System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving financial data from a user; generative artificial intelligence means for generating an investment portfolio based on the financial data; and means for presenting the investment portfolio to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional asset management systems generally provide uniform investment advice, or users lacking financial knowledge face the problem of difficulty in effectively managing their assets. Furthermore, many lack the functionality to provide preventative measures against future financial risks or respond to market fluctuations in real time. Furthermore, the lack of educational content to improve users' financial literacy makes it difficult for users to effectively manage their assets on their own initiative. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system including a means for receiving financial data from a user, a generative artificial intelligence means for generating an investment portfolio based on the financial data, and a means for presenting the investment portfolio to the user. In one aspect of the present invention, the system further includes a means for collecting and analyzing market data to assess the impact on the user's investment portfolio in real time and notifying the user. The system also provides a means for assessing future financial risks based on the user's financial data, generating preventative measures, and presenting them to the user. The system further includes a means for generating and providing educational content aimed at improving the user's financial literacy, and a means for tracking the user's learning progress. The present invention enables users to achieve individually tailored asset management and improve their financial stability while preparing for future risks.

[0006] A "user" is an entity that uses this system to input financial data and receive an individually optimized investment portfolio and various proposals.

[0007] "Financial data" refers to information that indicates the user's financial situation, such as income, expenditure, savings, and investment information.

[0008] "Generative AI" is an AI technology used to generate output tailored to a specific purpose (in this case, generating an investment portfolio) based on input data.

[0009] An "investment portfolio" is a set of investment targets organized based on a user's investment goals and risk tolerance.

[0010] "Market Data" means data related to financial markets, such as stocks, market indices, exchange rates, and economic indicators.

[0011] "Risk assessment" is an analytical tool for assessing the impact of future uncertain events on a user's financial position.

[0012] "Preventive measures" are actions or measures recommended to reduce or avoid financial risk.

[0013] "Educational Content" is educational material such as articles, video tutorials, and quizzes designed to improve users' financial literacy.

[0014] "Learning progress" is information indicating what the user has learned through educational content and their level of understanding.

[0015] A "notification" is information or suggestions sent by the system to a user. [Brief explanation of the drawings]

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

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

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

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

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

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

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

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

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

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

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

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

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

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

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

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

[0037] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[0038] The program processing of this system will be specifically explained below.

[0039] 1. Enter your user information:

[0040] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters this information into the terminal and clicks the submit button. The entered financial data is then sent to the server.

[0041] 2. Receiving and analyzing financial data:

[0042] The server analyzes the received financial data and utilizes generative artificial intelligence to assess the user's risk tolerance, financial goals, and current asset mix, based on which the server generates an optimal investment portfolio for the user.

[0043] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0044] 3. Portfolio Presentation:

[0045] The server sends the generated investment portfolio to the user's terminal, which displays it to the user, who can review the presented portfolio and adjust it as needed.

[0046] 4. Real-time market data collection and evaluation:

[0047] The server periodically collects market data and evaluates its impact on the user's investment portfolio in real time. When a significant market movement is detected, the server analyzes its impact and generates a notification for the user, which is sent to the user's device and displayed immediately.

[0048] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0049] 5. Preventive Risk Assessment:

[0050] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks, and then suggests specific preventive measures to the user based on the results of the evaluation.

[0051] 6. Education and Literacy:

[0052] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0053] These features allow users to make sound investment decisions, prepare for future risks, and improve financial stability.

[0054] The processing flow will be explained below.

[0055] Step 1:

[0056] The terminal displays a form for the user to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[0057] Step 2:

[0058] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[0059] Step 3:

[0060] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[0061] Step 4:

[0062] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[0063] Step 5:

[0064] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[0065] Step 6:

[0066] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0067] Step 7:

[0068] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[0069] Step 8:

[0070] The server evaluates future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, it generates recommendations for preventive measures (e.g., insurance products and emergency funds) for the user.

[0071] Step 9:

[0072] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[0073] Step 10:

[0074] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[0075] These processing steps enable users to achieve effective asset management and improve financial stability while preparing for future risks.

[0076] Example 1

[0077] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0078] Today's users have a wide variety of financial data, and there is a growing need for the ability to build optimal investment portfolios based on that data, reflect market data in real time, and evaluate future financial risks and provide preventative measures. However, conventional systems struggle to provide these functions in an integrated manner, forcing users to manually collect and analyze multiple pieces of information and make appropriate investment decisions. This places a significant burden on users and can delay their decision-making. Furthermore, there are limited means of providing educational content to improve financial literacy, leaving users with insufficient opportunities to acquire appropriate knowledge.

[0079] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0080] In this invention, the server includes means for receiving financial data from a user, a generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the financial data and market data and evaluating it in real time, means for notifying the user based on the evaluation results, and means for generating educational content to improve the user's financial knowledge. This allows the user to receive appropriate investment portfolio suggestions, enables investment decisions that reflect fluctuations in market data in real time, and provides prompt preventative measures against future financial risks. Educational content to improve the user's financial literacy is also provided, enabling efficient and effective comprehensive financial management.

[0081] "User" means any person or entity that inputs financial data and uses the investment portfolio, notifications, and educational content provided by the System.

[0082] "Financial Data" refers to information that indicates a user's financial status, such as income, expenses, savings, and investment information.

[0083] "Generative AI" refers to an AI technology that suggests optimal investment portfolios based on input data.

[0084] "Investment portfolio" refers to an investment plan that appropriately allocates a user's assets among stocks, bonds, real estate, cash, etc.

[0085] "Market data" refers to data showing trends in stock prices, bond yields, real estate prices, etc. in financial markets.

[0086] "Real-time" refers to a state in which data collection, analysis, notification, and other processes are carried out immediately without delay.

[0087] "Notifications" refer to information sent to users based on market movements and their impact on their investment portfolios.

[0088] "Preventive measures" refer to suggestions and advice on how to respond appropriately to future financial risks.

[0089] "Educational Content" refers to articles, video tutorials, quizzes, and other educational materials provided to improve a user's financial knowledge.

[0090] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[0091] System configuration

[0092] Entering user information

[0093] The terminal displays a form for the user to enter income, expenditure, savings, and investment information. This form is installed on a web browser using HTML and JavaScript. The user enters information such as income, expenditure, and savings and clicks the "Submit" button. This input data is converted to JSON format and sent to the server using the HTTPS protocol.

[0094] Receiving and analyzing financial data

[0095] The server receives financial data sent by the user using a Python framework. The received data is preprocessed and passed to a generative AI model (e.g., GPT-4). Using the following prompt, the AI ​​model analyzes the user's financial data and generates an optimal investment portfolio.

[0096] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[0097] The resulting portfolio may be allocated, for example, as 40% stocks, 30% bonds, 20% real estate, and 10% cash.

[0098] Portfolio presentation

[0099] The server converts the generated investment portfolio into JSON format and sends it to the terminal. The terminal visualizes this data using HTML and JavaScript and presents it to the user in the form of graphs, etc. The user can review the portfolio and adjust it as needed.

[0100] Real-time market data collection and evaluation

[0101] The server periodically collects real-time market data through market data APIs (e.g., Alpha Vantage and Yahoo Finance). This data is used to evaluate the impact on the user's investment portfolio in real time. When there is a significant market fluctuation, the following prompt sentence is passed to the AI ​​model for evaluation:

[0102] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[0103] The server generates a notification for the user based on the analysis results, sends it to the terminal in JSON format, and displays it immediately.

[0104] Preventive Risk Assessment

[0105] The server uses Python statistical analysis libraries (e.g., pandas and scikit-learn) to assess future financial risks based on the user's financial data, analyzing income fluctuations, changes in economic conditions, health risks, etc., and recommends specific preventive measures to the user as needed.

[0106] Education and Literacy

[0107] The server uses the generative AI model to generate educational content to improve the user's financial literacy. The content is generated using the following prompt sentence as an example.

[0108] "Generate educational content on the fundamentals of investing that your users are interested in."

[0109] The generated educational content includes articles, video tutorials, quizzes, etc., and is provided to the user via their device. The learning progress is tracked by the server, and additional educational content is provided based on the user's level of understanding.

[0110] These features allow users to make appropriate investment decisions, prepare for future risks, and improve financial stability.

[0111] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0112] Step 1:

[0113] Entering user information

[0114] The terminal displays a form using HTML and JavaScript for the user to enter income, expenditure, savings, and investment information.

[0115] Input: User's income, expenses, savings, and investment information.

[0116] Behavior: Validates input using JavaScript.

[0117] Output: Validated financial data.

[0118] The user enters information such as income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, and clicks the "Submit" button.

[0119] What it does: Form input data is converted to JSON format.

[0120] Output: Financial data in JSON format.

[0121] The terminal sends the generated financial data in JSON format to the server via the HTTPS protocol.

[0122] Input: Financial data in JSON format.

[0123] How it works: Encodes transmitted data and sends it securely via HTTPS.

[0124] Output: Connection established with the server and notification of completion.

[0125] Step 2:

[0126] Receiving and analyzing financial data

[0127] The server receives the HTTPS request to receive financial data from the user.

[0128] Input: Financial data in JSON format sent from the terminal.

[0129] What it does: Decodes and receives data, then processes it in a Python framework (e.g. Flask).

[0130] Output: Financial data in internal data format.

[0131] The server preprocesses the received data and passes it to a generative AI model (e.g., GPT-4).

[0132] Input: Financial data in internal data format.

[0133] Action: Any necessary data transformations and preprocessing (e.g., data normalization).

[0134] Output: A prompt to the generative AI model.

[0135] The generative AI model is passed the following prompts to generate an optimal investment portfolio based on the user's risk tolerance and financial goals.

[0136] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[0137] How it works: Analyzes generative AI models and generates portfolios based on prompts.

[0138] Output: An investment portfolio generated by the AI ​​model (e.g., 40% stocks, 30% bonds, 20% real estate, 10% cash).

[0139] Step 3:

[0140] Portfolio presentation

[0141] The server converts the generated investment portfolio into JSON format and sends it to the terminal.

[0142] Input: An investment portfolio generated by an AI model.

[0143] What it does: Converts portfolio data into JSON format.

[0144] Output: Investment portfolio data in JSON format.

[0145] The terminal uses HTML and JavaScript to visualize the received investment portfolio in graphs and other formats and presents it to the user.

[0146] Input: Investment portfolio data in JSON format.

[0147] How it works: Visualization is done using a graphing library (e.g. D3.js, Chart.js).

[0148] Output: A visualized portfolio (e.g., graphs and charts).

[0149] The user reviews the presented portfolio and makes adjustments as necessary.

[0150] Action: Portfolio adjustment (e.g. increase stock percentage to 50%).

[0151] Output: Adjusted portfolio data.

[0152] Step 4:

[0153] Real-time market data collection and evaluation

[0154] The server periodically collects real-time market data via market data APIs (e.g., Alpha Vantage, Yahoo Finance).

[0155] Input: Market data obtained from API.

[0156] How it works: Collects data using HTTP requests.

[0157] Output: Real-time market data.

[0158] The server analyzes the collected market data and assesses its impact on the user's investment portfolio.

[0159] Input: Real-time market data and user's investment portfolio.

[0160] Actions: Use data analysis libraries (e.g. pandas, NumPy) to assess impact.

[0161] Output: Evaluation results.

[0162] If a significant market fluctuation is detected, the server passes the following prompts to the AI ​​model to generate a countermeasure:

[0163] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[0164] Action: Impact assessment and countermeasure generation using AI models.

[0165] Output: Specific notification and action to the user.

[0166] The device immediately displays notifications received from the server to the user using HTML and JavaScript.

[0167] Input: Notification data received from the server.

[0168] Action: Show a notification (e.g. popup, alert).

[0169] Output: A notification is displayed to the user.

[0170] Step 5:

[0171] Preventive Risk Assessment

[0172] The server uses Python statistical analysis libraries (e.g., pandas, scikit-learn) to assess future financial risk based on the user's financial data.

[0173] Input: User's financial data.

[0174] Behavior: Application of statistical analysis and predictive models.

[0175] Output: Risk assessment results.

[0176] The server generates preventive measures based on the risk assessment results and presents them to the user.

[0177] Input: Risk assessment results.

[0178] Action: Generate preventative measures (using AI models).

[0179] Output: Provides specific preventive measures to the user.

[0180] Step 6:

[0181] Education and Literacy

[0182] The server uses the generative AI model to generate educational content to improve the user's financial literacy.

[0183] Input: User's learning needs.

[0184] How it works: Generating educational content using AI models.

[0185] Output: Financial education content.

[0186] The server sends the generated educational content to the terminal in JSON format.

[0187] Input: Generated educational content.

[0188] Operation: Convert to JSON format and send.

[0189] Output: Educational content in JSON format.

[0190] The device displays educational content using HTML and JavaScript and tracks the user's learning progress.

[0191] Input: Educational content in JSON format.

[0192] What it does: Presents educational content and tracks progress.

[0193] Output: User's learning progress data.

[0194] (Application example 1)

[0195] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0196] Conventional financial management systems struggled to provide optimal investment portfolios based on users' individual financial data, and lacked the functionality to collect and analyze market data in real time and immediately notify users of its impact on their investment portfolios. This made it difficult for users to make timely and appropriate investment decisions, and they were inadequately prepared for future financial risks. Furthermore, there was no system in place that provided educational content to help improve financial literacy, so it was difficult to expect users' financial knowledge to improve.

[0197] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0198] In this invention, the server includes a means for receiving financial data from a user, a generating AI model means for generating an investment portfolio based on the financial data, a means for presenting the investment portfolio to the user, and a means for providing educational content to the user, thereby enabling the user to obtain an individually optimized investment portfolio and improve their financial literacy.

[0199] Furthermore, in this invention, the server includes means for collecting market data, means for analyzing the market data to assess the impact on the user's investment portfolio, means for generating and sending notifications to the user in real time based on the assessment results, and means for collecting and analyzing expenditure data in cooperation with a payment service, thereby enabling the user to quickly respond appropriately to real-time market fluctuations.

[0200] Furthermore, in this invention, the server includes means for assessing future financial risks based on the user's financial data, means for generating preventive measures based on the risk assessment results and presenting them to the user, and means for providing additional educational content according to the user's level of understanding, thereby enabling the user to take more specific preventive measures against future financial risks and deepen their financial knowledge.

[0201] "Financial Data" means information about a User's income, expenses, savings, and investments.

[0202] The "generative AI model means" is an artificial intelligence technology that analyzes a user's financial data and generates an optimal investment portfolio.

[0203] An "investment portfolio" is a combination of various financial instruments and assets based on a user's financial goals and risk tolerance.

[0204] "Educational Content" is learning material such as articles, videos, and quizzes designed to improve users' financial literacy.

[0205] "Market data" refers to real-time trading information and related data in financial markets, such as stock prices, bond prices, and exchange rates.

[0206] "Means for generating and sending notifications to users in real time" refers to technology that instantly analyzes important information such as market fluctuations and sends appropriate notifications to users.

[0207] "Means for collecting and analyzing expenditure data in cooperation with payment services" refers to technology that works in cooperation with the electronic payment services used by users to collect expenditure data and integrate it into financial data.

[0208] "Means for assessing future financial risks" refers to technology that predicts and assesses risks associated with a user's financial situation, taking into account factors such as fluctuations in income, changes in economic conditions, and health risks.

[0209] "Means for generating preventive measures and presenting them to users" is a technology that proposes and displays specific measures that users should take in response to assessed financial risks.

[0210] The "means for providing additional educational content according to the user's level of understanding" is a technology that provides optimal additional learning materials based on the user's learning progress and level of understanding.

[0211] This invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data, analyzes it using generative AI, and presents an optimal investment portfolio based on the results. It also provides educational content to improve the user's financial literacy, collects and analyzes market data in real time, and immediately notifies the user of the impact on the investment portfolio.

[0212] The server first receives financial data from the user, including income, expenses, savings, and investment information. The data entered by the user is encrypted and stored in cloud storage. The received data is then analyzed using a generative AI model to evaluate the user's risk tolerance, financial goals, and current asset mix. Based on this, the server generates an optimal investment portfolio for the user and presents it to the user's device.

[0213] Users can review the proposed investment portfolio and adjust it as necessary, and the adjusted portfolio can also be re-analyzed by the AI ​​in real time.

[0214] The server also collects real-time market data via APIs from external financial data providers. Based on this market data, the impact on the user's investment portfolio is assessed, and if significant market fluctuations are detected, the system immediately notifies the user. For example, if there is a major market fluctuation, the system can send a notification such as, "Based on the current market conditions, we recommend reducing your stock portfolio by 10% and allocating that capital to bonds."

[0215] In addition, the system works in conjunction with electronic payment services to collect and analyze users' spending data and reflect it in real-time financial data, allowing users to constantly monitor their spending patterns and more accurately assess their financial situation.

[0216] The server also evaluates future financial risks based on the user's financial data, and generates and presents to the user preventive measures that take into account, for example, fluctuations in income, changes in economic conditions, health risks, etc. This evaluation and preventive measures allow the user to prepare for future unforeseen events.

[0217] Additionally, to improve users' financial literacy, the server generates and provides appropriate educational content to users. The educational content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[0218] For example, if a user inputs their annual income of ¥6 million, monthly expenses of ¥300,000, and savings of ¥1 million, the server will use this data to generate a portfolio with 40% stocks, 30% bonds, 20% real estate, and 10% cash. This information is fed into the generative AI model using the following prompt:

[0219] Example prompt sentence:

[0220] "Analyze this financial data and suggest the optimal investment portfolio:

[0221] Income: 6 million yen

[0222] Expenses: 300,000 yen

[0223] Savings: 1 million yen

[0224] Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen

[0225] In this way, the present invention provides users with an effective means of making optimal financial management and investment proposals and preparing for future financial risks.

[0226] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0227] Step 1:

[0228] Users launch the application on their smartphone and enter their income, expenses, savings, and investment information. This data is encrypted and sent to the server, where it is stored in cloud storage in JSON format.

[0229] Step 2:

[0230] The server inputs the received user's financial data (income, expenses, savings, and investment information) into a generative AI model to generate an optimal investment portfolio. The generative AI model processes and analyzes the data using the analysis prompt: "Analyze this financial data and propose the optimal investment portfolio: Income: 6 million yen, Expenses: 300,000 yen, Savings: 1 million yen, Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen," and outputs the optimal investment portfolio.

[0231] Step 3:

[0232] The server sends the generated investment portfolio to the user's device. The device displays the portfolio in a user-friendly interface, allowing the user to review and adjust it. If the user makes any adjustments, the data is sent back to the server and reanalyzed by the generative AI model.

[0233] Step 4:

[0234] The server collects market data in real time from external financial data providers (e.g., financial market data API). This data includes price fluctuations of financial products and stock price information. The server periodically analyzes this data and evaluates its impact on the user's investment portfolio. The server analyzes the data using the evaluation prompt: "Based on the current market situation, please evaluate the impact on this portfolio and suggest any necessary changes: Portfolio information, Market data" and obtains the impact evaluation results as output.

[0235] Step 5:

[0236] The server generates real-time notifications based on the evaluation results and sends them to the user's terminal. The notifications include specific investment action recommendations (e.g., "We recommend reducing your stock portfolio by 10% and allocating the funds to bonds.") The user receives the notifications on their terminal and adjusts their investment portfolio as necessary.

[0237] Step 6:

[0238] The server works with the electronic payment service to collect and analyze the user's spending data. It obtains data on the user's spending from the payment service and reflects it in real time in the financial data. This allows the user's spending patterns to be tracked and financial management to be more accurate based on spending.

[0239] Step 7:

[0240] The server evaluates future financial risks based on the user's financial data. For example, it takes into account fluctuations in income, changes in economic conditions, health risks, etc., and performs analysis using the risk assessment prompt: "Given the user's current financial situation, assess possible risks and propose preventive measures: financial data, economic data, user information," and obtains a financial risk assessment result as an output.

[0241] Step 8:

[0242] The server generates preventive measures based on the evaluation results and presents them to the user, allowing the user to prepare for future unforeseen events.Specific preventive measures (e.g., insurance product recommendations, emergency savings suggestions) are presented.

[0243] Step 9:

[0244] The server generates and provides educational content to improve users' financial literacy. The content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[0245] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0246] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[0247] The program processing of this system will be specifically explained below.

[0248] 1. Enter your user information:

[0249] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[0250] 2. Receiving and analyzing financial data:

[0251] The server analyzes the received financial data. The server activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[0252] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0253] 3. Portfolio Presentation:

[0254] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[0255] 4. Real-time market data collection and evaluation:

[0256] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0257] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0258] 5. Preventive Risk Assessment:

[0259] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[0260] 6. Education and Literacy:

[0261] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0262] 7. Emotion Recognition and Customization with Emotion Engine:

[0263] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[0264] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[0265] 8. Support and relaxation content:

[0266] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[0267] These features allow users to achieve personalized asset management, prepare for future risks, and improve their financial stability with emotionally sensitive support.

[0268] The processing flow will be explained below.

[0269] Step 1:

[0270] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[0271] Step 2:

[0272] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[0273] Step 3:

[0274] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[0275] Step 4:

[0276] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[0277] Step 5:

[0278] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[0279] Step 6:

[0280] The device captures the user's facial expressions, voice tone, text data, etc. into the emotion engine. The user may interact with the device to provide this data (e.g., answering questions, using the camera, etc.).

[0281] Step 7:

[0282] The emotion engine analyzes the collected data and evaluates the user's emotional state, generating emotion data such as whether the user is relaxed, excited, or stressed.

[0283] Step 8:

[0284] The server receives the emotion data generated by the emotion engine and evaluates the user's current mental state, and customizes financial advice based on the evaluation.

[0285] Step 9:

[0286] If the server determines that the user's emotional state indicates increased stress or anxiety, it can refrain from offering risky investment advice and suggest safer investment options (e.g., bonds or cash). It can also emphasize proactive risk assessment advice if it recognizes the user's state of agitation.

[0287] Step 10:

[0288] The server generates relaxation content based on the user's emotional state, such as relaxation music or guided meditation videos.

[0289] Step 11:

[0290] The server transmits the generated relaxation content to the user's terminal, which displays the content to the user to encourage mental refreshment.

[0291] Step 12:

[0292] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0293] Step 13:

[0294] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[0295] Step 14:

[0296] The server assesses future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, the server recommends specific preventive measures (e.g., insurance products or emergency fund arrangements) to the user.

[0297] Step 15:

[0298] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[0299] Step 16:

[0300] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[0301] These specific processing steps allow users to effectively manage their assets, prepare for future risks, and improve their financial stability while receiving support that takes into account their emotional state.

[0302] Example 2

[0303] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0304] While existing financial analysis systems have the ability to generate investment portfolios based on users' financial data, they lack the ability to respond to users' emotional states and real-time market fluctuations. This leaves users with the problem of having to make investment decisions while feeling stressed and anxious. Furthermore, they lack the provision of educational content to help users address future financial risks and improve their financial knowledge.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0306] In this invention, the server includes a generative artificial intelligence means for receiving financial data from a user and generating an investment portfolio based on the financial data, a means for collecting emotional data from the user and customizing financial advice based on the emotional data, and a means for evaluating the user's mental state and generating relaxation content, thereby enabling the provision of preventive risk assessment and educational content for improving financial knowledge in response to the user's emotional state and real-time market fluctuations.

[0307] "Financial data" refers to data that indicates the user's financial situation, such as income, expenditure, savings, and investment information.

[0308] A "generative artificial intelligence vehicle" is a vehicle that uses artificial intelligence techniques to generate investment portfolios based on financial data.

[0309] "Investment Portfolio" refers to a combination of investment products, such as stocks, bonds, real estate, and cash, created with a particular user's financial goals and risk tolerance in mind.

[0310] "Emotion data" refers to data that indicates the user's emotional state, collected from the user's facial expression, voice tone, text data, and the like.

[0311] The "means for customizing financial advice" is a means for optimizing financial advice for a user based on collected emotional data.

[0312] "Relaxation content" refers to content such as relaxation music and guided meditation videos that are provided to encourage users to refresh their minds.

[0313] "Market data" refers to data related to various markets that affect investment decisions, such as stock market fluctuations, economic indicators, and exchange rates.

[0314] "Means for generating and transmitting notifications to users in real time" refers to means for quickly analyzing fluctuations in market data and, based on the results, generating and transmitting notifications in real time that recommend appropriate investment actions to users.

[0315] "Financial Risk Assessment" refers to the analysis and assessment of potential future risks based on your financial data.

[0316] "Preventive measures" refer to specific actions or measures that users should take in advance to address assessed risks.

[0317] "Educational Content" means learning materials such as articles, video tutorials, and quizzes that are provided to improve a user's financial knowledge.

[0318] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[0319] Hardware and Software Configuration

[0320] The present invention uses the following hardware and software.

[0321] Hardware:

[0322] Terminal: A device (e.g., computer, smartphone, tablet) that provides a user interface for users to enter data.

[0323] Server: The central device that receives data, analyzes it, generates portfolios, sends notifications, etc.

[0324] software:

[0325] Programming language: Python

[0326] Generative AI model: TensorFlow

[0327] Emotion engine: Microsoft Azure Emotion API or AWS Rekognition

[0328] Database management system: MySQL

[0329] Program processing explanation

[0330] 1. Enter your user information:

[0331] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[0332] 2. Receiving and analyzing financial data:

[0333] The server analyzes the received financial data. The server runs a generative artificial intelligence (AI) model to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[0334] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0335] 3. Portfolio Presentation:

[0336] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[0337] 4. Real-time market data collection and evaluation:

[0338] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0339] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0340] 5. Preventive Risk Assessment:

[0341] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[0342] 6. Education and Literacy:

[0343] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0344] 7. Emotion Recognition and Customization with Emotion Engine:

[0345] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[0346] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[0347] 8. Support and relaxation content:

[0348] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[0349] Examples of prompt statements

[0350] Example prompt sentence:

[0351] "Based on market data, due to the current stock market volatility, I would recommend reducing your stock portfolio by 10% to reduce risk and allocating that money to bonds. Also, you can watch a guided meditation video here to help reduce stress."

[0352] In this way, a system is constructed that provides customized advice and support to users that takes into account their individual financial circumstances and emotional state. With this invention, users can manage their assets in an individually optimized manner, and achieve mental stability while preparing for future risks.

[0353] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0354] Step 1: Enter your user information

[0355] The terminal presents the user with a form for entering financial data, including fields for income, expenses, savings, and investment information.

[0356] Input: The user enters income, expenses, savings, and investment information and clicks the submit button.

[0357] Data processing: Convert the data entered by the user into JSON format and send it to the server.

[0358] Output: User's financial data sent to the server.

[0359] Step 2: Receiving and parsing financial data

[0360] The server receives the financial data sent from the user's terminal.

[0361] Input: User's financial data received from the terminal.

[0362] Data Processing and Computation: The server analyzes the received data and processes it using a generative AI model to assess the user's risk tolerance, financial goals, and current asset mix, specifically using Python and TensorFlow.

[0363] Output: Analysis results and optimized investment portfolio.

[0364] Step 3: Generate a portfolio

[0365] The server runs a generative artificial intelligence (AI) model and generates an optimal investment portfolio for the user based on the analysis results.

[0366] Input: Financial data parsed by the server and the user's risk tolerance.

[0367] Data Computing: Generative AI models are used to generate portfolios that take profitability and risk into account.

[0368] Output: Generated investment portfolio (e.g. 40% stocks, 30% bonds, 20% real estate, 10% cash).

[0369] Step 4: Present your portfolio

[0370] The server transmits the generated investment portfolio to the user's terminal.

[0371] Input: Server-generated investment portfolio.

[0372] Output: Display the portfolio on the terminal.

[0373] The device displays the transferred portfolio on the screen, allowing the user to review and adjust it.

[0374] Step 5: Real-time market data collection and evaluation

[0375] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, and currency exchange rates.

[0376] Input: Market data obtained using external APIs and web scraping techniques.

[0377] Data processing and calculation: The server analyzes market fluctuations and assesses their impact on the user's investment portfolio.

[0378] Output: Evaluation results and real-time notifications sent to users.

[0379] For example, if a user's stock holdings suddenly fall, the server may generate and send a notification to the user saying, "Based on current market conditions, we recommend reducing your stock portfolio by 10% and allocating that money to bonds."

[0380] Step 6: Preemptive risk assessment

[0381] The server assesses future financial risk based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks.

[0382] Input: User's financial and market data.

[0383] Data calculation: The server considers multiple risk scenarios and performs a comprehensive risk assessment.

[0384] Output: Predicted risks and recommended preventative measures.

[0385] Based on the evaluation results, the server suggests specific preventive measures to the user.

[0386] Step 7: Education and Literacy

[0387] The server generates appropriate educational content to improve the user's financial knowledge, including articles, video tutorials, and quizzes.

[0388] Input: User comprehension information and current financial knowledge.

[0389] Data processing: Generate educational content and track user learning progress.

[0390] Output: Educational content and learning progress reports.

[0391] The terminal can display the generated educational content to the user and track their learning progress.

[0392] Step 8: Emotion Recognition and Customization with the Emotion Engine

[0393] The terminal or server uses an emotion engine to recognize the user's emotions. It analyzes emotions from the user's facial expressions, voice tone, text data, etc., and transmits the results to the server as emotion data.

[0394] Input: User emotion data.

[0395] Data calculation: The server analyzes the emotion data and evaluates the user's current mental state.

[0396] Output: Sentiment evaluation results and customized advice.

[0397] For example, if the server detects that the user is stressed, it may refrain from providing risky investment advice and suggest safer investment options.

[0398] Step 9: Support and relaxation content

[0399] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos.

[0400] Input: Emotion data and content database.

[0401] Data processing and calculation: Select and generate relaxation content.

[0402] Output: The relaxation content provided to the user.

[0403] The terminal can display these contents to the user to encourage mental refreshment.

[0404] (Application example 2)

[0405] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0406] Previously, there were systems that generated investment portfolios using users' financial data, but they were not customized to take into account the user's emotional state, making it impossible to reduce investment anxiety and stress. Furthermore, they lacked the functionality to analyze market data in real time and send appropriate notifications to users. Furthermore, there was a lack of a system that provided relaxation content based on the user's emotional state. This made it difficult to achieve comprehensive financial management and mental health for users.

[0407] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0408] In this invention, the server includes means for receiving financial data from a user, generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the user's emotional data and evaluating the emotional state, means for customizing investment advice based on the emotional state, and means for generating relaxation content based on the emotional state, thereby enabling the user to receive not only an individually optimized investment portfolio but also investment advice and relaxation content that take into account their emotional state.

[0409] The "means for receiving financial data from a user" refers to the interface and process by which a user inputs financial data such as their income, expenses, savings, and investment information, and the system receives that data.

[0410] A "generative artificial intelligence tool" is an artificial intelligence algorithm and associated system for analyzing input financial data and generating an optimal investment portfolio for a user.

[0411] A "means for presenting an investment portfolio to a user" is an interface and process for displaying the generated investment portfolio on a user's device.

[0412] The "means for analyzing emotional data and assessing an emotional state" refers to software and processes for analyzing emotional data such as a user's facial expression, voice, text, etc., and assessing the user's current emotional state.

[0413] A "means for customizing investment advice based on emotional state" is an algorithm and process for providing appropriate investment advice to a user based on the assessed emotional state.

[0414] A "means for generating relaxation content based on emotional state" is software and processes for generating and providing relaxation content, such as relaxation music or guided meditation videos, based on an assessment of a user's emotional state.

[0415] "Means for collecting market data" refers to algorithms and processes for collecting market data, such as stock market data, economic indicators, and exchange rates, from the Internet and other data sources.

[0416] "Means for analyzing market data to assess the impact on a user's investment portfolio" refers to algorithms and processes for analyzing collected market data and assessing its impact on a user's investment portfolio.

[0417] "Means for generating and sending notifications to users in real time" means software and processes for generating key information and recommendations in real time based on the analysis of market data and sending notifications to users' devices.

[0418] "Means for assessing future financial risks" refers to algorithms and processes for predicting and assessing future financial risks, such as income fluctuations, changes in economic conditions, and health risks, based on the user's current financial data.

[0419] The "means for generating and presenting to a user preventative measures based on the results of risk assessment" refers to software and processes for generating appropriate preventative measures for the assessed financial risks and presenting them to a user's device.

[0420] The "means for providing optimal relaxation content to a user in accordance with emotional data" refers to software and processes for analyzing emotional data and providing relaxation content to reduce the user's stress and anxiety based on the results of the analysis.

[0421] The present invention is a system for analyzing a user's financial and emotional data and providing optimal investment portfolios and relaxation content. This system comprehensively considers the user's financial situation and emotional state and provides optimal advice to support the user's financial management.

[0422] Hardware and software used

[0423] This system is realized using the following hardware and software:

[0424] Hardware: Smartphones, computer servers

[0425] Software: Python, pandas, scikit-learn, TextBlob, generative artificial intelligence

[0426] What the program does

[0427] 1. Enter your user information:

[0428] The device (smartphone) displays a form for the user to enter income, expenditure, savings, and investment information. The user enters this data and clicks the send button to send the data. The sent data is stored on the server.

[0429] 2. Analysis of Financial Data:

[0430] The server analyzes the received financial data and uses generative artificial intelligence to generate an optimal investment portfolio for the user. For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0431] 3. Emotional Data Analysis:

[0432] The terminal or server analyzes the user's emotional data (e.g., facial expressions, voice, and text) and evaluates their emotional state. Based on the evaluated emotional state, it customizes investment advice and generates relaxation content as needed. For example, if it determines that the user is feeling "stressed," it provides relaxation music.

[0433] 4. Portfolio presentation and adjustment:

[0434] The generated investment portfolio is displayed on the user's smartphone. The user can review the portfolio and make adjustments as needed. The adjusted portfolio is also saved in the system for later analysis.

[0435] 5. Real-time market data collection and evaluation:

[0436] The server periodically collects market data, analyzes it, and evaluates the impact on the user's investment portfolio. For example, if the value of stocks drops sharply, a notification will be sent to the user's smartphone saying, "Based on current market conditions, we recommend that you reduce your stock portfolio by 10% and convert that money into bonds."

[0437] Specific examples

[0438] The user entered financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen. The emotion was entered as "stress." Based on this data, the server generated an investment portfolio consisting of 40% stocks, 30% bonds, 20% real estate, and 10% cash, and recommended relaxation music to users who were in a "stressed" state.

[0439] Prompt Sentence Examples

[0440] Based on the financial and emotional data below, please suggest the best investment portfolio and relaxation content for you.

[0441] Income: 6 million yen

[0442] Monthly expenses: 300,000 yen

[0443] Savings: 1 million yen

[0444] Emotion: Stress

[0445] Proposed format:

[0446] 1. Investment Portfolio:

[0447] Stock: XX%

[0448] Bond: XX%

[0449] Real Estate: XX%

[0450] Cash: XX%

[0451] 2. Relaxation Content:

[0452] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0453] Step 1:

[0454] Enter your user information:

[0455] Users enter financial data such as income, expenses, savings, and investment information into an input form on their smartphone. The entered data is sent to the server by clicking the send button. At this time, the input data includes "annual income," "monthly expenses," "savings amount," etc., and this data is received as output by the server.

[0456] Step 2:

[0457] Financial Data Analysis:

[0458] The server analyzes the received financial data. Here, it activates generative artificial intelligence (AI) to generate an optimal investment portfolio for the user based on the input data. Specifically, using input data such as income, expenses, and savings, it calculates asset allocation (stocks, bonds, real estate, cash, etc.) and determines the optimal percentages. For example, if an income is 6 million yen, expenses are 300,000 yen, and savings are 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash. The generated portfolio data is obtained as output.

[0459] Step 3:

[0460] Portfolio presentation:

[0461] The server sends the generated investment portfolio to the user's smartphone. The user can check the portfolio on the smartphone screen and adjust it as necessary. The input data is the portfolio information sent from the server, and the output is the portfolio screen displayed on the user's smartphone.

[0462] Step 4:

[0463] Emotion data acquisition and analysis:

[0464] Users input their emotional state in a separate form on their smartphone. This emotional data is sent to a server, which then uses emotion analysis software to evaluate the emotional state. Input data includes emotional states such as "stress," "anxiety," and "calm," and the analysis results (emotion scores) are obtained as output.

[0465] Step 5:

[0466] Customized investment advice based on sentiment data:

[0467] The server customizes investment advice based on the analyzed emotional data. For example, if the emotional analysis determines that the user is feeling "stressed," it will recommend low-risk investment options. On the other hand, if the analysis determines that the user is "excited," it will suggest investment options that are high-risk but also have high expected returns. The input is an emotional score, and the output is customized investment advice.

[0468] Step 6:

[0469] Creation and provision of relaxation content:

[0470] The server generates relaxation content based on the evaluated emotional data. For example, if the user is judged to be in a high-stress state, it generates relaxation music or guided meditation videos and provides them to the user's smartphone. The input data is the emotion analysis results, and the generated relaxation content is obtained as the output.

[0471] Step 7:

[0472] Real-time market data collection and evaluation:

[0473] The server periodically collects and analyzes market data from the Internet. This data includes stock market fluctuations, economic indicators, and exchange rates. Based on the analysis results, it evaluates the impact on the user's investment portfolio. For example, if a particular stock falls sharply, the server generates a notification such as, "We recommend reducing your stock portfolio by 10% and converting that money into bonds." The input data is the latest market data, and the output is investment advice based on the analysis.

[0474] Step 8:

[0475] Providing real-time notification and prevention:

[0476] The server generates important notifications based on real-time market data and the user's financial data and sends them to the user's smartphone. It also assesses future financial risks and provides specific preventative measures. For example, it provides a notification such as, "There is a high risk of income decline, so we recommend that you save a certain amount." The input data are the user's financial data and market data, and the generated notifications and preventative measures are obtained as outputs.

[0477] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0478] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0479] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0480] [Second embodiment]

[0481] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0482] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0483] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0484] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0485] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0486] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0487] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0488] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0489] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0490] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0491] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0492] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0493] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[0494] The program processing of this system will be specifically explained below.

[0495] 1. Enter your user information:

[0496] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters this information into the terminal and clicks the submit button. The entered financial data is then sent to the server.

[0497] 2. Receiving and analyzing financial data:

[0498] The server analyzes the received financial data and utilizes generative artificial intelligence to assess the user's risk tolerance, financial goals, and current asset mix, based on which the server generates an optimal investment portfolio for the user.

[0499] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0500] 3. Portfolio Presentation:

[0501] The server sends the generated investment portfolio to the user's terminal, which displays it to the user, who can review the presented portfolio and adjust it as needed.

[0502] 4. Real-time market data collection and evaluation:

[0503] The server periodically collects market data and evaluates its impact on the user's investment portfolio in real time. When a significant market movement is detected, the server analyzes its impact and generates a notification for the user, which is sent to the user's device and displayed immediately.

[0504] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0505] 5. Preventive Risk Assessment:

[0506] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks, and then suggests specific preventive measures to the user based on the results of the evaluation.

[0507] 6. Education and Literacy:

[0508] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0509] These features allow users to make sound investment decisions, prepare for future risks, and improve financial stability.

[0510] The processing flow will be explained below.

[0511] Step 1:

[0512] The terminal displays a form for the user to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[0513] Step 2:

[0514] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[0515] Step 3:

[0516] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[0517] Step 4:

[0518] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[0519] Step 5:

[0520] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[0521] Step 6:

[0522] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0523] Step 7:

[0524] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[0525] Step 8:

[0526] The server evaluates future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, it generates recommendations for preventive measures (e.g., insurance products and emergency funds) for the user.

[0527] Step 9:

[0528] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[0529] Step 10:

[0530] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[0531] These processing steps enable users to achieve effective asset management and improve financial stability while preparing for future risks.

[0532] Example 1

[0533] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0534] Today's users have a wide variety of financial data, and there is a growing need for the ability to build optimal investment portfolios based on that data, reflect market data in real time, and evaluate future financial risks and provide preventative measures. However, conventional systems struggle to provide these functions in an integrated manner, forcing users to manually collect and analyze multiple pieces of information and make appropriate investment decisions. This places a significant burden on users and can delay their decision-making. Furthermore, there are limited means of providing educational content to improve financial literacy, leaving users with insufficient opportunities to acquire appropriate knowledge.

[0535] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0536] In this invention, the server includes means for receiving financial data from a user, a generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the financial data and market data and evaluating it in real time, means for notifying the user based on the evaluation results, and means for generating educational content to improve the user's financial knowledge. This allows the user to receive appropriate investment portfolio suggestions, enables investment decisions that reflect fluctuations in market data in real time, and provides prompt preventative measures against future financial risks. Educational content to improve the user's financial literacy is also provided, enabling efficient and effective comprehensive financial management.

[0537] "User" means any person or entity that inputs financial data and uses the investment portfolio, notifications, and educational content provided by the System.

[0538] "Financial Data" refers to information that indicates a user's financial status, such as income, expenses, savings, and investment information.

[0539] "Generative AI" refers to an AI technology that suggests optimal investment portfolios based on input data.

[0540] "Investment portfolio" refers to an investment plan that appropriately allocates a user's assets among stocks, bonds, real estate, cash, etc.

[0541] "Market data" refers to data showing trends in stock prices, bond yields, real estate prices, etc. in financial markets.

[0542] "Real-time" refers to a state in which data collection, analysis, notification, and other processes are carried out immediately without delay.

[0543] "Notifications" refer to information sent to users based on market movements and their impact on their investment portfolios.

[0544] "Preventive measures" refer to suggestions and advice on how to respond appropriately to future financial risks.

[0545] "Educational Content" refers to articles, video tutorials, quizzes, and other educational materials provided to improve a user's financial knowledge.

[0546] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[0547] System configuration

[0548] Entering user information

[0549] The terminal displays a form for the user to enter income, expenditure, savings, and investment information. This form is installed on a web browser using HTML and JavaScript. The user enters information such as income, expenditure, and savings and clicks the "Submit" button. This input data is converted to JSON format and sent to the server using the HTTPS protocol.

[0550] Receiving and analyzing financial data

[0551] The server receives financial data sent by the user using a Python framework. The received data is preprocessed and passed to a generative AI model (e.g., GPT-4). Using the following prompt, the AI ​​model analyzes the user's financial data and generates an optimal investment portfolio.

[0552] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[0553] The resulting portfolio may be allocated, for example, as 40% stocks, 30% bonds, 20% real estate, and 10% cash.

[0554] Portfolio presentation

[0555] The server converts the generated investment portfolio into JSON format and sends it to the terminal. The terminal visualizes this data using HTML and JavaScript and presents it to the user in the form of graphs, etc. The user can review the portfolio and adjust it as needed.

[0556] Real-time market data collection and evaluation

[0557] The server periodically collects real-time market data through market data APIs (e.g., Alpha Vantage and Yahoo Finance). This data is used to evaluate the impact on the user's investment portfolio in real time. When there is a significant market fluctuation, the following prompt sentence is passed to the AI ​​model for evaluation:

[0558] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[0559] The server generates a notification for the user based on the analysis results, sends it to the terminal in JSON format, and displays it immediately.

[0560] Preventive Risk Assessment

[0561] The server uses Python statistical analysis libraries (e.g., pandas and scikit-learn) to assess future financial risks based on the user's financial data, analyzing income fluctuations, changes in economic conditions, health risks, etc., and recommends specific preventive measures to the user as needed.

[0562] Education and Literacy

[0563] The server uses the generative AI model to generate educational content to improve the user's financial literacy. The content is generated using the following prompt sentence as an example.

[0564] "Generate educational content on the fundamentals of investing that your users are interested in."

[0565] The generated educational content includes articles, video tutorials, quizzes, etc., and is provided to the user via their device. The learning progress is tracked by the server, and additional educational content is provided based on the user's level of understanding.

[0566] These features allow users to make appropriate investment decisions, prepare for future risks, and improve financial stability.

[0567] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0568] Step 1:

[0569] Entering user information

[0570] The terminal displays a form using HTML and JavaScript for the user to enter income, expenditure, savings, and investment information.

[0571] Input: User's income, expenses, savings, and investment information.

[0572] Behavior: Validates input using JavaScript.

[0573] Output: Validated financial data.

[0574] The user enters information such as income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, and clicks the "Submit" button.

[0575] What it does: Form input data is converted to JSON format.

[0576] Output: Financial data in JSON format.

[0577] The terminal sends the generated financial data in JSON format to the server via the HTTPS protocol.

[0578] Input: Financial data in JSON format.

[0579] How it works: Encodes transmitted data and sends it securely via HTTPS.

[0580] Output: Connection established with the server and notification of completion.

[0581] Step 2:

[0582] Receiving and analyzing financial data

[0583] The server receives the HTTPS request to receive financial data from the user.

[0584] Input: Financial data in JSON format sent from the terminal.

[0585] What it does: Decodes and receives data, then processes it in a Python framework (e.g. Flask).

[0586] Output: Financial data in internal data format.

[0587] The server preprocesses the received data and passes it to a generative AI model (e.g., GPT-4).

[0588] Input: Financial data in internal data format.

[0589] Action: Any necessary data transformations and preprocessing (e.g., data normalization).

[0590] Output: A prompt to the generative AI model.

[0591] The generative AI model is passed the following prompts to generate an optimal investment portfolio based on the user's risk tolerance and financial goals.

[0592] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[0593] How it works: Analyzes generative AI models and generates portfolios based on prompts.

[0594] Output: An investment portfolio generated by the AI ​​model (e.g., 40% stocks, 30% bonds, 20% real estate, 10% cash).

[0595] Step 3:

[0596] Portfolio presentation

[0597] The server converts the generated investment portfolio into JSON format and sends it to the terminal.

[0598] Input: An investment portfolio generated by an AI model.

[0599] What it does: Converts portfolio data into JSON format.

[0600] Output: Investment portfolio data in JSON format.

[0601] The terminal uses HTML and JavaScript to visualize the received investment portfolio in graphs and other formats and presents it to the user.

[0602] Input: Investment portfolio data in JSON format.

[0603] How it works: Visualization is done using a graphing library (e.g. D3.js, Chart.js).

[0604] Output: A visualized portfolio (e.g., graphs and charts).

[0605] The user reviews the presented portfolio and makes adjustments as necessary.

[0606] Action: Portfolio adjustment (e.g. increase stock percentage to 50%).

[0607] Output: Adjusted portfolio data.

[0608] Step 4:

[0609] Real-time market data collection and evaluation

[0610] The server periodically collects real-time market data via market data APIs (e.g., Alpha Vantage, Yahoo Finance).

[0611] Input: Market data obtained from API.

[0612] How it works: Collects data using HTTP requests.

[0613] Output: Real-time market data.

[0614] The server analyzes the collected market data and assesses its impact on the user's investment portfolio.

[0615] Input: Real-time market data and user's investment portfolio.

[0616] Actions: Use data analysis libraries (e.g. pandas, NumPy) to assess impact.

[0617] Output: Evaluation results.

[0618] If a significant market fluctuation is detected, the server passes the following prompts to the AI ​​model to generate a countermeasure:

[0619] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[0620] Action: Impact assessment and countermeasure generation using AI models.

[0621] Output: Specific notification and action to the user.

[0622] The device immediately displays notifications received from the server to the user using HTML and JavaScript.

[0623] Input: Notification data received from the server.

[0624] Action: Show a notification (e.g. popup, alert).

[0625] Output: A notification is displayed to the user.

[0626] Step 5:

[0627] Preventive Risk Assessment

[0628] The server uses Python statistical analysis libraries (e.g., pandas, scikit-learn) to assess future financial risk based on the user's financial data.

[0629] Input: User's financial data.

[0630] Behavior: Application of statistical analysis and predictive models.

[0631] Output: Risk assessment results.

[0632] The server generates preventive measures based on the risk assessment results and presents them to the user.

[0633] Input: Risk assessment results.

[0634] Action: Generate preventative measures (using AI models).

[0635] Output: Provides specific preventive measures to the user.

[0636] Step 6:

[0637] Education and Literacy

[0638] The server uses the generative AI model to generate educational content to improve the user's financial literacy.

[0639] Input: User's learning needs.

[0640] How it works: Generating educational content using AI models.

[0641] Output: Financial education content.

[0642] The server sends the generated educational content to the terminal in JSON format.

[0643] Input: Generated educational content.

[0644] Operation: Convert to JSON format and send.

[0645] Output: Educational content in JSON format.

[0646] The device displays educational content using HTML and JavaScript and tracks the user's learning progress.

[0647] Input: Educational content in JSON format.

[0648] What it does: Presents educational content and tracks progress.

[0649] Output: User's learning progress data.

[0650] (Application example 1)

[0651] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0652] Conventional financial management systems struggled to provide optimal investment portfolios based on users' individual financial data, and lacked the functionality to collect and analyze market data in real time and immediately notify users of its impact on their investment portfolios. This made it difficult for users to make timely and appropriate investment decisions, and they were inadequately prepared for future financial risks. Furthermore, there was no system in place that provided educational content to help improve financial literacy, so it was difficult to expect users' financial knowledge to improve.

[0653] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0654] In this invention, the server includes a means for receiving financial data from a user, a generating AI model means for generating an investment portfolio based on the financial data, a means for presenting the investment portfolio to the user, and a means for providing educational content to the user, thereby enabling the user to obtain an individually optimized investment portfolio and improve their financial literacy.

[0655] Furthermore, in this invention, the server includes means for collecting market data, means for analyzing the market data to assess the impact on the user's investment portfolio, means for generating and sending notifications to the user in real time based on the assessment results, and means for collecting and analyzing expenditure data in cooperation with a payment service, thereby enabling the user to quickly respond appropriately to real-time market fluctuations.

[0656] Furthermore, in this invention, the server includes means for assessing future financial risks based on the user's financial data, means for generating preventive measures based on the risk assessment results and presenting them to the user, and means for providing additional educational content according to the user's level of understanding, thereby enabling the user to take more specific preventive measures against future financial risks and deepen their financial knowledge.

[0657] "Financial Data" means information about a User's income, expenses, savings, and investments.

[0658] The "generative AI model means" is an artificial intelligence technology that analyzes a user's financial data and generates an optimal investment portfolio.

[0659] An "investment portfolio" is a combination of various financial instruments and assets based on a user's financial goals and risk tolerance.

[0660] "Educational Content" is learning material such as articles, videos, and quizzes designed to improve users' financial literacy.

[0661] "Market data" refers to real-time trading information and related data in financial markets, such as stock prices, bond prices, and exchange rates.

[0662] "Means for generating and sending notifications to users in real time" refers to technology that instantly analyzes important information such as market fluctuations and sends appropriate notifications to users.

[0663] "Means for collecting and analyzing expenditure data in cooperation with payment services" refers to technology that works in cooperation with the electronic payment services used by users to collect expenditure data and integrate it into financial data.

[0664] "Means for assessing future financial risks" refers to technology that predicts and assesses risks associated with a user's financial situation, taking into account factors such as fluctuations in income, changes in economic conditions, and health risks.

[0665] "Means for generating preventive measures and presenting them to users" is a technology that proposes and displays specific measures that users should take in response to assessed financial risks.

[0666] The "means for providing additional educational content according to the user's level of understanding" is a technology that provides optimal additional learning materials based on the user's learning progress and level of understanding.

[0667] This invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data, analyzes it using generative AI, and presents an optimal investment portfolio based on the results. It also provides educational content to improve the user's financial literacy, collects and analyzes market data in real time, and immediately notifies the user of the impact on the investment portfolio.

[0668] The server first receives financial data from the user, including income, expenses, savings, and investment information. The data entered by the user is encrypted and stored in cloud storage. The received data is then analyzed using a generative AI model to evaluate the user's risk tolerance, financial goals, and current asset mix. Based on this, the server generates an optimal investment portfolio for the user and presents it to the user's device.

[0669] Users can review the proposed investment portfolio and adjust it as necessary, and the adjusted portfolio can also be re-analyzed by the AI ​​in real time.

[0670] The server also collects real-time market data via APIs from external financial data providers. Based on this market data, the impact on the user's investment portfolio is assessed, and if significant market fluctuations are detected, the system immediately notifies the user. For example, if there is a major market fluctuation, the system can send a notification such as, "Based on the current market conditions, we recommend reducing your stock portfolio by 10% and allocating that capital to bonds."

[0671] In addition, the system works in conjunction with electronic payment services to collect and analyze users' spending data and reflect it in real-time financial data, allowing users to constantly monitor their spending patterns and more accurately assess their financial situation.

[0672] The server also evaluates future financial risks based on the user's financial data, and generates and presents to the user preventive measures that take into account, for example, fluctuations in income, changes in economic conditions, health risks, etc. This evaluation and preventive measures allow the user to prepare for future unforeseen events.

[0673] Additionally, to improve users' financial literacy, the server generates and provides appropriate educational content to users. The educational content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[0674] For example, if a user inputs their annual income of ¥6 million, monthly expenses of ¥300,000, and savings of ¥1 million, the server will use this data to generate a portfolio with 40% stocks, 30% bonds, 20% real estate, and 10% cash. This information is fed into the generative AI model using the following prompt:

[0675] Example prompt sentence:

[0676] "Analyze this financial data and suggest the optimal investment portfolio:

[0677] Income: 6 million yen

[0678] Expenses: 300,000 yen

[0679] Savings: 1 million yen

[0680] Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen

[0681] In this way, the present invention provides users with an effective means of making optimal financial management and investment proposals and preparing for future financial risks.

[0682] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0683] Step 1:

[0684] Users launch the application on their smartphone and enter their income, expenses, savings, and investment information. This data is encrypted and sent to the server, where it is stored in cloud storage in JSON format.

[0685] Step 2:

[0686] The server inputs the received user's financial data (income, expenses, savings, and investment information) into a generative AI model to generate an optimal investment portfolio. The generative AI model processes and analyzes the data using the analysis prompt: "Analyze this financial data and propose the optimal investment portfolio: Income: 6 million yen, Expenses: 300,000 yen, Savings: 1 million yen, Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen," and outputs the optimal investment portfolio.

[0687] Step 3:

[0688] The server sends the generated investment portfolio to the user's device. The device displays the portfolio in a user-friendly interface, allowing the user to review and adjust it. If the user makes any adjustments, the data is sent back to the server and reanalyzed by the generative AI model.

[0689] Step 4:

[0690] The server collects market data in real time from external financial data providers (e.g., financial market data API). This data includes price fluctuations of financial products and stock price information. The server periodically analyzes this data and evaluates its impact on the user's investment portfolio. The server analyzes the data using the evaluation prompt: "Based on the current market situation, please evaluate the impact on this portfolio and suggest any necessary changes: Portfolio information, Market data" and obtains the impact evaluation results as output.

[0691] Step 5:

[0692] The server generates real-time notifications based on the evaluation results and sends them to the user's terminal. The notifications include specific investment action recommendations (e.g., "We recommend reducing your stock portfolio by 10% and allocating the funds to bonds.") The user receives the notifications on their terminal and adjusts their investment portfolio as necessary.

[0693] Step 6:

[0694] The server works with the electronic payment service to collect and analyze the user's spending data. It obtains data on the user's spending from the payment service and reflects it in real time in the financial data. This allows the user's spending patterns to be tracked and financial management to be more accurate based on spending.

[0695] Step 7:

[0696] The server evaluates future financial risks based on the user's financial data. For example, it takes into account fluctuations in income, changes in economic conditions, health risks, etc., and performs analysis using the risk assessment prompt: "Given the user's current financial situation, assess possible risks and propose preventive measures: financial data, economic data, user information," and obtains a financial risk assessment result as an output.

[0697] Step 8:

[0698] The server generates preventive measures based on the evaluation results and presents them to the user, allowing the user to prepare for future unforeseen events.Specific preventive measures (e.g., insurance product recommendations, emergency savings suggestions) are presented.

[0699] Step 9:

[0700] The server generates and provides educational content to improve users' financial literacy. The content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[0701] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0702] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[0703] The program processing of this system will be specifically explained below.

[0704] 1. Enter your user information:

[0705] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[0706] 2. Receiving and analyzing financial data:

[0707] The server analyzes the received financial data. The server activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[0708] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0709] 3. Portfolio Presentation:

[0710] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[0711] 4. Real-time market data collection and evaluation:

[0712] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0713] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0714] 5. Preventive Risk Assessment:

[0715] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[0716] 6. Education and Literacy:

[0717] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0718] 7. Emotion Recognition and Customization with Emotion Engine:

[0719] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[0720] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[0721] 8. Support and relaxation content:

[0722] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[0723] These features allow users to achieve personalized asset management, prepare for future risks, and improve their financial stability with emotionally sensitive support.

[0724] The processing flow will be explained below.

[0725] Step 1:

[0726] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[0727] Step 2:

[0728] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[0729] Step 3:

[0730] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[0731] Step 4:

[0732] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[0733] Step 5:

[0734] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[0735] Step 6:

[0736] The device captures the user's facial expressions, voice tone, text data, etc. into the emotion engine. The user may interact with the device to provide this data (e.g., answering questions, using the camera, etc.).

[0737] Step 7:

[0738] The emotion engine analyzes the collected data and evaluates the user's emotional state, generating emotion data such as whether the user is relaxed, excited, or stressed.

[0739] Step 8:

[0740] The server receives the emotion data generated by the emotion engine and evaluates the user's current mental state, and customizes financial advice based on the evaluation.

[0741] Step 9:

[0742] If the server determines that the user's emotional state indicates increased stress or anxiety, it can refrain from offering risky investment advice and suggest safer investment options (e.g., bonds or cash). It can also emphasize proactive risk assessment advice if it recognizes the user's state of agitation.

[0743] Step 10:

[0744] The server generates relaxation content based on the user's emotional state, such as relaxation music or guided meditation videos.

[0745] Step 11:

[0746] The server transmits the generated relaxation content to the user's terminal, which displays the content to the user to encourage mental refreshment.

[0747] Step 12:

[0748] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0749] Step 13:

[0750] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[0751] Step 14:

[0752] The server assesses future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, the server recommends specific preventive measures (e.g., insurance products or emergency fund arrangements) to the user.

[0753] Step 15:

[0754] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[0755] Step 16:

[0756] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[0757] These specific processing steps allow users to effectively manage their assets, prepare for future risks, and improve their financial stability while receiving support that takes into account their emotional state.

[0758] Example 2

[0759] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0760] While existing financial analysis systems have the ability to generate investment portfolios based on users' financial data, they lack the ability to respond to users' emotional states and real-time market fluctuations. This leaves users with the problem of having to make investment decisions while feeling stressed and anxious. Furthermore, they lack the provision of educational content to help users address future financial risks and improve their financial knowledge.

[0761] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0762] In this invention, the server includes a generative artificial intelligence means for receiving financial data from a user and generating an investment portfolio based on the financial data, a means for collecting emotional data from the user and customizing financial advice based on the emotional data, and a means for evaluating the user's mental state and generating relaxation content, thereby enabling the provision of preventive risk assessment and educational content for improving financial knowledge in response to the user's emotional state and real-time market fluctuations.

[0763] "Financial data" refers to data that indicates the user's financial situation, such as income, expenditure, savings, and investment information.

[0764] A "generative artificial intelligence vehicle" is a vehicle that uses artificial intelligence techniques to generate investment portfolios based on financial data.

[0765] "Investment Portfolio" refers to a combination of investment products, such as stocks, bonds, real estate, and cash, created with a particular user's financial goals and risk tolerance in mind.

[0766] "Emotion data" refers to data that indicates the user's emotional state, collected from the user's facial expression, voice tone, text data, and the like.

[0767] The "means for customizing financial advice" is a means for optimizing financial advice for a user based on collected emotional data.

[0768] "Relaxation content" refers to content such as relaxation music and guided meditation videos that are provided to encourage users to refresh their minds.

[0769] "Market data" refers to data related to various markets that affect investment decisions, such as stock market fluctuations, economic indicators, and exchange rates.

[0770] "Means for generating and transmitting notifications to users in real time" refers to means for quickly analyzing fluctuations in market data and, based on the results, generating and transmitting notifications in real time that recommend appropriate investment actions to users.

[0771] "Financial Risk Assessment" refers to the analysis and assessment of potential future risks based on your financial data.

[0772] "Preventive measures" refer to specific actions or measures that users should take in advance to address assessed risks.

[0773] "Educational Content" means learning materials such as articles, video tutorials, and quizzes that are provided to improve a user's financial knowledge.

[0774] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[0775] Hardware and Software Configuration

[0776] The present invention uses the following hardware and software.

[0777] Hardware:

[0778] Terminal: A device (e.g., computer, smartphone, tablet) that provides a user interface for users to enter data.

[0779] Server: The central device that receives data, analyzes it, generates portfolios, sends notifications, etc.

[0780] software:

[0781] Programming language: Python

[0782] Generative AI model: TensorFlow

[0783] Emotion engine: Microsoft Azure Emotion API or AWS Rekognition

[0784] Database management system: MySQL

[0785] Program processing explanation

[0786] 1. Enter your user information:

[0787] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[0788] 2. Receiving and analyzing financial data:

[0789] The server analyzes the received financial data. The server runs a generative artificial intelligence (AI) model to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[0790] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0791] 3. Portfolio Presentation:

[0792] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[0793] 4. Real-time market data collection and evaluation:

[0794] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0795] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0796] 5. Preventive Risk Assessment:

[0797] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[0798] 6. Education and Literacy:

[0799] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0800] 7. Emotion Recognition and Customization with Emotion Engine:

[0801] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[0802] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[0803] 8. Support and relaxation content:

[0804] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[0805] Examples of prompt statements

[0806] Example prompt sentence:

[0807] "Based on market data, due to the current stock market volatility, I would recommend reducing your stock portfolio by 10% to reduce risk and allocating that money to bonds. Also, you can watch a guided meditation video here to help reduce stress."

[0808] In this way, a system is constructed that provides customized advice and support to users that takes into account their individual financial circumstances and emotional state. With this invention, users can manage their assets in an individually optimized manner, and achieve mental stability while preparing for future risks.

[0809] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0810] Step 1: Enter your user information

[0811] The terminal presents the user with a form for entering financial data, including fields for income, expenses, savings, and investment information.

[0812] Input: The user enters income, expenses, savings, and investment information and clicks the submit button.

[0813] Data processing: Convert the data entered by the user into JSON format and send it to the server.

[0814] Output: User's financial data sent to the server.

[0815] Step 2: Receiving and parsing financial data

[0816] The server receives the financial data sent from the user's terminal.

[0817] Input: User's financial data received from the terminal.

[0818] Data Processing and Computation: The server analyzes the received data and processes it using a generative AI model to assess the user's risk tolerance, financial goals, and current asset mix, specifically using Python and TensorFlow.

[0819] Output: Analysis results and optimized investment portfolio.

[0820] Step 3: Generate a portfolio

[0821] The server runs a generative artificial intelligence (AI) model and generates an optimal investment portfolio for the user based on the analysis results.

[0822] Input: Financial data parsed by the server and the user's risk tolerance.

[0823] Data Computing: Generative AI models are used to generate portfolios that take profitability and risk into account.

[0824] Output: Generated investment portfolio (e.g. 40% stocks, 30% bonds, 20% real estate, 10% cash).

[0825] Step 4: Present your portfolio

[0826] The server transmits the generated investment portfolio to the user's terminal.

[0827] Input: Server-generated investment portfolio.

[0828] Output: Display the portfolio on the terminal.

[0829] The device displays the transferred portfolio on the screen, allowing the user to review and adjust it.

[0830] Step 5: Real-time market data collection and evaluation

[0831] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, and currency exchange rates.

[0832] Input: Market data obtained using external APIs and web scraping techniques.

[0833] Data processing and calculation: The server analyzes market fluctuations and assesses their impact on the user's investment portfolio.

[0834] Output: Evaluation results and real-time notifications sent to users.

[0835] For example, if a user's stock holdings suddenly fall, the server may generate and send a notification to the user saying, "Based on current market conditions, we recommend reducing your stock portfolio by 10% and allocating that money to bonds."

[0836] Step 6: Preemptive risk assessment

[0837] The server assesses future financial risk based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks.

[0838] Input: User's financial and market data.

[0839] Data calculation: The server considers multiple risk scenarios and performs a comprehensive risk assessment.

[0840] Output: Predicted risks and recommended preventative measures.

[0841] Based on the evaluation results, the server suggests specific preventive measures to the user.

[0842] Step 7: Education and Literacy

[0843] The server generates appropriate educational content to improve the user's financial knowledge, including articles, video tutorials, and quizzes.

[0844] Input: User comprehension information and current financial knowledge.

[0845] Data processing: Generate educational content and track user learning progress.

[0846] Output: Educational content and learning progress reports.

[0847] The terminal can display the generated educational content to the user and track their learning progress.

[0848] Step 8: Emotion Recognition and Customization with the Emotion Engine

[0849] The terminal or server uses an emotion engine to recognize the user's emotions. It analyzes emotions from the user's facial expressions, voice tone, text data, etc., and transmits the results to the server as emotion data.

[0850] Input: User emotion data.

[0851] Data calculation: The server analyzes the emotion data and evaluates the user's current mental state.

[0852] Output: Sentiment evaluation results and customized advice.

[0853] For example, if the server detects that the user is stressed, it may refrain from providing risky investment advice and suggest safer investment options.

[0854] Step 9: Support and relaxation content

[0855] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos.

[0856] Input: Emotion data and content database.

[0857] Data processing and calculation: Select and generate relaxation content.

[0858] Output: The relaxation content provided to the user.

[0859] The terminal can display these contents to the user to encourage mental refreshment.

[0860] (Application example 2)

[0861] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0862] Previously, there were systems that generated investment portfolios using users' financial data, but they were not customized to take into account the user's emotional state, making it impossible to reduce investment anxiety and stress. Furthermore, they lacked the functionality to analyze market data in real time and send appropriate notifications to users. Furthermore, there was a lack of a system that provided relaxation content based on the user's emotional state. This made it difficult to achieve comprehensive financial management and mental health for users.

[0863] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0864] In this invention, the server includes means for receiving financial data from a user, generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the user's emotional data and evaluating the emotional state, means for customizing investment advice based on the emotional state, and means for generating relaxation content based on the emotional state, thereby enabling the user to receive not only an individually optimized investment portfolio but also investment advice and relaxation content that take into account their emotional state.

[0865] The "means for receiving financial data from a user" refers to the interface and process by which a user inputs financial data such as their income, expenses, savings, and investment information, and the system receives that data.

[0866] A "generative artificial intelligence tool" is an artificial intelligence algorithm and associated system for analyzing input financial data and generating an optimal investment portfolio for a user.

[0867] A "means for presenting an investment portfolio to a user" is an interface and process for displaying the generated investment portfolio on a user's device.

[0868] The "means for analyzing emotional data and assessing an emotional state" refers to software and processes for analyzing emotional data such as a user's facial expression, voice, text, etc., and assessing the user's current emotional state.

[0869] A "means for customizing investment advice based on emotional state" is an algorithm and process for providing appropriate investment advice to a user based on the assessed emotional state.

[0870] A "means for generating relaxation content based on emotional state" is software and processes for generating and providing relaxation content, such as relaxation music or guided meditation videos, based on an assessment of a user's emotional state.

[0871] "Means for collecting market data" refers to algorithms and processes for collecting market data, such as stock market data, economic indicators, and exchange rates, from the Internet and other data sources.

[0872] "Means for analyzing market data to assess the impact on a user's investment portfolio" refers to algorithms and processes for analyzing collected market data and assessing its impact on a user's investment portfolio.

[0873] "Means for generating and sending notifications to users in real time" means software and processes for generating key information and recommendations in real time based on the analysis of market data and sending notifications to users' devices.

[0874] "Means for assessing future financial risks" refers to algorithms and processes for predicting and assessing future financial risks, such as income fluctuations, changes in economic conditions, and health risks, based on the user's current financial data.

[0875] The "means for generating and presenting to a user preventative measures based on the results of risk assessment" refers to software and processes for generating appropriate preventative measures for the assessed financial risks and presenting them to a user's device.

[0876] The "means for providing optimal relaxation content to a user in accordance with emotional data" refers to software and processes for analyzing emotional data and providing relaxation content to reduce the user's stress and anxiety based on the results of the analysis.

[0877] The present invention is a system for analyzing a user's financial and emotional data and providing optimal investment portfolios and relaxation content. This system comprehensively considers the user's financial situation and emotional state and provides optimal advice to support the user's financial management.

[0878] Hardware and software used

[0879] This system is realized using the following hardware and software:

[0880] Hardware: Smartphones, computer servers

[0881] Software: Python, pandas, scikit-learn, TextBlob, generative artificial intelligence

[0882] What the program does

[0883] 1. Enter your user information:

[0884] The device (smartphone) displays a form for the user to enter income, expenditure, savings, and investment information. The user enters this data and clicks the send button to send the data. The sent data is stored on the server.

[0885] 2. Analysis of Financial Data:

[0886] The server analyzes the received financial data and uses generative artificial intelligence to generate an optimal investment portfolio for the user. For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0887] 3. Emotional Data Analysis:

[0888] The terminal or server analyzes the user's emotional data (e.g., facial expressions, voice, and text) and evaluates their emotional state. Based on the evaluated emotional state, it customizes investment advice and generates relaxation content as needed. For example, if it determines that the user is feeling "stressed," it provides relaxation music.

[0889] 4. Portfolio presentation and adjustment:

[0890] The generated investment portfolio is displayed on the user's smartphone. The user can review the portfolio and make adjustments as needed. The adjusted portfolio is also saved in the system for later analysis.

[0891] 5. Real-time market data collection and evaluation:

[0892] The server periodically collects market data, analyzes it, and evaluates the impact on the user's investment portfolio. For example, if the value of stocks drops sharply, a notification will be sent to the user's smartphone saying, "Based on current market conditions, we recommend that you reduce your stock portfolio by 10% and convert that money into bonds."

[0893] Specific examples

[0894] The user entered financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen. The emotion was entered as "stress." Based on this data, the server generated an investment portfolio consisting of 40% stocks, 30% bonds, 20% real estate, and 10% cash, and recommended relaxation music to users who were in a "stressed" state.

[0895] Prompt Sentence Examples

[0896] Based on the financial and emotional data below, please suggest the best investment portfolio and relaxation content for you.

[0897] Income: 6 million yen

[0898] Monthly expenses: 300,000 yen

[0899] Savings: 1 million yen

[0900] Emotion: Stress

[0901] Proposed format:

[0902] 1. Investment Portfolio:

[0903] Stock: XX%

[0904] Bond: XX%

[0905] Real Estate: XX%

[0906] Cash: XX%

[0907] 2. Relaxation Content:

[0908] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0909] Step 1:

[0910] Enter your user information:

[0911] Users enter financial data such as income, expenses, savings, and investment information into an input form on their smartphone. The entered data is sent to the server by clicking the send button. At this time, the input data includes "annual income," "monthly expenses," "savings amount," etc., and this data is received as output by the server.

[0912] Step 2:

[0913] Financial Data Analysis:

[0914] The server analyzes the received financial data. Here, it activates generative artificial intelligence (AI) to generate an optimal investment portfolio for the user based on the input data. Specifically, using input data such as income, expenses, and savings, it calculates asset allocation (stocks, bonds, real estate, cash, etc.) and determines the optimal percentages. For example, if an income is 6 million yen, expenses are 300,000 yen, and savings are 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash. The generated portfolio data is obtained as output.

[0915] Step 3:

[0916] Portfolio presentation:

[0917] The server sends the generated investment portfolio to the user's smartphone. The user can check the portfolio on the smartphone screen and adjust it as necessary. The input data is the portfolio information sent from the server, and the output is the portfolio screen displayed on the user's smartphone.

[0918] Step 4:

[0919] Emotion data acquisition and analysis:

[0920] Users input their emotional state in a separate form on their smartphone. This emotional data is sent to a server, which then uses emotion analysis software to evaluate the emotional state. Input data includes emotional states such as "stress," "anxiety," and "calm," and the analysis results (emotion scores) are obtained as output.

[0921] Step 5:

[0922] Customized investment advice based on sentiment data:

[0923] The server customizes investment advice based on the analyzed emotional data. For example, if the emotional analysis determines that the user is feeling "stressed," it will recommend low-risk investment options. On the other hand, if the analysis determines that the user is "excited," it will suggest investment options that are high-risk but also have high expected returns. The input is an emotional score, and the output is customized investment advice.

[0924] Step 6:

[0925] Creation and provision of relaxation content:

[0926] The server generates relaxation content based on the evaluated emotional data. For example, if the user is judged to be in a high-stress state, it generates relaxation music or guided meditation videos and provides them to the user's smartphone. The input data is the emotion analysis results, and the generated relaxation content is obtained as the output.

[0927] Step 7:

[0928] Real-time market data collection and evaluation:

[0929] The server periodically collects and analyzes market data from the Internet. This data includes stock market fluctuations, economic indicators, and exchange rates. Based on the analysis results, it evaluates the impact on the user's investment portfolio. For example, if a particular stock falls sharply, the server generates a notification such as, "We recommend reducing your stock portfolio by 10% and converting that money into bonds." The input data is the latest market data, and the output is investment advice based on the analysis.

[0930] Step 8:

[0931] Providing real-time notification and prevention:

[0932] The server generates important notifications based on real-time market data and the user's financial data and sends them to the user's smartphone. It also assesses future financial risks and provides specific preventative measures. For example, it provides a notification such as, "There is a high risk of income decline, so we recommend that you save a certain amount." The input data are the user's financial data and market data, and the generated notifications and preventative measures are obtained as outputs.

[0933] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0934] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0935] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0936] [Third embodiment]

[0937] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0938] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0939] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0940] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0941] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0942] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0943] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0944] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0945] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0946] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0947] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0948] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0949] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[0950] The program processing of this system will be specifically explained below.

[0951] 1. Enter your user information:

[0952] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters this information into the terminal and clicks the submit button. The entered financial data is then sent to the server.

[0953] 2. Receiving and analyzing financial data:

[0954] The server analyzes the received financial data and utilizes generative artificial intelligence to assess the user's risk tolerance, financial goals, and current asset mix, based on which the server generates an optimal investment portfolio for the user.

[0955] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[0956] 3. Portfolio Presentation:

[0957] The server sends the generated investment portfolio to the user's terminal, which displays it to the user, who can review the presented portfolio and adjust it as needed.

[0958] 4. Real-time market data collection and evaluation:

[0959] The server periodically collects market data and evaluates its impact on the user's investment portfolio in real time. When a significant market movement is detected, the server analyzes its impact and generates a notification for the user, which is sent to the user's device and displayed immediately.

[0960] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[0961] 5. Preventive Risk Assessment:

[0962] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks, and then suggests specific preventive measures to the user based on the results of the evaluation.

[0963] 6. Education and Literacy:

[0964] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[0965] These features allow users to make sound investment decisions, prepare for future risks, and improve financial stability.

[0966] The processing flow will be explained below.

[0967] Step 1:

[0968] The terminal displays a form for the user to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[0969] Step 2:

[0970] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[0971] Step 3:

[0972] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[0973] Step 4:

[0974] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[0975] Step 5:

[0976] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[0977] Step 6:

[0978] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[0979] Step 7:

[0980] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[0981] Step 8:

[0982] The server evaluates future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, it generates recommendations for preventive measures (e.g., insurance products and emergency funds) for the user.

[0983] Step 9:

[0984] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[0985] Step 10:

[0986] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[0987] These processing steps enable users to achieve effective asset management and improve financial stability while preparing for future risks.

[0988] Example 1

[0989] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0990] Today's users have a wide variety of financial data, and there is a growing need for the ability to build optimal investment portfolios based on that data, reflect market data in real time, and evaluate future financial risks and provide preventative measures. However, conventional systems struggle to provide these functions in an integrated manner, forcing users to manually collect and analyze multiple pieces of information and make appropriate investment decisions. This places a significant burden on users and can delay their decision-making. Furthermore, there are limited means of providing educational content to improve financial literacy, leaving users with insufficient opportunities to acquire appropriate knowledge.

[0991] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0992] In this invention, the server includes means for receiving financial data from a user, a generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the financial data and market data and evaluating it in real time, means for notifying the user based on the evaluation results, and means for generating educational content to improve the user's financial knowledge. This allows the user to receive appropriate investment portfolio suggestions, enables investment decisions that reflect fluctuations in market data in real time, and provides prompt preventative measures against future financial risks. Educational content to improve the user's financial literacy is also provided, enabling efficient and effective comprehensive financial management.

[0993] "User" means any person or entity that inputs financial data and uses the investment portfolio, notifications, and educational content provided by the System.

[0994] "Financial Data" refers to information that indicates a user's financial status, such as income, expenses, savings, and investment information.

[0995] "Generative AI" refers to an AI technology that suggests optimal investment portfolios based on input data.

[0996] "Investment portfolio" refers to an investment plan that appropriately allocates a user's assets among stocks, bonds, real estate, cash, etc.

[0997] "Market data" refers to data showing trends in stock prices, bond yields, real estate prices, etc. in financial markets.

[0998] "Real-time" refers to a state in which data collection, analysis, notification, and other processes are carried out immediately without delay.

[0999] "Notifications" refer to information sent to users based on market movements and their impact on their investment portfolios.

[1000] "Preventive measures" refer to suggestions and advice on how to respond appropriately to future financial risks.

[1001] "Educational Content" refers to articles, video tutorials, quizzes, and other educational materials provided to improve a user's financial knowledge.

[1002] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[1003] System configuration

[1004] Entering user information

[1005] The terminal displays a form for the user to enter income, expenditure, savings, and investment information. This form is installed on a web browser using HTML and JavaScript. The user enters information such as income, expenditure, and savings and clicks the "Submit" button. This input data is converted to JSON format and sent to the server using the HTTPS protocol.

[1006] Receiving and analyzing financial data

[1007] The server receives financial data sent by the user using a Python framework. The received data is preprocessed and passed to a generative AI model (e.g., GPT-4). Using the following prompt, the AI ​​model analyzes the user's financial data and generates an optimal investment portfolio.

[1008] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[1009] The resulting portfolio may be allocated, for example, as 40% stocks, 30% bonds, 20% real estate, and 10% cash.

[1010] Portfolio presentation

[1011] The server converts the generated investment portfolio into JSON format and sends it to the terminal. The terminal visualizes this data using HTML and JavaScript and presents it to the user in the form of graphs, etc. The user can review the portfolio and adjust it as needed.

[1012] Real-time market data collection and evaluation

[1013] The server periodically collects real-time market data through market data APIs (e.g., Alpha Vantage and Yahoo Finance). This data is used to evaluate the impact on the user's investment portfolio in real time. When there is a significant market fluctuation, the following prompt sentence is passed to the AI ​​model for evaluation:

[1014] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[1015] The server generates a notification for the user based on the analysis results, sends it to the terminal in JSON format, and displays it immediately.

[1016] Preventive Risk Assessment

[1017] The server uses Python statistical analysis libraries (e.g., pandas and scikit-learn) to assess future financial risks based on the user's financial data, analyzing income fluctuations, changes in economic conditions, health risks, etc., and recommends specific preventive measures to the user as needed.

[1018] Education and Literacy

[1019] The server uses the generative AI model to generate educational content to improve the user's financial literacy. The content is generated using the following prompt sentence as an example.

[1020] "Generate educational content on the fundamentals of investing that your users are interested in."

[1021] The generated educational content includes articles, video tutorials, quizzes, etc., and is provided to the user via their device. The learning progress is tracked by the server, and additional educational content is provided based on the user's level of understanding.

[1022] These features allow users to make appropriate investment decisions, prepare for future risks, and improve financial stability.

[1023] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1024] Step 1:

[1025] Entering user information

[1026] The terminal displays a form using HTML and JavaScript for the user to enter income, expenditure, savings, and investment information.

[1027] Input: User's income, expenses, savings, and investment information.

[1028] Behavior: Validates input using JavaScript.

[1029] Output: Validated financial data.

[1030] The user enters information such as income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, and clicks the "Submit" button.

[1031] What it does: Form input data is converted to JSON format.

[1032] Output: Financial data in JSON format.

[1033] The terminal sends the generated financial data in JSON format to the server via the HTTPS protocol.

[1034] Input: Financial data in JSON format.

[1035] How it works: Encodes transmitted data and sends it securely via HTTPS.

[1036] Output: Connection established with the server and notification of completion.

[1037] Step 2:

[1038] Receiving and analyzing financial data

[1039] The server receives the HTTPS request to receive financial data from the user.

[1040] Input: Financial data in JSON format sent from the terminal.

[1041] What it does: Decodes and receives data, then processes it in a Python framework (e.g. Flask).

[1042] Output: Financial data in internal data format.

[1043] The server preprocesses the received data and passes it to a generative AI model (e.g., GPT-4).

[1044] Input: Financial data in internal data format.

[1045] Action: Any necessary data transformations and preprocessing (e.g., data normalization).

[1046] Output: A prompt to the generative AI model.

[1047] The generative AI model is passed the following prompts to generate an optimal investment portfolio based on the user's risk tolerance and financial goals.

[1048] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[1049] How it works: Analyzes generative AI models and generates portfolios based on prompts.

[1050] Output: An investment portfolio generated by the AI ​​model (e.g., 40% stocks, 30% bonds, 20% real estate, 10% cash).

[1051] Step 3:

[1052] Portfolio presentation

[1053] The server converts the generated investment portfolio into JSON format and sends it to the terminal.

[1054] Input: An investment portfolio generated by an AI model.

[1055] What it does: Converts portfolio data into JSON format.

[1056] Output: Investment portfolio data in JSON format.

[1057] The terminal uses HTML and JavaScript to visualize the received investment portfolio in graphs and other formats and presents it to the user.

[1058] Input: Investment portfolio data in JSON format.

[1059] How it works: Visualization is done using a graphing library (e.g. D3.js, Chart.js).

[1060] Output: A visualized portfolio (e.g., graphs and charts).

[1061] The user reviews the presented portfolio and makes adjustments as necessary.

[1062] Action: Portfolio adjustment (e.g. increase stock percentage to 50%).

[1063] Output: Adjusted portfolio data.

[1064] Step 4:

[1065] Real-time market data collection and evaluation

[1066] The server periodically collects real-time market data via market data APIs (e.g., Alpha Vantage, Yahoo Finance).

[1067] Input: Market data obtained from API.

[1068] How it works: Collects data using HTTP requests.

[1069] Output: Real-time market data.

[1070] The server analyzes the collected market data and assesses its impact on the user's investment portfolio.

[1071] Input: Real-time market data and user's investment portfolio.

[1072] Actions: Use data analysis libraries (e.g. pandas, NumPy) to assess impact.

[1073] Output: Evaluation results.

[1074] If a significant market fluctuation is detected, the server passes the following prompts to the AI ​​model to generate a countermeasure:

[1075] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[1076] Action: Impact assessment and countermeasure generation using AI models.

[1077] Output: Specific notification and action to the user.

[1078] The device immediately displays notifications received from the server to the user using HTML and JavaScript.

[1079] Input: Notification data received from the server.

[1080] Action: Show a notification (e.g. popup, alert).

[1081] Output: A notification is displayed to the user.

[1082] Step 5:

[1083] Preventive Risk Assessment

[1084] The server uses Python statistical analysis libraries (e.g., pandas, scikit-learn) to assess future financial risk based on the user's financial data.

[1085] Input: User's financial data.

[1086] Behavior: Application of statistical analysis and predictive models.

[1087] Output: Risk assessment results.

[1088] The server generates preventive measures based on the risk assessment results and presents them to the user.

[1089] Input: Risk assessment results.

[1090] Action: Generate preventative measures (using AI models).

[1091] Output: Provides specific preventive measures to the user.

[1092] Step 6:

[1093] Education and Literacy

[1094] The server uses the generative AI model to generate educational content to improve the user's financial literacy.

[1095] Input: User's learning needs.

[1096] How it works: Generating educational content using AI models.

[1097] Output: Financial education content.

[1098] The server sends the generated educational content to the terminal in JSON format.

[1099] Input: Generated educational content.

[1100] Operation: Convert to JSON format and send.

[1101] Output: Educational content in JSON format.

[1102] The device displays educational content using HTML and JavaScript and tracks the user's learning progress.

[1103] Input: Educational content in JSON format.

[1104] What it does: Presents educational content and tracks progress.

[1105] Output: User's learning progress data.

[1106] (Application example 1)

[1107] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1108] Conventional financial management systems struggled to provide optimal investment portfolios based on users' individual financial data, and lacked the functionality to collect and analyze market data in real time and immediately notify users of its impact on their investment portfolios. This made it difficult for users to make timely and appropriate investment decisions, and they were inadequately prepared for future financial risks. Furthermore, there was no system in place that provided educational content to help improve financial literacy, so it was difficult to expect users' financial knowledge to improve.

[1109] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1110] In this invention, the server includes a means for receiving financial data from a user, a generating AI model means for generating an investment portfolio based on the financial data, a means for presenting the investment portfolio to the user, and a means for providing educational content to the user, thereby enabling the user to obtain an individually optimized investment portfolio and improve their financial literacy.

[1111] Furthermore, in this invention, the server includes means for collecting market data, means for analyzing the market data to assess the impact on the user's investment portfolio, means for generating and sending notifications to the user in real time based on the assessment results, and means for collecting and analyzing expenditure data in cooperation with a payment service, thereby enabling the user to quickly respond appropriately to real-time market fluctuations.

[1112] Furthermore, in this invention, the server includes means for assessing future financial risks based on the user's financial data, means for generating preventive measures based on the risk assessment results and presenting them to the user, and means for providing additional educational content according to the user's level of understanding, thereby enabling the user to take more specific preventive measures against future financial risks and deepen their financial knowledge.

[1113] "Financial Data" means information about a User's income, expenses, savings, and investments.

[1114] The "generative AI model means" is an artificial intelligence technology that analyzes a user's financial data and generates an optimal investment portfolio.

[1115] An "investment portfolio" is a combination of various financial instruments and assets based on a user's financial goals and risk tolerance.

[1116] "Educational Content" is learning material such as articles, videos, and quizzes designed to improve users' financial literacy.

[1117] "Market data" refers to real-time trading information and related data in financial markets, such as stock prices, bond prices, and exchange rates.

[1118] "Means for generating and sending notifications to users in real time" refers to technology that instantly analyzes important information such as market fluctuations and sends appropriate notifications to users.

[1119] "Means for collecting and analyzing expenditure data in cooperation with payment services" refers to technology that works in cooperation with the electronic payment services used by users to collect expenditure data and integrate it into financial data.

[1120] "Means for assessing future financial risks" refers to technology that predicts and assesses risks associated with a user's financial situation, taking into account factors such as fluctuations in income, changes in economic conditions, and health risks.

[1121] "Means for generating preventive measures and presenting them to users" is a technology that proposes and displays specific measures that users should take in response to assessed financial risks.

[1122] The "means for providing additional educational content according to the user's level of understanding" is a technology that provides optimal additional learning materials based on the user's learning progress and level of understanding.

[1123] This invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data, analyzes it using generative AI, and presents an optimal investment portfolio based on the results. It also provides educational content to improve the user's financial literacy, collects and analyzes market data in real time, and immediately notifies the user of the impact on the investment portfolio.

[1124] The server first receives financial data from the user, including income, expenses, savings, and investment information. The data entered by the user is encrypted and stored in cloud storage. The received data is then analyzed using a generative AI model to evaluate the user's risk tolerance, financial goals, and current asset mix. Based on this, the server generates an optimal investment portfolio for the user and presents it to the user's device.

[1125] Users can review the proposed investment portfolio and adjust it as necessary, and the adjusted portfolio can also be re-analyzed by the AI ​​in real time.

[1126] The server also collects real-time market data via APIs from external financial data providers. Based on this market data, the impact on the user's investment portfolio is assessed, and if significant market fluctuations are detected, the system immediately notifies the user. For example, if there is a major market fluctuation, the system can send a notification such as, "Based on the current market conditions, we recommend reducing your stock portfolio by 10% and allocating that capital to bonds."

[1127] In addition, the system works in conjunction with electronic payment services to collect and analyze users' spending data and reflect it in real-time financial data, allowing users to constantly monitor their spending patterns and more accurately assess their financial situation.

[1128] The server also evaluates future financial risks based on the user's financial data, and generates and presents to the user preventive measures that take into account, for example, fluctuations in income, changes in economic conditions, health risks, etc. This evaluation and preventive measures allow the user to prepare for future unforeseen events.

[1129] Additionally, to improve users' financial literacy, the server generates and provides appropriate educational content to users. The educational content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[1130] For example, if a user inputs their annual income of ¥6 million, monthly expenses of ¥300,000, and savings of ¥1 million, the server will use this data to generate a portfolio with 40% stocks, 30% bonds, 20% real estate, and 10% cash. This information is fed into the generative AI model using the following prompt:

[1131] Example prompt sentence:

[1132] "Analyze this financial data and suggest the optimal investment portfolio:

[1133] Income: 6 million yen

[1134] Expenses: 300,000 yen

[1135] Savings: 1 million yen

[1136] Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen

[1137] In this way, the present invention provides users with an effective means of making optimal financial management and investment proposals and preparing for future financial risks.

[1138] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1139] Step 1:

[1140] Users launch the application on their smartphone and enter their income, expenses, savings, and investment information. This data is encrypted and sent to the server, where it is stored in cloud storage in JSON format.

[1141] Step 2:

[1142] The server inputs the received user's financial data (income, expenses, savings, and investment information) into a generative AI model to generate an optimal investment portfolio. The generative AI model processes and analyzes the data using the analysis prompt: "Analyze this financial data and propose the optimal investment portfolio: Income: 6 million yen, Expenses: 300,000 yen, Savings: 1 million yen, Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen," and outputs the optimal investment portfolio.

[1143] Step 3:

[1144] The server sends the generated investment portfolio to the user's device. The device displays the portfolio in a user-friendly interface, allowing the user to review and adjust it. If the user makes any adjustments, the data is sent back to the server and reanalyzed by the generative AI model.

[1145] Step 4:

[1146] The server collects market data in real time from external financial data providers (e.g., financial market data API). This data includes price fluctuations of financial products and stock price information. The server periodically analyzes this data and evaluates its impact on the user's investment portfolio. The server analyzes the data using the evaluation prompt: "Based on the current market situation, please evaluate the impact on this portfolio and suggest any necessary changes: Portfolio information, Market data" and obtains the impact evaluation results as output.

[1147] Step 5:

[1148] The server generates real-time notifications based on the evaluation results and sends them to the user's terminal. The notifications include specific investment action recommendations (e.g., "We recommend reducing your stock portfolio by 10% and allocating the funds to bonds.") The user receives the notifications on their terminal and adjusts their investment portfolio as necessary.

[1149] Step 6:

[1150] The server works with the electronic payment service to collect and analyze the user's spending data. It obtains data on the user's spending from the payment service and reflects it in real time in the financial data. This allows the user's spending patterns to be tracked and financial management to be more accurate based on spending.

[1151] Step 7:

[1152] The server evaluates future financial risks based on the user's financial data. For example, it takes into account fluctuations in income, changes in economic conditions, health risks, etc., and performs analysis using the risk assessment prompt: "Given the user's current financial situation, assess possible risks and propose preventive measures: financial data, economic data, user information," and obtains a financial risk assessment result as an output.

[1153] Step 8:

[1154] The server generates preventive measures based on the evaluation results and presents them to the user, allowing the user to prepare for future unforeseen events.Specific preventive measures (e.g., insurance product recommendations, emergency savings suggestions) are presented.

[1155] Step 9:

[1156] The server generates and provides educational content to improve users' financial literacy. The content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[1157] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1158] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[1159] The program processing of this system will be specifically explained below.

[1160] 1. Enter your user information:

[1161] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[1162] 2. Receiving and analyzing financial data:

[1163] The server analyzes the received financial data. The server activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[1164] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1165] 3. Portfolio Presentation:

[1166] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[1167] 4. Real-time market data collection and evaluation:

[1168] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1169] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[1170] 5. Preventive Risk Assessment:

[1171] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[1172] 6. Education and Literacy:

[1173] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[1174] 7. Emotion Recognition and Customization with Emotion Engine:

[1175] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[1176] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[1177] 8. Support and relaxation content:

[1178] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[1179] These features allow users to achieve personalized asset management, prepare for future risks, and improve their financial stability with emotionally sensitive support.

[1180] The processing flow will be explained below.

[1181] Step 1:

[1182] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[1183] Step 2:

[1184] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[1185] Step 3:

[1186] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[1187] Step 4:

[1188] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[1189] Step 5:

[1190] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[1191] Step 6:

[1192] The device captures the user's facial expressions, voice tone, text data, etc. into the emotion engine. The user may interact with the device to provide this data (e.g., answering questions, using the camera, etc.).

[1193] Step 7:

[1194] The emotion engine analyzes the collected data and evaluates the user's emotional state, generating emotion data such as whether the user is relaxed, excited, or stressed.

[1195] Step 8:

[1196] The server receives the emotion data generated by the emotion engine and evaluates the user's current mental state, and customizes financial advice based on the evaluation.

[1197] Step 9:

[1198] If the server determines that the user's emotional state indicates increased stress or anxiety, it can refrain from offering risky investment advice and suggest safer investment options (e.g., bonds or cash). It can also emphasize proactive risk assessment advice if it recognizes the user's state of agitation.

[1199] Step 10:

[1200] The server generates relaxation content based on the user's emotional state, such as relaxation music or guided meditation videos.

[1201] Step 11:

[1202] The server transmits the generated relaxation content to the user's terminal, which displays the content to the user to encourage mental refreshment.

[1203] Step 12:

[1204] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1205] Step 13:

[1206] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[1207] Step 14:

[1208] The server assesses future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, the server recommends specific preventive measures (e.g., insurance products or emergency fund arrangements) to the user.

[1209] Step 15:

[1210] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[1211] Step 16:

[1212] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[1213] These specific processing steps allow users to effectively manage their assets, prepare for future risks, and improve their financial stability while receiving support that takes into account their emotional state.

[1214] Example 2

[1215] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1216] While existing financial analysis systems have the ability to generate investment portfolios based on users' financial data, they lack the ability to respond to users' emotional states and real-time market fluctuations. This leaves users with the problem of having to make investment decisions while feeling stressed and anxious. Furthermore, they lack the provision of educational content to help users address future financial risks and improve their financial knowledge.

[1217] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1218] In this invention, the server includes a generative artificial intelligence means for receiving financial data from a user and generating an investment portfolio based on the financial data, a means for collecting emotional data from the user and customizing financial advice based on the emotional data, and a means for evaluating the user's mental state and generating relaxation content, thereby enabling the provision of preventive risk assessment and educational content for improving financial knowledge in response to the user's emotional state and real-time market fluctuations.

[1219] "Financial data" refers to data that indicates the user's financial situation, such as income, expenditure, savings, and investment information.

[1220] A "generative artificial intelligence vehicle" is a vehicle that uses artificial intelligence techniques to generate investment portfolios based on financial data.

[1221] "Investment Portfolio" refers to a combination of investment products, such as stocks, bonds, real estate, and cash, created with a particular user's financial goals and risk tolerance in mind.

[1222] "Emotion data" refers to data that indicates the user's emotional state, collected from the user's facial expression, voice tone, text data, and the like.

[1223] The "means for customizing financial advice" is a means for optimizing financial advice for a user based on collected emotional data.

[1224] "Relaxation content" refers to content such as relaxation music and guided meditation videos that are provided to encourage users to refresh their minds.

[1225] "Market data" refers to data related to various markets that affect investment decisions, such as stock market fluctuations, economic indicators, and exchange rates.

[1226] "Means for generating and transmitting notifications to users in real time" refers to means for quickly analyzing fluctuations in market data and, based on the results, generating and transmitting notifications in real time that recommend appropriate investment actions to users.

[1227] "Financial Risk Assessment" refers to the analysis and assessment of potential future risks based on your financial data.

[1228] "Preventive measures" refer to specific actions or measures that users should take in advance to address assessed risks.

[1229] "Educational Content" means learning materials such as articles, video tutorials, and quizzes that are provided to improve a user's financial knowledge.

[1230] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[1231] Hardware and Software Configuration

[1232] The present invention uses the following hardware and software.

[1233] Hardware:

[1234] Terminal: A device (e.g., computer, smartphone, tablet) that provides a user interface for users to enter data.

[1235] Server: The central device that receives data, analyzes it, generates portfolios, sends notifications, etc.

[1236] software:

[1237] Programming language: Python

[1238] Generative AI model: TensorFlow

[1239] Emotion engine: Microsoft Azure Emotion API or AWS Rekognition

[1240] Database management system: MySQL

[1241] Program processing explanation

[1242] 1. Enter your user information:

[1243] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[1244] 2. Receiving and analyzing financial data:

[1245] The server analyzes the received financial data. The server runs a generative artificial intelligence (AI) model to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[1246] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1247] 3. Portfolio Presentation:

[1248] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[1249] 4. Real-time market data collection and evaluation:

[1250] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1251] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[1252] 5. Preventive Risk Assessment:

[1253] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[1254] 6. Education and Literacy:

[1255] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[1256] 7. Emotion Recognition and Customization with Emotion Engine:

[1257] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[1258] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[1259] 8. Support and relaxation content:

[1260] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[1261] Examples of prompt statements

[1262] Example prompt sentence:

[1263] "Based on market data, due to the current stock market volatility, I would recommend reducing your stock portfolio by 10% to reduce risk and allocating that money to bonds. Also, you can watch a guided meditation video here to help reduce stress."

[1264] In this way, a system is constructed that provides customized advice and support to users that takes into account their individual financial circumstances and emotional state. With this invention, users can manage their assets in an individually optimized manner, and achieve mental stability while preparing for future risks.

[1265] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1266] Step 1: Enter your user information

[1267] The terminal presents the user with a form for entering financial data, including fields for income, expenses, savings, and investment information.

[1268] Input: The user enters income, expenses, savings, and investment information and clicks the submit button.

[1269] Data processing: Convert the data entered by the user into JSON format and send it to the server.

[1270] Output: User's financial data sent to the server.

[1271] Step 2: Receiving and parsing financial data

[1272] The server receives the financial data sent from the user's terminal.

[1273] Input: User's financial data received from the terminal.

[1274] Data Processing and Computation: The server analyzes the received data and processes it using a generative AI model to assess the user's risk tolerance, financial goals, and current asset mix, specifically using Python and TensorFlow.

[1275] Output: Analysis results and optimized investment portfolio.

[1276] Step 3: Generate a portfolio

[1277] The server runs a generative artificial intelligence (AI) model and generates an optimal investment portfolio for the user based on the analysis results.

[1278] Input: Financial data parsed by the server and the user's risk tolerance.

[1279] Data Computing: Generative AI models are used to generate portfolios that take profitability and risk into account.

[1280] Output: Generated investment portfolio (e.g. 40% stocks, 30% bonds, 20% real estate, 10% cash).

[1281] Step 4: Present your portfolio

[1282] The server transmits the generated investment portfolio to the user's terminal.

[1283] Input: Server-generated investment portfolio.

[1284] Output: Display the portfolio on the terminal.

[1285] The device displays the transferred portfolio on the screen, allowing the user to review and adjust it.

[1286] Step 5: Real-time market data collection and evaluation

[1287] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, and currency exchange rates.

[1288] Input: Market data obtained using external APIs and web scraping techniques.

[1289] Data processing and calculation: The server analyzes market fluctuations and assesses their impact on the user's investment portfolio.

[1290] Output: Evaluation results and real-time notifications sent to users.

[1291] For example, if a user's stock holdings suddenly fall, the server may generate and send a notification to the user saying, "Based on current market conditions, we recommend reducing your stock portfolio by 10% and allocating that money to bonds."

[1292] Step 6: Preemptive risk assessment

[1293] The server assesses future financial risk based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks.

[1294] Input: User's financial and market data.

[1295] Data calculation: The server considers multiple risk scenarios and performs a comprehensive risk assessment.

[1296] Output: Predicted risks and recommended preventative measures.

[1297] Based on the evaluation results, the server suggests specific preventive measures to the user.

[1298] Step 7: Education and Literacy

[1299] The server generates appropriate educational content to improve the user's financial knowledge, including articles, video tutorials, and quizzes.

[1300] Input: User comprehension information and current financial knowledge.

[1301] Data processing: Generate educational content and track user learning progress.

[1302] Output: Educational content and learning progress reports.

[1303] The terminal can display the generated educational content to the user and track their learning progress.

[1304] Step 8: Emotion Recognition and Customization with the Emotion Engine

[1305] The terminal or server uses an emotion engine to recognize the user's emotions. It analyzes emotions from the user's facial expressions, voice tone, text data, etc., and transmits the results to the server as emotion data.

[1306] Input: User emotion data.

[1307] Data calculation: The server analyzes the emotion data and evaluates the user's current mental state.

[1308] Output: Sentiment evaluation results and customized advice.

[1309] For example, if the server detects that the user is stressed, it may refrain from providing risky investment advice and suggest safer investment options.

[1310] Step 9: Support and relaxation content

[1311] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos.

[1312] Input: Emotion data and content database.

[1313] Data processing and calculation: Select and generate relaxation content.

[1314] Output: The relaxation content provided to the user.

[1315] The terminal can display these contents to the user to encourage mental refreshment.

[1316] (Application example 2)

[1317] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1318] Previously, there were systems that generated investment portfolios using users' financial data, but they were not customized to take into account the user's emotional state, making it impossible to reduce investment anxiety and stress. Furthermore, they lacked the functionality to analyze market data in real time and send appropriate notifications to users. Furthermore, there was a lack of a system that provided relaxation content based on the user's emotional state. This made it difficult to achieve comprehensive financial management and mental health for users.

[1319] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1320] In this invention, the server includes means for receiving financial data from a user, generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the user's emotional data and evaluating the emotional state, means for customizing investment advice based on the emotional state, and means for generating relaxation content based on the emotional state, thereby enabling the user to receive not only an individually optimized investment portfolio but also investment advice and relaxation content that take into account their emotional state.

[1321] The "means for receiving financial data from a user" refers to the interface and process by which a user inputs financial data such as their income, expenses, savings, and investment information, and the system receives that data.

[1322] A "generative artificial intelligence tool" is an artificial intelligence algorithm and associated system for analyzing input financial data and generating an optimal investment portfolio for a user.

[1323] A "means for presenting an investment portfolio to a user" is an interface and process for displaying the generated investment portfolio on a user's device.

[1324] The "means for analyzing emotional data and assessing an emotional state" refers to software and processes for analyzing emotional data such as a user's facial expression, voice, text, etc., and assessing the user's current emotional state.

[1325] A "means for customizing investment advice based on emotional state" is an algorithm and process for providing appropriate investment advice to a user based on the assessed emotional state.

[1326] A "means for generating relaxation content based on emotional state" is software and processes for generating and providing relaxation content, such as relaxation music or guided meditation videos, based on an assessment of a user's emotional state.

[1327] "Means for collecting market data" refers to algorithms and processes for collecting market data, such as stock market data, economic indicators, and exchange rates, from the Internet and other data sources.

[1328] "Means for analyzing market data to assess the impact on a user's investment portfolio" refers to algorithms and processes for analyzing collected market data and assessing its impact on a user's investment portfolio.

[1329] "Means for generating and sending notifications to users in real time" means software and processes for generating key information and recommendations in real time based on the analysis of market data and sending notifications to users' devices.

[1330] "Means for assessing future financial risks" refers to algorithms and processes for predicting and assessing future financial risks, such as income fluctuations, changes in economic conditions, and health risks, based on the user's current financial data.

[1331] The "means for generating and presenting to a user preventative measures based on the results of risk assessment" refers to software and processes for generating appropriate preventative measures for the assessed financial risks and presenting them to a user's device.

[1332] The "means for providing optimal relaxation content to a user in accordance with emotional data" refers to software and processes for analyzing emotional data and providing relaxation content to reduce the user's stress and anxiety based on the results of the analysis.

[1333] The present invention is a system for analyzing a user's financial and emotional data and providing optimal investment portfolios and relaxation content. This system comprehensively considers the user's financial situation and emotional state and provides optimal advice to support the user's financial management.

[1334] Hardware and software used

[1335] This system is realized using the following hardware and software:

[1336] Hardware: Smartphones, computer servers

[1337] Software: Python, pandas, scikit-learn, TextBlob, generative artificial intelligence

[1338] What the program does

[1339] 1. Enter your user information:

[1340] The device (smartphone) displays a form for the user to enter income, expenditure, savings, and investment information. The user enters this data and clicks the send button to send the data. The sent data is stored on the server.

[1341] 2. Analysis of Financial Data:

[1342] The server analyzes the received financial data and uses generative artificial intelligence to generate an optimal investment portfolio for the user. For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1343] 3. Emotional Data Analysis:

[1344] The terminal or server analyzes the user's emotional data (e.g., facial expressions, voice, and text) and evaluates their emotional state. Based on the evaluated emotional state, it customizes investment advice and generates relaxation content as needed. For example, if it determines that the user is feeling "stressed," it provides relaxation music.

[1345] 4. Portfolio presentation and adjustment:

[1346] The generated investment portfolio is displayed on the user's smartphone. The user can review the portfolio and make adjustments as needed. The adjusted portfolio is also saved in the system for later analysis.

[1347] 5. Real-time market data collection and evaluation:

[1348] The server periodically collects market data, analyzes it, and evaluates the impact on the user's investment portfolio. For example, if the value of stocks drops sharply, a notification will be sent to the user's smartphone saying, "Based on current market conditions, we recommend that you reduce your stock portfolio by 10% and convert that money into bonds."

[1349] Specific examples

[1350] The user entered financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen. The emotion was entered as "stress." Based on this data, the server generated an investment portfolio consisting of 40% stocks, 30% bonds, 20% real estate, and 10% cash, and recommended relaxation music to users who were in a "stressed" state.

[1351] Prompt Sentence Examples

[1352] Based on the financial and emotional data below, please suggest the best investment portfolio and relaxation content for you.

[1353] Income: 6 million yen

[1354] Monthly expenses: 300,000 yen

[1355] Savings: 1 million yen

[1356] Emotion: Stress

[1357] Proposed format:

[1358] 1. Investment Portfolio:

[1359] Stock: XX%

[1360] Bond: XX%

[1361] Real Estate: XX%

[1362] Cash: XX%

[1363] 2. Relaxation Content:

[1364] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1365] Step 1:

[1366] Enter your user information:

[1367] Users enter financial data such as income, expenses, savings, and investment information into an input form on their smartphone. The entered data is sent to the server by clicking the send button. At this time, the input data includes "annual income," "monthly expenses," "savings amount," etc., and this data is received as output by the server.

[1368] Step 2:

[1369] Financial Data Analysis:

[1370] The server analyzes the received financial data. Here, it activates generative artificial intelligence (AI) to generate an optimal investment portfolio for the user based on the input data. Specifically, using input data such as income, expenses, and savings, it calculates asset allocation (stocks, bonds, real estate, cash, etc.) and determines the optimal percentages. For example, if an income is 6 million yen, expenses are 300,000 yen, and savings are 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash. The generated portfolio data is obtained as output.

[1371] Step 3:

[1372] Portfolio presentation:

[1373] The server sends the generated investment portfolio to the user's smartphone. The user can check the portfolio on the smartphone screen and adjust it as necessary. The input data is the portfolio information sent from the server, and the output is the portfolio screen displayed on the user's smartphone.

[1374] Step 4:

[1375] Emotion data acquisition and analysis:

[1376] Users input their emotional state in a separate form on their smartphone. This emotional data is sent to a server, which then uses emotion analysis software to evaluate the emotional state. Input data includes emotional states such as "stress," "anxiety," and "calm," and the analysis results (emotion scores) are obtained as output.

[1377] Step 5:

[1378] Customized investment advice based on sentiment data:

[1379] The server customizes investment advice based on the analyzed emotional data. For example, if the emotional analysis determines that the user is feeling "stressed," it will recommend low-risk investment options. On the other hand, if the analysis determines that the user is "excited," it will suggest investment options that are high-risk but also have high expected returns. The input is an emotional score, and the output is customized investment advice.

[1380] Step 6:

[1381] Creation and provision of relaxation content:

[1382] The server generates relaxation content based on the evaluated emotional data. For example, if the user is judged to be in a high-stress state, it generates relaxation music or guided meditation videos and provides them to the user's smartphone. The input data is the emotion analysis results, and the generated relaxation content is obtained as the output.

[1383] Step 7:

[1384] Real-time market data collection and evaluation:

[1385] The server periodically collects and analyzes market data from the Internet. This data includes stock market fluctuations, economic indicators, and exchange rates. Based on the analysis results, it evaluates the impact on the user's investment portfolio. For example, if a particular stock falls sharply, the server generates a notification such as, "We recommend reducing your stock portfolio by 10% and converting that money into bonds." The input data is the latest market data, and the output is investment advice based on the analysis.

[1386] Step 8:

[1387] Providing real-time notification and prevention:

[1388] The server generates important notifications based on real-time market data and the user's financial data and sends them to the user's smartphone. It also assesses future financial risks and provides specific preventative measures. For example, it provides a notification such as, "There is a high risk of income decline, so we recommend that you save a certain amount." The input data are the user's financial data and market data, and the generated notifications and preventative measures are obtained as outputs.

[1389] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1390] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1391] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1392] [Fourth embodiment]

[1393] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1394] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1395] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1396] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1397] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1398] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1399] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1400] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1401] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1402] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1403] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1404] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1405] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1406] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[1407] The program processing of this system will be specifically explained below.

[1408] 1. Enter your user information:

[1409] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters this information into the terminal and clicks the submit button. The entered financial data is then sent to the server.

[1410] 2. Receiving and analyzing financial data:

[1411] The server analyzes the received financial data and utilizes generative artificial intelligence to assess the user's risk tolerance, financial goals, and current asset mix, based on which the server generates an optimal investment portfolio for the user.

[1412] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1413] 3. Portfolio Presentation:

[1414] The server sends the generated investment portfolio to the user's terminal, which displays it to the user, who can review the presented portfolio and adjust it as needed.

[1415] 4. Real-time market data collection and evaluation:

[1416] The server periodically collects market data and evaluates its impact on the user's investment portfolio in real time. When a significant market movement is detected, the server analyzes its impact and generates a notification for the user, which is sent to the user's device and displayed immediately.

[1417] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[1418] 5. Preventive Risk Assessment:

[1419] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks, and then suggests specific preventive measures to the user based on the results of the evaluation.

[1420] 6. Education and Literacy:

[1421] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[1422] These features allow users to make sound investment decisions, prepare for future risks, and improve financial stability.

[1423] The processing flow will be explained below.

[1424] Step 1:

[1425] The terminal displays a form for the user to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[1426] Step 2:

[1427] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[1428] Step 3:

[1429] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[1430] Step 4:

[1431] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[1432] Step 5:

[1433] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[1434] Step 6:

[1435] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1436] Step 7:

[1437] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[1438] Step 8:

[1439] The server evaluates future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, it generates recommendations for preventive measures (e.g., insurance products and emergency funds) for the user.

[1440] Step 9:

[1441] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[1442] Step 10:

[1443] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[1444] These processing steps enable users to achieve effective asset management and improve financial stability while preparing for future risks.

[1445] Example 1

[1446] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1447] Today's users have a wide variety of financial data, and there is a growing need for the ability to build optimal investment portfolios based on that data, reflect market data in real time, and evaluate future financial risks and provide preventative measures. However, conventional systems struggle to provide these functions in an integrated manner, forcing users to manually collect and analyze multiple pieces of information and make appropriate investment decisions. This places a significant burden on users and can delay their decision-making. Furthermore, there are limited means of providing educational content to improve financial literacy, leaving users with insufficient opportunities to acquire appropriate knowledge.

[1448] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1449] In this invention, the server includes means for receiving financial data from a user, a generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the financial data and market data and evaluating it in real time, means for notifying the user based on the evaluation results, and means for generating educational content to improve the user's financial knowledge. This allows the user to receive appropriate investment portfolio suggestions, enables investment decisions that reflect fluctuations in market data in real time, and provides prompt preventative measures against future financial risks. Educational content to improve the user's financial literacy is also provided, enabling efficient and effective comprehensive financial management.

[1450] "User" means any person or entity that inputs financial data and uses the investment portfolio, notifications, and educational content provided by the System.

[1451] "Financial Data" refers to information that indicates a user's financial status, such as income, expenses, savings, and investment information.

[1452] "Generative AI" refers to an AI technology that suggests optimal investment portfolios based on input data.

[1453] "Investment portfolio" refers to an investment plan that appropriately allocates a user's assets among stocks, bonds, real estate, cash, etc.

[1454] "Market data" refers to data showing trends in stock prices, bond yields, real estate prices, etc. in financial markets.

[1455] "Real-time" refers to a state in which data collection, analysis, notification, and other processes are carried out immediately without delay.

[1456] "Notifications" refer to information sent to users based on market movements and their impact on their investment portfolios.

[1457] "Preventive measures" refer to suggestions and advice on how to respond appropriately to future financial risks.

[1458] "Educational Content" refers to articles, video tutorials, quizzes, and other educational materials provided to improve a user's financial knowledge.

[1459] The present invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data and analyzes it using generative artificial intelligence. It also collects and analyzes market data in real time, evaluates its impact on the user's investment portfolio, and notifies the user as necessary. It also provides educational content to improve the user's financial literacy.

[1460] System configuration

[1461] Entering user information

[1462] The terminal displays a form for the user to enter income, expenditure, savings, and investment information. This form is installed on a web browser using HTML and JavaScript. The user enters information such as income, expenditure, and savings and clicks the "Submit" button. This input data is converted to JSON format and sent to the server using the HTTPS protocol.

[1463] Receiving and analyzing financial data

[1464] The server receives financial data sent by the user using a Python framework. The received data is preprocessed and passed to a generative AI model (e.g., GPT-4). Using the following prompt, the AI ​​model analyzes the user's financial data and generates an optimal investment portfolio.

[1465] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[1466] The resulting portfolio may be allocated, for example, as 40% stocks, 30% bonds, 20% real estate, and 10% cash.

[1467] Portfolio presentation

[1468] The server converts the generated investment portfolio into JSON format and sends it to the terminal. The terminal visualizes this data using HTML and JavaScript and presents it to the user in the form of graphs, etc. The user can review the portfolio and adjust it as needed.

[1469] Real-time market data collection and evaluation

[1470] The server periodically collects real-time market data through market data APIs (e.g., Alpha Vantage and Yahoo Finance). This data is used to evaluate the impact on the user's investment portfolio in real time. When there is a significant market fluctuation, the following prompt sentence is passed to the AI ​​model for evaluation:

[1471] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[1472] The server generates a notification for the user based on the analysis results, sends it to the terminal in JSON format, and displays it immediately.

[1473] Preventive Risk Assessment

[1474] The server uses Python statistical analysis libraries (e.g., pandas and scikit-learn) to assess future financial risks based on the user's financial data, analyzing income fluctuations, changes in economic conditions, health risks, etc., and recommends specific preventive measures to the user as needed.

[1475] Education and Literacy

[1476] The server uses the generative AI model to generate educational content to improve the user's financial literacy. The content is generated using the following prompt sentence as an example.

[1477] "Generate educational content on the fundamentals of investing that your users are interested in."

[1478] The generated educational content includes articles, video tutorials, quizzes, etc., and is provided to the user via their device. The learning progress is tracked by the server, and additional educational content is provided based on the user's level of understanding.

[1479] These features allow users to make appropriate investment decisions, prepare for future risks, and improve financial stability.

[1480] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1481] Step 1:

[1482] Entering user information

[1483] The terminal displays a form using HTML and JavaScript for the user to enter income, expenditure, savings, and investment information.

[1484] Input: User's income, expenses, savings, and investment information.

[1485] Behavior: Validates input using JavaScript.

[1486] Output: Validated financial data.

[1487] The user enters information such as income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, and clicks the "Submit" button.

[1488] What it does: Form input data is converted to JSON format.

[1489] Output: Financial data in JSON format.

[1490] The terminal sends the generated financial data in JSON format to the server via the HTTPS protocol.

[1491] Input: Financial data in JSON format.

[1492] How it works: Encodes transmitted data and sends it securely via HTTPS.

[1493] Output: Connection established with the server and notification of completion.

[1494] Step 2:

[1495] Receiving and analyzing financial data

[1496] The server receives the HTTPS request to receive financial data from the user.

[1497] Input: Financial data in JSON format sent from the terminal.

[1498] What it does: Decodes and receives data, then processes it in a Python framework (e.g. Flask).

[1499] Output: Financial data in internal data format.

[1500] The server preprocesses the received data and passes it to a generative AI model (e.g., GPT-4).

[1501] Input: Financial data in internal data format.

[1502] Action: Any necessary data transformations and preprocessing (e.g., data normalization).

[1503] Output: A prompt to the generative AI model.

[1504] The generative AI model is passed the following prompts to generate an optimal investment portfolio based on the user's risk tolerance and financial goals.

[1505] "User's financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, savings of 1 million yen. Please suggest the optimal investment portfolio taking into account the user's risk tolerance."

[1506] How it works: Analyzes generative AI models and generates portfolios based on prompts.

[1507] Output: An investment portfolio generated by the AI ​​model (e.g., 40% stocks, 30% bonds, 20% real estate, 10% cash).

[1508] Step 3:

[1509] Portfolio presentation

[1510] The server converts the generated investment portfolio into JSON format and sends it to the terminal.

[1511] Input: An investment portfolio generated by an AI model.

[1512] What it does: Converts portfolio data into JSON format.

[1513] Output: Investment portfolio data in JSON format.

[1514] The terminal uses HTML and JavaScript to visualize the received investment portfolio in graphs and other formats and presents it to the user.

[1515] Input: Investment portfolio data in JSON format.

[1516] How it works: Visualization is done using a graphing library (e.g. D3.js, Chart.js).

[1517] Output: A visualized portfolio (e.g., graphs and charts).

[1518] The user reviews the presented portfolio and makes adjustments as necessary.

[1519] Action: Portfolio adjustment (e.g. increase stock percentage to 50%).

[1520] Output: Adjusted portfolio data.

[1521] Step 4:

[1522] Real-time market data collection and evaluation

[1523] The server periodically collects real-time market data via market data APIs (e.g., Alpha Vantage, Yahoo Finance).

[1524] Input: Market data obtained from API.

[1525] How it works: Collects data using HTTP requests.

[1526] Output: Real-time market data.

[1527] The server analyzes the collected market data and assesses its impact on the user's investment portfolio.

[1528] Input: Real-time market data and user's investment portfolio.

[1529] Actions: Use data analysis libraries (e.g. pandas, NumPy) to assess impact.

[1530] Output: Evaluation results.

[1531] If a significant market fluctuation is detected, the server passes the following prompts to the AI ​​model to generate a countermeasure:

[1532] "Evaluate current market data based on your investment portfolio and notify me of any significant market movements, their impact, and how to respond. Current Market Data: Stock market down 10%."

[1533] Action: Impact assessment and countermeasure generation using AI models.

[1534] Output: Specific notification and action to the user.

[1535] The device immediately displays notifications received from the server to the user using HTML and JavaScript.

[1536] Input: Notification data received from the server.

[1537] Action: Show a notification (e.g. popup, alert).

[1538] Output: A notification is displayed to the user.

[1539] Step 5:

[1540] Preventive Risk Assessment

[1541] The server uses Python statistical analysis libraries (e.g., pandas, scikit-learn) to assess future financial risk based on the user's financial data.

[1542] Input: User's financial data.

[1543] Behavior: Application of statistical analysis and predictive models.

[1544] Output: Risk assessment results.

[1545] The server generates preventive measures based on the risk assessment results and presents them to the user.

[1546] Input: Risk assessment results.

[1547] Action: Generate preventative measures (using AI models).

[1548] Output: Provides specific preventive measures to the user.

[1549] Step 6:

[1550] Education and Literacy

[1551] The server uses the generative AI model to generate educational content to improve the user's financial literacy.

[1552] Input: User's learning needs.

[1553] How it works: Generating educational content using AI models.

[1554] Output: Financial education content.

[1555] The server sends the generated educational content to the terminal in JSON format.

[1556] Input: Generated educational content.

[1557] Operation: Convert to JSON format and send.

[1558] Output: Educational content in JSON format.

[1559] The device displays educational content using HTML and JavaScript and tracks the user's learning progress.

[1560] Input: Educational content in JSON format.

[1561] What it does: Presents educational content and tracks progress.

[1562] Output: User's learning progress data.

[1563] (Application example 1)

[1564] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1565] Conventional financial management systems struggled to provide optimal investment portfolios based on users' individual financial data, and lacked the functionality to collect and analyze market data in real time and immediately notify users of its impact on their investment portfolios. This made it difficult for users to make timely and appropriate investment decisions, and they were inadequately prepared for future financial risks. Furthermore, there was no system in place that provided educational content to help improve financial literacy, so it was difficult to expect users' financial knowledge to improve.

[1566] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1567] In this invention, the server includes a means for receiving financial data from a user, a generating AI model means for generating an investment portfolio based on the financial data, a means for presenting the investment portfolio to the user, and a means for providing educational content to the user, thereby enabling the user to obtain an individually optimized investment portfolio and improve their financial literacy.

[1568] Furthermore, in this invention, the server includes means for collecting market data, means for analyzing the market data to assess the impact on the user's investment portfolio, means for generating and sending notifications to the user in real time based on the assessment results, and means for collecting and analyzing expenditure data in cooperation with a payment service, thereby enabling the user to quickly respond appropriately to real-time market fluctuations.

[1569] Furthermore, in this invention, the server includes means for assessing future financial risks based on the user's financial data, means for generating preventive measures based on the risk assessment results and presenting them to the user, and means for providing additional educational content according to the user's level of understanding, thereby enabling the user to take more specific preventive measures against future financial risks and deepen their financial knowledge.

[1570] "Financial Data" means information about a User's income, expenses, savings, and investments.

[1571] The "generative AI model means" is an artificial intelligence technology that analyzes a user's financial data and generates an optimal investment portfolio.

[1572] An "investment portfolio" is a combination of various financial instruments and assets based on a user's financial goals and risk tolerance.

[1573] "Educational Content" is learning material such as articles, videos, and quizzes designed to improve users' financial literacy.

[1574] "Market data" refers to real-time trading information and related data in financial markets, such as stock prices, bond prices, and exchange rates.

[1575] "Means for generating and sending notifications to users in real time" refers to technology that instantly analyzes important information such as market fluctuations and sends appropriate notifications to users.

[1576] "Means for collecting and analyzing expenditure data in cooperation with payment services" refers to technology that works in cooperation with the electronic payment services used by users to collect expenditure data and integrate it into financial data.

[1577] "Means for assessing future financial risks" refers to technology that predicts and assesses risks associated with a user's financial situation, taking into account factors such as fluctuations in income, changes in economic conditions, and health risks.

[1578] "Means for generating preventive measures and presenting them to users" is a technology that proposes and displays specific measures that users should take in response to assessed financial risks.

[1579] The "means for providing additional educational content according to the user's level of understanding" is a technology that provides optimal additional learning materials based on the user's learning progress and level of understanding.

[1580] This invention relates to an integrated system that analyzes a user's financial data, provides an individually optimized investment portfolio, and prepares for future financial risks. The system collects the user's financial data, analyzes it using generative AI, and presents an optimal investment portfolio based on the results. It also provides educational content to improve the user's financial literacy, collects and analyzes market data in real time, and immediately notifies the user of the impact on the investment portfolio.

[1581] The server first receives financial data from the user, including income, expenses, savings, and investment information. The data entered by the user is encrypted and stored in cloud storage. The received data is then analyzed using a generative AI model to evaluate the user's risk tolerance, financial goals, and current asset mix. Based on this, the server generates an optimal investment portfolio for the user and presents it to the user's device.

[1582] Users can review the proposed investment portfolio and adjust it as necessary, and the adjusted portfolio can also be re-analyzed by the AI ​​in real time.

[1583] The server also collects real-time market data via APIs from external financial data providers. Based on this market data, the impact on the user's investment portfolio is assessed, and if significant market fluctuations are detected, the system immediately notifies the user. For example, if there is a major market fluctuation, the system can send a notification such as, "Based on the current market conditions, we recommend reducing your stock portfolio by 10% and allocating that capital to bonds."

[1584] In addition, the system works in conjunction with electronic payment services to collect and analyze users' spending data and reflect it in real-time financial data, allowing users to constantly monitor their spending patterns and more accurately assess their financial situation.

[1585] The server also evaluates future financial risks based on the user's financial data, and generates and presents to the user preventive measures that take into account, for example, fluctuations in income, changes in economic conditions, health risks, etc. This evaluation and preventive measures allow the user to prepare for future unforeseen events.

[1586] Additionally, to improve users' financial literacy, the server generates and provides appropriate educational content to users. The educational content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[1587] For example, if a user inputs their annual income of ¥6 million, monthly expenses of ¥300,000, and savings of ¥1 million, the server will use this data to generate a portfolio with 40% stocks, 30% bonds, 20% real estate, and 10% cash. This information is fed into the generative AI model using the following prompt:

[1588] Example prompt sentence:

[1589] "Analyze this financial data and suggest the optimal investment portfolio:

[1590] Income: 6 million yen

[1591] Expenses: 300,000 yen

[1592] Savings: 1 million yen

[1593] Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen

[1594] In this way, the present invention provides users with an effective means of making optimal financial management and investment proposals and preparing for future financial risks.

[1595] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1596] Step 1:

[1597] Users launch the application on their smartphone and enter their income, expenses, savings, and investment information. This data is encrypted and sent to the server, where it is stored in cloud storage in JSON format.

[1598] Step 2:

[1599] The server inputs the received user's financial data (income, expenses, savings, and investment information) into a generative AI model to generate an optimal investment portfolio. The generative AI model processes and analyzes the data using the analysis prompt: "Analyze this financial data and propose the optimal investment portfolio: Income: 6 million yen, Expenses: 300,000 yen, Savings: 1 million yen, Investments: Stocks: 200,000 yen, Bonds: 100,000 yen, Real Estate: 50,000 yen," and outputs the optimal investment portfolio.

[1600] Step 3:

[1601] The server sends the generated investment portfolio to the user's device. The device displays the portfolio in a user-friendly interface, allowing the user to review and adjust it. If the user makes any adjustments, the data is sent back to the server and reanalyzed by the generative AI model.

[1602] Step 4:

[1603] The server collects market data in real time from external financial data providers (e.g., financial market data API). This data includes price fluctuations of financial products and stock price information. The server periodically analyzes this data and evaluates its impact on the user's investment portfolio. The server analyzes the data using the evaluation prompt: "Based on the current market situation, please evaluate the impact on this portfolio and suggest any necessary changes: Portfolio information, Market data" and obtains the impact evaluation results as output.

[1604] Step 5:

[1605] The server generates real-time notifications based on the evaluation results and sends them to the user's terminal. The notifications include specific investment action recommendations (e.g., "We recommend reducing your stock portfolio by 10% and allocating the funds to bonds.") The user receives the notifications on their terminal and adjusts their investment portfolio as necessary.

[1606] Step 6:

[1607] The server works with the electronic payment service to collect and analyze the user's spending data. It obtains data on the user's spending from the payment service and reflects it in real time in the financial data. This allows the user's spending patterns to be tracked and financial management to be more accurate based on spending.

[1608] Step 7:

[1609] The server evaluates future financial risks based on the user's financial data. For example, it takes into account fluctuations in income, changes in economic conditions, health risks, etc., and performs analysis using the risk assessment prompt: "Given the user's current financial situation, assess possible risks and propose preventive measures: financial data, economic data, user information," and obtains a financial risk assessment result as an output.

[1610] Step 8:

[1611] The server generates preventive measures based on the evaluation results and presents them to the user, allowing the user to prepare for future unforeseen events.Specific preventive measures (e.g., insurance product recommendations, emergency savings suggestions) are presented.

[1612] Step 9:

[1613] The server generates and provides educational content to improve users' financial literacy. The content includes articles explaining the basics of financial management, video tutorials introducing investment best practices, and quiz-style learning materials. The server tracks the user's learning progress and provides additional educational content based on their level of understanding.

[1614] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1615] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[1616] The program processing of this system will be specifically explained below.

[1617] 1. Enter your user information:

[1618] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[1619] 2. Receiving and analyzing financial data:

[1620] The server analyzes the received financial data. The server activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[1621] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1622] 3. Portfolio Presentation:

[1623] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[1624] 4. Real-time market data collection and evaluation:

[1625] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1626] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[1627] 5. Preventive Risk Assessment:

[1628] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[1629] 6. Education and Literacy:

[1630] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[1631] 7. Emotion Recognition and Customization with Emotion Engine:

[1632] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[1633] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[1634] 8. Support and relaxation content:

[1635] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[1636] These features allow users to achieve personalized asset management, prepare for future risks, and improve their financial stability with emotionally sensitive support.

[1637] The processing flow will be explained below.

[1638] Step 1:

[1639] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button.

[1640] Step 2:

[1641] The terminal converts the user's financial data into JSON format and sends it to the server, including information on income, expenses, savings, and existing investments.

[1642] Step 3:

[1643] The server analyzes the received financial data and activates a generative artificial intelligence (AI) module to process the data to assess the user's risk tolerance, financial goals, and current asset mix.

[1644] Step 4:

[1645] The server then generates an optimal investment portfolio based on the analysis, which includes the proportions of stocks, bonds, real estate, cash, and other investments.

[1646] Step 5:

[1647] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as necessary.

[1648] Step 6:

[1649] The device captures the user's facial expressions, voice tone, text data, etc. into the emotion engine. The user may interact with the device to provide this data (e.g., answering questions, using the camera, etc.).

[1650] Step 7:

[1651] The emotion engine analyzes the collected data and evaluates the user's emotional state, generating emotion data such as whether the user is relaxed, excited, or stressed.

[1652] Step 8:

[1653] The server receives the emotion data generated by the emotion engine and evaluates the user's current mental state, and customizes financial advice based on the evaluation.

[1654] Step 9:

[1655] If the server determines that the user's emotional state indicates increased stress or anxiety, it can refrain from offering risky investment advice and suggest safer investment options (e.g., bonds or cash). It can also emphasize proactive risk assessment advice if it recognizes the user's state of agitation.

[1656] Step 10:

[1657] The server generates relaxation content based on the user's emotional state, such as relaxation music or guided meditation videos.

[1658] Step 11:

[1659] The server transmits the generated relaxation content to the user's terminal, which displays the content to the user to encourage mental refreshment.

[1660] Step 12:

[1661] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1662] Step 13:

[1663] If a significant market movement is detected, the server notifies the user of its impact, including suggestions for specific actions (e.g., portfolio readjustment). The terminal displays this notification to the user in real time.

[1664] Step 14:

[1665] The server assesses future financial risks based on the user's financial data. The risk assessment takes into account income fluctuations, changes in economic conditions, health risks, etc. Based on the assessment results, the server recommends specific preventive measures (e.g., insurance products or emergency fund arrangements) to the user.

[1666] Step 15:

[1667] The server generates educational content to improve the user's financial literacy, including articles, video tutorials, quizzes, etc. The terminal provides the educational content to the user and allows the user to check their learning progress.

[1668] Step 16:

[1669] The device tracks the user's learning progress and sends it to the server, which analyzes the learning progress and provides additional educational content according to the user's level of understanding.

[1670] These specific processing steps allow users to effectively manage their assets, prepare for future risks, and improve their financial stability while receiving support that takes into account their emotional state.

[1671] Example 2

[1672] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1673] While existing financial analysis systems have the ability to generate investment portfolios based on users' financial data, they lack the ability to respond to users' emotional states and real-time market fluctuations. This leaves users with the problem of having to make investment decisions while feeling stressed and anxious. Furthermore, they lack the provision of educational content to help users address future financial risks and improve their financial knowledge.

[1674] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1675] In this invention, the server includes a generative artificial intelligence means for receiving financial data from a user and generating an investment portfolio based on the financial data, a means for collecting emotional data from the user and customizing financial advice based on the emotional data, and a means for evaluating the user's mental state and generating relaxation content, thereby enabling the provision of preventive risk assessment and educational content for improving financial knowledge in response to the user's emotional state and real-time market fluctuations.

[1676] "Financial data" refers to data that indicates the user's financial situation, such as income, expenditure, savings, and investment information.

[1677] A "generative artificial intelligence vehicle" is a vehicle that uses artificial intelligence techniques to generate investment portfolios based on financial data.

[1678] "Investment Portfolio" refers to a combination of investment products, such as stocks, bonds, real estate, and cash, created with a particular user's financial goals and risk tolerance in mind.

[1679] "Emotion data" refers to data that indicates the user's emotional state, collected from the user's facial expression, voice tone, text data, and the like.

[1680] The "means for customizing financial advice" is a means for optimizing financial advice for a user based on collected emotional data.

[1681] "Relaxation content" refers to content such as relaxation music and guided meditation videos that are provided to encourage users to refresh their minds.

[1682] "Market data" refers to data related to various markets that affect investment decisions, such as stock market fluctuations, economic indicators, and exchange rates.

[1683] "Means for generating and transmitting notifications to users in real time" refers to means for quickly analyzing fluctuations in market data and, based on the results, generating and transmitting notifications in real time that recommend appropriate investment actions to users.

[1684] "Financial Risk Assessment" refers to the analysis and assessment of potential future risks based on your financial data.

[1685] "Preventive measures" refer to specific actions or measures that users should take in advance to address assessed risks.

[1686] "Educational Content" means learning materials such as articles, video tutorials, and quizzes that are provided to improve a user's financial knowledge.

[1687] The present invention is an integrated system that analyzes a user's financial data, provides a personalized investment portfolio, and prepares for future financial risks. The present invention also includes a system that recognizes a user's emotions and utilizes the data to provide optimal advice and recommendations. The system customizes financial advice based on the user's emotional data, assesses the user's stress and anxiety levels, and potentially provides relaxation content.

[1688] Hardware and Software Configuration

[1689] The present invention uses the following hardware and software.

[1690] Hardware:

[1691] Terminal: A device (e.g., computer, smartphone, tablet) that provides a user interface for users to enter data.

[1692] Server: The central device that receives data, analyzes it, generates portfolios, sends notifications, etc.

[1693] software:

[1694] Programming language: Python

[1695] Generative AI model: TensorFlow

[1696] Emotion engine: Microsoft Azure Emotion API or AWS Rekognition

[1697] Database management system: MySQL

[1698] Program processing explanation

[1699] 1. Enter your user information:

[1700] The terminal presents the user with a form to enter income, expenses, savings, and investment information. The user enters the required financial data into the form and clicks the submit button. The entered financial data is then sent to the server.

[1701] 2. Receiving and analyzing financial data:

[1702] The server analyzes the received financial data. The server runs a generative artificial intelligence (AI) model to process the data to assess the user's risk tolerance, financial goals, and current asset mix. Based on the analysis, the server generates an optimal investment portfolio for the user.

[1703] For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, the server will use this data to generate a portfolio with 40% allocated to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1704] 3. Portfolio Presentation:

[1705] The server sends the generated investment portfolio to the user's terminal, which displays the portfolio to the user, who can review the presented portfolio and adjust it as needed.

[1706] 4. Real-time market data collection and evaluation:

[1707] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, exchange rates, etc. The server analyzes the collected market data and evaluates its impact on the user's investment portfolio.

[1708] For example, if a user's stock holdings plummet, the server might send the user a notification such as, "Based on current market conditions, we recommend you reduce your stock portfolio by 10% and allocate that money to bonds."

[1709] 5. Preventive Risk Assessment:

[1710] The server evaluates future financial risks based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks. Based on the results of the evaluation, the server suggests specific preventive measures for the user.

[1711] 6. Education and Literacy:

[1712] The server generates appropriate educational content to improve the user's financial knowledge. The content can include articles, video tutorials, and quizzes, and is provided to the user via their device. The server tracks the user's progress through the content, and provides additional educational content based on the user's level of understanding.

[1713] 7. Emotion Recognition and Customization with Emotion Engine:

[1714] The device or server uses an emotion engine to recognize the user's emotions. It analyzes the user's emotions from facial expressions, voice tone, text data, etc. and sends them to the server as emotion data. The server then evaluates the user's current mental state based on this emotion data.

[1715] For example, if the server detects that the user is stressed, it can refrain from offering risky investment advice and suggest safer investment options, or if the server detects that the user is agitated, it can emphasize proactive risk assessment advice.

[1716] 8. Support and relaxation content:

[1717] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos. The device displays this content to the user, encouraging them to refresh their mind.

[1718] Examples of prompt statements

[1719] Example prompt sentence:

[1720] "Based on market data, due to the current stock market volatility, I would recommend reducing your stock portfolio by 10% to reduce risk and allocating that money to bonds. Also, you can watch a guided meditation video here to help reduce stress."

[1721] In this way, a system is constructed that provides customized advice and support to users that takes into account their individual financial circumstances and emotional state. With this invention, users can manage their assets in an individually optimized manner, and achieve mental stability while preparing for future risks.

[1722] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1723] Step 1: Enter your user information

[1724] The terminal presents the user with a form for entering financial data, including fields for income, expenses, savings, and investment information.

[1725] Input: The user enters income, expenses, savings, and investment information and clicks the submit button.

[1726] Data processing: Convert the data entered by the user into JSON format and send it to the server.

[1727] Output: User's financial data sent to the server.

[1728] Step 2: Receiving and parsing financial data

[1729] The server receives the financial data sent from the user's terminal.

[1730] Input: User's financial data received from the terminal.

[1731] Data Processing and Computation: The server analyzes the received data and processes it using a generative AI model to assess the user's risk tolerance, financial goals, and current asset mix, specifically using Python and TensorFlow.

[1732] Output: Analysis results and optimized investment portfolio.

[1733] Step 3: Generate a portfolio

[1734] The server runs a generative artificial intelligence (AI) model and generates an optimal investment portfolio for the user based on the analysis results.

[1735] Input: Financial data parsed by the server and the user's risk tolerance.

[1736] Data Computing: Generative AI models are used to generate portfolios that take profitability and risk into account.

[1737] Output: Generated investment portfolio (e.g. 40% stocks, 30% bonds, 20% real estate, 10% cash).

[1738] Step 4: Present your portfolio

[1739] The server transmits the generated investment portfolio to the user's terminal.

[1740] Input: Server-generated investment portfolio.

[1741] Output: Display the portfolio on the terminal.

[1742] The device displays the transferred portfolio on the screen, allowing the user to review and adjust it.

[1743] Step 5: Real-time market data collection and evaluation

[1744] The server periodically collects and analyzes market data, including stock market fluctuations, economic indicators, and currency exchange rates.

[1745] Input: Market data obtained using external APIs and web scraping techniques.

[1746] Data processing and calculation: The server analyzes market fluctuations and assesses their impact on the user's investment portfolio.

[1747] Output: Evaluation results and real-time notifications sent to users.

[1748] For example, if a user's stock holdings suddenly fall, the server may generate and send a notification to the user saying, "Based on current market conditions, we recommend reducing your stock portfolio by 10% and allocating that money to bonds."

[1749] Step 6: Preemptive risk assessment

[1750] The server assesses future financial risk based on the user's financial data, taking into account factors such as income fluctuations, changes in economic conditions, and health risks.

[1751] Input: User's financial and market data.

[1752] Data calculation: The server considers multiple risk scenarios and performs a comprehensive risk assessment.

[1753] Output: Predicted risks and recommended preventative measures.

[1754] Based on the evaluation results, the server suggests specific preventive measures to the user.

[1755] Step 7: Education and Literacy

[1756] The server generates appropriate educational content to improve the user's financial knowledge, including articles, video tutorials, and quizzes.

[1757] Input: User comprehension information and current financial knowledge.

[1758] Data processing: Generate educational content and track user learning progress.

[1759] Output: Educational content and learning progress reports.

[1760] The terminal can display the generated educational content to the user and track their learning progress.

[1761] Step 8: Emotion Recognition and Customization with the Emotion Engine

[1762] The terminal or server uses an emotion engine to recognize the user's emotions. It analyzes emotions from the user's facial expressions, voice tone, text data, etc., and transmits the results to the server as emotion data.

[1763] Input: User emotion data.

[1764] Data calculation: The server analyzes the emotion data and evaluates the user's current mental state.

[1765] Output: Sentiment evaluation results and customized advice.

[1766] For example, if the server detects that the user is stressed, it may refrain from providing risky investment advice and suggest safer investment options.

[1767] Step 9: Support and relaxation content

[1768] The server generates relaxation content based on the user's emotional data. For example, if the server detects that the user is in a high-stress state, it will provide relaxation music or guided meditation videos.

[1769] Input: Emotion data and content database.

[1770] Data processing and calculation: Select and generate relaxation content.

[1771] Output: The relaxation content provided to the user.

[1772] The terminal can display these contents to the user to encourage mental refreshment.

[1773] (Application example 2)

[1774] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1775] Previously, there were systems that generated investment portfolios using users' financial data, but they were not customized to take into account the user's emotional state, making it impossible to reduce investment anxiety and stress. Furthermore, they lacked the functionality to analyze market data in real time and send appropriate notifications to users. Furthermore, there was a lack of a system that provided relaxation content based on the user's emotional state. This made it difficult to achieve comprehensive financial management and mental health for users.

[1776] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1777] In this invention, the server includes means for receiving financial data from a user, generative artificial intelligence means for generating an investment portfolio based on the financial data, means for presenting the investment portfolio to the user, means for analyzing the user's emotional data and evaluating the emotional state, means for customizing investment advice based on the emotional state, and means for generating relaxation content based on the emotional state, thereby enabling the user to receive not only an individually optimized investment portfolio but also investment advice and relaxation content that take into account their emotional state.

[1778] The "means for receiving financial data from a user" refers to the interface and process by which a user inputs financial data such as their income, expenses, savings, and investment information, and the system receives that data.

[1779] A "generative artificial intelligence tool" is an artificial intelligence algorithm and associated system for analyzing input financial data and generating an optimal investment portfolio for a user.

[1780] A "means for presenting an investment portfolio to a user" is an interface and process for displaying the generated investment portfolio on a user's device.

[1781] The "means for analyzing emotional data and assessing an emotional state" refers to software and processes for analyzing emotional data such as a user's facial expression, voice, text, etc., and assessing the user's current emotional state.

[1782] A "means for customizing investment advice based on emotional state" is an algorithm and process for providing appropriate investment advice to a user based on the assessed emotional state.

[1783] A "means for generating relaxation content based on emotional state" is software and processes for generating and providing relaxation content, such as relaxation music or guided meditation videos, based on an assessment of a user's emotional state.

[1784] "Means for collecting market data" refers to algorithms and processes for collecting market data, such as stock market data, economic indicators, and exchange rates, from the Internet and other data sources.

[1785] "Means for analyzing market data to assess the impact on a user's investment portfolio" refers to algorithms and processes for analyzing collected market data and assessing its impact on a user's investment portfolio.

[1786] "Means for generating and sending notifications to users in real time" means software and processes for generating key information and recommendations in real time based on the analysis of market data and sending notifications to users' devices.

[1787] "Means for assessing future financial risks" refers to algorithms and processes for predicting and assessing future financial risks, such as income fluctuations, changes in economic conditions, and health risks, based on the user's current financial data.

[1788] The "means for generating and presenting to a user preventative measures based on the results of risk assessment" refers to software and processes for generating appropriate preventative measures for the assessed financial risks and presenting them to a user's device.

[1789] The "means for providing optimal relaxation content to a user in accordance with emotional data" refers to software and processes for analyzing emotional data and providing relaxation content to reduce the user's stress and anxiety based on the results of the analysis.

[1790] The present invention is a system for analyzing a user's financial and emotional data and providing optimal investment portfolios and relaxation content. This system comprehensively considers the user's financial situation and emotional state and provides optimal advice to support the user's financial management.

[1791] Hardware and software used

[1792] This system is realized using the following hardware and software:

[1793] Hardware: Smartphones, computer servers

[1794] Software: Python, pandas, scikit-learn, TextBlob, generative artificial intelligence

[1795] What the program does

[1796] 1. Enter your user information:

[1797] The device (smartphone) displays a form for the user to enter income, expenditure, savings, and investment information. The user enters this data and clicks the send button to send the data. The sent data is stored on the server.

[1798] 2. Analysis of Financial Data:

[1799] The server analyzes the received financial data and uses generative artificial intelligence to generate an optimal investment portfolio for the user. For example, if a user enters an annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash.

[1800] 3. Emotional Data Analysis:

[1801] The terminal or server analyzes the user's emotional data (e.g., facial expressions, voice, and text) and evaluates their emotional state. Based on the evaluated emotional state, it customizes investment advice and generates relaxation content as needed. For example, if it determines that the user is feeling "stressed," it provides relaxation music.

[1802] 4. Portfolio presentation and adjustment:

[1803] The generated investment portfolio is displayed on the user's smartphone. The user can review the portfolio and make adjustments as needed. The adjusted portfolio is also saved in the system for later analysis.

[1804] 5. Real-time market data collection and evaluation:

[1805] The server periodically collects market data, analyzes it, and evaluates the impact on the user's investment portfolio. For example, if the value of stocks drops sharply, a notification will be sent to the user's smartphone saying, "Based on current market conditions, we recommend that you reduce your stock portfolio by 10% and convert that money into bonds."

[1806] Specific examples

[1807] The user entered financial data: annual income of 6 million yen, monthly expenses of 300,000 yen, and savings of 1 million yen. The emotion was entered as "stress." Based on this data, the server generated an investment portfolio consisting of 40% stocks, 30% bonds, 20% real estate, and 10% cash, and recommended relaxation music to users who were in a "stressed" state.

[1808] Prompt Sentence Examples

[1809] Based on the financial and emotional data below, please suggest the best investment portfolio and relaxation content for you.

[1810] Income: 6 million yen

[1811] Monthly expenses: 300,000 yen

[1812] Savings: 1 million yen

[1813] Emotion: Stress

[1814] Proposed format:

[1815] 1. Investment Portfolio:

[1816] Stock: XX%

[1817] Bond: XX%

[1818] Real Estate: XX%

[1819] Cash: XX%

[1820] 2. Relaxation Content:

[1821] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1822] Step 1:

[1823] Enter your user information:

[1824] Users enter financial data such as income, expenses, savings, and investment information into an input form on their smartphone. The entered data is sent to the server by clicking the send button. At this time, the input data includes "annual income," "monthly expenses," "savings amount," etc., and this data is received as output by the server.

[1825] Step 2:

[1826] Financial Data Analysis:

[1827] The server analyzes the received financial data. Here, it activates generative artificial intelligence (AI) to generate an optimal investment portfolio for the user based on the input data. Specifically, using input data such as income, expenses, and savings, it calculates asset allocation (stocks, bonds, real estate, cash, etc.) and determines the optimal percentages. For example, if an income is 6 million yen, expenses are 300,000 yen, and savings are 1 million yen, a portfolio will be generated that allocates 40% to stocks, 30% to bonds, 20% to real estate, and 10% to cash. The generated portfolio data is obtained as output.

[1828] Step 3:

[1829] Portfolio presentation:

[1830] The server sends the generated investment portfolio to the user's smartphone. The user can check the portfolio on the smartphone screen and adjust it as necessary. The input data is the portfolio information sent from the server, and the output is the portfolio screen displayed on the user's smartphone.

[1831] Step 4:

[1832] Emotion data acquisition and analysis:

[1833] Users input their emotional state in a separate form on their smartphone. This emotional data is sent to a server, which then uses emotion analysis software to evaluate the emotional state. Input data includes emotional states such as "stress," "anxiety," and "calm," and the analysis results (emotion scores) are obtained as output.

[1834] Step 5:

[1835] Customized investment advice based on sentiment data:

[1836] The server customizes investment advice based on the analyzed emotional data. For example, if the emotional analysis determines that the user is feeling "stressed," it will recommend low-risk investment options. On the other hand, if the analysis determines that the user is "excited," it...

Claims

1. means for receiving financial data from a user; a generative artificial intelligence means for generating an investment portfolio based on the financial data; means for presenting said investment portfolio to a user; A system including:

2. a means of collecting market data; means for analyzing said market data to assess the impact on a user's investment portfolio; means for generating and sending a notification to a user in real time based on the evaluation results; The system of claim 1 further comprising:

3. a means for assessing future financial risk based on the user's financial data; means for generating preventive measures based on the risk assessment results and presenting the preventive measures to a user; The system of claim 1 further comprising:

4. A means for generating educational content aimed at improving the financial literacy of users; means for providing said educational content to a user; a means for tracking a user's learning progress; The system of claim 1 further comprising:

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