system

Abstract

We provide the system. [Solution] A means of securely collecting financial data using an application programming interface as a means of acquiring data from financial institutions, A means of encrypting the collected financial data and integrating it for each user, A method of using multiple authentication factors during user authentication, A means to detect abnormal transactions in real time and send alerts, A means of regularly backing up data, A means of providing security education information to users, 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, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a character of the chatbot, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance as a response to the user utterance.

Prior Art Documents

Patent Documents

[0003] [[ID=二十一]] [[ID=二十二]]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern times, most individuals having accounts across multiple financial institutions need means to integrate data while ensuring security and privacy in order to manage the data of each account safely and efficiently. At this time, it is an issue to reduce security risks such as unauthorized access, data leakage, overlooking abnormal transactions, and data disappearance that may occur during data collection and integration.

Means for Solving the Problems

[0005] To address this challenge, the present invention provides a system for securely collecting and integrating data using the application programming interface of financial institutions. The system encrypts the collected data and manages it on a per-user basis. Furthermore, it prevents unauthorized access using multi-factor authentication during login and enables rapid response by detecting abnormal transactions in real time and issuing immediate alerts. It also reduces the risk of data loss by regularly backing up data and operating in a way that allows for rapid restoration. Additionally, it promotes best practices in data management by providing security education and advice to users.

[0006] A "financial institution" is an organization that provides financial services to customers, such as asset management, loans, and investment consultations, including banks, credit unions, and securities companies.

[0007] An "application programming interface" is an interface used by a software application to communicate with and utilize the functions of other software or systems.

[0008] "Data encryption" is a security technology that transforms data so that its contents cannot be deciphered by third parties, and is used to prevent unauthorized access and data leaks.

[0009] "Multi-factor authentication" is a security method that requires a combination of multiple different authentication factors when a user accesses a system.

[0010] Anomaly detection is the process of identifying unusual data patterns or behaviors to uncover potentially fraudulent or problematic events.

[0011] A "real-time alert" is a function that immediately issues a warning when an anomaly or emergency occurs, and is used to encourage a quick response.

[0012] "Data backup" is the process of regularly duplicating data and storing it in a secure location to protect against data loss or corruption.

[0013] "Security education" is an educational activity that conveys the importance of information security, knowledge of risk management, and best practices to users. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13]It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

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

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be one arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be one type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), etc.

[0018] In the following embodiments, the 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, the 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 disk (e.g., hard disk), or magnetic tape, etc.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

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

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a system for securely collecting and centrally managing account data held by a user across multiple financial institutions. Specific embodiments of the system, including servers, terminals, and data processing between them, will be described.

[0036] The server securely utilizes the financial institution's application programming interface to periodically collect necessary data from user accounts. The server encrypts the collected data on the spot and stores it in a database, associated with each user's identification information. This significantly reduces the risk of data theft or leakage.

[0037] The terminal is used when users log in to the system. In addition to their usual ID and password, users must go through multi-factor authentication. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, to prevent unauthorized access.

[0038] The server continuously monitors the stored data and, upon detecting any unusual transactions, immediately sends a real-time alert to the terminal. This alert allows users to take swift action.

[0039] Furthermore, the server regularly backs up all data. This backup data is stored on secure external storage to enable rapid restoration in the event of a disaster or data loss.

[0040] Furthermore, the server provides users with ongoing security education. For example, information on best practices for data management and advice on countermeasures against the latest security threats are delivered to users through their devices.

[0041] As a concrete example, consider a case where a user wants to check their transaction history from their financial institution. The user goes through multi-factor authentication on their device, and the server decrypts the transaction history, which is stored in an encrypted state, based on the user's request. Next, the device displays the decrypted data to the user, allowing the user to check the detailed transaction history.

[0042] In this way, the present invention can securely and efficiently manage users' financial data, improving its convenience while protecting privacy.

[0043] The following describes the processing flow.

[0044] Step 1:

[0045] The user logs into the system using a terminal. The user first enters their ID and password. The terminal receives this information and sends it to the server.

[0046] Step 2:

[0047] The server compares the received ID and password with the authentication database. If authentication is successful, the server sends a multi-factor authentication request to the terminal.

[0048] Step 3:

[0049] The user completes the multi-factor authentication requested on the device. This uses biometric authentication or a verification code sent via SMS. The device then sends the result to the server.

[0050] Step 4:

[0051] The server verifies the results of multi-factor authentication and, if successful, initiates the user's session. This grants the user access to the system.

[0052] Step 5:

[0053] The server retrieves user account data through the financial institution's application programming interface. This is done regularly and securely.

[0054] Step 6:

[0055] The acquired data is immediately encrypted on the server and stored in the database in a format recognizable to each user.

[0056] Step 7:

[0057] The server analyzes the stored data in real time and applies an anomaly detection algorithm if an abnormal transaction occurs.

[0058] Step 8:

[0059] When an unusual transaction is detected, the server immediately sends a real-time alert to the terminal. The user can receive this alert and view the details.

[0060] Step 9:

[0061] The server regularly backs up all data and stores it on secure external storage. This allows for quick recovery in the event of data loss.

[0062] Step 10:

[0063] The server regularly provides users with security education information and content on best practices. Users can receive this information through their devices and improve their security awareness.

[0064] (Example 1)

[0065] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0066] Information agencies are required to manage user data securely and efficiently, while protecting privacy and enhancing convenience. However, conventional systems are prone to security risks during data collection and storage, and lack sufficient timeliness and reliability in anomaly detection and data recovery.

[0067] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0068] In this invention, the server includes means for securely collecting information data using a communication interface as a means for acquiring data from an information agency, means for transforming the collected information data and integrating it for each user, and means for using multiple authentication factors when authenticating users. This enables secure collection, management, anomaly detection, and rapid recovery of information data.

[0069] An "information agency" is an organization or system that manages information data and provides necessary data securely.

[0070] A "communication interface" is a means of connection that allows different systems or software to exchange information with each other.

[0071] "Information data" refers to the collection of all data related to accounts and transactions held by a user.

[0072] A "user" is an individual or organization that uses this system to manage, view, or manipulate information data.

[0073] "Anomaly detection" is the process of identifying fraudulent or unexpected behavior that deviates from normal usage patterns in real time.

[0074] A "warning" is a notification intended to promptly inform users when an anomaly or risk is detected.

[0075] "Record keeping" refers to the act of regularly saving informational data in a secure location for future reference or recovery.

[0076] "Security education information" refers to the knowledge and information on the latest security threats that users need to manage their information data securely.

[0077] The system in this invention specifically demonstrates a method for safely and efficiently collecting, managing, and providing user information data. The implementation of this system is described below.

[0078] The server functions as the central hub of this system, securely collecting data from intelligence agencies using communication interfaces. The server encrypts the collected data and stores it in a database for each user. Security protocols such as HTTPS and AES (Advanced Encryption Standard) are used in this process.

[0079] The terminal provides users with a means to access the system and view and manipulate information data. Users can log in through the terminal using their ID, password, and multi-factor authentication to securely use the system. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, which prevents unauthorized access.

[0080] The server also has the ability to monitor stored data in real time and immediately generate and send alerts to terminals if unusual transactions or unauthorized access are detected. This alert function allows users to respond quickly to abnormal situations.

[0081] Furthermore, the server is configured to regularly back up all data in the database, allowing for rapid restoration of the stored data in the event of a disaster or data loss. The backup data is securely stored on secure external storage.

[0082] Furthermore, the server provides users with security education information through their terminals. This includes best practices for data management and information on the latest security threats. This ensures that users can always manage their information data securely based on the most up-to-date information.

[0083] As a concrete example, consider the procedure for a user to check their transaction history. The user logs into their device and goes through multi-factor authentication. Next, the server decrypts the encrypted transaction data and sends it back to the device. The user can then view the detailed transaction history on the device screen and export the data if necessary.

[0084] An example of a prompt sentence to be input into the generating AI model would be, "Please provide detailed instructions on how to securely manage financial data." This system would enable users to manage their data securely and efficiently.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The server securely collects data from intelligence agencies using a communication interface. It receives authentication information and necessary API keys for each user as input. The server uses this information to send HTTP requests to the API, receiving data such as transaction history and account balances. This output data is the raw data collected.

[0088] Step 2:

[0089] The server encrypts the collected raw data. It receives the information data collected in step 1 as input. The server encrypts the data using the AES encryption algorithm and stores it in a database, integrating it for each user. This output data becomes encrypted and secure.

[0090] Step 3:

[0091] The user logs into the system using a terminal. The user is required to enter a user ID, password, and multi-factor authentication information. The terminal sends this information to the server for authentication. Upon successful authentication, secure access rights are granted as output.

[0092] Step 4:

[0093] The server monitors the stored data in real time. Encrypted data from the database is used as input. The server applies anomaly detection algorithms to detect fraudulent transactions and access. If detected, an alert is generated as output and immediately sent to the terminal.

[0094] Step 5:

[0095] The user checks alerts from the server via their terminal and takes immediate action if necessary. The input is the alert information generated in step 4. The user reviews the alert content and takes action, such as canceling the process or reporting the information to the administrator. The output is the maintenance of a secure state after the action has been taken.

[0096] Step 6:

[0097] The server periodically backs up all the data in the database. It receives encrypted stored data as input. The server securely transfers this data to external storage and stores it there. As output, recoverable backup data is generated.

[0098] Step 7:

[0099] The server regularly delivers security education information to users. As input, it prepares the latest security information and best practices. By providing this information to users through their terminals, the server enables users to gain the knowledge to securely manage their own data. As output, the security awareness of users who receive the information improves.

[0100] (Application Example 1)

[0101] 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."

[0102] Modern users are required to efficiently and securely manage financial information dispersed across multiple financial information sources. However, existing systems have been insufficient in information collection and monitoring, resulting in a heavy management burden on users. Furthermore, the risk of fraudulent transactions and information leaks is high, and measures to adequately avoid these are needed. Improving this situation and providing an environment in which users can conduct financial transactions with peace of mind is an urgent task.

[0103] 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.

[0104] In this invention, the server includes means for securely collecting financial information using a communication protocol as a means for acquiring data from financial information sources, means for encoding the collected financial information and integrating it for each user, and means for collecting and managing users' financial information using a mobile information terminal. This enables users to centrally manage data from multiple financial information sources and strengthen monitoring of fraudulent transactions.

[0105] A "financial information source" refers to an organization or system that provides data related to users' financial activities.

[0106] A "communication protocol" is a set of rules and procedures that define how data is exchanged between different systems.

[0107] "Encoding" refers to the process of transforming data using specific algorithms to protect it from unauthorized access and eavesdropping by third parties.

[0108] "User" refers to a person or organization that uses the system, and in this invention, it refers to the entity that manages financial information.

[0109] A "portable information terminal" refers to a computing device that users can easily carry around, and includes smartphones and tablets.

[0110] "Fraudulent transactions" refer to financial transactions conducted against the user's will, and can be carried out through fraud or unauthorized access.

[0111] The system realizing this invention mainly consists of a server, a mobile information terminal, and communication means connecting them. The server connects to financial information sources, periodically collects financial data through communication protocols, encodes the collected data, and stores it securely. The server also utilizes anomaly transaction detection algorithms to analyze the collected data and identify signs of fraudulent transactions. This allows users to receive warnings in real time.

[0112] The personal digital assistant (PDCA) provides an interface for users to enter their authentication information and ensures secure access by utilizing multiple authentication factors. Users can use the PDCA to check their financial information and receive security education information provided by the system. The server is designed to ensure user convenience by balancing ease of operation with high security throughout the entire system.

[0113] For example, when a user uses a payment application on their mobile device while shopping on the weekend, the system collects the latest financial information in the background and provides the user with safety education information as needed.

[0114] An example of a prompt using a generative AI model is, "Please suggest a method to securely and efficiently manage users' financial data and detect abnormal transactions in real time."

[0115] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0116] Step 1:

[0117] The server connects to financial information sources and collects financial data using communication protocols. In this process, the server sends API requests to financial information sources to retrieve data such as the user's transaction history and account information. The input is the data obtained from the financial information source's API, and the output is the raw financial data received by the server.

[0118] Step 2:

[0119] The server encodes the acquired financial data. Specifically, the server transforms the data using an encryption algorithm (e.g., AES) and stores it securely. The input is raw financial data, and the output is encrypted data. This protects the data from unauthorized access.

[0120] Step 3:

[0121] Users log in to the system using a mobile device. The device receives the user's ID, password, and multi-factor authentication elements (e.g., biometric authentication or SMS code) and performs secure authentication. The input is the user's authentication information, and the output is the success or failure of the authentication.

[0122] Step 4:

[0123] The server analyzes encrypted data and identifies fraudulent transactions through an anomaly detection algorithm. Specifically, the anomaly detection algorithm builds a statistical model based on historical data and detects abnormal patterns. The input is decoded financial data, and the output is a list of transactions considered anomaly.

[0124] Step 5:

[0125] If the server detects a fraudulent transaction, it sends a real-time warning to the mobile device. The device then notifies the user of this warning, prompting them to take immediate action. The input is an abnormal transaction alert, and the output is a warning display on the device.

[0126] Step 6:

[0127] The server periodically generates security education information and distributes it to users via mobile devices. Specifically, it updates information on the latest cybersecurity threats and countermeasures to raise users' security awareness. The input is the periodic update information on the server, and the output is the display of educational content on the device.

[0128] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0129] This invention provides a system that, in addition to managing users' financial data, recognizes users' emotions and dynamically adjusts the interface based on those emotions. The system includes a server, a terminal, and an emotion engine, and the roles of each will be described below.

[0130] The server handles the traditional processes of collecting and managing financial data. Simultaneously, it analyzes user emotional data through an emotion engine and optimizes the user experience based on the results. It can also adjust security levels according to the user's emotional state.

[0131] The emotion engine analyzes user input information, such as voice and facial expressions, to identify the user's emotional state. The emotion engine then sends this information to a server, providing a foundation for the entire system to adapt based on emotions.

[0132] The device functions as a user interface, optimizing screen display and operation methods based on feedback from the emotion engine. For example, if the device determines that the user is experiencing stress, it will provide a simpler, stress-reducing interface. This simplified display allows the user to access information and perform actions more smoothly than usual.

[0133] Furthermore, the system provides personalized advice in real time based on insights gained from analyzing the user's emotions. For example, if the emotion engine detects high levels of anxiety in a user, the server immediately suggests financial advice or relaxation methods, and the terminal notifies the user of this.

[0134] In this way, embodiments of the present invention are capable of not only securely managing financial data but also improving the user experience based on user emotions and providing more personalized services. This increases user satisfaction and significantly enhances the usability of the system.

[0135] The following describes the processing flow.

[0136] Step 1:

[0137] The user logs into the system via their device. The user enters their ID and password and completes multi-factor authentication to obtain secure access.

[0138] Step 2:

[0139] The server retrieves the user's financial data through the financial institution's application programming interface. This data is stored on the server in an encrypted state.

[0140] Step 3:

[0141] The emotion engine acquires the user's facial expressions and voice data and analyzes their emotional state in real time. The results of this analysis are then sent to the server.

[0142] Step 4:

[0143] The server adjusts the interface and content according to the user's situation based on the emotional data received from the emotion engine. This adjustment is then transmitted to the device.

[0144] Step 5:

[0145] The terminal provides a user interface that adapts to the user's emotional state based on instructions from the server. For example, if it is determined that the user is experiencing high levels of stress, a simpler and easier-to-understand interface will be displayed.

[0146] Step 6:

[0147] The server comprehensively analyzes the user's financial and emotional data to generate personalized financial advice and security alerts. This information is then communicated to the user via their device.

[0148] Step 7:

[0149] The terminal displays advice and warnings sent from the server to the user and assists the user's actions as needed. This allows the user to take quick and appropriate action.

[0150] Step 8:

[0151] The server backs up data and analysis results and stores them in secure storage for future reference. This backup reduces the risk of data loss and improves system reliability.

[0152] (Example 2)

[0153] 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".

[0154] In recent years, financial services have demanded secure data management and improved user experience. However, challenges remain, including the risk of misuse and leakage of financial information, as well as the fact that uniform interfaces that do not consider users' emotional responses lower user satisfaction. Furthermore, there is a lack of dynamic service delivery that responds to emotions, making it difficult to provide services that meet the needs of individual users.

[0155] 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.

[0156] In this invention, the server includes means for securely collecting financial information, means for dynamically adjusting the display interface and operating methods based on the user's emotions, and means for generating and notifying appropriate financial advice according to the user's emotional state. This enables the secure management of financial information and personalized services that are tailored to the user's emotional needs.

[0157] "Financial institutions" refer to organizations and institutions that provide financial services, such as banks and securities companies.

[0158] An "application programming interface" refers to a set of conventions and tools that enable communication between different software applications.

[0159] "Financial information" refers to data about an individual's or organization's financial situation, such as bank account balances, transaction history, and spending patterns.

[0160] "Encryption" refers to the process of protecting data by encoding it using a specific algorithm.

[0161] "Users" refer to individuals or organizations that use a particular system or service.

[0162] "Authentication factors" are identifying information used to grant access to a system, and include passwords and biometric information.

[0163] "Economic activity" refers to the trading of assets and services and other financial activities carried out by individuals or organizations.

[0164] "Backup storage" refers to the process of creating copies of the same information and storing them in a separate location to prevent data loss.

[0165] "Security education" refers to educational activities aimed at providing users with knowledge and measures related to information security and raising their awareness.

[0166] "Emotions" refer to an individual's inner feelings or state of being, such as joy, sadness, or anger.

[0167] An "interface" refers to the screen display or means of operation that serves as a window for a user to interact with a system or device.

[0168] "Advice" refers to suggestions or instructions that are offered based on the situation or circumstances.

[0169] A "warning" refers to a notification intended to draw attention to a specific risk or anomaly.

[0170] The system of the present invention provides an advanced user experience that integrates financial data management and user emotion recognition. The following describes specific implementations of this system.

[0171] The server securely collects and manages financial information, integrating it into user-specific databases. This utilizes technologies that protect and make the information accessible using traditional database management systems and application programming interfaces (APIs). The server also analyzes data received from the emotion engine to generate insights for optimizing the user experience. Based on these insights, the system's security level is adjusted as needed.

[0172] The emotion engine utilizes hardware and software to analyze emotions from the user's voice and facial expressions. Specifically, it processes data acquired using cameras and microphones with machine learning models to estimate the user's emotional state. This emotional information is transmitted to the server in real time, forming the foundation for the entire system to provide services tailored to the user's emotional state.

[0173] The device provides an interface that directly interacts with the user. Based on feedback from the emotion engine, it dynamically changes the displayed content and operation methods to provide a more comfortable user experience. If the device detects that the user is experiencing stress, it automatically adjusts to an easier-to-use interface to reduce the user's burden.

[0174] As a concrete example, if the emotion engine detects that a user is stressed while trading stocks, the server immediately generates financial advice and provides a message through the terminal stating, "We recommend that you calmly analyze the situation and check for additional information if necessary." This allows the user to make decisions while remaining emotionally calm.

[0175] An example of a prompt message is: "Based on the analysis of the user's facial expressions and voice, the user is experiencing high levels of stress. How should the system adjust the interface and provide feedback to the user in this situation?" Thus, the present invention aims to improve the user experience from both the perspectives of financial information management and sentiment analysis.

[0176] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0177] Step 1:

[0178] The server collects financial information through the application programming interface of financial institutions. This information includes user transaction history and account balances. Input is data from financial institutions, and output is organized financial information. The server ensures security by encrypting the received information and storing it in a database. Specifically, it periodically calls the API to retrieve the latest data.

[0179] Step 2:

[0180] The emotion engine receives user audio and video data from the device. Inputs include the user's real-time voice and facial expressions. The emotion engine analyzes this data and evaluates the user's emotional state. Data processing is performed using an emotion analysis algorithm, and the output is the evaluation result of the emotional state. This information is sent to the server and stored as the user's emotional foundational data. Specific operations include acquiring data using speech recognition and facial expression detection technologies and inputting it into the model.

[0181] Step 3:

[0182] The server integrates financial and emotional data for comprehensive analysis. Inputs include financial information and emotional state data. Data processing involves algorithmic operation to correlate this information and identify user behavior patterns and needs; the output is a personalized user profile. Based on continuous analysis, it prepares appropriate advice and interface adjustments. Specifically, it uses machine learning models to analyze the dataset and extract insights.

[0183] Step 4:

[0184] The terminal receives results from the server and adjusts the user interface. Input is the analysis results from the server, and output is the adjusted display screen and operation method. Based on the user's state, the terminal changes the interface to reduce stress and provides voice navigation and guidance as needed. Specific actions include simplifying the graphic display and rearranging the layout to make important operation buttons more prominent.

[0185] Step 5:

[0186] The server generates appropriate financial advice based on user behavior and sentiment analysis. The input is integrated user data, and the output is personalized advice. The generating AI model generates future recommended actions and risk warnings based on historical data. This information is sent to the terminal in the form of prompts. Specifically, this involves inputting data into a predictive algorithm and sending the generated text to the user.

[0187] (Application Example 2)

[0188] 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".

[0189] While existing financial data management systems are effective in securely managing users' financial data, they struggle to provide more personalized support and optimized user interfaces based on users' emotional states. Furthermore, there is a need to adjust security levels according to users' emotional states and to create a comfortable user experience. The challenge lies in improving user satisfaction and reducing stress.

[0190] 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.

[0191] In this invention, the server includes means for securely collecting financial data using an application programming interface as a means for acquiring data from financial institutions, means for recognizing the emotional state of the user, and means for dynamically adjusting the user interface based on the emotional state. This enables the secure management of the user's financial data, as well as the optimization of the interface in response to emotions, thereby improving user satisfaction and providing a personalized user experience.

[0192] "Data acquisition means" refers to a function that securely acquires financial data using the application programming interface of a financial institution.

[0193] "Encryption methods" are technologies used to protect acquired financial data and integrate it for each user.

[0194] "Authentication method" refers to the process of verifying the identity of a user using multi-factor authentication.

[0195] An "anomaly detection system" is a system that identifies fraudulent or abnormal transactions in real time and generates warnings.

[0196] A "backup method" is a procedure for regularly saving data and making it possible to restore it as needed.

[0197] A "security education tool" is a system for providing users with knowledge about information security.

[0198] "Emotion recognition means" refers to technology that analyzes voice and facial expressions to identify the emotional state of a user.

[0199] An "interface adjustment mechanism" is a system that dynamically changes the displayed content and operating procedures according to the user's current situation.

[0200] "Personalized advice tools" are functions that provide specific advice and suggestions based on the user's emotions and circumstances.

[0201] The system implementing this invention primarily consists of a server, a terminal, and an emotion recognition engine. The server is responsible for collecting and integrating financial data, and also manages data necessary to recognize the emotional state of the user. The server obtains financial information using APIs from financial institutions, encrypts it, and then organizes and integrates it for each user. Furthermore, the server dynamically adjusts the interface and service provision based on the results of the user's emotion recognition.

[0202] The emotion recognition engine analyzes the user's voice and facial expression data acquired by the device to identify the user's emotional state. Specifically, it utilizes speech recognition and image processing technologies to determine whether the user is experiencing stress. The emotional data generated by the emotion recognition engine is sent to a server and used for further analysis and interface optimization.

[0203] The terminal functions as an interface with the user, optimizing screen displays and operation methods based on instructions provided by the server. For example, if the terminal determines that the user is stressed, it reduces the user's operational burden by displaying a simpler interface that responds to their emotions. Conversely, if the user is relaxed, it can display detailed financial information comprehensively, providing the user with deeper insights.

[0204] Furthermore, the generative AI model uses the user's emotional state and financial data to provide personalized advice and suggestions in real time. This AI model has the ability to provide more optimal advice by analyzing past data and trends.

[0205] As a concrete example, when a user uses an electronic wallet application through their device, the system analyzes their facial expressions and voice for the day and presents the interface best suited to their emotions at that time. For instance, if the system detects a visually tired expression on a weekday evening, it can alleviate fatigue by providing the user with key functions in a simple quick-access mode.

[0206] An example of a prompt for a generated AI model is: "Generate an AI model that adjusts the interface based on the user's emotional state and provides appropriate advice where reconfirmation is needed."

[0207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0208] Step 1:

[0209] The device acquires the user's voice and facial expressions through its camera and microphone. This data serves as input to identify the user's emotional state. Voice data is converted to text using speech recognition software, and image data is categorized into emotional categories using a facial recognition algorithm.

[0210] Step 2:

[0211] The server receives audio and facial expression data from the emotion recognition engine and analyzes it using an emotion identification algorithm. This process outputs the user's emotional state as "stressed," "relaxed," "concentrated," etc. The identified emotion is then used as a criterion for subsequent interface adjustments.

[0212] Step 3:

[0213] The server dynamically adjusts the user interface based on the identified emotional state. For example, if the server identifies that the user is stressed, it translates the data into a command to "provide a simple interface" and sends it to the terminal. When selecting or reconfiguring the user interface, a generative AI model presents appropriate scenarios.

[0214] Step 4:

[0215] The terminal dynamically changes the user interface based on instructions from the server. This operation provides the user with a simple and intuitive display, reducing the burden of operation. For example, it can highlight only important financial information and omit other details.

[0216] Step 5:

[0217] When a user performs a transaction or operation through the user interface, the terminal sends the details to the server. This data is processed through the financial institution's API, and the security of the transaction is verified. Transaction information is properly encrypted in the backend and stored in a financial database.

[0218] Step 6:

[0219] Based on the user's transaction and behavioral history, the server uses a generative AI model to create personalized advice and suggestions. The generated content is structured as something like "Investment advice perfect for a relaxing evening" and is ultimately presented to the user through their device.

[0220] This entire process is designed to provide a more personalized user experience, allowing users to conduct financial transactions in a relaxed state.

[0221] 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.

[0222] 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.

[0223] 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.

[0224] [Second Embodiment]

[0225] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0226] 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.

[0227] 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).

[0228] 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.

[0229] 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.

[0230] 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).

[0231] 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.

[0232] 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.

[0233] 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.

[0234] 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.

[0235] 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.

[0236] 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".

[0237] This invention provides a system for securely collecting and centrally managing account data held by a user across multiple financial institutions. Specific embodiments of the system, including servers, terminals, and data processing between them, will be described.

[0238] The server securely utilizes the financial institution's application programming interface to periodically collect necessary data from user accounts. The server encrypts the collected data on the spot and stores it in a database, associated with each user's identification information. This significantly reduces the risk of data theft or leakage.

[0239] The terminal is used when users log in to the system. In addition to their usual ID and password, users must go through multi-factor authentication. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, to prevent unauthorized access.

[0240] The server continuously monitors the stored data and, upon detecting any unusual transactions, immediately sends a real-time alert to the terminal. This alert allows users to take swift action.

[0241] Furthermore, the server regularly backs up all data. This backup data is stored on secure external storage to enable rapid restoration in the event of a disaster or data loss.

[0242] Furthermore, the server provides users with ongoing security education. For example, information on best practices for data management and advice on countermeasures against the latest security threats are delivered to users through their devices.

[0243] As a concrete example, consider a case where a user wants to check their transaction history from their financial institution. The user goes through multi-factor authentication on their device, and the server decrypts the transaction history, which is stored in an encrypted state, based on the user's request. Next, the device displays the decrypted data to the user, allowing the user to check the detailed transaction history.

[0244] In this way, the present invention can securely and efficiently manage users' financial data, improving its convenience while protecting privacy.

[0245] The following describes the processing flow.

[0246] Step 1:

[0247] The user logs into the system using a terminal. The user first enters their ID and password. The terminal receives this information and sends it to the server.

[0248] Step 2:

[0249] The server compares the received ID and password with the authentication database. If authentication is successful, the server sends a multi-factor authentication request to the terminal.

[0250] Step 3:

[0251] The user completes the multi-factor authentication requested on the device. This uses biometric authentication or a verification code sent via SMS. The device then sends the result to the server.

[0252] Step 4:

[0253] The server verifies the results of multi-factor authentication and, if successful, initiates the user's session. This grants the user access to the system.

[0254] Step 5:

[0255] The server retrieves user account data through the financial institution's application programming interface. This is done regularly and securely.

[0256] Step 6:

[0257] The acquired data is immediately encrypted on the server and stored in the database in a format recognizable to each user.

[0258] Step 7:

[0259] The server analyzes the stored data in real time and applies an anomaly detection algorithm if an abnormal transaction occurs.

[0260] Step 8:

[0261] When an unusual transaction is detected, the server immediately sends a real-time alert to the terminal. The user can receive this alert and view the details.

[0262] Step 9:

[0263] The server regularly backs up all data and stores it on secure external storage. This allows for quick recovery in the event of data loss.

[0264] Step 10:

[0265] The server regularly provides users with security education information and content on best practices. Users can receive this information through their devices and improve their security awareness.

[0266] (Example 1)

[0267] 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."

[0268] Information agencies are required to manage user data securely and efficiently, while protecting privacy and enhancing convenience. However, conventional systems are prone to security risks during data collection and storage, and lack sufficient timeliness and reliability in anomaly detection and data recovery.

[0269] 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.

[0270] In this invention, the server includes means for securely collecting information data using a communication interface as a means for acquiring data from an information agency, means for transforming the collected information data and integrating it for each user, and means for using multiple authentication factors when authenticating users. This enables secure collection, management, anomaly detection, and rapid recovery of information data.

[0271] An "information agency" is an organization or system that manages information data and provides necessary data securely.

[0272] A "communication interface" is a means of connection that allows different systems or software to exchange information with each other.

[0273] "Information data" refers to the collection of all data related to accounts and transactions held by a user.

[0274] A "user" is an individual or organization that uses this system to manage, view, or manipulate information data.

[0275] "Anomaly detection" is the process of identifying fraudulent or unexpected behavior that deviates from normal usage patterns in real time.

[0276] A "warning" is a notification intended to promptly inform users when an anomaly or risk is detected.

[0277] "Record keeping" refers to the act of regularly saving informational data in a secure location for future reference or recovery.

[0278] "Security education information" refers to the knowledge and information on the latest security threats that users need to manage their information data securely.

[0279] The system in this invention specifically demonstrates a method for safely and efficiently collecting, managing, and providing user information data. The implementation of this system is described below.

[0280] The server functions as the center of this system and securely collects data from information institutions using a communication interface. The server encrypts the collected information data and integrates and stores it in a database for each user. In this process, security protocols such as HTTPS or AES (Advanced Encryption Standard) are used.

[0281] The terminal provides a means for users to access the system and view and operate information data. Users can log in securely to the system using an ID, password, and multi-factor authentication through the terminal. The terminal supports multiple authentication methods including biometric authentication and SMS codes, thereby preventing unauthorized access.

[0282] The server further has a function of monitoring the stored data in real time, generating an alert immediately when an abnormal transaction or unauthorized access is detected, and sending it to the terminal. With this alert function, users can respond quickly to abnormal situations.

[0283] Also, the server is configured to regularly back up all the data in the database so that the recorded and stored data can be quickly restored in case of a disaster or data loss. The backup data is securely stored in a secure external storage.

[0284] Furthermore, the server provides security education information to users through the terminal. This includes information on best practices for data management and the latest security threats. Thereby, users can always manage information data securely based on the latest information.

[0285] As a specific example, consider the procedure when a user checks their transaction history. The user logs in to the terminal and passes multi-factor authentication. Next, the server decrypts the targeted encrypted transaction data and sends it back to the terminal. The user can view the detailed transaction history on the terminal screen and export the data if necessary.

[0286] As an example of a prompt sentence to input into the generative AI model, a sentence such as "Please teach me in detail the procedure for securely managing financial data" can be considered. With this system, users can manage their data securely and efficiently.

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

[0288] Step 1:

[0289] The server securely collects data from the information institution using the communication interface. As inputs, it receives authentication information and the necessary API keys for each user. The server uses these to send an HTTP request to the API and receives information data such as transaction history and account balance. This output data is the raw data collected.

[0290] Step 2:

[0291] The server encrypts the collected raw data. As an input, it receives the information data collected in Step 1. The server encrypts the data using the AES encryption algorithm and integrates and stores it in the database for each user. This output data is the encrypted and secure data.

[0292] Step 3:

[0293] The user logs into the system using a terminal. The user is required to enter a user ID, password, and multi-factor authentication information. The terminal sends this information to the server for authentication. Upon successful authentication, secure access rights are granted as output.

[0294] Step 4:

[0295] The server monitors the stored data in real time. Encrypted data from the database is used as input. The server applies anomaly detection algorithms to detect fraudulent transactions and access. If detected, an alert is generated as output and immediately sent to the terminal.

[0296] Step 5:

[0297] The user checks alerts from the server via their terminal and takes immediate action if necessary. The input is the alert information generated in step 4. The user reviews the alert content and takes action, such as canceling the process or reporting the information to the administrator. The output is the maintenance of a secure state after the action has been taken.

[0298] Step 6:

[0299] The server periodically backs up all the data in the database. It receives encrypted stored data as input. The server securely transfers this data to external storage and stores it there. As output, recoverable backup data is generated.

[0300] Step 7:

[0301] The server regularly delivers security education information to users. As input, it prepares the latest security information and best practices. By providing this information to users through their terminals, the server enables users to gain the knowledge to securely manage their own data. As output, the security awareness of users who receive the information improves.

[0302] (Application Example 1)

[0303] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart glasses 214 are referred to as a "terminal".

[0304] Modern users are required to efficiently and securely manage financial information distributed across multiple financial information sources. However, in previous systems, information collection and monitoring were insufficient, and the management burden on the users themselves was large. In addition, the risks of illegal transactions and information leakage were high, and measures to adequately avoid these were required. It is urgent to improve such a situation and provide an environment in which users can conduct financial transactions with confidence.

[0305] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0306] In this invention, the server includes means for securely collecting financial information using a communication protocol as a means for acquiring data from a financial information source, means for encoding the collected financial information and integrating it for each user, and means for collecting and managing the financial information of the user using a portable information terminal. As a result, users can centrally manage data from multiple financial information sources and strengthen the monitoring of illegal transactions.

[0307] A "financial information source" refers to an organization or system that provides data related to a user's financial activities.

[0308] A "communication protocol" defines the rules and procedures for data exchange between different systems.<了

[0309] "Encoding" means converting data using a specific algorithm to protect it from unauthorized access and eavesdropping by third parties.

[0310] "User" refers to a person or organization that uses the system, and in this invention, it refers to the entity that manages financial information.

[0311] A "portable information terminal" refers to a computing device that users can easily carry around, and includes smartphones and tablets.

[0312] "Fraudulent transactions" refer to financial transactions conducted against the user's will, and can be carried out through fraud or unauthorized access.

[0313] The system realizing this invention mainly consists of a server, a mobile information terminal, and communication means connecting them. The server connects to financial information sources, periodically collects financial data through communication protocols, encodes the collected data, and stores it securely. The server also utilizes anomaly transaction detection algorithms to analyze the collected data and identify signs of fraudulent transactions. This allows users to receive warnings in real time.

[0314] The personal digital assistant (PDCA) provides an interface for users to enter their authentication information and ensures secure access by utilizing multiple authentication factors. Users can use the PDCA to check their financial information and receive security education information provided by the system. The server is designed to ensure user convenience by balancing ease of operation with high security throughout the entire system.

[0315] For example, when a user uses a payment application on their mobile device while shopping on the weekend, the system collects the latest financial information in the background and provides the user with safety education information as needed.

[0316] An example of a prompt using a generative AI model is, "Please suggest a method to securely and efficiently manage users' financial data and detect abnormal transactions in real time."

[0317] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0318] Step 1:

[0319] The server connects to financial information sources and collects financial data using communication protocols. In this process, the server sends API requests to financial information sources to retrieve data such as the user's transaction history and account information. The input is the data obtained from the financial information source's API, and the output is the raw financial data received by the server.

[0320] Step 2:

[0321] The server encodes the acquired financial data. Specifically, the server transforms the data using an encryption algorithm (e.g., AES) and stores it securely. The input is raw financial data, and the output is encrypted data. This protects the data from unauthorized access.

[0322] Step 3:

[0323] Users log in to the system using a mobile device. The device receives the user's ID, password, and multi-factor authentication elements (e.g., biometric authentication or SMS code) and performs secure authentication. The input is the user's authentication information, and the output is the success or failure of the authentication.

[0324] Step 4:

[0325] The server analyzes encrypted data and identifies fraudulent transactions through an anomaly detection algorithm. Specifically, the anomaly detection algorithm builds a statistical model based on historical data and detects abnormal patterns. The input is decoded financial data, and the output is a list of transactions considered anomaly.

[0326] Step 5:

[0327] If the server detects a fraudulent transaction, it sends a real-time warning to the mobile device. The device then notifies the user of this warning, prompting them to take immediate action. The input is an abnormal transaction alert, and the output is a warning display on the device.

[0328] Step 6:

[0329] The server periodically generates security education information and distributes it to users via mobile devices. Specifically, it updates information on the latest cybersecurity threats and countermeasures to raise users' security awareness. The input is the periodic update information on the server, and the output is the display of educational content on the device.

[0330] 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.

[0331] This invention provides a system that, in addition to managing users' financial data, recognizes users' emotions and dynamically adjusts the interface based on those emotions. The system includes a server, a terminal, and an emotion engine, and the roles of each will be described below.

[0332] The server handles the traditional processes of collecting and managing financial data. Simultaneously, it analyzes user emotional data through an emotion engine and optimizes the user experience based on the results. It can also adjust security levels according to the user's emotional state.

[0333] The emotion engine analyzes user input information, such as voice and facial expressions, to identify the user's emotional state. The emotion engine then sends this information to a server, providing a foundation for the entire system to adapt based on emotions.

[0334] The device functions as a user interface, optimizing screen display and operation methods based on feedback from the emotion engine. For example, if the device determines that the user is experiencing stress, it will provide a simpler, stress-reducing interface. This simplified display allows the user to access information and perform actions more smoothly than usual.

[0335] Furthermore, the system provides personalized advice in real time based on insights gained from analyzing the user's emotions. For example, if the emotion engine detects high levels of anxiety in a user, the server immediately suggests financial advice or relaxation methods, and the terminal notifies the user of this.

[0336] In this way, embodiments of the present invention are capable of not only securely managing financial data but also improving the user experience based on user emotions and providing more personalized services. This increases user satisfaction and significantly enhances the usability of the system.

[0337] The following describes the processing flow.

[0338] Step 1:

[0339] The user logs into the system via their device. The user enters their ID and password and completes multi-factor authentication to obtain secure access.

[0340] Step 2:

[0341] The server retrieves the user's financial data through the financial institution's application programming interface. This data is stored on the server in an encrypted state.

[0342] Step 3:

[0343] The emotion engine acquires the user's facial expressions and voice data and analyzes their emotional state in real time. The results of this analysis are then sent to the server.

[0344] Step 4:

[0345] The server adjusts the interface and content according to the user's situation based on the emotional data received from the emotion engine. This adjustment is then transmitted to the device.

[0346] Step 5:

[0347] The terminal provides a user interface that adapts to the user's emotional state based on instructions from the server. For example, if it is determined that the user is experiencing high levels of stress, a simpler and easier-to-understand interface will be displayed.

[0348] Step 6:

[0349] The server comprehensively analyzes the user's financial and emotional data to generate personalized financial advice and security alerts. This information is then communicated to the user via their device.

[0350] Step 7:

[0351] The terminal displays advice and warnings sent from the server to the user and assists the user's actions as needed. This allows the user to take quick and appropriate action.

[0352] Step 8:

[0353] The server backs up data and analysis results and stores them in secure storage for future reference. This backup reduces the risk of data loss and improves system reliability.

[0354] (Example 2)

[0355] 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".

[0356] In recent years, financial services have demanded secure data management and improved user experience. However, challenges remain, including the risk of misuse and leakage of financial information, as well as the fact that uniform interfaces that do not consider users' emotional responses lower user satisfaction. Furthermore, there is a lack of dynamic service delivery that responds to emotions, making it difficult to provide services that meet the needs of individual users.

[0357] 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.

[0358] In this invention, the server includes means for securely collecting financial information, means for dynamically adjusting the display interface and operating methods based on the user's emotions, and means for generating and notifying appropriate financial advice according to the user's emotional state. This enables the secure management of financial information and personalized services that are tailored to the user's emotional needs.

[0359] "Financial institutions" refer to organizations and institutions that provide financial services, such as banks and securities companies.

[0360] An "application programming interface" refers to a set of conventions and tools that enable communication between different software applications.

[0361] "Financial information" refers to data about an individual's or organization's financial situation, such as bank account balances, transaction history, and spending patterns.

[0362] "Encryption" refers to the process of protecting data by encoding it using a specific algorithm.

[0363] "Users" refer to individuals or organizations that use a particular system or service.

[0364] "Authentication factors" are identifying information used to grant access to a system, and include passwords and biometric information.

[0365] "Economic activity" refers to the trading of assets and services and other financial activities carried out by individuals or organizations.

[0366] "Backup storage" refers to the process of creating copies of the same information and storing them in a separate location to prevent data loss.

[0367] "Security education" refers to educational activities aimed at providing users with knowledge and measures related to information security and raising their awareness.

[0368] "Emotions" refer to an individual's inner feelings or state of being, such as joy, sadness, or anger.

[0369] An "interface" refers to the screen display or means of operation that serves as a window for a user to interact with a system or device.

[0370] "Advice" refers to suggestions or instructions that are offered based on the situation or circumstances.

[0371] A "warning" refers to a notification intended to draw attention to a specific risk or anomaly.

[0372] The system of the present invention provides an advanced user experience that integrates financial data management and user emotion recognition. The following describes specific implementations of this system.

[0373] The server securely collects and manages financial information, integrating it into user-specific databases. This utilizes technologies that protect and make the information accessible using traditional database management systems and application programming interfaces (APIs). The server also analyzes data received from the emotion engine to generate insights for optimizing the user experience. Based on these insights, the system's security level is adjusted as needed.

[0374] The emotion engine utilizes hardware and software to analyze emotions from the user's voice and facial expressions. Specifically, it processes data acquired using cameras and microphones with machine learning models to estimate the user's emotional state. This emotional information is transmitted to the server in real time, forming the foundation for the entire system to provide services tailored to the user's emotional state.

[0375] The device provides an interface that directly interacts with the user. Based on feedback from the emotion engine, it dynamically changes the displayed content and operation methods to provide a more comfortable user experience. If the device detects that the user is experiencing stress, it automatically adjusts to an easier-to-use interface to reduce the user's burden.

[0376] As a concrete example, if the emotion engine detects that a user is stressed while trading stocks, the server immediately generates financial advice and provides a message through the terminal stating, "We recommend that you calmly analyze the situation and check for additional information if necessary." This allows the user to make decisions while remaining emotionally calm.

[0377] An example of a prompt message is: "Based on the analysis of the user's facial expressions and voice, the user is experiencing high levels of stress. How should the system adjust the interface and provide feedback to the user in this situation?" Thus, the present invention aims to improve the user experience from both the perspectives of financial information management and sentiment analysis.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The server collects financial information through the application programming interface of financial institutions. This information includes user transaction history and account balances. Input is data from financial institutions, and output is organized financial information. The server ensures security by encrypting the received information and storing it in a database. Specifically, it periodically calls the API to retrieve the latest data.

[0381] Step 2:

[0382] The emotion engine receives user audio and video data from the device. Inputs include the user's real-time voice and facial expressions. The emotion engine analyzes this data and evaluates the user's emotional state. Data processing is performed using an emotion analysis algorithm, and the output is the evaluation result of the emotional state. This information is sent to the server and stored as the user's emotional foundational data. Specific operations include acquiring data using speech recognition and facial expression detection technologies and inputting it into the model.

[0383] Step 3:

[0384] The server integrates financial and emotional data for comprehensive analysis. Inputs include financial information and emotional state data. Data processing involves algorithmic operation to correlate this information and identify user behavior patterns and needs; the output is a personalized user profile. Based on continuous analysis, it prepares appropriate advice and interface adjustments. Specifically, it uses machine learning models to analyze the dataset and extract insights.

[0385] Step 4:

[0386] The terminal receives results from the server and adjusts the user interface. Input is the analysis results from the server, and output is the adjusted display screen and operation method. Based on the user's state, the terminal changes the interface to reduce stress and provides voice navigation and guidance as needed. Specific actions include simplifying the graphic display and rearranging the layout to make important operation buttons more prominent.

[0387] Step 5:

[0388] The server generates appropriate financial advice based on user behavior and sentiment analysis. The input is integrated user data, and the output is personalized advice. The generating AI model generates future recommended actions and risk warnings based on historical data. This information is sent to the terminal in the form of prompts. Specifically, this involves inputting data into a predictive algorithm and sending the generated text to the user.

[0389] (Application Example 2)

[0390] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0391] While existing financial data management systems are effective in securely managing users' financial data, they struggle to provide more personalized support and optimized user interfaces based on users' emotional states. Furthermore, there is a need to adjust security levels according to users' emotional states and to create a comfortable user experience. The challenge lies in improving user satisfaction and reducing stress.

[0392] 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.

[0393] In this invention, the server includes means for securely collecting financial data using an application programming interface as a means for acquiring data from financial institutions, means for recognizing the emotional state of the user, and means for dynamically adjusting the user interface based on the emotional state. This enables the secure management of the user's financial data, as well as the optimization of the interface in response to emotions, thereby improving user satisfaction and providing a personalized user experience.

[0394] "Data acquisition means" refers to a function that securely acquires financial data using the application programming interface of a financial institution.

[0395] "Encryption methods" are technologies used to protect acquired financial data and integrate it for each user.

[0396] "Authentication method" refers to the process of verifying the identity of a user using multi-factor authentication.

[0397] An "anomaly detection system" is a system that identifies fraudulent or abnormal transactions in real time and generates warnings.

[0398] A "backup method" is a procedure for regularly saving data and making it possible to restore it as needed.

[0399] A "security education tool" is a system for providing users with knowledge about information security.

[0400] "Emotion recognition means" refers to technology that analyzes voice and facial expressions to identify the emotional state of a user.

[0401] An "interface adjustment mechanism" is a system that dynamically changes the displayed content and operating procedures according to the user's current situation.

[0402] "Personalized advice tools" are functions that provide specific advice and suggestions based on the user's emotions and circumstances.

[0403] The system implementing this invention primarily consists of a server, a terminal, and an emotion recognition engine. The server is responsible for collecting and integrating financial data, and also manages data necessary to recognize the emotional state of the user. The server obtains financial information using APIs from financial institutions, encrypts it, and then organizes and integrates it for each user. Furthermore, the server dynamically adjusts the interface and service provision based on the results of the user's emotion recognition.

[0404] The emotion recognition engine analyzes the user's voice and facial expression data acquired by the device to identify the user's emotional state. Specifically, it utilizes speech recognition and image processing technologies to determine whether the user is experiencing stress. The emotional data generated by the emotion recognition engine is sent to a server and used for further analysis and interface optimization.

[0405] The terminal functions as an interface with the user, optimizing screen displays and operation methods based on instructions provided by the server. For example, if the terminal determines that the user is stressed, it reduces the user's operational burden by displaying a simpler interface that responds to their emotions. Conversely, if the user is relaxed, it can display detailed financial information comprehensively, providing the user with deeper insights.

[0406] Furthermore, the generative AI model uses the user's emotional state and financial data to provide personalized advice and suggestions in real time. This AI model has the ability to provide more optimal advice by analyzing past data and trends.

[0407] As a concrete example, when a user uses an electronic wallet application through their device, the system analyzes their facial expressions and voice for the day and presents the interface best suited to their emotions at that time. For instance, if the system detects a visually tired expression on a weekday evening, it can alleviate fatigue by providing the user with key functions in a simple quick-access mode.

[0408] An example of a prompt for a generated AI model is: "Generate an AI model that adjusts the interface based on the user's emotional state and provides appropriate advice where reconfirmation is needed."

[0409] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0410] Step 1:

[0411] The device acquires the user's voice and facial expressions through its camera and microphone. This data serves as input to identify the user's emotional state. Voice data is converted to text using speech recognition software, and image data is categorized into emotional categories using a facial recognition algorithm.

[0412] Step 2:

[0413] The server receives audio and facial expression data from the emotion recognition engine and analyzes it using an emotion identification algorithm. This process outputs the user's emotional state as "stressed," "relaxed," "concentrated," etc. The identified emotion is then used as a criterion for subsequent interface adjustments.

[0414] Step 3:

[0415] The server dynamically adjusts the user interface based on the identified emotional state. For example, if the server identifies that the user is stressed, it translates the data into a command to "provide a simple interface" and sends it to the terminal. When selecting or reconfiguring the user interface, a generative AI model presents appropriate scenarios.

[0416] Step 4:

[0417] The terminal dynamically changes the user interface based on instructions from the server. This operation provides the user with a simple and intuitive display, reducing the burden of operation. For example, it can highlight only important financial information and omit other details.

[0418] Step 5:

[0419] When a user performs a transaction or operation through the user interface, the terminal sends the details to the server. This data is processed through the financial institution's API, and the security of the transaction is verified. Transaction information is properly encrypted in the backend and stored in a financial database.

[0420] Step 6:

[0421] Based on the user's transaction and behavioral history, the server uses a generative AI model to create personalized advice and suggestions. The generated content is structured as something like "Investment advice perfect for a relaxing evening" and is ultimately presented to the user through their device.

[0422] This entire process is designed to provide a more personalized user experience, allowing users to conduct financial transactions in a relaxed state.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] [Third Embodiment]

[0427] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0428] 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.

[0429] 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).

[0430] 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.

[0431] 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.

[0432] 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).

[0433] 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.

[0434] 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.

[0435] 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.

[0436] 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.

[0437] 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.

[0438] 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".

[0439] This invention provides a system for securely collecting and centrally managing account data held by a user across multiple financial institutions. Specific embodiments of the system, including servers, terminals, and data processing between them, will be described.

[0440] The server securely utilizes the financial institution's application programming interface to periodically collect necessary data from user accounts. The server encrypts the collected data on the spot and stores it in a database, associated with each user's identification information. This significantly reduces the risk of data theft or leakage.

[0441] The terminal is used when users log in to the system. In addition to their usual ID and password, users must go through multi-factor authentication. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, to prevent unauthorized access.

[0442] The server continuously monitors the stored data and, upon detecting any unusual transactions, immediately sends a real-time alert to the terminal. This alert allows users to take swift action.

[0443] Furthermore, the server regularly backs up all data. This backup data is stored on secure external storage to enable rapid restoration in the event of a disaster or data loss.

[0444] Furthermore, the server provides users with ongoing security education. For example, information on best practices for data management and advice on countermeasures against the latest security threats are delivered to users through their devices.

[0445] As a concrete example, consider a case where a user wants to check their transaction history from their financial institution. The user goes through multi-factor authentication on their device, and the server decrypts the transaction history, which is stored in an encrypted state, based on the user's request. Next, the device displays the decrypted data to the user, allowing the user to check the detailed transaction history.

[0446] In this way, the present invention can securely and efficiently manage users' financial data, improving its convenience while protecting privacy.

[0447] The following describes the processing flow.

[0448] Step 1:

[0449] The user logs into the system using a terminal. The user first enters their ID and password. The terminal receives this information and sends it to the server.

[0450] Step 2:

[0451] The server compares the received ID and password with the authentication database. If authentication is successful, the server sends a multi-factor authentication request to the terminal.

[0452] Step 3:

[0453] The user completes the multi-factor authentication requested on the device. This uses biometric authentication or a verification code sent via SMS. The device then sends the result to the server.

[0454] Step 4:

[0455] The server verifies the results of multi-factor authentication and, if successful, initiates the user's session. This grants the user access to the system.

[0456] Step 5:

[0457] The server retrieves user account data through the financial institution's application programming interface. This is done regularly and securely.

[0458] Step 6:

[0459] The acquired data is immediately encrypted on the server and stored in the database in a format recognizable to each user.

[0460] Step 7:

[0461] The server analyzes the stored data in real time and applies an anomaly detection algorithm if an abnormal transaction occurs.

[0462] Step 8:

[0463] When an unusual transaction is detected, the server immediately sends a real-time alert to the terminal. The user can receive this alert and view the details.

[0464] Step 9:

[0465] The server regularly backs up all data and stores it on secure external storage. This allows for quick recovery in the event of data loss.

[0466] Step 10:

[0467] The server regularly provides users with security education information and content on best practices. Users can receive this information through their devices and improve their security awareness.

[0468] (Example 1)

[0469] 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."

[0470] Information agencies are required to manage user data securely and efficiently, while protecting privacy and enhancing convenience. However, conventional systems are prone to security risks during data collection and storage, and lack sufficient timeliness and reliability in anomaly detection and data recovery.

[0471] 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.

[0472] In this invention, the server includes means for securely collecting information data using a communication interface as a means for acquiring data from an information agency, means for transforming the collected information data and integrating it for each user, and means for using multiple authentication factors when authenticating users. This enables secure collection, management, anomaly detection, and rapid recovery of information data.

[0473] An "information agency" is an organization or system that manages information data and provides necessary data securely.

[0474] A "communication interface" is a means of connection that allows different systems or software to exchange information with each other.

[0475] "Information data" refers to the collection of all data related to accounts and transactions held by a user.

[0476] A "user" is an individual or organization that uses this system to manage, view, or manipulate information data.

[0477] "Anomaly detection" is the process of identifying fraudulent or unexpected behavior that deviates from normal usage patterns in real time.

[0478] A "warning" is a notification intended to promptly inform users when an anomaly or risk is detected.

[0479] "Record keeping" refers to the act of regularly saving informational data in a secure location for future reference or recovery.

[0480] "Security education information" refers to the knowledge and information on the latest security threats that users need to manage their information data securely.

[0481] The system in this invention specifically demonstrates a method for safely and efficiently collecting, managing, and providing user information data. The implementation of this system is described below.

[0482] The server functions as the central hub of this system, securely collecting data from intelligence agencies using communication interfaces. The server encrypts the collected data and stores it in a database for each user. Security protocols such as HTTPS and AES (Advanced Encryption Standard) are used in this process.

[0483] The terminal provides users with a means to access the system and view and manipulate information data. Users can log in through the terminal using their ID, password, and multi-factor authentication to securely use the system. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, which prevents unauthorized access.

[0484] The server also has the ability to monitor stored data in real time and immediately generate and send alerts to terminals if unusual transactions or unauthorized access are detected. This alert function allows users to respond quickly to abnormal situations.

[0485] Furthermore, the server is configured to regularly back up all data in the database, allowing for rapid restoration of the stored data in the event of a disaster or data loss. The backup data is securely stored on secure external storage.

[0486] Furthermore, the server provides users with security education information through their terminals. This includes best practices for data management and information on the latest security threats. This ensures that users can always manage their information data securely based on the most up-to-date information.

[0487] As a concrete example, consider the procedure for a user to check their transaction history. The user logs into their device and goes through multi-factor authentication. Next, the server decrypts the encrypted transaction data and sends it back to the device. The user can then view the detailed transaction history on the device screen and export the data if necessary.

[0488] An example of a prompt sentence to be input into the generating AI model would be, "Please provide detailed instructions on how to securely manage financial data." This system would enable users to manage their data securely and efficiently.

[0489] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0490] Step 1:

[0491] The server securely collects data from intelligence agencies using a communication interface. It receives authentication information and necessary API keys for each user as input. The server uses this information to send HTTP requests to the API, receiving data such as transaction history and account balances. This output data is the raw data collected.

[0492] Step 2:

[0493] The server encrypts the collected raw data. It receives the information data collected in step 1 as input. The server encrypts the data using the AES encryption algorithm and stores it in a database, integrating it for each user. This output data becomes encrypted and secure.

[0494] Step 3:

[0495] The user logs into the system using a terminal. The user is required to enter a user ID, password, and multi-factor authentication information. The terminal sends this information to the server for authentication. Upon successful authentication, secure access rights are granted as output.

[0496] Step 4:

[0497] The server monitors the stored data in real time. Encrypted data from the database is used as input. The server applies anomaly detection algorithms to detect fraudulent transactions and access. If detected, an alert is generated as output and immediately sent to the terminal.

[0498] Step 5:

[0499] The user checks alerts from the server via their terminal and takes immediate action if necessary. The input is the alert information generated in step 4. The user reviews the alert content and takes action, such as canceling the process or reporting the information to the administrator. The output is the maintenance of a secure state after the action has been taken.

[0500] Step 6:

[0501] The server periodically backs up all the data in the database. It receives encrypted stored data as input. The server securely transfers this data to external storage and stores it there. As output, recoverable backup data is generated.

[0502] Step 7:

[0503] The server regularly delivers security education information to users. As input, it prepares the latest security information and best practices. By providing this information to users through their terminals, the server enables users to gain the knowledge to securely manage their own data. As output, the security awareness of users who receive the information improves.

[0504] (Application Example 1)

[0505] 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."

[0506] Modern users are required to efficiently and securely manage financial information dispersed across multiple financial information sources. However, existing systems have been insufficient in information collection and monitoring, resulting in a heavy management burden on users. Furthermore, the risk of fraudulent transactions and information leaks is high, and measures to adequately avoid these are needed. Improving this situation and providing an environment in which users can conduct financial transactions with peace of mind is an urgent task.

[0507] 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.

[0508] In this invention, the server includes means for securely collecting financial information using a communication protocol as a means for acquiring data from financial information sources, means for encoding the collected financial information and integrating it for each user, and means for collecting and managing users' financial information using a mobile information terminal. This enables users to centrally manage data from multiple financial information sources and strengthen monitoring of fraudulent transactions.

[0509] A "financial information source" refers to an organization or system that provides data related to users' financial activities.

[0510] A "communication protocol" is a set of rules and procedures that define how data is exchanged between different systems.

[0511] "Encoding" refers to the process of transforming data using specific algorithms to protect it from unauthorized access and eavesdropping by third parties.

[0512] "User" refers to a person or organization that uses the system, and in this invention, it refers to the entity that manages financial information.

[0513] A "portable information terminal" refers to a computing device that users can easily carry around, and includes smartphones and tablets.

[0514] "Fraudulent transactions" refer to financial transactions conducted against the user's will, and can be carried out through fraud or unauthorized access.

[0515] The system realizing this invention mainly consists of a server, a mobile information terminal, and communication means connecting them. The server connects to financial information sources, periodically collects financial data through communication protocols, encodes the collected data, and stores it securely. The server also utilizes anomaly transaction detection algorithms to analyze the collected data and identify signs of fraudulent transactions. This allows users to receive warnings in real time.

[0516] The personal digital assistant (PDCA) provides an interface for users to enter their authentication information and ensures secure access by utilizing multiple authentication factors. Users can use the PDCA to check their financial information and receive security education information provided by the system. The server is designed to ensure user convenience by balancing ease of operation with high security throughout the entire system.

[0517] For example, when a user uses a payment application on their mobile device while shopping on the weekend, the system collects the latest financial information in the background and provides the user with safety education information as needed.

[0518] An example of a prompt using a generative AI model is, "Please suggest a method to securely and efficiently manage users' financial data and detect abnormal transactions in real time."

[0519] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0520] Step 1:

[0521] The server connects to financial information sources and collects financial data using communication protocols. In this process, the server sends API requests to financial information sources to retrieve data such as the user's transaction history and account information. The input is the data obtained from the financial information source's API, and the output is the raw financial data received by the server.

[0522] Step 2:

[0523] The server encodes the acquired financial data. Specifically, the server transforms the data using an encryption algorithm (e.g., AES) and stores it securely. The input is raw financial data, and the output is encrypted data. This protects the data from unauthorized access.

[0524] Step 3:

[0525] Users log in to the system using a mobile device. The device receives the user's ID, password, and multi-factor authentication elements (e.g., biometric authentication or SMS code) and performs secure authentication. The input is the user's authentication information, and the output is the success or failure of the authentication.

[0526] Step 4:

[0527] The server analyzes encrypted data and identifies fraudulent transactions through an anomaly detection algorithm. Specifically, the anomaly detection algorithm builds a statistical model based on historical data and detects abnormal patterns. The input is decoded financial data, and the output is a list of transactions considered anomaly.

[0528] Step 5:

[0529] If the server detects a fraudulent transaction, it sends a real-time warning to the mobile device. The device then notifies the user of this warning, prompting them to take immediate action. The input is an abnormal transaction alert, and the output is a warning display on the device.

[0530] Step 6:

[0531] The server periodically generates security education information and distributes it to users via mobile devices. Specifically, it updates information on the latest cybersecurity threats and countermeasures to raise users' security awareness. The input is the periodic update information on the server, and the output is the display of educational content on the device.

[0532] 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.

[0533] This invention provides a system that, in addition to managing users' financial data, recognizes users' emotions and dynamically adjusts the interface based on those emotions. The system includes a server, a terminal, and an emotion engine, and the roles of each will be described below.

[0534] The server handles the traditional processes of collecting and managing financial data. Simultaneously, it analyzes user emotional data through an emotion engine and optimizes the user experience based on the results. It can also adjust security levels according to the user's emotional state.

[0535] The emotion engine analyzes user input information, such as voice and facial expressions, to identify the user's emotional state. The emotion engine then sends this information to a server, providing a foundation for the entire system to adapt based on emotions.

[0536] The device functions as a user interface, optimizing screen display and operation methods based on feedback from the emotion engine. For example, if the device determines that the user is experiencing stress, it will provide a simpler, stress-reducing interface. This simplified display allows the user to access information and perform actions more smoothly than usual.

[0537] Furthermore, the system provides personalized advice in real time based on insights gained from analyzing the user's emotions. For example, if the emotion engine detects high levels of anxiety in a user, the server immediately suggests financial advice or relaxation methods, and the terminal notifies the user of this.

[0538] In this way, embodiments of the present invention are capable of not only securely managing financial data but also improving the user experience based on user emotions and providing more personalized services. This increases user satisfaction and significantly enhances the usability of the system.

[0539] The following describes the processing flow.

[0540] Step 1:

[0541] The user logs into the system via their device. The user enters their ID and password and completes multi-factor authentication to obtain secure access.

[0542] Step 2:

[0543] The server retrieves the user's financial data through the financial institution's application programming interface. This data is stored on the server in an encrypted state.

[0544] Step 3:

[0545] The emotion engine acquires the user's facial expressions and voice data and analyzes their emotional state in real time. The results of this analysis are then sent to the server.

[0546] Step 4:

[0547] The server adjusts the interface and content according to the user's situation based on the emotional data received from the emotion engine. This adjustment is then transmitted to the device.

[0548] Step 5:

[0549] The terminal provides a user interface that adapts to the user's emotional state based on instructions from the server. For example, if it is determined that the user is experiencing high levels of stress, a simpler and easier-to-understand interface will be displayed.

[0550] Step 6:

[0551] The server comprehensively analyzes the user's financial and emotional data to generate personalized financial advice and security alerts. This information is then communicated to the user via their device.

[0552] Step 7:

[0553] The terminal displays advice and warnings sent from the server to the user and assists the user's actions as needed. This allows the user to take quick and appropriate action.

[0554] Step 8:

[0555] The server backs up data and analysis results and stores them in secure storage for future reference. This backup reduces the risk of data loss and improves system reliability.

[0556] (Example 2)

[0557] 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."

[0558] In recent years, financial services have demanded secure data management and improved user experience. However, challenges remain, including the risk of misuse and leakage of financial information, as well as the fact that uniform interfaces that do not consider users' emotional responses lower user satisfaction. Furthermore, there is a lack of dynamic service delivery that responds to emotions, making it difficult to provide services that meet the needs of individual users.

[0559] 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.

[0560] In this invention, the server includes means for securely collecting financial information, means for dynamically adjusting the display interface and operating methods based on the user's emotions, and means for generating and notifying appropriate financial advice according to the user's emotional state. This enables the secure management of financial information and personalized services that are tailored to the user's emotional needs.

[0561] "Financial institutions" refer to organizations and institutions that provide financial services, such as banks and securities companies.

[0562] An "application programming interface" refers to a set of conventions and tools that enable communication between different software applications.

[0563] "Financial information" refers to data about an individual's or organization's financial situation, such as bank account balances, transaction history, and spending patterns.

[0564] "Encryption" refers to the process of protecting data by encoding it using a specific algorithm.

[0565] "Users" refer to individuals or organizations that use a particular system or service.

[0566] "Authentication factors" are identifying information used to grant access to a system, and include passwords and biometric information.

[0567] "Economic activity" refers to the trading of assets and services and other financial activities carried out by individuals or organizations.

[0568] "Backup storage" refers to the process of creating copies of the same information and storing them in a separate location to prevent data loss.

[0569] "Security education" refers to educational activities aimed at providing users with knowledge and measures related to information security and raising their awareness.

[0570] "Emotions" refer to an individual's inner feelings or state of being, such as joy, sadness, or anger.

[0571] An "interface" refers to the screen display or means of operation that serves as a window for a user to interact with a system or device.

[0572] "Advice" refers to suggestions or instructions that are offered based on the situation or circumstances.

[0573] A "warning" refers to a notification intended to draw attention to a specific risk or anomaly.

[0574] The system of the present invention provides an advanced user experience that integrates financial data management and user emotion recognition. The following describes specific implementations of this system.

[0575] The server securely collects and manages financial information, integrating it into user-specific databases. This utilizes technologies that protect and make the information accessible using traditional database management systems and application programming interfaces (APIs). The server also analyzes data received from the emotion engine to generate insights for optimizing the user experience. Based on these insights, the system's security level is adjusted as needed.

[0576] The emotion engine utilizes hardware and software to analyze emotions from the user's voice and facial expressions. Specifically, it processes data acquired using cameras and microphones with machine learning models to estimate the user's emotional state. This emotional information is transmitted to the server in real time, forming the foundation for the entire system to provide services tailored to the user's emotional state.

[0577] The device provides an interface that directly interacts with the user. Based on feedback from the emotion engine, it dynamically changes the displayed content and operation methods to provide a more comfortable user experience. If the device detects that the user is experiencing stress, it automatically adjusts to an easier-to-use interface to reduce the user's burden.

[0578] As a concrete example, if the emotion engine detects that a user is stressed while trading stocks, the server immediately generates financial advice and provides a message through the terminal stating, "We recommend that you calmly analyze the situation and check for additional information if necessary." This allows the user to make decisions while remaining emotionally calm.

[0579] An example of a prompt message is: "Based on the analysis of the user's facial expressions and voice, the user is experiencing high levels of stress. How should the system adjust the interface and provide feedback to the user in this situation?" Thus, the present invention aims to improve the user experience from both the perspectives of financial information management and sentiment analysis.

[0580] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0581] Step 1:

[0582] The server collects financial information through the application programming interface of financial institutions. This information includes user transaction history and account balances. Input is data from financial institutions, and output is organized financial information. The server ensures security by encrypting the received information and storing it in a database. Specifically, it periodically calls the API to retrieve the latest data.

[0583] Step 2:

[0584] The emotion engine receives user audio and video data from the device. Inputs include the user's real-time voice and facial expressions. The emotion engine analyzes this data and evaluates the user's emotional state. Data processing is performed using an emotion analysis algorithm, and the output is the evaluation result of the emotional state. This information is sent to the server and stored as the user's emotional foundational data. Specific operations include acquiring data using speech recognition and facial expression detection technologies and inputting it into the model.

[0585] Step 3:

[0586] The server integrates financial and emotional data for comprehensive analysis. Inputs include financial information and emotional state data. Data processing involves algorithmic operation to correlate this information and identify user behavior patterns and needs; the output is a personalized user profile. Based on continuous analysis, it prepares appropriate advice and interface adjustments. Specifically, it uses machine learning models to analyze the dataset and extract insights.

[0587] Step 4:

[0588] The terminal receives results from the server and adjusts the user interface. Input is the analysis results from the server, and output is the adjusted display screen and operation method. Based on the user's state, the terminal changes the interface to reduce stress and provides voice navigation and guidance as needed. Specific actions include simplifying the graphic display and rearranging the layout to make important operation buttons more prominent.

[0589] Step 5:

[0590] The server generates appropriate financial advice based on user behavior and sentiment analysis. The input is integrated user data, and the output is personalized advice. The generating AI model generates future recommended actions and risk warnings based on historical data. This information is sent to the terminal in the form of prompts. Specifically, this involves inputting data into a predictive algorithm and sending the generated text to the user.

[0591] (Application Example 2)

[0592] 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."

[0593] While existing financial data management systems are effective in securely managing users' financial data, they struggle to provide more personalized support and optimized user interfaces based on users' emotional states. Furthermore, there is a need to adjust security levels according to users' emotional states and to create a comfortable user experience. The challenge lies in improving user satisfaction and reducing stress.

[0594] 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.

[0595] In this invention, the server includes means for securely collecting financial data using an application programming interface as a means for acquiring data from financial institutions, means for recognizing the emotional state of the user, and means for dynamically adjusting the user interface based on the emotional state. This enables the secure management of the user's financial data, as well as the optimization of the interface in response to emotions, thereby improving user satisfaction and providing a personalized user experience.

[0596] "Data acquisition means" refers to a function that securely acquires financial data using the application programming interface of a financial institution.

[0597] "Encryption methods" are technologies used to protect acquired financial data and integrate it for each user.

[0598] "Authentication method" refers to the process of verifying the identity of a user using multi-factor authentication.

[0599] An "anomaly detection system" is a system that identifies fraudulent or abnormal transactions in real time and generates warnings.

[0600] A "backup method" is a procedure for regularly saving data and making it possible to restore it as needed.

[0601] A "security education tool" is a system for providing users with knowledge about information security.

[0602] "Emotion recognition means" refers to technology that analyzes voice and facial expressions to identify the emotional state of a user.

[0603] An "interface adjustment mechanism" is a system that dynamically changes the displayed content and operating procedures according to the user's current situation.

[0604] "Personalized advice tools" are functions that provide specific advice and suggestions based on the user's emotions and circumstances.

[0605] The system implementing this invention primarily consists of a server, a terminal, and an emotion recognition engine. The server is responsible for collecting and integrating financial data, and also manages data necessary to recognize the emotional state of the user. The server obtains financial information using APIs from financial institutions, encrypts it, and then organizes and integrates it for each user. Furthermore, the server dynamically adjusts the interface and service provision based on the results of the user's emotion recognition.

[0606] The emotion recognition engine analyzes the user's voice and facial expression data acquired by the device to identify the user's emotional state. Specifically, it utilizes speech recognition and image processing technologies to determine whether the user is experiencing stress. The emotional data generated by the emotion recognition engine is sent to a server and used for further analysis and interface optimization.

[0607] The terminal functions as an interface with the user, optimizing screen displays and operation methods based on instructions provided by the server. For example, if the terminal determines that the user is stressed, it reduces the user's operational burden by displaying a simpler interface that responds to their emotions. Conversely, if the user is relaxed, it can display detailed financial information comprehensively, providing the user with deeper insights.

[0608] Furthermore, the generative AI model uses the user's emotional state and financial data to provide personalized advice and suggestions in real time. This AI model has the ability to provide more optimal advice by analyzing past data and trends.

[0609] As a concrete example, when a user uses an electronic wallet application through their device, the system analyzes their facial expressions and voice for the day and presents the interface best suited to their emotions at that time. For instance, if the system detects a visually tired expression on a weekday evening, it can alleviate fatigue by providing the user with key functions in a simple quick-access mode.

[0610] An example of a prompt for a generated AI model is: "Generate an AI model that adjusts the interface based on the user's emotional state and provides appropriate advice where reconfirmation is needed."

[0611] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0612] Step 1:

[0613] The device acquires the user's voice and facial expressions through its camera and microphone. This data serves as input to identify the user's emotional state. Voice data is converted to text using speech recognition software, and image data is categorized into emotional categories using a facial recognition algorithm.

[0614] Step 2:

[0615] The server receives audio and facial expression data from the emotion recognition engine and analyzes it using an emotion identification algorithm. This process outputs the user's emotional state as "stressed," "relaxed," "concentrated," etc. The identified emotion is then used as a criterion for subsequent interface adjustments.

[0616] Step 3:

[0617] The server dynamically adjusts the user interface based on the identified emotional state. For example, if the server identifies that the user is stressed, it translates the data into a command to "provide a simple interface" and sends it to the terminal. When selecting or reconfiguring the user interface, a generative AI model presents appropriate scenarios.

[0618] Step 4:

[0619] The terminal dynamically changes the user interface based on instructions from the server. This operation provides the user with a simple and intuitive display, reducing the burden of operation. For example, it can highlight only important financial information and omit other details.

[0620] Step 5:

[0621] When a user performs a transaction or operation through the user interface, the terminal sends the details to the server. This data is processed through the financial institution's API, and the security of the transaction is verified. Transaction information is properly encrypted in the backend and stored in a financial database.

[0622] Step 6:

[0623] Based on the user's transaction and behavioral history, the server uses a generative AI model to create personalized advice and suggestions. The generated content is structured as something like "Investment advice perfect for a relaxing evening" and is ultimately presented to the user through their device.

[0624] This entire process is designed to provide a more personalized user experience, allowing users to conduct financial transactions in a relaxed state.

[0625] 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.

[0626] 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.

[0627] 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.

[0628] [Fourth Embodiment]

[0629] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0630] 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.

[0631] 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).

[0632] 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.

[0633] 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.

[0634] 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).

[0635] 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.

[0636] 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.

[0637] 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.

[0638] 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.

[0639] 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.

[0640] 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.

[0641] 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".

[0642] This invention provides a system for securely collecting and centrally managing account data held by a user across multiple financial institutions. Specific embodiments of the system, including servers, terminals, and data processing between them, will be described.

[0643] The server securely utilizes the financial institution's application programming interface to periodically collect necessary data from user accounts. The server encrypts the collected data on the spot and stores it in a database, associated with each user's identification information. This significantly reduces the risk of data theft or leakage.

[0644] The terminal is used when users log in to the system. In addition to their usual ID and password, users must go through multi-factor authentication. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, to prevent unauthorized access.

[0645] The server continuously monitors the stored data and, upon detecting any unusual transactions, immediately sends a real-time alert to the terminal. This alert allows users to take swift action.

[0646] Furthermore, the server regularly backs up all data. This backup data is stored on secure external storage to enable rapid restoration in the event of a disaster or data loss.

[0647] Furthermore, the server provides users with ongoing security education. For example, information on best practices for data management and advice on countermeasures against the latest security threats are delivered to users through their devices.

[0648] As a concrete example, consider a case where a user wants to check their transaction history from their financial institution. The user goes through multi-factor authentication on their device, and the server decrypts the transaction history, which is stored in an encrypted state, based on the user's request. Next, the device displays the decrypted data to the user, allowing the user to check the detailed transaction history.

[0649] In this way, the present invention can securely and efficiently manage users' financial data, improving its convenience while protecting privacy.

[0650] The following describes the processing flow.

[0651] Step 1:

[0652] The user logs into the system using a terminal. The user first enters their ID and password. The terminal receives this information and sends it to the server.

[0653] Step 2:

[0654] The server compares the received ID and password with the authentication database. If authentication is successful, the server sends a multi-factor authentication request to the terminal.

[0655] Step 3:

[0656] The user completes the multi-factor authentication requested on the device. This uses biometric authentication or a verification code sent via SMS. The device then sends the result to the server.

[0657] Step 4:

[0658] The server verifies the results of multi-factor authentication and, if successful, initiates the user's session. This grants the user access to the system.

[0659] Step 5:

[0660] The server retrieves user account data through the financial institution's application programming interface. This is done regularly and securely.

[0661] Step 6:

[0662] The acquired data is immediately encrypted on the server and stored in the database in a format recognizable to each user.

[0663] Step 7:

[0664] The server analyzes the stored data in real time and applies an anomaly detection algorithm if an abnormal transaction occurs.

[0665] Step 8:

[0666] When an unusual transaction is detected, the server immediately sends a real-time alert to the terminal. The user can receive this alert and view the details.

[0667] Step 9:

[0668] The server regularly backs up all data and stores it on secure external storage. This allows for quick recovery in the event of data loss.

[0669] Step 10:

[0670] The server regularly provides users with security education information and content on best practices. Users can receive this information through their devices and improve their security awareness.

[0671] (Example 1)

[0672] 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".

[0673] Information agencies are required to manage user data securely and efficiently, while protecting privacy and enhancing convenience. However, conventional systems are prone to security risks during data collection and storage, and lack sufficient timeliness and reliability in anomaly detection and data recovery.

[0674] 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.

[0675] In this invention, the server includes means for securely collecting information data using a communication interface as a means for acquiring data from an information agency, means for transforming the collected information data and integrating it for each user, and means for using multiple authentication factors when authenticating users. This enables secure collection, management, anomaly detection, and rapid recovery of information data.

[0676] An "information agency" is an organization or system that manages information data and provides necessary data securely.

[0677] A "communication interface" is a means of connection that allows different systems or software to exchange information with each other.

[0678] "Information data" refers to the collection of all data related to accounts and transactions held by a user.

[0679] A "user" is an individual or organization that uses this system to manage, view, or manipulate information data.

[0680] "Anomaly detection" is the process of identifying fraudulent or unexpected behavior that deviates from normal usage patterns in real time.

[0681] A "warning" is a notification intended to promptly inform users when an anomaly or risk is detected.

[0682] "Record keeping" refers to the act of regularly saving informational data in a secure location for future reference or recovery.

[0683] "Security education information" refers to the knowledge and information on the latest security threats that users need to manage their information data securely.

[0684] The system in this invention specifically demonstrates a method for safely and efficiently collecting, managing, and providing user information data. The implementation of this system is described below.

[0685] The server functions as the central hub of this system, securely collecting data from intelligence agencies using communication interfaces. The server encrypts the collected data and stores it in a database for each user. Security protocols such as HTTPS and AES (Advanced Encryption Standard) are used in this process.

[0686] The terminal provides users with a means to access the system and view and manipulate information data. Users can log in through the terminal using their ID, password, and multi-factor authentication to securely use the system. The terminal supports multiple authentication methods, including biometric authentication and SMS codes, which prevents unauthorized access.

[0687] The server also has the ability to monitor stored data in real time and immediately generate and send alerts to terminals if unusual transactions or unauthorized access are detected. This alert function allows users to respond quickly to abnormal situations.

[0688] Furthermore, the server is configured to regularly back up all data in the database, allowing for rapid restoration of the stored data in the event of a disaster or data loss. The backup data is securely stored on secure external storage.

[0689] Furthermore, the server provides users with security education information through their terminals. This includes best practices for data management and information on the latest security threats. This ensures that users can always manage their information data securely based on the most up-to-date information.

[0690] As a concrete example, consider the procedure for a user to check their transaction history. The user logs into their device and goes through multi-factor authentication. Next, the server decrypts the encrypted transaction data and sends it back to the device. The user can then view the detailed transaction history on the device screen and export the data if necessary.

[0691] An example of a prompt sentence to be input into the generating AI model would be, "Please provide detailed instructions on how to securely manage financial data." This system would enable users to manage their data securely and efficiently.

[0692] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0693] Step 1:

[0694] The server securely collects data from intelligence agencies using a communication interface. It receives authentication information and necessary API keys for each user as input. The server uses this information to send HTTP requests to the API, receiving data such as transaction history and account balances. This output data is the raw data collected.

[0695] Step 2:

[0696] The server encrypts the collected raw data. It receives the information data collected in step 1 as input. The server encrypts the data using the AES encryption algorithm and stores it in a database, integrating it for each user. This output data becomes encrypted and secure.

[0697] Step 3:

[0698] The user logs into the system using a terminal. The user is required to enter a user ID, password, and multi-factor authentication information. The terminal sends this information to the server for authentication. Upon successful authentication, secure access rights are granted as output.

[0699] Step 4:

[0700] The server monitors the stored data in real time. Encrypted data from the database is used as input. The server applies anomaly detection algorithms to detect fraudulent transactions and access. If detected, an alert is generated as output and immediately sent to the terminal.

[0701] Step 5:

[0702] The user checks alerts from the server via their terminal and takes immediate action if necessary. The input is the alert information generated in step 4. The user reviews the alert content and takes action, such as canceling the process or reporting the information to the administrator. The output is the maintenance of a secure state after the action has been taken.

[0703] Step 6:

[0704] The server periodically backs up all the data in the database. It receives encrypted stored data as input. The server securely transfers this data to external storage and stores it there. As output, recoverable backup data is generated.

[0705] Step 7:

[0706] The server regularly delivers security education information to users. As input, it prepares the latest security information and best practices. By providing this information to users through their terminals, the server enables users to gain the knowledge to securely manage their own data. As output, the security awareness of users who receive the information improves.

[0707] (Application Example 1)

[0708] 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".

[0709] Modern users are required to efficiently and securely manage financial information dispersed across multiple financial information sources. However, existing systems have been insufficient in information collection and monitoring, resulting in a heavy management burden on users. Furthermore, the risk of fraudulent transactions and information leaks is high, and measures to adequately avoid these are needed. Improving this situation and providing an environment in which users can conduct financial transactions with peace of mind is an urgent task.

[0710] 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.

[0711] In this invention, the server includes means for securely collecting financial information using a communication protocol as a means for acquiring data from financial information sources, means for encoding the collected financial information and integrating it for each user, and means for collecting and managing users' financial information using a mobile information terminal. This enables users to centrally manage data from multiple financial information sources and strengthen monitoring of fraudulent transactions.

[0712] A "financial information source" refers to an organization or system that provides data related to users' financial activities.

[0713] A "communication protocol" is a set of rules and procedures that define how data is exchanged between different systems.

[0714] "Encoding" refers to the process of transforming data using specific algorithms to protect it from unauthorized access and eavesdropping by third parties.

[0715] "User" refers to a person or organization that uses the system, and in this invention, it refers to the entity that manages financial information.

[0716] A "portable information terminal" refers to a computing device that users can easily carry around, and includes smartphones and tablets.

[0717] "Fraudulent transactions" refer to financial transactions conducted against the user's will, and can be carried out through fraud or unauthorized access.

[0718] The system realizing this invention mainly consists of a server, a mobile information terminal, and communication means connecting them. The server connects to financial information sources, periodically collects financial data through communication protocols, encodes the collected data, and stores it securely. The server also utilizes anomaly transaction detection algorithms to analyze the collected data and identify signs of fraudulent transactions. This allows users to receive warnings in real time.

[0719] The personal digital assistant (PDCA) provides an interface for users to enter their authentication information and ensures secure access by utilizing multiple authentication factors. Users can use the PDCA to check their financial information and receive security education information provided by the system. The server is designed to ensure user convenience by balancing ease of operation with high security throughout the entire system.

[0720] For example, when a user uses a payment application on their mobile device while shopping on the weekend, the system collects the latest financial information in the background and provides the user with safety education information as needed.

[0721] An example of a prompt using a generative AI model is, "Please suggest a method to securely and efficiently manage users' financial data and detect abnormal transactions in real time."

[0722] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0723] Step 1:

[0724] The server connects to financial information sources and collects financial data using communication protocols. In this process, the server sends API requests to financial information sources to retrieve data such as the user's transaction history and account information. The input is the data obtained from the financial information source's API, and the output is the raw financial data received by the server.

[0725] Step 2:

[0726] The server encodes the acquired financial data. Specifically, the server transforms the data using an encryption algorithm (e.g., AES) and stores it securely. The input is raw financial data, and the output is encrypted data. This protects the data from unauthorized access.

[0727] Step 3:

[0728] Users log in to the system using a mobile device. The device receives the user's ID, password, and multi-factor authentication elements (e.g., biometric authentication or SMS code) and performs secure authentication. The input is the user's authentication information, and the output is the success or failure of the authentication.

[0729] Step 4:

[0730] The server analyzes encrypted data and identifies fraudulent transactions through an anomaly detection algorithm. Specifically, the anomaly detection algorithm builds a statistical model based on historical data and detects abnormal patterns. The input is decoded financial data, and the output is a list of transactions considered anomaly.

[0731] Step 5:

[0732] If the server detects a fraudulent transaction, it sends a real-time warning to the mobile device. The device then notifies the user of this warning, prompting them to take immediate action. The input is an abnormal transaction alert, and the output is a warning display on the device.

[0733] Step 6:

[0734] The server periodically generates security education information and distributes it to users via mobile devices. Specifically, it updates information on the latest cybersecurity threats and countermeasures to raise users' security awareness. The input is the periodic update information on the server, and the output is the display of educational content on the device.

[0735] 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.

[0736] This invention provides a system that, in addition to managing users' financial data, recognizes users' emotions and dynamically adjusts the interface based on those emotions. The system includes a server, a terminal, and an emotion engine, and the roles of each will be described below.

[0737] The server handles the traditional processes of collecting and managing financial data. Simultaneously, it analyzes user emotional data through an emotion engine and optimizes the user experience based on the results. It can also adjust security levels according to the user's emotional state.

[0738] The emotion engine analyzes user input information, such as voice and facial expressions, to identify the user's emotional state. The emotion engine then sends this information to a server, providing a foundation for the entire system to adapt based on emotions.

[0739] The device functions as a user interface, optimizing screen display and operation methods based on feedback from the emotion engine. For example, if the device determines that the user is experiencing stress, it will provide a simpler, stress-reducing interface. This simplified display allows the user to access information and perform actions more smoothly than usual.

[0740] Furthermore, the system provides personalized advice in real time based on insights gained from analyzing the user's emotions. For example, if the emotion engine detects high levels of anxiety in a user, the server immediately suggests financial advice or relaxation methods, and the terminal notifies the user of this.

[0741] In this way, embodiments of the present invention are capable of not only securely managing financial data but also improving the user experience based on user emotions and providing more personalized services. This increases user satisfaction and significantly enhances the usability of the system.

[0742] The following describes the processing flow.

[0743] Step 1:

[0744] The user logs into the system via their device. The user enters their ID and password and completes multi-factor authentication to obtain secure access.

[0745] Step 2:

[0746] The server retrieves the user's financial data through the financial institution's application programming interface. This data is stored on the server in an encrypted state.

[0747] Step 3:

[0748] The emotion engine acquires the user's facial expressions and voice data and analyzes their emotional state in real time. The results of this analysis are then sent to the server.

[0749] Step 4:

[0750] The server adjusts the interface and content according to the user's situation based on the emotional data received from the emotion engine. This adjustment is then transmitted to the device.

[0751] Step 5:

[0752] The terminal provides a user interface that adapts to the user's emotional state based on instructions from the server. For example, if it is determined that the user is experiencing high levels of stress, a simpler and easier-to-understand interface will be displayed.

[0753] Step 6:

[0754] The server comprehensively analyzes the user's financial and emotional data to generate personalized financial advice and security alerts. This information is then communicated to the user via their device.

[0755] Step 7:

[0756] The terminal displays advice and warnings sent from the server to the user and assists the user's actions as needed. This allows the user to take quick and appropriate action.

[0757] Step 8:

[0758] The server backs up data and analysis results and stores them in secure storage for future reference. This backup reduces the risk of data loss and improves system reliability.

[0759] (Example 2)

[0760] 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".

[0761] In recent years, financial services have demanded secure data management and improved user experience. However, challenges remain, including the risk of misuse and leakage of financial information, as well as the fact that uniform interfaces that do not consider users' emotional responses lower user satisfaction. Furthermore, there is a lack of dynamic service delivery that responds to emotions, making it difficult to provide services that meet the needs of individual users.

[0762] 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.

[0763] In this invention, the server includes means for securely collecting financial information, means for dynamically adjusting the display interface and operating methods based on the user's emotions, and means for generating and notifying appropriate financial advice according to the user's emotional state. This enables the secure management of financial information and personalized services that are tailored to the user's emotional needs.

[0764] "Financial institutions" refer to organizations and institutions that provide financial services, such as banks and securities companies.

[0765] An "application programming interface" refers to a set of conventions and tools that enable communication between different software applications.

[0766] "Financial information" refers to data about an individual's or organization's financial situation, such as bank account balances, transaction history, and spending patterns.

[0767] "Encryption" refers to the process of protecting data by encoding it using a specific algorithm.

[0768] "Users" refer to individuals or organizations that use a particular system or service.

[0769] "Authentication factors" are identifying information used to grant access to a system, and include passwords and biometric information.

[0770] "Economic activity" refers to the trading of assets and services and other financial activities carried out by individuals or organizations.

[0771] "Backup storage" refers to the process of creating copies of the same information and storing them in a separate location to prevent data loss.

[0772] "Security education" refers to educational activities aimed at providing users with knowledge and measures related to information security and raising their awareness.

[0773] "Emotions" refer to an individual's inner feelings or state of being, such as joy, sadness, or anger.

[0774] An "interface" refers to the screen display or means of operation that serves as a window for a user to interact with a system or device.

[0775] "Advice" refers to suggestions or instructions that are offered based on the situation or circumstances.

[0776] A "warning" refers to a notification intended to draw attention to a specific risk or anomaly.

[0777] The system of the present invention provides an advanced user experience that integrates financial data management and user emotion recognition. The following describes specific implementations of this system.

[0778] The server securely collects and manages financial information, integrating it into user-specific databases. This utilizes technologies that protect and make the information accessible using traditional database management systems and application programming interfaces (APIs). The server also analyzes data received from the emotion engine to generate insights for optimizing the user experience. Based on these insights, the system's security level is adjusted as needed.

[0779] The emotion engine utilizes hardware and software to analyze emotions from the user's voice and facial expressions. Specifically, it processes data acquired using cameras and microphones with machine learning models to estimate the user's emotional state. This emotional information is transmitted to the server in real time, forming the foundation for the entire system to provide services tailored to the user's emotional state.

[0780] The device provides an interface that directly interacts with the user. Based on feedback from the emotion engine, it dynamically changes the displayed content and operation methods to provide a more comfortable user experience. If the device detects that the user is experiencing stress, it automatically adjusts to an easier-to-use interface to reduce the user's burden.

[0781] As a concrete example, if the emotion engine detects that a user is stressed while trading stocks, the server immediately generates financial advice and provides a message through the terminal stating, "We recommend that you calmly analyze the situation and check for additional information if necessary." This allows the user to make decisions while remaining emotionally calm.

[0782] An example of a prompt message is: "Based on the analysis of the user's facial expressions and voice, the user is experiencing high levels of stress. How should the system adjust the interface and provide feedback to the user in this situation?" Thus, the present invention aims to improve the user experience from both the perspectives of financial information management and sentiment analysis.

[0783] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0784] Step 1:

[0785] The server collects financial information through the application programming interface of financial institutions. This information includes user transaction history and account balances. Input is data from financial institutions, and output is organized financial information. The server ensures security by encrypting the received information and storing it in a database. Specifically, it periodically calls the API to retrieve the latest data.

[0786] Step 2:

[0787] The emotion engine receives user audio and video data from the device. Inputs include the user's real-time voice and facial expressions. The emotion engine analyzes this data and evaluates the user's emotional state. Data processing is performed using an emotion analysis algorithm, and the output is the evaluation result of the emotional state. This information is sent to the server and stored as the user's emotional foundational data. Specific operations include acquiring data using speech recognition and facial expression detection technologies and inputting it into the model.

[0788] Step 3:

[0789] The server integrates financial and emotional data for comprehensive analysis. Inputs include financial information and emotional state data. Data processing involves algorithmic operation to correlate this information and identify user behavior patterns and needs; the output is a personalized user profile. Based on continuous analysis, it prepares appropriate advice and interface adjustments. Specifically, it uses machine learning models to analyze the dataset and extract insights.

[0790] Step 4:

[0791] The terminal receives results from the server and adjusts the user interface. Input is the analysis results from the server, and output is the adjusted display screen and operation method. Based on the user's state, the terminal changes the interface to reduce stress and provides voice navigation and guidance as needed. Specific actions include simplifying the graphic display and rearranging the layout to make important operation buttons more prominent.

[0792] Step 5:

[0793] The server generates appropriate financial advice based on user behavior and sentiment analysis. The input is integrated user data, and the output is personalized advice. The generating AI model generates future recommended actions and risk warnings based on historical data. This information is sent to the terminal in the form of prompts. Specifically, this involves inputting data into a predictive algorithm and sending the generated text to the user.

[0794] (Application Example 2)

[0795] 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".

[0796] While existing financial data management systems are effective in securely managing users' financial data, they struggle to provide more personalized support and optimized user interfaces based on users' emotional states. Furthermore, there is a need to adjust security levels according to users' emotional states and to create a comfortable user experience. The challenge lies in improving user satisfaction and reducing stress.

[0797] 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.

[0798] In this invention, the server includes means for securely collecting financial data using an application programming interface as a means for acquiring data from financial institutions, means for recognizing the emotional state of the user, and means for dynamically adjusting the user interface based on the emotional state. This enables the secure management of the user's financial data, as well as the optimization of the interface in response to emotions, thereby improving user satisfaction and providing a personalized user experience.

[0799] "Data acquisition means" refers to a function that securely acquires financial data using the application programming interface of a financial institution.

[0800] "Encryption methods" are technologies used to protect acquired financial data and integrate it for each user.

[0801] "Authentication method" refers to the process of verifying the identity of a user using multi-factor authentication.

[0802] An "anomaly detection system" is a system that identifies fraudulent or abnormal transactions in real time and generates warnings.

[0803] A "backup method" is a procedure for regularly saving data and making it possible to restore it as needed.

[0804] A "security education tool" is a system for providing users with knowledge about information security.

[0805] "Emotion recognition means" refers to technology that analyzes voice and facial expressions to identify the emotional state of a user.

[0806] An "interface adjustment mechanism" is a system that dynamically changes the displayed content and operating procedures according to the user's current situation.

[0807] "Personalized advice tools" are functions that provide specific advice and suggestions based on the user's emotions and circumstances.

[0808] The system implementing this invention primarily consists of a server, a terminal, and an emotion recognition engine. The server is responsible for collecting and integrating financial data, and also manages data necessary to recognize the emotional state of the user. The server obtains financial information using APIs from financial institutions, encrypts it, and then organizes and integrates it for each user. Furthermore, the server dynamically adjusts the interface and service provision based on the results of the user's emotion recognition.

[0809] The emotion recognition engine analyzes the user's voice and facial expression data acquired by the device to identify the user's emotional state. Specifically, it utilizes speech recognition and image processing technologies to determine whether the user is experiencing stress. The emotional data generated by the emotion recognition engine is sent to a server and used for further analysis and interface optimization.

[0810] The terminal functions as an interface with the user, optimizing screen displays and operation methods based on instructions provided by the server. For example, if the terminal determines that the user is stressed, it reduces the user's operational burden by displaying a simpler interface that responds to their emotions. Conversely, if the user is relaxed, it can display detailed financial information comprehensively, providing the user with deeper insights.

[0811] Furthermore, the generative AI model uses the user's emotional state and financial data to provide personalized advice and suggestions in real time. This AI model has the ability to provide more optimal advice by analyzing past data and trends.

[0812] As a concrete example, when a user uses an electronic wallet application through their device, the system analyzes their facial expressions and voice for the day and presents the interface best suited to their emotions at that time. For instance, if the system detects a visually tired expression on a weekday evening, it can alleviate fatigue by providing the user with key functions in a simple quick-access mode.

[0813] An example of a prompt for a generated AI model is: "Generate an AI model that adjusts the interface based on the user's emotional state and provides appropriate advice where reconfirmation is needed."

[0814] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0815] Step 1:

[0816] The device acquires the user's voice and facial expressions through its camera and microphone. This data serves as input to identify the user's emotional state. Voice data is converted to text using speech recognition software, and image data is categorized into emotional categories using a facial recognition algorithm.

[0817] Step 2:

[0818] The server receives audio and facial expression data from the emotion recognition engine and analyzes it using an emotion identification algorithm. This process outputs the user's emotional state as "stressed," "relaxed," "concentrated," etc. The identified emotion is then used as a criterion for subsequent interface adjustments.

[0819] Step 3:

[0820] The server dynamically adjusts the user interface based on the identified emotional state. For example, if the server identifies that the user is stressed, it translates the data into a command to "provide a simple interface" and sends it to the terminal. When selecting or reconfiguring the user interface, a generative AI model presents appropriate scenarios.

[0821] Step 4:

[0822] The terminal dynamically changes the user interface based on instructions from the server. This operation provides the user with a simple and intuitive display, reducing the burden of operation. For example, it can highlight only important financial information and omit other details.

[0823] Step 5:

[0824] When a user performs a transaction or operation through the user interface, the terminal sends the details to the server. This data is processed through the financial institution's API, and the security of the transaction is verified. Transaction information is properly encrypted in the backend and stored in a financial database.

[0825] Step 6:

[0826] Based on the user's transaction and behavioral history, the server uses a generative AI model to create personalized advice and suggestions. The generated content is structured as something like "Investment advice perfect for a relaxing evening" and is ultimately presented to the user through their device.

[0827] This entire process is designed to provide a more personalized user experience, allowing users to conduct financial transactions in a relaxed state.

[0828] 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.

[0829] 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.

[0830] 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.

[0831] 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.

[0832] 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.

[0833] 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.

[0834] 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.

[0835] 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.

[0836] 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."

[0837] 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.

[0838] 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.

[0839] 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.

[0840] 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.

[0841] 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.

[0842] 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.

[0843] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] The following is further disclosed regarding the embodiments described above.

[0850] (Claim 1)

[0851] A means of securely collecting financial data using an application programming interface as a means of acquiring data from financial institutions,

[0852] A means of encrypting the collected financial data and integrating it for each user,

[0853] A method of using multiple authentication factors during user authentication,

[0854] A means to detect abnormal transactions in real time and send alerts,

[0855] A means of regularly backing up data,

[0856] A means of providing security education information to users,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, comprising means for detecting anomalies using an anomaly detection algorithm by analyzing each user's financial data obtained from the application programming interface of a financial institution, and for automatically issuing an alert when an anomaly is detected.

[0860] (Claim 3)

[0861] The system according to claim 1, configured to allow for the rapid restoration of backed-up data in the event of a disaster or data loss.

[0862] "Example 1"

[0863] (Claim 1)

[0864] A means of securely collecting information data using a communication interface as a means of data acquisition by an intelligence agency,

[0865] A means of converting the collected information data and integrating it for each user,

[0866] A method of using multiple authentication factors during user authentication,

[0867] A means for detecting abnormal processing in real time and sending a warning,

[0868] A means of periodically recording and saving data,

[0869] A means of providing safety education information to users,

[0870] A system that includes this.

[0871] (Claim 2)

[0872] The system according to claim 1, comprising means for detecting anomalies using an anomaly detection method by analyzing information data of each user obtained from the communication interface of an information agency, and for automatically issuing a warning when an anomaly is detected.

[0873] (Claim 3)

[0874] The system according to claim 1, configured to allow for the rapid restoration of recorded and stored data in the event of a disaster or data loss.

[0875] "Application Example 1"

[0876] (Claim 1)

[0877] A means of securely collecting financial information using communication protocols as a means of acquiring data from financial information sources,

[0878] A means of encoding the collected financial information and integrating it for each user,

[0879] A method of using multiple authentication factors during user authentication,

[0880] A means of detecting fraudulent transactions in real time and sending warnings,

[0881] A means of regularly recording information for safety,

[0882] A means of providing safety education information to users,

[0883] A means of collecting and managing users' financial information using mobile devices,

[0884] A system that includes this.

[0885] (Claim 2)

[0886] The system according to claim 1, comprising means for detecting anomalies using an anomaly detection algorithm by analyzing financial information of each user obtained from a communication protocol, and for automatically issuing a warning when an anomaly is detected.

[0887] (Claim 3)

[0888] The system according to claim 1, configured to allow for the rapid restoration of recorded information in the event of a natural disaster or data loss.

[0889] "Example 2 of combining an emotion engine"

[0890] (Claim 1)

[0891] A means of securely collecting financial information using an application programming interface as a means of acquiring data from financial institutions,

[0892] A means of encrypting the collected financial information and integrating it for each user,

[0893] A method of using multiple authentication factors during user authentication,

[0894] A means of detecting abnormal economic activity in real time and sending warnings,

[0895] A means of periodically backing up data,

[0896] A means of providing information to users for security education,

[0897] A means of dynamically adjusting the display interface and operation methods based on the user's emotions,

[0898] A means of generating and notifying users of appropriate financial advice based on their emotional state,

[0899] A system that includes this.

[0900] (Claim 2)

[0901] The system according to claim 1, comprising means for detecting anomalies using anomaly detection technology by analyzing the financial information of each user obtained from the application programming interface of a financial institution, and for automatically issuing a warning when an anomaly is detected.

[0902] (Claim 3)

[0903] The system according to claim 1, configured to allow for the rapid restoration of backup data in the event of a disaster or data loss.

[0904] "Application example 2 when combining with an emotional engine"

[0905] (Claim 1)

[0906] A means of securely collecting financial data using an application programming interface as a means of acquiring data from financial institutions,

[0907] A means of encrypting the collected financial data and integrating it for each user,

[0908] A method of using multiple authentication factors during user authentication,

[0909] A means of detecting abnormal transactions in real time and sending warnings,

[0910] A means of regularly backing up data,

[0911] A means of providing security education information to users,

[0912] Means for recognizing the emotional state of the user,

[0913] A means of dynamically adjusting the user interface based on emotional state,

[0914] A means of providing personalized recommendations in real time based on emotional state,

[0915] A system that includes this.

[0916] (Claim 2)

[0917] The system according to claim 1, comprising means for detecting anomalies using an anomaly detection algorithm by analyzing each user's financial data obtained from the application programming interface of a financial institution, and for automatically issuing a warning when an anomaly is detected.

[0918] (Claim 3)

[0919] The system according to claim 1, configured to allow for the rapid restoration of backed-up data in the event of a disaster or data loss. [Explanation of symbols]

[0920] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means of securely collecting financial data using an application programming interface as a means of acquiring data from financial institutions, A means of encrypting the collected financial data and integrating it for each user, A method of using multiple authentication factors during user authentication, A means to detect abnormal transactions in real time and send alerts, A means of regularly backing up data, A means of providing security education information to users, A system that includes this.

2. The system according to claim 1, comprising means for detecting anomalies using an anomaly detection algorithm by analyzing each user's financial data obtained from the application programming interface of a financial institution, and for automatically issuing an alert when an anomaly is detected.

3. The system according to claim 1, configured to enable rapid restoration of backed-up data in the event of a disaster or data loss.

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