system

Abstract

We provide the system. [Solution] An input method for entering the user's financial information, An analysis means that analyzes the input financial information and generates individually tailored financial advice, A sentiment analysis tool that analyzes user emotions and creates messages based on their psychological state, An output method that provides users with real-time advice and emotion-based messages, A system that includes this.

Description

【Technical Field】 【0001】 The technology of the present disclosure relates to a system. 【Background Art】 【0002】 Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, the method including: receiving a user utterance; adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot; encoding the prompt; and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. 【Prior Art Documents】 【Patent Documents】 【0003】 【Patent Document 1】 Japanese Patent Application Laid-Open No. 2022-180282 【Summary of the Invention】 【Problems to be Solved by the Invention】 【0004】 In modern society, it is necessary to reduce the financial anxiety faced by individuals and to compensate for the shortage of reliable financial advisors. In addition, there is a demand for a system that can provide personalized advice according to the financial situation of users. However, in the prior art, it is difficult to provide this in real time and considering the emotional aspect. Furthermore, it is required to create an environment that can be easily accessed by users who are not familiar with technology using voice input. 【Means for Solving the Problems】 【0005】 This invention provides an analysis means that first inputs the user's financial information and generates individually tailored financial advice based on that information. Furthermore, by using an emotion analysis means, it analyzes the user's emotions and creates messages based on their psychological state, enabling the user to use the system with confidence. In addition, it is equipped with an output means that provides this advice and messages in real time, and by using a voice analysis means, it accepts voice input, making it easy for even tech-inexperienced users to use. Moreover, it is equipped with a learning means that receives feedback and continuously improves the system, adapting to the user's needs. 【0006】 A "user" refers to an individual who uses the system to input financial information and receive advice. 【0007】 "Financial information" refers to data related to the user's economic situation, such as age, income, asset status, debt status, and financial goals. 【0008】 "Input means" refers to interfaces or devices used to input a user's financial information into the system. 【0009】 "Analysis means" refers to a function that generates financial advice tailored to the user based on the input financial information. 【0010】 "Emotional analysis methods" refer to technologies that analyze emotions from data and interactions obtained from users and evaluate their psychological state. 【0011】 "Output means" refers to an interface or device for providing the user with generated advice and emotionally tuned messages in real time. 【0012】 "Voice analysis means" refers to technology that analyzes voice input from users to understand their intentions and requests. 【0013】 "Learning tools" refer to functions that receive feedback from users and continuously improve the system's performance and the accuracy of its advice. [Brief explanation of the drawing] 【0014】 [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of the data processing device and smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14]It is a sequence diagram showing the processing flow of a data processing system in Application Example 2 when a sentiment engine is combined. 【Embodiments for Carrying Out the Invention】 【0015】 Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings. 【0016】 First, the terms used in the following description will be explained. 【0017】 In the following embodiments, a numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like. 【0018】 In the following embodiments, a numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor. 【0019】 In the following embodiments, a numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc. 【0020】 In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark). 【0021】 In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or." 【0022】 [First Embodiment] 【0023】 Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment. 【0024】 As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server. 【0025】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0026】 The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52. 【0027】 The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input. 【0028】 The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor. 【0029】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54. 【0030】 Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14. 【0031】 As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30. 【0032】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0033】 In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0034】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0035】 The personal AI financial planner system according to the present invention aims to alleviate users' financial anxieties and provide individually personalized financial advice. This system inputs and analyzes the user's financial information and provides advice, including emotion-based messages, in real time. 【0036】 1. User Input Phase 【0037】 The terminal accepts financial information such as the user's age, income, asset status, debt information, and goals. This information is provided by the user and entered through the terminal interface. 【0038】 2. Data Analysis Phase 【0039】 The server receives data sent by users and securely stores it in a database. Next, it analyzes this data using analytical tools to assess the user's current financial situation and calculate the necessary approaches to achieve their goals. It then generates optimal advice for each user. 【0040】 3. Emotional Analysis Phase 【0041】 The server performs sentiment analysis based on user input. This analysis assesses the user's current psychological state. In particular, if the user is feeling anxious, the sentiment analysis tool generates a reassuring message based on the results. 【0042】 4. Advice Provision Phase 【0043】 Based on the results of analysis and sentiment analysis, the server creates user-optimized advice and appropriate emotional messages. This information is transmitted to the device in real time, and the device provides the advice to the user via screen or audio. 【0044】 As a concrete example, consider a case where a user is trying to create a savings plan for buying a house. This user aims to save 5 million yen in 5 years for the purchase of a house. The device receives the user's annual income, current savings status, and monthly expenses as input. 【0045】 The server analyzes this data, calculates the monthly savings requirement, and identifies areas where savings can be made. Furthermore, if the user is experiencing stress regarding this savings plan, it provides messages based on the emotional analysis results, including realistic spending plans and budget advice. 【0046】 Through this system, individual users can create specific and reliable financial plans tailored to their own needs. 【0047】 The following describes the processing flow. 【0048】 Step 1: 【0049】 The user enters financial information such as their age, income, assets, liabilities, and financial goals through the terminal's input interface. The terminal formats the entered data and sends it to the server using a secure protocol. 【0050】 Step 2: 【0051】 The server stores the user's financial information received from the terminal in a database. Next, it uses analytical tools to understand the user's current situation and performs basic calculations and analyses to achieve financial goals. 【0052】 Step 3: 【0053】 The server uses sentiment analysis tools to evaluate the user's psychological state based on user input and past interaction data. This allows it to understand the user's current emotional tendencies and generate reassuring messages when necessary. 【0054】 Step 4: 【0055】 The server generates personalized financial advice applicable to the user based on data analysis and sentiment analysis results. It also prepares sentiment-based responses. 【0056】 Step 5: 【0057】 The server sends the generated financial advice and emotional messages to the terminal. The terminal displays this through its user interface and provides audio output as needed. 【0058】 Step 6: 【0059】 The user enters feedback and additional questions about the advice provided via the terminal. The terminal then sends this feedback to the server. 【0060】 Step 7: 【0061】 The server analyzes the feedback and uses the AI ​​model to learn what is needed to improve future advice. This allows the system to continuously improve and better meet user needs. 【0062】 (Example 1) 【0063】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0064】 Managing financial information while quickly providing appropriate suggestions tailored to individual circumstances is difficult with conventional systems. Furthermore, the lack of information that considers user emotions makes it difficult for users to make financial decisions with confidence. 【0065】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0066】 In this invention, the server includes an input means for inputting information about the user's finances, an analysis means for analyzing the input financial information and proposing individually tailored finances, and an emotion evaluation means for evaluating the user's psychological state and generating information based on that state. This makes it possible to provide users with individually customized financial proposals and reassuring information in real time. 【0067】 An "input method" is an interface that allows users to provide financial information to the system. 【0068】 "Analysis means" refers to the process of analyzing the input financial information and proposing the optimal financial plan to the user. 【0069】 An "emotional evaluation method" is a process for evaluating a user's psychological state and generating information based on that state. 【0070】 The "output means" is an interface for communicating the results of the analysis and sentiment evaluation to the user. 【0071】 "Voice processing functionality" refers to a function that analyzes voice information to understand user requests. 【0072】 The "learning function" is a feature that analyzes user feedback and continuously improves the content of suggestions based on that feedback. 【0073】 This invention relates to a personal AI financial planner system that alleviates users' financial anxieties and provides individually personalized financial advice. The system works by inputting information about the user's finances, analyzing it, evaluating their emotions, and then providing information based on the results. 【0074】 The device receives financial information from the user. This information includes age, income, assets, liabilities, and goals. The device interface is implemented through web forms or dedicated applications. 【0075】 The server receives this information and securely stores it in a database. Analysis is performed using data analysis libraries in Python and an SQL database. This evaluates the user's financial situation and calculates the optimal approach to achieving the goals to be accomplished. 【0076】 Furthermore, the server uses emotion evaluation tools and natural language processing techniques to analyze the user's psychological state. Based on this analysis, it generates emotionally supportive messages tailored to the user. 【0077】 As a concrete example, consider a user who wants to create a savings plan for buying a house. The user inputs their annual income, current savings status, and monthly expenses into a terminal. The server analyzes this information and provides a calculation of the required monthly savings amount and tips for reducing expenses. Furthermore, if the user is feeling stressed, a message is generated that provides reassurance based on the results of the emotion analysis. 【0078】 As an example of a prompt, the following sentence is input into the AI ​​generation model: "The user aims to save 5 million yen in 5 years. Please provide monthly savings amounts and specific advice on how to save to achieve this goal. Also, please include emotional support to reduce the user's stress level." This prompt allows the system to provide information optimized for the user. 【0079】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0080】 Step 1: 【0081】 Users input information such as age, income, asset status, debt information, and financial goals through their device. The input information is formatted in JSON or XML format and sent to the server. The input in this step is information about the user's finances, and the output is formatted data for storage in the database. 【0082】 Step 2: 【0083】 The server receives user information sent from the terminal and stores it in the database in a secure manner. The database has an SQL structure, with each field corresponding to user information. The input for this step is formatted data sent from the terminal, and the output is the storage operation into the database. 【0084】 Step 3: 【0085】 The server retrieves stored data using SQL queries and performs analysis using a Python data analysis library. The analysis evaluates the balance of income and expenses, savings and debt levels, and calculates the optimal plan for the user to achieve their goals. The input for this step is user information retrieved from the database, and the output is the calculated financial proposal. 【0086】 Step 4: 【0087】 The server uses natural language processing (NLP) techniques to analyze user input and perform sentiment analysis. Specifically, it estimates the user's psychological state from their text and generates messages to alleviate anxiety if present. The input for this step is the user's input, and the output is the generated message based on the sentiment analysis. 【0088】 Step 5: 【0089】 The server integrates analyzed financial recommendations and sentiment analysis-based messages to construct final advice. It selects the most relevant information and prepares to provide immediate feedback to the user. The input for this step is the results of the financial and sentiment analysis, and the output is the final advice and message provided to the user. 【0090】 Step 6: 【0091】 The terminal receives advice and messages sent from the server and presents them to the user via display or audio output. This presentation is in a format that is easy for the user to understand. Specifically, it provides text or audio feedback to help the user act on the suggestions. The input for this step is the final advice and messages from the server, and the output is what is presented to the user. 【0092】 (Application Example 1) 【0093】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal." 【0094】 In modern society, individual consumers face increasing financial anxieties and challenges in managing complex spending. The widespread adoption of electronic payments, in particular, has made it difficult for consumers to track their spending in real time and stick to their budgets. In this context, there is a need for support tools that enable consumers to live their daily lives with peace of mind and to create financial plans that align with their goals. 【0095】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0096】 In this invention, the server includes a device for inputting the user's financial information, a processing device for analyzing the input financial information and generating individually adapted financial advice, an emotion analysis device for analyzing the user's emotions and creating messages based on their psychological state, an output device for providing advice and emotion-based messages to the user in real time, and a notification device for analyzing electronic payment data to evaluate spending patterns and support budget-friendly behavior. This enables consumers to manage their financial situation in real time while also gaining peace of mind. 【0097】 A "device for inputting user financial information" is a device equipped with an interface for collecting information provided by the user, such as age, income, asset status, debt information, and goals. 【0098】 A "processing device that analyzes financial information and generates individually tailored financial advice" is a computing device that calculates and generates the most suitable financial advice for each user based on collected financial information, in real time. 【0099】 A "sentiment analysis device that analyzes emotions and creates messages based on psychological state" is a mechanism that evaluates a user's psychological state based on their input information and behavioral data, and creates a message corresponding to the evaluation results. 【0100】 An "output device that provides users with real-time advice and sentiment-based messages" is a device that instantly transmits financial advice generated by a processing unit and messages created by a sentiment analysis device to the user. 【0101】 A "notification device that analyzes electronic payment data to evaluate spending patterns and support budget-conscious behavior" is a device that analyzes data related to a user's electronic payments, evaluates spending trends, and has the function of notifying the user to maintain spending within their budget. 【0102】 To implement this invention, the user's device must act as a financial information input device, requiring the user to input financial information such as age, income, asset status, debt information, and goals. This information is transmitted to the server via a secure connection. 【0103】 The server acts as a processing unit, analyzing the received financial information. Using a series of analytical methods, it assesses the user's current financial situation and generates personalized financial advice. The analysis utilizes specific algorithms and trend analysis of historical spending data. This technology often employs programming languages ​​such as Python and R, along with data analysis libraries. 【0104】 Furthermore, the server functions as an emotion analyzer, performing emotion analysis based on user-provided text and other interaction data. This analysis evaluates the user's state of anxiety and reassurance, and based on this evaluation, creates emotion-based messages. Natural language processing technology can be used for emotion analysis, and cloud services such as Google's Natural Language API or IBM's Watson® may be used. 【0105】 To provide users with information in real time, the server sends generated financial advice and sentiment messages to the user's device. The user's device displays the message instantly using its notification function. The notification device receives information from the server and provides notifications to help users stay within their budget. For example, if a user is likely to exceed the budget they set at the beginning of the month, the app will display a real-time notification such as, "Your food expenses for this month have reached 80% of your budget." This notification may also refer to past spending trends to indicate areas where savings are possible. 【0106】 Furthermore, it utilizes a generative AI model to generate messages based on the user's thoughts and feelings. This process is achieved by prompting the AI ​​model, for example, by instructing it in the form of "Generate reassuring advice based on the user's current spending." 【0107】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0108】 Step 1: 【0109】 The user enters their financial information into the terminal. The terminal receives information such as age, income, assets, liabilities, and goals, and sends it to the server. This information becomes the input and forms the basis for the next analysis. 【0110】 Step 2: 【0111】 The server analyzes the received financial information. The processing unit calculates the user's income and expenses and evaluates the progress of asset building. An algorithm is used for this, and the specific output generated includes monthly savings requirements and investment plan suggestions. 【0112】 Step 3: 【0113】 The server uses a generative AI model to analyze the user's emotions. It analyzes the words and behavioral history entered by the user using an emotion analysis device to determine their psychological state, such as anxiety or reassurance. Emotional information is used as input, and messages that provide a sense of security are output. 【0114】 Step 4: 【0115】 The server integrates financial advice and sentiment-based messages to generate optimal advice. The processing unit combines the analysis results and sentiment analysis output to formulate the most suitable recommendations for the user. The output includes customized recommendations and reassuring information. 【0116】 Step 5: 【0117】 The server sends the generated advice to the user's terminal in real time. The output device immediately displays a notification on the user's screen, and voice guidance is also available. This allows the user to receive information on their financial situation and psychological support at all times. 【0118】 Step 6: 【0119】 The server analyzes the user's electronic payment data and evaluates spending patterns. It then notifies the user via a notification device of any anomalies or concerns about budget overruns discovered through this analysis. The input is the electronic payment history, and the output includes specific alerts for spending control. 【0120】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0121】 The system according to the present invention aims to alleviate individual financial anxieties by providing personalized financial advice using the user's financial information. In particular, by combining this system with an emotion engine, the system can recognize the user's emotions and reflect them in the content of the advice. 【0122】 First, the user enters their financial information through the terminal's input interface. This information includes age, income, asset status, liabilities, and financial goals. The terminal collects this data and transmits it to the server using a secure communication method. 【0123】 The server analyzes the received data using analytical tools to evaluate the user's financial situation. Based on this, it generates specific financial advice tailored to the user's goals. 【0124】 One of the system's key features is its built-in emotion engine. This engine analyzes the user's emotions based on their input and conversation history. The analyzed emotion data is then used to tailor the advice it provides. For example, if a user is feeling stressed, the emotion engine will generate reassuring messages and reflect this in the advice. 【0125】 The generated advice and emotion-based messages are sent to the device in real time. The device displays this information on the screen and, if necessary, also provides it via audio. Users can provide feedback on the advice, which is sent from the device to the server and used to further improve the system. 【0126】 As a concrete example, consider a scenario where a user has set a savings goal for retirement and wants advice on how to create that plan. In this case, the user enters the necessary information into a terminal. The server analyzes this information and uses an emotion engine to prepare a message that alleviates the user's anxiety. After that, it provides the user with specific advice regarding their savings plan. 【0127】 Thus, the present invention provides personalized financial support that takes user emotions into consideration, creating an environment in which users can confidently engage in financial planning. 【0128】 The following describes the processing flow. 【0129】 Step 1: 【0130】 Users access a dedicated application on their device and enter their personal financial information. This information includes age, income, current assets, debt, and specific financial goals, which the device then organizes as digital data. 【0131】 Step 2: 【0132】 The terminal sends organized user data to the server using a secure protocol. This communication is encrypted to ensure data confidentiality. 【0133】 Step 3: 【0134】 The server first stores the received user data in a database. Next, it uses analytical tools to analyze the user's wealth management situation in detail and consider specific strategies for achieving goals. 【0135】 Step 4: 【0136】 The server activates the emotion engine, analyzes the user's input data and past interactions, and assesses their current emotional state. If it detects that the user is, for example, stressed, it tailors the message to address that. 【0137】 Step 5: 【0138】 The server integrates the analysis results and sentiment analysis results to generate user-optimized financial advice and emotionally sensitive messages. 【0139】 Step 6: 【0140】 The generated advice and messages are sent to the terminal in real time. The terminal displays them through its user interface and also provides audio output if necessary. 【0141】 Step 7: 【0142】 Users can enter feedback on the advice provided into their device. This feedback is sent to the server and used to improve the accuracy of future advice generation. 【0143】 Step 8: 【0144】 The server learns from feedback and improves the overall system performance. This process makes it possible to provide users with more highly personalized financial services. 【0145】 (Example 2) 【0146】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal". 【0147】 In modern life, receiving advice tailored to individual financial situations is a challenging task. Furthermore, existing technologies are insufficient to provide timely and appropriate advice while considering user emotions. Moreover, mechanisms for effectively utilizing user feedback to evolve the system are lacking. The objective of this invention is to address these issues and provide customized financial guidance to each individual user. 【0148】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0149】 In this invention, the server includes acquisition means for receiving the user's financial information, processing means for analyzing the acquired financial information and generating balanced financial guidance, and sentiment analysis means for evaluating the user's emotions and constructing messages based on psychological characteristics. This makes it possible to provide individually customized financial guidance in real time and to realize a service that takes the user's emotions into consideration. 【0150】 "Means of acquisition" refers to the interface and process for receiving financial information from the user. 【0151】 "Processing means" refers to the functions and processes for analyzing acquired financial information and generating individually tailored financial guidance. 【0152】 "Emotion analysis means" refers to the functions and processes for evaluating a user's emotions and generating messages based on those emotions. 【0153】 "Display means" refers to an interface and process for presenting users with real-time generated financial guidance and sentiment-based information. 【0154】 "Learning tools" refer to the functions and processes used to improve financial guidance and dynamically evolve the system using user feedback. 【0155】 "Voice processing means" refers to a function and process for receiving voice information, analyzing that information, and identifying user requests. 【0156】 The system according to this invention is started when a user enters financial information using a terminal. The terminal collects information such as the user's age, income, asset status, liabilities, and financial goals via a dedicated input interface. The collected information is transmitted to a server via a secure communication method such as SSL or TLS. 【0157】 The server uses a database management system and data analysis libraries to analyze the received financial information. Specifically, it uses a database management system with MySQL® and analysis libraries such as NumPy and Pandas to analyze the user's financial situation in detail. This generates financial guidance that is tailored to the user's goals. 【0158】 Furthermore, the sentiment analysis engine installed on the server evaluates the user's emotions through natural language processing libraries (e.g., spaCy, NLTK). Based on this, a generative AI model is used to generate financial guidance that takes the user's emotions into consideration, in the form of prompts. An example of a prompt is, "Generate advice tailored to the user's current financial situation and emotions." 【0159】 The generated financial guidance is transmitted to the terminal in real time, and the terminal communicates it to the user through a display. The terminal not only provides information visually but also provides voice guidance if voice output functionality is available. Users can provide feedback on the advice provided, and the terminal collects this feedback and sends it to the server. This information is used to further improve the system and enhance the user experience. 【0160】 This system provides users with personalized financial guidance through this series of processes, creating an environment where users can confidently proceed with their financial planning. 【0161】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0162】 Step 1: 【0163】 Users enter financial information using a terminal. This data includes age, income, asset status, liabilities, and financial goals. The terminal provides a form-based input interface to accurately collect this information. The entered data is temporarily stored within the terminal. 【0164】 Step 2: 【0165】 The terminal transmits the collected financial information to the server. At this time, the data is encrypted using a secure communication method (e.g., SSL / TLS) to prevent unauthorized access by third parties. The transmitted data is appropriately encoded to protect user privacy. 【0166】 Step 3: 【0167】 The server analyzes the received financial information. It uses a database management system (e.g., MySQL) and data analysis libraries (e.g., NumPy, Pandas) to examine the user's financial situation. After the analysis, it calculates specific financial guidance to help the user achieve their goals. The output results determine appropriate financial plans and actions. 【0168】 Step 4: 【0169】 The server uses an emotion analysis engine to evaluate the user's emotions. It extracts emotional characteristics from text data using natural language processing libraries (e.g., spaCy, NLTK). An example of a prompt is, "Generate advice tailored to my current financial situation and emotions." The analyzed emotion data is used to refine the advice. 【0170】 Step 5: 【0171】 Leveraging a generative AI model, the server generates financial guidance best suited to the user. Based on prompts, it constructs messages tailored to the individual user's emotions and financial situation. The generated advice is then prepared for real-time delivery. 【0172】 Step 6: 【0173】 The terminal receives financial guidance transmitted from the server. This guidance is presented visually on the screen, and if voice output functionality is available, voice guidance is also possible. Based on this information, the user can review and adjust their financial plan. 【0174】 Step 7: 【0175】 Users can provide feedback on the financial guidance and emotion-based messages provided. The device collects this feedback and sends it to the server. The submitted feedback is used to improve the system and further optimize the advice. 【0176】 (Application Example 2) 【0177】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal". 【0178】 In today's world, users are required to create complex financial plans and manage their spending based on those plans. However, traditional financial advisory systems often fail to consider the user's emotional state, making it difficult to provide personalized advice. As a result, users are prone to financial anxiety and struggle to manage their spending efficiently. Therefore, there is a need for a system that takes user emotions into account and provides personalized spending advice. 【0179】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0180】 In this invention, the server includes information input means, information analysis means, emotion analysis means, information output means, expenditure management means, and psychological consideration means. This makes it possible to provide specific expenditure advice based on the user's individual financial situation and emotional state. 【0181】 "Information input means" refers to devices or software that allow users to input financial information and spending history. 【0182】 "Information analysis means" refers to devices or software that have the function of processing input financial information and generating individually tailored financial advice. 【0183】 "Emotional analysis tools" refer to devices or software used to analyze a user's emotions and create messages based on those emotions. 【0184】 "Information output means" refers to devices or software that provide users with advice and emotionally charged messages. 【0185】 "Expense management tools" refer to devices or software that analyze a user's spending history and generate a plan tailored to their financial status. 【0186】 "Psychological consideration measures" refer to devices or software that provide spending advice that takes into account the user's emotional state. 【0187】 The system for realizing this invention consists of several main components. The server plays a central role in processing information received from the user's terminal. The user uses a terminal such as a smartphone to input their financial information and spending history via an information input device. The terminal sends this information to the server using a secure protocol (e.g., HTTPS). 【0188】 On the server, information analysis tools use Python and Django to analyze financial information and generate personalized advice for the user. Furthermore, a natural language processing model using TENSORFLOW® is employed as an emotion analysis tool to analyze the user's emotions from their input text and voice. The results of the emotion analysis are then used by psychological consideration tools to generate messages that take the user's psychological state into account, and these messages are provided to the user in real time through an information output tool. 【0189】 As a means of managing spending, the system analyzes the user's past spending history and develops savings plans and advice tailored to their financial situation. This allows users to manage their spending more effectively. 【0190】 As a concrete example, suppose a user is feeling anxious because their spending has increased at the end of the month. In this case, the emotion analysis tool recognizes this anxious feeling, and the psychological consideration tool generates a message that reassures the user. Furthermore, the spending management tool makes suggestions for future savings and provides them to the user through the information output tool. 【0191】 An example of a prompt might be: "The user is feeling anxious about increased spending this month. Take this into consideration and generate an encouraging message and specific savings suggestions." 【0192】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0193】 Step 1: 【0194】 Users input their financial information and spending history using their smartphones. The entered data is sent to the server in JSON format via the device's input method. 【0195】 Step 2: 【0196】 The server retrieves received financial information and spending history data and analyzes the data using data analysis tools. This process uses Python and Django to generate personalized advice based on each user's financial situation. The output of the analysis is personalized advice data optimized for each user. 【0197】 Step 3: 【0198】 The server uses a natural language processing model based on TensorFlow as a means of sentiment analysis to analyze user input text and audio data. This process acquires the user's emotional state as digital data, laying the foundation for taking the user's feelings into consideration. The output of the analysis is data indicating the user's emotional state. 【0199】 Step 4: 【0200】 The server combines the outputs of information analysis and emotion analysis methods, and uses psychological considerations to generate a message that takes the user's emotional state into account. This message is sent to the user's terminal in real time and serves to provide a sense of security. 【0201】 Step 5: 【0202】 The server uses expenditure management tools to analyze the user's past spending data and develop a future savings plan. This plan is aligned with the user's financial goals and is provided to the user through an information output tool. The savings plan output is displayed on the user's terminal as a concrete implementation plan. 【0203】 Step 6: 【0204】 Users can send feedback on the advice and messages provided. The feedback data received from the device is sent to the server and used to continuously improve the system's advice using learning mechanisms. This feedback output is reflected in subsequent advice generation. 【0205】 The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data. 【0206】 Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0207】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14. 【0208】 [Second Embodiment] 【0209】 Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment. 【0210】 As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server. 【0211】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0212】 The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52. 【0213】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0214】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0215】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0216】 Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0217】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0218】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0219】 In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0220】 Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0221】 The personal AI financial planner system according to the present invention aims to alleviate users' financial anxieties and provide individually personalized financial advice. This system inputs and analyzes the user's financial information and provides advice, including emotion-based messages, in real time. 【0222】 1. User Input Phase 【0223】 The terminal accepts financial information such as the user's age, income, asset status, debt information, and goals. This information is provided by the user and entered through the terminal interface. 【0224】 2. Data Analysis Phase 【0225】 The server receives data sent by users and securely stores it in a database. Next, it analyzes this data using analytical tools to assess the user's current financial situation and calculate the necessary approaches to achieve their goals. It then generates optimal advice for each user. 【0226】 3. Emotional Analysis Phase 【0227】 The server performs sentiment analysis based on user input. This analysis assesses the user's current psychological state. In particular, if the user is feeling anxious, the sentiment analysis tool generates a reassuring message based on the results. 【0228】 4. Advice Provision Phase 【0229】 Based on the results of analysis and sentiment analysis, the server creates user-optimized advice and appropriate emotional messages. This information is transmitted to the device in real time, and the device provides the advice to the user via screen or audio. 【0230】 As a concrete example, consider a case where a user is trying to create a savings plan for buying a house. This user aims to save 5 million yen in 5 years for the purchase of a house. The device receives the user's annual income, current savings status, and monthly expenses as input. 【0231】 The server analyzes this data, calculates the monthly savings requirement, and identifies areas where savings can be made. Furthermore, if the user is experiencing stress regarding this savings plan, it provides messages based on the emotional analysis results, including realistic spending plans and budget advice. 【0232】 Through this system, individual users can create specific and reliable financial plans tailored to their own needs. 【0233】 The following describes the processing flow. 【0234】 Step 1: 【0235】 The user enters financial information such as their age, income, assets, liabilities, and financial goals through the terminal's input interface. The terminal formats the entered data and sends it to the server using a secure protocol. 【0236】 Step 2: 【0237】 The server stores the user's financial information received from the terminal in a database. Next, it uses analytical tools to understand the user's current situation and performs basic calculations and analyses to achieve financial goals. 【0238】 Step 3: 【0239】 The server uses sentiment analysis tools to evaluate the user's psychological state based on user input and past interaction data. This allows it to understand the user's current emotional tendencies and generate reassuring messages when necessary. 【0240】 Step 4: 【0241】 The server generates personalized financial advice applicable to the user based on data analysis and sentiment analysis results. It also prepares sentiment-based responses. 【0242】 Step 5: 【0243】 The server sends the generated financial advice and emotional messages to the terminal. The terminal displays this through its user interface and provides audio output as needed. 【0244】 Step 6: 【0245】 The user enters feedback and additional questions about the advice provided via the terminal. The terminal then sends this feedback to the server. 【0246】 Step 7: 【0247】 The server analyzes the feedback and uses the AI ​​model to learn what is needed to improve future advice. This allows the system to continuously improve and better meet user needs. 【0248】 (Example 1) 【0249】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0250】 Managing financial information while quickly providing appropriate suggestions tailored to individual circumstances is difficult with conventional systems. Furthermore, the lack of information that considers user emotions makes it difficult for users to make financial decisions with confidence. 【0251】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0252】 In this invention, the server includes an input means for inputting information about the user's finances, an analysis means for analyzing the input financial information and proposing individually tailored finances, and an emotion evaluation means for evaluating the user's psychological state and generating information based on that state. This makes it possible to provide users with individually customized financial proposals and reassuring information in real time. 【0253】 An "input method" is an interface that allows users to provide financial information to the system. 【0254】 "Analysis means" refers to the process of analyzing the input financial information and proposing the optimal financial plan to the user. 【0255】 An "emotional evaluation method" is a process for evaluating a user's psychological state and generating information based on that state. 【0256】 The "output means" is an interface for communicating the results of the analysis and sentiment evaluation to the user. 【0257】 "Voice processing functionality" refers to a function that analyzes voice information to understand user requests. 【0258】 The "learning function" is a feature that analyzes user feedback and continuously improves the content of suggestions based on that feedback. 【0259】 This invention relates to a personal AI financial planner system that alleviates users' financial anxieties and provides individually personalized financial advice. The system works by inputting information about the user's finances, analyzing it, evaluating their emotions, and then providing information based on the results. 【0260】 The device receives financial information from the user. This information includes age, income, assets, liabilities, and goals. The device interface is implemented through web forms or dedicated applications. 【0261】 The server receives this information and securely stores it in a database. Analysis is performed using data analysis libraries in Python and an SQL database. This evaluates the user's financial situation and calculates the optimal approach to achieving the goals to be accomplished. 【0262】 Furthermore, the server uses emotion evaluation tools and natural language processing techniques to analyze the user's psychological state. Based on this analysis, it generates emotionally supportive messages tailored to the user. 【0263】 As a concrete example, consider a user who wants to create a savings plan for buying a house. The user inputs their annual income, current savings status, and monthly expenses into a terminal. The server analyzes this information and provides a calculation of the required monthly savings amount and tips for reducing expenses. Furthermore, if the user is feeling stressed, a message is generated that provides reassurance based on the results of the emotion analysis. 【0264】 As an example of a prompt, the following sentence is input into the AI ​​generation model: "The user aims to save 5 million yen in 5 years. Please provide monthly savings amounts and specific advice on how to save to achieve this goal. Also, please include emotional support to reduce the user's stress level." This prompt allows the system to provide information optimized for the user. 【0265】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0266】 Step 1: 【0267】 Users input information such as age, income, asset status, debt information, and financial goals through their device. The input information is formatted in JSON or XML format and sent to the server. The input in this step is information about the user's finances, and the output is formatted data for storage in the database. 【0268】 Step 2: 【0269】 The server receives user information sent from the terminal and stores it in the database in a secure manner. The database has an SQL structure, with each field corresponding to user information. The input for this step is formatted data sent from the terminal, and the output is the storage operation into the database. 【0270】 Step 3: 【0271】 The server retrieves stored data using SQL queries and performs analysis using a Python data analysis library. The analysis evaluates the balance of income and expenses, savings and debt levels, and calculates the optimal plan for the user to achieve their goals. The input for this step is user information retrieved from the database, and the output is the calculated financial proposal. 【0272】 Step 4: 【0273】 The server uses natural language processing (NLP) techniques to analyze user input and perform sentiment analysis. Specifically, it estimates the user's psychological state from their text and generates messages to alleviate anxiety if present. The input for this step is the user's input, and the output is the generated message based on the sentiment analysis. 【0274】 Step 5: 【0275】 The server integrates analyzed financial recommendations and sentiment analysis-based messages to construct final advice. It selects the most relevant information and prepares to provide immediate feedback to the user. The input for this step is the results of the financial and sentiment analysis, and the output is the final advice and message provided to the user. 【0276】 Step 6: 【0277】 The terminal receives advice and messages sent from the server and presents them to the user via display or audio output. This presentation is in a format that is easy for the user to understand. Specifically, it provides text or audio feedback to help the user act on the suggestions. The input for this step is the final advice and messages from the server, and the output is what is presented to the user. 【0278】 (Application Example 1) 【0279】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal." 【0280】 In modern society, individual consumers face increasing financial anxieties and challenges in managing complex spending. The widespread adoption of electronic payments, in particular, has made it difficult for consumers to track their spending in real time and stick to their budgets. In this context, there is a need for support tools that enable consumers to live their daily lives with peace of mind and to create financial plans that align with their goals. 【0281】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0282】 In this invention, the server includes a device for inputting the user's financial information, a processing device for analyzing the input financial information and generating individually adapted financial advice, an emotion analysis device for analyzing the user's emotions and creating messages based on their psychological state, an output device for providing advice and emotion-based messages to the user in real time, and a notification device for analyzing electronic payment data to evaluate spending patterns and support budget-friendly behavior. This enables consumers to manage their financial situation in real time while also gaining peace of mind. 【0283】 A "device for inputting user financial information" is a device equipped with an interface for collecting information provided by the user, such as age, income, asset status, debt information, and goals. 【0284】 The "processing device that analyzes financial information and generates personalized financial advice" is an arithmetic device that calculates and generates optimal financial advice for each user in real time based on the collected financial information. 【0285】 The "emotion analysis device that analyzes emotions and creates messages based on the psychological state" is a mechanism that evaluates the psychological state based on the user's input information and behavioral data, and creates messages according to the evaluation results. 【0286】 The "output device that provides users with real-time advice and emotion-based messages" is a device that instantly transmits the financial advice generated by the processing device and the messages created by the emotion analysis device to the user. 【0287】 The "notification device that analyzes electronic payment data, evaluates spending patterns, and supports in-budget behavior" is a device that has the function of analyzing the data related to the user's electronic payments, evaluating the spending trends, and sending notifications to the user to maintain in-budget spending. 【0288】 To implement this invention, the user's device needs to act as a financial information input device and input financial information such as age, income, asset status, debt information, and goals from the user. This information is transmitted to the server through a secure connection. 【0289】 The server, as a processing device, analyzes the received financial information. Using a series of analysis means, it evaluates the user's current financial situation and generates optimized financial advice for each user. Specific algorithms and trend analysis of past spending data are used in the analysis. This technology often uses programming languages such as Python and R and data analysis libraries. 【0290】 Furthermore, the server functions as an emotion analyzer, performing sentiment analysis based on user-provided text and other interaction data. This analysis evaluates the user's state of anxiety and reassurance, and based on this evaluation, creates emotion-based messages. Natural language processing technology can be used for sentiment analysis, and cloud services such as Google's Natural Language API or IBM's Watson may be used. 【0291】 To provide users with information in real time, the server sends generated financial advice and sentiment messages to the user's device. The user's device displays the message instantly using its notification function. The notification device receives information from the server and provides notifications to help users stay within their budget. For example, if a user is likely to exceed the budget they set at the beginning of the month, the app will display a real-time notification such as, "Your food expenses for this month have reached 80% of your budget." This notification may also refer to past spending trends to indicate areas where savings are possible. 【0292】 Furthermore, it utilizes a generative AI model to generate messages based on the user's thoughts and feelings. This process is achieved by prompting the AI ​​model, for example, by instructing it in the form of "Generate reassuring advice based on the user's current spending." 【0293】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0294】 Step 1: 【0295】 The user enters their financial information into the terminal. The terminal receives information such as age, income, assets, liabilities, and goals, and sends it to the server. This information becomes the input and forms the basis for the next analysis. 【0296】 Step 2: 【0297】 The server analyzes the received financial information. The processing unit calculates the user's income and expenses and evaluates the progress of asset building. An algorithm is used for this, and the specific output generated includes monthly savings requirements and investment plan suggestions. 【0298】 Step 3: 【0299】 The server uses a generative AI model to analyze the user's emotions. It analyzes the words and behavioral history entered by the user using an emotion analysis device to determine their psychological state, such as anxiety or reassurance. Emotional information is used as input, and messages that provide a sense of security are output. 【0300】 Step 4: 【0301】 The server integrates financial advice and sentiment-based messages to generate optimal advice. The processing unit combines the analysis results and sentiment analysis output to formulate the most suitable recommendations for the user. The output includes customized recommendations and reassuring information. 【0302】 Step 5: 【0303】 The server sends the generated advice to the user's terminal in real time. The output device immediately displays a notification on the user's screen, and voice guidance is also available. This allows the user to receive information on their financial situation and psychological support at all times. 【0304】 Step 6: 【0305】 The server analyzes the user's electronic payment data and evaluates spending patterns. It then notifies the user via a notification device of any anomalies or concerns about budget overruns discovered through this analysis. The input is the electronic payment history, and the output includes specific alerts for spending control. 【0306】 Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions. 【0307】 The system according to the present invention aims to reduce individual financial anxiety by providing personalized financial advice using the user's financial information. This system can recognize the user's emotions by combining an emotion engine in particular and reflect them in the content of the advice. 【0308】 First, the user inputs their financial information through the input interface of the terminal. This information includes age, income, asset status, liabilities, financial goals, and the like. The terminal collects these data and transmits them to the server using secure communication means. 【0309】 The server analyzes the received data by an analysis means and evaluates the user's financial situation. Thereby, specific financial advice corresponding to the user's goals is generated. 【0310】 One of the features of the system is that it is equipped with an emotion engine. This emotion engine analyzes the user's emotions from the user's input and conversation history. The analyzed emotion data is used to adjust the content of the advice. For example, when the user is feeling stressed, the emotion engine generates a reassuring message and reflects it in the advice. 【0311】 The generated advice and emotion-based messages are transmitted to the terminal in real time. The terminal displays this information on the screen and provides it in voice if necessary. The user can give feedback on the content of the advice, and this feedback is transmitted from the terminal to the server and utilized for further system improvement. 【0312】 As a concrete example, consider a scenario where a user has set a savings goal for retirement and wants advice on how to create that plan. In this case, the user enters the necessary information into a terminal. The server analyzes this information and uses an emotion engine to prepare a message that alleviates the user's anxiety. After that, it provides the user with specific advice regarding their savings plan. 【0313】 Thus, the present invention provides personalized financial support that takes user emotions into consideration, creating an environment in which users can confidently engage in financial planning. 【0314】 The following describes the processing flow. 【0315】 Step 1: 【0316】 Users access a dedicated application on their device and enter their personal financial information. This information includes age, income, current assets, debt, and specific financial goals, which the device then organizes as digital data. 【0317】 Step 2: 【0318】 The terminal sends organized user data to the server using a secure protocol. This communication is encrypted to ensure data confidentiality. 【0319】 Step 3: 【0320】 The server first stores the received user data in a database. Next, it uses analytical tools to analyze the user's wealth management situation in detail and consider specific strategies for achieving goals. 【0321】 Step 4: 【0322】 The server activates the emotion engine, analyzes the user's input data and past interactions, and assesses their current emotional state. If it detects that the user is, for example, stressed, it tailors the message to address that. 【0323】 Step 5: 【0324】 The server integrates the analysis results and sentiment analysis results to generate user-optimized financial advice and emotionally sensitive messages. 【0325】 Step 6: 【0326】 The generated advice and messages are sent to the terminal in real time. The terminal displays them through its user interface and also provides audio output if necessary. 【0327】 Step 7: 【0328】 Users can enter feedback on the advice provided into their device. This feedback is sent to the server and used to improve the accuracy of future advice generation. 【0329】 Step 8: 【0330】 The server learns from feedback and improves the overall system performance. This process makes it possible to provide users with more highly personalized financial services. 【0331】 (Example 2) 【0332】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal". 【0333】 In modern life, receiving advice tailored to individual financial situations is a challenging task. Furthermore, existing technologies are insufficient to provide timely and appropriate advice while considering user emotions. Moreover, mechanisms for effectively utilizing user feedback to evolve the system are lacking. The objective of this invention is to address these issues and provide customized financial guidance to each individual user. 【0334】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0335】 In this invention, the server includes acquisition means for receiving the user's financial information, processing means for analyzing the acquired financial information and generating balanced financial guidance, and sentiment analysis means for evaluating the user's emotions and constructing messages based on psychological characteristics. This makes it possible to provide individually customized financial guidance in real time and to realize a service that takes the user's emotions into consideration. 【0336】 "Means of acquisition" refers to the interface and process for receiving financial information from the user. 【0337】 "Processing means" refers to the functions and processes for analyzing acquired financial information and generating individually tailored financial guidance. 【0338】 "Emotion analysis means" refers to the functions and processes for evaluating a user's emotions and generating messages based on those emotions. 【0339】 "Display means" refers to an interface and process for presenting users with real-time generated financial guidance and sentiment-based information. 【0340】 "Learning tools" refer to the functions and processes used to improve financial guidance and dynamically evolve the system using user feedback. 【0341】 "Voice processing means" refers to a function and process for receiving voice information, analyzing that information, and identifying user requests. 【0342】 The system according to this invention is started when a user enters financial information using a terminal. The terminal collects information such as the user's age, income, asset status, liabilities, and financial goals via a dedicated input interface. The collected information is transmitted to a server via a secure communication method such as SSL or TLS. 【0343】 The server uses a database management system and data analysis libraries to analyze the received financial information. Specifically, it uses a MySQL database for management and analysis libraries such as NumPy and Pandas to analyze the user's financial situation in detail. This generates financial guidance that is tailored to the user's goals. 【0344】 Furthermore, the sentiment analysis engine installed on the server evaluates the user's emotions through natural language processing libraries (e.g., spaCy, NLTK). Based on this, a generative AI model is used to generate financial guidance that takes the user's emotions into consideration, in the form of prompts. An example of a prompt is, "Generate advice tailored to the user's current financial situation and emotions." 【0345】 The generated financial guidance is transmitted to the terminal in real time, and the terminal communicates it to the user through a display. The terminal not only provides information visually but also provides voice guidance if voice output functionality is available. Users can provide feedback on the advice provided, and the terminal collects this feedback and sends it to the server. This information is used to further improve the system and enhance the user experience. 【0346】 This system provides users with personalized financial guidance through this series of processes, creating an environment where users can confidently proceed with their financial planning. 【0347】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0348】 Step 1: 【0349】 Users enter financial information using a terminal. This data includes age, income, asset status, liabilities, and financial goals. The terminal provides a form-based input interface to accurately collect this information. The entered data is temporarily stored within the terminal. 【0350】 Step 2: 【0351】 The terminal transmits the collected financial information to the server. At this time, the data is encrypted using a secure communication method (e.g., SSL / TLS) to prevent unauthorized access by third parties. The transmitted data is appropriately encoded to protect user privacy. 【0352】 Step 3: 【0353】 The server analyzes the received financial information. It uses a database management system (e.g., MySQL) and data analysis libraries (e.g., NumPy, Pandas) to examine the user's financial situation. After the analysis, it calculates specific financial guidance to help the user achieve their goals. The output results determine appropriate financial plans and actions. 【0354】 Step 4: 【0355】 The server uses an emotion analysis engine to evaluate the user's emotions. It extracts emotional characteristics from text data using natural language processing libraries (e.g., spaCy, NLTK). An example of a prompt is, "Generate advice tailored to my current financial situation and emotions." The analyzed emotion data is used to refine the advice. 【0356】 Step 5: 【0357】 Leveraging a generative AI model, the server generates financial guidance best suited to the user. Based on prompts, it constructs messages tailored to the individual user's emotions and financial situation. The generated advice is then prepared for real-time delivery. 【0358】 Step 6: 【0359】 The terminal receives financial guidance transmitted from the server. This guidance is presented visually on the screen, and if voice output functionality is available, voice guidance is also possible. Based on this information, the user can review and adjust their financial plan. 【0360】 Step 7: 【0361】 Users can provide feedback on the financial guidance and emotion-based messages provided. The device collects this feedback and sends it to the server. The submitted feedback is used to improve the system and further optimize the advice. 【0362】 (Application Example 2) 【0363】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal". 【0364】 In today's world, users are required to create complex financial plans and manage their spending based on those plans. However, traditional financial advisory systems often fail to consider the user's emotional state, making it difficult to provide personalized advice. As a result, users are prone to financial anxiety and struggle to manage their spending efficiently. Therefore, there is a need for a system that takes user emotions into account and provides personalized spending advice. 【0365】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0366】 In this invention, the server includes information input means, information analysis means, emotion analysis means, information output means, expenditure management means, and psychological consideration means. This makes it possible to provide specific expenditure advice based on the user's individual financial situation and emotional state. 【0367】 "Information input means" refers to devices or software that allow users to input financial information and spending history. 【0368】 "Information analysis means" refers to devices or software that have the function of processing input financial information and generating individually tailored financial advice. 【0369】 "Emotional analysis tools" refer to devices or software used to analyze a user's emotions and create messages based on those emotions. 【0370】 "Information output means" refers to devices or software that provide users with advice and emotionally charged messages. 【0371】 "Expense management tools" refer to devices or software that analyze a user's spending history and generate a plan tailored to their financial status. 【0372】 "Psychological consideration measures" refer to devices or software that provide spending advice that takes into account the user's emotional state. 【0373】 The system for realizing this invention consists of several main components. The server plays a central role in processing information received from the user's terminal. The user uses a terminal such as a smartphone to input their financial information and spending history via an information input device. The terminal sends this information to the server using a secure protocol (e.g., HTTPS). 【0374】 On the server, information analysis tools use Python and Django to analyze financial information and generate advice tailored to the user. Furthermore, a natural language processing model using TensorFlow is employed as an emotion analysis tool to analyze the user's emotions from their input text and voice. The results of the emotion analysis are then used by psychological consideration tools to generate messages that take the user's psychological state into account, and these messages are provided to the user in real time through an information output tool. 【0375】 As a means of managing spending, the system analyzes the user's past spending history and develops savings plans and advice tailored to their financial situation. This allows users to manage their spending more effectively. 【0376】 As a concrete example, suppose a user is feeling anxious because their spending has increased at the end of the month. In this case, the emotion analysis tool recognizes this anxious feeling, and the psychological consideration tool generates a message that reassures the user. Furthermore, the spending management tool makes suggestions for future savings and provides them to the user through the information output tool. 【0377】 An example of a prompt might be: "The user is feeling anxious about increased spending this month. Take this into consideration and generate an encouraging message and specific savings suggestions." 【0378】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0379】 Step 1: 【0380】 Users input their financial information and spending history using their smartphones. The entered data is sent to the server in JSON format via the device's input method. 【0381】 Step 2: 【0382】 The server retrieves received financial information and spending history data and analyzes the data using data analysis tools. This process uses Python and Django to generate personalized advice based on each user's financial situation. The output of the analysis is personalized advice data optimized for each user. 【0383】 Step 3: 【0384】 The server uses a natural language processing model based on TensorFlow as a means of sentiment analysis to analyze user input text and audio data. This process acquires the user's emotional state as digital data, laying the foundation for taking the user's feelings into consideration. The output of the analysis is data indicating the user's emotional state. 【0385】 Step 4: 【0386】 The server combines the outputs of information analysis and emotion analysis methods, and uses psychological considerations to generate a message that takes the user's emotional state into account. This message is sent to the user's terminal in real time and serves to provide a sense of security. 【0387】 Step 5: 【0388】 The server uses expenditure management tools to analyze the user's past spending data and develop a future savings plan. This plan is aligned with the user's financial goals and is provided to the user through an information output tool. The savings plan output is displayed on the user's terminal as a concrete implementation plan. 【0389】 Step 6: 【0390】 Users can send feedback on the advice and messages provided. The feedback data received from the device is sent to the server and used to continuously improve the system's advice using learning mechanisms. This feedback output is reflected in subsequent advice generation. 【0391】 The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0392】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0393】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214. 【0394】 [Third Embodiment] 【0395】 Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment. 【0396】 As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server. 【0397】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0398】 The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52. 【0399】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0400】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0401】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0402】 Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0403】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0404】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0405】 In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0406】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal". 【0407】 The personal AI financial planner system according to the present invention aims to alleviate users' financial anxieties and provide individually personalized financial advice. This system inputs and analyzes the user's financial information and provides advice, including emotion-based messages, in real time. 【0408】 1. User Input Phase 【0409】 The terminal accepts financial information such as the user's age, income, asset status, debt information, and goals. This information is provided by the user and entered through the terminal interface. 【0410】 2. Data Analysis Phase 【0411】 The server receives data sent by users and securely stores it in a database. Next, it analyzes this data using analytical tools to assess the user's current financial situation and calculate the necessary approaches to achieve their goals. It then generates optimal advice for each user. 【0412】 3. Emotional Analysis Phase 【0413】 The server performs sentiment analysis based on user input. This analysis assesses the user's current psychological state. In particular, if the user is feeling anxious, the sentiment analysis tool generates a reassuring message based on the results. 【0414】 4. Advice Provision Phase 【0415】 Based on the results of analysis and sentiment analysis, the server creates user-optimized advice and appropriate emotional messages. This information is transmitted to the device in real time, and the device provides the advice to the user via screen or audio. 【0416】 As a concrete example, consider a case where a user is trying to create a savings plan for buying a house. This user aims to save 5 million yen in 5 years for the purchase of a house. The device receives the user's annual income, current savings status, and monthly expenses as input. 【0417】 The server analyzes this data, calculates the monthly savings requirement, and identifies areas where savings can be made. Furthermore, if the user is experiencing stress regarding this savings plan, it provides messages based on the emotional analysis results, including realistic spending plans and budget advice. 【0418】 Through this system, individual users can create specific and reliable financial plans tailored to their own needs. 【0419】 The following describes the processing flow. 【0420】 Step 1: 【0421】 The user enters financial information such as their age, income, assets, liabilities, and financial goals through the terminal's input interface. The terminal formats the entered data and sends it to the server using a secure protocol. 【0422】 Step 2: 【0423】 The server stores the user's financial information received from the terminal in a database. Next, it uses analytical tools to understand the user's current situation and performs basic calculations and analyses to achieve financial goals. 【0424】 Step 3: 【0425】 The server uses sentiment analysis tools to evaluate the user's psychological state based on user input and past interaction data. This allows it to understand the user's current emotional tendencies and generate reassuring messages when necessary. 【0426】 Step 4: 【0427】 The server generates personalized financial advice applicable to the user based on data analysis and sentiment analysis results. It also prepares sentiment-based responses. 【0428】 Step 5: 【0429】 The server sends the generated financial advice and emotional messages to the terminal. The terminal displays this through its user interface and provides audio output as needed. 【0430】 Step 6: 【0431】 The user enters feedback and additional questions about the advice provided via the terminal. The terminal then sends this feedback to the server. 【0432】 Step 7: 【0433】 The server analyzes the feedback and uses the AI ​​model to learn what is needed to improve future advice. This allows the system to continuously improve and better meet user needs. 【0434】 (Example 1) 【0435】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0436】 Managing financial information while quickly providing appropriate suggestions tailored to individual circumstances is difficult with conventional systems. Furthermore, the lack of information that considers user emotions makes it difficult for users to make financial decisions with confidence. 【0437】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0438】 In this invention, the server includes an input means for inputting information about the user's finances, an analysis means for analyzing the input financial information and proposing individually tailored finances, and an emotion evaluation means for evaluating the user's psychological state and generating information based on that state. This makes it possible to provide users with individually customized financial proposals and reassuring information in real time. 【0439】 An "input method" is an interface that allows users to provide financial information to the system. 【0440】 "Analysis means" refers to the process of analyzing the input financial information and proposing the optimal financial plan to the user. 【0441】 An "emotional evaluation method" is a process for evaluating a user's psychological state and generating information based on that state. 【0442】 The "output means" is an interface for communicating the results of the analysis and sentiment evaluation to the user. 【0443】 "Voice processing functionality" refers to a function that analyzes voice information to understand user requests. 【0444】 The "learning function" is a feature that analyzes user feedback and continuously improves the content of suggestions based on that feedback. 【0445】 This invention relates to a personal AI financial planner system that alleviates users' financial anxieties and provides individually personalized financial advice. The system works by inputting information about the user's finances, analyzing it, evaluating their emotions, and then providing information based on the results. 【0446】 The device receives financial information from the user. This information includes age, income, assets, liabilities, and goals. The device interface is implemented through web forms or dedicated applications. 【0447】 The server receives this information and securely stores it in a database. Analysis is performed using data analysis libraries in Python and an SQL database. This evaluates the user's financial situation and calculates the optimal approach to achieving the goals to be accomplished. 【0448】 Furthermore, the server uses emotion evaluation tools and natural language processing techniques to analyze the user's psychological state. Based on this analysis, it generates emotionally supportive messages tailored to the user. 【0449】 As a concrete example, consider a user who wants to create a savings plan for buying a house. The user inputs their annual income, current savings status, and monthly expenses into a terminal. The server analyzes this information and provides a calculation of the required monthly savings amount and tips for reducing expenses. Furthermore, if the user is feeling stressed, a message is generated that provides reassurance based on the results of the emotion analysis. 【0450】 As an example of a prompt, the following sentence is input into the AI ​​generation model: "The user aims to save 5 million yen in 5 years. Please provide monthly savings amounts and specific advice on how to save to achieve this goal. Also, please include emotional support to reduce the user's stress level." This prompt allows the system to provide information optimized for the user. 【0451】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0452】 Step 1: 【0453】 Users input information such as age, income, asset status, debt information, and financial goals through their device. The input information is formatted in JSON or XML format and sent to the server. The input in this step is information about the user's finances, and the output is formatted data for storage in the database. 【0454】 Step 2: 【0455】 The server receives user information sent from the terminal and stores it in the database in a secure manner. The database has an SQL structure, with each field corresponding to user information. The input for this step is formatted data sent from the terminal, and the output is the storage operation into the database. 【0456】 Step 3: 【0457】 The server retrieves stored data using SQL queries and performs analysis using a Python data analysis library. The analysis evaluates the balance of income and expenses, savings and debt levels, and calculates the optimal plan for the user to achieve their goals. The input for this step is user information retrieved from the database, and the output is the calculated financial proposal. 【0458】 Step 4: 【0459】 The server uses natural language processing (NLP) techniques to analyze user input and perform sentiment analysis. Specifically, it estimates the user's psychological state from their text and generates messages to alleviate anxiety if present. The input for this step is the user's input, and the output is the generated message based on the sentiment analysis. 【0460】 Step 5: 【0461】 The server integrates analyzed financial recommendations and sentiment analysis-based messages to construct final advice. It selects the most relevant information and prepares to provide immediate feedback to the user. The input for this step is the results of the financial and sentiment analysis, and the output is the final advice and message provided to the user. 【0462】 Step 6: 【0463】 The terminal receives advice and messages sent from the server and presents them to the user via display or audio output. This presentation is in a format that is easy for the user to understand. Specifically, it provides text or audio feedback to help the user act on the suggestions. The input for this step is the final advice and messages from the server, and the output is what is presented to the user. 【0464】 (Application Example 1) 【0465】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0466】 In modern society, individual consumers face increasing financial anxieties and challenges in managing complex spending. The widespread adoption of electronic payments, in particular, has made it difficult for consumers to track their spending in real time and stick to their budgets. In this context, there is a need for support tools that enable consumers to live their daily lives with peace of mind and to create financial plans that align with their goals. 【0467】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0468】 In this invention, the server includes a device for inputting the user's financial information, a processing device for analyzing the input financial information and generating individually adapted financial advice, an emotion analysis device for analyzing the user's emotions and creating messages based on their psychological state, an output device for providing advice and emotion-based messages to the user in real time, and a notification device for analyzing electronic payment data to evaluate spending patterns and support budget-friendly behavior. This enables consumers to manage their financial situation in real time while also gaining peace of mind. 【0469】 A "device for inputting user financial information" is a device equipped with an interface for collecting information provided by the user, such as age, income, asset status, debt information, and goals. 【0470】 A "processing device that analyzes financial information and generates individually tailored financial advice" is a computing device that calculates and generates the most suitable financial advice for each user based on collected financial information, in real time. 【0471】 A "sentiment analysis device that analyzes emotions and creates messages based on psychological state" is a mechanism that evaluates a user's psychological state based on their input information and behavioral data, and creates a message corresponding to the evaluation results. 【0472】 An "output device that provides users with real-time advice and sentiment-based messages" is a device that instantly transmits financial advice generated by a processing unit and messages created by a sentiment analysis device to the user. 【0473】 A "notification device that analyzes electronic payment data to evaluate spending patterns and support budget-conscious behavior" is a device that analyzes data related to a user's electronic payments, evaluates spending trends, and has the function of notifying the user to maintain spending within their budget. 【0474】 To implement this invention, the user's device must act as a financial information input device, requiring the user to input financial information such as age, income, asset status, debt information, and goals. This information is transmitted to the server via a secure connection. 【0475】 The server acts as a processing unit, analyzing the received financial information. Using a series of analytical methods, it assesses the user's current financial situation and generates personalized financial advice. The analysis utilizes specific algorithms and trend analysis of historical spending data. This technology often employs programming languages ​​such as Python and R, along with data analysis libraries. 【0476】 Furthermore, the server functions as an emotion analyzer, performing sentiment analysis based on user-provided text and other interaction data. This analysis evaluates the user's state of anxiety and reassurance, and based on this evaluation, creates emotion-based messages. Natural language processing technology can be used for sentiment analysis, and cloud services such as Google's Natural Language API or IBM's Watson may be used. 【0477】 To provide users with information in real time, the server sends generated financial advice and sentiment messages to the user's device. The user's device displays the message instantly using its notification function. The notification device receives information from the server and provides notifications to help users stay within their budget. For example, if a user is likely to exceed the budget they set at the beginning of the month, the app will display a real-time notification such as, "Your food expenses for this month have reached 80% of your budget." This notification may also refer to past spending trends to indicate areas where savings are possible. 【0478】 Furthermore, it utilizes a generative AI model to generate messages based on the user's thoughts and feelings. This process is achieved by prompting the AI ​​model, for example, by instructing it in the form of "Generate reassuring advice based on the user's current spending." 【0479】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0480】 Step 1: 【0481】 The user enters their financial information into the terminal. The terminal receives information such as age, income, assets, liabilities, and goals, and sends it to the server. This information becomes the input and forms the basis for the next analysis. 【0482】 Step 2: 【0483】 The server analyzes the received financial information. The processing unit calculates the user's income and expenses and evaluates the progress of asset building. An algorithm is used for this, and the specific output generated includes monthly savings requirements and investment plan suggestions. 【0484】 Step 3: 【0485】 The server uses a generative AI model to analyze the user's emotions. It analyzes the words and behavioral history entered by the user using an emotion analysis device to determine their psychological state, such as anxiety or reassurance. Emotional information is used as input, and messages that provide a sense of security are output. 【0486】 Step 4: 【0487】 The server integrates financial advice and sentiment-based messages to generate optimal advice. The processing unit combines the analysis results and sentiment analysis output to formulate the most suitable recommendations for the user. The output includes customized recommendations and reassuring information. 【0488】 Step 5: 【0489】 The server sends the generated advice to the user's terminal in real time. The output device immediately displays a notification on the user's screen, and voice guidance is also available. This allows the user to receive information on their financial situation and psychological support at all times. 【0490】 Step 6: 【0491】 The server analyzes the user's electronic payment data and evaluates spending patterns. It then notifies the user via a notification device of any anomalies or concerns about budget overruns discovered through this analysis. The input is the electronic payment history, and the output includes specific alerts for spending control. 【0492】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0493】 The system according to the present invention aims to alleviate individual financial anxieties by providing personalized financial advice using the user's financial information. In particular, by combining this system with an emotion engine, the system can recognize the user's emotions and reflect them in the content of the advice. 【0494】 First, the user enters their financial information through the terminal's input interface. This information includes age, income, asset status, liabilities, and financial goals. The terminal collects this data and transmits it to the server using a secure communication method. 【0495】 The server analyzes the received data using analytical tools to evaluate the user's financial situation. Based on this, it generates specific financial advice tailored to the user's goals. 【0496】 One of the system's key features is its built-in emotion engine. This engine analyzes the user's emotions based on their input and conversation history. The analyzed emotion data is then used to tailor the advice it provides. For example, if a user is feeling stressed, the emotion engine will generate reassuring messages and reflect this in the advice. 【0497】 The generated advice and emotion-based messages are sent to the device in real time. The device displays this information on the screen and, if necessary, also provides it via audio. Users can provide feedback on the advice, which is sent from the device to the server and used to further improve the system. 【0498】 As a concrete example, consider a scenario where a user has set a savings goal for retirement and wants advice on how to create that plan. In this case, the user enters the necessary information into a terminal. The server analyzes this information and uses an emotion engine to prepare a message that alleviates the user's anxiety. After that, it provides the user with specific advice regarding their savings plan. 【0499】 Thus, the present invention provides personalized financial support that takes user emotions into consideration, creating an environment in which users can confidently engage in financial planning. 【0500】 The following describes the processing flow. 【0501】 Step 1: 【0502】 Users access a dedicated application on their device and enter their personal financial information. This information includes age, income, current assets, debt, and specific financial goals, which the device then organizes as digital data. 【0503】 Step 2: 【0504】 The terminal sends organized user data to the server using a secure protocol. This communication is encrypted to ensure data confidentiality. 【0505】 Step 3: 【0506】 The server first stores the received user data in a database. Next, it uses analytical tools to analyze the user's wealth management situation in detail and consider specific strategies for achieving goals. 【0507】 Step 4: 【0508】 The server activates the emotion engine, analyzes the user's input data and past interactions, and assesses their current emotional state. If it detects that the user is, for example, stressed, it tailors the message to address that. 【0509】 Step 5: 【0510】 The server integrates the analysis results and sentiment analysis results to generate user-optimized financial advice and emotionally sensitive messages. 【0511】 Step 6: 【0512】 The generated advice and messages are sent to the terminal in real time. The terminal displays them through its user interface and also provides audio output if necessary. 【0513】 Step 7: 【0514】 Users can enter feedback on the advice provided into their device. This feedback is sent to the server and used to improve the accuracy of future advice generation. 【0515】 Step 8: 【0516】 The server learns from feedback and improves the overall system performance. This process makes it possible to provide users with more highly personalized financial services. 【0517】 (Example 2) 【0518】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0519】 In modern life, receiving advice tailored to individual financial situations is a challenging task. Furthermore, existing technologies are insufficient to provide timely and appropriate advice while considering user emotions. Moreover, mechanisms for effectively utilizing user feedback to evolve the system are lacking. The objective of this invention is to address these issues and provide customized financial guidance to each individual user. 【0520】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0521】 In this invention, the server includes acquisition means for receiving the user's financial information, processing means for analyzing the acquired financial information and generating balanced financial guidance, and sentiment analysis means for evaluating the user's emotions and constructing messages based on psychological characteristics. This makes it possible to provide individually customized financial guidance in real time and to realize a service that takes the user's emotions into consideration. 【0522】 "Means of acquisition" refers to the interface and process for receiving financial information from the user. 【0523】 "Processing means" refers to the functions and processes for analyzing acquired financial information and generating individually tailored financial guidance. 【0524】 "Emotion analysis means" refers to the functions and processes for evaluating a user's emotions and generating messages based on those emotions. 【0525】 "Display means" refers to an interface and process for presenting users with real-time generated financial guidance and sentiment-based information. 【0526】 "Learning tools" refer to the functions and processes used to improve financial guidance and dynamically evolve the system using user feedback. 【0527】 "Voice processing means" refers to a function and process for receiving voice information, analyzing that information, and identifying user requests. 【0528】 The system according to this invention is started when a user enters financial information using a terminal. The terminal collects information such as the user's age, income, asset status, liabilities, and financial goals via a dedicated input interface. The collected information is transmitted to a server via a secure communication method such as SSL or TLS. 【0529】 The server uses a database management system and data analysis libraries to analyze the received financial information. Specifically, it uses a MySQL database for management and analysis libraries such as NumPy and Pandas to analyze the user's financial situation in detail. This generates financial guidance that is tailored to the user's goals. 【0530】 Furthermore, the sentiment analysis engine installed on the server evaluates the user's emotions through natural language processing libraries (e.g., spaCy, NLTK). Based on this, a generative AI model is used to generate financial guidance that takes the user's emotions into consideration, in the form of prompts. An example of a prompt is, "Generate advice tailored to the user's current financial situation and emotions." 【0531】 The generated financial guidance is transmitted to the terminal in real time, and the terminal communicates it to the user through a display. The terminal not only provides information visually but also provides voice guidance if voice output functionality is available. Users can provide feedback on the advice provided, and the terminal collects this feedback and sends it to the server. This information is used to further improve the system and enhance the user experience. 【0532】 This system provides users with personalized financial guidance through this series of processes, creating an environment where users can confidently proceed with their financial planning. 【0533】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0534】 Step 1: 【0535】 Users enter financial information using a terminal. This data includes age, income, asset status, liabilities, and financial goals. The terminal provides a form-based input interface to accurately collect this information. The entered data is temporarily stored within the terminal. 【0536】 Step 2: 【0537】 The terminal transmits the collected financial information to the server. At this time, the data is encrypted using a secure communication method (e.g., SSL / TLS) to prevent unauthorized access by third parties. The transmitted data is appropriately encoded to protect user privacy. 【0538】 Step 3: 【0539】 The server analyzes the received financial information. It uses a database management system (e.g., MySQL) and data analysis libraries (e.g., NumPy, Pandas) to examine the user's financial situation. After the analysis, it calculates specific financial guidance to help the user achieve their goals. The output results determine appropriate financial plans and actions. 【0540】 Step 4: 【0541】 The server uses an emotion analysis engine to evaluate the user's emotions. It extracts emotional characteristics from text data using natural language processing libraries (e.g., spaCy, NLTK). An example of a prompt is, "Generate advice tailored to my current financial situation and emotions." The analyzed emotion data is used to refine the advice. 【0542】 Step 5: 【0543】 Leveraging a generative AI model, the server generates financial guidance best suited to the user. Based on prompts, it constructs messages tailored to the individual user's emotions and financial situation. The generated advice is then prepared for real-time delivery. 【0544】 Step 6: 【0545】 The terminal receives financial guidance transmitted from the server. This guidance is presented visually on the screen, and if voice output functionality is available, voice guidance is also possible. Based on this information, the user can review and adjust their financial plan. 【0546】 Step 7: 【0547】 Users can provide feedback on the financial guidance and emotion-based messages provided. The device collects this feedback and sends it to the server. The submitted feedback is used to improve the system and further optimize the advice. 【0548】 (Application Example 2) 【0549】 Next, we will explain Application Example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal." 【0550】 In today's world, users are required to create complex financial plans and manage their spending based on those plans. However, traditional financial advisory systems often fail to consider the user's emotional state, making it difficult to provide personalized advice. As a result, users are prone to financial anxiety and struggle to manage their spending efficiently. Therefore, there is a need for a system that takes user emotions into account and provides personalized spending advice. 【0551】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0552】 In this invention, the server includes information input means, information analysis means, emotion analysis means, information output means, expenditure management means, and psychological consideration means. This makes it possible to provide specific expenditure advice based on the user's individual financial situation and emotional state. 【0553】 "Information input means" refers to devices or software that allow users to input financial information and spending history. 【0554】 "Information analysis means" refers to devices or software that have the function of processing input financial information and generating individually tailored financial advice. 【0555】 "Emotional analysis tools" refer to devices or software used to analyze a user's emotions and create messages based on those emotions. 【0556】 "Information output means" refers to devices or software that provide users with advice and emotionally charged messages. 【0557】 "Expense management tools" refer to devices or software that analyze a user's spending history and generate a plan tailored to their financial status. 【0558】 "Psychological consideration measures" refer to devices or software that provide spending advice that takes into account the user's emotional state. 【0559】 The system for realizing this invention consists of several main components. The server plays a central role in processing information received from the user's terminal. The user uses a terminal such as a smartphone to input their financial information and spending history via an information input device. The terminal sends this information to the server using a secure protocol (e.g., HTTPS). 【0560】 On the server, information analysis tools use Python and Django to analyze financial information and generate advice tailored to the user. Furthermore, a natural language processing model using TensorFlow is employed as an emotion analysis tool to analyze the user's emotions from their input text and voice. The results of the emotion analysis are then used by psychological consideration tools to generate messages that take the user's psychological state into account, and these messages are provided to the user in real time through an information output tool. 【0561】 As a means of managing spending, the system analyzes the user's past spending history and develops savings plans and advice tailored to their financial situation. This allows users to manage their spending more effectively. 【0562】 As a concrete example, suppose a user is feeling anxious because their spending has increased at the end of the month. In this case, the emotion analysis tool recognizes this anxious feeling, and the psychological consideration tool generates a message that reassures the user. Furthermore, the spending management tool makes suggestions for future savings and provides them to the user through the information output tool. 【0563】 An example of a prompt might be: "The user is feeling anxious about increased spending this month. Take this into consideration and generate an encouraging message and specific savings suggestions." 【0564】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0565】 Step 1: 【0566】 Users input their financial information and spending history using their smartphones. The entered data is sent to the server in JSON format via the device's input method. 【0567】 Step 2: 【0568】 The server retrieves received financial information and spending history data and analyzes the data using data analysis tools. This process uses Python and Django to generate personalized advice based on each user's financial situation. The output of the analysis is personalized advice data optimized for each user. 【0569】 Step 3: 【0570】 The server uses a natural language processing model based on TensorFlow as a means of sentiment analysis to analyze user input text and audio data. This process acquires the user's emotional state as digital data, laying the foundation for taking the user's feelings into consideration. The output of the analysis is data indicating the user's emotional state. 【0571】 Step 4: 【0572】 The server combines the outputs of information analysis and emotion analysis methods, and uses psychological considerations to generate a message that takes the user's emotional state into account. This message is sent to the user's terminal in real time and serves to provide a sense of security. 【0573】 Step 5: 【0574】 The server uses expenditure management tools to analyze the user's past spending data and develop a future savings plan. This plan is aligned with the user's financial goals and is provided to the user through an information output tool. The savings plan output is displayed on the user's terminal as a concrete implementation plan. 【0575】 Step 6: 【0576】 Users can send feedback on the advice and messages provided. The feedback data received from the device is sent to the server and used to continuously improve the system's advice using learning mechanisms. This feedback output is reflected in subsequent advice generation. 【0577】 The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0578】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0579】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314. 【0580】 [Fourth Embodiment] 【0581】 Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment. 【0582】 As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server. 【0583】 The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network). 【0584】 The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52. 【0585】 The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46. 【0586】 Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision). 【0587】 Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner. 【0588】 The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes. 【0589】 Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56. 【0590】 The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30. 【0591】 The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. 【0592】 In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48. 【0593】 Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0594】 The personal AI financial planner system according to the present invention aims to alleviate users' financial anxieties and provide individually personalized financial advice. This system inputs and analyzes the user's financial information and provides advice, including emotion-based messages, in real time. 【0595】 1. User Input Phase 【0596】 The terminal accepts financial information such as the user's age, income, asset status, debt information, and goals. This information is provided by the user and entered through the terminal interface. 【0597】 2. Data Analysis Phase 【0598】 The server receives data sent by users and securely stores it in a database. Next, it analyzes this data using analytical tools to assess the user's current financial situation and calculate the necessary approaches to achieve their goals. It then generates optimal advice for each user. 【0599】 3. Emotional Analysis Phase 【0600】 The server performs sentiment analysis based on user input. This analysis assesses the user's current psychological state. In particular, if the user is feeling anxious, the sentiment analysis tool generates a reassuring message based on the results. 【0601】 4. Advice Provision Phase 【0602】 Based on the results of analysis and sentiment analysis, the server creates user-optimized advice and appropriate emotional messages. This information is transmitted to the device in real time, and the device provides the advice to the user via screen or audio. 【0603】 As a concrete example, consider a case where a user is trying to create a savings plan for buying a house. This user aims to save 5 million yen in 5 years for the purchase of a house. The device receives the user's annual income, current savings status, and monthly expenses as input. 【0604】 The server analyzes this data, calculates the monthly savings requirement, and identifies areas where savings can be made. Furthermore, if the user is experiencing stress regarding this savings plan, it provides messages based on the emotional analysis results, including realistic spending plans and budget advice. 【0605】 Through this system, individual users can create specific and reliable financial plans tailored to their own needs. 【0606】 The following describes the processing flow. 【0607】 Step 1: 【0608】 The user enters financial information such as their age, income, assets, liabilities, and financial goals through the terminal's input interface. The terminal formats the entered data and sends it to the server using a secure protocol. 【0609】 Step 2: 【0610】 The server stores the user's financial information received from the terminal in a database. Next, it uses analytical tools to understand the user's current situation and performs basic calculations and analyses to achieve financial goals. 【0611】 Step 3: 【0612】 The server uses sentiment analysis tools to evaluate the user's psychological state based on user input and past interaction data. This allows it to understand the user's current emotional tendencies and generate reassuring messages when necessary. 【0613】 Step 4: 【0614】 The server generates personalized financial advice applicable to the user based on data analysis and sentiment analysis results. It also prepares sentiment-based responses. 【0615】 Step 5: 【0616】 The server sends the generated financial advice and emotional messages to the terminal. The terminal displays this through its user interface and provides audio output as needed. 【0617】 Step 6: 【0618】 The user enters feedback and additional questions about the advice provided via the terminal. The terminal then sends this feedback to the server. 【0619】 Step 7: 【0620】 The server analyzes the feedback and uses the AI ​​model to learn what is needed to improve future advice. This allows the system to continuously improve and better meet user needs. 【0621】 (Example 1) 【0622】 Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0623】 Managing financial information while quickly providing appropriate suggestions tailored to individual circumstances is difficult with conventional systems. Furthermore, the lack of information that considers user emotions makes it difficult for users to make financial decisions with confidence. 【0624】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means. 【0625】 In this invention, the server includes an input means for inputting information about the user's finances, an analysis means for analyzing the input financial information and proposing individually tailored finances, and an emotion evaluation means for evaluating the user's psychological state and generating information based on that state. This makes it possible to provide users with individually customized financial proposals and reassuring information in real time. 【0626】 An "input method" is an interface that allows users to provide financial information to the system. 【0627】 "Analysis means" refers to the process of analyzing the input financial information and proposing the optimal financial plan to the user. 【0628】 An "emotional evaluation method" is a process for evaluating a user's psychological state and generating information based on that state. 【0629】 The "output means" is an interface for communicating the results of the analysis and sentiment evaluation to the user. 【0630】 "Voice processing functionality" refers to a function that analyzes voice information to understand user requests. 【0631】 The "learning function" is a feature that analyzes user feedback and continuously improves the content of suggestions based on that feedback. 【0632】 This invention relates to a personal AI financial planner system that alleviates users' financial anxieties and provides individually personalized financial advice. The system works by inputting information about the user's finances, analyzing it, evaluating their emotions, and then providing information based on the results. 【0633】 The device receives financial information from the user. This information includes age, income, assets, liabilities, and goals. The device interface is implemented through web forms or dedicated applications. 【0634】 The server receives this information and securely stores it in a database. Analysis is performed using data analysis libraries in Python and an SQL database. This evaluates the user's financial situation and calculates the optimal approach to achieving the goals to be accomplished. 【0635】 Furthermore, the server uses emotion evaluation tools and natural language processing techniques to analyze the user's psychological state. Based on this analysis, it generates emotionally supportive messages tailored to the user. 【0636】 As a concrete example, consider a user who wants to create a savings plan for buying a house. The user inputs their annual income, current savings status, and monthly expenses into a terminal. The server analyzes this information and provides a calculation of the required monthly savings amount and tips for reducing expenses. Furthermore, if the user is feeling stressed, a message is generated that provides reassurance based on the results of the emotion analysis. 【0637】 As an example of a prompt, the following sentence is input into the AI ​​generation model: "The user aims to save 5 million yen in 5 years. Please provide monthly savings amounts and specific advice on how to save to achieve this goal. Also, please include emotional support to reduce the user's stress level." This prompt allows the system to provide information optimized for the user. 【0638】 The flow of the specific processing in Example 1 will be explained using Figure 11. 【0639】 Step 1: 【0640】 Users input information such as age, income, asset status, debt information, and financial goals through their device. The input information is formatted in JSON or XML format and sent to the server. The input in this step is information about the user's finances, and the output is formatted data for storage in the database. 【0641】 Step 2: 【0642】 The server receives user information sent from the terminal and stores it in the database in a secure manner. The database has an SQL structure, with each field corresponding to user information. The input for this step is formatted data sent from the terminal, and the output is the storage operation into the database. 【0643】 Step 3: 【0644】 The server retrieves stored data using SQL queries and performs analysis using a Python data analysis library. The analysis evaluates the balance of income and expenses, savings and debt levels, and calculates the optimal plan for the user to achieve their goals. The input for this step is user information retrieved from the database, and the output is the calculated financial proposal. 【0645】 Step 4: 【0646】 The server uses natural language processing (NLP) techniques to analyze user input and perform sentiment analysis. Specifically, it estimates the user's psychological state from their text and generates messages to alleviate anxiety if present. The input for this step is the user's input, and the output is the generated message based on the sentiment analysis. 【0647】 Step 5: 【0648】 The server integrates analyzed financial recommendations and sentiment analysis-based messages to construct final advice. It selects the most relevant information and prepares to provide immediate feedback to the user. The input for this step is the results of the financial and sentiment analysis, and the output is the final advice and message provided to the user. 【0649】 Step 6: 【0650】 The terminal receives advice and messages sent from the server and presents them to the user via display or audio output. This presentation is in a format that is easy for the user to understand. Specifically, it provides text or audio feedback to help the user act on the suggestions. The input for this step is the final advice and messages from the server, and the output is what is presented to the user. 【0651】 (Application Example 1) 【0652】 Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0653】 In modern society, individual consumers face increasing financial anxieties and challenges in managing complex spending. The widespread adoption of electronic payments, in particular, has made it difficult for consumers to track their spending in real time and stick to their budgets. In this context, there is a need for support tools that enable consumers to live their daily lives with peace of mind and to create financial plans that align with their goals. 【0654】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. 【0655】 In this invention, the server includes a device for inputting the user's financial information, a processing device for analyzing the input financial information and generating individually adapted financial advice, an emotion analysis device for analyzing the user's emotions and creating messages based on their psychological state, an output device for providing advice and emotion-based messages to the user in real time, and a notification device for analyzing electronic payment data to evaluate spending patterns and support budget-friendly behavior. This enables consumers to manage their financial situation in real time while also gaining peace of mind. 【0656】 A "device for inputting user financial information" is a device equipped with an interface for collecting information provided by the user, such as age, income, asset status, debt information, and goals. 【0657】 A "processing device that analyzes financial information and generates individually tailored financial advice" is a computing device that calculates and generates the most suitable financial advice for each user based on collected financial information, in real time. 【0658】 A "sentiment analysis device that analyzes emotions and creates messages based on psychological state" is a mechanism that evaluates a user's psychological state based on their input information and behavioral data, and creates a message corresponding to the evaluation results. 【0659】 An "output device that provides users with real-time advice and sentiment-based messages" is a device that instantly transmits financial advice generated by a processing unit and messages created by a sentiment analysis device to the user. 【0660】 A "notification device that analyzes electronic payment data to evaluate spending patterns and support budget-conscious behavior" is a device that analyzes data related to a user's electronic payments, evaluates spending trends, and has the function of notifying the user to maintain spending within their budget. 【0661】 To implement this invention, the user's device must act as a financial information input device, requiring the user to input financial information such as age, income, asset status, debt information, and goals. This information is transmitted to the server via a secure connection. 【0662】 The server acts as a processing unit, analyzing the received financial information. Using a series of analytical methods, it assesses the user's current financial situation and generates personalized financial advice. The analysis utilizes specific algorithms and trend analysis of historical spending data. This technology often employs programming languages ​​such as Python and R, along with data analysis libraries. 【0663】 Furthermore, the server functions as an emotion analyzer, performing sentiment analysis based on user-provided text and other interaction data. This analysis evaluates the user's state of anxiety and reassurance, and based on this evaluation, creates emotion-based messages. Natural language processing technology can be used for sentiment analysis, and cloud services such as Google's Natural Language API or IBM's Watson may be used. 【0664】 To provide users with information in real time, the server sends generated financial advice and sentiment messages to the user's device. The user's device displays the message instantly using its notification function. The notification device receives information from the server and provides notifications to help users stay within their budget. For example, if a user is likely to exceed the budget they set at the beginning of the month, the app will display a real-time notification such as, "Your food expenses for this month have reached 80% of your budget." This notification may also refer to past spending trends to indicate areas where savings are possible. 【0665】 Furthermore, it utilizes a generative AI model to generate messages based on the user's thoughts and feelings. This process is achieved by prompting the AI ​​model, for example, by instructing it in the form of "Generate reassuring advice based on the user's current spending." 【0666】 The flow of a specific process in Application Example 1 will be explained using Figure 12. 【0667】 Step 1: 【0668】 The user enters their financial information into the terminal. The terminal receives information such as age, income, assets, liabilities, and goals, and sends it to the server. This information becomes the input and forms the basis for the next analysis. 【0669】 Step 2: 【0670】 The server analyzes the received financial information. The processing unit calculates the user's income and expenses and evaluates the progress of asset building. An algorithm is used for this, and the specific output generated includes monthly savings requirements and investment plan suggestions. 【0671】 Step 3: 【0672】 The server uses a generative AI model to analyze the user's emotions. It analyzes the words and behavioral history entered by the user using an emotion analysis device to determine their psychological state, such as anxiety or reassurance. Emotional information is used as input, and messages that provide a sense of security are output. 【0673】 Step 4: 【0674】 The server integrates financial advice and sentiment-based messages to generate optimal advice. The processing unit combines the analysis results and sentiment analysis output to formulate the most suitable recommendations for the user. The output includes customized recommendations and reassuring information. 【0675】 Step 5: 【0676】 The server sends the generated advice to the user's terminal in real time. The output device immediately displays a notification on the user's screen, and voice guidance is also available. This allows the user to receive information on their financial situation and psychological support at all times. 【0677】 Step 6: 【0678】 The server analyzes the user's electronic payment data and evaluates spending patterns. It then notifies the user via a notification device of any anomalies or concerns about budget overruns discovered through this analysis. The input is the electronic payment history, and the output includes specific alerts for spending control. 【0679】 Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions. 【0680】 The system according to the present invention aims to alleviate individual financial anxieties by providing personalized financial advice using the user's financial information. In particular, by combining this system with an emotion engine, the system can recognize the user's emotions and reflect them in the content of the advice. 【0681】 First, the user enters their financial information through the terminal's input interface. This information includes age, income, asset status, liabilities, and financial goals. The terminal collects this data and transmits it to the server using a secure communication method. 【0682】 The server analyzes the received data using analytical tools to evaluate the user's financial situation. Based on this, it generates specific financial advice tailored to the user's goals. 【0683】 One of the system's key features is its built-in emotion engine. This engine analyzes the user's emotions based on their input and conversation history. The analyzed emotion data is then used to tailor the advice it provides. For example, if a user is feeling stressed, the emotion engine will generate reassuring messages and reflect this in the advice. 【0684】 The generated advice and emotion-based messages are sent to the device in real time. The device displays this information on the screen and, if necessary, also provides it via audio. Users can provide feedback on the advice, which is sent from the device to the server and used to further improve the system. 【0685】 As a concrete example, consider a scenario where a user has set a savings goal for retirement and wants advice on how to create that plan. In this case, the user enters the necessary information into a terminal. The server analyzes this information and uses an emotion engine to prepare a message that alleviates the user's anxiety. After that, it provides the user with specific advice regarding their savings plan. 【0686】 Thus, the present invention provides personalized financial support that takes user emotions into consideration, creating an environment in which users can confidently engage in financial planning. 【0687】 The following describes the processing flow. 【0688】 Step 1: 【0689】 Users access a dedicated application on their device and enter their personal financial information. This information includes age, income, current assets, debt, and specific financial goals, which the device then organizes as digital data. 【0690】 Step 2: 【0691】 The terminal sends organized user data to the server using a secure protocol. This communication is encrypted to ensure data confidentiality. 【0692】 Step 3: 【0693】 The server first stores the received user data in a database. Next, it uses analytical tools to analyze the user's wealth management situation in detail and consider specific strategies for achieving goals. 【0694】 Step 4: 【0695】 The server activates the emotion engine, analyzes the user's input data and past interactions, and assesses their current emotional state. If it detects that the user is, for example, stressed, it tailors the message to address that. 【0696】 Step 5: 【0697】 The server integrates the analysis results and sentiment analysis results to generate user-optimized financial advice and emotionally sensitive messages. 【0698】 Step 6: 【0699】 The generated advice and messages are sent to the terminal in real time. The terminal displays them through its user interface and also provides audio output if necessary. 【0700】 Step 7: 【0701】 Users can enter feedback on the advice provided into their device. This feedback is sent to the server and used to improve the accuracy of future advice generation. 【0702】 Step 8: 【0703】 The server learns from feedback and improves the overall system performance. This process makes it possible to provide users with more highly personalized financial services. 【0704】 (Example 2) 【0705】 Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0706】 In modern life, receiving advice tailored to individual financial situations is a challenging task. Furthermore, existing technologies are insufficient to provide timely and appropriate advice while considering user emotions. Moreover, mechanisms for effectively utilizing user feedback to evolve the system are lacking. The objective of this invention is to address these issues and provide customized financial guidance to each individual user. 【0707】 The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. 【0708】 In this invention, the server includes acquisition means for receiving the user's financial information, processing means for analyzing the acquired financial information and generating balanced financial guidance, and sentiment analysis means for evaluating the user's emotions and constructing messages based on psychological characteristics. This makes it possible to provide individually customized financial guidance in real time and to realize a service that takes the user's emotions into consideration. 【0709】 "Means of acquisition" refers to the interface and process for receiving financial information from the user. 【0710】 "Processing means" refers to the functions and processes for analyzing acquired financial information and generating individually tailored financial guidance. 【0711】 "Emotion analysis means" refers to the functions and processes for evaluating a user's emotions and generating messages based on those emotions. 【0712】 "Display means" refers to an interface and process for presenting users with real-time generated financial guidance and sentiment-based information. 【0713】 "Learning tools" refer to the functions and processes used to improve financial guidance and dynamically evolve the system using user feedback. 【0714】 "Voice processing means" refers to a function and process for receiving voice information, analyzing that information, and identifying user requests. 【0715】 The system according to this invention is started when a user enters financial information using a terminal. The terminal collects information such as the user's age, income, asset status, liabilities, and financial goals via a dedicated input interface. The collected information is transmitted to a server via a secure communication method such as SSL or TLS. 【0716】 The server uses a database management system and data analysis libraries to analyze the received financial information. Specifically, it uses a MySQL database for management and analysis libraries such as NumPy and Pandas to analyze the user's financial situation in detail. This generates financial guidance that is tailored to the user's goals. 【0717】 Furthermore, the sentiment analysis engine installed on the server evaluates the user's emotions through natural language processing libraries (e.g., spaCy, NLTK). Based on this, a generative AI model is used to generate financial guidance that takes the user's emotions into consideration, in the form of prompts. An example of a prompt is, "Generate advice tailored to the user's current financial situation and emotions." 【0718】 The generated financial guidance is transmitted to the terminal in real time, and the terminal communicates it to the user through a display. The terminal not only provides information visually but also provides voice guidance if voice output functionality is available. Users can provide feedback on the advice provided, and the terminal collects this feedback and sends it to the server. This information is used to further improve the system and enhance the user experience. 【0719】 This system provides users with personalized financial guidance through this series of processes, creating an environment where users can confidently proceed with their financial planning. 【0720】 The flow of the specific processing in Example 2 will be explained using Figure 13. 【0721】 Step 1: 【0722】 Users enter financial information using a terminal. This data includes age, income, asset status, liabilities, and financial goals. The terminal provides a form-based input interface to accurately collect this information. The entered data is temporarily stored within the terminal. 【0723】 Step 2: 【0724】 The terminal transmits the collected financial information to the server. At this time, the data is encrypted using a secure communication method (e.g., SSL / TLS) to prevent unauthorized access by third parties. The transmitted data is appropriately encoded to protect user privacy. 【0725】 Step 3: 【0726】 The server analyzes the received financial information. It uses a database management system (e.g., MySQL) and data analysis libraries (e.g., NumPy, Pandas) to examine the user's financial situation. After the analysis, it calculates specific financial guidance to help the user achieve their goals. The output results determine appropriate financial plans and actions. 【0727】 Step 4: 【0728】 The server uses an emotion analysis engine to evaluate the user's emotions. It extracts emotional characteristics from text data using natural language processing libraries (e.g., spaCy, NLTK). An example of a prompt is, "Generate advice tailored to my current financial situation and emotions." The analyzed emotion data is used to refine the advice. 【0729】 Step 5: 【0730】 Leveraging a generative AI model, the server generates financial guidance best suited to the user. Based on prompts, it constructs messages tailored to the individual user's emotions and financial situation. The generated advice is then prepared for real-time delivery. 【0731】 Step 6: 【0732】 The terminal receives financial guidance transmitted from the server. This guidance is presented visually on the screen, and if voice output functionality is available, voice guidance is also possible. Based on this information, the user can review and adjust their financial plan. 【0733】 Step 7: 【0734】 Users can provide feedback on the financial guidance and emotion-based messages provided. The device collects this feedback and sends it to the server. The submitted feedback is used to improve the system and further optimize the advice. 【0735】 (Application Example 2) 【0736】 Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal". 【0737】 In today's world, users are required to create complex financial plans and manage their spending based on those plans. However, traditional financial advisory systems often fail to consider the user's emotional state, making it difficult to provide personalized advice. As a result, users are prone to financial anxiety and struggle to manage their spending efficiently. Therefore, there is a need for a system that takes user emotions into account and provides personalized spending advice. 【0738】 The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. 【0739】 In this invention, the server includes information input means, information analysis means, emotion analysis means, information output means, expenditure management means, and psychological consideration means. This makes it possible to provide specific expenditure advice based on the user's individual financial situation and emotional state. 【0740】 "Information input means" refers to devices or software that allow users to input financial information and spending history. 【0741】 "Information analysis means" refers to devices or software that have the function of processing input financial information and generating individually tailored financial advice. 【0742】 "Emotional analysis tools" refer to devices or software used to analyze a user's emotions and create messages based on those emotions. 【0743】 "Information output means" refers to devices or software that provide users with advice and emotionally charged messages. 【0744】 "Expense management tools" refer to devices or software that analyze a user's spending history and generate a plan tailored to their financial status. 【0745】 "Psychological consideration measures" refer to devices or software that provide spending advice that takes into account the user's emotional state. 【0746】 The system for realizing this invention consists of several main components. The server plays a central role in processing information received from the user's terminal. The user uses a terminal such as a smartphone to input their financial information and spending history via an information input device. The terminal sends this information to the server using a secure protocol (e.g., HTTPS). 【0747】 On the server, information analysis tools use Python and Django to analyze financial information and generate advice tailored to the user. Furthermore, a natural language processing model using TensorFlow is employed as an emotion analysis tool to analyze the user's emotions from their input text and voice. The results of the emotion analysis are then used by psychological consideration tools to generate messages that take the user's psychological state into account, and these messages are provided to the user in real time through an information output tool. 【0748】 As a means of managing spending, the system analyzes the user's past spending history and develops savings plans and advice tailored to their financial situation. This allows users to manage their spending more effectively. 【0749】 As a concrete example, suppose a user is feeling anxious because their spending has increased at the end of the month. In this case, the emotion analysis tool recognizes this anxious feeling, and the psychological consideration tool generates a message that reassures the user. Furthermore, the spending management tool makes suggestions for future savings and provides them to the user through the information output tool. 【0750】 An example of a prompt might be: "The user is feeling anxious about increased spending this month. Take this into consideration and generate an encouraging message and specific savings suggestions." 【0751】 The flow of a specific process in Application Example 2 will be explained using Figure 14. 【0752】 Step 1: 【0753】 Users input their financial information and spending history using their smartphones. The entered data is sent to the server in JSON format via the device's input method. 【0754】 Step 2: 【0755】 The server retrieves received financial information and spending history data and analyzes the data using data analysis tools. This process uses Python and Django to generate personalized advice based on each user's financial situation. The output of the analysis is personalized advice data optimized for each user. 【0756】 Step 3: 【0757】 The server uses a natural language processing model based on TensorFlow as a means of sentiment analysis to analyze user input text and audio data. This process acquires the user's emotional state as digital data, laying the foundation for taking the user's feelings into consideration. The output of the analysis is data indicating the user's emotional state. 【0758】 Step 4: 【0759】 The server combines the outputs of information analysis and emotion analysis methods, and uses psychological considerations to generate a message that takes the user's emotional state into account. This message is sent to the user's terminal in real time and serves to provide a sense of security. 【0760】 Step 5: 【0761】 The server uses expenditure management tools to analyze the user's past spending data and develop a future savings plan. This plan is aligned with the user's financial goals and is provided to the user through an information output tool. The savings plan output is displayed on the user's terminal as a concrete implementation plan. 【0762】 Step 6: 【0763】 Users can send feedback on the advice and messages provided. The feedback data received from the device is sent to the server and used to continuously improve the system's advice using learning mechanisms. This feedback output is reflected in subsequent advice generation. 【0764】 The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data. 【0765】 Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. 【0766】 In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414. 【0767】 Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion. 【0768】 Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together. 【0769】 These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression. 【0770】 The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become. 【0771】 Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant. 【0772】 The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more." 【0773】 The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values. 【0774】 The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format. 【0775】 In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data. 【0776】 In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56. 【0777】 Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12. 【0778】 Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56. 【0779】 The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using this memory. 【0780】 The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor. 【0781】 Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources. 【0782】 Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose. 【0783】 The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above. 【0784】 All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference. 【0785】 The following is further disclosed regarding the embodiments described above. 【0786】 (Claim 1) 【0787】 An input method for entering the user's financial information, 【0788】 An analysis means that analyzes the input financial information and generates individually tailored financial advice, 【0789】 A sentiment analysis tool that analyzes user emotions and creates messages based on their psychological state, 【0790】 An output method that provides users with real-time advice and emotion-based messages, 【0791】 A system that includes this. 【0792】 (Claim 2) 【0793】 The system according to claim 1, comprising a voice analysis means that accepts voice input and understands the user's request through voice analysis. 【0794】 (Claim 3) 【0795】 The system according to claim 1, comprising a learning means for receiving user feedback and continuously improving the content of advice based on the analyzed feedback. 【0796】 "Example 1" 【0797】 (Claim 1) 【0798】 An input method for entering the user's financial information, 【0799】 An analysis means that analyzes the input financial information and proposes individually tailored financials, 【0800】 A means of evaluating the user's psychological state and generating information based on that state, 【0801】 An output means that integrates the results of analysis and sentiment evaluation and conveys optimal information to the user, 【0802】 A system that includes this. 【0803】 (Claim 2) 【0804】 The system according to claim 1, comprising a voice processing function that analyzes voice information and understands requests. 【0805】 (Claim 3) 【0806】 The system according to claim 1, which includes a learning function that collects and analyzes user feedback and continuously improves the content of the proposal based on that feedback. 【0807】 "Application Example 1" 【0808】 (Claim 1) 【0809】 A device for inputting the user's financial information, 【0810】 A processing device that analyzes the input financial information and generates individually adapted financial advice, 【0811】 A sentiment analysis device that analyzes the user's emotions and creates messages based on their psychological state, 【0812】 An output device that provides users with advice and emotion-based messages in real time, 【0813】 A notification device that analyzes electronic payment data to evaluate spending patterns and supports budget-friendly behavior, 【0814】 A system that includes this. 【0815】 (Claim 2) 【0816】 The system according to claim 1, comprising a voice analysis device that accepts voice input and understands the user's request through voice analysis. 【0817】 (Claim 3) 【0818】 The system according to claim 1, comprising a learning device that receives user feedback and continuously improves the content of advice based on the analyzed feedback. 【0819】 "Example 2 of combining an emotion engine" 【0820】 (Claim 1) 【0821】 A means of obtaining the user's financial information, 【0822】 A processing means for analyzing the acquired financial information and generating compromised financial guidance, 【0823】 A sentiment analysis method that evaluates user emotions and constructs messages based on psychological characteristics, 【0824】 A display means that presents guidance and emotion-based information to the user in real time, 【0825】 A learning method that receives user feedback and dynamically improves the content of instruction based on said feedback, 【0826】 A system that includes this. 【0827】 (Claim 2) 【0828】 The system according to claim 1, comprising voice processing means for receiving voice information and analyzing the voice information to identify a user's request. 【0829】 (Claim 3) 【0830】 The system according to claim 1, comprising the function of shaping instruction using a generative AI model. 【0831】 "Application example 2 when combining with an emotional engine" 【0832】 (Claim 1) 【0833】 A means for inputting user financial information, 【0834】 Information analysis means for analyzing the input financial information and generating individually tailored financial advice, 【0835】 A means of sentiment analysis for analyzing user emotions and creating messages based on their psychological state, 【0836】 Information output means for providing users with real-time advice and emotion-based messages, 【0837】 A means of managing spending to analyze a user's spending history and generate a plan tailored to their financial status, 【0838】 Psychological considerations for providing spending advice that takes emotional state into account, 【0839】 A system that includes this. 【0840】 (Claim 2) 【0841】 The system according to claim 1, comprising voice analysis means for receiving voice input and understanding user requests through voice analysis. 【0842】 (Claim 3) 【0843】 The system according to claim 1, comprising a learning means for receiving user feedback and continuously improving the content of advice based on the analyzed feedback. [Explanation of symbols] 【0844】 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

[Claim 1] An input method for entering the user's financial information, An analysis means that analyzes the input financial information and generates individually tailored financial advice, A sentiment analysis tool that analyzes user emotions and creates messages based on their psychological state, An output method that provides users with real-time advice and emotion-based messages, A system that includes this. [Claim 2] The system according to claim 1, comprising a voice analysis means that accepts voice input and understands the user's request through voice analysis. [Claim 3] The system according to claim 1, comprising a learning means for receiving user feedback and continuously improving the content of advice based on the analyzed feedback.

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