System

Abstract

A system is provided.SOLUTION: A system comprising: means for collecting statute information; means for analyzing the collected statute information; means for storing the analyzed statute information; means for managing company-specific operation rules; means for receiving a question from a user; means for generating an answer by referring to the analyzed statute information and the company-specific operation rules based on the received question; means for providing the generated answer to the user; means for checking legality of a new service; and means for detecting and notifying new statute revision information and business improvement information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Financial services require strict compliance with laws and regulations, and any violations pose a risk of disrupting business continuity. Furthermore, when starting a new business, legal reorganization and proper communication with authorities are essential, forcing companies to expend a great deal of time and effort. This can make it difficult to quickly launch new services and risk reducing a company's competitiveness. Furthermore, managing and applying frequently revised legal information requires specialized knowledge and carries the risk of human error. Companies need a way to resolve these issues and ensure compliance while smoothly rolling out new services. [Means for solving the problem]

[0005] The present invention provides a system including means for collecting legal information, means for analyzing the collected legal information, means for saving the analyzed legal information, means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, and means for detecting and notifying new legal revision information and business improvement information.

[0006] This system allows companies to keep up with the latest legal information and quickly check legality. It also enables companies to efficiently manage their own operational rules and instantly obtain specific answers regarding legal compliance. This enables the rapid launch of new services and ensures legal compliance, reducing business risks for companies.

[0007] "Legal information" refers to information such as laws, regulations, and guidelines issued or published by government agencies or public institutions.

[0008] "Analysis" refers to the data processing carried out to convert collected legal information into structured data.

[0009] "Company-specific operating rules" are rules such as business procedures, regulations, and guidelines established internally by a specific company.

[0010] "Generative AI" refers to artificial intelligence technology that understands the content and context of a question and generates a specific answer based on that.

[0011] "Legality Check" is the process of inspecting and assessing whether a new service complies with current laws and regulations.

[0012] "Notification" refers to messages or alerts used to convey important information, such as information on legal revisions or business improvement, to relevant parties.

[0013] "New services" refer to new products or services that a company plans to offer, or improved versions of existing services.

[0014] "Base area" refers to a data area that stores common legal information.

[0015] The "customization area" refers to the data area that stores each company's specific operational rules and manual information. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: a server, a terminal, and a user.

[0038] Overall system configuration

[0039] server

[0040] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the base area, and company-specific operational rules are stored in the customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information and notifying companies.

[0041] Terminal

[0042] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[0043] User

[0044] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[0045] Program processing overview

[0046] Collection and updating of legal information

[0047] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[0048] Management of company-specific operational rules

[0049] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[0050] Support for resolving legal issues

[0051] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[0052] Checking the legality of new services

[0053] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[0054] Notification function for legal revisions and business improvements

[0055] The server detects information on legal revisions and business improvement information in real time from the collected data. It automatically analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[0056] Specific examples

[0057] 1. Collection and updating of legal information

[0058] The server periodically collects new financial laws and regulations from government agency websites using scraping technology.

[0059] The server analyzes the collected information using an AI analysis engine and stores it in a base area.

[0060] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[0061] 2. Managing company-specific operational rules

[0062] The user gives an instruction to "input new bank agency procedure rules."

[0063] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[0064] 3. Support for resolving legal issues

[0065] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[0066] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[0067] The server sends this response to the terminal and displays it to the user.

[0068] 4. Legality checks for new services

[0069] The user instructs "Enter details for new funds transfer service."

[0070] The terminal transmits the service information to the server, and the server checks the legitimacy.

[0071] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[0072] 5. Notification function for legal revisions and business improvements

[0073] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[0074] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[0075] The user receives a notification and reviews the business rules.

[0076] The above is a concrete example of the financial license supporter. This system will enable companies to rapidly develop new services while ensuring compliance with laws and regulations.

[0077] The processing flow will be explained below.

[0078] Collection and updating of legal information

[0079] Step 1:

[0080] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[0081] Step 2:

[0082] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[0083] Step 3:

[0084] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[0085] Step 4:

[0086] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[0087] Management of company-specific operational rules

[0088] Step 1:

[0089] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[0090] Step 2:

[0091] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[0092] Step 3:

[0093] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[0094] Support for resolving legal issues

[0095] Step 1:

[0096] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[0097] Step 2:

[0098] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[0099] Step 3:

[0100] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[0101] Step 4:

[0102] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[0103] Checking the legality of new services

[0104] Step 1:

[0105] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[0106] Step 2:

[0107] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[0108] Step 3:

[0109] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[0110] Step 4:

[0111] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[0112] Step 5:

[0113] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[0114] Notification function for legal revisions and business improvements

[0115] Step 1:

[0116] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[0117] Step 2:

[0118] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[0119] Step 3:

[0120] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[0121] Step 4:

[0122] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[0123] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. As a result, new services can be launched quickly and business risks can be reduced.

[0124] Example 1

[0125] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0126] To ensure that financial companies comply with laws and regulations quickly and reliably and provide new services legally, they must constantly collect and analyze the latest legal information and compare it with their own operational rules. However, collecting and analyzing legal information takes time and effort, making it difficult to keep up with modern financial laws, which are frequently revised. Furthermore, when checking individual legal issues or the legality of new services, companies must be able to efficiently and accurately refer to legal information. In this environment, a system is needed that enables companies to effectively comply with laws and regulations and smoothly deploy new services.

[0127] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0128] In this invention, the server includes: means for collecting legal information; means for automatically acquiring the collected legal information using scraping or API technology; means for inputting and analyzing the collected legal information into an AI analysis engine; means for saving the analyzed legal information in a base area; means for inputting company-specific operational rules and transmitting them from a terminal to the server; means for managing the saved company-specific operational rules; means for receiving questions from users; means for generating answers using a generative AI model by referencing the analyzed legal information and company-specific operational rules based on the received questions; means for sending the generated answers to the terminal and providing them to the user; means for users to input detailed information about new services; means for checking the legality of the input new services; and means for detecting and notifying legal revision information and business improvement information in real time. This enables companies to effectively collect and analyze the latest legal information, compare it with operational rules, and take appropriate action. Furthermore, the system can check the legality of new services and provide quick and accurate answers to individual legal issues, enabling the smooth deployment of new services while maintaining compliance with laws and regulations.

[0129] "Legal information" is a general term for information about laws, ordinances, regulations, guidelines, etc. published by government agencies and public institutions.

[0130] "Means of collection" refers to the methods and tools used to obtain the necessary data from a specific source, such as scraping tools and APIs.

[0131] "Scraping technology" refers to the technology or process of automatically extracting structured or unstructured data from a specific website.

[0132] "API technology" refers to a method of obtaining data from a specific service using an application program interface (API).

[0133] "AI analytics engine" refers to software or systems that use artificial intelligence to analyze data, including, for example, generative AI models for natural language processing.

[0134] "Base area" refers to a database or storage area for storing analyzed legal information.

[0135] "Company-specific operating rules" refer to the internal regulations and guidelines that a particular company must follow in its business operations and activities.

[0136] "Terminal" refers to a device used by a user, such as a computer or smartphone.

[0137] A "server" refers to a computer system that provides services to other devices over the Internet or a network.

[0138] A "generative AI model" is a model that uses artificial intelligence to generate appropriate output for specific inputs, such as models for natural language processing and text generation.

[0139] "Means for checking legality" refers to methods and technologies for verifying whether a new service complies with existing laws and regulations.

[0140] "Legal amendment information" refers to information on newly amended laws and regulations and newly enacted laws.

[0141] "Business improvement information" refers to information and suggestions for improving a company's business efficiency and compliance.

[0142] "Real-time detection means" refers to methods and technologies for instantly analyzing collected data and detecting changes or anomalies.

[0143] "Means of notification" refers to the method or technology used to communicate specific information to the target user, including, for example, email and push notifications.

[0144] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and rapidly develop new services. This system is composed of the following elements: a server, a terminal, and a user.

[0145] Overall system configuration

[0146] server

[0147] The server plays a central role in collecting, analyzing, and storing legal information. The server periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the "base area," while company-specific operational rules are stored in the "customization area." The server also receives questions from users, generates answers based on analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information in real time and notifying companies.

[0148] Terminal

[0149] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[0150] User

[0151] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[0152] Program processing overview

[0153] Collection and updating of legal information

[0154] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[0155] Examples:

[0156] Every Monday, the server uses scraping technology to collect new financial laws and regulations from government agency websites.

[0157] The server analyzes the collected information using an AI analysis engine (e.g., OpenAI's GPT series) and stores it in the base area.

[0158] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[0159] Management of company-specific operational rules

[0160] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[0161] Examples:

[0162] The user gives an instruction to "input new bank agency procedure rules."

[0163] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[0164] Support for resolving legal issues

[0165] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[0166] Examples:

[0167] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[0168] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[0169] The server sends this response to the terminal and displays it to the user.

[0170] Checking the legality of new services

[0171] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[0172] Examples:

[0173] The user instructs "Enter details for new funds transfer service."

[0174] The terminal transmits the service information to the server, and the server checks the legitimacy.

[0175] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[0176] Notification function for legal revisions and business improvements

[0177] The server detects information on legal revisions and business improvement information in real time from the collected data. Important revision information is automatically analyzed and customized notifications are generated for each relevant company. Users receive the notifications on their devices, check the content, and update their company's business rules and manuals.

[0178] Examples:

[0179] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[0180] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[0181] The user receives a notification and reviews the business rules.

[0182] Example prompts for generative AI models

[0183] Below are some specific examples of prompt sentences to input to the generative AI model.

[0184] "What license do I need to launch a new electronic payment service?"

[0185] "I would like to perform a legality check on a new service. Please enter the following details:..."

[0186] The above is an embodiment of the present invention, which enables financial companies to ensure compliance with laws and regulations and efficiently provide new services.

[0187] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0188] A concrete explanation of the program's processing flow

[0189] Step 1:

[0190] Collection of legal information

[0191] The server accesses designated government agency or public websites (e.g., the official Financial Services Agency website) at 2:00 a.m. every Monday.

[0192] Input: Legal information collection schedule and access URL

[0193] Specific operation: The server uses a scraping tool (e.g., Beautiful Soup, Scrapy) to collect new financial-related legal information from web pages.

[0194] Output: Raw data of the acquired legal information (HTML, JSON, etc.)

[0195] Step 2:

[0196] Analysis of information

[0197] The server inputs the collected legal information into an AI analysis engine (e.g., OpenAI's GPT series).

[0198] Input: Raw data of collected legal information

[0199] Specific operation: The server uses an AI analysis engine to analyze legal information using natural language processing, and extracts the importance of legal provisions and revision details.

[0200] Output: Analyzed legal information (e.g. legal clause, importance, revision date, etc.)

[0201] Step 3:

[0202] Data storage

[0203] The server stores the analyzed legal information in a "base area."

[0204] Input: Parsed legal information

[0205] Specific operation: The parsed information is stored in a base area using a database management system (e.g., MySQL, PostgreSQL).

[0206] Output: Updated legal information for the base region

[0207] Step 4:

[0208] Entering company-specific operational rules

[0209] Users use a dedicated interface to input company-specific operational rules.

[0210] Input: Contents of the operation rules (e.g., text, checklist format)

[0211] Specific operation: The terminal formats the input and sends it to the server.

[0212] Output: Formatted data of the operational rules

[0213] Step 5:

[0214] Data transmission and storage

[0215] The terminal transmits the input operation rules to the server.

[0216] Input: Operational rule data sent from the terminal

[0217] Specific operation: The server stores the received operational rules in the "customization area."

[0218] Output: Updated operational rules for the customization area

[0219] Step 6:

[0220] Receive questions about legal issues

[0221] The user inputs a question about a legal issue from a terminal.

[0222] Input: Questions about legal issues (e.g., "What licenses are required to launch a new electronic payment service?")

[0223] Specific operation: The terminal converts the entered question into a prompt sentence and sends it to the server.

[0224] Output: prompt statement

[0225] Step 7:

[0226] Question analysis and answer generation

[0227] The server analyzes the question and compares it with relevant legal information and company-specific operational rules.

[0228] Input: Prompt text, legal information in the base area, operational rules in the customization area

[0229] Specific operation: The server uses a generative AI model to generate the optimal answer (e.g., OpenAI GPT series).

[0230] Output: The generated answer

[0231] Step 8:

[0232] Submitting and viewing answers

[0233] The server sends the generated response to the terminal.

[0234] Input: Generated Answer

[0235] Specific operation: The server sends the answer data to the terminal, and the terminal displays the answer to the user.

[0236] Output: Answer displayed on terminal

[0237] Step 9:

[0238] Enter details of new service

[0239] The user enters the details of the new service.

[0240] Enter: New service details (e.g., "New Funds Transfer Service Details")

[0241] Specific operations: The terminal formats the information and sends it to the server.

[0242] Output: Formatted information about the new service

[0243] Step 10:

[0244] Legality analysis

[0245] The server analyzes the input for the new service and extracts any necessary licenses and legal requirements.

[0246] Input: New service details, legal information in the base area, operational rules in the customization area

[0247] Specific operation: Using a generative AI model, the system checks legal information and operational rules related to new services to confirm legality.

[0248] Output: Legality check results and required licenses

[0249] Step 11:

[0250] Sending and displaying results

[0251] The server generates the results of the legality check in the form of a report and sends it to the terminal.

[0252] Input: Legality check result

[0253] Specific operation: The generated report is sent to the terminal, and the terminal displays the report to the user.

[0254] Output: Report provided to the user

[0255] Step 12:

[0256] Detecting and notifying information on legal revisions and business improvement

[0257] The server detects information on legal revisions and business improvement in real time from the collected data and customizes notifications.

[0258] Input: Base area legal information

[0259] Specific operation: Using generative AI models and natural language processing technology, information on legal amendments and business improvement is analyzed, and notification content is generated for relevant companies.

[0260] Output: Customized notifications for each company

[0261] Step 13:

[0262] Sending and receiving notifications

[0263] The server automatically sends the generated notification, and the user receives the notification on the terminal.

[0264] Input: Generated notification content

[0265] Specific operation: The server sends notification data to the terminal, and the terminal displays the notification to the user.

[0266] Output: Notifications displayed on the device

[0267] The above is the specific processing steps of the financial license supporter system and the flow of its operation.

[0268] (Application example 1)

[0269] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0270] Adapting to rapidly changing laws and regulations and ensuring legal compliance is a major challenge for current electronic payment services. Obtaining information on legal revisions in real time and quickly adapting operations based on that information is particularly difficult. Additionally, the process of checking the legality of new services and confirming necessary licenses and legal requirements is complex and time-consuming. There is a need for a support system that can address these challenges and quickly deploy new services while complying with laws and regulations.

[0271] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0272] In this invention, the server includes a means for collecting legal information, a means for analyzing the collected legal information, and a means for automatically notifying the company of important revisions to the analyzed legal information. This allows the company to grasp the latest legal revision information in real time and adapt its business accordingly. In addition, by including a means for inputting detailed information about new services and a means for analyzing and providing the necessary licenses and legal requirements, the legality of new services can be checked quickly and reliably, enabling the rapid deployment of new services.

[0273] "Legal information" refers to information on laws, regulations, ordinances, etc., and information on amendments thereto, provided by government agencies and public institutions.

[0274] "Analysis" refers to the process of analyzing collected data and information and extracting and organizing the necessary information.

[0275] "Storing" refers to recording collected and analyzed information in a database or storage device so that it can be used later.

[0276] "Company-specific operating rules" refer to internal rules and guidelines established by a specific company for compliance with laws and regulations and business operations.

[0277] "Receiving questions" refers to receiving inquiries or confirmations from users through a device or system.

[0278] "Generating an answer" refers to creating an appropriate response to a received question or inquiry based on relevant information and data.

[0279] "Providing to the user" refers to conveying the generated answers or information to the user in an appropriate manner.

[0280] "New Services" refers to new products, services, or improved versions thereof offered by a company.

[0281] "Checking legality" refers to the process of verifying whether the services or products offered comply with current laws and regulations.

[0282] "Legal amendment information" refers to new information and amendments when existing laws and regulations are changed.

[0283] "Business improvement information" refers to information related to suggestions, advice, and best practices for improving the efficiency of corporate operations and business.

[0284] "Real-time notification" means instantly informing companies and users of the latest information and data.

[0285] "Detailed information about new services" refers to information such as specific data, features, and specifications about new services provided by a company.

[0286] "Necessary Licenses and Legal Requirements" means the permits, licenses and legal requirements that must be obtained in order to provide certain services or products.

[0287] The present invention, "Financial License Supporter System," helps financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: servers, terminals, and users.

[0288] Overall system configuration

[0289] server

[0290] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using a generative AI model. The analyzed information is stored in a base area, and company-specific operational rules are stored in a customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services.

[0291] The server also has the ability to detect legal revisions and business improvement information in real time and notify companies. Specifically, it automatically obtains legal information periodically from government agencies and public websites using scraping technology and APIs, and passes the collected information to a generative AI model for analysis. The analyzed information is stored in a database, and if important revisions are detected, relevant companies are notified.

[0292] Terminal

[0293] The terminal is the device that the user uses as an interface. The user uses the terminal to input questions and details of new services. The terminal sends this input information to the server and displays the server's response or results. For example, if a user inputs a question such as "What licenses are required to start a new electronic payment service?", the terminal sends this information to the server, and the server analyzes legal information and the company's operating rules to generate an answer, which the terminal then displays to the user.

[0294] User

[0295] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, and check the legality of new services. Furthermore, the terminal can also be used to input and update company-specific operational rules into the server. For example, when launching a new service, a user can issue an instruction to "enter detailed information about a new fund transfer service." The terminal then sends the information to the server, which checks legality and analyzes and provides the necessary licenses and legal requirements.

[0296] Hardware and software used

[0297] Hardware: Physical servers and cloud servers (e.g. AWS, GCP, Azure)

[0298] Software: Python, Flask, BeautifulSoup, requests, apscheduler, any AI analysis library (e.g. GPT-3, BERT)

[0299] Data processing and calculation

[0300] 1. Data Collection

[0301] The server periodically collects legal information from government agencies and public websites using scraping techniques using BeautifulSoup and requests.

[0302] 2. Data Analysis

[0303] The collected legal information is passed to a generative AI model on the server for analysis. The analysis results are saved in the base area. Company-specific operational rules are also saved in the customization area.

[0304] 3. Answer generation and notification

[0305] When a user asks a question, the server analyzes the legal information related to the question and the company's operating rules to generate an appropriate answer. By entering detailed information about a new service, the server checks its legality and analyzes and provides necessary licenses and legal requirements. Furthermore, if important legal revision information is detected, the server notifies relevant companies in real time.

[0306] Specific examples

[0307] Prompt Sentence Examples

[0308] "What licenses are required to launch a new electronic payment service?"

[0309] "If new legal changes are made to the prepaid payment instrument issuing industry, how will our business be affected?"

[0310] This will enable companies to rapidly roll out new services while ensuring compliance with regulations.

[0311] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0312] Step 1:

[0313] The server periodically collects legal information from government agencies and public websites. As input, it receives the target website URL and obtains legal information using scraping technology (BeautifulSoup,requests). As output, it generates a dataset of the collected legal information.

[0314] Step 2:

[0315] The server analyzes the collected legal information. As input, it passes the legal information collected in step 1 to the AI ​​analysis engine (generative AI model). As data calculation, the AI ​​model classifies the legal information into applicable legal categories and importance levels, and outputs the analysis results. As output, it saves the analyzed legal information in a base area.

[0316] Step 3:

[0317] The server receives company-specific operational rules from the user and stores them. The user inputs their company's operational rules via a terminal, and the input data is sent to the server. The server receives the operational rules entered by the user as input and stores them in a customization area. The server generates a dataset of operational rules as output.

[0318] Step 4:

[0319] The user enters questions about the licenses and legal requirements required for the new service into their device and sends them to the server. The server receives the user's question as input and analyzes it. As a data calculation, the AI ​​analysis engine generates the optimal answer to the question based on legal information and the company's operating rules. As an output, the answer is sent to the device and displayed to the user.

[0320] Step 5:

[0321] The user enters details of the new service they wish to offer into their device and sends it to the server. The server receives the details of the new service as input and checks its legality. As data calculations, the AI ​​analysis engine compares the content of the new service with legal information and analyzes the necessary licenses and legal requirements. As output, the results of the legality check are sent to the device as a report and provided to the user.

[0322] Step 6:

[0323] The server detects information on legal revisions and business improvement information in real time and notifies companies. It periodically monitors analyzed legal information as input, and generates notification information when important revisions are detected. It outputs the notification information, sending it to relevant companies in real time and displaying it on the user's device.

[0324] Step 7:

[0325] The terminal displays the entered operational rules and questions, detailed information about new services, and notifications from the server. It receives answers sent from the server, legality check results, and notification information as input, and immediately displays them to the user as output. Specifically, the user can enter a prompt to receive prompt feedback on legality and questions.

[0326] The above are the specific processing steps of the program for the system that realizes the application example.

[0327] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0328] The present invention is a system that not only helps financial companies ensure compliance with laws and regulations and quickly launch new services, but also recognizes users' emotions and provides appropriate responses. Below, we will specifically explain an embodiment of the invention that combines an emotion engine.

[0329] Overall system configuration

[0330] server

[0331] The server plays a central role in collecting, analyzing, and storing legal information. It also uses an emotion engine to analyze users' emotions and adjust the content of responses and notifications.

[0332] Terminal

[0333] The terminal is a device that the user uses as an interface. The user inputs questions from the terminal and receives answers and notifications from the server. The terminal also collects the user's emotional data and sends it to the server.

[0334] User

[0335] The users are financial business personnel. They operate the terminal to check legal information, input questions, check the legality of new services, etc. The user's emotional data is also analyzed, and the system adjusts the response accordingly.

[0336] Program processing overview

[0337] Collection and updating of legal information

[0338] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs. It then analyzes the collected legal information using an AI analysis engine and stores it in a base area. When it detects important legal amendments or new regulatory information, it sends notifications to relevant companies.

[0339] Management of company-specific operational rules

[0340] The user inputs company-specific operational rules using a dedicated interface. The terminal sends the input operational rules to the server, which then stores them in a customization area.

[0341] Support for resolving legal issues

[0342] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and the AI ​​generates an appropriate answer. The answer is then provided to the user via the device.

[0343] Checking the legality of new services

[0344] When a user enters details of a new service, the device sends them to the server. The server checks the legality of the new service by comparing it with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements, and sends the check results and details to the device for provision to the user.

[0345] Notification function for legal revisions and business improvements

[0346] The server detects information on legal revisions and business improvement information in real time from the collected data. It analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[0347] Emotion recognition and response adjustment

[0348] Emotion Engine

[0349] The emotion engine has the function to recognize and analyze the user's emotions. When the user enters a question or details of a new service, the device simultaneously collects the user's emotion data and sends it to the server.

[0350] Emotion recognition processing

[0351] Step 1

[0352] The server uses an emotion engine to analyze the emotion data sent by the user and determine their current emotional state. For example, if the user is feeling anxious or stressed, the server generates an analysis result that reflects that.

[0353] Emotion-based response adjustment

[0354] Step 2

[0355] The server adjusts the tone and content of the appropriate response based on the perceived emotion, for example, providing a more relaxed tone of response if the user is feeling stressed.

[0356] Emotion-based notification timing

[0357] Step 3

[0358] The server then selects the appropriate timing and format for notifications based on the emotion recognition results. For example, it can avoid notifications when the user is concentrating and send notifications when the user is relaxed.

[0359] Specific examples

[0360] 1. Emotion-aware response adjustment

[0361] When a user types a question such as "What are the licensing requirements for new electronic payment services?", the terminal collects the user's sentiment.

[0362] The server uses an emotion engine to determine the user's anxiety and generates a response in a stress-reducing tone, saying, "A license for electronic payment services is required."

[0363] The server sends this response to the terminal and provides it to the user.

[0364] 2. Emotion-aware notification adjustment

[0365] When the server detects new legal amendments and prepares to notify relevant companies, it also analyzes user emotional data.

[0366] The server takes into account the user's emotional state and sends a notification that "there are new legal changes" at an appropriate time.

[0367] 3. Legality checks for new services and emotional responses

[0368] When a user enters details of a new service and the device sends them to the server, emotional data is also collected at the same time.

[0369] The server uses an emotion engine to recognize the user's state of excitement and generates a report on the legality of the service, along with a detailed and reassuring explanation.

[0370] The server sends this report to the terminal and provides it to the user.

[0371] The system enables businesses to respond to users' emotional states while ensuring compliance, improving operational efficiency and customer satisfaction, while also enabling the rapid launch of new services and reducing business risks.

[0372] The processing flow will be explained below.

[0373] Processing flow of a system that combines emotion engines

[0374] Collection and updating of legal information

[0375] Step 1:

[0376] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[0377] Step 2:

[0378] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[0379] Step 3:

[0380] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[0381] Step 4:

[0382] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[0383] Management of company-specific operational rules

[0384] Step 1:

[0385] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[0386] Step 2:

[0387] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[0388] Step 3:

[0389] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[0390] Support for resolving legal issues

[0391] Step 1:

[0392] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[0393] Step 2:

[0394] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[0395] Step 3:

[0396] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[0397] Step 4:

[0398] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[0399] Checking the legality of new services

[0400] Step 1:

[0401] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[0402] Step 2:

[0403] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[0404] Step 3:

[0405] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[0406] Step 4:

[0407] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[0408] Step 5:

[0409] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[0410] Notification function for legal revisions and business improvements

[0411] Step 1:

[0412] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[0413] Step 2:

[0414] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[0415] Step 3:

[0416] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[0417] Step 4:

[0418] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[0419] Emotion recognition and response adjustment process flow

[0420] Emotion recognition processing

[0421] Step 1:

[0422] When a user enters a question or details of a new service through the device, the device simultaneously collects emotional data, such as facial expressions, tone of voice, and heart rate, using a camera, microphone, and sensors.

[0423] Step 2:

[0424] The device sends the collected emotion data to a server, where the data is formatted and adjusted so that it can be analyzed by the emotion engine.

[0425] Step 3:

[0426] The server analyzes the emotion data through an emotion engine to determine the user's current emotional state, for example, identifying emotions such as stress, anxiety, and relaxation.

[0427] Emotion-based response adjustment

[0428] Step 1:

[0429] The server adjusts the tone and content of responses and notifications based on the analysis results. For example, if the user is feeling stressed, it will adopt a polite and friendly tone to help them relax.

[0430] Step 2:

[0431] The server generates a response or notification based on the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the server may provide a message such as, "Don't worry. There will be no problem if you obtain a license for electronic payment services."

[0432] Adjusting notification timing based on emotions

[0433] Step 1:

[0434] The server selects the appropriate timing for notifications based on the user's emotional state, for example, when the user is relaxing or has free time at work.

[0435] Step 2:

[0436] The server generates a notification at an appropriate time and sends it to the device. By notifying the user that "there are new revisions to the law" during a time when the user is relaxing, the information is received effectively.

[0437] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. Furthermore, the system can respond according to the user's emotional state, improving business efficiency and user satisfaction, enabling the rapid launch of new services and reducing business risks.

[0438] Example 2

[0439] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0440] In modern financial operations, legal compliance is an important issue for companies, but it is difficult to quickly collect and analyze frequently updated legal information. There is also a need to check the legality of new services and provide prompt answers to legal issues. Furthermore, it is also necessary to recognize user emotions and respond appropriately based on them. However, no system currently exists that can meet these diverse requirements. Therefore, there is a need for a system that integrates the collection, analysis, and notification of legal information, the legality check of new services, and the user emotion recognition functions.

[0441] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0442] In this invention, the server includes means for collecting legal information, means for analyzing the collected legal information, means for saving the analyzed legal information, means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, means for detecting and notifying new legal revision information and business improvement information, means for collecting user emotional data, means for analyzing the collected emotional data to determine the user's emotional state, means for adjusting the tone and content of the answer based on the determined emotional state, and means for selecting the appropriate timing and format of notifications. This enables support for legal compliance, rapid launch of new services, optimization of company operational rules, and optimal responses according to the user's emotional state.

[0443] "Legal Information" refers to laws, regulations, and amendments thereto published by government agencies and public websites.

[0444] "Analyzing" refers to the process of classifying and interpreting collected legal information using machine learning models and natural language processing technology.

[0445] "Storing" refers to storing the analyzed data in a designated database or storage system.

[0446] "Company-specific operating rules" refer to specific business processes and standards established internally by a company.

[0447] "Receiving a question" refers to the server receiving a question or information request sent by a user via a terminal.

[0448] "Generating an answer" refers to the process of generating an appropriate response based on the received question, by referring to relevant legal information and company-specific operational rules.

[0449] "Checking legality" refers to the process of verifying whether a new service or product complies with current laws and regulations.

[0450] "Emotional data" refers to data that indicates a user's emotional state, such as data collected from the user's tone of voice, facial expression, and tone of writing.

[0451] "Determining emotional state" refers to identifying the psychological state the user is currently experiencing based on the collected emotional data.

[0452] "Adjusting the tone and content of your response" refers to appropriately changing the tone and wording of your response based on your determined emotional state.

[0453] "Selecting the appropriate timing and format for notifications" refers to determining the best time and method for sending notifications, taking into account emotional data and work schedules.

[0454] A "generative AI model" refers to an artificial intelligence system that generates natural language text based on input data.

[0455] The present invention is a system that not only helps financial companies ensure compliance with laws and regulations and quickly launch new services, but also recognizes users' emotions and provides appropriate responses. Specific embodiments of this system are described below.

[0456] Overall system configuration

[0457] The system mainly consists of three elements: a server, a terminal, and a user.

[0458] server

[0459] The server plays a central role in collecting, analyzing, and storing legal information. It also has the ability to analyze user sentiment using an emotion engine and adjust the content of responses and notifications. To do this, the server collects legal information through scraping technologies (e.g., Beautiful Soup or Scrapy) or API access, analyzes the data using an AI analysis engine (e.g., TensorFlow or Scikit-learn), and generates responses using a generative AI model (e.g., GPT-3).

[0460] Terminal

[0461] The device is the interface used by the user. The user inputs questions through the device and receives answers and notifications from the server. The device also collects the user's emotional data (e.g., voice tone and facial expression data) and sends it to the server. For this purpose, the device is equipped with hardware such as a microphone and a camera.

[0462] User

[0463] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. The information and emotional data entered by the user are sent to the server via the terminal, and the analyzed results are provided.

[0464] Procedures for collecting and updating legal information

[0465] The server periodically collects legal information from government agencies and public websites using scraping technologies such as Python's Beautiful Soup and Scrapy, as well as the government's public API. The collected information is analyzed using an AI analysis engine using TensorFlow and Scikit-learn, and then stored in a base area.

[0466] Examples:

[0467] The user checks the updated status of legal information from the terminal.

[0468] The server collects legal information and checks for updates.

[0469] Send a notification to the user saying, "The latest financial regulations have been updated."

[0470] Example prompt:

[0471] "Collect the latest legal information and inform companies."

[0472] Management procedures for company-specific operational rules

[0473] The user inputs the company's unique operational rules using a dedicated interface and sends them to the server via the terminal. The server saves the input operational rules in the customization area.

[0474] Examples:

[0475] The user enters the "company's internal rules" from the terminal.

[0476] The terminal transmits the input information to the server, which stores it in the customization area.

[0477] Example prompt:

[0478] Enter your company's internal rules and save them in the customization area.

[0479] Legal issue resolution support procedures

[0480] When a user inputs a question or inquiry into their device, the device sends it to the server. The server analyzes the question using TensorFlow and Scikit-learn, compares it with relevant legal information and the company's operational rules, and generates an appropriate answer. The generated answer is then provided to the user via the device.

[0481] Examples:

[0482] The user types into the terminal, "Is this transaction legitimate?"

[0483] The server compares the legal information with the company's operating rules and responds, "This transaction is legal."

[0484] Example prompt:

[0485] "Analyze user questions, compare legal information and operational rules, and generate answers."

[0486] Procedures for checking the legality of new services

[0487] When a user enters details of a new service, the device sends them to the server, which checks the legality of the new service by comparing it with the information in the base and customization areas. The generative AI model extracts any necessary licenses or legal requirements, and sends the check results and details to the device for presentation to the user.

[0488] Examples:

[0489] The user enters the details of the new payment service into the terminal.

[0490] The server parses the input, extracts any necessary licenses and legal requirements, and generates a report.

[0491] Example prompt:

[0492] "Please analyze the details of the new service and check the legal requirements and legality."

[0493] Emotion recognition and response adjustment procedures

[0494] When a user enters details of a question or new service, the device collects emotional data and sends it to the server. The server then analyzes the data using an emotion engine to determine the user's emotional state. Based on the determined emotional state, the generative AI model adjusts the tone and content of the appropriate response and delivers it to the user via the device. It also determines the appropriate timing and format for notification.

[0495] Examples:

[0496] A user types a question: "What are the licensing requirements for new electronic payment services?"

[0497] The server analyzes the user's emotions and responds in a relaxed tone.

[0498] Example prompt:

[0499] "Analyze user sentiment data and generate appropriate responses."

[0500] The system enables businesses to improve operational efficiency and customer satisfaction by providing responses that respond to users' emotional states while ensuring compliance with regulations.

[0501] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0502] Step 1: Gather legal information

[0503] The server periodically collects legal information from government agencies and public websites using scraping technologies such as Python's Beautiful Soup and Scrapy, as well as public APIs, to obtain the latest legal information.

[0504] Input: URL of a government or public website.

[0505] Data processing and calculation: Data acquisition using scraping technology and APIs.

[0506] Output: Raw data of the legal information obtained.

[0507] Step 2: Analyzing legal information

[0508] The server analyzes the collected legal information using an AI analysis engine (such as TensorFlow or Scikit-learn) to classify the type and content of the law. As a result of the analysis, important parts of the law are extracted.

[0509] Input: Raw legal information collected in step 1.

[0510] Data processing and calculation: Classifying data and extracting important parts.

[0511] Output: Parsed legal information.

[0512] Step 3: Save legal information

[0513] The server stores the analyzed legal information in the base area of ​​the database, which allows the necessary information to be quickly accessed in subsequent processes.

[0514] Input: The legal information parsed in step 2.

[0515] Data processing and calculation: Data storage process in database.

[0516] Output: Saved legal information.

[0517] Step 4: Managing company-specific operational rules

[0518] The user inputs company-specific operational rules using a dedicated interface. The terminal sends the input operational rules to the server, which then stores them in the customization area.

[0519] Input: Operational rules entered by the user.

[0520] Data processing and calculation: Data transmission from the terminal to the server and storage in the database.

[0521] Output: Saved company-specific operating rules.

[0522] Step 5: Receive legal questions

[0523] The user enters a question through the interface, which the terminal then sends to the server, for example, "Is this transaction legal?"

[0524] Input: Legal challenge questions entered by the user.

[0525] Data processing and calculation: Data transmission from the terminal to the server.

[0526] Output: The query data received by the server.

[0527] Step 6: Parsing the question and generating an answer

[0528] The server analyzes the received questions using an AI analysis engine, compares them with relevant legal information and the company's operational rules, and generates an appropriate answer using a generative AI model (e.g., GPT-3).

[0529] Input: Question data received in step 5, and stored legal information and operational rules.

[0530] Data processing and calculation: Analyzing data and generating answers using AI models.

[0531] Output: The generated answer.

[0532] Step 7: Provide your answers

[0533] The server sends the generated response to the terminal and provides it to the user, for example, providing a response such as "This transaction is legal."

[0534] Input: The response data generated in step 6.

[0535] Data processing and calculation: Sending response data to the terminal.

[0536] Output: The answer provided to the user.

[0537] Step 8: Check the legality of new services

[0538] The user enters details of the new service, and the device sends them to the server, which analyzes the content of the new service and checks its legality.

[0539] Input: New service details entered by the user.

[0540] Data processing and calculation: Data transmission from the terminal to the server and comparison with legal information and operational rules.

[0541] Output: Legality check result.

[0542] Step 9: Provide legality check results

[0543] The server uses a generative AI model to explain the check results in detail and provide them to the user via their device.

[0544] Input: The legality check results parsed in step 8.

[0545] Data processing and calculation: Generative AI model generates detailed explanations.

[0546] Output: The legitimacy check result provided to the user.

[0547] Step 10: Collect emotion data

[0548] The device collects emotional data (e.g., voice tone and facial expression data) when the user enters a question or details of a new service and transmits it to the server.

[0549] Input: Emotion data collected from users.

[0550] Data processing and calculation: Collecting emotion data and sending it to the server.

[0551] Output: Emotion data received by the server.

[0552] Step 11: Analyze the emotion data

[0553] The server uses an emotion engine to analyze the emotion data and determine the user's emotional state.

[0554] Input: Emotion data collected in step 10.

[0555] Data processing and computation: Analysis of emotion data.

[0556] Output: Determined emotional state.

[0557] Step 12: Emotion-Based Response Adjustment

[0558] Based on the determined emotional state, the server uses a generative AI model to tailor the tone and content of the appropriate response, as well as determine the appropriate timing and format for notification.

[0559] Input: Emotional state determined in step 11.

[0560] Data processing and calculation: Generative AI models adjust tone and content and determine notification timing.

[0561] Output: Coordinated answers and notifications.

[0562] (Application example 2)

[0563] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0564] Modern companies often need to simultaneously comply with laws and regulations and provide emotional support. However, while traditional systems can collect and analyze legal information, they struggle to respond appropriately to users' emotional states, often resulting in delayed responses. It is also difficult to respond quickly and appropriately to security-related issues. This poses a risk of reducing a company's credibility and productivity.

[0565] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting legal information, means for analyzing the collected legal information, and means for saving the analyzed legal information. This includes means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and the company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, means for detecting and notifying new legal revision information and business improvement information, emotion recognition means for analyzing emotional states, means for adjusting the tone and content of answers based on the emotion recognition results, and means for adjusting the timing of notifications based on the emotion recognition results. This enables prompt and appropriate responses according to the user's emotional state while ensuring compliance with laws and regulations.

[0566] "Means for collecting legal information" refers to devices or software that automatically obtain the latest legal information from government agencies or public websites.

[0567] "Means for analyzing collected legal information" refers to devices or software that analyze collected legal information using artificial intelligence or natural language processing technology and extract the necessary information.

[0568] "Means for storing analyzed legal information" refers to a device or software that stores analyzed legal information in a database or the like and keeps it accessible at any time.

[0569] "Means for managing company-specific operational rules" refers to devices or software for inputting, saving, and managing operational rules established independently by a company.

[0570] The "means for receiving a question from a user" refers to a device or software that receives a question entered by a user and transmits the question to a server.

[0571] "Means for generating an answer by referring to legal information analyzed based on the received question and company-specific operational rules" refers to a device or software that analyzes the received question and generates an appropriate answer by referring to relevant legal information and company-specific operational rules.

[0572] "Means for providing a generated answer to a user" refers to a device or software that provides a generated answer to a user.

[0573] "Means for checking the legality of new services" refers to devices or software that check whether new services planned by a company are legally legal.

[0574] "Means for detecting and notifying new information on revisions to laws and regulations and business improvement information" refers to devices or software that detect the latest information on revisions to laws and regulations and business improvement information and notify related companies of this information.

[0575] "Emotion recognition means for analyzing an emotional state" refers to a device or software that analyzes the emotions of a user and determines that emotional state.

[0576] The "means for adjusting the tone and content of a response based on the emotion recognition result" refers to a device or software that appropriately adjusts the tone and content of a generated response based on the result of the emotion recognition means.

[0577] "Means for adjusting the timing of notification based on the emotion recognition result" refers to a device or software that selects and adjusts the appropriate timing for notification based on the emotion recognition result.

[0578] MODE FOR CARRYING OUT THE INVENTION

[0579] This invention is a system for simultaneously achieving corporate compliance with laws and regulations and emotional care, with a particular focus on security services. The system includes functions such as collecting, analyzing, and storing legal information, managing company-specific operational rules, analyzing emotions and adjusting responses using an emotion engine, checking the legality of new services, and providing notifications.

[0580] Overall system configuration

[0581] 1. Server

[0582] The server has the following features:

[0583] Legal information collection: Automatically collect legal information from government agencies and public websites. Use a Python scraping tool to retrieve the information and store it in a database.

[0584] Analysis and storage: The collected legal information is analyzed using an AI analysis engine, and information related to each company is extracted and stored. The AI ​​analysis engine used here is a tool with natural language processing capabilities (e.g., GPT-4).

[0585] Emotion recognition: Analyzes the user's emotional state using an emotion engine (IBM Watson Emotion Analysis API). Data is collected in real time, and the analysis results are used to generate answers and adjust notifications.

[0586] Answer generation: Uses generative AI (GPT-4 API) to generate appropriate answers to user questions.

[0587] 2. Terminal

[0588] A terminal is a device that a company's personnel uses as an interface. It has the following functions:

[0589] Input and receive: The user inputs the details of the question or new service and sends it to the server. At the same time, the user's emotional data is also collected and sent to the server.

[0590] Display and Notifications: Displays responses and notifications sent from the server, with tone and timing adjustments based on emotion.

[0591] 3. Users

[0592] The user is a company security officer who operates a terminal to check legal information and enter questions.

[0593] Legal problem solving: Enter a question to answer a legal question or check the legitimacy of a new security measure. Results are adjusted based on emotion recognition to provide answers in a reassuring tone.

[0594] Providing emotional data: When asking questions or conducting checks, emotional data is collected in real time and sent to the server.

[0595] Specific examples

[0596] 1. Collection and analysis of legal information

[0597] The server collects legal information from government agency websites, analyzes it using an AI analysis engine, and stores it in a database.

[0598] 2. Emotion-aware response adjustment

[0599] When a user types a question into a terminal, such as "What are the legal requirements for new security measures?", the server uses an emotion engine to analyze the user's emotions.

[0600] The emotion engine determines the user's anxiety and generates responses in a relaxed tone as needed. For example, the generative AI (GPT-4) generates responses such as, "When implementing new security measures, you must first ensure that the measures comply with data protection laws. It is also important to implement appropriate access controls and audit logs."

[0601] 3. Appropriate timing of notifications

[0602] The server detects new legal changes and analyzes the user's emotional data. For example, it avoids times when the user is concentrating and notifies the user when they are relaxed.

[0603] Prompt Sentence Examples

[0604] User Question: "What are the legal requirements for new security measures?"

[0605] Answer Tone: "Relaxed Tone"

[0606] answer:

[0607] This system enables companies to ensure compliance with laws and regulations while also enabling them to respond quickly and appropriately to users' emotional states, thereby improving business efficiency and user satisfaction.

[0608] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0609] Step 1:

[0610] The server collects legal information from government agencies and public websites. It uses a Python scraping tool to automatically retrieve data from websites and store it as initial data. The input data is the page content of government agency websites, and the output data is the collected legal information.

[0611] Step 2:

[0612] The server analyzes the collected legal information. Here, it uses natural language processing technology to extract necessary information and structure the legal information. Specifically, it uses generative AI models such as GPT-4 to extract and classify important regulations and amendments. The input data is the collected legal information, and the output data is the analyzed legal information.

[0613] Step 3:

[0614] The server stores the analyzed legal information in a database. The database classifies legal information relevant to each company and stores it in a state that can be accessed at any time. The input data is the analyzed legal information, and the output data is the stored legal information.

[0615] Step 4:

[0616] The user uses a terminal to input detailed information about a legal issue or a new service. The terminal sends this information to the server, and simultaneously collects and transmits the user's emotional data. The input data is the question, service details, and emotional data, and the output data is the information sent to the server.

[0617] Step 5:

[0618] The server performs analysis based on the received questions and detailed information about new services. It uses an emotion engine (IBM Watson Emotion Analysis API) to analyze the user's emotional state and generate emotion recognition results. The input data is the question, service details, and emotion data, and the output data is the emotion recognition results.

[0619] Step 6:

[0620] The server responds to questions and checks the legality of new services based on emotion recognition results. Using a generation AI (GPT-4 API), it references relevant legal information and company-specific operational rules to generate answers. The input data is the question, service details, analysis results, and emotion recognition results, and the output data is the generated answer.

[0621] Step 7:

[0622] The server adjusts the tone of the generated answer according to the user's emotion and sends it to the device. Specifically, if the user feels anxious, the server generates an answer with a relaxed tone. The input data are the generated answer and the emotion recognition result, and the output data is the tone-adjusted answer.

[0623] Step 8:

[0624] The terminal displays the tone-adjusted response sent from the server. The user uses this response to resolve legal issues and manage business operations. The input data is the tone-adjusted response, and the output data is the display on the terminal.

[0625] Step 9:

[0626] The server periodically detects new legal revision information and business improvement information and notifies relevant companies. Notifications are sent at the appropriate time based on emotion recognition results. The input data is the latest legal revision information and emotion data, and the output data is notification information sent at the appropriate time.

[0627] This processing step allows companies to respond quickly and appropriately to user sentiment while ensuring compliance with regulations.

[0628] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0629] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0630] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0631] [Second embodiment]

[0632] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0633] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0634] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0635] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0636] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0637] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0638] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0639] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0640] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0641] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0642] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0643] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0644] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: a server, a terminal, and a user.

[0645] Overall system configuration

[0646] server

[0647] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the base area, and company-specific operational rules are stored in the customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information and notifying companies.

[0648] Terminal

[0649] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[0650] User

[0651] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[0652] Program processing overview

[0653] Collection and updating of legal information

[0654] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[0655] Management of company-specific operational rules

[0656] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[0657] Support for resolving legal issues

[0658] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[0659] Checking the legality of new services

[0660] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[0661] Notification function for legal revisions and business improvements

[0662] The server detects information on legal revisions and business improvement information in real time from the collected data. It automatically analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[0663] Specific examples

[0664] 1. Collection and updating of legal information

[0665] The server periodically collects new financial laws and regulations from government agency websites using scraping technology.

[0666] The server analyzes the collected information using an AI analysis engine and stores it in a base area.

[0667] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[0668] 2. Managing company-specific operational rules

[0669] The user gives an instruction to "input new bank agency procedure rules."

[0670] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[0671] 3. Support for resolving legal issues

[0672] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[0673] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[0674] The server sends this response to the terminal and displays it to the user.

[0675] 4. Legality checks for new services

[0676] The user instructs "Enter details for new funds transfer service."

[0677] The terminal transmits the service information to the server, and the server checks the legitimacy.

[0678] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[0679] 5. Notification function for legal revisions and business improvements

[0680] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[0681] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[0682] The user receives a notification and reviews the business rules.

[0683] The above is a concrete example of the financial license supporter. This system will enable companies to rapidly develop new services while ensuring compliance with laws and regulations.

[0684] The processing flow will be explained below.

[0685] Collection and updating of legal information

[0686] Step 1:

[0687] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[0688] Step 2:

[0689] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[0690] Step 3:

[0691] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[0692] Step 4:

[0693] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[0694] Management of company-specific operational rules

[0695] Step 1:

[0696] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[0697] Step 2:

[0698] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[0699] Step 3:

[0700] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[0701] Support for resolving legal issues

[0702] Step 1:

[0703] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[0704] Step 2:

[0705] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[0706] Step 3:

[0707] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[0708] Step 4:

[0709] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[0710] Checking the legality of new services

[0711] Step 1:

[0712] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[0713] Step 2:

[0714] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[0715] Step 3:

[0716] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[0717] Step 4:

[0718] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[0719] Step 5:

[0720] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[0721] Notification function for legal revisions and business improvements

[0722] Step 1:

[0723] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[0724] Step 2:

[0725] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[0726] Step 3:

[0727] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[0728] Step 4:

[0729] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[0730] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. As a result, new services can be launched quickly and business risks can be reduced.

[0731] Example 1

[0732] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0733] To ensure that financial companies comply with laws and regulations quickly and reliably and provide new services legally, they must constantly collect and analyze the latest legal information and compare it with their own operational rules. However, collecting and analyzing legal information takes time and effort, making it difficult to keep up with modern financial laws, which are frequently revised. Furthermore, when checking individual legal issues or the legality of new services, companies must be able to efficiently and accurately refer to legal information. In this environment, a system is needed that enables companies to effectively comply with laws and regulations and smoothly deploy new services.

[0734] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0735] In this invention, the server includes: means for collecting legal information; means for automatically acquiring the collected legal information using scraping or API technology; means for inputting and analyzing the collected legal information into an AI analysis engine; means for saving the analyzed legal information in a base area; means for inputting company-specific operational rules and transmitting them from a terminal to the server; means for managing the saved company-specific operational rules; means for receiving questions from users; means for generating answers using a generative AI model by referencing the analyzed legal information and company-specific operational rules based on the received questions; means for sending the generated answers to the terminal and providing them to the user; means for users to input detailed information about new services; means for checking the legality of the input new services; and means for detecting and notifying legal revision information and business improvement information in real time. This enables companies to effectively collect and analyze the latest legal information, compare it with operational rules, and take appropriate action. Furthermore, the system can check the legality of new services and provide quick and accurate answers to individual legal issues, enabling the smooth deployment of new services while maintaining compliance with laws and regulations.

[0736] "Legal information" is a general term for information about laws, ordinances, regulations, guidelines, etc. published by government agencies and public institutions.

[0737] "Means of collection" refers to the methods and tools used to obtain the necessary data from a specific source, such as scraping tools and APIs.

[0738] "Scraping technology" refers to the technology or process of automatically extracting structured or unstructured data from a specific website.

[0739] "API technology" refers to a method of obtaining data from a specific service using an application program interface (API).

[0740] "AI analytics engine" refers to software or systems that use artificial intelligence to analyze data, including, for example, generative AI models for natural language processing.

[0741] "Base area" refers to a database or storage area for storing analyzed legal information.

[0742] "Company-specific operating rules" refer to the internal regulations and guidelines that a particular company must follow in its business operations and activities.

[0743] "Terminal" refers to a device used by a user, such as a computer or smartphone.

[0744] A "server" refers to a computer system that provides services to other devices over the Internet or a network.

[0745] A "generative AI model" is a model that uses artificial intelligence to generate appropriate output for specific inputs, such as models for natural language processing and text generation.

[0746] "Means for checking legality" refers to methods and technologies for verifying whether a new service complies with existing laws and regulations.

[0747] "Legal amendment information" refers to information on newly amended laws and regulations and newly enacted laws.

[0748] "Business improvement information" refers to information and suggestions for improving a company's business efficiency and compliance.

[0749] "Real-time detection means" refers to methods and technologies for instantly analyzing collected data and detecting changes or anomalies.

[0750] "Means of notification" refers to the method or technology used to communicate specific information to the target user, including, for example, email and push notifications.

[0751] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and rapidly develop new services. This system is composed of the following elements: a server, a terminal, and a user.

[0752] Overall system configuration

[0753] server

[0754] The server plays a central role in collecting, analyzing, and storing legal information. The server periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the "base area," while company-specific operational rules are stored in the "customization area." The server also receives questions from users, generates answers based on analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information in real time and notifying companies.

[0755] Terminal

[0756] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[0757] User

[0758] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[0759] Program processing overview

[0760] Collection and updating of legal information

[0761] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[0762] Examples:

[0763] Every Monday, the server uses scraping technology to collect new financial laws and regulations from government agency websites.

[0764] The server analyzes the collected information using an AI analysis engine (e.g., OpenAI's GPT series) and stores it in the base area.

[0765] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[0766] Management of company-specific operational rules

[0767] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[0768] Examples:

[0769] The user gives an instruction to "input new bank agency procedure rules."

[0770] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[0771] Support for resolving legal issues

[0772] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[0773] Examples:

[0774] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[0775] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[0776] The server sends this response to the terminal and displays it to the user.

[0777] Checking the legality of new services

[0778] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[0779] Examples:

[0780] The user instructs "Enter details for new funds transfer service."

[0781] The terminal transmits the service information to the server, and the server checks the legitimacy.

[0782] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[0783] Notification function for legal revisions and business improvements

[0784] The server detects information on legal revisions and business improvement information in real time from the collected data. Important revision information is automatically analyzed and customized notifications are generated for each relevant company. Users receive the notifications on their devices, check the content, and update their company's business rules and manuals.

[0785] Examples:

[0786] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[0787] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[0788] The user receives a notification and reviews the business rules.

[0789] Example prompts for generative AI models

[0790] Below are some specific examples of prompt sentences to input to the generative AI model.

[0791] "What license do I need to launch a new electronic payment service?"

[0792] "I would like to perform a legality check on a new service. Please enter the following details:..."

[0793] The above is an embodiment of the present invention, which enables financial companies to ensure compliance with laws and regulations and efficiently provide new services.

[0794] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0795] A concrete explanation of the program's processing flow

[0796] Step 1:

[0797] Collection of legal information

[0798] The server accesses designated government agency or public websites (e.g., the official Financial Services Agency website) at 2:00 a.m. every Monday.

[0799] Input: Legal information collection schedule and access URL

[0800] Specific operation: The server uses a scraping tool (e.g., Beautiful Soup, Scrapy) to collect new financial-related legal information from web pages.

[0801] Output: Raw data of the acquired legal information (HTML, JSON, etc.)

[0802] Step 2:

[0803] Analysis of information

[0804] The server inputs the collected legal information into an AI analysis engine (e.g., OpenAI's GPT series).

[0805] Input: Raw data of collected legal information

[0806] Specific operation: The server uses an AI analysis engine to analyze legal information using natural language processing, and extracts the importance of legal provisions and revision details.

[0807] Output: Analyzed legal information (e.g. legal clause, importance, revision date, etc.)

[0808] Step 3:

[0809] Data storage

[0810] The server stores the analyzed legal information in a "base area."

[0811] Input: Parsed legal information

[0812] Specific operation: The parsed information is stored in a base area using a database management system (e.g., MySQL, PostgreSQL).

[0813] Output: Updated legal information for the base region

[0814] Step 4:

[0815] Entering company-specific operational rules

[0816] Users use a dedicated interface to input company-specific operational rules.

[0817] Input: Contents of the operation rules (e.g., text, checklist format)

[0818] Specific operation: The terminal formats the input and sends it to the server.

[0819] Output: Formatted data of the operational rules

[0820] Step 5:

[0821] Data transmission and storage

[0822] The terminal transmits the input operation rules to the server.

[0823] Input: Operational rule data sent from the terminal

[0824] Specific operation: The server stores the received operational rules in the "customization area."

[0825] Output: Updated operational rules for the customization area

[0826] Step 6:

[0827] Receive questions about legal issues

[0828] The user inputs a question about a legal issue from a terminal.

[0829] Input: Questions about legal issues (e.g., "What licenses are required to launch a new electronic payment service?")

[0830] Specific operation: The terminal converts the entered question into a prompt sentence and sends it to the server.

[0831] Output: prompt statement

[0832] Step 7:

[0833] Question analysis and answer generation

[0834] The server analyzes the question and compares it with relevant legal information and company-specific operational rules.

[0835] Input: Prompt text, legal information in the base area, operational rules in the customization area

[0836] Specific operation: The server uses a generative AI model to generate the optimal answer (e.g., OpenAI GPT series).

[0837] Output: The generated answer

[0838] Step 8:

[0839] Submitting and viewing answers

[0840] The server sends the generated response to the terminal.

[0841] Input: Generated Answer

[0842] Specific operation: The server sends the answer data to the terminal, and the terminal displays the answer to the user.

[0843] Output: Answer displayed on terminal

[0844] Step 9:

[0845] Enter details of new service

[0846] The user enters the details of the new service.

[0847] Enter: New service details (e.g., "New Funds Transfer Service Details")

[0848] Specific operations: The terminal formats the information and sends it to the server.

[0849] Output: Formatted information about the new service

[0850] Step 10:

[0851] Legality analysis

[0852] The server analyzes the input for the new service and extracts any necessary licenses and legal requirements.

[0853] Input: New service details, legal information in the base area, operational rules in the customization area

[0854] Specific operation: Using a generative AI model, the system checks legal information and operational rules related to new services to confirm legality.

[0855] Output: Legality check results and required licenses

[0856] Step 11:

[0857] Sending and displaying results

[0858] The server generates the results of the legality check in the form of a report and sends it to the terminal.

[0859] Input: Legality check result

[0860] Specific operation: The generated report is sent to the terminal, and the terminal displays the report to the user.

[0861] Output: Report provided to the user

[0862] Step 12:

[0863] Detecting and notifying information on legal revisions and business improvement

[0864] The server detects information on legal revisions and business improvement in real time from the collected data and customizes notifications.

[0865] Input: Base area legal information

[0866] Specific operation: Using generative AI models and natural language processing technology, information on legal amendments and business improvement is analyzed, and notification content is generated for relevant companies.

[0867] Output: Customized notifications for each company

[0868] Step 13:

[0869] Sending and receiving notifications

[0870] The server automatically sends the generated notification, and the user receives the notification on the terminal.

[0871] Input: Generated notification content

[0872] Specific operation: The server sends notification data to the terminal, and the terminal displays the notification to the user.

[0873] Output: Notifications displayed on the device

[0874] The above is the specific processing steps of the financial license supporter system and the flow of its operation.

[0875] (Application example 1)

[0876] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0877] Adapting to rapidly changing laws and regulations and ensuring legal compliance is a major challenge for current electronic payment services. Obtaining information on legal revisions in real time and quickly adapting operations based on that information is particularly difficult. Additionally, the process of checking the legality of new services and confirming necessary licenses and legal requirements is complex and time-consuming. There is a need for a support system that can address these challenges and quickly deploy new services while complying with laws and regulations.

[0878] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0879] In this invention, the server includes a means for collecting legal information, a means for analyzing the collected legal information, and a means for automatically notifying the company of important revisions to the analyzed legal information. This allows the company to grasp the latest legal revision information in real time and adapt its business accordingly. In addition, by including a means for inputting detailed information about new services and a means for analyzing and providing the necessary licenses and legal requirements, the legality of new services can be checked quickly and reliably, enabling the rapid deployment of new services.

[0880] "Legal information" refers to information on laws, regulations, ordinances, etc., and information on amendments thereto, provided by government agencies and public institutions.

[0881] "Analysis" refers to the process of analyzing collected data and information and extracting and organizing the necessary information.

[0882] "Storing" refers to recording collected and analyzed information in a database or storage device so that it can be used later.

[0883] "Company-specific operating rules" refer to internal rules and guidelines established by a specific company for compliance with laws and regulations and business operations.

[0884] "Receiving questions" refers to receiving inquiries or confirmations from users through a device or system.

[0885] "Generating an answer" refers to creating an appropriate response to a received question or inquiry based on relevant information and data.

[0886] "Providing to the user" refers to conveying the generated answers or information to the user in an appropriate manner.

[0887] "New Services" refers to new products, services, or improved versions thereof offered by a company.

[0888] "Checking legality" refers to the process of verifying whether the services or products offered comply with current laws and regulations.

[0889] "Legal amendment information" refers to new information and amendments when existing laws and regulations are changed.

[0890] "Business improvement information" refers to information related to suggestions, advice, and best practices for improving the efficiency of corporate operations and business.

[0891] "Real-time notification" means instantly informing companies and users of the latest information and data.

[0892] "Detailed information about new services" refers to information such as specific data, features, and specifications about new services provided by a company.

[0893] "Necessary Licenses and Legal Requirements" means the permits, licenses and legal requirements that must be obtained in order to provide certain services or products.

[0894] The present invention, "Financial License Supporter System," helps financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: servers, terminals, and users.

[0895] Overall system configuration

[0896] server

[0897] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using a generative AI model. The analyzed information is stored in a base area, and company-specific operational rules are stored in a customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services.

[0898] The server also has the ability to detect legal revisions and business improvement information in real time and notify companies. Specifically, it automatically obtains legal information periodically from government agencies and public websites using scraping technology and APIs, and passes the collected information to a generative AI model for analysis. The analyzed information is stored in a database, and if important revisions are detected, relevant companies are notified.

[0899] Terminal

[0900] The terminal is the device that the user uses as an interface. The user uses the terminal to input questions and details of new services. The terminal sends this input information to the server and displays the server's response or results. For example, if a user inputs a question such as "What licenses are required to start a new electronic payment service?", the terminal sends this information to the server, and the server analyzes legal information and the company's operating rules to generate an answer, which the terminal then displays to the user.

[0901] User

[0902] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, and check the legality of new services. Furthermore, the terminal can also be used to input and update company-specific operational rules into the server. For example, when launching a new service, a user can issue an instruction to "enter detailed information about a new fund transfer service." The terminal then sends the information to the server, which checks legality and analyzes and provides the necessary licenses and legal requirements.

[0903] Hardware and software used

[0904] Hardware: Physical servers and cloud servers (e.g. AWS, GCP, Azure)

[0905] Software: Python, Flask, BeautifulSoup, requests, apscheduler, any AI analysis library (e.g. GPT-3, BERT)

[0906] Data processing and calculation

[0907] 1. Data Collection

[0908] The server periodically collects legal information from government agencies and public websites using scraping techniques using BeautifulSoup and requests.

[0909] 2. Data Analysis

[0910] The collected legal information is passed to a generative AI model on the server for analysis. The analysis results are saved in the base area. Company-specific operational rules are also saved in the customization area.

[0911] 3. Answer generation and notification

[0912] When a user asks a question, the server analyzes the legal information related to the question and the company's operating rules to generate an appropriate answer. By entering detailed information about a new service, the server checks its legality and analyzes and provides necessary licenses and legal requirements. Furthermore, if important legal revision information is detected, the server notifies relevant companies in real time.

[0913] Specific examples

[0914] Prompt Sentence Examples

[0915] "What licenses are required to launch a new electronic payment service?"

[0916] "If new legal changes are made to the prepaid payment instrument issuing industry, how will our business be affected?"

[0917] This will enable companies to rapidly roll out new services while ensuring compliance with regulations.

[0918] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0919] Step 1:

[0920] The server periodically collects legal information from government agencies and public websites. As input, it receives the target website URL and obtains legal information using scraping technology (BeautifulSoup,requests). As output, it generates a dataset of the collected legal information.

[0921] Step 2:

[0922] The server analyzes the collected legal information. As input, it passes the legal information collected in step 1 to the AI ​​analysis engine (generative AI model). As data calculation, the AI ​​model classifies the legal information into applicable legal categories and importance levels, and outputs the analysis results. As output, it saves the analyzed legal information in a base area.

[0923] Step 3:

[0924] The server receives company-specific operational rules from the user and stores them. The user inputs their company's operational rules via a terminal, and the input data is sent to the server. The server receives the operational rules entered by the user as input and stores them in a customization area. The server generates a dataset of operational rules as output.

[0925] Step 4:

[0926] The user enters questions about the licenses and legal requirements required for the new service into their device and sends them to the server. The server receives the user's question as input and analyzes it. As a data calculation, the AI ​​analysis engine generates the optimal answer to the question based on legal information and the company's operating rules. As an output, the answer is sent to the device and displayed to the user.

[0927] Step 5:

[0928] The user enters details of the new service they wish to offer into their device and sends it to the server. The server receives the details of the new service as input and checks its legality. As data calculations, the AI ​​analysis engine compares the content of the new service with legal information and analyzes the necessary licenses and legal requirements. As output, the results of the legality check are sent to the device as a report and provided to the user.

[0929] Step 6:

[0930] The server detects information on legal revisions and business improvement information in real time and notifies companies. It periodically monitors analyzed legal information as input, and generates notification information when important revisions are detected. It outputs the notification information, sending it to relevant companies in real time and displaying it on the user's device.

[0931] Step 7:

[0932] The terminal displays the entered operational rules and questions, detailed information about new services, and notifications from the server. It receives answers sent from the server, legality check results, and notification information as input, and immediately displays them to the user as output. Specifically, the user can enter a prompt to receive prompt feedback on legality and questions.

[0933] The above are the specific processing steps of the program for the system that realizes the application example.

[0934] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0935] The present invention is a system that not only helps financial companies ensure compliance with laws and regulations and quickly launch new services, but also recognizes users' emotions and provides appropriate responses. Below, we will specifically explain an embodiment of the invention that combines an emotion engine.

[0936] Overall system configuration

[0937] server

[0938] The server plays a central role in collecting, analyzing, and storing legal information. It also uses an emotion engine to analyze users' emotions and adjust the content of responses and notifications.

[0939] Terminal

[0940] The terminal is a device that the user uses as an interface. The user inputs questions from the terminal and receives answers and notifications from the server. The terminal also collects the user's emotional data and sends it to the server.

[0941] User

[0942] The users are financial business personnel. They operate the terminal to check legal information, input questions, check the legality of new services, etc. The user's emotional data is also analyzed, and the system adjusts the response accordingly.

[0943] Program processing overview

[0944] Collection and updating of legal information

[0945] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs. It then analyzes the collected legal information using an AI analysis engine and stores it in a base area. When it detects important legal amendments or new regulatory information, it sends notifications to relevant companies.

[0946] Management of company-specific operational rules

[0947] The user inputs company-specific operational rules using a dedicated interface. The terminal sends the input operational rules to the server, which then stores them in a customization area.

[0948] Support for resolving legal issues

[0949] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and the AI ​​generates an appropriate answer. The answer is then provided to the user via the device.

[0950] Checking the legality of new services

[0951] When a user enters details of a new service, the device sends them to the server. The server checks the legality of the new service by comparing it with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements, and sends the check results and details to the device for provision to the user.

[0952] Notification function for legal revisions and business improvements

[0953] The server detects information on legal revisions and business improvement information in real time from the collected data. It analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[0954] Emotion recognition and response adjustment

[0955] Emotion Engine

[0956] The emotion engine has the function to recognize and analyze the user's emotions. When the user enters a question or details of a new service, the device simultaneously collects the user's emotion data and sends it to the server.

[0957] Emotion recognition processing

[0958] Step 1

[0959] The server uses an emotion engine to analyze the emotion data sent by the user and determine their current emotional state. For example, if the user is feeling anxious or stressed, the server generates an analysis result that reflects that.

[0960] Emotion-based response adjustment

[0961] Step 2

[0962] The server adjusts the tone and content of the appropriate response based on the perceived emotion, for example, providing a more relaxed tone of response if the user is feeling stressed.

[0963] Emotion-based notification timing

[0964] Step 3

[0965] The server then selects the appropriate timing and format for notifications based on the emotion recognition results. For example, it can avoid notifications when the user is concentrating and send notifications when the user is relaxed.

[0966] Specific examples

[0967] 1. Emotion-aware response adjustment

[0968] When a user types a question such as "What are the licensing requirements for new electronic payment services?", the terminal collects the user's sentiment.

[0969] The server uses an emotion engine to determine the user's anxiety and generates a response in a stress-reducing tone, saying, "A license for electronic payment services is required."

[0970] The server sends this response to the terminal and provides it to the user.

[0971] 2. Emotion-aware notification adjustment

[0972] When the server detects new legal amendments and prepares to notify relevant companies, it also analyzes user emotional data.

[0973] The server takes into account the user's emotional state and sends a notification that "there are new legal changes" at an appropriate time.

[0974] 3. Legality checks for new services and emotional responses

[0975] When a user enters details of a new service and the device sends them to the server, emotional data is also collected at the same time.

[0976] The server uses an emotion engine to recognize the user's state of excitement and generates a report on the legality of the service, along with a detailed and reassuring explanation.

[0977] The server sends this report to the terminal and provides it to the user.

[0978] The system enables businesses to respond to users' emotional states while ensuring compliance, improving operational efficiency and customer satisfaction, while also enabling the rapid launch of new services and reducing business risks.

[0979] The processing flow will be explained below.

[0980] Processing flow of a system that combines emotion engines

[0981] Collection and updating of legal information

[0982] Step 1:

[0983] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[0984] Step 2:

[0985] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[0986] Step 3:

[0987] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[0988] Step 4:

[0989] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[0990] Management of company-specific operational rules

[0991] Step 1:

[0992] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[0993] Step 2:

[0994] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[0995] Step 3:

[0996] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[0997] Support for resolving legal issues

[0998] Step 1:

[0999] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[1000] Step 2:

[1001] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[1002] Step 3:

[1003] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[1004] Step 4:

[1005] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[1006] Checking the legality of new services

[1007] Step 1:

[1008] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[1009] Step 2:

[1010] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[1011] Step 3:

[1012] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[1013] Step 4:

[1014] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[1015] Step 5:

[1016] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[1017] Notification function for legal revisions and business improvements

[1018] Step 1:

[1019] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[1020] Step 2:

[1021] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[1022] Step 3:

[1023] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[1024] Step 4:

[1025] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[1026] Emotion recognition and response adjustment process flow

[1027] Emotion recognition processing

[1028] Step 1:

[1029] When a user enters a question or details of a new service through the device, the device simultaneously collects emotional data, such as facial expressions, tone of voice, and heart rate, using a camera, microphone, and sensors.

[1030] Step 2:

[1031] The device sends the collected emotion data to a server, where the data is formatted and adjusted so that it can be analyzed by the emotion engine.

[1032] Step 3:

[1033] The server analyzes the emotion data through an emotion engine to determine the user's current emotional state, for example, identifying emotions such as stress, anxiety, and relaxation.

[1034] Emotion-based response adjustment

[1035] Step 1:

[1036] The server adjusts the tone and content of responses and notifications based on the analysis results. For example, if the user is feeling stressed, it will adopt a polite and friendly tone to help them relax.

[1037] Step 2:

[1038] The server generates a response or notification based on the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the server may provide a message such as, "Don't worry. There will be no problem if you obtain a license for electronic payment services."

[1039] Adjusting notification timing based on emotions

[1040] Step 1:

[1041] The server selects the appropriate timing for notifications based on the user's emotional state, for example, when the user is relaxing or has free time at work.

[1042] Step 2:

[1043] The server generates a notification at an appropriate time and sends it to the device. By notifying the user that "there are new revisions to the law" during a time when the user is relaxing, the information is received effectively.

[1044] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. Furthermore, the system can respond according to the user's emotional state, improving business efficiency and user satisfaction, enabling the rapid launch of new services and reducing business risks.

[1045] Example 2

[1046] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1047] In modern financial operations, legal compliance is an important issue for companies, but it is difficult to quickly collect and analyze frequently updated legal information. There is also a need to check the legality of new services and provide prompt answers to legal issues. Furthermore, it is also necessary to recognize user emotions and respond appropriately based on them. However, no system currently exists that can meet these diverse requirements. Therefore, there is a need for a system that integrates the collection, analysis, and notification of legal information, the legality check of new services, and the user emotion recognition functions.

[1048] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1049] In this invention, the server includes means for collecting legal information, means for analyzing the collected legal information, means for saving the analyzed legal information, means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, means for detecting and notifying new legal revision information and business improvement information, means for collecting user emotional data, means for analyzing the collected emotional data to determine the user's emotional state, means for adjusting the tone and content of the answer based on the determined emotional state, and means for selecting the appropriate timing and format of notifications. This enables support for legal compliance, rapid launch of new services, optimization of company operational rules, and optimal responses according to the user's emotional state.

[1050] "Legal Information" refers to laws, regulations, and amendments thereto published by government agencies and public websites.

[1051] "Analyzing" refers to the process of classifying and interpreting collected legal information using machine learning models and natural language processing technology.

[1052] "Storing" refers to storing the analyzed data in a designated database or storage system.

[1053] "Company-specific operating rules" refer to specific business processes and standards established internally by a company.

[1054] "Receiving a question" refers to the server receiving a question or information request sent by a user via a terminal.

[1055] "Generating an answer" refers to the process of generating an appropriate response based on the received question, by referring to relevant legal information and company-specific operational rules.

[1056] "Checking legality" refers to the process of verifying whether a new service or product complies with current laws and regulations.

[1057] "Emotional data" refers to data that indicates a user's emotional state, such as data collected from the user's tone of voice, facial expression, and tone of writing.

[1058] "Determining emotional state" refers to identifying the psychological state the user is currently experiencing based on the collected emotional data.

[1059] "Adjusting the tone and content of your response" refers to appropriately changing the tone and wording of your response based on your determined emotional state.

[1060] "Selecting the appropriate timing and format for notifications" refers to determining the best time and method for sending notifications, taking into account emotional data and work schedules.

[1061] A "generative AI model" refers to an artificial intelligence system that generates natural language text based on input data.

[1062] The present invention is a system that not only helps financial companies ensure compliance with laws and regulations and quickly launch new services, but also recognizes users' emotions and provides appropriate responses. Specific embodiments of this system are described below.

[1063] Overall system configuration

[1064] The system mainly consists of three elements: a server, a terminal, and a user.

[1065] server

[1066] The server plays a central role in collecting, analyzing, and storing legal information. It also has the ability to analyze user sentiment using an emotion engine and adjust the content of responses and notifications. To do this, the server collects legal information through scraping technologies (e.g., Beautiful Soup or Scrapy) or API access, analyzes the data using an AI analysis engine (e.g., TensorFlow or Scikit-learn), and generates responses using a generative AI model (e.g., GPT-3).

[1067] Terminal

[1068] The device is the interface used by the user. The user inputs questions through the device and receives answers and notifications from the server. The device also collects the user's emotional data (e.g., voice tone and facial expression data) and sends it to the server. For this purpose, the device is equipped with hardware such as a microphone and a camera.

[1069] User

[1070] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. The information and emotional data entered by the user are sent to the server via the terminal, and the analyzed results are provided.

[1071] Procedures for collecting and updating legal information

[1072] The server periodically collects legal information from government agencies and public websites using scraping technologies such as Python's Beautiful Soup and Scrapy, as well as the government's public API. The collected information is analyzed using an AI analysis engine using TensorFlow and Scikit-learn, and then stored in a base area.

[1073] Examples:

[1074] The user checks the updated status of legal information from the terminal.

[1075] The server collects legal information and checks for updates.

[1076] Send a notification to the user saying, "The latest financial regulations have been updated."

[1077] Example prompt:

[1078] "Collect the latest legal information and inform companies."

[1079] Management procedures for company-specific operational rules

[1080] The user inputs the company's unique operational rules using a dedicated interface and sends them to the server via the terminal. The server saves the input operational rules in the customization area.

[1081] Examples:

[1082] The user enters the "company's internal rules" from the terminal.

[1083] The terminal transmits the input information to the server, which stores it in the customization area.

[1084] Example prompt:

[1085] Enter your company's internal rules and save them in the customization area.

[1086] Legal issue resolution support procedures

[1087] When a user inputs a question or inquiry into their device, the device sends it to the server. The server analyzes the question using TensorFlow and Scikit-learn, compares it with relevant legal information and the company's operational rules, and generates an appropriate answer. The generated answer is then provided to the user via the device.

[1088] Examples:

[1089] The user types into the terminal, "Is this transaction legitimate?"

[1090] The server compares the legal information with the company's operating rules and responds, "This transaction is legal."

[1091] Example prompt:

[1092] "Analyze user questions, compare legal information and operational rules, and generate answers."

[1093] Procedures for checking the legality of new services

[1094] When a user enters details of a new service, the device sends them to the server, which checks the legality of the new service by comparing it with the information in the base and customization areas. The generative AI model extracts any necessary licenses or legal requirements, and sends the check results and details to the device for presentation to the user.

[1095] Examples:

[1096] The user enters the details of the new payment service into the terminal.

[1097] The server parses the input, extracts any necessary licenses and legal requirements, and generates a report.

[1098] Example prompt:

[1099] "Please analyze the details of the new service and check the legal requirements and legality."

[1100] Emotion recognition and response adjustment procedures

[1101] When a user enters details of a question or new service, the device collects emotional data and sends it to the server. The server then analyzes the data using an emotion engine to determine the user's emotional state. Based on the determined emotional state, the generative AI model adjusts the tone and content of the appropriate response and delivers it to the user via the device. It also determines the appropriate timing and format for notification.

[1102] Examples:

[1103] A user types a question: "What are the licensing requirements for new electronic payment services?"

[1104] The server analyzes the user's emotions and responds in a relaxed tone.

[1105] Example prompt:

[1106] "Analyze user sentiment data and generate appropriate responses."

[1107] The system enables businesses to improve operational efficiency and customer satisfaction by providing responses that respond to users' emotional states while ensuring compliance with regulations.

[1108] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1109] Step 1: Gather legal information

[1110] The server periodically collects legal information from government agencies and public websites using scraping technologies such as Python's Beautiful Soup and Scrapy, as well as public APIs, to obtain the latest legal information.

[1111] Input: URL of a government or public website.

[1112] Data processing and calculation: Data acquisition using scraping technology and APIs.

[1113] Output: Raw data of the legal information obtained.

[1114] Step 2: Analyzing legal information

[1115] The server analyzes the collected legal information using an AI analysis engine (such as TensorFlow or Scikit-learn) to classify the type and content of the law. As a result of the analysis, important parts of the law are extracted.

[1116] Input: Raw legal information collected in step 1.

[1117] Data processing and calculation: Classifying data and extracting important parts.

[1118] Output: Parsed legal information.

[1119] Step 3: Save legal information

[1120] The server stores the analyzed legal information in the base area of ​​the database, which allows the necessary information to be quickly accessed in subsequent processes.

[1121] Input: The legal information parsed in step 2.

[1122] Data processing and calculation: Data storage process in database.

[1123] Output: Saved legal information.

[1124] Step 4: Managing company-specific operational rules

[1125] The user inputs company-specific operational rules using a dedicated interface. The terminal sends the input operational rules to the server, which then stores them in the customization area.

[1126] Input: Operational rules entered by the user.

[1127] Data processing and calculation: Data transmission from the terminal to the server and storage in the database.

[1128] Output: Saved company-specific operating rules.

[1129] Step 5: Receive legal questions

[1130] The user enters a question through the interface, which the terminal then sends to the server, for example, "Is this transaction legal?"

[1131] Input: Legal challenge questions entered by the user.

[1132] Data processing and calculation: Data transmission from the terminal to the server.

[1133] Output: The query data received by the server.

[1134] Step 6: Parsing the question and generating an answer

[1135] The server analyzes the received questions using an AI analysis engine, compares them with relevant legal information and the company's operational rules, and generates an appropriate answer using a generative AI model (e.g., GPT-3).

[1136] Input: Question data received in step 5, and stored legal information and operational rules.

[1137] Data processing and calculation: Analyzing data and generating answers using AI models.

[1138] Output: The generated answer.

[1139] Step 7: Provide your answers

[1140] The server sends the generated response to the terminal and provides it to the user, for example, providing a response such as "This transaction is legal."

[1141] Input: The response data generated in step 6.

[1142] Data processing and calculation: Sending response data to the terminal.

[1143] Output: The answer provided to the user.

[1144] Step 8: Check the legality of new services

[1145] The user enters details of the new service, and the device sends them to the server, which analyzes the content of the new service and checks its legality.

[1146] Input: New service details entered by the user.

[1147] Data processing and calculation: Data transmission from the terminal to the server and comparison with legal information and operational rules.

[1148] Output: Legality check result.

[1149] Step 9: Provide legality check results

[1150] The server uses a generative AI model to explain the check results in detail and provide them to the user via their device.

[1151] Input: The legality check results parsed in step 8.

[1152] Data processing and calculation: Generative AI model generates detailed explanations.

[1153] Output: The legitimacy check result provided to the user.

[1154] Step 10: Collect emotion data

[1155] The device collects emotional data (e.g., voice tone and facial expression data) when the user enters a question or details of a new service and transmits it to the server.

[1156] Input: Emotion data collected from users.

[1157] Data processing and calculation: Collecting emotion data and sending it to the server.

[1158] Output: Emotion data received by the server.

[1159] Step 11: Analyze the emotion data

[1160] The server uses an emotion engine to analyze the emotion data and determine the user's emotional state.

[1161] Input: Emotion data collected in step 10.

[1162] Data processing and computation: Analysis of emotion data.

[1163] Output: Determined emotional state.

[1164] Step 12: Emotion-Based Response Adjustment

[1165] Based on the determined emotional state, the server uses a generative AI model to tailor the tone and content of the appropriate response, as well as determine the appropriate timing and format for notification.

[1166] Input: Emotional state determined in step 11.

[1167] Data processing and calculation: Generative AI models adjust tone and content and determine notification timing.

[1168] Output: Coordinated answers and notifications.

[1169] (Application example 2)

[1170] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1171] Modern companies often need to simultaneously comply with laws and regulations and provide emotional support. However, while traditional systems can collect and analyze legal information, they struggle to respond appropriately to users' emotional states, often resulting in delayed responses. It is also difficult to respond quickly and appropriately to security-related issues. This poses a risk of reducing a company's credibility and productivity.

[1172] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting legal information, means for analyzing the collected legal information, and means for saving the analyzed legal information. This includes means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and the company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, means for detecting and notifying new legal revision information and business improvement information, emotion recognition means for analyzing emotional states, means for adjusting the tone and content of answers based on the emotion recognition results, and means for adjusting the timing of notifications based on the emotion recognition results. This enables prompt and appropriate responses according to the user's emotional state while ensuring compliance with laws and regulations.

[1173] "Means for collecting legal information" refers to devices or software that automatically obtain the latest legal information from government agencies or public websites.

[1174] "Means for analyzing collected legal information" refers to devices or software that analyze collected legal information using artificial intelligence or natural language processing technology and extract the necessary information.

[1175] "Means for storing analyzed legal information" refers to a device or software that stores analyzed legal information in a database or the like and keeps it accessible at any time.

[1176] "Means for managing company-specific operational rules" refers to devices or software for inputting, saving, and managing operational rules established independently by a company.

[1177] The "means for receiving a question from a user" refers to a device or software that receives a question entered by a user and transmits the question to a server.

[1178] "Means for generating an answer by referring to legal information analyzed based on the received question and company-specific operational rules" refers to a device or software that analyzes the received question and generates an appropriate answer by referring to relevant legal information and company-specific operational rules.

[1179] "Means for providing a generated answer to a user" refers to a device or software that provides a generated answer to a user.

[1180] "Means for checking the legality of new services" refers to devices or software that check whether new services planned by a company are legally legal.

[1181] "Means for detecting and notifying new information on revisions to laws and regulations and business improvement information" refers to devices or software that detect the latest information on revisions to laws and regulations and business improvement information and notify related companies of this information.

[1182] "Emotion recognition means for analyzing an emotional state" refers to a device or software that analyzes the emotions of a user and determines that emotional state.

[1183] The "means for adjusting the tone and content of a response based on the emotion recognition result" refers to a device or software that appropriately adjusts the tone and content of a generated response based on the result of the emotion recognition means.

[1184] "Means for adjusting the timing of notification based on the emotion recognition result" refers to a device or software that selects and adjusts the appropriate timing for notification based on the emotion recognition result.

[1185] MODE FOR CARRYING OUT THE INVENTION

[1186] This invention is a system for simultaneously achieving corporate compliance with laws and regulations and emotional care, with a particular focus on security services. The system includes functions such as collecting, analyzing, and storing legal information, managing company-specific operational rules, analyzing emotions and adjusting responses using an emotion engine, checking the legality of new services, and providing notifications.

[1187] Overall system configuration

[1188] 1. Server

[1189] The server has the following features:

[1190] Legal information collection: Automatically collect legal information from government agencies and public websites. Use a Python scraping tool to retrieve the information and store it in a database.

[1191] Analysis and storage: The collected legal information is analyzed using an AI analysis engine, and information related to each company is extracted and stored. The AI ​​analysis engine used here is a tool with natural language processing capabilities (e.g., GPT-4).

[1192] Emotion recognition: Analyzes the user's emotional state using an emotion engine (IBM Watson Emotion Analysis API). Data is collected in real time, and the analysis results are used to generate answers and adjust notifications.

[1193] Answer generation: Uses generative AI (GPT-4 API) to generate appropriate answers to user questions.

[1194] 2. Terminal

[1195] A terminal is a device that a company's personnel uses as an interface. It has the following functions:

[1196] Input and receive: The user inputs the details of the question or new service and sends it to the server. At the same time, the user's emotional data is also collected and sent to the server.

[1197] Display and Notifications: Displays responses and notifications sent from the server, with tone and timing adjustments based on emotion.

[1198] 3. Users

[1199] The user is a company security officer who operates a terminal to check legal information and enter questions.

[1200] Legal problem solving: Enter a question to answer a legal question or check the legitimacy of a new security measure. Results are adjusted based on emotion recognition to provide answers in a reassuring tone.

[1201] Providing emotional data: When asking questions or conducting checks, emotional data is collected in real time and sent to the server.

[1202] Specific examples

[1203] 1. Collection and analysis of legal information

[1204] The server collects legal information from government agency websites, analyzes it using an AI analysis engine, and stores it in a database.

[1205] 2. Emotion-aware response adjustment

[1206] When a user types a question into a terminal, such as "What are the legal requirements for new security measures?", the server uses an emotion engine to analyze the user's emotions.

[1207] The emotion engine determines the user's anxiety and generates responses in a relaxed tone as needed. For example, the generative AI (GPT-4) generates responses such as, "When implementing new security measures, you must first ensure that the measures comply with data protection laws. It is also important to implement appropriate access controls and audit logs."

[1208] 3. Appropriate timing of notifications

[1209] The server detects new legal changes and analyzes the user's emotional data. For example, it avoids times when the user is concentrating and notifies the user when they are relaxed.

[1210] Prompt Sentence Examples

[1211] User Question: "What are the legal requirements for new security measures?"

[1212] Answer Tone: "Relaxed Tone"

[1213] answer:

[1214] This system enables companies to ensure compliance with laws and regulations while also enabling them to respond quickly and appropriately to users' emotional states, thereby improving business efficiency and user satisfaction.

[1215] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1216] Step 1:

[1217] The server collects legal information from government agencies and public websites. It uses a Python scraping tool to automatically retrieve data from websites and store it as initial data. The input data is the page content of government agency websites, and the output data is the collected legal information.

[1218] Step 2:

[1219] The server analyzes the collected legal information. Here, it uses natural language processing technology to extract necessary information and structure the legal information. Specifically, it uses generative AI models such as GPT-4 to extract and classify important regulations and amendments. The input data is the collected legal information, and the output data is the analyzed legal information.

[1220] Step 3:

[1221] The server stores the analyzed legal information in a database. The database classifies legal information relevant to each company and stores it in a state that can be accessed at any time. The input data is the analyzed legal information, and the output data is the stored legal information.

[1222] Step 4:

[1223] The user uses a terminal to input detailed information about a legal issue or a new service. The terminal sends this information to the server, and simultaneously collects and transmits the user's emotional data. The input data is the question, service details, and emotional data, and the output data is the information sent to the server.

[1224] Step 5:

[1225] The server performs analysis based on the received questions and detailed information about new services. It uses an emotion engine (IBM Watson Emotion Analysis API) to analyze the user's emotional state and generate emotion recognition results. The input data is the question, service details, and emotion data, and the output data is the emotion recognition results.

[1226] Step 6:

[1227] The server responds to questions and checks the legality of new services based on emotion recognition results. Using a generation AI (GPT-4 API), it references relevant legal information and company-specific operational rules to generate answers. The input data is the question, service details, analysis results, and emotion recognition results, and the output data is the generated answer.

[1228] Step 7:

[1229] The server adjusts the tone of the generated answer according to the user's emotion and sends it to the device. Specifically, if the user feels anxious, the server generates an answer with a relaxed tone. The input data are the generated answer and the emotion recognition result, and the output data is the tone-adjusted answer.

[1230] Step 8:

[1231] The terminal displays the tone-adjusted response sent from the server. The user uses this response to resolve legal issues and manage business operations. The input data is the tone-adjusted response, and the output data is the display on the terminal.

[1232] Step 9:

[1233] The server periodically detects new legal revision information and business improvement information and notifies relevant companies. Notifications are sent at the appropriate time based on emotion recognition results. The input data is the latest legal revision information and emotion data, and the output data is notification information sent at the appropriate time.

[1234] This processing step allows companies to respond quickly and appropriately to user sentiment while ensuring compliance with regulations.

[1235] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1236] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1237] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1238] [Third embodiment]

[1239] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1240] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1241] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1242] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1243] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1244] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1245] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1246] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1247] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1248] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1249] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1250] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1251] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: a server, a terminal, and a user.

[1252] Overall system configuration

[1253] server

[1254] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the base area, and company-specific operational rules are stored in the customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information and notifying companies.

[1255] Terminal

[1256] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[1257] User

[1258] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[1259] Program processing overview

[1260] Collection and updating of legal information

[1261] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[1262] Management of company-specific operational rules

[1263] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[1264] Support for resolving legal issues

[1265] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[1266] Checking the legality of new services

[1267] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[1268] Notification function for legal revisions and business improvements

[1269] The server detects information on legal revisions and business improvement information in real time from the collected data. It automatically analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[1270] Specific examples

[1271] 1. Collection and updating of legal information

[1272] The server periodically collects new financial laws and regulations from government agency websites using scraping technology.

[1273] The server analyzes the collected information using an AI analysis engine and stores it in a base area.

[1274] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[1275] 2. Managing company-specific operational rules

[1276] The user gives an instruction to "input new bank agency procedure rules."

[1277] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[1278] 3. Support for resolving legal issues

[1279] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[1280] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[1281] The server sends this response to the terminal and displays it to the user.

[1282] 4. Legality checks for new services

[1283] The user instructs "Enter details for new funds transfer service."

[1284] The terminal transmits the service information to the server, and the server checks the legitimacy.

[1285] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[1286] 5. Notification function for legal revisions and business improvements

[1287] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[1288] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[1289] The user receives a notification and reviews the business rules.

[1290] The above is a concrete example of the financial license supporter. This system will enable companies to rapidly develop new services while ensuring compliance with laws and regulations.

[1291] The processing flow will be explained below.

[1292] Collection and updating of legal information

[1293] Step 1:

[1294] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[1295] Step 2:

[1296] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[1297] Step 3:

[1298] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[1299] Step 4:

[1300] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[1301] Management of company-specific operational rules

[1302] Step 1:

[1303] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[1304] Step 2:

[1305] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[1306] Step 3:

[1307] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[1308] Support for resolving legal issues

[1309] Step 1:

[1310] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[1311] Step 2:

[1312] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[1313] Step 3:

[1314] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[1315] Step 4:

[1316] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[1317] Checking the legality of new services

[1318] Step 1:

[1319] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[1320] Step 2:

[1321] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[1322] Step 3:

[1323] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[1324] Step 4:

[1325] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[1326] Step 5:

[1327] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[1328] Notification function for legal revisions and business improvements

[1329] Step 1:

[1330] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[1331] Step 2:

[1332] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[1333] Step 3:

[1334] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[1335] Step 4:

[1336] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[1337] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. As a result, new services can be launched quickly and business risks can be reduced.

[1338] Example 1

[1339] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1340] To ensure that financial companies comply with laws and regulations quickly and reliably and provide new services legally, they must constantly collect and analyze the latest legal information and compare it with their own operational rules. However, collecting and analyzing legal information takes time and effort, making it difficult to keep up with modern financial laws, which are frequently revised. Furthermore, when checking individual legal issues or the legality of new services, companies must be able to efficiently and accurately refer to legal information. In this environment, a system is needed that enables companies to effectively comply with laws and regulations and smoothly deploy new services.

[1341] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1342] In this invention, the server includes: means for collecting legal information; means for automatically acquiring the collected legal information using scraping or API technology; means for inputting and analyzing the collected legal information into an AI analysis engine; means for saving the analyzed legal information in a base area; means for inputting company-specific operational rules and transmitting them from a terminal to the server; means for managing the saved company-specific operational rules; means for receiving questions from users; means for generating answers using a generative AI model by referencing the analyzed legal information and company-specific operational rules based on the received questions; means for sending the generated answers to the terminal and providing them to the user; means for users to input detailed information about new services; means for checking the legality of the input new services; and means for detecting and notifying legal revision information and business improvement information in real time. This enables companies to effectively collect and analyze the latest legal information, compare it with operational rules, and take appropriate action. Furthermore, the system can check the legality of new services and provide quick and accurate answers to individual legal issues, enabling the smooth deployment of new services while maintaining compliance with laws and regulations.

[1343] "Legal information" is a general term for information about laws, ordinances, regulations, guidelines, etc. published by government agencies and public institutions.

[1344] "Means of collection" refers to the methods and tools used to obtain the necessary data from a specific source, such as scraping tools and APIs.

[1345] "Scraping technology" refers to the technology or process of automatically extracting structured or unstructured data from a specific website.

[1346] "API technology" refers to a method of obtaining data from a specific service using an application program interface (API).

[1347] "AI analytics engine" refers to software or systems that use artificial intelligence to analyze data, including, for example, generative AI models for natural language processing.

[1348] "Base area" refers to a database or storage area for storing analyzed legal information.

[1349] "Company-specific operating rules" refer to the internal regulations and guidelines that a particular company must follow in its business operations and activities.

[1350] "Terminal" refers to a device used by a user, such as a computer or smartphone.

[1351] A "server" refers to a computer system that provides services to other devices over the Internet or a network.

[1352] A "generative AI model" is a model that uses artificial intelligence to generate appropriate output for specific inputs, such as models for natural language processing and text generation.

[1353] "Means for checking legality" refers to methods and technologies for verifying whether a new service complies with existing laws and regulations.

[1354] "Legal amendment information" refers to information on newly amended laws and regulations and newly enacted laws.

[1355] "Business improvement information" refers to information and suggestions for improving a company's business efficiency and compliance.

[1356] "Real-time detection means" refers to methods and technologies for instantly analyzing collected data and detecting changes or anomalies.

[1357] "Means of notification" refers to the method or technology used to communicate specific information to the target user, including, for example, email and push notifications.

[1358] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and rapidly develop new services. This system is composed of the following elements: a server, a terminal, and a user.

[1359] Overall system configuration

[1360] server

[1361] The server plays a central role in collecting, analyzing, and storing legal information. The server periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the "base area," while company-specific operational rules are stored in the "customization area." The server also receives questions from users, generates answers based on analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information in real time and notifying companies.

[1362] Terminal

[1363] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[1364] User

[1365] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[1366] Program processing overview

[1367] Collection and updating of legal information

[1368] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[1369] Examples:

[1370] Every Monday, the server uses scraping technology to collect new financial laws and regulations from government agency websites.

[1371] The server analyzes the collected information using an AI analysis engine (e.g., OpenAI's GPT series) and stores it in the base area.

[1372] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[1373] Management of company-specific operational rules

[1374] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[1375] Examples:

[1376] The user gives an instruction to "input new bank agency procedure rules."

[1377] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[1378] Support for resolving legal issues

[1379] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[1380] Examples:

[1381] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[1382] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[1383] The server sends this response to the terminal and displays it to the user.

[1384] Checking the legality of new services

[1385] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[1386] Examples:

[1387] The user instructs "Enter details for new funds transfer service."

[1388] The terminal transmits the service information to the server, and the server checks the legitimacy.

[1389] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[1390] Notification function for legal revisions and business improvements

[1391] The server detects information on legal revisions and business improvement information in real time from the collected data. Important revision information is automatically analyzed and customized notifications are generated for each relevant company. Users receive the notifications on their devices, check the content, and update their company's business rules and manuals.

[1392] Examples:

[1393] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[1394] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[1395] The user receives a notification and reviews the business rules.

[1396] Example prompts for generative AI models

[1397] Below are some specific examples of prompt sentences to input to the generative AI model.

[1398] "What license do I need to launch a new electronic payment service?"

[1399] "I would like to perform a legality check on a new service. Please enter the following details:..."

[1400] The above is an embodiment of the present invention, which enables financial companies to ensure compliance with laws and regulations and efficiently provide new services.

[1401] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1402] A concrete explanation of the program's processing flow

[1403] Step 1:

[1404] Collection of legal information

[1405] The server accesses designated government agency or public websites (e.g., the official Financial Services Agency website) at 2:00 a.m. every Monday.

[1406] Input: Legal information collection schedule and access URL

[1407] Specific operation: The server uses a scraping tool (e.g., Beautiful Soup, Scrapy) to collect new financial-related legal information from web pages.

[1408] Output: Raw data of the acquired legal information (HTML, JSON, etc.)

[1409] Step 2:

[1410] Analysis of information

[1411] The server inputs the collected legal information into an AI analysis engine (e.g., OpenAI's GPT series).

[1412] Input: Raw data of collected legal information

[1413] Specific operation: The server uses an AI analysis engine to analyze legal information using natural language processing, and extracts the importance of legal provisions and revision details.

[1414] Output: Analyzed legal information (e.g. legal clause, importance, revision date, etc.)

[1415] Step 3:

[1416] Data storage

[1417] The server stores the analyzed legal information in a "base area."

[1418] Input: Parsed legal information

[1419] Specific operation: The parsed information is stored in a base area using a database management system (e.g., MySQL, PostgreSQL).

[1420] Output: Updated legal information for the base region

[1421] Step 4:

[1422] Entering company-specific operational rules

[1423] Users use a dedicated interface to input company-specific operational rules.

[1424] Input: Contents of the operation rules (e.g., text, checklist format)

[1425] Specific operation: The terminal formats the input and sends it to the server.

[1426] Output: Formatted data of the operational rules

[1427] Step 5:

[1428] Data transmission and storage

[1429] The terminal transmits the input operation rules to the server.

[1430] Input: Operational rule data sent from the terminal

[1431] Specific operation: The server stores the received operational rules in the "customization area."

[1432] Output: Updated operational rules for the customization area

[1433] Step 6:

[1434] Receive questions about legal issues

[1435] The user inputs a question about a legal issue from a terminal.

[1436] Input: Questions about legal issues (e.g., "What licenses are required to launch a new electronic payment service?")

[1437] Specific operation: The terminal converts the entered question into a prompt sentence and sends it to the server.

[1438] Output: prompt statement

[1439] Step 7:

[1440] Question analysis and answer generation

[1441] The server analyzes the question and compares it with relevant legal information and company-specific operational rules.

[1442] Input: Prompt text, legal information in the base area, operational rules in the customization area

[1443] Specific operation: The server uses a generative AI model to generate the optimal answer (e.g., OpenAI GPT series).

[1444] Output: The generated answer

[1445] Step 8:

[1446] Submitting and viewing answers

[1447] The server sends the generated response to the terminal.

[1448] Input: Generated Answer

[1449] Specific operation: The server sends the answer data to the terminal, and the terminal displays the answer to the user.

[1450] Output: Answer displayed on terminal

[1451] Step 9:

[1452] Enter details of new service

[1453] The user enters the details of the new service.

[1454] Enter: New service details (e.g., "New Funds Transfer Service Details")

[1455] Specific operations: The terminal formats the information and sends it to the server.

[1456] Output: Formatted information about the new service

[1457] Step 10:

[1458] Legality analysis

[1459] The server analyzes the input for the new service and extracts any necessary licenses and legal requirements.

[1460] Input: New service details, legal information in the base area, operational rules in the customization area

[1461] Specific operation: Using a generative AI model, the system checks legal information and operational rules related to new services to confirm legality.

[1462] Output: Legality check results and required licenses

[1463] Step 11:

[1464] Sending and displaying results

[1465] The server generates the results of the legality check in the form of a report and sends it to the terminal.

[1466] Input: Legality check result

[1467] Specific operation: The generated report is sent to the terminal, and the terminal displays the report to the user.

[1468] Output: Report provided to the user

[1469] Step 12:

[1470] Detecting and notifying information on legal revisions and business improvement

[1471] The server detects information on legal revisions and business improvement in real time from the collected data and customizes notifications.

[1472] Input: Base area legal information

[1473] Specific operation: Using generative AI models and natural language processing technology, information on legal amendments and business improvement is analyzed, and notification content is generated for relevant companies.

[1474] Output: Customized notifications for each company

[1475] Step 13:

[1476] Sending and receiving notifications

[1477] The server automatically sends the generated notification, and the user receives the notification on the terminal.

[1478] Input: Generated notification content

[1479] Specific operation: The server sends notification data to the terminal, and the terminal displays the notification to the user.

[1480] Output: Notifications displayed on the device

[1481] The above is the specific processing steps of the financial license supporter system and the flow of its operation.

[1482] (Application example 1)

[1483] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1484] Adapting to rapidly changing laws and regulations and ensuring legal compliance is a major challenge for current electronic payment services. Obtaining information on legal revisions in real time and quickly adapting operations based on that information is particularly difficult. Additionally, the process of checking the legality of new services and confirming necessary licenses and legal requirements is complex and time-consuming. There is a need for a support system that can address these challenges and quickly deploy new services while complying with laws and regulations.

[1485] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1486] In this invention, the server includes a means for collecting legal information, a means for analyzing the collected legal information, and a means for automatically notifying the company of important revisions to the analyzed legal information. This allows the company to grasp the latest legal revision information in real time and adapt its business accordingly. In addition, by including a means for inputting detailed information about new services and a means for analyzing and providing the necessary licenses and legal requirements, the legality of new services can be checked quickly and reliably, enabling the rapid deployment of new services.

[1487] "Legal information" refers to information on laws, regulations, ordinances, etc., and information on amendments thereto, provided by government agencies and public institutions.

[1488] "Analysis" refers to the process of analyzing collected data and information and extracting and organizing the necessary information.

[1489] "Storing" refers to recording collected and analyzed information in a database or storage device so that it can be used later.

[1490] "Company-specific operating rules" refer to internal rules and guidelines established by a specific company for compliance with laws and regulations and business operations.

[1491] "Receiving questions" refers to receiving inquiries or confirmations from users through a device or system.

[1492] "Generating an answer" refers to creating an appropriate response to a received question or inquiry based on relevant information and data.

[1493] "Providing to the user" refers to conveying the generated answers or information to the user in an appropriate manner.

[1494] "New Services" refers to new products, services, or improved versions thereof offered by a company.

[1495] "Checking legality" refers to the process of verifying whether the services or products offered comply with current laws and regulations.

[1496] "Legal amendment information" refers to new information and amendments when existing laws and regulations are changed.

[1497] "Business improvement information" refers to information related to suggestions, advice, and best practices for improving the efficiency of corporate operations and business.

[1498] "Real-time notification" means instantly informing companies and users of the latest information and data.

[1499] "Detailed information about new services" refers to information such as specific data, features, and specifications about new services provided by a company.

[1500] "Necessary Licenses and Legal Requirements" means the permits, licenses and legal requirements that must be obtained in order to provide certain services or products.

[1501] The present invention, "Financial License Supporter System," helps financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: servers, terminals, and users.

[1502] Overall system configuration

[1503] server

[1504] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using a generative AI model. The analyzed information is stored in a base area, and company-specific operational rules are stored in a customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services.

[1505] The server also has the ability to detect legal revisions and business improvement information in real time and notify companies. Specifically, it automatically obtains legal information periodically from government agencies and public websites using scraping technology and APIs, and passes the collected information to a generative AI model for analysis. The analyzed information is stored in a database, and if important revisions are detected, relevant companies are notified.

[1506] Terminal

[1507] The terminal is the device that the user uses as an interface. The user uses the terminal to input questions and details of new services. The terminal sends this input information to the server and displays the server's response or results. For example, if a user inputs a question such as "What licenses are required to start a new electronic payment service?", the terminal sends this information to the server, and the server analyzes legal information and the company's operating rules to generate an answer, which the terminal then displays to the user.

[1508] User

[1509] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, and check the legality of new services. Furthermore, the terminal can also be used to input and update company-specific operational rules into the server. For example, when launching a new service, a user can issue an instruction to "enter detailed information about a new fund transfer service." The terminal then sends the information to the server, which checks legality and analyzes and provides the necessary licenses and legal requirements.

[1510] Hardware and software used

[1511] Hardware: Physical servers and cloud servers (e.g. AWS, GCP, Azure)

[1512] Software: Python, Flask, BeautifulSoup, requests, apscheduler, any AI analysis library (e.g. GPT-3, BERT)

[1513] Data processing and calculation

[1514] 1. Data Collection

[1515] The server periodically collects legal information from government agencies and public websites using scraping techniques using BeautifulSoup and requests.

[1516] 2. Data Analysis

[1517] The collected legal information is passed to a generative AI model on the server for analysis. The analysis results are saved in the base area. Company-specific operational rules are also saved in the customization area.

[1518] 3. Answer generation and notification

[1519] When a user asks a question, the server analyzes the legal information related to the question and the company's operating rules to generate an appropriate answer. By entering detailed information about a new service, the server checks its legality and analyzes and provides necessary licenses and legal requirements. Furthermore, if important legal revision information is detected, the server notifies relevant companies in real time.

[1520] Specific examples

[1521] Prompt Sentence Examples

[1522] "What licenses are required to launch a new electronic payment service?"

[1523] "If new legal changes are made to the prepaid payment instrument issuing industry, how will our business be affected?"

[1524] This will enable companies to rapidly roll out new services while ensuring compliance with regulations.

[1525] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1526] Step 1:

[1527] The server periodically collects legal information from government agencies and public websites. As input, it receives the target website URL and obtains legal information using scraping technology (BeautifulSoup,requests). As output, it generates a dataset of the collected legal information.

[1528] Step 2:

[1529] The server analyzes the collected legal information. As input, it passes the legal information collected in step 1 to the AI ​​analysis engine (generative AI model). As data calculation, the AI ​​model classifies the legal information into applicable legal categories and importance levels, and outputs the analysis results. As output, it saves the analyzed legal information in a base area.

[1530] Step 3:

[1531] The server receives company-specific operational rules from the user and stores them. The user inputs their company's operational rules via a terminal, and the input data is sent to the server. The server receives the operational rules entered by the user as input and stores them in a customization area. The server generates a dataset of operational rules as output.

[1532] Step 4:

[1533] The user enters questions about the licenses and legal requirements required for the new service into their device and sends them to the server. The server receives the user's question as input and analyzes it. As a data calculation, the AI ​​analysis engine generates the optimal answer to the question based on legal information and the company's operating rules. As an output, the answer is sent to the device and displayed to the user.

[1534] Step 5:

[1535] The user enters details of the new service they wish to offer into their device and sends it to the server. The server receives the details of the new service as input and checks its legality. As data calculations, the AI ​​analysis engine compares the content of the new service with legal information and analyzes the necessary licenses and legal requirements. As output, the results of the legality check are sent to the device as a report and provided to the user.

[1536] Step 6:

[1537] The server detects information on legal revisions and business improvement information in real time and notifies companies. It periodically monitors analyzed legal information as input, and generates notification information when important revisions are detected. It outputs the notification information, sending it to relevant companies in real time and displaying it on the user's device.

[1538] Step 7:

[1539] The terminal displays the entered operational rules and questions, detailed information about new services, and notifications from the server. It receives answers sent from the server, legality check results, and notification information as input, and immediately displays them to the user as output. Specifically, the user can enter a prompt to receive prompt feedback on legality and questions.

[1540] The above are the specific processing steps of the program for the system that realizes the application example.

[1541] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1542] The present invention is a system that not only helps financial companies ensure compliance with laws and regulations and quickly launch new services, but also recognizes users' emotions and provides appropriate responses. Below, we will specifically explain an embodiment of the invention that combines an emotion engine.

[1543] Overall system configuration

[1544] server

[1545] The server plays a central role in collecting, analyzing, and storing legal information. It also uses an emotion engine to analyze users' emotions and adjust the content of responses and notifications.

[1546] Terminal

[1547] The terminal is a device that the user uses as an interface. The user inputs questions from the terminal and receives answers and notifications from the server. The terminal also collects the user's emotional data and sends it to the server.

[1548] User

[1549] The users are financial business personnel. They operate the terminal to check legal information, input questions, check the legality of new services, etc. The user's emotional data is also analyzed, and the system adjusts the response accordingly.

[1550] Program processing overview

[1551] Collection and updating of legal information

[1552] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs. It then analyzes the collected legal information using an AI analysis engine and stores it in a base area. When it detects important legal amendments or new regulatory information, it sends notifications to relevant companies.

[1553] Management of company-specific operational rules

[1554] The user inputs company-specific operational rules using a dedicated interface. The terminal sends the input operational rules to the server, which then stores them in a customization area.

[1555] Support for resolving legal issues

[1556] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and the AI ​​generates an appropriate answer. The answer is then provided to the user via the device.

[1557] Checking the legality of new services

[1558] When a user enters details of a new service, the device sends them to the server. The server checks the legality of the new service by comparing it with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements, and sends the check results and details to the device for provision to the user.

[1559] Notification function for legal revisions and business improvements

[1560] The server detects information on legal revisions and business improvement information in real time from the collected data. It analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[1561] Emotion recognition and response adjustment

[1562] Emotion Engine

[1563] The emotion engine has the function to recognize and analyze the user's emotions. When the user enters a question or details of a new service, the device simultaneously collects the user's emotion data and sends it to the server.

[1564] Emotion recognition processing

[1565] Step 1

[1566] The server uses an emotion engine to analyze the emotion data sent by the user and determine their current emotional state. For example, if the user is feeling anxious or stressed, the server generates an analysis result that reflects that.

[1567] Emotion-based response adjustment

[1568] Step 2

[1569] The server adjusts the tone and content of the appropriate response based on the perceived emotion, for example, providing a more relaxed tone of response if the user is feeling stressed.

[1570] Emotion-based notification timing

[1571] Step 3

[1572] The server then selects the appropriate timing and format for notifications based on the emotion recognition results. For example, it can avoid notifications when the user is concentrating and send notifications when the user is relaxed.

[1573] Specific examples

[1574] 1. Emotion-aware response adjustment

[1575] When a user types a question such as "What are the licensing requirements for new electronic payment services?", the terminal collects the user's sentiment.

[1576] The server uses an emotion engine to determine the user's anxiety and generates a response in a stress-reducing tone, saying, "A license for electronic payment services is required."

[1577] The server sends this response to the terminal and provides it to the user.

[1578] 2. Emotion-aware notification adjustment

[1579] When the server detects new legal amendments and prepares to notify relevant companies, it also analyzes user emotional data.

[1580] The server takes into account the user's emotional state and sends a notification that "there are new legal changes" at an appropriate time.

[1581] 3. Legality checks for new services and emotional responses

[1582] When a user enters details of a new service and the device sends them to the server, emotional data is also collected at the same time.

[1583] The server uses an emotion engine to recognize the user's state of excitement and generates a report on the legality of the service, along with a detailed and reassuring explanation.

[1584] The server sends this report to the terminal and provides it to the user.

[1585] The system enables businesses to respond to users' emotional states while ensuring compliance, improving operational efficiency and customer satisfaction, while also enabling the rapid launch of new services and reducing business risks.

[1586] The processing flow will be explained below.

[1587] Processing flow of a system that combines emotion engines

[1588] Collection and updating of legal information

[1589] Step 1:

[1590] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[1591] Step 2:

[1592] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[1593] Step 3:

[1594] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[1595] Step 4:

[1596] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[1597] Management of company-specific operational rules

[1598] Step 1:

[1599] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[1600] Step 2:

[1601] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[1602] Step 3:

[1603] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[1604] Support for resolving legal issues

[1605] Step 1:

[1606] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[1607] Step 2:

[1608] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[1609] Step 3:

[1610] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[1611] Step 4:

[1612] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[1613] Checking the legality of new services

[1614] Step 1:

[1615] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[1616] Step 2:

[1617] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[1618] Step 3:

[1619] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[1620] Step 4:

[1621] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[1622] Step 5:

[1623] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[1624] Notification function for legal revisions and business improvements

[1625] Step 1:

[1626] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[1627] Step 2:

[1628] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[1629] Step 3:

[1630] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[1631] Step 4:

[1632] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[1633] Emotion recognition and response adjustment process flow

[1634] Emotion recognition processing

[1635] Step 1:

[1636] When a user enters a question or details of a new service through the device, the device simultaneously collects emotional data, such as facial expressions, tone of voice, and heart rate, using a camera, microphone, and sensors.

[1637] Step 2:

[1638] The device sends the collected emotion data to a server, where the data is formatted and adjusted so that it can be analyzed by the emotion engine.

[1639] Step 3:

[1640] The server analyzes the emotion data through an emotion engine to determine the user's current emotional state, for example, identifying emotions such as stress, anxiety, and relaxation.

[1641] Emotion-based response adjustment

[1642] Step 1:

[1643] The server adjusts the tone and content of responses and notifications based on the analysis results. For example, if the user is feeling stressed, it will adopt a polite and friendly tone to help them relax.

[1644] Step 2:

[1645] The server generates a response or notification based on the user's emotional state and sends it to the terminal. For example, if the user is feeling anxious, the server may provide a message such as, "Don't worry. There will be no problem if you obtain a license for electronic payment services."

[1646] Adjusting notification timing based on emotions

[1647] Step 1:

[1648] The server selects the appropriate timing for notifications based on the user's emotional state, for example, when the user is relaxing or has free time at work.

[1649] Step 2:

[1650] The server generates a notification at an appropriate time and sends it to the device. By notifying the user that "there are new revisions to the law" during a time when the user is relaxing, the information is received effectively.

[1651] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. Furthermore, the system can respond according to the user's emotional state, improving business efficiency and user satisfaction, enabling the rapid launch of new services and reducing business risks.

[1652] Example 2

[1653] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1654] In modern financial operations, legal compliance is an important issue for companies, but it is difficult to quickly collect and analyze frequently updated legal information. There is also a need to check the legality of new services and provide prompt answers to legal issues. Furthermore, it is also necessary to recognize user emotions and respond appropriately based on them. However, no system currently exists that can meet these diverse requirements. Therefore, there is a need for a system that integrates the collection, analysis, and notification of legal information, the legality check of new services, and the user emotion recognition functions.

[1655] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1656] In this invention, the server includes means for collecting legal information, means for analyzing the collected legal information, means for saving the analyzed legal information, means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, means for detecting and notifying new legal revision information and business improvement information, means for collecting user emotional data, means for analyzing the collected emotional data to determine the user's emotional state, means for adjusting the tone and content of the answer based on the determined emotional state, and means for selecting the appropriate timing and format of notifications. This enables support for legal compliance, rapid launch of new services, optimization of company operational rules, and optimal responses according to the user's emotional state.

[1657] "Legal Information" refers to laws, regulations, and amendments thereto published by government agencies and public websites.

[1658] "Analyzing" refers to the process of classifying and interpreting collected legal information using machine learning models and natural language processing technology.

[1659] "Storing" refers to storing the analyzed data in a designated database or storage system.

[1660] "Company-specific operating rules" refer to specific business processes and standards established internally by a company.

[1661] "Receiving a question" refers to the server receiving a question or information request sent by a user via a terminal.

[1662] "Generating an answer" refers to the process of generating an appropriate response based on the received question, by referring to relevant legal information and company-specific operational rules.

[1663] "Checking legality" refers to the process of verifying whether a new service or product complies with current laws and regulations.

[1664] "Emotional data" refers to data that indicates a user's emotional state, such as data collected from the user's tone of voice, facial expression, and tone of writing.

[1665] "Determining emotional state" refers to identifying the psychological state the user is currently experiencing based on the collected emotional data.

[1666] "Adjusting the tone and content of your response" refers to appropriately changing the tone and wording of your response based on your determined emotional state.

[1667] "Selecting the appropriate timing and format for notifications" refers to determining the best time and method for sending notifications, taking into account emotional data and work schedules.

[1668] A "generative AI model" refers to an artificial intelligence system that generates natural language text based on input data.

[1669] The present invention is a system that not only helps financial companies ensure compliance with laws and regulations and quickly launch new services, but also recognizes users' emotions and provides appropriate responses. Specific embodiments of this system are described below.

[1670] Overall system configuration

[1671] The system mainly consists of three elements: a server, a terminal, and a user.

[1672] server

[1673] The server plays a central role in collecting, analyzing, and storing legal information. It also has the ability to analyze user sentiment using an emotion engine and adjust the content of responses and notifications. To do this, the server collects legal information through scraping technologies (e.g., Beautiful Soup or Scrapy) or API access, analyzes the data using an AI analysis engine (e.g., TensorFlow or Scikit-learn), and generates responses using a generative AI model (e.g., GPT-3).

[1674] Terminal

[1675] The device is the interface used by the user. The user inputs questions through the device and receives answers and notifications from the server. The device also collects the user's emotional data (e.g., voice tone and facial expression data) and sends it to the server. For this purpose, the device is equipped with hardware such as a microphone and a camera.

[1676] User

[1677] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. The information and emotional data entered by the user are sent to the server via the terminal, and the analyzed results are provided.

[1678] Procedures for collecting and updating legal information

[1679] The server periodically collects legal information from government agencies and public websites using scraping technologies such as Python's Beautiful Soup and Scrapy, as well as the government's public API. The collected information is analyzed using an AI analysis engine using TensorFlow and Scikit-learn, and then stored in a base area.

[1680] Examples:

[1681] The user checks the updated status of legal information from the terminal.

[1682] The server collects legal information and checks for updates.

[1683] Send a notification to the user saying, "The latest financial regulations have been updated."

[1684] Example prompt:

[1685] "Collect the latest legal information and inform companies."

[1686] Management procedures for company-specific operational rules

[1687] The user inputs the company's unique operational rules using a dedicated interface and sends them to the server via the terminal. The server saves the input operational rules in the customization area.

[1688] Examples:

[1689] The user enters the "company's internal rules" from the terminal.

[1690] The terminal transmits the input information to the server, which stores it in the customization area.

[1691] Example prompt:

[1692] Enter your company's internal rules and save them in the customization area.

[1693] Legal issue resolution support procedures

[1694] When a user inputs a question or inquiry into their device, the device sends it to the server. The server analyzes the question using TensorFlow and Scikit-learn, compares it with relevant legal information and the company's operational rules, and generates an appropriate answer. The generated answer is then provided to the user via the device.

[1695] Examples:

[1696] The user types into the terminal, "Is this transaction legitimate?"

[1697] The server compares the legal information with the company's operating rules and responds, "This transaction is legal."

[1698] Example prompt:

[1699] "Analyze user questions, compare legal information and operational rules, and generate answers."

[1700] Procedures for checking the legality of new services

[1701] When a user enters details of a new service, the device sends them to the server, which checks the legality of the new service by comparing it with the information in the base and customization areas. The generative AI model extracts any necessary licenses or legal requirements, and sends the check results and details to the device for presentation to the user.

[1702] Examples:

[1703] The user enters the details of the new payment service into the terminal.

[1704] The server parses the input, extracts any necessary licenses and legal requirements, and generates a report.

[1705] Example prompt:

[1706] "Please analyze the details of the new service and check the legal requirements and legality."

[1707] Emotion recognition and response adjustment procedures

[1708] When a user enters details of a question or new service, the device collects emotional data and sends it to the server. The server then analyzes the data using an emotion engine to determine the user's emotional state. Based on the determined emotional state, the generative AI model adjusts the tone and content of the appropriate response and delivers it to the user via the device. It also determines the appropriate timing and format for notification.

[1709] Examples:

[1710] A user types a question: "What are the licensing requirements for new electronic payment services?"

[1711] The server analyzes the user's emotions and responds in a relaxed tone.

[1712] Example prompt:

[1713] "Analyze user sentiment data and generate appropriate responses."

[1714] The system enables businesses to improve operational efficiency and customer satisfaction by providing responses that respond to users' emotional states while ensuring compliance with regulations.

[1715] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1716] Step 1: Gather legal information

[1717] The server periodically collects legal information from government agencies and public websites using scraping technologies such as Python's Beautiful Soup and Scrapy, as well as public APIs, to obtain the latest legal information.

[1718] Input: URL of a government or public website.

[1719] Data processing and calculation: Data acquisition using scraping technology and APIs.

[1720] Output: Raw data of the legal information obtained.

[1721] Step 2: Analyzing legal information

[1722] The server analyzes the collected legal information using an AI analysis engine (such as TensorFlow or Scikit-learn) to classify the type and content of the law. As a result of the analysis, important parts of the law are extracted.

[1723] Input: Raw legal information collected in step 1.

[1724] Data processing and calculation: Classifying data and extracting important parts.

[1725] Output: Parsed legal information.

[1726] Step 3: Save legal information

[1727] The server stores the analyzed legal information in the base area of ​​the database, which allows the necessary information to be quickly accessed in subsequent processes.

[1728] Input: The legal information parsed in step 2.

[1729] Data processing and calculation: Data storage process in database.

[1730] Output: Saved legal information.

[1731] Step 4: Managing company-specific operational rules

[1732] The user inputs company-specific operational rules using a dedicated interface. The terminal sends the input operational rules to the server, which then stores them in the customization area.

[1733] Input: Operational rules entered by the user.

[1734] Data processing and calculation: Data transmission from the terminal to the server and storage in the database.

[1735] Output: Saved company-specific operating rules.

[1736] Step 5: Receive legal questions

[1737] The user enters a question through the interface, which the terminal then sends to the server, for example, "Is this transaction legal?"

[1738] Input: Legal challenge questions entered by the user.

[1739] Data processing and calculation: Data transmission from the terminal to the server.

[1740] Output: The query data received by the server.

[1741] Step 6: Parsing the question and generating an answer

[1742] The server analyzes the received questions using an AI analysis engine, compares them with relevant legal information and the company's operational rules, and generates an appropriate answer using a generative AI model (e.g., GPT-3).

[1743] Input: Question data received in step 5, and stored legal information and operational rules.

[1744] Data processing and calculation: Analyzing data and generating answers using AI models.

[1745] Output: The generated answer.

[1746] Step 7: Provide your answers

[1747] The server sends the generated response to the terminal and provides it to the user, for example, providing a response such as "This transaction is legal."

[1748] Input: The response data generated in step 6.

[1749] Data processing and calculation: Sending response data to the terminal.

[1750] Output: The answer provided to the user.

[1751] Step 8: Check the legality of new services

[1752] The user enters details of the new service, and the device sends them to the server, which analyzes the content of the new service and checks its legality.

[1753] Input: New service details entered by the user.

[1754] Data processing and calculation: Data transmission from the terminal to the server and comparison with legal information and operational rules.

[1755] Output: Legality check result.

[1756] Step 9: Provide legality check results

[1757] The server uses a generative AI model to explain the check results in detail and provide them to the user via their device.

[1758] Input: The legality check results parsed in step 8.

[1759] Data processing and calculation: Generative AI model generates detailed explanations.

[1760] Output: The legitimacy check result provided to the user.

[1761] Step 10: Collect emotion data

[1762] The device collects emotional data (e.g., voice tone and facial expression data) when the user enters a question or details of a new service and transmits it to the server.

[1763] Input: Emotion data collected from users.

[1764] Data processing and calculation: Collecting emotion data and sending it to the server.

[1765] Output: Emotion data received by the server.

[1766] Step 11: Analyze the emotion data

[1767] The server uses an emotion engine to analyze the emotion data and determine the user's emotional state.

[1768] Input: Emotion data collected in step 10.

[1769] Data processing and computation: Analysis of emotion data.

[1770] Output: Determined emotional state.

[1771] Step 12: Emotion-Based Response Adjustment

[1772] Based on the determined emotional state, the server uses a generative AI model to tailor the tone and content of the appropriate response, as well as determine the appropriate timing and format for notification.

[1773] Input: Emotional state determined in step 11.

[1774] Data processing and calculation: Generative AI models adjust tone and content and determine notification timing.

[1775] Output: Coordinated answers and notifications.

[1776] (Application example 2)

[1777] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1778] Modern companies often need to simultaneously comply with laws and regulations and provide emotional support. However, while traditional systems can collect and analyze legal information, they struggle to respond appropriately to users' emotional states, often resulting in delayed responses. It is also difficult to respond quickly and appropriately to security-related issues. This poses a risk of reducing a company's credibility and productivity.

[1779] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for collecting legal information, means for analyzing the collected legal information, and means for saving the analyzed legal information. This includes means for managing company-specific operational rules, means for receiving questions from users, means for generating answers by referencing the analyzed legal information and the company-specific operational rules based on the received questions, means for providing the generated answers to users, means for checking the legality of new services, means for detecting and notifying new legal revision information and business improvement information, emotion recognition means for analyzing emotional states, means for adjusting the tone and content of answers based on the emotion recognition results, and means for adjusting the timing of notifications based on the emotion recognition results. This enables prompt and appropriate responses according to the user's emotional state while ensuring compliance with laws and regulations.

[1780] "Means for collecting legal information" refers to devices or software that automatically obtain the latest legal information from government agencies or public websites.

[1781] "Means for analyzing collected legal information" refers to devices or software that analyze collected legal information using artificial intelligence or natural language processing technology and extract the necessary information.

[1782] "Means for storing analyzed legal information" refers to a device or software that stores analyzed legal information in a database or the like and keeps it accessible at any time.

[1783] "Means for managing company-specific operational rules" refers to devices or software for inputting, saving, and managing operational rules established independently by a company.

[1784] The "means for receiving a question from a user" refers to a device or software that receives a question entered by a user and transmits the question to a server.

[1785] "Means for generating an answer by referring to legal information analyzed based on the received question and company-specific operational rules" refers to a device or software that analyzes the received question and generates an appropriate answer by referring to relevant legal information and company-specific operational rules.

[1786] "Means for providing a generated answer to a user" refers to a device or software that provides a generated answer to a user.

[1787] "Means for checking the legality of new services" refers to devices or software that check whether new services planned by a company are legally legal.

[1788] "Means for detecting and notifying new information on revisions to laws and regulations and business improvement information" refers to devices or software that detect the latest information on revisions to laws and regulations and business improvement information and notify related companies of this information.

[1789] "Emotion recognition means for analyzing an emotional state" refers to a device or software that analyzes the emotions of a user and determines that emotional state.

[1790] The "means for adjusting the tone and content of a response based on the emotion recognition result" refers to a device or software that appropriately adjusts the tone and content of a generated response based on the result of the emotion recognition means.

[1791] "Means for adjusting the timing of notification based on the emotion recognition result" refers to a device or software that selects and adjusts the appropriate timing for notification based on the emotion recognition result.

[1792] MODE FOR CARRYING OUT THE INVENTION

[1793] This invention is a system for simultaneously achieving corporate compliance with laws and regulations and emotional care, with a particular focus on security services. The system includes functions such as collecting, analyzing, and storing legal information, managing company-specific operational rules, analyzing emotions and adjusting responses using an emotion engine, checking the legality of new services, and providing notifications.

[1794] Overall system configuration

[1795] 1. Server

[1796] The server has the following features:

[1797] Legal information collection: Automatically collect legal information from government agencies and public websites. Use a Python scraping tool to retrieve the information and store it in a database.

[1798] Analysis and storage: The collected legal information is analyzed using an AI analysis engine, and information related to each company is extracted and stored. The AI ​​analysis engine used here is a tool with natural language processing capabilities (e.g., GPT-4).

[1799] Emotion recognition: Analyzes the user's emotional state using an emotion engine (IBM Watson Emotion Analysis API). Data is collected in real time, and the analysis results are used to generate answers and adjust notifications.

[1800] Answer generation: Uses generative AI (GPT-4 API) to generate appropriate answers to user questions.

[1801] 2. Terminal

[1802] A terminal is a device that a company's personnel uses as an interface. It has the following functions:

[1803] Input and receive: The user inputs the details of the question or new service and sends it to the server. At the same time, the user's emotional data is also collected and sent to the server.

[1804] Display and Notifications: Displays responses and notifications sent from the server, with tone and timing adjustments based on emotion.

[1805] 3. Users

[1806] The user is a company security officer who operates a terminal to check legal information and enter questions.

[1807] Legal problem solving: Enter a question to answer a legal question or check the legitimacy of a new security measure. Results are adjusted based on emotion recognition to provide answers in a reassuring tone.

[1808] Providing emotional data: When asking questions or conducting checks, emotional data is collected in real time and sent to the server.

[1809] Specific examples

[1810] 1. Collection and analysis of legal information

[1811] The server collects legal information from government agency websites, analyzes it using an AI analysis engine, and stores it in a database.

[1812] 2. Emotion-aware response adjustment

[1813] When a user types a question into a terminal, such as "What are the legal requirements for new security measures?", the server uses an emotion engine to analyze the user's emotions.

[1814] The emotion engine determines the user's anxiety and generates responses in a relaxed tone as needed. For example, the generative AI (GPT-4) generates responses such as, "When implementing new security measures, you must first ensure that the measures comply with data protection laws. It is also important to implement appropriate access controls and audit logs."

[1815] 3. Appropriate timing of notifications

[1816] The server detects new legal changes and analyzes the user's emotional data. For example, it avoids times when the user is concentrating and notifies the user when they are relaxed.

[1817] Prompt Sentence Examples

[1818] User Question: "What are the legal requirements for new security measures?"

[1819] Answer Tone: "Relaxed Tone"

[1820] answer:

[1821] This system enables companies to ensure compliance with laws and regulations while also enabling them to respond quickly and appropriately to users' emotional states, thereby improving business efficiency and user satisfaction.

[1822] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1823] Step 1:

[1824] The server collects legal information from government agencies and public websites. It uses a Python scraping tool to automatically retrieve data from websites and store it as initial data. The input data is the page content of government agency websites, and the output data is the collected legal information.

[1825] Step 2:

[1826] The server analyzes the collected legal information. Here, it uses natural language processing technology to extract necessary information and structure the legal information. Specifically, it uses generative AI models such as GPT-4 to extract and classify important regulations and amendments. The input data is the collected legal information, and the output data is the analyzed legal information.

[1827] Step 3:

[1828] The server stores the analyzed legal information in a database. The database classifies legal information relevant to each company and stores it in a state that can be accessed at any time. The input data is the analyzed legal information, and the output data is the stored legal information.

[1829] Step 4:

[1830] The user uses a terminal to input detailed information about a legal issue or a new service. The terminal sends this information to the server, and simultaneously collects and transmits the user's emotional data. The input data is the question, service details, and emotional data, and the output data is the information sent to the server.

[1831] Step 5:

[1832] The server performs analysis based on the received questions and detailed information about new services. It uses an emotion engine (IBM Watson Emotion Analysis API) to analyze the user's emotional state and generate emotion recognition results. The input data is the question, service details, and emotion data, and the output data is the emotion recognition results.

[1833] Step 6:

[1834] The server responds to questions and checks the legality of new services based on emotion recognition results. Using a generation AI (GPT-4 API), it references relevant legal information and company-specific operational rules to generate answers. The input data is the question, service details, analysis results, and emotion recognition results, and the output data is the generated answer.

[1835] Step 7:

[1836] The server adjusts the tone of the generated answer according to the user's emotion and sends it to the device. Specifically, if the user feels anxious, the server generates an answer with a relaxed tone. The input data are the generated answer and the emotion recognition result, and the output data is the tone-adjusted answer.

[1837] Step 8:

[1838] The terminal displays the tone-adjusted response sent from the server. The user uses this response to resolve legal issues and manage business operations. The input data is the tone-adjusted response, and the output data is the display on the terminal.

[1839] Step 9:

[1840] The server periodically detects new legal revision information and business improvement information and notifies relevant companies. Notifications are sent at the appropriate time based on emotion recognition results. The input data is the latest legal revision information and emotion data, and the output data is notification information sent at the appropriate time.

[1841] This processing step allows companies to respond quickly and appropriately to user sentiment while ensuring compliance with regulations.

[1842] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1843] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1844] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1845] [Fourth embodiment]

[1846] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1847] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1848] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1849] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1850] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1851] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1852] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1853] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1854] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1855] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1856] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1857] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1858] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1859] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and quickly launch new services. This system is composed of the following elements: a server, a terminal, and a user.

[1860] Overall system configuration

[1861] server

[1862] The server plays a central role in collecting, analyzing, and storing legal information. It periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the base area, and company-specific operational rules are stored in the customization area. The server also receives questions from users, generates answers based on the analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information and notifying companies.

[1863] Terminal

[1864] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[1865] User

[1866] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[1867] Program processing overview

[1868] Collection and updating of legal information

[1869] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[1870] Management of company-specific operational rules

[1871] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[1872] Support for resolving legal issues

[1873] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[1874] Checking the legality of new services

[1875] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[1876] Notification function for legal revisions and business improvements

[1877] The server detects information on legal revisions and business improvement information in real time from the collected data. It automatically analyzes important revision information and sends notifications to relevant companies. Users can update their internal business rules and manuals based on the notifications they receive.

[1878] Specific examples

[1879] 1. Collection and updating of legal information

[1880] The server periodically collects new financial laws and regulations from government agency websites using scraping technology.

[1881] The server analyzes the collected information using an AI analysis engine and stores it in a base area.

[1882] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[1883] 2. Managing company-specific operational rules

[1884] The user gives an instruction to "input new bank agency procedure rules."

[1885] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[1886] 3. Support for resolving legal issues

[1887] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[1888] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[1889] The server sends this response to the terminal and displays it to the user.

[1890] 4. Legality checks for new services

[1891] The user instructs "Enter details for new funds transfer service."

[1892] The terminal transmits the service information to the server, and the server checks the legitimacy.

[1893] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[1894] 5. Notification function for legal revisions and business improvements

[1895] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[1896] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[1897] The user receives a notification and reviews the business rules.

[1898] The above is a concrete example of the financial license supporter. This system will enable companies to rapidly develop new services while ensuring compliance with laws and regulations.

[1899] The processing flow will be explained below.

[1900] Collection and updating of legal information

[1901] Step 1:

[1902] The server periodically collects legal information from government agencies and public websites, using scraping technology and APIs to automatically obtain the information.

[1903] Step 2:

[1904] The server passes the collected legal information to an AI analysis engine, which converts the collected information into structured data.

[1905] Step 3:

[1906] The server stores the analyzed legal information in a base area, and compares it with past legal information as needed to detect important revisions.

[1907] Step 4:

[1908] When the server detects important changes in laws and regulations or new regulatory information, it automatically sends notifications to relevant companies.

[1909] Management of company-specific operational rules

[1910] Step 1:

[1911] The user uses the terminal interface to input company-specific operational rules, such as procedural rules for a new banking agency business.

[1912] Step 2:

[1913] The terminal sends the entered operational rules to the server, and the data format is adjusted so that the details of the operational rules are accurately transmitted to the server.

[1914] Step 3:

[1915] The server saves the received operation rules in the customization area and notifies the terminal that the operation rules have been successfully saved.

[1916] Support for resolving legal issues

[1917] Step 1:

[1918] Users enter their doubts or questions into the interface, for example, "What licenses do I need to launch a new electronic payment service?"

[1919] Step 2:

[1920] The device sends the question to the server, which formats the data so that the question is conveyed specifically and clearly.

[1921] Step 3:

[1922] The server analyzes the question and compares it with relevant legal information and the company's operational rules, allowing the AI ​​to generate an appropriate answer.

[1923] Step 4:

[1924] The server then sends the generated response to the terminal, providing a specific response such as "You need a license for electronic payment services."

[1925] Checking the legality of new services

[1926] Step 1:

[1927] The user enters details of a new service through the interface, for example details of a new funds transfer service.

[1928] Step 2:

[1929] The device sends this information to the server, where the data format is adjusted to ensure that information about the new service is transmitted accurately.

[1930] Step 3:

[1931] The server checks the legality of the new service by comparing the content of the new service with the information in the base and customization areas. The generation AI extracts any necessary licenses and legal requirements.

[1932] Step 4:

[1933] The server generates a report containing the check results and any required license information. For example, a detailed report stating "A license for money transfer business is required" is created.

[1934] Step 5:

[1935] The server sends this report to the terminal and provides it to the user, who can then review the report and confirm the legitimacy of the transaction.

[1936] Notification function for legal revisions and business improvements

[1937] Step 1:

[1938] The server detects legal amendments and business improvement information in real time from the collected data, such as new legal amendments for the prepaid payment instrument issuing business.

[1939] Step 2:

[1940] The server analyzes the important revision information and prepares to send notifications to relevant companies based on the analysis results.

[1941] Step 3:

[1942] The server prepares the notification content in an appropriate format and sends it to the terminal. The notification content is prepared in a format that is easy for the company to understand.

[1943] Step 4:

[1944] The terminal displays the revision information sent from the server to the user, who then checks the notification and updates the business rules and manuals.

[1945] This system allows companies to effortlessly obtain the latest legal information and quickly check legality. It also efficiently manages company-specific operational rules, increasing the certainty of legal compliance. As a result, new services can be launched quickly and business risks can be reduced.

[1946] Example 1

[1947] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1948] To ensure that financial companies comply with laws and regulations quickly and reliably and provide new services legally, they must constantly collect and analyze the latest legal information and compare it with their own operational rules. However, collecting and analyzing legal information takes time and effort, making it difficult to keep up with modern financial laws, which are frequently revised. Furthermore, when checking individual legal issues or the legality of new services, companies must be able to efficiently and accurately refer to legal information. In this environment, a system is needed that enables companies to effectively comply with laws and regulations and smoothly deploy new services.

[1949] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1950] In this invention, the server includes: means for collecting legal information; means for automatically acquiring the collected legal information using scraping or API technology; means for inputting and analyzing the collected legal information into an AI analysis engine; means for saving the analyzed legal information in a base area; means for inputting company-specific operational rules and transmitting them from a terminal to the server; means for managing the saved company-specific operational rules; means for receiving questions from users; means for generating answers using a generative AI model by referencing the analyzed legal information and company-specific operational rules based on the received questions; means for sending the generated answers to the terminal and providing them to the user; means for users to input detailed information about new services; means for checking the legality of the input new services; and means for detecting and notifying legal revision information and business improvement information in real time. This enables companies to effectively collect and analyze the latest legal information, compare it with operational rules, and take appropriate action. Furthermore, the system can check the legality of new services and provide quick and accurate answers to individual legal issues, enabling the smooth deployment of new services while maintaining compliance with laws and regulations.

[1951] "Legal information" is a general term for information about laws, ordinances, regulations, guidelines, etc. published by government agencies and public institutions.

[1952] "Means of collection" refers to the methods and tools used to obtain the necessary data from a specific source, such as scraping tools and APIs.

[1953] "Scraping technology" refers to the technology or process of automatically extracting structured or unstructured data from a specific website.

[1954] "API technology" refers to a method of obtaining data from a specific service using an application program interface (API).

[1955] "AI analytics engine" refers to software or systems that use artificial intelligence to analyze data, including, for example, generative AI models for natural language processing.

[1956] "Base area" refers to a database or storage area for storing analyzed legal information.

[1957] "Company-specific operating rules" refer to the internal regulations and guidelines that a particular company must follow in its business operations and activities.

[1958] "Terminal" refers to a device used by a user, such as a computer or smartphone.

[1959] A "server" refers to a computer system that provides services to other devices over the Internet or a network.

[1960] A "generative AI model" is a model that uses artificial intelligence to generate appropriate output for specific inputs, such as models for natural language processing and text generation.

[1961] "Means for checking legality" refers to methods and technologies for verifying whether a new service complies with existing laws and regulations.

[1962] "Legal amendment information" refers to information on newly amended laws and regulations and newly enacted laws.

[1963] "Business improvement information" refers to information and suggestions for improving a company's business efficiency and compliance.

[1964] "Real-time detection means" refers to methods and technologies for instantly analyzing collected data and detecting changes or anomalies.

[1965] "Means of notification" refers to the method or technology used to communicate specific information to the target user, including, for example, email and push notifications.

[1966] The financial license supporter system of this invention is designed to help financial businesses ensure compliance with laws and regulations and rapidly develop new services. This system is composed of the following elements: a server, a terminal, and a user.

[1967] Overall system configuration

[1968] server

[1969] The server plays a central role in collecting, analyzing, and storing legal information. The server periodically collects legal information and analyzes it using an AI analysis engine. The analyzed information is stored in the "base area," while company-specific operational rules are stored in the "customization area." The server also receives questions from users, generates answers based on analysis, and checks the legality of new services. It also has the function of detecting legal revisions and business improvement information in real time and notifying companies.

[1970] Terminal

[1971] The terminal is the device that the user uses as an interface. The user enters questions and details about new services on the terminal. The terminal transmits this information to the server and displays the answers and results from the server.

[1972] User

[1973] The users are employees of financial companies. They operate the terminal to check legal information, enter questions, check the legality of new services, etc. Furthermore, they can also input and update their company-specific operational rules to the server via the terminal.

[1974] Program processing overview

[1975] Collection and updating of legal information

[1976] The server periodically collects legal information from government agencies and public websites. It automatically obtains the information using scraping technology and APIs, and passes the collected legal information to an AI analysis engine. The analyzed information is stored in a "base area."

[1977] Examples:

[1978] Every Monday, the server uses scraping technology to collect new financial laws and regulations from government agency websites.

[1979] The server analyzes the collected information using an AI analysis engine (e.g., OpenAI's GPT series) and stores it in the base area.

[1980] If the server detects an important revision, it notifies relevant companies that "there are new revisions to the law."

[1981] Management of company-specific operational rules

[1982] Users input company-specific operational rules using a dedicated interface. The terminal sends the input information to the server, which then stores it in a "customization area." This allows company-specific operational rules to be managed efficiently.

[1983] Examples:

[1984] The user gives an instruction to "input new bank agency procedure rules."

[1985] The terminal transmits the input operation rules to the server, which then stores them in the customization area.

[1986] Support for resolving legal issues

[1987] When a user inputs a question or inquiry through the interface, the device sends it to the server. The server analyzes the question, compares it with relevant legal information and the company's operational rules, and generates the most appropriate answer. The generated answer is then provided to the user via the device.

[1988] Examples:

[1989] The user types the question, "What licenses do I need to launch a new electronic payment service?"

[1990] The server analyzes the legal information and operational rules in response to the question and generates a response such as "A license for electronic payment agency services is required."

[1991] The server sends this response to the terminal and displays it to the user.

[1992] Checking the legality of new services

[1993] When a user enters details of a new service, the device sends them to the server. The server then performs a legality check based on the content of the new service, analyzing and extracting any necessary licenses and legal requirements. The results of the check and details are then provided to the user via the device.

[1994] Examples:

[1995] The user instructs "Enter details for new funds transfer service."

[1996] The terminal transmits the service information to the server, and the server checks the legitimacy.

[1997] The server analyzes the necessary licenses and legal requirements, generates a report stating "A license for the money transfer business is required," sends it to the terminal, and provides it to the user.

[1998] Notification function for legal revisions and business improvements

[1999] The server detects information on legal revisions and business improvement information in real time from the collected data. Important revision information is automatically analyzed and customized notifications are generated for each relevant company. Users receive the notifications on their devices, check the content, and update their company's business rules and manuals.

[2000] Examples:

[2001] The server detects and analyzes new legal changes for the prepaid payment instrument issuing business.

[2002] The server notifies the company to "review its business rules in accordance with the new laws and regulations."

[2003] The user receives a notification and reviews the business rules.

[2004] Example prompts for generative AI models

[2005] Below are some specific examples of prompt sentences to input to the generative AI model.

[2006] "What license do I need to launch a new electronic payment service?"

[2007] "I would like to perform a legality check on a new service. Please enter the following details:..."

[2008] The above is an embodiment of the present invention, which enables financial companies to ensure compliance with laws and regulations and efficiently provide new services.

[2009] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2010] A concrete explanation of the program's processing flow

[2011] Step 1:

[2012] Collection of legal information

[2013] The server accesses designated government agency or public websites (e.g., the official Financial Services Agency website) at 2:00 a.m. every Monday.

[2014] Input: Legal information collection schedule and access URL

[2015] Specific operation: The server uses a scraping tool (e.g., Beautiful Soup, Scrapy) to collect new financial-related legal information from web pages.

[2016] Output: Raw data of the acquired legal information (HTML, JSON, etc.)

[2017] Step 2:

[2018] Analysis of information

[2019] The server inputs the collected legal information into an AI analysis engine (e.g., OpenAI's GPT series).

[2020] Input: Raw data of collected legal information

[2021] Specific operation: The server uses an AI analysis engine to analyze legal information using natural language processing, and extracts the importance of legal provisions and revision details.

[2022] Output: Analyzed legal information (e.g. legal clause, importance, revision date, etc.)

[2023] Step 3:

[2024] Data storage

[2025] The server stores the analyzed legal information in a "base area."

[2026] Input: Parsed legal information

[2027] Specific operation: The parsed information is stored in a base area using a database management system (e.g., MySQL, PostgreSQL).

[2028] Output: Updated legal information for the base region

[2029] Step 4:

[2030] Entering company-specific operational rules

[2031] Users use a dedicated interface to input company-specific operational rules.

[2032] Input: Contents of the operation rules (e.g., text, checklist format)

[2033] Specific operation: The terminal formats the input and sends it to the server.

[2034] Output: Formatted data of the operational rules

[2035] Step 5:

[2036] Data transmission and storage

[2037] The terminal transmits the input operation rules to the server.

[2038] Input: Operational rule data sent from the terminal

[2039] Specific operation: The server stores the received operational rules in the "customization area."

[2040] Output: Updated operational rules for the customization area

[2041] Step 6:

[2042] Receive questions about legal issues

[2043] The user inputs a question about a legal issue from a terminal.

[2044] Input: Questions about legal issues (e.g., "What licenses are required to launch a new electronic payment service?")

[2045] Specific operation: The terminal converts the entered question into a prompt sentence and sends it to the server.

[2046] Output: prompt statement

[2047] Step 7:

[2048] Question analysis and answer generation

[2049] The server analyzes the question and compares it with relevant legal information and company-specific operational rules.

[2050] Input: Prompt text, legal information in the base area, operational rules in the customization area

[2051] Specific operation: The server uses a generative AI model to generate the optimal answer (e.g., OpenAI GPT series).

[2052] Output: The generated answer

[2053] Step 8:

[2054] Submitting and viewing answers

[2055] The server sends the generated response to the terminal.

[2056] Input: Generated Answer

[2057] Specific operation: The server sends the answer data to the terminal, and the terminal displays the answer to the user.

[2058] Output: Answer displayed on terminal

[2059] Step 9:

[2060] Enter details of new service

[2061] The user enters the details of the new service.

[2062] Enter: New service details (e.g., "New Funds Transfer Service Details")

[2063] Specific operations: The terminal formats the information and sends it to the server.

[2064] Output: Formatted information about the new service

[2065] Step 10:

[2066] Legality analysis

[2067] The server analyzes the input for the new service and extracts any necessary licenses and legal requirements.

[2068] Input: New service details, legal information in the base area, operational rules in the customization area

[2069] Specific operation: Using a generative AI model, the system checks legal information and operational rules related to new services to confirm legality.

[2070] Output: Legality check results and required licenses

[2071] Step 11:

[2072] Sending and displaying results

[2073] The server generates the results of the legality check in the form of a report and sends it to the terminal.

[2074] Input: Legality check result

[2075] Specific operation: The generated report is sent to the terminal, and the terminal displays the report to the user.

[2076] Output: Report provided to the user

[2077] Step 12:

[2078] Detecting and notifying information on legal revisions and business improvement

[2079] The server detects information on legal revisions and business improvement in real time from the collected data and customizes notifications.

[2080] Input: Base area legal information

[2081] Specific operation: Using generative AI models and natural language processing technology, information on legal amendments and business improvement is analyzed, and notification content is generated for relevant companies.

[2082] Output: Customized notifications for each company

[2083] Step 13:

[2084] Sending and receiving notifications

[2085] The server automatically sends the generated notification, and the user receives the notification on the terminal.

[2086] Input: Generated notification content

[2087] Specific operation: The server sends notification data to the terminal, and the terminal displays the notification to the user.

[2088] Output: Notifications displayed on the device

[2089] The above is the specific processing steps of the financial license supporter system and the flow of its operation.

[2090] (Application example 1)

[2091] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2092] Adapting to rapidly changing laws and regulations and ensuring legal compliance is a major challenge for current electronic payment services. Obtaining information on legal revisions in real time and quickly adapting operations based on that information is particularly difficult. Additionally, the process of checking the legality of new services and confirming necessary licenses and legal requirements is complex and time-consuming. There is a need for a support system that can address these challenges and quickly deploy new services while complying with laws and regulations.

[2093] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[2094] In this invention, the server includes a means for collecting legal information, a means for analyzing the collected legal information, and a means for automatically notifying the company of important revisions to the analyzed legal information. This allows the company t...

Claims

1. means of collecting legal information; a means for analyzing the collected legal information; a means for storing the analyzed legal information; A means of managing company-specific operational rules; means for receiving a question from a user; A means for generating an answer by referring to the legal information analyzed based on the received question and the company's specific operational rules; a means for providing the generated answer to a user; A means of checking the legality of new services, A system that includes a means of detecting and notifying new legal amendments and business improvement information.

2. 2. The system according to claim 1, wherein important revisions to collected legal information and new regulatory information are detected and automatically notified to relevant companies.

3. 2. The system according to claim 1, wherein an operational rule specific to a company is input and an answer to a legal issue is generated based on the saved operational rule specific to the company.

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