system

Abstract

We provide the system. [Solution] A means of providing an interface for users to input financial information, A means of collecting input financial information and storing it in a database, A means of executing an algorithm that analyzes stored financial information to predict future financial conditions, A means of generating financial advice for users based on their predicted financial situation, A means of notifying users of advice, A means of providing reminders to users at the timing of life events, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, social situations and economic environments change daily, and personal household management has become complicated. To maintain a stable financial situation in the future, it is important to make appropriate plans. However, concerns about privacy when consulting experts and the cost burden are issues. In addition, it is difficult to manage household finances alone in the long term, and a flexible plan adapted to the changing environment is required.

Means for Solving the Problems

[0005] This invention relates to an interactive application that allows users to utilize a dedicated AI financial advisor to predict their future financial situation and receive appropriate reminders while protecting their privacy. Specifically, it collects financial information from the user through an input interface, stores it in a database, and then uses an analysis algorithm to predict future financial conditions. Furthermore, it generates and notifies the user of specific financial advice based on the prediction and provides reminders according to life events, thereby supporting long-term and flexible household financial management. This enables users to formulate appropriate financial strategies based on their career and life events in a cost-effective manner without disclosing detailed financial information to specific third parties.

[0006] "User" refers to an individual or entity that uses the system to input their financial information and receive household management and financial advice.

[0007] "Financial information" refers to data related to a user's financial status, such as income, assets, liabilities, expenses, and life event plans.

[0008] "Interface" refers to input screens or interactive methods used by users to enter financial information into a system.

[0009] A "database" refers to a digital storage medium or system used to store and manage financial information collected from users.

[0010] An "algorithm" refers to a set of calculation procedures and programs used to analyze input financial information data and predict future financial conditions.

[0011] "Financial advice" refers to specific instructions that provide appropriate action plans and asset management suggestions based on the user's current financial situation and future projections.

[0012] "Reminders" refers to a feature that notifies users at the appropriate time to draw their attention to important life events or financial periods. [Brief explanation of the drawing]

[0013] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined.

Embodiments for Carrying Out the Invention

[0014] 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.

[0015] First, the terms used in the following description will be explained.

[0016] In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0017] In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0018] In the following embodiments, a numbered 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.

[0019] 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).

[0020] 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."

[0021] [First Embodiment]

[0022] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] 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.

[0028] 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.

[0029] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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".

[0034] The interactive application of the present invention enables users to manage their financial information and receive necessary advice while maintaining their privacy. Embodiments thereof are described below.

[0035] Upon launching the application on their device, users first access an interface to input their financial information. This interface allows them to enter income, expenses, assets, liabilities, future life events, and more. Once the input is complete, the device sends the data to the server.

[0036] The server stores the user's received financial data in a database and uses an AI algorithm to analyze their future financial situation. This AI algorithm takes into account income trends, spending patterns, and economic trends to predict the user's future financial situation.

[0037] Based on the analysis results, the server generates specific financial advice for the user. This advice concerns financial strategies, such as "You need to increase your monthly savings" or "You should consider certain investment products."

[0038] The generated advice is notified to the user via their device, and the user confirms it. Furthermore, the server provides reminders at appropriate times depending on the user's life events and market conditions. For example, if a user is planning for their child to enter higher education, the system has a function to remind them in advance when preparations need to be made.

[0039] As a concrete example, consider a scenario where a user sets a goal of purchasing a home in five years. In this case, the server calculates the necessary savings based on projected future income and housing price forecasts, and advises the user on how to improve their current financial situation. The server also continuously monitors changes in the housing market and interest rate trends, providing the user with timely information.

[0040] Thus, the application of the present invention provides a concrete means for achieving effective household financial management by providing timely and private financial advice tailored to the user.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user launches the application using their device and is taken to a financial information input screen. Here, they enter their income, expenses, assets, liabilities, and future life event plans. The device validates the data entered by the user to ensure it conforms to the format, and prompts for re-entry if there are any discrepancies.

[0044] Step 2:

[0045] The terminal encrypts the financial information that has passed validation and sends it to the server via a secure communication protocol. The server stores the received data in a database for analysis.

[0046] Step 3:

[0047] The system retrieves data stored on the server and uses AI algorithms to analyze the user's future financial situation. This analysis includes revenue growth forecasting, spending trend analysis, and integration of economic data.

[0048] Step 4:

[0049] The server generates specific advice based on the analysis results to help the user achieve their financial goals. This includes, for example, recommended savings amounts to reach savings targets and investment recommendations.

[0050] Step 5:

[0051] The server formats the generated advice into a user-friendly format and prepares it for notification to the terminal. The terminal receives this information and displays it visually to the user.

[0052] Step 6:

[0053] The user reviews the advice provided, enters additional information as needed, and fine-tunes the plan. The device then sends this information back to the server.

[0054] Step 7:

[0055] The server continuously monitors life events and economic indicators in real time, preparing to send reminders to users at critical moments. This helps users revise their plans in a timely manner.

[0056] (Example 1)

[0057] 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."

[0058] In modern society, it is crucial for individuals to effectively manage their own financial situation and secure future economic stability. However, many people lack the confidence to grasp complex economic information and obtain appropriate economic guidance. To address this problem, a support system is needed that allows users to easily input their financial information and receive specific guidance based on predicted economic conditions. Furthermore, continuous updates of economic guidance in response to changes in external data are required while protecting user privacy.

[0059] 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.

[0060] In this invention, the server includes means for providing a screen for the user to input economic information, means for storing the input economic information in a storage device, means for generating economic guidance for the user based on predicted economic conditions, and means for continuously updating and providing the generated guidance to the user. This allows the user to obtain specific guidance based on their own economic situation and to update the economic guidance with the latest data as needed, while protecting their privacy.

[0061] A "user" is an individual or group that uses the system to manage their own financial information and obtain appropriate financial guidance.

[0062] "Economic information" refers to information entered by users, such as income, expenses, assets, liabilities, and future life events.

[0063] A "screen" is a display device that serves as an interface for users to input information into a system.

[0064] A "storage device" is a hardware or software device used to securely store collected economic information.

[0065] A "computational tool" is an algorithm or computer program used to analyze stored economic information and predict future economic conditions.

[0066] "Economic guidelines" refer to specific action plans and advice provided to users based on predicted economic conditions.

[0067] "Notifications" are a means of communication used to convey generated economic guidelines to users.

[0068] "Means of providing notifications" refers to a function or service within a system that delivers information to users at the time of life events.

[0069] "Means for continuously updating generated guidelines" refers to the process of improving the guidelines to the latest version in response to changes in external data and analysis results, and providing them to the user.

[0070] A "system" is a technological configuration that comprehensively includes these means and is designed to support the user's financial management.

[0071] This invention relates to a system that allows users to effectively manage their financial situation and obtain necessary financial guidance. The system aims to provide specific guidance by having users input their financial information from a terminal, performing analysis based on that information, and providing concrete guidance.

[0072] The user launches the application on their device and inputs financial information such as income, expenses, assets, liabilities, and future life events through the screen. The device provides an interface for sending this information to the server. This information is encrypted and securely transmitted to the server.

[0073] The server stores the input economic information in a storage device. This storage device is a large-capacity database that manages data individually for each user. Once the data is stored, an analysis is performed using a generative AI model installed on the server to predict future economic conditions. This model utilizes machine learning algorithms and can run, for example, in Python.

[0074] Based on the analysis results, the server generates economic guidance for the user. This guidance consists of specific action plans and advice based on the user's current financial situation. The generated guidance is continuously updated to accommodate changes in the user's life events and external environment. The generated guidance is notified to the user via their device.

[0075] As a concrete example of this system, when a user enters a prompt such as, "I want to buy a house in five years. Please tell me about a future financial plan to achieve this goal," the server will present a detailed savings plan based on projected future income and housing market trends, and notify the user of appropriate financial guidance. The user can then put this into action and implement a concrete plan.

[0076] Thus, the system of the present invention enables effective economic management by providing users with simple, reliable, and continuously updated economic guidelines.

[0077] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0078] Step 1:

[0079] The user launches the application on their device and enters financial information using the on-screen input interface. Specifically, they manually enter information such as income, expenses, assets, liabilities, and future life events. This information is temporarily stored on the device. After the user completes the input, the device prepares to send this information to the next processing step.

[0080] Step 2:

[0081] The terminal encrypts the entered economic information and sends it to the server using a secure communication protocol. Specifically, it encrypts the data using the SSL / TLS protocol. The input is the raw economic information entered by the user, and the output is the encrypted data received by the server.

[0082] Step 3:

[0083] The server decrypts the received encrypted data and stores it in storage. This process checks the integrity of the information and verifies that there are no missing or incorrect entries. The input is encrypted economic information, and the output is data stored in the database.

[0084] Step 4:

[0085] The server analyzes stored economic data using a generating AI model. Machine learning algorithms are employed to analyze user income and expenditure trends, and to predict future economic conditions, taking external economic trends into consideration. The input is economic information obtained from the database, and the output is the predicted economic situation.

[0086] Step 5:

[0087] The server generates financial guidance for the user based on predicted economic conditions. In this process, it outputs specific advice tailored to the user's goals and life events. The generated guidance may include, for example, "You need to save a specific amount of money each month" or "Review your risky investments." The input is the analyzed data, and the output is the generated financial guidance.

[0088] Step 6:

[0089] The server sends the generated economic guidelines to the terminal, which then notifies the user. Specifically, the terminal uses its notification function to display the guidelines on the user's screen. The input is the economic guidelines sent from the server, and the output is the information displayed to the user.

[0090] Step 7:

[0091] The server continuously updates the generated economic guidelines to respond to changes in the user's life events and economic environment. This updated information is then provided to the user again via the terminal as needed. Inputs are external economic data and user events, and output is the updated economic guidelines.

[0092] (Application Example 1)

[0093] 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."

[0094] For individuals to effectively manage their finances and develop future economic projections, specific and targeted guidance is necessary. However, providing accurate financial advice based on real-time, ever-changing market data while considering the protection of personal information is not easy. The challenge is to improve this situation and provide an environment where users can develop financial strategies safely and efficiently.

[0095] 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.

[0096] In this invention, the server includes means for providing a device for receiving financial information from a user, means for storing the information in a storage device, means for performing a calculation to predict future financial conditions, means for analyzing income and expenditure patterns using AI technology and constructing appropriate savings and investment strategies, and means including data management and customizable notification functions specifically designed to protect privacy. This enables users to receive accurate financial guidance based on real-time updated information in a privacy-enhanced environment.

[0097] A "user" is an entity that manages its own financial information using an application.

[0098] "Financial information" refers to economic data such as a user's income, expenses, assets, and liabilities.

[0099] "Device" refers to hardware or software that provides an interface for users to input financial information.

[0100] A "memory device" is a digital storage medium used to store entered financial information.

[0101] "Calculation method" refers to the process of analyzing data using algorithms to predict future financial conditions.

[0102] "AI technology" refers to technologies that utilize machine learning and data analysis to analyze users' income and spending patterns.

[0103] "Income and expenditure patterns" refer to trends in the increase or decrease of income and expenditure in a user's economic activities.

[0104] A "savings and investment strategy" is a specific plan or guideline designed to achieve a user's long-term financial goals.

[0105] "Privacy protection" refers to measures taken to prevent users' personal information from being used inappropriately by third parties.

[0106] "Data management" refers to the process of securely handling, storing, and updating users' financial information.

[0107] A "customizable notification feature" is a function that notifies users of necessary information at the appropriate time, according to their settings.

[0108] To realize this invention, the user first uses a terminal to input financial information through an interface. This terminal includes smartphones and computers, and the UI has forms that allow the user to input data such as income, expenses, assets, and liabilities. The entered information is stored in a storage device, and to protect the user's privacy, the information is sent to the server after undergoing an anonymization process.

[0109] The server runs on the cloud and manages data using the Django framework. The server uses received financial information and AI technology, specifically TENSORFLOW®, to predict the user's future financial situation. Machine learning models are used for analysis, employing calculation methods that incorporate historical economic data and trends. Based on the predicted results, the server designs and generates optimal savings and investment strategies for the user as guidance.

[0110] Guidance content is communicated to the user through a React Native-based application. These notifications are customizable and can send and receive alerts based on user-defined life events. This functionality allows users to receive real-time information and guidance in a private environment, making financial management easier and more effective.

[0111] For example, if a user aims to buy a house in five years, the server will calculate the amount of savings needed based on projected income and market changes, and advise on an appropriate savings strategy. Examples of prompts include: "If my income increases next year, what is the best investment strategy?" and "What is a savings plan for my children's education?"

[0112] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0113] Step 1:

[0114] The user uses a terminal to input financial information into the interface. The data entered includes items such as income, expenses, assets, and liabilities. The entered information is temporarily stored within the terminal.

[0115] Step 2:

[0116] The terminal anonymizes the entered financial information and sends it to the server. Anonymization ensures that the information is handled in a way that makes personal identification impossible. The output is the anonymized financial data sent to the server.

[0117] Step 3:

[0118] The server stores the received anonymized data in storage. The data is then passed to an AI model for analysis. The input is anonymized financial data, and the output is secure storage in a database.

[0119] Step 4:

[0120] The server uses TensorFlow to perform data analysis with an AI model. The analysis considers past economic data and trends to predict future financial conditions. The input is the data used by the AI ​​model, and the output is the prediction result.

[0121] Step 5:

[0122] The server generates optimal guidance for the user based on the analysis results. This generation process uses a generation AI model to create financial advice in response to prompts. The input is predictive data, and the output is the guidance content.

[0123] Step 6:

[0124] The server notifies the user of the generated guidance via a React Native application. The user can view the advice on their device and, if necessary, change the settings. The input is the guidance content, and the output is the user's expression of intent via notification.

[0125] Step 7:

[0126] The user reviews the received guidance and incorporates it into their future financial planning. Specific actions include viewing advice on the device and adjusting life event reminder functions as needed. The input is the notified advice, and the output is the user's action plan.

[0127] 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.

[0128] This invention is an interactive application that allows users to manage their own financial information while maintaining privacy, and further combines it with an emotion engine to provide more personalized financial advice.

[0129] This system provides an interface on the user's device for initial setup, where they input financial information. The user enters their income, expenses, assets, liabilities, and life event plans. This information is then sent from the device to a server. The server stores the received data in a database and uses AI algorithms to predict future financial situations.

[0130] Furthermore, this invention incorporates an emotion engine that recognizes the user's emotional state. This emotion engine can analyze emotions from the wording, context, and even voice used by the user during input. For example, if it determines that the user is in an emotional or stressful state, it takes that situation into consideration and generates financial advice to reduce stress. The server incorporates this emotional information into its algorithm, adjusts the financial advice, and then notifies the terminal.

[0131] This system displays advice to the user in a visually easy-to-understand format. Furthermore, through personalized, emotion-based communication, users can review and adjust their plans. Notification timing is optimized according to the user's emotions; for example, important notifications are delivered when the user is relaxed.

[0132] As a concrete example, consider a scenario where the terminal recognizes signs of stress from the user's input. The server suggests approaches to reduce stress, such as tools to simplify expense management or methods to alleviate psychological burden. As life events approach, the server supports the user by reminding them of necessary preparations while taking their emotional state into consideration.

[0133] Thus, the present invention provides information that takes into account not only financial data but also the user's emotional state, supporting efficient and humane household management.

[0134] The following describes the processing flow.

[0135] Step 1:

[0136] Users launch the application on their device and use an interface to input their emotional state along with their financial information. This interface allows them to input income, expenses, assets, and liabilities, as well as provide emotionally related questions and feedback.

[0137] Step 2:

[0138] The terminal encrypts the entered financial information and emotional data and sends it to the server via a secure protocol. The server stores the received data in a database for analysis.

[0139] Step 3:

[0140] The server uses AI algorithms to analyze financial information in the database and predict future financial conditions. In addition, it uses an emotion engine to analyze the emotional state expressed by the user. For example, it calculates stress levels and happiness indices and adjusts the data based on these results.

[0141] Step 4:

[0142] The server generates personalized financial advice for the user based on the analysis results. If the emotional state indicates stress, it includes advice to help reduce stress. The generated advice is emotionally appropriate and structured in an actionable way.

[0143] Step 5:

[0144] The server-generated advice and prediction data are organized and prepared for notifications. The user's emotional state is taken into consideration, and notifications are scheduled to arrive at the optimal time.

[0145] Step 6:

[0146] The device receives advice sent from the server and displays it visually to the user. The effectiveness of the advice is further enhanced by soliciting emotion-based feedback.

[0147] Step 7:

[0148] Users review the advice they receive and fine-tune their plans as needed. They can then resubmit their feedback to the server via their device, which will be reflected in future advice.

[0149] (Example 2)

[0150] 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".

[0151] In modern society, users need to manage a wide range of economic data and make future plans. However, conventional systems do not take into account the user's emotional state, making it difficult to provide information that is easy for users to understand and reduces stress. Therefore, the present invention aims to provide personalized information that also takes into account the user's emotional state, in a timely manner, thereby reducing the user's burden and enabling efficient information management.

[0152] 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.

[0153] In this invention, the server includes display means for receiving numerical data from the user, calculation means for analyzing the numerical data and predicting future numerical conditions, and means for analyzing the user's emotional state along with the numerical data using an emotion engine. This makes it possible to provide personalized information based on the user's emotional state.

[0154] "User" is a term that refers to an individual or organization that uses a system.

[0155] "Numerical data" refers to data provided by users, including information about their income, expenses, assets, and liabilities.

[0156] A "display means" is a device that provides a screen or interface for users to input information.

[0157] A "storage medium" is a software or hardware data storage device used to store input numerical data.

[0158] "Computational means" refers to algorithms and processing devices that perform analysis based on data and predict future situations.

[0159] "Information" refers to the results and advice generated using computational methods, and the content provided to the user.

[0160] "Notification methods" refer to methods such as email, messages, and screen notifications used to inform users of generated information.

[0161] An "emotion engine" refers to a program or function that analyzes a user's emotional state based on their input data.

[0162] "Personalized information" refers to advice and reminders tailored based on the user's numerical data and emotional state.

[0163] "External data" refers to information about market fluctuations and economic conditions, and includes data that the system collects independently.

[0164] This system comprehensively analyzes users' numerical data and emotional states to provide personalized information, thereby supporting efficient financial planning. It primarily consists of the following elements:

[0165] Users input numerical data such as income, expenses, assets, and liabilities into the system using a terminal. This information is entered via the user interface and transmitted to the server via a secure communication protocol from the terminal. The entered numerical data is securely stored on the server's storage medium.

[0166] The server uses stored data to execute AI algorithms and predict the user's future financial situation. This process employs generative AI models built in Python or similar programming languages. These models analyze multiple predictor variables to calculate the most suitable financial advice for the user.

[0167] Furthermore, the device uses an emotion engine to analyze the user's speech patterns and tone of voice, scoring the user's emotional state. This emotional data, along with numerical data, is sent to a server, which then adjusts the information based on the analysis results. For example, if the user is feeling stressed, the server might recommend spending management measures to alleviate that stress.

[0168] Information is sent from the server to the terminal and notified to the user in a visually easy-to-understand format. The timing of notifications is optimized to the user's emotional state, so important notifications can be received when the user is relaxed.

[0169] As a concrete example, when a user is planning a trip, the system provides financial advice based on the user's current financial situation and projected future income. Interaction can be initiated using prompts such as, "I'm worried about next month's travel expenses; how should I save money?"

[0170] This system allows users to receive not only information based on numerical data, but also efficient and personalized advice that takes into account their emotional well-being.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] Users use a terminal to input numerical data such as income, expenses, assets, and liabilities. This input is done through the user interface and stored on the terminal as numerical data. The terminal then prepares this input data for transmission to the server. This process includes format verification of the collected data and security checks with necessary signatures.

[0174] Step 2:

[0175] The terminal uses a secure communication protocol to send numerical data entered by the user to the server. This communication is encrypted to ensure the reliability of the data. The server verifies the received data and stores it in the appropriate database. During this process, the data format is checked and duplicates with existing data are checked; if there are no duplicates, the data is saved as new data.

[0176] Step 3:

[0177] The server uses a generative AI model to predict future numerical conditions based on stored numerical data. Specifically, it uses a statistical model that analyzes past data to predict future trends. The input is stored numerical data, and the output is predicted data of future numerical conditions. This model calculation is executed by a Python script, ensuring real-time computation.

[0178] Step 4:

[0179] The device uses an emotion engine to analyze the user's emotional state from their voice data and input patterns. This voice data is converted to text using speech recognition technology, and then emotion analysis is performed using natural language processing technology. The input is the user's voice or text, and the output is the result of the emotional state analysis. This result is sent to the server along with numerical data.

[0180] Step 5:

[0181] The server combines predicted numerical data with the user's emotional state to generate personalized information. The server takes this data as input and creates specific advice tailored to the user's current challenges. This might include suggestions to refrain from purchasing financial products or to review spending habits. The output is the information provided to the user.

[0182] Step 6:

[0183] The server sends the generated information to the terminal, which then notifies the user. This notification is displayed in a reminder format and is provided through a visually easy-to-understand graphical user interface. The server adjusts the notification timing based on the user's emotional state, sending the notification when it determines the user is relaxed. The output is the notification content that the user sees.

[0184] (Application Example 2)

[0185] 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".

[0186] Existing financial management systems often fail to adequately address human needs such as personalization and stress reduction, as they only provide standardized advice without considering the user's emotional state. Furthermore, there is a need for timely advice that is sensitive to the user's emotions while protecting their privacy.

[0187] 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.

[0188] In this invention, the server includes means for providing an interface for users to input financial information and emotional status information; means for collecting the input financial information and emotional status information and storing it in a database; and means for executing an algorithm that analyzes the stored financial information and emotional status information to predict future financial conditions and generate personalized financial advice based on the user's emotional status. This enables the provision of personalized financial advice according to the user's emotional status and stress-free financial management that takes privacy into consideration.

[0189] An "interface" is a means of providing users with screens and procedures for inputting financial and emotional information.

[0190] A "database" is an information storage location that appropriately organizes and stores collected financial and emotional information, and manages it in a format that can be used for later analysis.

[0191] An "algorithm" is a procedure that analyzes stored information, predicts future financial conditions, and generates financial advice tailored to the user's emotional state.

[0192] "Privacy protection" means anonymizing users' personal and emotional information and processing it in a way that makes it impossible for anyone other than the individual to identify them.

[0193] "Real-time monitoring" is a means of continuously observing changes in users' financial information, sentiment information, and market data, and updating advice as needed.

[0194] The system that realizes this invention executes a program on both the user's terminal and the server. The user inputs financial and emotional information into the terminal through an interface. This interface is designed to facilitate user input, and the data is automatically anonymized.

[0195] The device analyzes emotions using an AI camera for facial recognition and voice input. Specifically, it uses OpenCV to determine the user's emotional state from their facial expressions and Google® Cloud Speech-to-Text to infer emotions from their tone of voice. This information is sent to a server in real time, where it is stored in a database.

[0196] The server executes stored algorithms based on the collected financial and emotional information. These algorithms utilize generative AI models to predict future financial situations and generate personalized financial advice tailored to the user's emotional state. Furthermore, the server processes all data in an anonymized form to protect user privacy.

[0197] By providing timely advice that takes into account the user's emotional state, it is possible to reduce stress. For example, users who are under stress are provided with tools to simplify spending management, and important notifications are sent when they are relaxed. This allows users to manage their finances rationally and without stress in their daily lives.

[0198] An example of a prompt message is: "Based on data obtained from the camera and voice input, analyze the user's emotional state and check if they are stressed. Based on the analysis results, generate appropriate budget management advice for that day and send a notification."

[0199] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0200] Step 1:

[0201] Users enter financial and emotional information using the device's interface. This information is anonymized to protect privacy and temporarily stored on the device. The entered information includes data on the user's income, expenses, and life events.

[0202] Step 2:

[0203] The device uses an AI camera to analyze the user's facial expressions and OpenCV to identify their emotional state. Simultaneously, it analyzes audio data acquired from the microphone using Google Cloud Speech-to-Text to infer emotions from the tone of voice. The input consists of camera video and audio data, while the output is data related to the user's emotional state.

[0204] Step 3:

[0205] The terminal sends processed financial information and sentiment data to the server. The server receives this data and stores it in a database. The input is anonymized financial information and sentiment data, and the output is the state of storage in the database.

[0206] Step 4:

[0207] The server uses information retrieved from the database to run a generative AI model that predicts the user's future financial situation and generates personalized financial advice based on their emotional state. The input is the information from the database, and the output is the prediction results and advice.

[0208] Step 5:

[0209] The server sends generated advice to the device at a timing optimized for the user's emotional state. The timing of the notifications is adjusted based on emotional data, so that important notifications are sent when the user is relaxed, for example. The input is the generated advice and emotional data, and the output is the notification to the user.

[0210] 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.

[0211] 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.

[0212] 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.

[0213] [Second Embodiment]

[0214] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0215] 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.

[0216] 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).

[0217] 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.

[0218] 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.

[0219] 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).

[0220] 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.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] 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.

[0225] 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".

[0226] The interactive application of the present invention enables users to manage their financial information and receive necessary advice while maintaining their privacy. Embodiments thereof are described below.

[0227] Upon launching the application on their device, users first access an interface to input their financial information. This interface allows them to enter income, expenses, assets, liabilities, future life events, and more. Once the input is complete, the device sends the data to the server.

[0228] The server stores the user's received financial data in a database and uses an AI algorithm to analyze their future financial situation. This AI algorithm takes into account income trends, spending patterns, and economic trends to predict the user's future financial situation.

[0229] Based on the analysis results, the server generates specific financial advice for the user. This advice concerns financial strategies, such as "You need to increase your monthly savings" or "You should consider certain investment products."

[0230] The generated advice is notified to the user via their device, and the user confirms it. Furthermore, the server provides reminders at appropriate times depending on the user's life events and market conditions. For example, if a user is planning for their child to enter higher education, the system has a function to remind them in advance when preparations need to be made.

[0231] As a concrete example, consider a scenario where a user sets a goal of purchasing a home in five years. In this case, the server calculates the necessary savings based on projected future income and housing price forecasts, and advises the user on how to improve their current financial situation. The server also continuously monitors changes in the housing market and interest rate trends, providing the user with timely information.

[0232] Thus, the application of the present invention provides a concrete means for achieving effective household financial management by providing timely and private financial advice tailored to the user.

[0233] The following describes the processing flow.

[0234] Step 1:

[0235] The user launches the application using their device and is taken to a financial information input screen. Here, they enter their income, expenses, assets, liabilities, and future life event plans. The device validates the data entered by the user to ensure it conforms to the format, and prompts for re-entry if there are any discrepancies.

[0236] Step 2:

[0237] The terminal encrypts the financial information that has passed validation and sends it to the server via a secure communication protocol. The server stores the received data in a database for analysis.

[0238] Step 3:

[0239] The system retrieves data stored on the server and uses AI algorithms to analyze the user's future financial situation. This analysis includes revenue growth forecasting, spending trend analysis, and integration of economic data.

[0240] Step 4:

[0241] The server generates specific advice based on the analysis results to help the user achieve their financial goals. This includes, for example, recommended savings amounts to reach savings targets and investment recommendations.

[0242] Step 5:

[0243] The server formats the generated advice into a user-friendly format and prepares it for notification to the terminal. The terminal receives this information and displays it visually to the user.

[0244] Step 6:

[0245] The user reviews the advice provided, enters additional information as needed, and fine-tunes the plan. The device then sends this information back to the server.

[0246] Step 7:

[0247] The server continuously monitors life events and economic indicators in real time, preparing to send reminders to users at critical moments. This helps users revise their plans in a timely manner.

[0248] (Example 1)

[0249] 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."

[0250] In modern society, it is crucial for individuals to effectively manage their own financial situation and secure future economic stability. However, many people lack the confidence to grasp complex economic information and obtain appropriate economic guidance. To address this problem, a support system is needed that allows users to easily input their financial information and receive specific guidance based on predicted economic conditions. Furthermore, continuous updates of economic guidance in response to changes in external data are required while protecting user privacy.

[0251] 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.

[0252] In this invention, the server includes means for providing a screen for the user to input economic information, means for storing the input economic information in a storage device, means for generating economic guidance for the user based on predicted economic conditions, and means for continuously updating and providing the generated guidance to the user. This allows the user to obtain specific guidance based on their own economic situation and to update the economic guidance with the latest data as needed, while protecting their privacy.

[0253] A "user" is an individual or group that uses the system to manage their own financial information and obtain appropriate financial guidance.

[0254] "Economic information" refers to information entered by users, such as income, expenses, assets, liabilities, and future life events.

[0255] A "screen" is a display device that serves as an interface for users to input information into a system.

[0256] A "storage device" is a hardware or software device used to securely store collected economic information.

[0257] A "computational tool" is an algorithm or computer program used to analyze stored economic information and predict future economic conditions.

[0258] "Economic guidelines" refer to specific action plans and advice provided to users based on predicted economic conditions.

[0259] "Notifications" are a means of communication used to convey generated economic guidelines to users.

[0260] "Means of providing notifications" refers to a function or service within a system that delivers information to users at the time of life events.

[0261] "Means for continuously updating generated guidelines" refers to the process of improving the guidelines to the latest version in response to changes in external data and analysis results, and providing them to the user.

[0262] A "system" is a technological configuration that comprehensively includes these means and is designed to support the user's financial management.

[0263] This invention relates to a system that allows users to effectively manage their financial situation and obtain necessary financial guidance. The system aims to provide specific guidance by having users input their financial information from a terminal, performing analysis based on that information, and providing concrete guidance.

[0264] The user launches the application on their device and inputs financial information such as income, expenses, assets, liabilities, and future life events through the screen. The device provides an interface for sending this information to the server. This information is encrypted and securely transmitted to the server.

[0265] The server stores the input economic information in a storage device. This storage device is a large-capacity database that manages data individually for each user. Once the data is stored, an analysis is performed using a generative AI model installed on the server to predict future economic conditions. This model utilizes machine learning algorithms and can run, for example, in Python.

[0266] Based on the analysis results, the server generates economic guidance for the user. This guidance consists of specific action plans and advice based on the user's current financial situation. The generated guidance is continuously updated to accommodate changes in the user's life events and external environment. The generated guidance is notified to the user via their device.

[0267] As a concrete example of this system, when a user enters a prompt such as, "I want to buy a house in five years. Please tell me about a future financial plan to achieve this goal," the server will present a detailed savings plan based on projected future income and housing market trends, and notify the user of appropriate financial guidance. The user can then put this into action and implement a concrete plan.

[0268] Thus, the system of the present invention enables effective economic management by providing users with simple, reliable, and continuously updated economic guidelines.

[0269] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0270] Step 1:

[0271] The user launches the application on their device and enters financial information using the on-screen input interface. Specifically, they manually enter information such as income, expenses, assets, liabilities, and future life events. This information is temporarily stored on the device. After the user completes the input, the device prepares to send this information to the next processing step.

[0272] Step 2:

[0273] The terminal encrypts the entered economic information and sends it to the server using a secure communication protocol. Specifically, it encrypts the data using the SSL / TLS protocol. The input is the raw economic information entered by the user, and the output is the encrypted data received by the server.

[0274] Step 3:

[0275] The server decrypts the received encrypted data and stores it in storage. This process checks the integrity of the information and verifies that there are no missing or incorrect entries. The input is encrypted economic information, and the output is data stored in the database.

[0276] Step 4:

[0277] The server analyzes stored economic data using a generating AI model. Machine learning algorithms are employed to analyze user income and expenditure trends, and to predict future economic conditions, taking external economic trends into consideration. The input is economic information obtained from the database, and the output is the predicted economic situation.

[0278] Step 5:

[0279] The server generates economic guidelines for the user based on the predicted economic situation. In this process, specific advice suitable for the user's goals and life events is output. The generated guidelines are, for example, "Monthly savings of a specific amount are required" or "Review of investment with risks". The input is the analyzed data, and the output is the generated economic guidelines.

[0280] Step 6:

[0281] The server sends the generated economic guidelines to the terminal, and the terminal notifies the user of them. Specifically, the terminal uses the notification function to display the guidelines on the user's screen. The input is the economic guidelines sent from the server, and the output is the information displayed to the user.

[0282] Step 7:

[0283] The server continuously updates the generated economic guidelines to respond to changes in the user's life events and economic environment. This updated information is provided to the user again through the terminal as needed. The input is external economic data and user events, and the output is the updated economic guidelines.

[0284] (Application Example 1)

[0285] 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".

[0286] For an individual to effectively manage their financial situation and set a future economic outlook, specific and targeted guidance is necessary. However, it is not easy to make predictions based on real-time changing market data while considering the protection of personal information and provide accurate financial advice. Improving such a situation and providing an environment where users can formulate financial strategies safely and efficiently is an issue.

[0287] 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.

[0288] In this invention, the server includes means for providing a device for receiving financial information from a user, means for storing the information in a storage device, means for performing a calculation to predict future financial conditions, means for analyzing income and expenditure patterns using AI technology and constructing appropriate savings and investment strategies, and means including data management and customizable notification functions specifically designed to protect privacy. This enables users to receive accurate financial guidance based on real-time updated information in a privacy-enhanced environment.

[0289] A "user" is an entity that manages its own financial information using an application.

[0290] "Financial information" refers to economic data such as a user's income, expenses, assets, and liabilities.

[0291] "Device" refers to hardware or software that provides an interface for users to input financial information.

[0292] A "memory device" is a digital storage medium used to store entered financial information.

[0293] "Calculation method" refers to the process of analyzing data using algorithms to predict future financial conditions.

[0294] "AI technology" refers to technologies that utilize machine learning and data analysis to analyze users' income and spending patterns.

[0295] "Income and expenditure patterns" refer to trends in the increase or decrease of income and expenditure in a user's economic activities.

[0296] A "savings and investment strategy" is a specific plan or guideline designed to achieve a user's long-term financial goals.

[0297] "Privacy protection" refers to measures taken to prevent users' personal information from being used inappropriately by third parties.

[0298] "Data management" refers to the process of securely handling, storing, and updating users' financial information.

[0299] A "customizable notification feature" is a function that notifies users of necessary information at the appropriate time, according to their settings.

[0300] To realize this invention, the user first uses a terminal to input financial information through an interface. This terminal includes smartphones and computers, and the UI has forms that allow the user to input data such as income, expenses, assets, and liabilities. The entered information is stored in a storage device, and to protect the user's privacy, the information is sent to the server after undergoing an anonymization process.

[0301] The server runs on the cloud and manages data using the Django framework. The server uses AI technology, specifically TensorFlow, with the received financial information to predict the user's future financial situation. Machine learning models are used for analysis, employing calculation methods that incorporate historical economic data and trends. Based on the predicted results, it designs and generates optimal savings and investment strategies for the user as guidance.

[0302] Guidance content is communicated to the user through a React Native-based application. These notifications are customizable and can send and receive alerts based on user-defined life events. This functionality allows users to receive real-time information and guidance in a private environment, making financial management easier and more effective.

[0303] As a specific example, when a user aims to purchase a house in five years, the server calculates the savings amount based on the projected income and market changes, and advises an appropriate savings strategy. The following are examples of prompt sentences: "Please tell me the optimal investment strategy if my income increases next year," "Please tell me the savings plan for my child's education."

[0304] The flow of the specific process in Application Example 1 will be described using FIG. 12.

[0305] Step 1:

[0306] The user inputs financial information into the interface using the terminal. The data to be input are items such as income, expenditure, assets, and liabilities. The input information is temporarily held inside the terminal.

[0307] Step 2:

[0308] The terminal anonymizes the input financial information and sends it to the server. Through anonymization, information is handled only in a form that makes it impossible to identify individuals. As output, the anonymized financial data is sent to the server.

[0309] Step 3:

[0310] The server stores the received anonymized data in a storage device. The data is then passed to an AI model for analysis. The input is the anonymized financial data, and the output is secure storage in a database.

[0311] Step 4:

[0312] The server performs data analysis using an AI model with TensorFlow. In the analysis, past economic data and trends are considered to predict the future financial situation. The input is the data using the AI model, and the output is the prediction result.

[0313] Step 5:

[0314] The server generates optimal guidance for the user based on the analysis results. This generation process uses a generation AI model to create financial advice in response to prompts. The input is predictive data, and the output is the guidance content.

[0315] Step 6:

[0316] The server notifies the user of the generated guidance via a React Native application. The user can view the advice on their device and, if necessary, change the settings. The input is the guidance content, and the output is the user's expression of intent via notification.

[0317] Step 7:

[0318] The user reviews the received guidance and incorporates it into their future financial planning. Specific actions include viewing advice on the device and adjusting life event reminder functions as needed. The input is the notified advice, and the output is the user's action plan.

[0319] 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.

[0320] This invention is an interactive application that allows users to manage their own financial information while maintaining privacy, and further combines it with an emotion engine to provide more personalized financial advice.

[0321] This system provides an interface on the user's device for initial setup, where they input financial information. The user enters their income, expenses, assets, liabilities, and life event plans. This information is then sent from the device to a server. The server stores the received data in a database and uses AI algorithms to predict future financial situations.

[0322] Furthermore, this invention incorporates an emotion engine that recognizes the user's emotional state. This emotion engine can analyze emotions from the wording, context, and even voice used by the user during input. For example, if it determines that the user is in an emotional or stressful state, it takes that situation into consideration and generates financial advice to reduce stress. The server incorporates this emotional information into its algorithm, adjusts the financial advice, and then notifies the terminal.

[0323] This system displays advice to the user in a visually easy-to-understand format. Furthermore, through personalized, emotion-based communication, users can review and adjust their plans. Notification timing is optimized according to the user's emotions; for example, important notifications are delivered when the user is relaxed.

[0324] As a concrete example, consider a scenario where the terminal recognizes signs of stress from the user's input. The server suggests approaches to reduce stress, such as tools to simplify expense management or methods to alleviate psychological burden. As life events approach, the server supports the user by reminding them of necessary preparations while taking their emotional state into consideration.

[0325] Thus, the present invention provides information that takes into account not only financial data but also the user's emotional state, supporting efficient and humane household management.

[0326] The following describes the processing flow.

[0327] Step 1:

[0328] Users launch the application on their device and use an interface to input their emotional state along with their financial information. This interface allows them to input income, expenses, assets, and liabilities, as well as provide emotionally related questions and feedback.

[0329] Step 2:

[0330] The terminal encrypts the entered financial information and emotional data and sends it to the server via a secure protocol. The server stores the received data in a database for analysis.

[0331] Step 3:

[0332] The server uses AI algorithms to analyze financial information in the database and predict future financial conditions. In addition, it uses an emotion engine to analyze the emotional state expressed by the user. For example, it calculates stress levels and happiness indices and adjusts the data based on these results.

[0333] Step 4:

[0334] The server generates personalized financial advice for the user based on the analysis results. If the emotional state indicates stress, it includes advice to help reduce stress. The generated advice is emotionally appropriate and structured in an actionable way.

[0335] Step 5:

[0336] The server-generated advice and prediction data are organized and prepared for notifications. The user's emotional state is taken into consideration, and notifications are scheduled to arrive at the optimal time.

[0337] Step 6:

[0338] The device receives advice sent from the server and displays it visually to the user. The effectiveness of the advice is further enhanced by soliciting emotion-based feedback.

[0339] Step 7:

[0340] Users review the advice they receive and fine-tune their plans as needed. They can then resubmit their feedback to the server via their device, which will be reflected in future advice.

[0341] (Example 2)

[0342] 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".

[0343] In modern society, users need to manage a wide range of economic data and make future plans. However, conventional systems do not take into account the user's emotional state, making it difficult to provide information that is easy for users to understand and reduces stress. Therefore, the present invention aims to provide personalized information that also takes into account the user's emotional state, in a timely manner, thereby reducing the user's burden and enabling efficient information management.

[0344] 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.

[0345] In this invention, the server includes display means for receiving numerical data from the user, calculation means for analyzing the numerical data and predicting future numerical conditions, and means for analyzing the user's emotional state along with the numerical data using an emotion engine. This makes it possible to provide personalized information based on the user's emotional state.

[0346] "User" is a term that refers to an individual or organization that uses a system.

[0347] "Numerical data" refers to data provided by users, including information about their income, expenses, assets, and liabilities.

[0348] A "display means" is a device that provides a screen or interface for users to input information.

[0349] A "storage medium" is a software or hardware data storage device used to store input numerical data.

[0350] "Computational means" refers to algorithms and processing devices that perform analysis based on data and predict future situations.

[0351] "Information" refers to the results and advice generated using computational methods, and the content provided to the user.

[0352] "Notification methods" refer to methods such as email, messages, and screen notifications used to inform users of generated information.

[0353] An "emotion engine" refers to a program or function that analyzes a user's emotional state based on their input data.

[0354] "Personalized information" refers to advice and reminders tailored based on the user's numerical data and emotional state.

[0355] "External data" refers to information about market fluctuations and economic conditions, and includes data that the system collects independently.

[0356] This system comprehensively analyzes users' numerical data and emotional states to provide personalized information, thereby supporting efficient financial planning. It primarily consists of the following elements:

[0357] Users input numerical data such as income, expenses, assets, and liabilities into the system using a terminal. This information is entered via the user interface and transmitted to the server via a secure communication protocol from the terminal. The entered numerical data is securely stored on the server's storage medium.

[0358] The server uses stored data to execute AI algorithms and predict the user's future financial situation. This process employs generative AI models built in Python or similar programming languages. These models analyze multiple predictor variables to calculate the most suitable financial advice for the user.

[0359] Furthermore, the device uses an emotion engine to analyze the user's speech patterns and tone of voice, scoring the user's emotional state. This emotional data, along with numerical data, is sent to a server, which then adjusts the information based on the analysis results. For example, if the user is feeling stressed, the server might recommend spending management measures to alleviate that stress.

[0360] Information is sent from the server to the terminal and notified to the user in a visually easy-to-understand format. The timing of notifications is optimized to the user's emotional state, so important notifications can be received when the user is relaxed.

[0361] As a concrete example, when a user is planning a trip, the system provides financial advice based on the user's current financial situation and projected future income. Interaction can be initiated using prompts such as, "I'm worried about next month's travel expenses; how should I save money?"

[0362] This system allows users to receive not only information based on numerical data, but also efficient and personalized advice that takes into account their emotional well-being.

[0363] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0364] Step 1:

[0365] Users use a terminal to input numerical data such as income, expenses, assets, and liabilities. This input is done through the user interface and stored on the terminal as numerical data. The terminal then prepares this input data for transmission to the server. This process includes format verification of the collected data and security checks with necessary signatures.

[0366] Step 2:

[0367] The terminal uses a secure communication protocol to send numerical data entered by the user to the server. This communication is encrypted to ensure the reliability of the data. The server verifies the received data and stores it in the appropriate database. During this process, the data format is checked and duplicates with existing data are checked; if there are no duplicates, the data is saved as new data.

[0368] Step 3:

[0369] The server uses a generative AI model to predict future numerical conditions based on stored numerical data. Specifically, it uses a statistical model that analyzes past data to predict future trends. The input is stored numerical data, and the output is predicted data of future numerical conditions. This model calculation is executed by a Python script, ensuring real-time computation.

[0370] Step 4:

[0371] The device uses an emotion engine to analyze the user's emotional state from their voice data and input patterns. This voice data is converted to text using speech recognition technology, and then emotion analysis is performed using natural language processing technology. The input is the user's voice or text, and the output is the result of the emotional state analysis. This result is sent to the server along with numerical data.

[0372] Step 5:

[0373] The server combines predicted numerical data with the user's emotional state to generate personalized information. The server takes this data as input and creates specific advice tailored to the user's current challenges. This might include suggestions to refrain from purchasing financial products or to review spending habits. The output is the information provided to the user.

[0374] Step 6:

[0375] The server sends the generated information to the terminal, which then notifies the user. This notification is displayed in a reminder format and is provided through a visually easy-to-understand graphical user interface. The server adjusts the notification timing based on the user's emotional state, sending the notification when it determines the user is relaxed. The output is the notification content that the user sees.

[0376] (Application Example 2)

[0377] 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."

[0378] Existing financial management systems often fail to adequately address human needs such as personalization and stress reduction, as they only provide standardized advice without considering the user's emotional state. Furthermore, there is a need for timely advice that is sensitive to the user's emotions while protecting their privacy.

[0379] 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.

[0380] In this invention, the server includes means for providing an interface for users to input financial information and emotional status information; means for collecting the input financial information and emotional status information and storing it in a database; and means for executing an algorithm that analyzes the stored financial information and emotional status information to predict future financial conditions and generate personalized financial advice based on the user's emotional status. This enables the provision of personalized financial advice according to the user's emotional status and stress-free financial management that takes privacy into consideration.

[0381] An "interface" is a means of providing users with screens and procedures for inputting financial and emotional information.

[0382] A "database" is an information storage location that appropriately organizes and stores collected financial and emotional information, and manages it in a format that can be used for later analysis.

[0383] An "algorithm" is a procedure that analyzes stored information, predicts future financial conditions, and generates financial advice tailored to the user's emotional state.

[0384] "Privacy protection" means anonymizing users' personal and emotional information and processing it in a way that makes it impossible for anyone other than the individual to identify them.

[0385] "Real-time monitoring" is a means of continuously observing changes in users' financial information, sentiment information, and market data, and updating advice as needed.

[0386] The system that realizes this invention executes a program on both the user's terminal and the server. The user inputs financial and emotional information into the terminal through an interface. This interface is designed to facilitate user input, and the data is automatically anonymized.

[0387] The device analyzes emotions using an AI camera for facial recognition and voice input. Specifically, it uses OpenCV to determine the user's emotional state from their facial expressions and Google Cloud Speech-to-Text to infer emotions from their tone of voice. This information is sent to a server in real time, where it is stored in a database.

[0388] The server executes stored algorithms based on the collected financial and emotional information. These algorithms utilize generative AI models to predict future financial situations and generate personalized financial advice tailored to the user's emotional state. Furthermore, the server processes all data in an anonymized form to protect user privacy.

[0389] By providing timely advice that takes into account the user's emotional state, it is possible to reduce stress. For example, users who are under stress are provided with tools to simplify spending management, and important notifications are sent when they are relaxed. This allows users to manage their finances rationally and without stress in their daily lives.

[0390] An example of a prompt message is: "Based on data obtained from the camera and voice input, analyze the user's emotional state and check if they are stressed. Based on the analysis results, generate appropriate budget management advice for that day and send a notification."

[0391] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0392] Step 1:

[0393] Users enter financial and emotional information using the device's interface. This information is anonymized to protect privacy and temporarily stored on the device. The entered information includes data on the user's income, expenses, and life events.

[0394] Step 2:

[0395] The device uses an AI camera to analyze the user's facial expressions and OpenCV to identify their emotional state. Simultaneously, it analyzes audio data acquired from the microphone using Google Cloud Speech-to-Text to infer emotions from the tone of voice. The input consists of camera video and audio data, while the output is data related to the user's emotional state.

[0396] Step 3:

[0397] The terminal sends processed financial information and sentiment data to the server. The server receives this data and stores it in a database. The input is anonymized financial information and sentiment data, and the output is the state of storage in the database.

[0398] Step 4:

[0399] The server uses information retrieved from the database to run a generative AI model that predicts the user's future financial situation and generates personalized financial advice based on their emotional state. The input is the information from the database, and the output is the prediction results and advice.

[0400] Step 5:

[0401] The server sends generated advice to the device at a timing optimized for the user's emotional state. The timing of the notifications is adjusted based on emotional data, so that important notifications are sent when the user is relaxed, for example. The input is the generated advice and emotional data, and the output is the notification to the user.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] [Third Embodiment]

[0406] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0407] 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.

[0408] 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).

[0409] 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.

[0410] 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.

[0411] 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).

[0412] 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.

[0413] 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.

[0414] 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.

[0415] 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.

[0416] 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.

[0417] 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".

[0418] The interactive application of the present invention enables users to manage their financial information and receive necessary advice while maintaining their privacy. Embodiments thereof are described below.

[0419] Upon launching the application on their device, users first access an interface to input their financial information. This interface allows them to enter income, expenses, assets, liabilities, future life events, and more. Once the input is complete, the device sends the data to the server.

[0420] The server stores the user's received financial data in a database and uses an AI algorithm to analyze their future financial situation. This AI algorithm takes into account income trends, spending patterns, and economic trends to predict the user's future financial situation.

[0421] Based on the analysis results, the server generates specific financial advice for the user. This advice concerns financial strategies, such as "You need to increase your monthly savings" or "You should consider certain investment products."

[0422] The generated advice is notified to the user via their device, and the user confirms it. Furthermore, the server provides reminders at appropriate times depending on the user's life events and market conditions. For example, if a user is planning for their child to enter higher education, the system has a function to remind them in advance when preparations need to be made.

[0423] As a concrete example, consider a scenario where a user sets a goal of purchasing a home in five years. In this case, the server calculates the necessary savings based on projected future income and housing price forecasts, and advises the user on how to improve their current financial situation. The server also continuously monitors changes in the housing market and interest rate trends, providing the user with timely information.

[0424] Thus, the application of the present invention provides a concrete means for achieving effective household financial management by providing timely and private financial advice tailored to the user.

[0425] The following describes the processing flow.

[0426] Step 1:

[0427] The user launches the application using their device and is taken to a financial information input screen. Here, they enter their income, expenses, assets, liabilities, and future life event plans. The device validates the data entered by the user to ensure it conforms to the format, and prompts for re-entry if there are any discrepancies.

[0428] Step 2:

[0429] The terminal encrypts the financial information that has passed validation and sends it to the server via a secure communication protocol. The server stores the received data in a database for analysis.

[0430] Step 3:

[0431] The system retrieves data stored on the server and uses AI algorithms to analyze the user's future financial situation. This analysis includes revenue growth forecasting, spending trend analysis, and integration of economic data.

[0432] Step 4:

[0433] The server generates specific advice based on the analysis results to help the user achieve their financial goals. This includes, for example, recommended savings amounts to reach savings targets and investment recommendations.

[0434] Step 5:

[0435] The server formats the generated advice into a user-friendly format and prepares it for notification to the terminal. The terminal receives this information and displays it visually to the user.

[0436] Step 6:

[0437] The user reviews the advice provided, enters additional information as needed, and fine-tunes the plan. The device then sends this information back to the server.

[0438] Step 7:

[0439] The server continuously monitors life events and economic indicators in real time, preparing to send reminders to users at critical moments. This helps users revise their plans in a timely manner.

[0440] (Example 1)

[0441] 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."

[0442] In modern society, it is crucial for individuals to effectively manage their own financial situation and secure future economic stability. However, many people lack the confidence to grasp complex economic information and obtain appropriate economic guidance. To address this problem, a support system is needed that allows users to easily input their financial information and receive specific guidance based on predicted economic conditions. Furthermore, continuous updates of economic guidance in response to changes in external data are required while protecting user privacy.

[0443] 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.

[0444] In this invention, the server includes means for providing a screen for the user to input economic information, means for storing the input economic information in a storage device, means for generating economic guidance for the user based on predicted economic conditions, and means for continuously updating and providing the generated guidance to the user. This allows the user to obtain specific guidance based on their own economic situation and to update the economic guidance with the latest data as needed, while protecting their privacy.

[0445] A "user" is an individual or group that uses the system to manage their own financial information and obtain appropriate financial guidance.

[0446] "Economic information" refers to information entered by users, such as income, expenses, assets, liabilities, and future life events.

[0447] A "screen" is a display device that serves as an interface for users to input information into a system.

[0448] A "storage device" is a hardware or software device used to securely store collected economic information.

[0449] A "computational tool" is an algorithm or computer program used to analyze stored economic information and predict future economic conditions.

[0450] "Economic guidelines" refer to specific action plans and advice provided to users based on predicted economic conditions.

[0451] "Notifications" are a means of communication used to convey generated economic guidelines to users.

[0452] "Means of providing notifications" refers to a function or service within a system that delivers information to users at the time of life events.

[0453] "Means for continuously updating generated guidelines" refers to the process of improving the guidelines to the latest version in response to changes in external data and analysis results, and providing them to the user.

[0454] A "system" is a technological configuration that comprehensively includes these means and is designed to support the user's financial management.

[0455] This invention relates to a system that allows users to effectively manage their financial situation and obtain necessary financial guidance. The system aims to provide specific guidance by having users input their financial information from a terminal, performing analysis based on that information, and providing concrete guidance.

[0456] The user launches the application on their device and inputs financial information such as income, expenses, assets, liabilities, and future life events through the screen. The device provides an interface for sending this information to the server. This information is encrypted and securely transmitted to the server.

[0457] The server stores the input economic information in a storage device. This storage device is a large-capacity database that manages data individually for each user. Once the data is stored, an analysis is performed using a generative AI model installed on the server to predict future economic conditions. This model utilizes machine learning algorithms and can run, for example, in Python.

[0458] Based on the analysis results, the server generates economic guidance for the user. This guidance consists of specific action plans and advice based on the user's current financial situation. The generated guidance is continuously updated to accommodate changes in the user's life events and external environment. The generated guidance is notified to the user via their device.

[0459] As a concrete example of this system, when a user enters a prompt such as, "I want to buy a house in five years. Please tell me about a future financial plan to achieve this goal," the server will present a detailed savings plan based on projected future income and housing market trends, and notify the user of appropriate financial guidance. The user can then put this into action and implement a concrete plan.

[0460] Thus, the system of the present invention enables effective economic management by providing users with simple, reliable, and continuously updated economic guidelines.

[0461] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0462] Step 1:

[0463] The user launches the application on their device and enters financial information using the on-screen input interface. Specifically, they manually enter information such as income, expenses, assets, liabilities, and future life events. This information is temporarily stored on the device. After the user completes the input, the device prepares to send this information to the next processing step.

[0464] Step 2:

[0465] The terminal encrypts the entered economic information and sends it to the server using a secure communication protocol. Specifically, it encrypts the data using the SSL / TLS protocol. The input is the raw economic information entered by the user, and the output is the encrypted data received by the server.

[0466] Step 3:

[0467] The server decrypts the received encrypted data and stores it in storage. This process checks the integrity of the information and verifies that there are no missing or incorrect entries. The input is encrypted economic information, and the output is data stored in the database.

[0468] Step 4:

[0469] The server analyzes stored economic data using a generating AI model. Machine learning algorithms are employed to analyze user income and expenditure trends, and to predict future economic conditions, taking external economic trends into consideration. The input is economic information obtained from the database, and the output is the predicted economic situation.

[0470] Step 5:

[0471] The server generates financial guidance for the user based on predicted economic conditions. In this process, it outputs specific advice tailored to the user's goals and life events. The generated guidance may include, for example, "You need to save a specific amount of money each month" or "Review your risky investments." The input is the analyzed data, and the output is the generated financial guidance.

[0472] Step 6:

[0473] The server sends the generated economic guidelines to the terminal, which then notifies the user. Specifically, the terminal uses its notification function to display the guidelines on the user's screen. The input is the economic guidelines sent from the server, and the output is the information displayed to the user.

[0474] Step 7:

[0475] The server continuously updates the generated economic guidelines to respond to changes in the user's life events and economic environment. This updated information is then provided to the user again via the terminal as needed. Inputs are external economic data and user events, and output is the updated economic guidelines.

[0476] (Application Example 1)

[0477] 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."

[0478] For individuals to effectively manage their finances and develop future economic projections, specific and targeted guidance is necessary. However, providing accurate financial advice based on real-time, ever-changing market data while considering the protection of personal information is not easy. The challenge is to improve this situation and provide an environment where users can develop financial strategies safely and efficiently.

[0479] 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.

[0480] In this invention, the server includes means for providing a device for receiving financial information from a user, means for storing the information in a storage device, means for performing a calculation to predict future financial conditions, means for analyzing income and expenditure patterns using AI technology and constructing appropriate savings and investment strategies, and means including data management and customizable notification functions specifically designed to protect privacy. This enables users to receive accurate financial guidance based on real-time updated information in a privacy-enhanced environment.

[0481] A "user" is an entity that manages its own financial information using an application.

[0482] "Financial information" refers to economic data such as a user's income, expenses, assets, and liabilities.

[0483] "Device" refers to hardware or software that provides an interface for users to input financial information.

[0484] A "memory device" is a digital storage medium used to store entered financial information.

[0485] "Calculation method" refers to the process of analyzing data using algorithms to predict future financial conditions.

[0486] "AI technology" refers to technologies that utilize machine learning and data analysis to analyze users' income and spending patterns.

[0487] "Income and expenditure patterns" refer to trends in the increase or decrease of income and expenditure in a user's economic activities.

[0488] A "savings and investment strategy" is a specific plan or guideline designed to achieve a user's long-term financial goals.

[0489] "Privacy protection" refers to measures taken to prevent users' personal information from being used inappropriately by third parties.

[0490] "Data management" refers to the process of securely handling, storing, and updating users' financial information.

[0491] A "customizable notification feature" is a function that notifies users of necessary information at the appropriate time, according to their settings.

[0492] To realize this invention, the user first uses a terminal to input financial information through an interface. This terminal includes smartphones and computers, and the UI has forms that allow the user to input data such as income, expenses, assets, and liabilities. The entered information is stored in a storage device, and to protect the user's privacy, the information is sent to the server after undergoing an anonymization process.

[0493] The server runs on the cloud and manages data using the Django framework. The server uses AI technology, specifically TensorFlow, with the received financial information to predict the user's future financial situation. Machine learning models are used for analysis, employing calculation methods that incorporate historical economic data and trends. Based on the predicted results, it designs and generates optimal savings and investment strategies for the user as guidance.

[0494] Guidance content is communicated to the user through a React Native-based application. These notifications are customizable and can send and receive alerts based on user-defined life events. This functionality allows users to receive real-time information and guidance in a private environment, making financial management easier and more effective.

[0495] For example, if a user aims to buy a house in five years, the server will calculate the amount of savings needed based on projected income and market changes, and advise on an appropriate savings strategy. Examples of prompts include: "If my income increases next year, what is the best investment strategy?" and "What is a savings plan for my children's education?"

[0496] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0497] Step 1:

[0498] The user uses a terminal to input financial information into the interface. The data entered includes items such as income, expenses, assets, and liabilities. The entered information is temporarily stored within the terminal.

[0499] Step 2:

[0500] The terminal anonymizes the entered financial information and sends it to the server. Anonymization ensures that the information is handled in a way that makes personal identification impossible. The output is the anonymized financial data sent to the server.

[0501] Step 3:

[0502] The server stores the received anonymized data in storage. The data is then passed to an AI model for analysis. The input is anonymized financial data, and the output is secure storage in a database.

[0503] Step 4:

[0504] The server uses TensorFlow to perform data analysis with an AI model. The analysis considers past economic data and trends to predict future financial conditions. The input is the data used by the AI ​​model, and the output is the prediction result.

[0505] Step 5:

[0506] The server generates optimal guidance for the user based on the analysis results. This generation process uses a generation AI model to create financial advice in response to prompts. The input is predictive data, and the output is the guidance content.

[0507] Step 6:

[0508] The server notifies the user of the generated guidance via a React Native application. The user can view the advice on their device and, if necessary, change the settings. The input is the guidance content, and the output is the user's expression of intent via notification.

[0509] Step 7:

[0510] The user reviews the received guidance and incorporates it into their future financial planning. Specific actions include viewing advice on the device and adjusting life event reminder functions as needed. The input is the notified advice, and the output is the user's action plan.

[0511] 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.

[0512] This invention is an interactive application that allows users to manage their own financial information while maintaining privacy, and further combines it with an emotion engine to provide more personalized financial advice.

[0513] This system provides an interface on the user's device for initial setup, where they input financial information. The user enters their income, expenses, assets, liabilities, and life event plans. This information is then sent from the device to a server. The server stores the received data in a database and uses AI algorithms to predict future financial situations.

[0514] Furthermore, this invention incorporates an emotion engine that recognizes the user's emotional state. This emotion engine can analyze emotions from the wording, context, and even voice used by the user during input. For example, if it determines that the user is in an emotional or stressful state, it takes that situation into consideration and generates financial advice to reduce stress. The server incorporates this emotional information into its algorithm, adjusts the financial advice, and then notifies the terminal.

[0515] This system displays advice to the user in a visually easy-to-understand format. Furthermore, through personalized, emotion-based communication, users can review and adjust their plans. Notification timing is optimized according to the user's emotions; for example, important notifications are delivered when the user is relaxed.

[0516] As a concrete example, consider a scenario where the terminal recognizes signs of stress from the user's input. The server suggests approaches to reduce stress, such as tools to simplify expense management or methods to alleviate psychological burden. As life events approach, the server supports the user by reminding them of necessary preparations while taking their emotional state into consideration.

[0517] Thus, the present invention provides information that takes into account not only financial data but also the user's emotional state, supporting efficient and humane household management.

[0518] The following describes the processing flow.

[0519] Step 1:

[0520] Users launch the application on their device and use an interface to input their emotional state along with their financial information. This interface allows them to input income, expenses, assets, and liabilities, as well as provide emotionally related questions and feedback.

[0521] Step 2:

[0522] The terminal encrypts the entered financial information and emotional data and sends it to the server via a secure protocol. The server stores the received data in a database for analysis.

[0523] Step 3:

[0524] The server uses AI algorithms to analyze financial information in the database and predict future financial conditions. In addition, it uses an emotion engine to analyze the emotional state expressed by the user. For example, it calculates stress levels and happiness indices and adjusts the data based on these results.

[0525] Step 4:

[0526] The server generates personalized financial advice for the user based on the analysis results. If the emotional state indicates stress, it includes advice to help reduce stress. The generated advice is emotionally appropriate and structured in an actionable way.

[0527] Step 5:

[0528] The server-generated advice and prediction data are organized and prepared for notifications. The user's emotional state is taken into consideration, and notifications are scheduled to arrive at the optimal time.

[0529] Step 6:

[0530] The device receives advice sent from the server and displays it visually to the user. The effectiveness of the advice is further enhanced by soliciting emotion-based feedback.

[0531] Step 7:

[0532] Users review the advice they receive and fine-tune their plans as needed. They can then resubmit their feedback to the server via their device, which will be reflected in future advice.

[0533] (Example 2)

[0534] 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."

[0535] In modern society, users need to manage a wide range of economic data and make future plans. However, conventional systems do not take into account the user's emotional state, making it difficult to provide information that is easy for users to understand and reduces stress. Therefore, the present invention aims to provide personalized information that also takes into account the user's emotional state, in a timely manner, thereby reducing the user's burden and enabling efficient information management.

[0536] 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.

[0537] In this invention, the server includes display means for receiving numerical data from the user, calculation means for analyzing the numerical data and predicting future numerical conditions, and means for analyzing the user's emotional state along with the numerical data using an emotion engine. This makes it possible to provide personalized information based on the user's emotional state.

[0538] "User" is a term that refers to an individual or organization that uses a system.

[0539] "Numerical data" refers to data provided by users, including information about their income, expenses, assets, and liabilities.

[0540] A "display means" is a device that provides a screen or interface for users to input information.

[0541] A "storage medium" is a software or hardware data storage device used to store input numerical data.

[0542] "Computational means" refers to algorithms and processing devices that perform analysis based on data and predict future situations.

[0543] "Information" refers to the results and advice generated using computational methods, and the content provided to the user.

[0544] "Notification methods" refer to methods such as email, messages, and screen notifications used to inform users of generated information.

[0545] An "emotion engine" refers to a program or function that analyzes a user's emotional state based on their input data.

[0546] "Personalized information" refers to advice and reminders tailored based on the user's numerical data and emotional state.

[0547] "External data" refers to information about market fluctuations and economic conditions, and includes data that the system collects independently.

[0548] This system comprehensively analyzes users' numerical data and emotional states to provide personalized information, thereby supporting efficient financial planning. It primarily consists of the following elements:

[0549] Users input numerical data such as income, expenses, assets, and liabilities into the system using a terminal. This information is entered via the user interface and transmitted to the server via a secure communication protocol from the terminal. The entered numerical data is securely stored on the server's storage medium.

[0550] The server uses stored data to execute AI algorithms and predict the user's future financial situation. This process employs generative AI models built in Python or similar programming languages. These models analyze multiple predictor variables to calculate the most suitable financial advice for the user.

[0551] Furthermore, the device uses an emotion engine to analyze the user's speech patterns and tone of voice, scoring the user's emotional state. This emotional data, along with numerical data, is sent to a server, which then adjusts the information based on the analysis results. For example, if the user is feeling stressed, the server might recommend spending management measures to alleviate that stress.

[0552] Information is sent from the server to the terminal and notified to the user in a visually easy-to-understand format. The timing of notifications is optimized to the user's emotional state, so important notifications can be received when the user is relaxed.

[0553] As a concrete example, when a user is planning a trip, the system provides financial advice based on the user's current financial situation and projected future income. Interaction can be initiated using prompts such as, "I'm worried about next month's travel expenses; how should I save money?"

[0554] This system allows users to receive not only information based on numerical data, but also efficient and personalized advice that takes into account their emotional well-being.

[0555] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0556] Step 1:

[0557] Users use a terminal to input numerical data such as income, expenses, assets, and liabilities. This input is done through the user interface and stored on the terminal as numerical data. The terminal then prepares this input data for transmission to the server. This process includes format verification of the collected data and security checks with necessary signatures.

[0558] Step 2:

[0559] The terminal uses a secure communication protocol to send numerical data entered by the user to the server. This communication is encrypted to ensure the reliability of the data. The server verifies the received data and stores it in the appropriate database. During this process, the data format is checked and duplicates with existing data are checked; if there are no duplicates, the data is saved as new data.

[0560] Step 3:

[0561] The server uses a generative AI model to predict future numerical conditions based on stored numerical data. Specifically, it uses a statistical model that analyzes past data to predict future trends. The input is stored numerical data, and the output is predicted data of future numerical conditions. This model calculation is executed by a Python script, ensuring real-time computation.

[0562] Step 4:

[0563] The device uses an emotion engine to analyze the user's emotional state from their voice data and input patterns. This voice data is converted to text using speech recognition technology, and then emotion analysis is performed using natural language processing technology. The input is the user's voice or text, and the output is the result of the emotional state analysis. This result is sent to the server along with numerical data.

[0564] Step 5:

[0565] The server combines predicted numerical data with the user's emotional state to generate personalized information. The server takes this data as input and creates specific advice tailored to the user's current challenges. This might include suggestions to refrain from purchasing financial products or to review spending habits. The output is the information provided to the user.

[0566] Step 6:

[0567] The server sends the generated information to the terminal, which then notifies the user. This notification is displayed in a reminder format and is provided through a visually easy-to-understand graphical user interface. The server adjusts the notification timing based on the user's emotional state, sending the notification when it determines the user is relaxed. The output is the notification content that the user sees.

[0568] (Application Example 2)

[0569] 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."

[0570] Existing financial management systems often fail to adequately address human needs such as personalization and stress reduction, as they only provide standardized advice without considering the user's emotional state. Furthermore, there is a need for timely advice that is sensitive to the user's emotions while protecting their privacy.

[0571] 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.

[0572] In this invention, the server includes means for providing an interface for users to input financial information and emotional status information; means for collecting the input financial information and emotional status information and storing it in a database; and means for executing an algorithm that analyzes the stored financial information and emotional status information to predict future financial conditions and generate personalized financial advice based on the user's emotional status. This enables the provision of personalized financial advice according to the user's emotional status and stress-free financial management that takes privacy into consideration.

[0573] An "interface" is a means of providing users with screens and procedures for inputting financial and emotional information.

[0574] A "database" is an information storage location that appropriately organizes and stores collected financial and emotional information, and manages it in a format that can be used for later analysis.

[0575] An "algorithm" is a procedure that analyzes stored information, predicts future financial conditions, and generates financial advice tailored to the user's emotional state.

[0576] "Privacy protection" means anonymizing users' personal and emotional information and processing it in a way that makes it impossible for anyone other than the individual to identify them.

[0577] "Real-time monitoring" is a means of continuously observing changes in users' financial information, sentiment information, and market data, and updating advice as needed.

[0578] The system that realizes this invention executes a program on both the user's terminal and the server. The user inputs financial and emotional information into the terminal through an interface. This interface is designed to facilitate user input, and the data is automatically anonymized.

[0579] The device analyzes emotions using an AI camera for facial recognition and voice input. Specifically, it uses OpenCV to determine the user's emotional state from their facial expressions and Google Cloud Speech-to-Text to infer emotions from their tone of voice. This information is sent to a server in real time, where it is stored in a database.

[0580] The server executes stored algorithms based on the collected financial and emotional information. These algorithms utilize generative AI models to predict future financial situations and generate personalized financial advice tailored to the user's emotional state. Furthermore, the server processes all data in an anonymized form to protect user privacy.

[0581] By providing timely advice that takes into account the user's emotional state, it is possible to reduce stress. For example, users who are under stress are provided with tools to simplify spending management, and important notifications are sent when they are relaxed. This allows users to manage their finances rationally and without stress in their daily lives.

[0582] An example of a prompt message is: "Based on data obtained from the camera and voice input, analyze the user's emotional state and check if they are stressed. Based on the analysis results, generate appropriate budget management advice for that day and send a notification."

[0583] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0584] Step 1:

[0585] Users enter financial and emotional information using the device's interface. This information is anonymized to protect privacy and temporarily stored on the device. The entered information includes data on the user's income, expenses, and life events.

[0586] Step 2:

[0587] The device uses an AI camera to analyze the user's facial expressions and OpenCV to identify their emotional state. Simultaneously, it analyzes audio data acquired from the microphone using Google Cloud Speech-to-Text to infer emotions from the tone of voice. The input consists of camera video and audio data, while the output is data related to the user's emotional state.

[0588] Step 3:

[0589] The terminal sends processed financial information and sentiment data to the server. The server receives this data and stores it in a database. The input is anonymized financial information and sentiment data, and the output is the state of storage in the database.

[0590] Step 4:

[0591] The server uses information retrieved from the database to run a generative AI model that predicts the user's future financial situation and generates personalized financial advice based on their emotional state. The input is the information from the database, and the output is the prediction results and advice.

[0592] Step 5:

[0593] The server sends generated advice to the device at a timing optimized for the user's emotional state. The timing of the notifications is adjusted based on emotional data, so that important notifications are sent when the user is relaxed, for example. The input is the generated advice and emotional data, and the output is the notification to the user.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] [Fourth Embodiment]

[0598] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0599] 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.

[0600] 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).

[0601] 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.

[0602] 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.

[0603] 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).

[0604] 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.

[0605] 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.

[0606] 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.

[0607] 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.

[0608] 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.

[0609] 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.

[0610] 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".

[0611] The interactive application of the present invention enables users to manage their financial information and receive necessary advice while maintaining their privacy. Embodiments thereof are described below.

[0612] Upon launching the application on their device, users first access an interface to input their financial information. This interface allows them to enter income, expenses, assets, liabilities, future life events, and more. Once the input is complete, the device sends the data to the server.

[0613] The server stores the user's received financial data in a database and uses an AI algorithm to analyze their future financial situation. This AI algorithm takes into account income trends, spending patterns, and economic trends to predict the user's future financial situation.

[0614] Based on the analysis results, the server generates specific financial advice for the user. This advice concerns financial strategies, such as "You need to increase your monthly savings" or "You should consider certain investment products."

[0615] The generated advice is notified to the user via their device, and the user confirms it. Furthermore, the server provides reminders at appropriate times depending on the user's life events and market conditions. For example, if a user is planning for their child to enter higher education, the system has a function to remind them in advance when preparations need to be made.

[0616] As a concrete example, consider a scenario where a user sets a goal of purchasing a home in five years. In this case, the server calculates the necessary savings based on projected future income and housing price forecasts, and advises the user on how to improve their current financial situation. The server also continuously monitors changes in the housing market and interest rate trends, providing the user with timely information.

[0617] Thus, the application of the present invention provides a concrete means for achieving effective household financial management by providing timely and private financial advice tailored to the user.

[0618] The following describes the processing flow.

[0619] Step 1:

[0620] The user launches the application using their device and is taken to a financial information input screen. Here, they enter their income, expenses, assets, liabilities, and future life event plans. The device validates the data entered by the user to ensure it conforms to the format, and prompts for re-entry if there are any discrepancies.

[0621] Step 2:

[0622] The terminal encrypts the financial information that has passed validation and sends it to the server via a secure communication protocol. The server stores the received data in a database for analysis.

[0623] Step 3:

[0624] The system retrieves data stored on the server and uses AI algorithms to analyze the user's future financial situation. This analysis includes revenue growth forecasting, spending trend analysis, and integration of economic data.

[0625] Step 4:

[0626] The server generates specific advice based on the analysis results to help the user achieve their financial goals. This includes, for example, recommended savings amounts to reach savings targets and investment recommendations.

[0627] Step 5:

[0628] The server formats the generated advice into a user-friendly format and prepares it for notification to the terminal. The terminal receives this information and displays it visually to the user.

[0629] Step 6:

[0630] The user reviews the advice provided, enters additional information as needed, and fine-tunes the plan. The device then sends this information back to the server.

[0631] Step 7:

[0632] The server continuously monitors life events and economic indicators in real time, preparing to send reminders to users at critical moments. This helps users revise their plans in a timely manner.

[0633] (Example 1)

[0634] 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".

[0635] In modern society, it is crucial for individuals to effectively manage their own financial situation and secure future economic stability. However, many people lack the confidence to grasp complex economic information and obtain appropriate economic guidance. To address this problem, a support system is needed that allows users to easily input their financial information and receive specific guidance based on predicted economic conditions. Furthermore, continuous updates of economic guidance in response to changes in external data are required while protecting user privacy.

[0636] 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.

[0637] In this invention, the server includes means for providing a screen for the user to input economic information, means for storing the input economic information in a storage device, means for generating economic guidance for the user based on predicted economic conditions, and means for continuously updating and providing the generated guidance to the user. This allows the user to obtain specific guidance based on their own economic situation and to update the economic guidance with the latest data as needed, while protecting their privacy.

[0638] A "user" is an individual or group that uses the system to manage their own financial information and obtain appropriate financial guidance.

[0639] "Economic information" refers to information entered by users, such as income, expenses, assets, liabilities, and future life events.

[0640] A "screen" is a display device that serves as an interface for users to input information into a system.

[0641] A "storage device" is a hardware or software device used to securely store collected economic information.

[0642] A "computational tool" is an algorithm or computer program used to analyze stored economic information and predict future economic conditions.

[0643] "Economic guidelines" refer to specific action plans and advice provided to users based on predicted economic conditions.

[0644] "Notifications" are a means of communication used to convey generated economic guidelines to users.

[0645] "Means of providing notifications" refers to a function or service within a system that delivers information to users at the time of life events.

[0646] "Means for continuously updating generated guidelines" refers to the process of improving the guidelines to the latest version in response to changes in external data and analysis results, and providing them to the user.

[0647] A "system" is a technological configuration that comprehensively includes these means and is designed to support the user's financial management.

[0648] This invention relates to a system that allows users to effectively manage their financial situation and obtain necessary financial guidance. The system aims to provide specific guidance by having users input their financial information from a terminal, performing analysis based on that information, and providing concrete guidance.

[0649] The user launches the application on their device and inputs financial information such as income, expenses, assets, liabilities, and future life events through the screen. The device provides an interface for sending this information to the server. This information is encrypted and securely transmitted to the server.

[0650] The server stores the input economic information in a storage device. This storage device is a large-capacity database that manages data individually for each user. Once the data is stored, an analysis is performed using a generative AI model installed on the server to predict future economic conditions. This model utilizes machine learning algorithms and can run, for example, in Python.

[0651] Based on the analysis results, the server generates economic guidance for the user. This guidance consists of specific action plans and advice based on the user's current financial situation. The generated guidance is continuously updated to accommodate changes in the user's life events and external environment. The generated guidance is notified to the user via their device.

[0652] As a concrete example of this system, when a user enters a prompt such as, "I want to buy a house in five years. Please tell me about a future financial plan to achieve this goal," the server will present a detailed savings plan based on projected future income and housing market trends, and notify the user of appropriate financial guidance. The user can then put this into action and implement a concrete plan.

[0653] Thus, the system of the present invention enables effective economic management by providing users with simple, reliable, and continuously updated economic guidelines.

[0654] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0655] Step 1:

[0656] The user launches the application on their device and enters financial information using the on-screen input interface. Specifically, they manually enter information such as income, expenses, assets, liabilities, and future life events. This information is temporarily stored on the device. After the user completes the input, the device prepares to send this information to the next processing step.

[0657] Step 2:

[0658] The terminal encrypts the entered economic information and sends it to the server using a secure communication protocol. Specifically, it encrypts the data using the SSL / TLS protocol. The input is the raw economic information entered by the user, and the output is the encrypted data received by the server.

[0659] Step 3:

[0660] The server decrypts the received encrypted data and stores it in storage. This process checks the integrity of the information and verifies that there are no missing or incorrect entries. The input is encrypted economic information, and the output is data stored in the database.

[0661] Step 4:

[0662] The server analyzes stored economic data using a generating AI model. Machine learning algorithms are employed to analyze user income and expenditure trends, and to predict future economic conditions, taking external economic trends into consideration. The input is economic information obtained from the database, and the output is the predicted economic situation.

[0663] Step 5:

[0664] The server generates financial guidance for the user based on predicted economic conditions. In this process, it outputs specific advice tailored to the user's goals and life events. The generated guidance may include, for example, "You need to save a specific amount of money each month" or "Review your risky investments." The input is the analyzed data, and the output is the generated financial guidance.

[0665] Step 6:

[0666] The server sends the generated economic guidelines to the terminal, which then notifies the user. Specifically, the terminal uses its notification function to display the guidelines on the user's screen. The input is the economic guidelines sent from the server, and the output is the information displayed to the user.

[0667] Step 7:

[0668] The server continuously updates the generated economic guidelines to respond to changes in the user's life events and economic environment. This updated information is then provided to the user again via the terminal as needed. Inputs are external economic data and user events, and output is the updated economic guidelines.

[0669] (Application Example 1)

[0670] 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".

[0671] For individuals to effectively manage their finances and develop future economic projections, specific and targeted guidance is necessary. However, providing accurate financial advice based on real-time, ever-changing market data while considering the protection of personal information is not easy. The challenge is to improve this situation and provide an environment where users can develop financial strategies safely and efficiently.

[0672] 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.

[0673] In this invention, the server includes means for providing a device for receiving financial information from a user, means for storing the information in a storage device, means for performing a calculation to predict future financial conditions, means for analyzing income and expenditure patterns using AI technology and constructing appropriate savings and investment strategies, and means including data management and customizable notification functions specifically designed to protect privacy. This enables users to receive accurate financial guidance based on real-time updated information in a privacy-enhanced environment.

[0674] A "user" is an entity that manages its own financial information using an application.

[0675] "Financial information" refers to economic data such as a user's income, expenses, assets, and liabilities.

[0676] "Device" refers to hardware or software that provides an interface for users to input financial information.

[0677] A "memory device" is a digital storage medium used to store entered financial information.

[0678] "Calculation method" refers to the process of analyzing data using algorithms to predict future financial conditions.

[0679] "AI technology" refers to technologies that utilize machine learning and data analysis to analyze users' income and spending patterns.

[0680] "Income and expenditure patterns" refer to trends in the increase or decrease of income and expenditure in a user's economic activities.

[0681] A "savings and investment strategy" is a specific plan or guideline designed to achieve a user's long-term financial goals.

[0682] "Privacy protection" refers to measures taken to prevent users' personal information from being used inappropriately by third parties.

[0683] "Data management" refers to the process of securely handling, storing, and updating users' financial information.

[0684] A "customizable notification feature" is a function that notifies users of necessary information at the appropriate time, according to their settings.

[0685] To realize this invention, the user first uses a terminal to input financial information through an interface. This terminal includes smartphones and computers, and the UI has forms that allow the user to input data such as income, expenses, assets, and liabilities. The entered information is stored in a storage device, and to protect the user's privacy, the information is sent to the server after undergoing an anonymization process.

[0686] The server runs on the cloud and manages data using the Django framework. The server uses AI technology, specifically TensorFlow, with the received financial information to predict the user's future financial situation. Machine learning models are used for analysis, employing calculation methods that incorporate historical economic data and trends. Based on the predicted results, it designs and generates optimal savings and investment strategies for the user as guidance.

[0687] Guidance content is communicated to the user through a React Native-based application. These notifications are customizable and can send and receive alerts based on user-defined life events. This functionality allows users to receive real-time information and guidance in a private environment, making financial management easier and more effective.

[0688] For example, if a user aims to buy a house in five years, the server will calculate the amount of savings needed based on projected income and market changes, and advise on an appropriate savings strategy. Examples of prompts include: "If my income increases next year, what is the best investment strategy?" and "What is a savings plan for my children's education?"

[0689] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0690] Step 1:

[0691] The user uses a terminal to input financial information into the interface. The data entered includes items such as income, expenses, assets, and liabilities. The entered information is temporarily stored within the terminal.

[0692] Step 2:

[0693] The terminal anonymizes the entered financial information and sends it to the server. Anonymization ensures that the information is handled in a way that makes personal identification impossible. The output is the anonymized financial data sent to the server.

[0694] Step 3:

[0695] The server stores the received anonymized data in storage. The data is then passed to an AI model for analysis. The input is anonymized financial data, and the output is secure storage in a database.

[0696] Step 4:

[0697] The server uses TensorFlow to perform data analysis with an AI model. The analysis considers past economic data and trends to predict future financial conditions. The input is the data used by the AI ​​model, and the output is the prediction result.

[0698] Step 5:

[0699] The server generates optimal guidance for the user based on the analysis results. This generation process uses a generation AI model to create financial advice in response to prompts. The input is predictive data, and the output is the guidance content.

[0700] Step 6:

[0701] The server notifies the user of the generated guidance via a React Native application. The user can view the advice on their device and, if necessary, change the settings. The input is the guidance content, and the output is the user's expression of intent via notification.

[0702] Step 7:

[0703] The user reviews the received guidance and incorporates it into their future financial planning. Specific actions include viewing advice on the device and adjusting life event reminder functions as needed. The input is the notified advice, and the output is the user's action plan.

[0704] 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.

[0705] This invention is an interactive application that allows users to manage their own financial information while maintaining privacy, and further combines it with an emotion engine to provide more personalized financial advice.

[0706] This system provides an interface on the user's device for initial setup, where they input financial information. The user enters their income, expenses, assets, liabilities, and life event plans. This information is then sent from the device to a server. The server stores the received data in a database and uses AI algorithms to predict future financial situations.

[0707] Furthermore, this invention incorporates an emotion engine that recognizes the user's emotional state. This emotion engine can analyze emotions from the wording, context, and even voice used by the user during input. For example, if it determines that the user is in an emotional or stressful state, it takes that situation into consideration and generates financial advice to reduce stress. The server incorporates this emotional information into its algorithm, adjusts the financial advice, and then notifies the terminal.

[0708] This system displays advice to the user in a visually easy-to-understand format. Furthermore, through personalized, emotion-based communication, users can review and adjust their plans. Notification timing is optimized according to the user's emotions; for example, important notifications are delivered when the user is relaxed.

[0709] As a concrete example, consider a scenario where the terminal recognizes signs of stress from the user's input. The server suggests approaches to reduce stress, such as tools to simplify expense management or methods to alleviate psychological burden. As life events approach, the server supports the user by reminding them of necessary preparations while taking their emotional state into consideration.

[0710] Thus, the present invention provides information that takes into account not only financial data but also the user's emotional state, supporting efficient and humane household management.

[0711] The following describes the processing flow.

[0712] Step 1:

[0713] Users launch the application on their device and use an interface to input their emotional state along with their financial information. This interface allows them to input income, expenses, assets, and liabilities, as well as provide emotionally related questions and feedback.

[0714] Step 2:

[0715] The terminal encrypts the entered financial information and emotional data and sends it to the server via a secure protocol. The server stores the received data in a database for analysis.

[0716] Step 3:

[0717] The server uses AI algorithms to analyze financial information in the database and predict future financial conditions. In addition, it uses an emotion engine to analyze the emotional state expressed by the user. For example, it calculates stress levels and happiness indices and adjusts the data based on these results.

[0718] Step 4:

[0719] The server generates personalized financial advice for the user based on the analysis results. If the emotional state indicates stress, it includes advice to help reduce stress. The generated advice is emotionally appropriate and structured in an actionable way.

[0720] Step 5:

[0721] The server-generated advice and prediction data are organized and prepared for notifications. The user's emotional state is taken into consideration, and notifications are scheduled to arrive at the optimal time.

[0722] Step 6:

[0723] The device receives advice sent from the server and displays it visually to the user. The effectiveness of the advice is further enhanced by soliciting emotion-based feedback.

[0724] Step 7:

[0725] Users review the advice they receive and fine-tune their plans as needed. They can then resubmit their feedback to the server via their device, which will be reflected in future advice.

[0726] (Example 2)

[0727] 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".

[0728] In modern society, users need to manage a wide range of economic data and make future plans. However, conventional systems do not take into account the user's emotional state, making it difficult to provide information that is easy for users to understand and reduces stress. Therefore, the present invention aims to provide personalized information that also takes into account the user's emotional state, in a timely manner, thereby reducing the user's burden and enabling efficient information management.

[0729] 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.

[0730] In this invention, the server includes display means for receiving numerical data from the user, calculation means for analyzing the numerical data and predicting future numerical conditions, and means for analyzing the user's emotional state along with the numerical data using an emotion engine. This makes it possible to provide personalized information based on the user's emotional state.

[0731] "User" is a term that refers to an individual or organization that uses a system.

[0732] "Numerical data" refers to data provided by users, including information about their income, expenses, assets, and liabilities.

[0733] A "display means" is a device that provides a screen or interface for users to input information.

[0734] A "storage medium" is a software or hardware data storage device used to store input numerical data.

[0735] "Computational means" refers to algorithms and processing devices that perform analysis based on data and predict future situations.

[0736] "Information" refers to the results and advice generated using computational methods, and the content provided to the user.

[0737] "Notification methods" refer to methods such as email, messages, and screen notifications used to inform users of generated information.

[0738] An "emotion engine" refers to a program or function that analyzes a user's emotional state based on their input data.

[0739] "Personalized information" refers to advice and reminders tailored based on the user's numerical data and emotional state.

[0740] "External data" refers to information about market fluctuations and economic conditions, and includes data that the system collects independently.

[0741] This system comprehensively analyzes users' numerical data and emotional states to provide personalized information, thereby supporting efficient financial planning. It primarily consists of the following elements:

[0742] Users input numerical data such as income, expenses, assets, and liabilities into the system using a terminal. This information is entered via the user interface and transmitted to the server via a secure communication protocol from the terminal. The entered numerical data is securely stored on the server's storage medium.

[0743] The server uses stored data to execute AI algorithms and predict the user's future financial situation. This process employs generative AI models built in Python or similar programming languages. These models analyze multiple predictor variables to calculate the most suitable financial advice for the user.

[0744] Furthermore, the device uses an emotion engine to analyze the user's speech patterns and tone of voice, scoring the user's emotional state. This emotional data, along with numerical data, is sent to a server, which then adjusts the information based on the analysis results. For example, if the user is feeling stressed, the server might recommend spending management measures to alleviate that stress.

[0745] Information is sent from the server to the terminal and notified to the user in a visually easy-to-understand format. The timing of notifications is optimized to the user's emotional state, so important notifications can be received when the user is relaxed.

[0746] As a concrete example, when a user is planning a trip, the system provides financial advice based on the user's current financial situation and projected future income. Interaction can be initiated using prompts such as, "I'm worried about next month's travel expenses; how should I save money?"

[0747] This system allows users to receive not only information based on numerical data, but also efficient and personalized advice that takes into account their emotional well-being.

[0748] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0749] Step 1:

[0750] Users use a terminal to input numerical data such as income, expenses, assets, and liabilities. This input is done through the user interface and stored on the terminal as numerical data. The terminal then prepares this input data for transmission to the server. This process includes format verification of the collected data and security checks with necessary signatures.

[0751] Step 2:

[0752] The terminal uses a secure communication protocol to send numerical data entered by the user to the server. This communication is encrypted to ensure the reliability of the data. The server verifies the received data and stores it in the appropriate database. During this process, the data format is checked and duplicates with existing data are checked; if there are no duplicates, the data is saved as new data.

[0753] Step 3:

[0754] The server uses a generative AI model to predict future numerical conditions based on stored numerical data. Specifically, it uses a statistical model that analyzes past data to predict future trends. The input is stored numerical data, and the output is predicted data of future numerical conditions. This model calculation is executed by a Python script, ensuring real-time computation.

[0755] Step 4:

[0756] The device uses an emotion engine to analyze the user's emotional state from their voice data and input patterns. This voice data is converted to text using speech recognition technology, and then emotion analysis is performed using natural language processing technology. The input is the user's voice or text, and the output is the result of the emotional state analysis. This result is sent to the server along with numerical data.

[0757] Step 5:

[0758] The server combines predicted numerical data with the user's emotional state to generate personalized information. The server takes this data as input and creates specific advice tailored to the user's current challenges. This might include suggestions to refrain from purchasing financial products or to review spending habits. The output is the information provided to the user.

[0759] Step 6:

[0760] The server sends the generated information to the terminal, which then notifies the user. This notification is displayed in a reminder format and is provided through a visually easy-to-understand graphical user interface. The server adjusts the notification timing based on the user's emotional state, sending the notification when it determines the user is relaxed. The output is the notification content that the user sees.

[0761] (Application Example 2)

[0762] 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".

[0763] Existing financial management systems often fail to adequately address human needs such as personalization and stress reduction, as they only provide standardized advice without considering the user's emotional state. Furthermore, there is a need for timely advice that is sensitive to the user's emotions while protecting their privacy.

[0764] 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.

[0765] In this invention, the server includes means for providing an interface for users to input financial information and emotional status information; means for collecting the input financial information and emotional status information and storing it in a database; and means for executing an algorithm that analyzes the stored financial information and emotional status information to predict future financial conditions and generate personalized financial advice based on the user's emotional status. This enables the provision of personalized financial advice according to the user's emotional status and stress-free financial management that takes privacy into consideration.

[0766] An "interface" is a means of providing users with screens and procedures for inputting financial and emotional information.

[0767] A "database" is an information storage location that appropriately organizes and stores collected financial and emotional information, and manages it in a format that can be used for later analysis.

[0768] An "algorithm" is a procedure that analyzes stored information, predicts future financial conditions, and generates financial advice tailored to the user's emotional state.

[0769] "Privacy protection" means anonymizing users' personal and emotional information and processing it in a way that makes it impossible for anyone other than the individual to identify them.

[0770] "Real-time monitoring" is a means of continuously observing changes in users' financial information, sentiment information, and market data, and updating advice as needed.

[0771] The system that realizes this invention executes a program on both the user's terminal and the server. The user inputs financial and emotional information into the terminal through an interface. This interface is designed to facilitate user input, and the data is automatically anonymized.

[0772] The device analyzes emotions using an AI camera for facial recognition and voice input. Specifically, it uses OpenCV to determine the user's emotional state from their facial expressions and Google Cloud Speech-to-Text to infer emotions from their tone of voice. This information is sent to a server in real time, where it is stored in a database.

[0773] The server executes stored algorithms based on the collected financial and emotional information. These algorithms utilize generative AI models to predict future financial situations and generate personalized financial advice tailored to the user's emotional state. Furthermore, the server processes all data in an anonymized form to protect user privacy.

[0774] By providing timely advice that takes into account the user's emotional state, it is possible to reduce stress. For example, users who are under stress are provided with tools to simplify spending management, and important notifications are sent when they are relaxed. This allows users to manage their finances rationally and without stress in their daily lives.

[0775] An example of a prompt message is: "Based on data obtained from the camera and voice input, analyze the user's emotional state and check if they are stressed. Based on the analysis results, generate appropriate budget management advice for that day and send a notification."

[0776] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0777] Step 1:

[0778] Users enter financial and emotional information using the device's interface. This information is anonymized to protect privacy and temporarily stored on the device. The entered information includes data on the user's income, expenses, and life events.

[0779] Step 2:

[0780] The device uses an AI camera to analyze the user's facial expressions and OpenCV to identify their emotional state. Simultaneously, it analyzes audio data acquired from the microphone using Google Cloud Speech-to-Text to infer emotions from the tone of voice. The input consists of camera video and audio data, while the output is data related to the user's emotional state.

[0781] Step 3:

[0782] The terminal sends processed financial information and sentiment data to the server. The server receives this data and stores it in a database. The input is anonymized financial information and sentiment data, and the output is the state of storage in the database.

[0783] Step 4:

[0784] The server uses information retrieved from the database to run a generative AI model that predicts the user's future financial situation and generates personalized financial advice based on their emotional state. The input is the information from the database, and the output is the prediction results and advice.

[0785] Step 5:

[0786] The server sends generated advice to the device at a timing optimized for the user's emotional state. The timing of the notifications is adjusted based on emotional data, so that important notifications are sent when the user is relaxed, for example. The input is the generated advice and emotional data, and the output is the notification to the user.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] 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.

[0793] 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.

[0794] 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.

[0795] 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."

[0796] 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.

[0797] 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.

[0798] 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.

[0799] 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.

[0800] 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.

[0801] 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.

[0802] 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.

[0803] 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.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] 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.

[0808] The following is further disclosed regarding the embodiments described above.

[0809] (Claim 1)

[0810] A means of providing an interface for users to input financial information,

[0811] A means of collecting input financial information and storing it in a database,

[0812] A means of executing an algorithm that analyzes stored financial information to predict future financial conditions,

[0813] A means of generating financial advice for users based on their predicted financial situation,

[0814] A means of notifying users of advice,

[0815] A means of providing reminders to users at the timing of life events,

[0816] A system that includes this.

[0817] (Claim 2)

[0818] The system according to claim 1, comprising means for anonymizing and processing user input information for the purpose of protecting privacy.

[0819] (Claim 3)

[0820] The system according to claim 1, comprising means for monitoring changes in the user's financial information and market data in real time and updating financial advice as necessary.

[0821] "Example 1"

[0822] (Claim 1)

[0823] A means of providing a screen for users to input economic information,

[0824] A means for collecting input economic information and storing it in a memory device,

[0825] A computing means that analyzes stored economic information to predict future economic conditions,

[0826] A means of generating economic guidance for users based on predicted economic conditions,

[0827] Means of notifying users of the guidelines,

[0828] A means of providing notifications to users at the timing of life events,

[0829] A means of continuously updating and providing the generated guidelines to users,

[0830] A system that includes this.

[0831] (Claim 2)

[0832] The system according to claim 1, which processes user input information anonymized for the purpose of protecting confidentiality.

[0833] (Claim 3)

[0834] The system according to claim 1, which monitors changes in the user's economic information and external data in real time and updates economic guidelines as necessary.

[0835] "Application Example 1"

[0836] (Claim 1)

[0837] A means of providing a device for allowing users to input financial information,

[0838] A means for collecting input financial information and storing it in a memory device,

[0839] A means for performing a calculation method that analyzes stored financial information to predict future financial conditions,

[0840] A means of generating financial guidance for users based on their projected financial situation,

[0841] A means of notifying users of the guidance,

[0842] Means of providing users with warnings during life events,

[0843] A means of analyzing income and expenditure patterns using AI technology to construct appropriate savings and investment strategies,

[0844] This includes data management and customizable notification features specifically designed for privacy protection.

[0845] A system that includes this.

[0846] (Claim 2)

[0847] The system according to claim 1, comprising means for anonymizing and processing user input information for the purpose of protecting privacy.

[0848] (Claim 3)

[0849] The system according to claim 1, comprising means for immediately monitoring changes in the user's financial information and external information and updating financial guidance as necessary.

[0850] "Example 2 of combining an emotion engine"

[0851] (Claim 1)

[0852] A display means for allowing users to input numerical data,

[0853] A means for collecting input numerical data and storing it in a storage medium,

[0854] A computational means that analyzes stored numerical data to predict future numerical conditions,

[0855] A means of generating information for the user based on predicted numerical conditions,

[0856] Means of notifying users of information,

[0857] A method for analyzing a user's emotional state using an emotion engine along with numerical data,

[0858] A means of adjusting information based on analysis results and providing personalized information tailored to the user's situation,

[0859] A means to optimize the timing of notifications based on the user's emotional state,

[0860] A system that includes this.

[0861] (Claim 2)

[0862] The system according to claim 1, comprising means for anonymizing and processing input information.

[0863] (Claim 3)

[0864] The system according to claim 1, comprising means for monitoring changes in user numerical data and external data in real time and updating the information as necessary.

[0865] "Application example 2 when combining with an emotional engine"

[0866] (Claim 1)

[0867] A means of providing an interface for users to input financial information and information regarding their emotional state,

[0868] A means for collecting input financial and sentiment information and storing it in a database,

[0869] A means for executing an algorithm that analyzes stored financial and emotional information to predict future financial conditions and generates personalized financial advice based on the user's emotional state,

[0870] A means of providing advice at the appropriate time based on the user's emotional state,

[0871] A means of providing reminders that take into account the user's emotional state at the timing of life events,

[0872] A system that includes this.

[0873] (Claim 2)

[0874] The system according to claim 1, comprising means for anonymizing and processing user input information and emotional information for the purpose of protecting privacy.

[0875] (Claim 3)

[0876] The system according to claim 1, comprising means for monitoring changes in a user's financial information, sentiment information, and market data in real time, and updating financial advice based on sentiment as necessary. [Explanation of symbols]

[0877] 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 providing an interface for users to input financial information, A means of collecting input financial information and storing it in a database, A means of executing an algorithm that analyzes stored financial information to predict future financial conditions, A means of generating financial advice for users based on their predicted financial situation, A means of notifying users of advice, A means of providing reminders to users at the timing of life events, A system that includes this.

2. The system according to claim 1, comprising means for anonymizing and processing user input information for the purpose of protecting privacy.

3. The system according to claim 1, comprising means for monitoring changes in the user's financial information and market data in real time and updating financial advice as necessary.

Images