] (Example 1)

[0275] 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."

[0276] In modern times, it is crucial for individuals to efficiently and safely manage their financial situation and develop optimal asset management plans based on that information. However, manual data entry and goal setting are time-consuming, and making appropriate investment and savings decisions is difficult. This invention aims to provide a means to solve these problems.

[0277] 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.

[0278] In this invention, the server includes means for collecting the user's economic information, encrypting it, and securely storing it, means for automatically generating an asset management plan based on the input target, and means for improving the asset management plan using a generated AI model. As a result, the user can safely manage their financial situation and automatically plan efficient asset management.

[0279] The "user" refers to an individual or group that uses a financial management system and is the entity that inputs financial data and sets goals.

[0280] The "server" refers to a computer system that receives data from the user, securely stores and manages it, and plays a central role in executing various processes.

[0281] The "economic information" is a general term for financial information such as income, expenditure, assets, and liabilities held by the user.

[0282] "Encryption" refers to the process of securely converting the content of data so that it cannot be decoded by a third party in information technology.

[0283] The "asset management plan" refers to a plan for providing an optimal savings and investment strategy based on the user's goals.

[0284] The "generated AI model" is a model that uses artificial intelligence technology to generate an optimal asset management plan based on the input data.

[0285] The "investment and savings proposal" refers to a specific proposal on how to manage assets based on the user's financial situation and market data.

[0286] The "financial education content" refers to educational content provided to deepen the user's knowledge of asset management and investment.

[0287] The embodiments for implementing this invention will be described.

[0288] System Configuration

[0289] This system allows users to input their own financial information into a terminal, and based on that information, it provides an appropriate asset management plan. The server is responsible for data collection, storage, and analysis, and automatically generates the asset management plan using a generative AI model.

[0290] Hardware and software

[0291] Users utilize devices such as personal computers and smartphones. Dedicated application software runs on these devices to assist users in inputting economic information. The server consists of computers with high processing power, and secure protocols are used to encrypt stored data. The generative AI model is implemented on a software application running within the server.

[0292] Data processing and calculations

[0293] The server stores economic information entered by users in a structured data format and performs analysis of income, expenses, assets, and liabilities based on this data. The analyzed data is used to generate asset management plans to help users achieve their goals, and this is supported by a generative AI model.

[0294] Specific example

[0295] For example, if a user sets a financial goal of "buying a new car in three years," this goal is entered through the application on their device. The server receives this information and uses a generative AI model to generate and present an asset management plan, including an optimal savings plan and investment strategy. To achieve this process, the prompt given to the AI ​​model is, "Please suggest an investment portfolio suitable for the user's goal of buying a new car in three years." This specific plan serves as an important guide for the user to efficiently control their financial situation.

[0296] This allows users to clarify their financial goals and manage their assets systematically. The system utilizes advanced analytical techniques and generative AI models to enhance financial support for users.

[0297] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0298] Step 1:

[0299] Users use a terminal to input information about their income, expenses, assets, and liabilities. This input data undergoes basic formatting checks on the terminal before being sent to the server. The economic information, as input, is transmitted in a structured data format and received as output on the server.

[0300] Step 2:

[0301] The server encrypts the received economic information and securely stores it in a database. The AES-256 encryption algorithm is used to protect the data. The input to this process is economic information from the user, and the output is recorded as encrypted data.

[0302] Step 3:

[0303] The server analyzes stored economic information and performs data processing to evaluate the user's financial situation. Based on statistical analysis, it checks income and expenditure patterns and the balance of assets and liabilities. In this process, the input is encrypted information in the database, and the output is a report of the analyzed financial situation.

[0304] Step 4:

[0305] Users set specific financial goals through their devices. For example, they might input a goal like "I want to buy a new car in three years." This goal is sent to the server and registered as input. Based on this information, the server uses a generated AI model to formulate an asset management plan.

[0306] Step 5:

[0307] The server executes the generative AI model and generates an optimal asset management plan based on the user's financial information and goals. For this, the prompt sentence "Please propose an investment portfolio suitable for the goal of purchasing a new car within three years for the user" is used. The input is the user's financial information and goals, and the output is a detailed asset management plan including a monthly savings plan and recommended investment strategies.

[0308] Step 6:

[0309] The server sends the generated asset management plan to the user's terminal and displays it on the UI on the terminal. The output is provided as visual feedback to the user, and further operations and adjustments for each item of the plan are possible.

[0310] Step 7:

[0311] The server continues to monitor the user's spending patterns in real time and issues warnings about abnormal or unplanned expenditures. If the budget is exceeded, a notification is sent to the terminal. The input for this process is the user's latest spending data, and the output is a warning message displayed on the terminal.

[0312] (Application Example 1)[[ID=**25**]] [[ID=**26**]]

[0313] [[ID=**27**]] [[ID=**28**]]Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal". [[ID=**29**]] [[ID=**30**]]

[0314] [[ID=**31**]] [[ID=**32**]]Modern consumers need to manage diverse financial information and make appropriate economic decisions based on it, but there are insufficient means to do this efficiently and securely. Also, tools for real-time spending management and creating appropriate asset management plans for future financial goals are inadequate. Such a situation is an obstacle for consumers to achieve economic freedom. [[ID=**33**]] [[ID=**34**]]

[0315] [[ID=**35**]] 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.

[0316] This invention includes a server that collects, encrypts, and securely stores the user's financial data; a server that automatically generates an asset management plan based on the user's financial goals; and a server that uses a smart device to notify the user in real time when unusual spending is detected. This enables consumers to manage their financial information safely and efficiently, monitor their spending in real time, and develop appropriate asset management plans.

[0317] "Financial data" refers to information about a user's income, expenses, assets, and liabilities, and is the data on which economic decisions are made.

[0318] "Encryption" is a method of securely transforming information using special algorithms and techniques to protect it from unauthorized access.

[0319] "Economic goals" refer to specific financial outcomes or targets that users wish to achieve, such as saving money or making large purchases.

[0320] An "asset management plan" refers to a plan or strategy for asset management and investment aimed at achieving a user's financial goals.

[0321] "Real-time monitoring" refers to the process of immediately observing and analyzing ongoing data and situations.

[0322] "Market data" refers to information about financial markets, such as prices, trends, and economic indicators, which are used as the basis for investment and economic decisions.

[0323] A "smart device" refers to a portable electronic device equipped with communication and computer functions, and generally includes smartphones and wearable devices.

[0324] "Real-time notification when abnormal spending is detected" is a feature that immediately provides information to the user when deviations from normal spending patterns are detected.

[0325] The system that implements this application example is provided as an application installed on the user's smart device, such as a smartphone. Through the application, the user inputs their financial data and sends it to the server using a secure encryption method. The server operates in a cloud environment, and databases such as MongoDB or Firebase are used.

[0326] The server receives this data and uses a generative AI model to automatically generate an asset management plan based on economic goals. Furthermore, it monitors spending through real-time data monitoring and immediately sends an alert to the user's smartphone if spending exceeds normal levels. The alert serves as a notification when an anomaly is detected, helping the user prevent wasteful spending.

[0327] The software used includes Python and R libraries for data analysis, and AES encryption technology for encryption. This ensures the security of the information and the accuracy of the analysis.

[0328] Furthermore, the server analyzes market data and provides users with appropriate investment recommendations. This is done using an advanced data analytics platform on the cloud, providing users with guidance for long-term asset management with reduced risk.

[0329] As a concrete example, suppose a user planning a short family trip during the holidays sets this goal in the app. The server monitors shopping and travel expenses that deviate from the user's usual spending patterns and prompts the user to review their spending as needed. This allows the user to proceed with their plan while avoiding unnecessary expenses.

[0330] An example of a prompt using a generative AI model is, "How can I save 2.5 million yen in three years and buy a new car?" In this way, the generative AI model generates specific advice to help the user achieve their specific financial goals.

[0331] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0332] Step 1:

[0333] The user launches an application on their smart device and enters their financial data. This data includes income, daily expenses, assets, and liability information. This data is immediately encrypted using AES by the device. The encrypted data is then sent to the server via a secure communication protocol.

[0334] Step 2:

[0335] The server decrypts the received encrypted data and securely stores it in a database. A database such as MongoDB is used to store data in a structured format. The server also uses a generative AI model to analyze user prompts (e.g., "How to save 2.5 million yen in 3 years") and generate an asset management plan to achieve the goal. The output includes monthly savings plans and investment recommendations.

[0336] Step 3:

[0337] The server monitors user spending in real time. It analyzes purchase history and spending data transmitted from smart devices, and if it determines that there is a deviation from normal spending patterns, it is confirmed by an anomaly detection algorithm. Information on detected anomaly spending is notified to the device as an alert.

[0338] Step 4:

[0339] The server analyzes market data and provides investment and savings recommendations tailored to the user's risk management needs. This analysis utilizes data analysis libraries in Python and R, outputting strategic suggestions based on risk profiles derived from past market trends and economic indicators.

[0340] Step 5:

[0341] Users review investment and savings suggestions provided from their terminal and adjust their asset management plan as needed. They can also provide prompts to receive further advice from the server. The output includes specific goal achievement scenarios and improvement plans for asset management.

[0342] 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.

[0343] This invention is a household financial management system that recognizes users' emotions and utilizes them in financial planning and asset management. This system manages financial data while also understanding users' emotions, and optimizes various suggestions based on that understanding.

[0344] First, the user enters their financial data via a terminal. This includes information on income, expenses, assets, and liabilities. The terminal sends the entered data to a server, which securely encrypts and stores the received data.

[0345] Next, users can set financial goals and budgets using the interface provided on their devices during their daily lives. These settings are immediately transmitted to the server for analysis.

[0346] An emotion engine is running to understand the user's feelings. The device infers emotions by drawing hints from the user's input data and actions on the interface. This emotion data is sent to the server in real time.

[0347] The server uses the user's financial and emotional data to generate personalized investment plans. For example, if a user is feeling stressed, the server may suggest a low-risk investment plan to provide reassurance.

[0348] Furthermore, it monitors users' spending behavior in real time and provides emotionally-driven warnings and suggestions. If budget overruns are predicted, it recommends actions that will help users reduce costs.

[0349] Market data analysis will also be performed in conjunction with an emotion engine. This will allow the server to generate investment and savings plans tailored to the user's current mental state and recommend them through the device.

[0350] In insurance reviews, the server provides suggestions that take into account the user's emotional information, supporting appropriate risk management.

[0351] Based on analysis by an emotion engine, the server delivers advice and content to the user to help reduce stress. The device then delivers this to the user, aiming to maintain not only a healthy financial state but also mental well-being.

[0352] Thus, the system of the present invention supports comprehensive household management that links financial management and emotion recognition, as well as the optimization of the user's life balance.

[0353] The following describes the processing flow.

[0354] Step 1:

[0355] The user uses a device to input financial data such as income, expenses, assets, and liabilities. The device sends this data to a server, which encrypts and securely stores the data.

[0356] Step 2:

[0357] Users set individual financial goals and budgets on their devices. For example, they might enter a goal such as "Save 500,000 yen in one year." The device then transmits these settings to the server.

[0358] Step 3:

[0359] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and behavioral patterns resulting from their interface interactions.

[0360] Step 4:

[0361] The server integrates emotional and financial data sent from the terminal to automatically generate the most suitable asset management plan for the user. For example, if the user is feeling anxious, it will suggest a low-risk savings plan.

[0362] Step 5:

[0363] The server sends the user's monthly savings and spending plan to their device based on the generated plan. The device then displays this information visually to the user, highlighting the gap between their current situation and the plan.

[0364] Step 6:

[0365] The device tracks the user's daily spending in real time and reports that data to the server. If spending that exceeds the budget is predicted, the device warns the user and suggests specific countermeasures.

[0366] Step 7:

[0367] The server collects market data and makes appropriate investment and savings suggestions tailored to the user's sentiment. The terminal receives these suggestions and clearly displays the risk-return relationship to the user.

[0368] Step 8:

[0369] Based on the user's sentiment analysis, the server suggests a review of their insurance. This presents an optimal risk management plan that provides emotional reassurance.

[0370] Step 9:

[0371] The server selects and delivers stress-reducing advice and relaxation-promoting content based on the user's emotional and financial information, through the terminal.

[0372] This series of steps allows the entire system to work together to provide support tailored to the user's financial situation and emotions.

[0373] (Example 2)

[0374] 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".

[0375] Traditional household budgeting systems can only offer suggestions based on financial information, making it difficult to provide optimal asset management and spending control that takes into account the user's emotions and psychological state. This results in a challenge in providing effective support that addresses situations where users feel stressed or when their emotions change.

[0376] 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.

[0377] In this invention, the server includes means for recognizing the user's emotional state and integrating and analyzing emotional data and financial information, means for generating individual asset management plans, and means for providing content for relaxation and stress reduction based on the user's emotions. This enables flexible and appropriate financial management and support according to the user's emotional state.

[0378] "User financial information" refers to the collective economic data owned by a user, including income, expenses, assets, and liabilities.

[0379] "Encryption" is a technology that enhances information security by converting data into a format that cannot be understood by third parties.

[0380] A "financial plan" is a detailed plan for asset management, investment, and savings, based on the user's goals.

[0381] Real-time tracking means instantly monitoring current actions and situations and updating the data accordingly.

[0382] "Market information" refers to trends and data related to financial markets, including information on stocks, foreign exchange, and interest rates.

[0383] A "personalized asset management plan" is a customized investment and asset management proposal tailored to the user's individual circumstances, goals, and emotions.

[0384] "Emotional state" refers to the psychological situation and emotions experienced by the user, including the degree of stress and relaxation.

[0385] "Content" refers to data such as text, audio, and video that provides users with information, entertainment, and education.

[0386] This invention is a comprehensive household financial management system that manages users' financial information and provides asset management plans that take their emotional state into consideration. Users input monthly financial information such as income, expenses, assets, and liabilities using devices such as smartphones or personal computers. The device transmits this information to a server, which stores it securely using advanced encryption technology.

[0387] An emotion engine is built into the device, inferring emotions from the user's interface interactions. For example, input speed and click patterns are analyzed. The inferred emotion data is sent to a server in real time and integrated with financial information. The server uses a generative AI model to create an asset management plan that is suitable for the user's financial and emotional state. This model develops a financial strategy that prioritizes the user's peace of mind, such as suggesting low-risk investments based on the user's feelings.

[0388] For example, when a user sets a goal such as "I want to achieve my savings goal for next month's trip," the server provides advice on how to reduce related expenses. Also, if a user is feeling stressed, the server provides online yoga and meditation content via the device to help maintain mental and physical health.

[0389] An example of a prompt message would be: "Understand the user's emotional state and combine it with financial information to propose the optimal investment plan. If the user is feeling stressed, consider a low-risk investment plan; if they are feeling positive, consider a more aggressive investment plan."

[0390] The system implemented in this way provides comprehensive support for the user's financial situation and utilizes emotional data to optimize their lifestyle balance.

[0391] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0392] Step 1:

[0393] The user uses a terminal to input financial information regarding income, expenses, assets, and liabilities. The terminal sends this information as input data to the server. Specifically, the terminal receives the user's input, converts it to a digital format, and transmits it to the server over the network. The output is encrypted financial information stored on the server.

[0394] Step 2:

[0395] The server encrypts the received financial information using advanced encryption technology (e.g., AES-256). This ensures the confidentiality of the data and allows for secure storage. The input is raw data, and the output is securely stored encrypted data. Specifically, the process involves encrypting the data and securely storing it in the database.

[0396] Step 3:

[0397] The user sets financial targets and budgets through the terminal interface. The terminal sends these settings as input data to the server. The input is user configuration data, and the output is the configuration information incorporated into the latest financial plan on the server. The specific operation involves the immediate transfer and processing of the configuration data.

[0398] Step 4:

[0399] The device performs analysis to infer emotional data from the user's interface operations and input. Here, the input is the user's interaction data, and the output is emotional information inferred in real time. The emotional engine operates, meticulously analyzing input speed and operation patterns.

[0400] Step 5:

[0401] The server integrates and analyzes the user's financial data and inferred sentiment data. Using a generative AI model, it generates an optimal investment plan. The input is an integrated dataset, and the output is an investment plan optimized for the user. This specific operation includes the processes of data integration analysis and plan generation.

[0402] Step 6:

[0403] The server monitors users' spending in real time and generates alerts if anomalies are detected. The input is spending data, and the output is an alert message. The goal is to analyze spending trends and immediately notify users if any warning signs are detected.

[0404] Step 7:

[0405] The server analyzes market information and provides investment and savings suggestions that take into account the user's emotional state. Inputs are market data and emotional data, and output is a suggested plan. The specific operation involves using a generative AI model to integrate market information with emotional data and generate suggestions.

[0406] Step 8:

[0407] The server generates content for relaxation and stress reduction based on the user's emotional state and delivers it to the user via the terminal. The input is emotional data, and the output is content. Specifically, it is a mechanism that selects appropriate content according to the user's emotional state and provides it to the user.

[0408] (Application Example 2)

[0409] 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."

[0410] In modern society, users are required to make optimal financial decisions while considering complex financial data and their own emotional state. However, spending behavior is easily influenced by emotions, and selecting appropriate investment and savings strategies is difficult, often leading to anxiety and stress for users. These factors then become obstacles to maintaining a healthy financial state. This invention aims to optimize the user's economic and emotional balance by providing a financial management support system that takes these emotional factors into account.

[0411] 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.

[0412] In this invention, the server includes means for collecting the user's financial data and securely storing it through information processing, means for automatically generating a financial plan based on the entered goals, and means for inferring the user's emotions using emotion recognition technology and providing advice according to their spending. This allows the user to always be aware of their financial situation and make flexible financial decisions based on their emotions.

[0413] A "user" is an individual or organization that uses a financial management system to achieve their own financial goals.

[0414] "Economic data" refers to data that includes financial information such as income, expenses, assets, and liabilities.

[0415] "Information processing" is the process of analyzing and organizing collected data and taking necessary protective measures.

[0416] "Emotion recognition technology" is a technology that infers a user's emotional state from their input data and behavioral patterns.

[0417] A "financial plan" is a financial strategy that takes into account profitability, risks, and other factors based on the user's economic goals.

[0418] A "server" is an information technology infrastructure that receives and processes data from users and provides necessary information and services.

[0419] "Advice" refers to guidance and suggestions provided in accordance with the user's economic activities and emotional state.

[0420] The system of this invention is designed to integrate and manage a user's economic data and emotions, and to provide appropriate advice. This system mainly consists of the user's terminal, a server, and an emotion recognition engine.

[0421] Users input their financial data using devices such as smartphones and personal computers. This data includes income, expenses, assets, and liabilities. Upon receiving this information, the device encrypts the data and sends it to the server. Standard encryption technologies such as AES-256 are used to protect the information.

[0422] The server securely stores the received data and prepares it for subsequent processing. Cloud-based data processing platforms such as AWS Lambda and Azure Functions are used for this purpose. Based on the user's financial data, the server automatically generates a financial plan. This plan includes risk analysis, investment strategies, and insurance review proposals.

[0423] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state. This engine utilizes machine learning libraries such as TensorFlow and PyTorch to infer emotions based on the user's input data and daily interactions. When the user is experiencing stress or anxiety, low-risk investment and savings strategies are suggested.

[0424] For example, if a user is feeling down due to bad weather, the system will suggest ways to save money on their budget for the day. Also, if planned spending is necessary on a particular day, the system will use emotional data to suggest adjusting the timing and type of spending.

[0425] An example of a prompt for a generative AI model might be: "How can I use the emotion recognition engine to determine if a user's stress level is high and then display cost-saving advice based on that?" This prompt clarifies how each component of the system works together and guides developers to more accurately execute application examples.

[0426] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0427] Step 1:

[0428] The user inputs economic data using a terminal. This data includes income, expenses, assets, and liabilities. The terminal combines this data and securely encrypts it using AES-256 encryption technology. After encrypting the input data, it is sent to the server, which then becomes the input for the next process.

[0429] Step 2:

[0430] The server decrypts the received encrypted data and stores it in a database. Based on the information stored in the database, the server uses a machine learning algorithm (e.g., TensorFlow) to automatically generate a financial plan for the user. This involves analyzing the user's financial situation and providing a financial plan that includes optimal investment and savings strategies as output.

[0431] Step 3:

[0432] The emotion recognition engine analyzes interactions and data sent from the device in response to a user request to infer the user's emotional state. The engine utilizes TensorFlow to process the input data and obtain inferred emotion information. The inference result is sent to the server and becomes input for the next step.

[0433] Step 4:

[0434] The server integrates the user's emotional and economic data to generate personalized advice. For example, if the user's emotions indicate stress, the server will create low-risk investment or savings plans and provide advice to alleviate their anxiety.

[0435] Step 5:

[0436] The user's device receives advice from the server and displays it to the user. At this time, the device renders the information in a format that is easy for the user to understand, providing specific suggestions and warnings. For example, a message such as "Let's try to stay within budget today" might be displayed.

[0437] Step 6:

[0438] Based on the advice provided, users adjust their economic activities. The user's actions and feedback are then fed back into the system as input for the next processing, leading to more personalized suggestions.

[0439] 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.

[0440] 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.

[0441] 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.

[0442] [Third Embodiment]

[0443] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0444] 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.

[0445] 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).

[0446] 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.

[0447] 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.

[0448] 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).

[0449] 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.

[0450] 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.

[0451] 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.

[0452] 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.

[0453] 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.

[0454] 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".

[0455] This invention is a household financial management system that allows users to efficiently and securely manage their own financial data, and further automates the creation of optimal financial plans and asset management based on that data. The system is configured as follows:

[0456] First, the user enters their income, expenses, assets, and liabilities information via a terminal. This information is immediately transmitted to the server and stored securely in an encrypted state. Based on this data, the server understands the user's current situation and initiates operations to achieve specific financial goals.

[0457] The user then sets their financial goals. This goal setting is easily done through the UI (user interface), and they can enter specific goals such as "I want to buy a new car in three years." The device then sends this information to the server.

[0458] The server automatically generates an asset management plan based on the user's financial data and set goals. This plan shows the monthly savings amount and other necessary financial actions the user needs to take to achieve their planned goals.

[0459] Furthermore, the server monitors user spending in real time. The terminal issues alerts if spending exceeds the set budget or if any anomalies are detected. Users can check these alerts sent from the terminal at any time and review their spending as needed.

[0460] Furthermore, the server analyzes market data and provides investment and savings suggestions tailored to the user. This allows users to achieve efficient asset management at an appropriate risk level. For example, it may suggest long-term, systematic investment with reduced risk.

[0461] In addition, the server can re-evaluate the user's asset information and suggest insurance review options. Users can then better manage their risks by following these suggestions.

[0462] Finally, to improve financial literacy, the server selects financial education content according to the user's interests and skill level and delivers it to the device, providing an environment where users can learn independently.

[0463] Thus, the system of the present invention goes beyond mere financial data management and provides a comprehensive household management solution that supports users in achieving their long-term economic goals.

[0464] The following describes the processing flow.

[0465] Step 1:

[0466] The user uses a terminal to input individual pieces of information regarding income, expenses, assets, and liabilities. The terminal then formats this information and sends it to the server.

[0467] Step 2:

[0468] The server stores the received user's financial data in an encrypted format in its database. It also verifies the data's integrity and checks for any anomalies.

[0469] Step 3:

[0470] Users set their personal financial goals on their devices. For example, they might enter a specific goal such as, "I want to save 1 million yen in one year."

[0471] Step 4:

[0472] The device sends the configured target data to the server. Based on that target, the server analyzes the user's current financial situation and generates an optimal asset management plan.

[0473] Step 5:

[0474] The server returns the generated asset management plan to the terminal and presents it to the user. The plan includes monthly savings targets and recommended investment plans.

[0475] Step 6:

[0476] The device tracks the user's daily spending in real time and sends that data to a server. If the budget is exceeded or unusual spending occurs, the device displays a warning to the user.

[0477] Step 7:

[0478] The server continuously collects and analyzes market data to provide users with the latest investment and savings plans. The terminal notifies the user of the analysis results and displays the plan details.

[0479] Step 8:

[0480] The server determines whether an insurance review is necessary based on the user's asset information and makes suggestions accordingly. The terminal displays these suggestions to the user and provides information to aid understanding.

[0481] Step 9:

[0482] The server selects financial education content based on the user's interests and current level of understanding. It then delivers this content to the user via their device, providing them with learning opportunities.

[0483] In this way, the entire system works together at each step to support the user's financial management.

[0484] (Example 1)

[0485] 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."

[0486] In modern times, it is crucial for individuals to efficiently and safely manage their financial situation and develop optimal asset management plans based on that information. However, manual data entry and goal setting are time-consuming, and making appropriate investment and savings decisions is difficult. This invention aims to provide a means to solve these problems.

[0487] 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.

[0488] In this invention, the server includes means for collecting, encrypting, and securely storing the user's financial information; means for automatically generating an asset management plan based on input goals; and means for improving the asset management plan using a generated AI model. This enables the user to securely manage their financial situation and automatically plan efficient asset management.

[0489] A "user" refers to an individual or organization that uses a financial management system, and is the entity that inputs financial data and sets goals.

[0490] A "server" refers to a computer system that receives data from users, securely stores and manages it, and plays a central role in executing various processes.

[0491] "Economic information" is a general term for financial information held by users, such as income, expenses, assets, and liabilities.

[0492] In information technology, "encryption" refers to the process of securely transforming data so that its content cannot be deciphered by a third party.

[0493] An "asset management plan" refers to a plan designed to provide the optimal savings and investment strategy based on the user's goals.

[0494] A "generative AI model" is a model that uses artificial intelligence technology to generate an optimal asset management plan based on the input data.

[0495] "Investment and accumulation proposals" refer to specific suggestions on how to manage assets based on the user's financial situation and market data.

[0496] "Financial education content" refers to educational content provided to users to deepen their knowledge of asset management and investment.

[0497] A description of embodiments for carrying out the present invention will be provided.

[0498] System Configuration

[0499] This system allows users to input their own financial information into a terminal, and based on that information, it provides an appropriate asset management plan. The server is responsible for data collection, storage, and analysis, and automatically generates the asset management plan using a generative AI model.

[0500] Hardware and software

[0501] Users utilize devices such as personal computers and smartphones. Dedicated application software runs on these devices to assist users in inputting economic information. The server consists of computers with high processing power, and secure protocols are used to encrypt stored data. The generative AI model is implemented on a software application running within the server.

[0502] Data processing and calculations

[0503] The server stores economic information entered by users in a structured data format and performs analysis of income, expenses, assets, and liabilities based on this data. The analyzed data is used to generate asset management plans to help users achieve their goals, and this is supported by a generative AI model.

[0504] Specific example

[0505] For example, if a user sets a financial goal of "buying a new car in three years," this goal is entered through the application on their device. The server receives this information and uses a generative AI model to generate and present an asset management plan, including an optimal savings plan and investment strategy. To achieve this process, the prompt given to the AI ​​model is, "Please suggest an investment portfolio suitable for the user's goal of buying a new car in three years." This specific plan serves as an important guide for the user to efficiently control their financial situation.

[0506] This allows users to clarify their financial goals and manage their assets systematically. The system utilizes advanced analytical techniques and generative AI models to enhance financial support for users.

[0507] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0508] Step 1:

[0509] Users use a terminal to input information about their income, expenses, assets, and liabilities. This input data undergoes basic formatting checks on the terminal before being sent to the server. The economic information, as input, is transmitted in a structured data format and received as output on the server.

[0510] Step 2:

[0511] The server encrypts the received economic information and securely stores it in a database. The AES-256 encryption algorithm is used to protect the data. The input to this process is economic information from the user, and the output is recorded as encrypted data.

[0512] Step 3:

[0513] The server analyzes stored economic information and performs data processing to evaluate the user's financial situation. Based on statistical analysis, it checks income and expenditure patterns and the balance of assets and liabilities. In this process, the input is encrypted information in the database, and the output is a report of the analyzed financial situation.

[0514] Step 4:

[0515] Users set specific financial goals through their devices. For example, they might input a goal like "I want to buy a new car in three years." This goal is sent to the server and registered as input. Based on this information, the server uses a generated AI model to formulate an asset management plan.

[0516] Step 5:

[0517] The server runs a generation AI model to create an optimal asset management plan based on the user's financial information and goals. This uses the prompt "Please suggest an investment portfolio suitable for the user's goal of purchasing a new car in three years." The input is the user's financial information and goals, and the output is a detailed asset management plan including monthly savings plans and recommended investment strategies.

[0518] Step 6:

[0519] The server sends the generated asset management plan to the user's terminal and displays it on the terminal's UI. The output is provided as visual feedback to the user, allowing for further manipulation and adjustment of each item in the plan.

[0520] Step 7:

[0521] The server continues to monitor the user's spending patterns in real time and issues warnings for unusual or unplanned spending. If the budget is exceeded, a notification is sent to the device. The input to this process is the user's latest spending data, and the output is a warning message displayed on the device.

[0522] (Application Example 1)

[0523] 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."

[0524] Modern consumers need to manage diverse financial information and make sound financial decisions based on it, but they lack the means to do so efficiently and safely. Furthermore, there is a lack of tools for real-time spending management and creating appropriate asset management plans for future financial goals. This situation is an obstacle to consumers achieving financial freedom.

[0525] 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.

[0526] This invention includes a server that collects, encrypts, and securely stores the user's financial data; a server that automatically generates an asset management plan based on the user's financial goals; and a server that uses a smart device to notify the user in real time when unusual spending is detected. This enables consumers to manage their financial information safely and efficiently, monitor their spending in real time, and develop appropriate asset management plans.

[0527] "Financial data" refers to information about a user's income, expenses, assets, and liabilities, and is the data on which economic decisions are made.

[0528] "Encryption" is a method of securely transforming information using special algorithms and techniques to protect it from unauthorized access.

[0529] "Economic goals" refer to specific financial outcomes or targets that users wish to achieve, such as saving money or making large purchases.

[0530] An "asset management plan" refers to a plan or strategy for asset management and investment aimed at achieving a user's financial goals.

[0531] "Real-time monitoring" refers to the process of immediately observing and analyzing ongoing data and situations.

[0532] "Market data" refers to information about financial markets, such as prices, trends, and economic indicators, which are used as the basis for investment and economic decisions.

[0533] A "smart device" refers to a portable electronic device equipped with communication and computer functions, and generally includes smartphones and wearable devices.

[0534] "Real-time notification when abnormal spending is detected" is a feature that immediately provides information to the user when deviations from normal spending patterns are detected.

[0535] The system that implements this application example is provided as an application installed on the user's smart device, such as a smartphone. Through the application, the user inputs their financial data and sends it to the server using a secure encryption method. The server operates in a cloud environment, and databases such as MongoDB or Firebase are used.

[0536] The server receives this data and uses a generative AI model to automatically generate an asset management plan based on economic goals. Furthermore, it monitors spending through real-time data monitoring and immediately sends an alert to the user's smartphone if spending exceeds normal levels. The alert serves as a notification when an anomaly is detected, helping the user prevent wasteful spending.

[0537] The software used includes Python and R libraries for data analysis, and AES encryption technology for encryption. This ensures the security of the information and the accuracy of the analysis.

[0538] Furthermore, the server analyzes market data and provides users with appropriate investment recommendations. This is done using an advanced data analytics platform on the cloud, providing users with guidance for long-term asset management with reduced risk.

[0539] As a concrete example, suppose a user planning a short family trip during the holidays sets this goal in the app. The server monitors shopping and travel expenses that deviate from the user's usual spending patterns and prompts the user to review their spending as needed. This allows the user to proceed with their plan while avoiding unnecessary expenses.

[0540] An example of a prompt using a generative AI model is, "How can I save 2.5 million yen in three years and buy a new car?" In this way, the generative AI model generates specific advice to help the user achieve their specific financial goals.

[0541] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0542] Step 1:

[0543] The user launches an application on their smart device and enters their financial data. This data includes income, daily expenses, assets, and liability information. This data is immediately encrypted using AES by the device. The encrypted data is then sent to the server via a secure communication protocol.

[0544] Step 2:

[0545] The server decrypts the received encrypted data and securely stores it in a database. A database such as MongoDB is used to store data in a structured format. The server also uses a generative AI model to analyze user prompts (e.g., "How to save 2.5 million yen in 3 years") and generate an asset management plan to achieve the goal. The output includes monthly savings plans and investment recommendations.

[0546] Step 3:

[0547] The server monitors user spending in real time. It analyzes purchase history and spending data transmitted from smart devices, and if it determines that there is a deviation from normal spending patterns, it is confirmed by an anomaly detection algorithm. Information on detected anomaly spending is notified to the device as an alert.

[0548] Step 4:

[0549] The server analyzes market data and provides investment and savings recommendations tailored to the user's risk management needs. This analysis utilizes data analysis libraries in Python and R, outputting strategic suggestions based on risk profiles derived from past market trends and economic indicators.

[0550] Step 5:

[0551] Users review investment and savings suggestions provided from their terminal and adjust their asset management plan as needed. They can also provide prompts to receive further advice from the server. The output includes specific goal achievement scenarios and improvement plans for asset management.

[0552] 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.

[0553] This invention is a household financial management system that recognizes users' emotions and utilizes them in financial planning and asset management. This system manages financial data while also understanding users' emotions, and optimizes various suggestions based on that understanding.

[0554] First, the user enters their financial data via a terminal. This includes information on income, expenses, assets, and liabilities. The terminal sends the entered data to a server, which securely encrypts and stores the received data.

[0555] Next, users can set financial goals and budgets using the interface provided on their devices during their daily lives. These settings are immediately transmitted to the server for analysis.

[0556] An emotion engine is running to understand the user's feelings. The device infers emotions by drawing hints from the user's input data and actions on the interface. This emotion data is sent to the server in real time.

[0557] The server uses the user's financial and emotional data to generate personalized investment plans. For example, if a user is feeling stressed, the server may suggest a low-risk investment plan to provide reassurance.

[0558] Furthermore, it monitors users' spending behavior in real time and provides emotionally-driven warnings and suggestions. If budget overruns are predicted, it recommends actions that will help users reduce costs.

[0559] Market data analysis will also be performed in conjunction with an emotion engine. This will allow the server to generate investment and savings plans tailored to the user's current mental state and recommend them through the device.

[0560] In insurance reviews, the server provides suggestions that take into account the user's emotional information, supporting appropriate risk management.

[0561] Based on analysis by an emotion engine, the server delivers advice and content to the user to help reduce stress. The device then delivers this to the user, aiming to maintain not only a healthy financial state but also mental well-being.

[0562] Thus, the system of the present invention supports comprehensive household management that links financial management and emotion recognition, as well as the optimization of the user's life balance.

[0563] The following describes the processing flow.

[0564] Step 1:

[0565] The user uses a device to input financial data such as income, expenses, assets, and liabilities. The device sends this data to a server, which encrypts and securely stores the data.

[0566] Step 2:

[0567] Users set individual financial goals and budgets on their devices. For example, they might enter a goal such as "Save 500,000 yen in one year." The device then transmits these settings to the server.

[0568] Step 3:

[0569] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and behavioral patterns resulting from their interface interactions.

[0570] Step 4:

[0571] The server integrates emotional and financial data sent from the terminal to automatically generate the most suitable asset management plan for the user. For example, if the user is feeling anxious, it will suggest a low-risk savings plan.

[0572] Step 5:

[0573] The server sends the user's monthly savings and spending plan to their device based on the generated plan. The device then displays this information visually to the user, highlighting the gap between their current situation and the plan.

[0574] Step 6:

[0575] The device tracks the user's daily spending in real time and reports that data to the server. If spending that exceeds the budget is predicted, the device warns the user and suggests specific countermeasures.

[0576] Step 7:

[0577] The server collects market data and makes appropriate investment and savings suggestions tailored to the user's sentiment. The terminal receives these suggestions and clearly displays the risk-return relationship to the user.

[0578] Step 8:

[0579] Based on the user's sentiment analysis, the server suggests a review of their insurance. This presents an optimal risk management plan that provides emotional reassurance.

[0580] Step 9:

[0581] The server selects and delivers stress-reducing advice and relaxation-promoting content based on the user's emotional and financial information, through the terminal.

[0582] This series of steps allows the entire system to work together to provide support tailored to the user's financial situation and emotions.

[0583] (Example 2)

[0584] 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."

[0585] Traditional household financial management systems can only offer suggestions based on financial information, making it difficult to provide optimal asset management and spending control that takes into account the user's emotions and psychological state. This results in a challenge in providing effective support that addresses situations where users feel stressed or when their emotions change.

[0586] 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.

[0587] In this invention, the server includes means for recognizing the user's emotional state and integrating and analyzing emotional data and financial information, means for generating individual asset management plans, and means for providing content for relaxation and stress reduction based on the user's emotions. This enables flexible and appropriate financial management and support in accordance with the user's emotional state.

[0588] "User financial information" refers to the collective economic data owned by a user, including income, expenses, assets, and liabilities.

[0589] "Encryption" is a technology that enhances information security by converting data into a format that cannot be understood by third parties.

[0590] A "financial plan" is a detailed plan for asset management, investment, and savings, based on the user's goals.

[0591] Real-time tracking means instantly monitoring current actions and situations and updating the data accordingly.

[0592] "Market information" refers to trends and data related to financial markets, including information on stocks, foreign exchange, and interest rates.

[0593] A "personalized asset management plan" is a customized investment and asset management proposal tailored to the user's individual circumstances, goals, and emotions.

[0594] "Emotional state" refers to the psychological situation and emotions experienced by the user, including the degree of stress and relaxation.

[0595] "Content" refers to data such as text, audio, and video that provides users with information, entertainment, and education.

[0596] This invention is a comprehensive household financial management system that manages users' financial information and provides asset management plans that take their emotional state into consideration. Users input monthly financial information such as income, expenses, assets, and liabilities using devices such as smartphones or personal computers. The device transmits this information to a server, which stores it securely using advanced encryption technology.

[0597] An emotion engine is built into the device, inferring emotions from the user's interface interactions. For example, input speed and click patterns are analyzed. The inferred emotion data is sent to a server in real time and integrated with financial information. The server uses a generative AI model to create an asset management plan that is suitable for the user's financial and emotional state. This model develops a financial strategy that prioritizes the user's peace of mind, such as suggesting low-risk investments based on the user's feelings.

[0598] For example, when a user sets a goal such as "I want to achieve my savings goal for next month's trip," the server provides advice on how to reduce related expenses. Also, if a user is feeling stressed, the server provides online yoga and meditation content via the device to help maintain mental and physical health.

[0599] An example of a prompt message would be: "Understand the user's emotional state and combine it with financial information to propose the optimal investment plan. If the user is feeling stressed, consider a low-risk investment plan; if they are feeling positive, consider a more aggressive investment plan."

[0600] The system implemented in this way provides comprehensive support for the user's financial situation and utilizes emotional data to optimize their lifestyle balance.

[0601] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0602] Step 1:

[0603] The user uses a terminal to input financial information regarding income, expenses, assets, and liabilities. The terminal sends this information as input data to the server. Specifically, the terminal receives the user's input, converts it to a digital format, and transmits it to the server over the network. The output is encrypted financial information stored on the server.

[0604] Step 2:

[0605] The server encrypts the received financial information using advanced encryption technology (e.g., AES-256). This ensures the confidentiality of the data and allows for secure storage. The input is raw data, and the output is securely stored encrypted data. Specifically, the process involves encrypting the data and securely storing it in the database.

[0606] Step 3:

[0607] The user sets financial targets and budgets through the terminal interface. The terminal sends these settings as input data to the server. The input is user configuration data, and the output is the configuration information incorporated into the latest financial plan on the server. The specific operation involves the immediate transfer and processing of the configuration data.

[0608] Step 4:

[0609] The device performs analysis to infer emotional data from the user's interface operations and input. Here, the input is user interaction data, and the output is emotional information inferred in real time. The emotional engine operates, meticulously analyzing input speed and operation patterns.

[0610] Step 5:

[0611] The server integrates and analyzes the user's financial data and inferred sentiment data. Using a generative AI model, it generates an optimal investment plan. The input is an integrated dataset, and the output is an investment plan optimized for the user. This specific operation includes the processes of data integration analysis and plan generation.

[0612] Step 6:

[0613] The server monitors users' spending in real time and generates alerts if anomalies are detected. The input is spending data, and the output is an alert message. The goal is to analyze spending trends and provide immediate notification if any warning signs are detected.

[0614] Step 7:

[0615] The server analyzes market information and provides investment and savings suggestions that take into account the user's emotional state. The inputs are market data and emotional data, and the output is a suggested plan. Specifically, it utilizes a generative AI model to integrate market information with emotional data and generate suggestions.

[0616] Step 8:

[0617] The server generates content for relaxation and stress reduction based on the user's emotional state and delivers it to the user via the device. The input is emotional data, and the output is content. Specifically, it is a mechanism that selects appropriate content according to the user's emotional state and provides it to the user.

[0618] (Application Example 2)

[0619] 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."

[0620] In modern society, users are required to make optimal financial decisions while considering complex financial data and their own emotional state. However, spending behavior is easily influenced by emotions, and selecting appropriate investment and savings strategies is difficult, often leading to anxiety and stress for users. These factors then become obstacles to maintaining a healthy financial state. This invention aims to optimize the user's economic and emotional balance by providing a financial management support system that takes these emotional factors into account.

[0621] 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.

[0622] In this invention, the server includes means for collecting the user's financial data and securely storing it through information processing, means for automatically generating a financial plan based on the entered goals, and means for inferring the user's emotions using emotion recognition technology and providing advice according to their spending. This allows the user to always be aware of their financial situation and make flexible financial decisions based on their emotions.

[0623] A "user" is an individual or organization that uses a financial management system to achieve their own financial goals.

[0624] "Economic data" refers to data that includes financial information such as income, expenses, assets, and liabilities.

[0625] "Information processing" is the process of analyzing and organizing collected data and taking necessary protective measures.

[0626] "Emotion recognition technology" is a technology that infers a user's emotional state from their input data and behavioral patterns.

[0627] A "financial plan" is a financial strategy that takes into account profitability, risks, and other factors based on the user's economic goals.

[0628] A "server" is an information technology infrastructure that receives and processes data from users and provides necessary information and services.

[0629] "Advice" refers to guidance and suggestions provided in accordance with the user's economic activities and emotional state.

[0630] The system of this invention is designed to integrate and manage a user's economic data and emotions, and to provide appropriate advice. This system mainly consists of the user's terminal, a server, and an emotion recognition engine.

[0631] Users input their financial data using devices such as smartphones and personal computers. This data includes income, expenses, assets, and liabilities. Upon receiving this information, the device encrypts the data and sends it to the server. Standard encryption technologies such as AES-256 are used to protect the information.

[0632] The server securely stores the received data and prepares it for subsequent processing. Cloud-based data processing platforms such as AWS Lambda and Azure Functions are used for this purpose. Based on the user's financial data, the server automatically generates a financial plan. This plan includes risk analysis, investment strategies, and insurance review proposals.

[0633] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state. This engine utilizes machine learning libraries such as TensorFlow and PyTorch to infer emotions based on the user's input data and daily interactions. When the user is experiencing stress or anxiety, low-risk investment and savings strategies are suggested.

[0634] For example, if a user is feeling down due to bad weather, the system will suggest ways to save money on their budget for the day. Also, if planned spending is necessary on a particular day, the system will use emotional data to suggest adjusting the timing and type of spending.

[0635] An example of a prompt for a generative AI model might be: "How can I use the emotion recognition engine to determine if a user's stress level is high and then display cost-saving advice based on that?" This prompt clarifies how each component of the system works together and guides developers to more accurately execute application examples.

[0636] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0637] Step 1:

[0638] The user inputs economic data using a terminal. This data includes income, expenses, assets, and liabilities. The terminal combines this data and securely encrypts it using AES-256 encryption technology. After encrypting the input data, it is sent to the server, which then becomes the input for the next process.

[0639] Step 2:

[0640] The server decrypts the received encrypted data and stores it in a database. Based on the information stored in the database, the server uses a machine learning algorithm (e.g., TensorFlow) to automatically generate a financial plan for the user. This involves analyzing the user's financial situation and providing a financial plan that includes optimal investment and savings strategies as output.

[0641] Step 3:

[0642] The emotion recognition engine analyzes interactions and data sent from the device in response to a user request to infer the user's emotional state. The engine utilizes TensorFlow to process the input data and obtain inferred emotion information. The inference result is sent to the server and becomes input for the next step.

[0643] Step 4:

[0644] The server integrates the user's emotional and economic data to generate personalized advice. For example, if the user's emotions indicate stress, the server will create low-risk investment or savings plans and provide advice to alleviate their anxiety.

[0645] Step 5:

[0646] The user's device receives advice from the server and displays it to the user. At this time, the device renders the information in a format that is easy for the user to understand, providing specific suggestions and warnings. For example, a message such as "Let's try to stay within budget today" might be displayed.

[0647] Step 6:

[0648] Based on the advice provided, users adjust their economic activities. The user's actions and feedback are then fed back into the system as input for the next processing, leading to more personalized suggestions.

[0649] 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.

[0650] 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.

[0651] 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.

[0652] [Fourth Embodiment]

[0653] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0654] 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.

[0655] 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).

[0656] 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.

[0657] 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.

[0658] 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).

[0659] 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.

[0660] 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.

[0661] 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.

[0662] 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.

[0663] 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.

[0664] 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.

[0665] 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".

[0666] This invention is a household financial management system that allows users to efficiently and securely manage their own financial data, and further automates the creation of optimal financial plans and asset management based on that data. The system is configured as follows:

[0667] First, the user enters their income, expenses, assets, and liabilities information via a terminal. This information is immediately transmitted to the server and stored securely in an encrypted state. Based on this data, the server understands the user's current situation and initiates operations to achieve specific financial goals.

[0668] The user then sets their financial goals. This goal setting is easily done through the UI (user interface), and they can enter specific goals such as "I want to buy a new car in three years." The device then sends this information to the server.

[0669] The server automatically generates an asset management plan based on the user's financial data and set goals. This plan shows the monthly savings amount and other necessary financial actions the user needs to take to achieve their planned goals.

[0670] Furthermore, the server monitors user spending in real time. The terminal issues alerts if spending exceeds the set budget or if any anomalies are detected. Users can check these alerts sent from the terminal at any time and review their spending as needed.

[0671] Furthermore, the server analyzes market data and provides investment and savings suggestions tailored to the user. This allows users to achieve efficient asset management at an appropriate risk level. For example, it may suggest long-term, systematic investment with reduced risk.

[0672] In addition, the server can re-evaluate the user's asset information and suggest insurance review options. Users can then better manage their risks by following these suggestions.

[0673] Finally, to improve financial literacy, the server selects financial education content according to the user's interests and skill level and delivers it to the device, providing an environment where users can learn independently.

[0674] Thus, the system of the present invention goes beyond mere financial data management and provides a comprehensive household management solution that supports users in achieving their long-term economic goals.

[0675] The following describes the processing flow.

[0676] Step 1:

[0677] The user uses a terminal to input individual pieces of information regarding income, expenses, assets, and liabilities. The terminal then formats this information and sends it to the server.

[0678] Step 2:

[0679] The server stores the received user's financial data in an encrypted format in its database. It also verifies the data's integrity and checks for any anomalies.

[0680] Step 3:

[0681] Users set their personal financial goals on their devices. For example, they might enter a specific goal such as, "I want to save 1 million yen in one year."

[0682] Step 4:

[0683] The device sends the configured target data to the server. Based on that target, the server analyzes the user's current financial situation and generates an optimal asset management plan.

[0684] Step 5:

[0685] The server returns the generated asset management plan to the terminal and presents it to the user. The plan includes monthly savings targets and recommended investment plans.

[0686] Step 6:

[0687] The device tracks the user's daily spending in real time and sends that data to a server. If the budget is exceeded or unusual spending occurs, the device displays a warning to the user.

[0688] Step 7:

[0689] The server continuously collects and analyzes market data to provide users with the latest investment and savings plans. The terminal notifies the user of the analysis results and displays the plan details.

[0690] Step 8:

[0691] The server determines whether an insurance review is necessary based on the user's asset information and makes suggestions accordingly. The terminal displays these suggestions to the user and provides information to aid understanding.

[0692] Step 9:

[0693] The server selects financial education content based on the user's interests and current level of understanding. It then delivers this content to the user via their device, providing them with learning opportunities.

[0694] In this way, the entire system works together at each step to support the user's financial management.

[0695] (Example 1)

[0696] 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".

[0697] In modern times, it is crucial for individuals to efficiently and safely manage their financial situation and develop optimal asset management plans based on that information. However, manual data entry and goal setting are time-consuming, and making appropriate investment and savings decisions is difficult. This invention aims to provide a means to solve these problems.

[0698] 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.

[0699] In this invention, the server includes means for collecting, encrypting, and securely storing the user's financial information; means for automatically generating an asset management plan based on input goals; and means for improving the asset management plan using a generated AI model. This enables the user to securely manage their financial situation and automatically plan efficient asset management.

[0700] A "user" refers to an individual or organization that uses a financial management system, and is the entity that inputs financial data and sets goals.

[0701] A "server" refers to a computer system that receives data from users, securely stores and manages it, and plays a central role in executing various processes.

[0702] "Economic information" is a general term for financial information held by users, such as income, expenses, assets, and liabilities.

[0703] In information technology, "encryption" refers to the process of securely transforming data so that its content cannot be deciphered by a third party.

[0704] An "asset management plan" refers to a plan designed to provide the optimal savings and investment strategy based on the user's goals.

[0705] A "generative AI model" is a model that uses artificial intelligence technology to generate an optimal asset management plan based on the input data.

[0706] "Investment and accumulation proposals" refer to specific suggestions on how to manage assets based on the user's financial situation and market data.

[0707] "Financial education content" refers to educational content provided to users to deepen their knowledge of asset management and investment.

[0708] A description of embodiments for carrying out the present invention will be provided.

[0709] System Configuration

[0710] This system allows users to input their own financial information into a terminal, and based on that information, it provides an appropriate asset management plan. The server is responsible for data collection, storage, and analysis, and automatically generates the asset management plan using a generative AI model.

[0711] Hardware and software

[0712] Users utilize devices such as personal computers and smartphones. Dedicated application software runs on these devices to assist users in inputting economic information. The server consists of computers with high processing power, and secure protocols are used to encrypt stored data. The generative AI model is implemented on a software application running within the server.

[0713] Data processing and calculations

[0714] The server stores economic information entered by users in a structured data format and performs analysis of income, expenses, assets, and liabilities based on this data. The analyzed data is used to generate asset management plans to help users achieve their goals, and this is supported by a generative AI model.

[0715] Specific example

[0716] For example, if a user sets a financial goal of "buying a new car in three years," this goal is entered through the application on their device. The server receives this information and uses a generative AI model to generate and present an asset management plan, including an optimal savings plan and investment strategy. To achieve this process, the prompt given to the AI ​​model is, "Please suggest an investment portfolio suitable for the user's goal of buying a new car in three years." This specific plan serves as an important guide for the user to efficiently control their financial situation.

[0717] This allows users to clarify their financial goals and manage their assets systematically. The system utilizes advanced analytical techniques and generative AI models to enhance financial support for users.

[0718] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0719] Step 1:

[0720] Users use a terminal to input information about their income, expenses, assets, and liabilities. This input data undergoes basic formatting checks on the terminal before being sent to the server. The economic information, as input, is transmitted in a structured data format and received as output on the server.

[0721] Step 2:

[0722] The server encrypts the received economic information and securely stores it in a database. The AES-256 encryption algorithm is used to protect the data. The input to this process is economic information from the user, and the output is recorded as encrypted data.

[0723] Step 3:

[0724] The server analyzes stored economic information and performs data processing to evaluate the user's financial situation. Based on statistical analysis, it checks income and expenditure patterns and the balance of assets and liabilities. In this process, the input is encrypted information in the database, and the output is a report of the analyzed financial situation.

[0725] Step 4:

[0726] Users set specific financial goals through their devices. For example, they might input a goal like "I want to buy a new car in three years." This goal is sent to the server and registered as input. Based on this information, the server uses a generated AI model to formulate an asset management plan.

[0727] Step 5:

[0728] The server runs a generation AI model to create an optimal asset management plan based on the user's financial information and goals. This uses the prompt "Please suggest an investment portfolio suitable for the user's goal of purchasing a new car in three years." The input is the user's financial information and goals, and the output is a detailed asset management plan including monthly savings plans and recommended investment strategies.

[0729] Step 6:

[0730] The server sends the generated asset management plan to the user's terminal and displays it on the terminal's UI. The output is provided as visual feedback to the user, allowing for further manipulation and adjustment of each item in the plan.

[0731] Step 7:

[0732] The server continues to monitor the user's spending patterns in real time and issues warnings for unusual or unplanned spending. If the budget is exceeded, a notification is sent to the device. The input to this process is the user's latest spending data, and the output is a warning message displayed on the device.

[0733] (Application Example 1)

[0734] 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".

[0735] Modern consumers need to manage diverse financial information and make sound financial decisions based on it, but they lack the means to do so efficiently and safely. Furthermore, there is a lack of tools for real-time spending management and creating appropriate asset management plans for future financial goals. This situation is an obstacle to consumers achieving financial freedom.

[0736] 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.

[0737] This invention includes a server that collects, encrypts, and securely stores the user's financial data; a server that automatically generates an asset management plan based on the user's financial goals; and a server that uses a smart device to notify the user in real time when unusual spending is detected. This enables consumers to manage their financial information safely and efficiently, monitor their spending in real time, and develop appropriate asset management plans.

[0738] "Financial data" refers to information about a user's income, expenses, assets, and liabilities, and is the data on which economic decisions are made.

[0739] "Encryption" is a method of securely transforming information using special algorithms and techniques to protect it from unauthorized access.

[0740] "Economic goals" refer to specific financial outcomes or targets that users wish to achieve, such as saving money or making large purchases.

[0741] An "asset management plan" refers to a plan or strategy for asset management and investment aimed at achieving a user's financial goals.

[0742] "Real-time monitoring" refers to the process of immediately observing and analyzing ongoing data and situations.

[0743] "Market data" refers to information about financial markets, such as prices, trends, and economic indicators, which are used as the basis for investment and economic decisions.

[0744] A "smart device" refers to a portable electronic device equipped with communication and computer functions, and generally includes smartphones and wearable devices.

[0745] "Real-time notification when abnormal spending is detected" is a feature that immediately provides information to the user when deviations from normal spending patterns are detected.

[0746] The system that implements this application example is provided as an application installed on the user's smart device, such as a smartphone. Through the application, the user inputs their financial data and sends it to the server using a secure encryption method. The server operates in a cloud environment, and databases such as MongoDB or Firebase are used.

[0747] The server receives this data and uses a generative AI model to automatically generate an asset management plan based on economic goals. Furthermore, it monitors spending through real-time data monitoring and immediately sends an alert to the user's smartphone if spending exceeds normal levels. The alert serves as a notification when an anomaly is detected, helping the user prevent wasteful spending.

[0748] The software used includes Python and R libraries for data analysis, and AES encryption technology for encryption. This ensures the security of the information and the accuracy of the analysis.

[0749] Furthermore, the server analyzes market data and provides users with appropriate investment recommendations. This is done using an advanced data analytics platform on the cloud, providing users with guidance for long-term asset management with reduced risk.

[0750] As a concrete example, suppose a user planning a short family trip during the holidays sets this goal in the app. The server monitors shopping and travel expenses that deviate from the user's usual spending patterns and prompts the user to review their spending as needed. This allows the user to proceed with their plan while avoiding unnecessary expenses.

[0751] An example of a prompt using a generative AI model is, "How can I save 2.5 million yen in three years and buy a new car?" In this way, the generative AI model generates specific advice to help the user achieve their specific financial goals.

[0752] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0753] Step 1:

[0754] The user launches an application on their smart device and enters their financial data. This data includes income, daily expenses, assets, and liability information. This data is immediately encrypted using AES by the device. The encrypted data is then sent to the server via a secure communication protocol.

[0755] Step 2:

[0756] The server decrypts the received encrypted data and securely stores it in a database. A database such as MongoDB is used to store data in a structured format. The server also uses a generative AI model to analyze user prompts (e.g., "How to save 2.5 million yen in 3 years") and generate an asset management plan to achieve the goal. The output includes monthly savings plans and investment recommendations.

[0757] Step 3:

[0758] The server monitors user spending in real time. It analyzes purchase history and spending data transmitted from smart devices, and if it determines that there is a deviation from normal spending patterns, it is confirmed by an anomaly detection algorithm. Information on detected anomaly spending is notified to the device as an alert.

[0759] Step 4:

[0760] The server analyzes market data and provides investment and savings recommendations tailored to the user's risk management needs. This analysis utilizes data analysis libraries in Python and R, outputting strategic suggestions based on risk profiles derived from past market trends and economic indicators.

[0761] Step 5:

[0762] Users review investment and savings suggestions provided from their terminal and adjust their asset management plan as needed. They can also provide prompts to receive further advice from the server. The output includes specific goal achievement scenarios and improvement plans for asset management.

[0763] 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.

[0764] This invention is a household financial management system that recognizes users' emotions and utilizes them in financial planning and asset management. This system manages financial data while also understanding users' emotions, and optimizes various suggestions based on that understanding.

[0765] First, the user enters their financial data via a terminal. This includes information on income, expenses, assets, and liabilities. The terminal sends the entered data to a server, which securely encrypts and stores the received data.

[0766] Next, users can set financial goals and budgets using the interface provided on their devices during their daily lives. These settings are immediately transmitted to the server for analysis.

[0767] An emotion engine is running to understand the user's feelings. The device infers emotions by drawing hints from the user's input data and actions on the interface. This emotion data is sent to the server in real time.

[0768] The server uses the user's financial and emotional data to generate personalized investment plans. For example, if a user is feeling stressed, the server may suggest a low-risk investment plan to provide reassurance.

[0769] Furthermore, it monitors users' spending behavior in real time and provides emotionally-driven warnings and suggestions. If budget overruns are predicted, it recommends actions that will help users reduce costs.

[0770] Market data analysis will also be performed in conjunction with an emotion engine. This will allow the server to generate investment and savings plans tailored to the user's current mental state and recommend them through the device.

[0771] In insurance reviews, the server provides suggestions that take into account the user's emotional information, supporting appropriate risk management.

[0772] Based on analysis by an emotion engine, the server delivers advice and content to the user to help reduce stress. The device then delivers this to the user, aiming to maintain not only a healthy financial state but also mental well-being.

[0773] Thus, the system of the present invention supports comprehensive household management that links financial management and emotion recognition, as well as the optimization of the user's life balance.

[0774] The following describes the processing flow.

[0775] Step 1:

[0776] The user uses a device to input financial data such as income, expenses, assets, and liabilities. The device sends this data to a server, which encrypts and securely stores the data.

[0777] Step 2:

[0778] Users set individual financial goals and budgets on their devices. For example, they might enter a goal such as "Save 500,000 yen in one year." The device then transmits these settings to the server.

[0779] Step 3:

[0780] The device is equipped with an emotion engine that analyzes the user's emotional state based on their input and behavioral patterns resulting from their interface interactions.

[0781] Step 4:

[0782] The server integrates emotional and financial data sent from the terminal to automatically generate the most suitable asset management plan for the user. For example, if the user is feeling anxious, it will suggest a low-risk savings plan.

[0783] Step 5:

[0784] The server sends the user's monthly savings and spending plan to their device based on the generated plan. The device then displays this information visually to the user, highlighting the gap between their current situation and the plan.

[0785] Step 6:

[0786] The device tracks the user's daily spending in real time and reports that data to the server. If spending that exceeds the budget is predicted, the device warns the user and suggests specific countermeasures.

[0787] Step 7:

[0788] The server collects market data and makes appropriate investment and savings suggestions tailored to the user's sentiment. The terminal receives these suggestions and clearly displays the risk-return relationship to the user.

[0789] Step 8:

[0790] Based on the user's sentiment analysis, the server suggests a review of their insurance. This presents an optimal risk management plan that provides emotional reassurance.

[0791] Step 9:

[0792] The server selects and delivers stress-reducing advice and relaxation-promoting content based on the user's emotional and financial information, through the terminal.

[0793] This series of steps allows the entire system to work together to provide support tailored to the user's financial situation and emotions.

[0794] (Example 2)

[0795] 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".

[0796] Traditional household financial management systems can only offer suggestions based on financial information, making it difficult to provide optimal asset management and spending control that takes into account the user's emotions and psychological state. This results in a challenge in providing effective support that addresses situations where users feel stressed or when their emotions change.

[0797] 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.

[0798] In this invention, the server includes means for recognizing the user's emotional state and integrating and analyzing emotional data and financial information, means for generating individual asset management plans, and means for providing content for relaxation and stress reduction based on the user's emotions. This enables flexible and appropriate financial management and support in accordance with the user's emotional state.

[0799] "User financial information" refers to the collective economic data owned by a user, including income, expenses, assets, and liabilities.

[0800] "Encryption" is a technology that enhances information security by converting data into a format that cannot be understood by third parties.

[0801] A "financial plan" is a detailed plan for asset management, investment, and savings, based on the user's goals.

[0802] Real-time tracking means instantly monitoring current actions and situations and updating the data accordingly.

[0803] "Market information" refers to trends and data related to financial markets, including information on stocks, foreign exchange, and interest rates.

[0804] A "personalized asset management plan" is a customized investment and asset management proposal tailored to the user's individual circumstances, goals, and emotions.

[0805] "Emotional state" refers to the psychological situation and emotions experienced by the user, including the degree of stress and relaxation.

[0806] "Content" refers to data such as text, audio, and video that provides users with information, entertainment, and education.

[0807] This invention is a comprehensive household financial management system that manages users' financial information and provides asset management plans that take their emotional state into consideration. Users input monthly financial information such as income, expenses, assets, and liabilities using devices such as smartphones or personal computers. The device transmits this information to a server, which stores it securely using advanced encryption technology.

[0808] An emotion engine is built into the device, inferring emotions from the user's interface interactions. For example, input speed and click patterns are analyzed. The inferred emotion data is sent to a server in real time and integrated with financial information. The server uses a generative AI model to create an asset management plan that is suitable for the user's financial and emotional state. This model develops a financial strategy that prioritizes the user's peace of mind, such as suggesting low-risk investments based on the user's feelings.

[0809] For example, when a user sets a goal such as "I want to achieve my savings goal for next month's trip," the server provides advice on how to reduce related expenses. Also, if a user is feeling stressed, the server provides online yoga and meditation content via the device to help maintain mental and physical health.

[0810] An example of a prompt message would be: "Understand the user's emotional state and combine it with financial information to propose the optimal investment plan. If the user is feeling stressed, consider a low-risk investment plan; if they are feeling positive, consider a more aggressive investment plan."

[0811] The system implemented in this way provides comprehensive support for the user's financial situation and utilizes emotional data to optimize their lifestyle balance.

[0812] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0813] Step 1:

[0814] The user uses a terminal to input financial information regarding income, expenses, assets, and liabilities. The terminal sends this information as input data to the server. Specifically, the terminal receives the user's input, converts it to a digital format, and transmits it to the server over the network. The output is encrypted financial information stored on the server.

[0815] Step 2:

[0816] The server encrypts the received financial information using advanced encryption technology (e.g., AES-256). This ensures the confidentiality of the data and allows for secure storage. The input is raw data, and the output is securely stored encrypted data. Specifically, the process involves encrypting the data and securely storing it in the database.

[0817] Step 3:

[0818] The user sets financial targets and budgets through the terminal interface. The terminal sends these settings as input data to the server. The input is user configuration data, and the output is the configuration information incorporated into the latest financial plan on the server. The specific operation involves the immediate transfer and processing of the configuration data.

[0819] Step 4:

[0820] The device performs analysis to infer emotional data from the user's interface operations and input. Here, the input is user interaction data, and the output is emotional information inferred in real time. The emotional engine operates, meticulously analyzing input speed and operation patterns.

[0821] Step 5:

[0822] The server integrates and analyzes the user's financial data and inferred sentiment data. Using a generative AI model, it generates an optimal investment plan. The input is an integrated dataset, and the output is an investment plan optimized for the user. This specific operation includes the processes of data integration analysis and plan generation.

[0823] Step 6:

[0824] The server monitors users' spending in real time and generates alerts if anomalies are detected. The input is spending data, and the output is an alert message. The goal is to analyze spending trends and provide immediate notification if any warning signs are detected.

[0825] Step 7:

[0826] The server analyzes market information and provides investment and savings suggestions that take into account the user's emotional state. The inputs are market data and emotional data, and the output is a suggested plan. Specifically, it utilizes a generative AI model to integrate market information with emotional data and generate suggestions.

[0827] Step 8:

[0828] The server generates content for relaxation and stress reduction based on the user's emotional state and delivers it to the user via the device. The input is emotional data, and the output is content. Specifically, it is a mechanism that selects appropriate content according to the user's emotional state and provides it to the user.

[0829] (Application Example 2)

[0830] 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".

[0831] In modern society, users are required to make optimal financial decisions while considering complex financial data and their own emotional state. However, spending behavior is easily influenced by emotions, and selecting appropriate investment and savings strategies is difficult, often leading to anxiety and stress for users. These factors then become obstacles to maintaining a healthy financial state. This invention aims to optimize the user's economic and emotional balance by providing a financial management support system that takes these emotional factors into account.

[0832] 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.

[0833] In this invention, the server includes means for collecting the user's financial data and securely storing it through information processing, means for automatically generating a financial plan based on the entered goals, and means for inferring the user's emotions using emotion recognition technology and providing advice according to their spending. This allows the user to always be aware of their financial situation and make flexible financial decisions based on their emotions.

[0834] A "user" is an individual or organization that uses a financial management system to achieve their own financial goals.

[0835] "Economic data" refers to data that includes financial information such as income, expenses, assets, and liabilities.

[0836] "Information processing" is the process of analyzing and organizing collected data and taking necessary protective measures.

[0837] "Emotion recognition technology" is a technology that infers a user's emotional state from their input data and behavioral patterns.

[0838] A "financial plan" is a financial strategy that takes into account profitability, risks, and other factors based on the user's economic goals.

[0839] A "server" is an information technology infrastructure that receives and processes data from users and provides necessary information and services.

[0840] "Advice" refers to guidance and suggestions provided in accordance with the user's economic activities and emotional state.

[0841] The system of this invention is designed to integrate and manage a user's economic data and emotions, and to provide appropriate advice. This system mainly consists of the user's terminal, a server, and an emotion recognition engine.

[0842] Users input their financial data using devices such as smartphones and personal computers. This data includes income, expenses, assets, and liabilities. Upon receiving this information, the device encrypts the data and sends it to the server. Standard encryption technologies such as AES-256 are used to protect the information.

[0843] The server securely stores the received data and prepares it for subsequent processing. Cloud-based data processing platforms such as AWS Lambda and Azure Functions are used for this purpose. Based on the user's financial data, the server automatically generates a financial plan. This plan includes risk analysis, investment strategies, and insurance review proposals.

[0844] Furthermore, the server uses an emotion recognition engine to analyze the user's emotional state. This engine utilizes machine learning libraries such as TensorFlow and PyTorch to infer emotions based on the user's input data and daily interactions. When the user is experiencing stress or anxiety, low-risk investment and savings strategies are suggested.

[0845] For example, if a user is feeling down due to bad weather, the system will suggest ways to save money on their budget for the day. Also, if planned spending is necessary on a particular day, the system will use emotional data to suggest adjusting the timing and type of spending.

[0846] An example of a prompt for a generative AI model might be: "How can I use the emotion recognition engine to determine if a user's stress level is high and then display cost-saving advice based on that?" This prompt clarifies how each component of the system works together and guides developers to more accurately execute application examples.

[0847] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0848] Step 1:

[0849] The user inputs economic data using a terminal. This data includes income, expenses, assets, and liabilities. The terminal combines this data and securely encrypts it using AES-256 encryption technology. After encrypting the input data, it is sent to the server, which then becomes the input for the next process.

[0850] Step 2:

[0851] The server decrypts the received encrypted data and stores it in a database. Based on the information stored in the database, the server uses a machine learning algorithm (e.g., TensorFlow) to automatically generate a financial plan for the user. This involves analyzing the user's financial situation and providing a financial plan that includes optimal investment and savings strategies as output.

[0852] Step 3:

[0853] The emotion recognition engine analyzes interactions and data sent from the device in response to a user request to infer the user's emotional state. The engine utilizes TensorFlow to process the input data and obtain inferred emotion information. The inference result is sent to the server and becomes input for the next step.

[0854] Step 4:

[0855] The server integrates the user's emotional and economic data to generate personalized advice. For example, if the user's emotions indicate stress, the server will create low-risk investment or savings plans and provide advice to alleviate their anxiety.

[0856] Step 5:

[0857] The user's device receives advice from the server and displays it to the user. At this time, the device renders the information in a format that is easy for the user to understand, providing specific suggestions and warnings. For example, a message such as "Let's try to stay within budget today" might be displayed.

[0858] Step 6:

[0859] Based on the advice provided, users adjust their economic activities. The user's actions and feedback are then fed back into the system as input for the next processing, leading to more personalized suggestions.

[0860] 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.

[0861] 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.

[0862] 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.

[0863] 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.

[0864] 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.

[0865] 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.

[0866] 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.

[0867] 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.

[0868] 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."

[0869] 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.

[0870] 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.

[0871] 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.

[0872] 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.

[0873] 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.

[0874] 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.

[0875] 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.

[0876] 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.

[0877] 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.

[0878] 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.

[0879] 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.

[0880] 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.

[0881] The following is further disclosed regarding the embodiments described above.

[0882] (Claim 1)

[0883] A means of collecting, encrypting, and securely storing users' financial data,

[0884] A means of automatically generating a financial plan based on the entered goals,

[0885] A means to monitor user spending in real time and warn of anomalies,

[0886] A means of analyzing market data to make investment and savings proposals,

[0887] A means of proposing insurance reviews based on the user's asset information,

[0888] Means of providing financial education content,

[0889] A system that includes this.

[0890] (Claim 2)

[0891] The system according to claim 1, further comprising means for setting financial targets and budgets through a user interface.

[0892] (Claim 3)

[0893] The system according to claim 1, further comprising means for providing the most up-to-date financial plan in response to information updates.

[0894] "Example 1"

[0895] (Claim 1)

[0896] A means of collecting users' economic information, encrypting it, and storing it securely,

[0897] A means for automatically generating an asset management plan based on the entered goals,

[0898] A means to instantly monitor user spending and warn of anomalies,

[0899] A means of analyzing market information to make investment and accumulation proposals,

[0900] A means of proposing insurance adjustments based on the user's resource information,

[0901] Means of providing financial education content,

[0902] A means of improving asset management plans using generative AI models,

[0903] A system that includes this.

[0904] (Claim 2)

[0905] The system according to claim 1, further comprising means for setting financial targets and budgets through connection with users.

[0906] (Claim 3)

[0907] The system according to claim 1, further comprising means for providing an up-to-date asset management plan in response to information updates.

[0908] "Application Example 1"

[0909] (Claim 1)

[0910] A means of collecting, encrypting, and securely storing users' financial data,

[0911] A means of automatically generating an asset management plan based on the entered financial goals,

[0912] A means to monitor user spending in real time and warn of anomalies,

[0913] A means of analyzing market data to make appropriate investment and savings suggestions,

[0914] A means of proposing insurance reviews based on the user's asset information,

[0915] Means of providing financial education content,

[0916] A means of notifying in real time when abnormal spending is detected using a smart device,

[0917] A system that includes this.

[0918] (Claim 2)

[0919] The system according to claim 1, further comprising means for setting financial targets and budgets through a user interaction interface.

[0920] (Claim 3)

[0921] The system according to claim 1, further comprising means for providing the latest asset management plan in accordance with information updates.

[0922] "Example 2 of combining an emotion engine"

[0923] (Claim 1)

[0924] A means of collecting users' financial information, encrypting it, and storing it securely,

[0925] A means of automatically generating a financial plan based on the entered targets,

[0926] A means to track user spending in real time and warn of anomalies,

[0927] A means of analyzing market information to make investment and savings proposals,

[0928] A means of proposing insurance reviews based on the user's asset information,

[0929] Means of providing financial education materials,

[0930] A means of recognizing a user's emotional state, integrating and analyzing emotional data with financial information, and generating an individualized asset management plan.

[0931] A means of providing content for relaxation and stress reduction based on the user's emotions,

[0932] A system that includes this.

[0933] (Claim 2)

[0934] The system according to claim 1, further comprising means for setting financial targets and budgets through user interaction.

[0935] (Claim 3)

[0936] The system according to claim 1, further comprising means for providing the most up-to-date financial plan in response to information updates.

[0937] "Application example 2 when combining with an emotional engine"

[0938] (Claim 1)

[0939] A means of collecting users' economic data and securely storing it through information processing,

[0940] A means of automatically generating a financial plan based on the input goals,

[0941] A means of monitoring user consumption behavior in real time and warning of anomalies,

[0942] A means of analyzing market information to make investment and savings proposals,

[0943] A means of proposing insurance reviews based on the user's asset information,

[0944] A means of providing advice based on spending by inferring the user's emotions using emotion recognition technology,

[0945] A means of providing financial education materials using information processing technology,

[0946] A system that includes this.

[0947] (Claim 2)

[0948] The system according to claim 1, further comprising means for setting economic goals and budgets through an interactive interface with the user.

[0949] (Claim 3)

[0950] The system according to claim 1, further comprising means for providing the most up-to-date financial plan in response to information updates. [Explanation of Symbols]

[0951] 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 of collecting, encrypting, and securely storing users' financial data, A means of automatically generating an asset management plan based on the entered financial goals, A means to monitor user spending in real time and warn of anomalies, A means of analyzing market data to make appropriate investment and savings suggestions, A means of proposing insurance reviews based on the user's asset information, Means of providing financial education content, A means of notifying in real time when abnormal spending is detected using a smart device, A system that includes this.

2. The system according to claim 1, further comprising means for setting financial targets and budgets through a user interaction interface.

3. The system according to claim 1, further comprising means for providing the latest asset management plan in accordance with information updates.

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