System

Abstract

A system is provided.SOLUTION: A data processing unit configured to receive input data of the user, perform normalization and validation, access a regulatory information database and an anti-social force list of each country, and collate the input data of the user with the regulatory information database and the anti-social force list; a determination unit configured to determine whether or not a transaction is possible based on a result of the collation, and generate a result of the determination; a response generation unit configured to transmit a determination result and related notes to a terminal of the user; and a question handling unit configured to receive an additional question from the user, access a generated AI again, and generate a response using the additional question.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] In today's economic environment, regulatory information, economic sanctions, and information on anti-social forces in each country are frequently changing, creating a need to quickly verify the trustworthiness of business partners. However, current services make this verification process cumbersome and difficult to perform accurately and quickly. The present invention aims to solve these problems by providing a system that quickly and accurately collates regulatory information from each country and enables smooth evaluation of business partners. [Means for solving the problem]

[0005] The present invention is a system that includes an input means for a user to input the name, address, and transaction details of a business partner, a data processing means that receives the user's input data and performs normalization and validation, a comparison means that accesses regulatory information databases and anti-social forces lists of each country and compares the user's input data with the data, a determination means that determines whether or not a transaction is possible based on the comparison results and generates the result, an answer generation means that transmits the determination result and related points to the user's terminal, and a question response means that accepts additional questions from the user and generates answers again using a generation AI. This allows the user to smoothly compare complex regulatory information from each country and quickly and accurately evaluate the reliability of business partners.

[0006] The "input means" is an interface through which the user inputs information such as the name, address, and transaction details of the business partner.

[0007] "Data processing means" refers to a device or program that has the function of normalizing input data received from a user and checking whether the format and content are correct.

[0008] "Verification means" refers to a device or program that has the function of accessing a database and verifying the information entered by the user against the regulatory information database and the list of anti-social forces.

[0009] The "Regulatory Information Database" is a database that stores information on economic sanctions from various countries, specific regulatory information for each industry, and lists of anti-social forces.

[0010] The "determination means" is a device or program having the function of determining whether or not a transaction is permitted based on the result of the verification means and generating the result.

[0011] The "answer generation means" is a device or program having the function of generating and transmitting to the user a response as to whether or not the transaction is possible based on the determination result.

[0012] A "question response means" is a device or program that has the function of accepting additional questions from users, generating answers to those questions using a generation AI, and providing them to the users. [Brief explanation of the drawings]

[0013] [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

[0014] 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.

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

[0016] 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).

[0017] 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.

[0018] 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.

[0019] 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.

[0020] 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."

[0021] [First embodiment]

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

[0023] 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.

[0024] 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).

[0025] 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.

[0026] 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.

[0027] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0028] 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.

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

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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."

[0034] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, and can compare various regulatory information based on user input, and provide a decision on whether or not to proceed with a transaction and important points to note. Specific embodiments of the system of the present invention are described below.

[0035] Program Overview

[0036] This system consists of a terminal where users can input the name, address, and transaction details of their business partners, and a server that processes and collates this data.

[0037] 1. User Input

[0038] Device:

[0039] The user enters the name, address, and transaction details of the business partner into the form on the terminal and clicks the "Confirm" button. By doing so, the user provides the system with information about the company or organization with which the transaction is being made.

[0040] 2. Receiving and Preprocessing Input Data

[0041] server:

[0042] Receives user input data sent from the terminal, then normalizes and validates the received data, for example, checking that the address format is correct and that the customer name does not contain inappropriate characters.

[0043] 3. Regulatory information collation

[0044] server:

[0045] The system accesses regulatory information databases and lists of anti-social forces and compares them with the data entered by the user, specifically checking whether the name of the business partner is on a sanctions list or whether the address is in a restricted area.

[0046] 4. Transaction Approval Determination

[0047] server:

[0048] Based on the result of the check, a decision is made as to whether the transaction can be carried out. This decision is classified as follows:

[0049] Transactions prohibited: If the business partner is included in the sanctions list or anti-social forces list

[0050] Transaction OK: If all matching results are OK

[0051] OK, but be careful: If your address is in a sanctioned area, or if you need to be careful with the transaction

[0052] 5. Answer Generation

[0053] server:

[0054] Based on the results of the transaction approval / disapproval judgment, a response is generated for the user. For example, a message such as "Transaction not permitted," "Transaction OK," or "Transaction OK, but caution required" is generated, and further detailed warnings are also added.

[0055] 6. Submit your response

[0056] server:

[0057] The generated answer is sent to the user's device, where the user can check whether the transaction is possible and any important points to note.

[0058] 7. Answering questions

[0059] Terminals, Servers:

[0060] The device provides a text box for the user to enter additional questions, allowing the user to request more detailed information. The server accepts the additional questions, uses a generative AI to generate appropriate answers, and sends them back to the device.

[0061] Specific examples

[0062] User Input

[0063] user:

[0064] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button.

[0065] Receiving and Preprocessing Input Data

[0066] server:

[0067] Check the format of the data received, for example, to make sure "123 Main Street, Tokyo, Japan" is a valid address format.

[0068] Regulatory information verification

[0069] server:

[0070] It checks against regulatory information databases to see, for example, whether "ABC Corporation" is on a sanctions list or whether "123 Main Street, Tokyo, Japan" is in a restricted area.

[0071] Determination of whether or not a transaction is possible

[0072] server:

[0073] Based on the results of the comparison, it is determined that "ABC Corporation is OK, but the address is in a sanctioned area, so transactions are OK but caution is required."

[0074] Generate and submit answers

[0075] server:

[0076] Generate and send a message saying, "Transaction OK, but additional verification is required for the transaction as the address is in a sanctioned area."

[0077] Device:

[0078] Display a response message to the user.

[0079] Answering questions

[0080] user:

[0081] The user types in a question such as, "I'd like to know more about areas subject to economic sanctions."

[0082] server:

[0083] The system receives the additional question and uses a generation AI to generate a response that reads, "The relevant region is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." and sends this to the device.

[0084] Device:

[0085] The generated AI's answer is displayed on the user's screen.

[0086] In this way, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides a response, thereby providing users with an efficient means of verifying the trustworthiness of their trading partners.

[0087] The processing flow will be explained below.

[0088] Step 1:

[0089] User:

[0090] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[0091] Step 2:

[0092] Device:

[0093] The terminal transmits the user's input data to the server.

[0094] Step 3:

[0095] server:

[0096] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[0097] Step 4:

[0098] server:

[0099] The server uses the normalized input data to access the regulatory information database and the anti-social forces list, and obtains the latest regulatory information from the database.

[0100] Step 5:

[0101] server:

[0102] The server compares the obtained regulatory information with the user's input data, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0103] Step 6:

[0104] server:

[0105] The server determines whether or not to allow the transaction based on the results of the check. For example, if the customer's name is on the sanctions list, the transaction is denied; if all checks are OK, the transaction is allowed; and if the address is in a sanctions area, the transaction is allowed, but with caution.

[0106] Step 7:

[0107] server:

[0108] The server generates a response message for the user based on the transaction approval / disapproval decision and any related points of caution, such as "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0109] Step 8:

[0110] server:

[0111] The generated reply message is sent to the user's terminal.

[0112] Step 9:

[0113] Device:

[0114] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[0115] Step 10:

[0116] User:

[0117] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[0118] Step 11:

[0119] Device:

[0120] The terminal sends the user's follow-up question to the server.

[0121] Step 12:

[0122] server:

[0123] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[0124] Step 13:

[0125] server:

[0126] The answer to the generated question is sent to the user's terminal.

[0127] Step 14:

[0128] Device:

[0129] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[0130] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[0131] Example 1

[0132] 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."

[0133] The objective of this invention is to quickly and accurately evaluate the trustworthiness of a trading partner. Conventional methods have the problem of being inefficient, taking time to verify regulatory information and determine whether or not to allow a transaction. In addition, it is difficult to respond appropriately to follow-up questions from users, which can result in a decline in the trustworthiness of the transaction.

[0134] 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.

[0135] In this invention, the server includes: input means for a user to input the business name, location, and transaction details; data processing means for receiving the user's input data and standardizing the format and confirming its validity; data comparison means for accessing regulatory information databases and illegal force lists in multiple countries and comparing the data with the user's input data; transaction determination means for determining whether or not the transaction is possible based on the comparison results and generating the result; answer generation means for transmitting the determination result and related points to the user's terminal; and question response means for receiving follow-up questions from the user and generating answers using a generative AI model. This makes it possible to quickly and accurately evaluate the reliability of a business partner and appropriately respond to follow-up questions from the user.

[0136] "User" refers to a user who uses the system to evaluate the trustworthiness of business partners.

[0137] "Business name" is the name of the business partner that the user inputs as the target of evaluation.

[0138] "Location" is the physical address information of the business partner entered by the user.

[0139] "Transaction details" refers to information entered by the user regarding the specific details and nature of the transaction with the business partner.

[0140] "Input means" refers to an interface that allows a user to input the name, address, and transaction details of a business partner into the system.

[0141] The "data processing means" is a part that has the function of standardizing the format and validating the data received from the user.

[0142] "Format unification" is a process for unifying the format of received data.

[0143] "Validation" is a verification process to ensure that received data is accurate.

[0144] The "data comparison means" is a part that has the function of comparing the data entered by the user with the regulatory information database and the list of illegal forces.

[0145] The "Regulatory Information Database" is a database containing information on sanctioned areas and restricted areas of each country.

[0146] The "List of Illegal Forces" is a list of information on anti-social forces and organizations subject to sanctions.

[0147] The "transaction determination means" is a part having a function for determining whether or not a transaction is permitted based on the result of the verification and generating a determination result.

[0148] The "answer generation means" is a part that has a function of generating a message to notify the user of the transaction judgment result and related points to note.

[0149] The "question response means" is the part that has the function of accepting additional questions from users and generating answers using a generative AI model.

[0150] A "generative AI model" is a model that uses AI to generate appropriate answers to questions in natural language.

[0151] This invention is a system for evaluating the reliability of trading partners, collating various regulatory information based on the business name, location, and transaction details entered by the user, and providing the propriety of the transaction and important points to note. This system handles user input, receives and preprocesses data, collates regulatory information, determines whether the transaction is permitted, generates and transmits answers, and responds to follow-up questions.

[0152] System Configuration

[0153] 1. Input Method

[0154] Users use their own devices (PC, smartphone, tablet, etc.) to enter the business name, address, and transaction details into a dedicated form, thereby providing the system with information about the company or organization with which the user is conducting business.

[0155] 2. Data processing means

[0156] The server receives the user's input data. The received data undergoes formatting and validation checks. For example, it standardizes the address format and removes inappropriate characters. It also checks whether the input data is in the correct format.

[0157] 3. Data verification methods

[0158] The server accesses databases of regulatory information from multiple countries (e.g., OFAC sanctions lists) and illegal power lists and checks the data entered by the user to see if the entity name is on a sanctions list or if its location is in a restricted area.

[0159] 4. Transaction Judgment Method

[0160] The server determines whether to allow the transaction based on the verification result. This determination is categorized as follows:

[0161] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[0162] Transaction OK: If there are no problems with the matching results.

[0163] OK, but with caveats: If you need to be careful with the transaction, for example, if your location is in a sanctioned area.

[0164] 5. Answer generation means

[0165] The server generates a response to the user based on the transaction judgment result, such as a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0166] 6. Method of sending responses

[0167] The server then sends the generated response to the user's device, where the user can check whether the transaction is possible and any important points to note.

[0168] 7. How to respond to questions

[0169] Users can use a text box to enter additional questions. The server accepts the user's additional questions, generates an appropriate answer using a generative AI model (e.g., ChatGPT), and sends it back to the user's device. For example, it might generate an answer like, "The region in question is included in Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to official guidelines for detailed regulations."

[0170] Specific examples

[0171] Let's say a user enters the information "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button. The server receives this information and verifies that the address format is correct. It then checks against a regulatory database to see if "Company A" is on a sanctions list and if "123 Main Street, Tokyo, Japan" is in a restricted area.

[0172] Based on the matching results, the server determines that "the transaction is OK, but caution is required, as the address is in a sanctioned area," and generates and sends a message to the user stating, "The transaction is OK, but additional confirmation is required as the address is in a sanctioned area."

[0173] When the user enters an additional question such as "I would like to know more about areas subject to economic sanctions," the server uses a generative AI model to generate an answer: "The area in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." This answer is then sent to the user's device.

[0174] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0175] Step 1: User Input

[0176] User: The user uses input means to enter the business name, address, and transaction details into the dedicated form on their device. For example, the user enters "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and clicks the "Confirm" button. In this step, the entered data is sent to the system.

[0177] Step 2: Receiving and Preprocessing Data

[0178] Server: The server receives input data sent from the terminal. The received data is checked for format consistency and validity. Specifically, it checks whether the address format is correct and whether the business name contains inappropriate characters. For example, it checks whether "123 Main Street, Tokyo, Japan" is a valid address format. The server stores the input data (business name, address, transaction details) in an organized format in an internal database.

[0179] Step 3: Regulatory information verification

[0180] Server: The server compares the data stored in the internal database with the regulatory information database. Specifically, it checks whether the business name is on a sanctions list or whether its location is in a restricted area. In this process, it accesses regulatory information databases from multiple countries (e.g., OFAC lists) and illegal force lists. For example, it checks to see if "Company A" is on a sanctions list. It then saves the comparison results in the internal database.

[0181] Step 4: Determine whether to proceed with the transaction

[0182] Server: Based on the verification result, the server determines whether the transaction is allowed or not. The criteria are as follows:

[0183] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[0184] Transaction OK: If there are no problems with the matching results.

[0185] OK, but with caveats: If the location is in a sanctioned area, you may need to be careful with the transaction.

[0186] For example, it may determine that "Company A is OK, but its location is in a sanctioned area, so transactions are OK but caution is required." It then generates a message to inform the user of the determination result.

[0187] Step 5: Generate an answer

[0188] Server: The server generates a response message for the user based on the transaction judgment result. For example, it generates a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction." The generated message is then stored in an internal database.

[0189] Step 6: Submit your response

[0190] Server: The server generates a response message and sends it to the user's device, where it is displayed.

[0191] On the device: The user sees a message on their device screen saying, "Transaction OK, but because you are located in a sanctioned area, additional verification is required to complete the transaction."

[0192] Step 7: Answer questions

[0193] User: The user uses a text box on the device to enter a follow-up question, for example, "I'd like to know more about sanctioned areas."

[0194] Server: The server receives the user's additional question and generates an appropriate answer using the generative AI model. For example, it generates a message such as, "The region in question is included in the Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to the official guidelines for detailed regulations." The generated answer message is then sent to the user's device.

[0195] Terminal: The user sees the AI's response message on the terminal screen, such as, "The region is included in the Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to the official guidelines for detailed regulations."

[0196] Through these steps, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides an answer. It can also respond to additional questions from users, improving the reliability of transactions.

[0197] (Application example 1)

[0198] 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."

[0199] In commercial transactions, it is extremely important to quickly and accurately assess the trustworthiness and regulatory compliance of trading partners. However, traditional methods rely heavily on manual verification, which is time-consuming and labor-intensive and prone to errors. Furthermore, it is difficult to timely collate multiple regulatory information and lists, resulting in a lack of reliability and efficiency in determining transaction risk. This has created a need for improved business reliability and reduced transaction risk.

[0200] 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.

[0201] In this invention, the server includes: input means for a user to input the name, address, and transaction details of a business partner; data processing means for receiving the user's input data and standardizing and verifying it; inspection means for accessing regulatory information sources and lists of anti-social forces in each country and comparing them with the user's input data; evaluation means for evaluating the feasibility of a transaction based on the comparison results and generating the results; answer generation means for transmitting the evaluation results and related points of caution to the user's device; response means for accepting additional questions from the user and generating answers again using a generation AI; and auxiliary means for comparing the user's business partner's name and address with regulatory information sources and evaluating and generating the feasibility of a transaction and points of caution in real time, thereby enabling the reliability of a business partner to be evaluated quickly and accurately and making transaction decisions based on the results of the comparison with regulatory information.

[0202] A "user" is a person or company that uses the system to input information about a business partner and request a reliability evaluation.

[0203] "Commercial name" is the name of the company or organization with which you are conducting business.

[0204] "Location" refers to information that indicates the specific address or geographic location of a business partner.

[0205] "Transaction details" refers to information about the products or services that the user plans to trade and details of the transaction.

[0206] The "input means" is an interface for the user to input the name, address, and transaction details of the business partner.

[0207] "Data Processing Means" means means for standardizing and verifying the accuracy of data received from users.

[0208] "Standardization" is the process of converting input information into a unified format.

[0209] "Validation" is the process of ensuring that input data is accurate.

[0210] "Regulatory Information Source" is a database that collects information on the laws and regulations of each country.

[0211] The "List of Anti-Social Forces" is a list of organizations and individuals that engage in anti-social activities.

[0212] "Testing means" refers to means for checking user-entered data against regulatory information sources and lists of anti-social forces.

[0213] The "evaluation means" is a means for determining whether or not a transaction can be carried out based on the result of the comparison.

[0214] The "answer generation means" is a means for generating evaluation results and related points of attention and providing them to the user.

[0215] A "response means" is a means of accepting additional questions from users and generating answers using a generation AI.

[0216] The "auxiliary means" refers to a means of comparing the name and location of the user's commercial counterparty with regulatory information sources, and generating a real-time assessment of whether a transaction is possible and what precautions need to be taken.

[0217] "Generative AI" is an artificial intelligence model that generates appropriate answers to user questions.

[0218] This invention is a system that allows users to quickly and accurately evaluate the trustworthiness of their business partners, providing real-time evaluation of whether or not to do business with them based on regulatory information sources and lists of anti-social forces in each country. This system mainly consists of the following components:

[0219] Hardware Configuration

[0220] User device: A device such as a smartphone or PC on which the user enters business partner information and receives evaluation results.

[0221] Server: A high-performance computing device for data processing, matching, evaluation, and answer generation.

[0222] Software Configuration

[0223] Input means: An interface through which a user inputs the name, address, and transaction details of a business partner. For example, this would be an input form on a smartphone application.

[0224] Data processing means: A program to normalize the data received from users and check its format. Specifically, a web framework such as Python's Flask is used.

[0225] Verification method: A program that checks user-entered data against regulatory information sources and lists of anti-social forces. It accesses external regulatory databases using APIs.

[0226] Evaluation method: Logic for determining whether or not a transaction is possible based on the matching results. A decision is made based on various conditions and a result is generated.

[0227] Answer generation means: A program for generating answers that combine the evaluation results and related points of attention and sending them to the user.

[0228] Response method: A function to accept additional questions from the user and generate answers again using generative AI. Possible generative AI models include OpenAI's GPT-3.

[0229] Auxiliary tool: A program that checks regulatory information in real time based on the user's commercial partner's name and location, and generates a transaction approval / disapproval and warnings.

[0230] Processing Flow

[0231] The user's terminal provides an interface for inputting the name, address, and transaction details of the business partner. This input is sent to the server, where the data processing means normalizes and verifies it. Then, based on the collated data, the inspection means accesses external regulatory information sources and lists of anti-social forces for collation.

[0232] The evaluation means determines whether or not the transaction is possible based on the collation result and generates an evaluation result. Based on this result, the answer generation means transmits to the user's terminal whether or not the transaction is possible and any necessary precautions.

[0233] If the user enters additional questions, the server's response mechanism will utilize AI generation to generate appropriate answers and send them to the user's device. In addition, the assistance mechanism will perform real-time verification to support quick and accurate trading decisions.

[0234] Specific examples

[0235] For example, a user enters a "general company name" as the business destination, a "general address" as the location, and "purchase of goods" as the transaction details. The server receives the information, and after the data processing means correctly formats it, the inspection means checks it against a regulatory information database and a list of anti-social forces. The evaluation means then determines that "the general company name is OK, but the general address requires caution," and the answer generation means notifies the user of the result. If the user adds a more detailed question, the response means uses a generation AI to respond, "Confirmation is required as specific regulations apply to general areas."

[0236] Prompt Sentence Examples

[0237] "Based on user input, check the regulatory information for companies and addresses and evaluate whether or not to allow transactions. Input example: 'General company name', 'General address'"

[0238] In this way, the system quickly and accurately evaluates the reliability of trading partners, and helps users make effective trading decisions.

[0239] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0240] Step 1:

[0241] User enters business name, address, and transaction details

[0242] The user uses the interface of their device (such as a smartphone or PC) to enter the name, address, and transaction details of the commercial partner. Once the input is complete, they press the "Confirm" button and the data is sent to the server. The input data is entered directly into the text box.

[0243] Input: Name of business partner, address, transaction details

[0244] Output: Input data (commercial name, address, transaction details)

[0245] Step 2:

[0246] Normalizing and validating data received by the server

[0247] The server receives input data sent by the user. The received data is first normalized. For example, commas and spaces are standardized, and address formats are checked to ensure they are correct. Next, the data is validated to ensure there are no errors in the input. If improperly formatted data or missing required fields are detected, an error message is generated and sent back to the user.

[0248] Input: Input data (business partner name, address, transaction details)

[0249] Output: Normalized and validated data, or error messages

[0250] Step 3:

[0251] The server accesses regulatory information sources and lists of anti-social forces and performs cross-checking.

[0252] After normalization and validation are complete, the server accesses regulatory information sources and anti-social forces lists to verify the data. Specifically, it checks whether the customer's name is on a sanctions list or whether the customer's location is in a restricted area. This verification is performed in real time through API communication with external databases.

[0253] Input: Normalized and validated data

[0254] Output: Matching result (whether the transaction is possible or not, points to note)

[0255] Step 4:

[0256] The server evaluates whether the transaction is possible based on the matching results and generates a result.

[0257] The server evaluates whether the transaction is possible or not based on the matching results. The evaluation is classified as follows: No transaction (if the business destination is on the sanctions list), OK transaction (if all matching results are OK), OK but with cautions (if the location is in a sanctions-listed area but the business destination itself is OK). Based on this evaluation, a result including detailed cautions is generated.

[0258] Input: Matching result (transaction possibility, points to note)

[0259] Output: Evaluation result (transaction possibility, points to note)

[0260] Step 5:

[0261] The server notifies the user of the evaluation results and related precautions.

[0262] The server uses the response generation means to send an appropriate message to the user's device based on the generated evaluation results and points to note. The message includes whether the transaction is OK, NG, OK with points to note, and specific points to note.

[0263] Input: Evaluation result (transaction possibility, points to note)

[0264] Output: A message to be sent to the user

[0265] Step 6:

[0266] Handling follow-up questions from the user

[0267] If the user wants more detailed information, an interface is provided for entering additional questions. Once the user enters and submits the question, the server receives the question and uses a generative AI model (e.g., GPT-3) to generate an appropriate answer. The generated answer is then sent back to the user.

[0268] Input: Additional question text

[0269] Output: The answer from the generative AI model and its transmission

[0270] Through the above steps, this system quickly and accurately evaluates the reliability of trading partners and helps users make effective trading decisions.

[0271] 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.

[0272] The present invention is a system that quickly and accurately evaluates the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to consider, thereby helping users to proceed with transactions with peace of mind. Furthermore, by combining the system with an emotion engine that recognizes user emotions and responds appropriately based on those emotions, the user experience can be improved. Specific embodiments of the system of the present invention are described below.

[0273] Program Overview

[0274] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server for processing and collating this data, and an emotion engine for recognizing the user's emotions.

[0275] 1. User Input

[0276] Device:

[0277] The user enters the name, address, and transaction details into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[0278] 2. Receiving and Preprocessing Input Data

[0279] server:

[0280] Receives user input data sent from the terminal and normalizes and validates it. For example, it checks whether the address format is correct or whether the customer name contains inappropriate characters, and corrects any inappropriate parts.

[0281] 3. Emotional Recognition

[0282] server:

[0283] The emotion engine analyzes the user's input data (e.g., typing speed, number of input errors, etc.) to recognize the user's emotional state, for example, determining whether they are feeling anxious or stressed.

[0284] 4. Regulatory information collation

[0285] server:

[0286] Using the normalized input data, the regulatory information database and anti-social forces list are accessed to obtain the latest regulatory information.

[0287] 5. Matching

[0288] server:

[0289] The system compares the obtained regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0290] 6. Transaction Approval Determination

[0291] server:

[0292] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[0293] 7. Answer Generation

[0294] server:

[0295] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0296] 8. Submitting your response

[0297] server:

[0298] The generated response message is sent to the user's terminal.

[0299] 9. View Answers

[0300] Device:

[0301] The received response message will be displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[0302] 10. Answering questions

[0303] Terminals, Servers:

[0304] If a user wants more detailed information, they can enter additional questions. These questions are sent to the server, which uses a generative AI to generate an appropriate answer and sends it back to the device. For example, if a user enters the question, "I'd like to know more about areas subject to economic sanctions," the server will generate the answer, "The relevant areas are included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[0305] Specific examples

[0306] User Input and Emotion Recognition

[0307] user:

[0308] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "purchasing electronic components," and presses the "Confirm" button. At this time, the emotion engine recognizes that the user is feeling anxious based on the speed of input and the frequency of error messages.

[0309] Answer generation and message sending

[0310] server:

[0311] Based on the results of the comparison, the server determines that the transaction is OK, but there are some caveats, and generates a message stating, "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction." In addition, the emotion engine detects the user's anxiety and adjusts the tone of the message to be softer.

[0312] Device:

[0313] Display the generated message on the user's screen.

[0314] In this way, the system quickly and accurately compares various regulatory information based on user input to determine whether a transaction can be carried out, and furthermore, by appropriately recognizing and responding to user emotions using an emotion engine, it improves the user experience.

[0315] The processing flow will be explained below.

[0316] Step 1:

[0317] User:

[0318] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[0319] Step 2:

[0320] Device:

[0321] The terminal transmits the user's input data to the server.

[0322] Step 3:

[0323] server:

[0324] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[0325] Step 4:

[0326] server:

[0327] The server sends the normalized input data to the emotion engine.

[0328] Step 5:

[0329] server:

[0330] The emotion engine analyzes the user's input data and recognizes the user's emotional state based on the input speed, frequency of error messages, etc. For example, if a user makes many input errors in a short period of time, it can determine that the user is feeling anxious or stressed.

[0331] Step 6:

[0332] server:

[0333] The server uses the normalized input data to access the regulatory information database and the anti-social forces list to obtain the latest regulatory information.

[0334] Step 7:

[0335] server:

[0336] The system compares the acquired regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0337] Step 8:

[0338] server:

[0339] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[0340] Step 9:

[0341] server:

[0342] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0343] Step 10:

[0344] server:

[0345] The generated reply message is sent to the user's terminal.

[0346] Step 11:

[0347] Device:

[0348] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[0349] Step 12:

[0350] User:

[0351] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[0352] Step 13:

[0353] Device:

[0354] The terminal sends the user's follow-up question to the server.

[0355] Step 14:

[0356] server:

[0357] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[0358] Step 15:

[0359] server:

[0360] The answer to the generated question is sent to the user's terminal.

[0361] Step 16:

[0362] Device:

[0363] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[0364] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[0365] Example 2

[0366] 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."

[0367] Conventional systems for evaluating the trustworthiness of business partners only evaluate basic information about business partners and do not take into account the user's emotional state, making it impossible to reduce user stress and anxiety. Furthermore, determining whether or not to transact based solely on the results of verification does not provide sufficient information on specific points to note or when additional confirmation is required. This does not adequately provide an environment in which users can proceed with transactions with peace of mind.

[0368] 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.

[0369] In this invention, the server includes: input means for a user to input the name, address, and transaction details of the business partner; data processing means for receiving the user's input data and normalizing and validating it; emotion recognition means for analyzing the user's emotions and recognizing their emotional state; comparison means for accessing regulatory information databases and anti-social forces lists in each country and comparing the user's input data with them; determination means for determining whether or not to allow a transaction based on the comparison results and generating the result; answer generation means for adjusting the determination result and related precautions based on the user's emotional state and transmitting them to the user's terminal; and question response means for receiving additional questions from the user and generating answers again using a generation AI. This enables appropriate responses that take the user's emotional state into consideration, allowing the user to proceed with the transaction with peace of mind.

[0370] "Input means" refers to a device or interface that allows a user to input the name, address, and transaction details of a business partner.

[0371] A "data processing means" is a system that has the functionality to receive user input data and normalize and validate that data.

[0372] An "emotion recognition means" is a system that has the function of analyzing a user's input behavior and data and identifying the user's emotional state.

[0373] The "matching means" is a system that has the function of matching the user's input data with each country's regulatory information database and anti-social forces list.

[0374] The "determination means" is a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[0375] The "answer generation means" is a system that has the function of adjusting the judgment results and related points of attention based on the user's emotional state and transmitting them to the user's terminal.

[0376] The "question response means" is a system that accepts additional questions from users, uses generation AI to generate appropriate answers, and provides them to the user again.

[0377] "Generative AI" is an artificial intelligence model that generates appropriate answers in natural language to users' questions.

[0378] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to note. It also improves the user experience by recognizing the user's emotions and responding appropriately based on those emotions. Specific embodiments of the present invention are described below.

[0379] System Overview

[0380] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server that processes this data and recognizes emotions, and a database that collates regulatory information.It also uses a generative AI model to generate appropriate answers to follow-up questions from users.

[0381] 1. User Input

[0382] Device:

[0383] The user enters the name, address, and transaction details of the customer into a web form on their device, for example, "XYZ Corporation," "456 Main Street, New York, USA," and "Sales of Electronics," and clicks the "Confirm" button. This input is then sent to the server.

[0384] 2. Data Reception and Preprocessing

[0385] server:

[0386] The server receives input data sent from the terminal. First, it normalizes the data and checks that the input format matches. For example, if the address format is incorrect or if an inappropriate character string is included in the customer name, the server can correct that part.

[0387] 3. Emotional Recognition

[0388] server:

[0389] The emotion engine analyzes the user's input data (e.g., input speed, number of input errors, etc.) and recognizes the user's emotional state. For example, if the input speed is slow and there are many input errors, it will recognize that the user is feeling anxious.

[0390] 4. Regulatory information collation

[0391] server:

[0392] The server uses the normalized input data to access regulatory information databases and anti-social forces lists to obtain the latest regulatory information, such as from the Office of Foreign Assets Control (OFAC) and Interpol databases.

[0393] 5. Matching and Judging

[0394] server:

[0395] The system compares the acquired regulatory information with the user's input data to check whether the business partner's name is included on a sanctions list or anti-social forces list. It also checks whether the address is in a specific restricted area. Based on the comparison results, the system determines whether the transaction is "NG," "OK," or "OK ​​but with caution."

[0396] 6. Answer Generation

[0397] server:

[0398] The server generates a response message for the user based on the result of the judgment and the user's emotional state. For example, the message might say, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction," and is written in a tone that takes the user's emotions into consideration.

[0399] 7. Submitting and Viewing Your Answers

[0400] server:

[0401] The generated response message is sent to the user's terminal.

[0402] Device:

[0403] The response message received by the terminal is displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[0404] 8. Answering questions

[0405] Terminals, Servers:

[0406] If the user wants more information, they can enter a follow-up question. The follow-up question is sent to the server, and a generative AI model (e.g., GPT-4) generates an appropriate answer and sends it back to the device. For example, if the prompt is "I'd like to know more about the area under economic sanctions," a detailed answer will be generated: "The area is subject to economic sanctions, and authorization is required for certain transactions."

[0407] In this way, the system quickly and accurately compares various regulatory information based on user input and determines whether a transaction can be carried out. It also uses an emotion engine to recognize user emotions and respond appropriately, enhancing the user's sense of security.

[0408] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0409] Step 1:

[0410] Input: The user enters the customer name, address, and transaction details.

[0411] What happens: A user enters information into a web form on their device, such as "XYZ Corporation," "456 Main Street, New York, USA," and "Electronics Sales," and clicks the "Confirm" button.

[0412] Output: User input data is sent from the device to the server.

[0413] Step 2:

[0414] Input: User input data received from the device.

[0415] Specific operation: The server receives the data sent from the terminal and normalizes and validates the data. For example, it checks whether there are any inappropriate characters in the address format or the customer name. If there are any inappropriate parts, it automatically corrects them.

[0416] Output: Normalized and validated data.

[0417] Step 3:

[0418] Input: Normalized and validated user input data.

[0419] Specific operation: The server's emotion engine analyzes the input speed of input data and the frequency of error messages to recognize the user's emotional state. For example, if the input speed is slower than usual and an error message appears three or more times, it will determine that the user is feeling "anxiety" or "stressed."

[0420] Output: User's emotional state (e.g., anxiety, stress).

[0421] Step 4:

[0422] Input: Normalized and validated user input data.

[0423] Specific operation: The server accesses regulatory information databases (e.g., OFAC lists, Interpol lists) and obtains the latest regulatory information.

[0424] Output: Latest regulatory information.

[0425] Step 5:

[0426] Input: Up-to-date regulatory information and normalized user input data.

[0427] Specific operation: The server compares the obtained regulatory information with the user's input data, for example, checking whether the customer name is on a sanctions list or anti-social forces list, or whether the address is in a specific restricted area.

[0428] Output: Verification result (e.g., no problem, transaction not accepted, caution required).

[0429] Step 6:

[0430] Input: Match result.

[0431] Specific operation: The server determines whether or not to allow a transaction based on the matching results. For example, if the customer name is included in the sanctions list, the transaction is denied. If all matching results are OK, the transaction is allowed. If the address is included in a sanctions area, the transaction is allowed, but with caution.

[0432] Output: Transaction approval / disapproval result.

[0433] Step 7:

[0434] Input: Transaction decision result and user's emotional state.

[0435] Specific operation: The server adjusts the judgment result and related points of caution based on the user's emotional state and generates a response message to the user. For example, if the transaction is OK but the address is in an area subject to economic sanctions, the server will create a message in a softer tone, sensing the user's anxiety, such as "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0436] Output: The reply message.

[0437] Step 8:

[0438] Input: The answer message.

[0439] Specific operation: The server sends the generated response message to the user's terminal.

[0440] Output: The reply message is sent to the user's terminal.

[0441] Step 9:

[0442] Input: The answer message sent to the user's device.

[0443] Specific operation: The device displays the received response message on the user's screen.

[0444] Output: Message displayed to the user regarding whether the transaction is possible or not and important points to note.

[0445] Step 10:

[0446] Input: Any additional questions from the user.

[0447] How it works: If a user wants more information, they enter an additional question on their device and send it to the server. The server uses a generative AI model (e.g., GPT-4) to generate an appropriate answer and send it back to the device. For example, if a user asks, "I'd like to know more about areas subject to economic sanctions," the generative AI model will generate the answer, "The area in question is subject to economic sanctions, and authorization is required for certain transactions."

[0448] Output: The generated answers to the follow-up questions are sent to the user's device and displayed.

[0449] (Application example 2)

[0450] 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."

[0451] Conventional supplier evaluation systems determine whether to approve a transaction by checking against a regulatory information database, but they often leave users feeling uneasy about the evaluation because they lack appropriate responses that reflect the user's emotional state. Furthermore, the lack of consideration for emotional recognition can sometimes impair the user experience, which is an issue.

[0452] The identification processing 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: input means through which a user inputs the name, address, and transaction details of the business partner; data processing means that receives the user's input data and normalizes and validates it; comparison means that accesses regulatory information databases and anti-social forces lists in various countries and compares the user's input data with the data; determination means that determines whether the transaction is permitted based on the comparison results and generates the result; answer generation means that transmits the determination result and related precautions to the user's terminal; question response means that accepts additional questions from the user and generates answers using a new generation AI; emotion recognition means that recognizes the user's emotional state based on the input speed and number of errors; and tone-adjusted message generation means that generates messages with the tone adjusted based on the user's emotional state. This makes it possible to provide appropriate responses that take the user's emotional state into consideration and improve the reliability of transaction decisions.

[0453] "Input means" refers to the device or software that allows a user to input the name, address, and transaction details of the customer.

[0454] "Data Processing Means" refers to the systems and algorithms that receive, normalize, and validate user input data.

[0455] "Matching means" refers to a system that has the ability to access regulatory information databases and anti-social force lists in each country and match them with user-entered data.

[0456] "Determination means" refers to a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[0457] "Answer generation means" refers to a system that has the function of transmitting the judgment results and related points of caution to the user's terminal.

[0458] "Question response means" refers to a system that has the function of accepting additional questions from users and generating answers again using generation AI.

[0459] "Emotion recognition means" refers to systems or algorithms that recognize a user's emotional state based on input speed or frequency of error messages.

[0460] "Tone-adjusted message generator" refers to a system or algorithm for generating tone-adjusted messages based on emotional state.

[0461] The present invention provides a system that enables a user to quickly and accurately evaluate the reliability of a trading partner and proceed with a transaction with peace of mind. Specific embodiments of the system of the present invention will be described below.

[0462] System Configuration

[0463] This system mainly consists of the following elements:

[0464] 1. Device:

[0465] The user is provided with input means for inputting the name, address, and transaction details of the business partner.

[0466] Specific devices that can be used include smartphones, computers, tablets, etc.

[0467] 2. Server:

[0468] A data processing means is provided for receiving user input data and for normalizing and validating the data.

[0469] It is equipped with a means of comparison that accesses regulatory information databases and anti-social force lists in each country and compares them with user-entered data.

[0470] The system includes a determination means for determining whether or not a transaction is possible based on the result of the verification and generating the result.

[0471] The system is provided with an answer generation means for transmitting the judgment result and related points of caution to the user's terminal.

[0472] It is equipped with a question response function that accepts additional questions from users and generates answers using the generation AI again.

[0473] The system is equipped with an emotion recognition means that recognizes the user's emotional state based on input speed and frequency of error messages.

[0474] The device includes a tone-adjusted message generating means for generating a message with a tone adjusted based on the emotional state.

[0475] 3. Software and Services Used:

[0476] Use Python as the programming language.

[0477] Use requests, a Python library for handling HTTP requests.

[0478] Use an emotion recognition engine API (e.g. emotionrecognition API) for emotion recognition.

[0479] Use regulatory information database APIs (e.g., regulatoryinfo API) to query regulatory information.

[0480] Processing flow

[0481] The user uses the terminal to enter the name of the business partner, address, and transaction details, and then clicks the "Confirm" button. An example of input is as follows:

[0482] Account Name: XYZ Corporation

[0483] Address: 456 Market Street, Tokyo, Japan

[0484] Transaction: Purchase of electronic components

[0485] The terminal sends the user's input data to the server, which first normalizes and validates the data, then accesses a regulatory information database and a list of anti-social forces to check and determine whether the transaction should proceed.

[0486] Additionally, the app uses an emotion recognition API to recognize a user's emotional state by analyzing their typing speed and the frequency of error messages. For example, if it determines that the user is feeling anxious, it will generate a message with a tone tailored to that emotional state.

[0487] The judgment result and emotion recognition result are integrated to generate a final answer message. This message is sent to the user's device and displayed to the user as an example:

[0488] The transaction is OK, but your address is in a sanctioned area. You seem to be concerned, so we need to do some additional verification.

[0489] If the user wants more information, they can ask a follow-up question, which is sent to the server, which uses the generative AI model to generate an appropriate answer and sends it back to the user.

[0490] The above is a specific example of the embodiment of the present invention. This system allows users to judge the reliability of their business partners with high accuracy, and provides a sense of security by receiving responses that correspond to their emotions.

[0491] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0492] Step 1:

[0493] The user enters the customer's name, address, and transaction details into the terminal.

[0494] The user enters the client name, address, and transaction details into the input form and clicks the "Confirm" button. An example of input is as follows:

[0495] Account Name: XYZ Corporation

[0496] Address: 456 Market Street, Tokyo, Japan

[0497] Transaction: Purchase of electronic components

[0498] The input data is sent from the terminal to the server.

[0499] Step 2:

[0500] The server receives the user input data and performs normalization and validation.

[0501] The server receives user-entered data sent from the terminal. The normalization process checks for address format consistency and appropriate client name strings to improve data consistency. The validation process checks whether all required fields are filled in and the data is accurate.

[0502] Input: User input data (client name, address, transaction details)

[0503] Output: Normalized and validated data

[0504] Step 3:

[0505] The server performs emotion recognition based on the input data.

[0506] The emotion recognition engine analyzes the user's emotional state based on data such as the user's input speed and the frequency of input error messages, and determines whether the user is feeling anxious or stressed, for example, based on the results of this analysis.

[0507] Input: Corrected user input data, input speed, frequency of error messages

[0508] Output: User's emotional state (e.g., anxious, calm, etc.)

[0509] Step 4:

[0510] The server accesses the regulatory information database and anti-social forces list to perform the check.

[0511] Using the normalized input data, the server accesses each country's regulatory information database and anti-social forces list and checks it against the user's input data. This check process verifies whether the customer name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0512] Input: Normalized user input data

[0513] Output: Verification result (e.g., transaction OK, transaction NG, cautions)

[0514] Step 5:

[0515] The server determines whether the transaction is possible and generates a result.

[0516] The server determines whether or not to allow the transaction based on the matching results. For example, if the client's name is on the sanctions list, the server determines that the transaction is "NG," but if all matching results are satisfactory, the server determines that the transaction is "OK." If the address is in a sanctions-targeted area, the server determines that the transaction is "OK, but with caution."

[0517] Input: Matching result

[0518] Output: Transaction availability determination result (e.g., transaction OK, transaction NG, cautions apply)

[0519] Step 6:

[0520] The server generates a response message based on the judgment result and emotion recognition result.

[0521] The server combines the transaction approval / disapproval judgment result with the emotion recognition result to generate a response message for the user. For example, if the transaction is OK but the user is feeling uneasy, the tone of the message is adjusted to generate a message such as, "The transaction is OK, but you seem to be feeling uneasy, so we will conduct further confirmation."

[0522] Input: Transaction approval / disapproval decision result, user's emotional state

[0523] Output: Tone-adjusted answer message

[0524] Step 7:

[0525] The server sends a response message to the terminal.

[0526] The generated response message is sent from the server to the user's terminal, where the judgment result and related points to note are displayed.

[0527] Input: Reply message

[0528] Output: Message displayed on the user's terminal

[0529] Step 8:

[0530] The user enters a follow-up question, and the server again uses the generation AI to generate an answer.

[0531] If the user enters a follow-up question, the question is sent to the server, which uses a generative AI model to generate an appropriate answer and sends it back to the user's device. For example, if the user enters, "I'd like to know more about sanctioned areas," the server might generate a response such as, "The area is on the sanctions list, and authorization is required for certain transactions."

[0532] Input: User's additional question

[0533] Output: Answer message from the generating AI

[0534] This series of processes allows users to quickly and accurately judge the reliability of their trading partners, allowing them to proceed with transactions with peace of mind. In addition, receiving responses that reflect their emotions improves the user experience.

[0535] 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.

[0536] 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.

[0537] 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.

[0538] [Second embodiment]

[0539] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0540] 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.

[0541] 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).

[0542] 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.

[0543] 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.

[0544] 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).

[0545] 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.

[0546] 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.

[0547] 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.

[0548] 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.

[0549] 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.

[0550] 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."

[0551] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, and can compare various regulatory information based on user input, and provide a decision on whether or not to proceed with a transaction and important points to note. Specific embodiments of the system of the present invention are described below.

[0552] Program Overview

[0553] This system consists of a terminal where users can input the name, address, and transaction details of their business partners, and a server that processes and collates this data.

[0554] 1. User Input

[0555] Device:

[0556] The user enters the name, address, and transaction details of the business partner into the form on the terminal and clicks the "Confirm" button. By doing so, the user provides the system with information about the company or organization with which the transaction is being made.

[0557] 2. Receiving and Preprocessing Input Data

[0558] server:

[0559] Receives user input data sent from the terminal, then normalizes and validates the received data, for example, checking that the address format is correct and that the customer name does not contain inappropriate characters.

[0560] 3. Regulatory information collation

[0561] server:

[0562] The system accesses regulatory information databases and lists of anti-social forces and compares them with the data entered by the user, specifically checking whether the name of the business partner is on a sanctions list or whether the address is in a restricted area.

[0563] 4. Transaction Approval Determination

[0564] server:

[0565] Based on the result of the check, a decision is made as to whether the transaction can be carried out. This decision is classified as follows:

[0566] Transactions prohibited: If the business partner is included in the sanctions list or anti-social forces list

[0567] Transaction OK: If all matching results are OK

[0568] OK, but be careful: If your address is in a sanctioned area, or if you need to be careful with the transaction

[0569] 5. Answer Generation

[0570] server:

[0571] Based on the results of the transaction approval / disapproval judgment, a response is generated for the user. For example, a message such as "Transaction not permitted," "Transaction OK," or "Transaction OK, but caution required" is generated, and further detailed warnings are also added.

[0572] 6. Submit your response

[0573] server:

[0574] The generated answer is sent to the user's device, where the user can check whether the transaction is possible and any important points to note.

[0575] 7. Answering questions

[0576] Terminals, Servers:

[0577] The device provides a text box for the user to enter additional questions, allowing the user to request more detailed information. The server accepts the additional questions, uses a generative AI to generate appropriate answers, and sends them back to the device.

[0578] Specific examples

[0579] User Input

[0580] user:

[0581] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button.

[0582] Receiving and Preprocessing Input Data

[0583] server:

[0584] Check the format of the data received, for example, to make sure "123 Main Street, Tokyo, Japan" is a valid address format.

[0585] Regulatory information verification

[0586] server:

[0587] It checks against regulatory information databases to see, for example, whether "ABC Corporation" is on a sanctions list or whether "123 Main Street, Tokyo, Japan" is in a restricted area.

[0588] Determination of whether or not a transaction is possible

[0589] server:

[0590] Based on the results of the comparison, it is determined that "ABC Corporation is OK, but the address is in a sanctioned area, so transactions are OK but caution is required."

[0591] Generate and submit answers

[0592] server:

[0593] Generate and send a message saying, "Transaction OK, but additional verification is required for the transaction as the address is in a sanctioned area."

[0594] Device:

[0595] Display a response message to the user.

[0596] Answering questions

[0597] user:

[0598] The user types in a question such as, "I'd like to know more about areas subject to economic sanctions."

[0599] server:

[0600] The system receives the additional question and uses a generation AI to generate a response that reads, "The relevant region is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." and sends this to the device.

[0601] Device:

[0602] The generated AI's answer is displayed on the user's screen.

[0603] In this way, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides a response, thereby providing users with an efficient means of verifying the trustworthiness of their trading partners.

[0604] The processing flow will be explained below.

[0605] Step 1:

[0606] User:

[0607] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[0608] Step 2:

[0609] Device:

[0610] The terminal transmits the user's input data to the server.

[0611] Step 3:

[0612] server:

[0613] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[0614] Step 4:

[0615] server:

[0616] The server uses the normalized input data to access the regulatory information database and the anti-social forces list, and obtains the latest regulatory information from the database.

[0617] Step 5:

[0618] server:

[0619] The server compares the obtained regulatory information with the user's input data, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0620] Step 6:

[0621] server:

[0622] The server determines whether or not to allow the transaction based on the results of the check. For example, if the customer's name is on the sanctions list, the transaction is denied; if all checks are OK, the transaction is allowed; and if the address is in a sanctions area, the transaction is allowed, but with caution.

[0623] Step 7:

[0624] server:

[0625] The server generates a response message for the user based on the transaction approval / disapproval decision and any related points of caution, such as "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0626] Step 8:

[0627] server:

[0628] The generated reply message is sent to the user's terminal.

[0629] Step 9:

[0630] Device:

[0631] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[0632] Step 10:

[0633] User:

[0634] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[0635] Step 11:

[0636] Device:

[0637] The terminal sends the user's follow-up question to the server.

[0638] Step 12:

[0639] server:

[0640] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[0641] Step 13:

[0642] server:

[0643] The answer to the generated question is sent to the user's terminal.

[0644] Step 14:

[0645] Device:

[0646] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[0647] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[0648] Example 1

[0649] 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."

[0650] The objective of this invention is to quickly and accurately evaluate the trustworthiness of a trading partner. Conventional methods have the problem of being inefficient, taking time to verify regulatory information and determine whether or not to allow a transaction. In addition, it is difficult to respond appropriately to follow-up questions from users, which can result in a decline in the trustworthiness of the transaction.

[0651] 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.

[0652] In this invention, the server includes: input means for a user to input the business name, location, and transaction details; data processing means for receiving the user's input data and standardizing the format and confirming its validity; data comparison means for accessing regulatory information databases and illegal force lists in multiple countries and comparing the data with the user's input data; transaction determination means for determining whether or not the transaction is possible based on the comparison results and generating the result; answer generation means for transmitting the determination result and related points to the user's terminal; and question response means for receiving follow-up questions from the user and generating answers using a generative AI model. This makes it possible to quickly and accurately evaluate the reliability of a business partner and appropriately respond to follow-up questions from the user.

[0653] "User" refers to a user who uses the system to evaluate the trustworthiness of business partners.

[0654] "Business name" is the name of the business partner that the user inputs as the target of evaluation.

[0655] "Location" is the physical address information of the business partner entered by the user.

[0656] "Transaction details" refers to information entered by the user regarding the specific details and nature of the transaction with the business partner.

[0657] "Input means" refers to an interface that allows a user to input the name, address, and transaction details of a business partner into the system.

[0658] The "data processing means" is a part that has the function of standardizing the format and validating the data received from the user.

[0659] "Format unification" is a process for unifying the format of received data.

[0660] "Validation" is a verification process to ensure that received data is accurate.

[0661] The "data comparison means" is a part that has the function of comparing the data entered by the user with the regulatory information database and the list of illegal forces.

[0662] The "Regulatory Information Database" is a database containing information on sanctioned areas and restricted areas of each country.

[0663] The "List of Illegal Forces" is a list of information on anti-social forces and organizations subject to sanctions.

[0664] The "transaction determination means" is a part having a function for determining whether or not a transaction is permitted based on the result of the verification and generating a determination result.

[0665] The "answer generation means" is a part that has a function of generating a message to notify the user of the transaction judgment result and related points to note.

[0666] The "question response means" is the part that has the function of accepting additional questions from users and generating answers using a generative AI model.

[0667] A "generative AI model" is a model that uses AI to generate appropriate answers to questions in natural language.

[0668] This invention is a system for evaluating the reliability of trading partners, collating various regulatory information based on the business name, location, and transaction details entered by the user, and providing the propriety of the transaction and important points to note. This system handles user input, receives and preprocesses data, collates regulatory information, determines whether the transaction is permitted, generates and transmits answers, and responds to follow-up questions.

[0669] System Configuration

[0670] 1. Input Method

[0671] Users use their own devices (PC, smartphone, tablet, etc.) to enter the business name, address, and transaction details into a dedicated form, thereby providing the system with information about the company or organization with which the user is conducting business.

[0672] 2. Data processing means

[0673] The server receives the user's input data. The received data undergoes formatting and validation checks. For example, it standardizes the address format and removes inappropriate characters. It also checks whether the input data is in the correct format.

[0674] 3. Data verification methods

[0675] The server accesses databases of regulatory information from multiple countries (e.g., OFAC sanctions lists) and illegal power lists and checks the data entered by the user to see if the entity name is on a sanctions list or if its location is in a restricted area.

[0676] 4. Transaction Judgment Method

[0677] The server determines whether to allow the transaction based on the verification result. This determination is categorized as follows:

[0678] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[0679] Transaction OK: If there are no problems with the matching results.

[0680] OK, but with caveats: If you need to be careful with the transaction, for example, if your location is in a sanctioned area.

[0681] 5. Answer generation means

[0682] The server generates a response to the user based on the transaction judgment result, such as a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0683] 6. Method of sending responses

[0684] The server then sends the generated response to the user's device, where the user can check whether the transaction is possible and any important points to note.

[0685] 7. How to respond to questions

[0686] Users can use a text box to enter additional questions. The server accepts the user's additional questions, generates an appropriate answer using a generative AI model (e.g., ChatGPT), and sends it back to the user's device. For example, it might generate an answer like, "The region in question is included in Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to official guidelines for detailed regulations."

[0687] Specific examples

[0688] Let's say a user enters the information "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button. The server receives this information and verifies that the address format is correct. It then checks against a regulatory database to see if "Company A" is on a sanctions list and if "123 Main Street, Tokyo, Japan" is in a restricted area.

[0689] Based on the matching results, the server determines that "the transaction is OK, but caution is required, as the address is in a sanctioned area," and generates and sends a message to the user stating, "The transaction is OK, but additional confirmation is required as the address is in a sanctioned area."

[0690] When the user enters an additional question such as "I would like to know more about areas subject to economic sanctions," the server uses a generative AI model to generate an answer: "The area in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." This answer is then sent to the user's device.

[0691] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0692] Step 1: User Input

[0693] User: The user uses input means to enter the business name, address, and transaction details into the dedicated form on their device. For example, the user enters "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and clicks the "Confirm" button. In this step, the entered data is sent to the system.

[0694] Step 2: Receiving and Preprocessing Data

[0695] Server: The server receives input data sent from the terminal. The received data is checked for format consistency and validity. Specifically, it checks whether the address format is correct and whether the business name contains inappropriate characters. For example, it checks whether "123 Main Street, Tokyo, Japan" is a valid address format. The server stores the input data (business name, address, transaction details) in an organized format in an internal database.

[0696] Step 3: Regulatory information verification

[0697] Server: The server compares the data stored in the internal database with the regulatory information database. Specifically, it checks whether the business name is on a sanctions list or whether its location is in a restricted area. In this process, it accesses regulatory information databases from multiple countries (e.g., OFAC lists) and illegal force lists. For example, it checks to see if "Company A" is on a sanctions list. It then saves the comparison results in the internal database.

[0698] Step 4: Determine whether to proceed with the transaction

[0699] Server: Based on the verification result, the server determines whether the transaction is allowed or not. The criteria are as follows:

[0700] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[0701] Transaction OK: If there are no problems with the matching results.

[0702] OK, but with caveats: If the location is in a sanctioned area, you may need to be careful with the transaction.

[0703] For example, it may determine that "Company A is OK, but its location is in a sanctioned area, so transactions are OK but caution is required." It then generates a message to inform the user of the determination result.

[0704] Step 5: Generate an answer

[0705] Server: The server generates a response message for the user based on the transaction judgment result. For example, it generates a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction." The generated message is then stored in an internal database.

[0706] Step 6: Submit your response

[0707] Server: The server generates a response message and sends it to the user's device, where it is displayed.

[0708] On the device: The user sees a message on their device screen saying, "Transaction OK, but because you are located in a sanctioned area, additional verification is required to complete the transaction."

[0709] Step 7: Answer questions

[0710] User: The user uses a text box on the device to enter a follow-up question, for example, "I'd like to know more about sanctioned areas."

[0711] Server: The server receives the user's additional question and generates an appropriate answer using the generative AI model. For example, it generates a message such as, "The region in question is included in the Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to the official guidelines for detailed regulations." The generated answer message is then sent to the user's device.

[0712] Terminal: The user sees the AI's response message on the terminal screen, such as, "The region is included in the Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to the official guidelines for detailed regulations."

[0713] Through these steps, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides an answer. It can also respond to additional questions from users, improving the reliability of transactions.

[0714] (Application example 1)

[0715] 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."

[0716] In commercial transactions, it is extremely important to quickly and accurately assess the trustworthiness and regulatory compliance of trading partners. However, traditional methods rely heavily on manual verification, which is time-consuming and labor-intensive and prone to errors. Furthermore, it is difficult to timely collate multiple regulatory information and lists, resulting in a lack of reliability and efficiency in determining transaction risk. This has created a need for improved business reliability and reduced transaction risk.

[0717] 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.

[0718] In this invention, the server includes: input means for a user to input the name, address, and transaction details of a business partner; data processing means for receiving the user's input data and standardizing and verifying it; inspection means for accessing regulatory information sources and lists of anti-social forces in each country and comparing them with the user's input data; evaluation means for evaluating the feasibility of a transaction based on the comparison results and generating the results; answer generation means for transmitting the evaluation results and related points of caution to the user's device; response means for accepting additional questions from the user and generating answers again using a generation AI; and auxiliary means for comparing the user's business partner's name and address with regulatory information sources and evaluating and generating the feasibility of a transaction and points of caution in real time, thereby enabling the reliability of a business partner to be evaluated quickly and accurately and making transaction decisions based on the results of the comparison with regulatory information.

[0719] A "user" is a person or company that uses the system to input information about a business partner and request a reliability evaluation.

[0720] "Commercial name" is the name of the company or organization with which you are conducting business.

[0721] "Location" refers to information that indicates the specific address or geographic location of a business partner.

[0722] "Transaction details" refers to information about the products or services that the user plans to trade and details of the transaction.

[0723] The "input means" is an interface for the user to input the name, address, and transaction details of the business partner.

[0724] "Data Processing Means" means means for standardizing and verifying the accuracy of data received from users.

[0725] "Standardization" is the process of converting input information into a unified format.

[0726] "Validation" is the process of ensuring that input data is accurate.

[0727] "Regulatory Information Source" is a database that collects information on the laws and regulations of each country.

[0728] The "List of Anti-Social Forces" is a list of organizations and individuals that engage in anti-social activities.

[0729] "Testing means" refers to means for checking user-entered data against regulatory information sources and lists of anti-social forces.

[0730] The "evaluation means" is a means for determining whether or not a transaction can be carried out based on the result of the comparison.

[0731] The "answer generation means" is a means for generating evaluation results and related points of attention and providing them to the user.

[0732] A "response means" is a means of accepting additional questions from users and generating answers using a generation AI.

[0733] The "auxiliary means" refers to a means of comparing the name and location of the user's commercial counterparty with regulatory information sources, and generating a real-time assessment of whether a transaction is possible and what precautions need to be taken.

[0734] "Generative AI" is an artificial intelligence model that generates appropriate answers to user questions.

[0735] This invention is a system that allows users to quickly and accurately evaluate the trustworthiness of their business partners, providing real-time evaluation of whether or not to do business with them based on regulatory information sources and lists of anti-social forces in each country. This system mainly consists of the following components:

[0736] Hardware Configuration

[0737] User device: A device such as a smartphone or PC on which the user enters business partner information and receives evaluation results.

[0738] Server: A high-performance computing device for data processing, matching, evaluation, and answer generation.

[0739] Software Configuration

[0740] Input means: An interface through which a user inputs the name, address, and transaction details of a business partner. For example, this would be an input form on a smartphone application.

[0741] Data processing means: A program to normalize the data received from users and check its format. Specifically, a web framework such as Python's Flask is used.

[0742] Verification method: A program that checks user-entered data against regulatory information sources and lists of anti-social forces. It accesses external regulatory databases using APIs.

[0743] Evaluation method: Logic for determining whether or not a transaction is possible based on the matching results. A decision is made based on various conditions and a result is generated.

[0744] Answer generation means: A program for generating answers that combine the evaluation results and related points of attention and sending them to the user.

[0745] Response method: A function to accept additional questions from the user and generate answers again using generative AI. Possible generative AI models include OpenAI's GPT-3.

[0746] Auxiliary tool: A program that checks regulatory information in real time based on the user's commercial partner's name and location, and generates a transaction approval / disapproval and warnings.

[0747] Processing Flow

[0748] The user's terminal provides an interface for inputting the name, address, and transaction details of the business partner. This input is sent to the server, where the data processing means normalizes and verifies it. Then, based on the collated data, the inspection means accesses external regulatory information sources and lists of anti-social forces for collation.

[0749] The evaluation means determines whether or not the transaction is possible based on the collation result and generates an evaluation result. Based on this result, the answer generation means transmits to the user's terminal whether or not the transaction is possible and any necessary precautions.

[0750] If the user enters additional questions, the server's response mechanism will utilize AI generation to generate appropriate answers and send them to the user's device. In addition, the assistance mechanism will perform real-time verification to support quick and accurate trading decisions.

[0751] Specific examples

[0752] For example, a user enters a "general company name" as the business destination, a "general address" as the location, and "purchase of goods" as the transaction details. The server receives the information, and after the data processing means correctly formats it, the inspection means checks it against a regulatory information database and a list of anti-social forces. The evaluation means then determines that "the general company name is OK, but the general address requires caution," and the answer generation means notifies the user of the result. If the user adds a more detailed question, the response means uses a generation AI to respond, "Confirmation is required as specific regulations apply to general areas."

[0753] Prompt Sentence Examples

[0754] "Based on user input, check the regulatory information for companies and addresses and evaluate whether or not to allow transactions. Input example: 'General company name', 'General address'"

[0755] In this way, the system quickly and accurately evaluates the reliability of trading partners, and helps users make effective trading decisions.

[0756] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0757] Step 1:

[0758] User enters business name, address, and transaction details

[0759] The user uses the interface of their device (such as a smartphone or PC) to enter the name, address, and transaction details of the commercial partner. Once the input is complete, they press the "Confirm" button and the data is sent to the server. The input data is entered directly into the text box.

[0760] Input: Name of business partner, address, transaction details

[0761] Output: Input data (commercial name, address, transaction details)

[0762] Step 2:

[0763] Normalizing and validating data received by the server

[0764] The server receives input data sent by the user. The received data is first normalized. For example, commas and spaces are standardized, and address formats are checked to ensure they are correct. Next, the data is validated to ensure there are no errors in the input. If improperly formatted data or missing required fields are detected, an error message is generated and sent back to the user.

[0765] Input: Input data (business partner name, address, transaction details)

[0766] Output: Normalized and validated data, or error messages

[0767] Step 3:

[0768] The server accesses regulatory information sources and lists of anti-social forces and performs cross-checking.

[0769] After normalization and validation are complete, the server accesses regulatory information sources and anti-social forces lists to verify the data. Specifically, it checks whether the customer's name is on a sanctions list or whether the customer's location is in a restricted area. This verification is performed in real time through API communication with external databases.

[0770] Input: Normalized and validated data

[0771] Output: Matching result (whether the transaction is possible or not, points to note)

[0772] Step 4:

[0773] The server evaluates whether the transaction is possible based on the matching results and generates a result.

[0774] The server evaluates whether the transaction is possible or not based on the matching results. The evaluation is classified as follows: No transaction (if the business destination is on the sanctions list), OK transaction (if all matching results are OK), OK but with cautions (if the location is in a sanctions-listed area but the business destination itself is OK). Based on this evaluation, a result including detailed cautions is generated.

[0775] Input: Matching result (transaction possibility, points to note)

[0776] Output: Evaluation result (transaction possibility, points to note)

[0777] Step 5:

[0778] The server notifies the user of the evaluation results and related precautions.

[0779] The server uses the response generation means to send an appropriate message to the user's device based on the generated evaluation results and points to note. The message includes whether the transaction is OK, NG, OK with points to note, and specific points to note.

[0780] Input: Evaluation result (transaction possibility, points to note)

[0781] Output: A message to be sent to the user

[0782] Step 6:

[0783] Handling follow-up questions from the user

[0784] If the user wants more detailed information, an interface is provided for entering additional questions. Once the user enters and submits the question, the server receives the question and uses a generative AI model (e.g., GPT-3) to generate an appropriate answer. The generated answer is then sent back to the user.

[0785] Input: Additional question text

[0786] Output: The answer from the generative AI model and its transmission

[0787] Through the above steps, this system quickly and accurately evaluates the reliability of trading partners and helps users make effective trading decisions.

[0788] 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.

[0789] The present invention is a system that quickly and accurately evaluates the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to consider, thereby helping users to proceed with transactions with peace of mind. Furthermore, by combining the system with an emotion engine that recognizes user emotions and responds appropriately based on those emotions, the user experience can be improved. Specific embodiments of the system of the present invention are described below.

[0790] Program Overview

[0791] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server for processing and collating this data, and an emotion engine for recognizing the user's emotions.

[0792] 1. User Input

[0793] Device:

[0794] The user enters the name, address, and transaction details into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[0795] 2. Receiving and Preprocessing Input Data

[0796] server:

[0797] Receives user input data sent from the terminal and normalizes and validates it. For example, it checks whether the address format is correct or whether the customer name contains inappropriate characters, and corrects any inappropriate parts.

[0798] 3. Emotional Recognition

[0799] server:

[0800] The emotion engine analyzes the user's input data (e.g., typing speed, number of input errors, etc.) to recognize the user's emotional state, for example, determining whether they are feeling anxious or stressed.

[0801] 4. Regulatory information collation

[0802] server:

[0803] Using the normalized input data, the regulatory information database and anti-social forces list are accessed to obtain the latest regulatory information.

[0804] 5. Matching

[0805] server:

[0806] The system compares the obtained regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0807] 6. Transaction Approval Determination

[0808] server:

[0809] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[0810] 7. Answer Generation

[0811] server:

[0812] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0813] 8. Submitting your response

[0814] server:

[0815] The generated response message is sent to the user's terminal.

[0816] 9. View Answers

[0817] Device:

[0818] The received response message will be displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[0819] 10. Answering questions

[0820] Terminals, Servers:

[0821] If a user wants more detailed information, they can enter additional questions. These questions are sent to the server, which uses a generative AI to generate an appropriate answer and sends it back to the device. For example, if a user enters the question, "I'd like to know more about areas subject to economic sanctions," the server will generate the answer, "The relevant areas are included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[0822] Specific examples

[0823] User Input and Emotion Recognition

[0824] user:

[0825] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "purchasing electronic components," and presses the "Confirm" button. At this time, the emotion engine recognizes that the user is feeling anxious based on the speed of input and the frequency of error messages.

[0826] Answer generation and message sending

[0827] server:

[0828] Based on the results of the comparison, the server determines that the transaction is OK, but there are some caveats, and generates a message stating, "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction." In addition, the emotion engine detects the user's anxiety and adjusts the tone of the message to be softer.

[0829] Device:

[0830] Display the generated message on the user's screen.

[0831] In this way, the system quickly and accurately compares various regulatory information based on user input to determine whether a transaction can be carried out, and furthermore, by appropriately recognizing and responding to user emotions using an emotion engine, it improves the user experience.

[0832] The processing flow will be explained below.

[0833] Step 1:

[0834] User:

[0835] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[0836] Step 2:

[0837] Device:

[0838] The terminal transmits the user's input data to the server.

[0839] Step 3:

[0840] server:

[0841] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[0842] Step 4:

[0843] server:

[0844] The server sends the normalized input data to the emotion engine.

[0845] Step 5:

[0846] server:

[0847] The emotion engine analyzes the user's input data and recognizes the user's emotional state based on the input speed, frequency of error messages, etc. For example, if a user makes many input errors in a short period of time, it can determine that the user is feeling anxious or stressed.

[0848] Step 6:

[0849] server:

[0850] The server uses the normalized input data to access the regulatory information database and the anti-social forces list to obtain the latest regulatory information.

[0851] Step 7:

[0852] server:

[0853] The system compares the acquired regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[0854] Step 8:

[0855] server:

[0856] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[0857] Step 9:

[0858] server:

[0859] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0860] Step 10:

[0861] server:

[0862] The generated reply message is sent to the user's terminal.

[0863] Step 11:

[0864] Device:

[0865] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[0866] Step 12:

[0867] User:

[0868] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[0869] Step 13:

[0870] Device:

[0871] The terminal sends the user's follow-up question to the server.

[0872] Step 14:

[0873] server:

[0874] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[0875] Step 15:

[0876] server:

[0877] The answer to the generated question is sent to the user's terminal.

[0878] Step 16:

[0879] Device:

[0880] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[0881] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[0882] Example 2

[0883] 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."

[0884] Conventional systems for evaluating the trustworthiness of business partners only evaluate basic information about business partners and do not take into account the user's emotional state, making it impossible to reduce user stress and anxiety. Furthermore, determining whether or not to transact based solely on the results of verification does not provide sufficient information on specific points to note or when additional confirmation is required. This does not adequately provide an environment in which users can proceed with transactions with peace of mind.

[0885] 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.

[0886] In this invention, the server includes: input means for a user to input the name, address, and transaction details of the business partner; data processing means for receiving the user's input data and normalizing and validating it; emotion recognition means for analyzing the user's emotions and recognizing their emotional state; comparison means for accessing regulatory information databases and anti-social forces lists in each country and comparing the user's input data with them; determination means for determining whether or not to allow a transaction based on the comparison results and generating the result; answer generation means for adjusting the determination result and related precautions based on the user's emotional state and transmitting them to the user's terminal; and question response means for receiving additional questions from the user and generating answers again using a generation AI. This enables appropriate responses that take the user's emotional state into consideration, allowing the user to proceed with the transaction with peace of mind.

[0887] "Input means" refers to a device or interface that allows a user to input the name, address, and transaction details of a business partner.

[0888] A "data processing means" is a system that has the functionality to receive user input data and normalize and validate that data.

[0889] An "emotion recognition means" is a system that has the function of analyzing a user's input behavior and data and identifying the user's emotional state.

[0890] The "matching means" is a system that has the function of matching the user's input data with each country's regulatory information database and anti-social forces list.

[0891] The "determination means" is a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[0892] The "answer generation means" is a system that has the function of adjusting the judgment results and related points of attention based on the user's emotional state and transmitting them to the user's terminal.

[0893] The "question response means" is a system that accepts additional questions from users, uses generation AI to generate appropriate answers, and provides them to the user again.

[0894] "Generative AI" is an artificial intelligence model that generates appropriate answers in natural language to users' questions.

[0895] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to note. It also improves the user experience by recognizing the user's emotions and responding appropriately based on those emotions. Specific embodiments of the present invention are described below.

[0896] System Overview

[0897] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server that processes this data and recognizes emotions, and a database that collates regulatory information.It also uses a generative AI model to generate appropriate answers to follow-up questions from users.

[0898] 1. User Input

[0899] Device:

[0900] The user enters the name, address, and transaction details of the customer into a web form on their device, for example, "XYZ Corporation," "456 Main Street, New York, USA," and "Sales of Electronics," and clicks the "Confirm" button. This input is then sent to the server.

[0901] 2. Data Reception and Preprocessing

[0902] server:

[0903] The server receives input data sent from the terminal. First, it normalizes the data and checks that the input format matches. For example, if the address format is incorrect or if an inappropriate character string is included in the customer name, the server can correct that part.

[0904] 3. Emotional Recognition

[0905] server:

[0906] The emotion engine analyzes the user's input data (e.g., input speed, number of input errors, etc.) and recognizes the user's emotional state. For example, if the input speed is slow and there are many input errors, it will recognize that the user is feeling anxious.

[0907] 4. Regulatory information collation

[0908] server:

[0909] The server uses the normalized input data to access regulatory information databases and anti-social forces lists to obtain the latest regulatory information, such as from the Office of Foreign Assets Control (OFAC) and Interpol databases.

[0910] 5. Matching and Judging

[0911] server:

[0912] The system compares the acquired regulatory information with the user's input data to check whether the business partner's name is included on a sanctions list or anti-social forces list. It also checks whether the address is in a specific restricted area. Based on the comparison results, the system determines whether the transaction is "NG," "OK," or "OK ​​but with caution."

[0913] 6. Answer Generation

[0914] server:

[0915] The server generates a response message for the user based on the result of the judgment and the user's emotional state. For example, the message might say, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction," and is written in a tone that takes the user's emotions into consideration.

[0916] 7. Submitting and Viewing Your Answers

[0917] server:

[0918] The generated response message is sent to the user's terminal.

[0919] Device:

[0920] The response message received by the terminal is displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[0921] 8. Answering questions

[0922] Terminals, Servers:

[0923] If the user wants more information, they can enter a follow-up question. The follow-up question is sent to the server, and a generative AI model (e.g., GPT-4) generates an appropriate answer and sends it back to the device. For example, if the prompt is "I'd like to know more about the area under economic sanctions," a detailed answer will be generated: "The area is subject to economic sanctions, and authorization is required for certain transactions."

[0924] In this way, the system quickly and accurately compares various regulatory information based on user input and determines whether a transaction can be carried out. It also uses an emotion engine to recognize user emotions and respond appropriately, enhancing the user's sense of security.

[0925] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0926] Step 1:

[0927] Input: The user enters the customer name, address, and transaction details.

[0928] What happens: A user enters information into a web form on their device, such as "XYZ Corporation," "456 Main Street, New York, USA," and "Electronics Sales," and clicks the "Confirm" button.

[0929] Output: User input data is sent from the device to the server.

[0930] Step 2:

[0931] Input: User input data received from the device.

[0932] Specific operation: The server receives the data sent from the terminal and normalizes and validates the data. For example, it checks whether there are any inappropriate characters in the address format or the customer name. If there are any inappropriate parts, it automatically corrects them.

[0933] Output: Normalized and validated data.

[0934] Step 3:

[0935] Input: Normalized and validated user input data.

[0936] Specific operation: The server's emotion engine analyzes the input speed of input data and the frequency of error messages to recognize the user's emotional state. For example, if the input speed is slower than usual and an error message appears three or more times, it will determine that the user is feeling "anxiety" or "stressed."

[0937] Output: User's emotional state (e.g., anxiety, stress).

[0938] Step 4:

[0939] Input: Normalized and validated user input data.

[0940] Specific operation: The server accesses regulatory information databases (e.g., OFAC lists, Interpol lists) and obtains the latest regulatory information.

[0941] Output: Latest regulatory information.

[0942] Step 5:

[0943] Input: Up-to-date regulatory information and normalized user input data.

[0944] Specific operation: The server compares the obtained regulatory information with the user's input data, for example, checking whether the customer name is on a sanctions list or anti-social forces list, or whether the address is in a specific restricted area.

[0945] Output: Verification result (e.g., no problem, transaction not accepted, caution required).

[0946] Step 6:

[0947] Input: Match result.

[0948] Specific operation: The server determines whether or not to allow a transaction based on the matching results. For example, if the customer name is included in the sanctions list, the transaction is denied. If all matching results are OK, the transaction is allowed. If the address is included in a sanctions area, the transaction is allowed, but with caution.

[0949] Output: Transaction approval / disapproval result.

[0950] Step 7:

[0951] Input: Transaction decision result and user's emotional state.

[0952] Specific operation: The server adjusts the judgment result and related points of caution based on the user's emotional state and generates a response message to the user. For example, if the transaction is OK but the address is in an area subject to economic sanctions, the server will create a message in a softer tone, sensing the user's anxiety, such as "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[0953] Output: The reply message.

[0954] Step 8:

[0955] Input: The answer message.

[0956] Specific operation: The server sends the generated response message to the user's terminal.

[0957] Output: The reply message is sent to the user's terminal.

[0958] Step 9:

[0959] Input: The answer message sent to the user's device.

[0960] Specific operation: The device displays the received response message on the user's screen.

[0961] Output: Message displayed to the user regarding whether the transaction is possible or not and important points to note.

[0962] Step 10:

[0963] Input: Any additional questions from the user.

[0964] How it works: If a user wants more information, they enter an additional question on their device and send it to the server. The server uses a generative AI model (e.g., GPT-4) to generate an appropriate answer and send it back to the device. For example, if a user asks, "I'd like to know more about areas subject to economic sanctions," the generative AI model will generate the answer, "The area in question is subject to economic sanctions, and authorization is required for certain transactions."

[0965] Output: The generated answers to the follow-up questions are sent to the user's device and displayed.

[0966] (Application example 2)

[0967] 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."

[0968] Conventional supplier evaluation systems determine whether to approve a transaction by checking against a regulatory information database, but they often leave users feeling uneasy about the evaluation because they lack appropriate responses that reflect the user's emotional state. Furthermore, the lack of consideration for emotional recognition can sometimes impair the user experience, which is an issue.

[0969] The identification processing 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: input means through which a user inputs the name, address, and transaction details of the business partner; data processing means that receives the user's input data and normalizes and validates it; comparison means that accesses regulatory information databases and anti-social forces lists in various countries and compares the user's input data with the data; determination means that determines whether the transaction is permitted based on the comparison results and generates the result; answer generation means that transmits the determination result and related precautions to the user's terminal; question response means that accepts additional questions from the user and generates answers using a new generation AI; emotion recognition means that recognizes the user's emotional state based on the input speed and number of errors; and tone-adjusted message generation means that generates messages with the tone adjusted based on the user's emotional state. This makes it possible to provide appropriate responses that take the user's emotional state into consideration and improve the reliability of transaction decisions.

[0970] "Input means" refers to the device or software that allows a user to input the name, address, and transaction details of the customer.

[0971] "Data Processing Means" refers to the systems and algorithms that receive, normalize, and validate user input data.

[0972] "Matching means" refers to a system that has the ability to access regulatory information databases and anti-social force lists in each country and match them with user-entered data.

[0973] "Determination means" refers to a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[0974] "Answer generation means" refers to a system that has the function of transmitting the judgment results and related points of caution to the user's terminal.

[0975] "Question response means" refers to a system that has the function of accepting additional questions from users and generating answers again using generation AI.

[0976] "Emotion recognition means" refers to systems or algorithms that recognize a user's emotional state based on input speed or frequency of error messages.

[0977] "Tone-adjusted message generator" refers to a system or algorithm for generating tone-adjusted messages based on emotional state.

[0978] The present invention provides a system that enables a user to quickly and accurately evaluate the reliability of a trading partner and proceed with a transaction with peace of mind. Specific embodiments of the system of the present invention will be described below.

[0979] System Configuration

[0980] This system mainly consists of the following elements:

[0981] 1. Device:

[0982] The user is provided with input means for inputting the name, address, and transaction details of the business partner.

[0983] Specific devices that can be used include smartphones, computers, tablets, etc.

[0984] 2. Server:

[0985] A data processing means is provided for receiving user input data and for normalizing and validating the data.

[0986] It is equipped with a means of comparison that accesses regulatory information databases and anti-social force lists in each country and compares them with user-entered data.

[0987] The system includes a determination means for determining whether or not a transaction is possible based on the result of the verification and generating the result.

[0988] The system is provided with an answer generation means for transmitting the judgment result and related points of caution to the user's terminal.

[0989] It is equipped with a question response function that accepts additional questions from users and generates answers using the generation AI again.

[0990] The system is equipped with an emotion recognition means that recognizes the user's emotional state based on input speed and frequency of error messages.

[0991] The device includes a tone-adjusted message generating means for generating a message with a tone adjusted based on the emotional state.

[0992] 3. Software and Services Used:

[0993] Use Python as the programming language.

[0994] Use requests, a Python library for handling HTTP requests.

[0995] Use an emotion recognition engine API (e.g. emotionrecognition API) for emotion recognition.

[0996] Use regulatory information database APIs (e.g., regulatoryinfo API) to query regulatory information.

[0997] Processing flow

[0998] The user uses the terminal to enter the name of the business partner, address, and transaction details, and then clicks the "Confirm" button. An example of input is as follows:

[0999] Account Name: XYZ Corporation

[1000] Address: 456 Market Street, Tokyo, Japan

[1001] Transaction: Purchase of electronic components

[1002] The terminal sends the user's input data to the server, which first normalizes and validates the data, then accesses a regulatory information database and a list of anti-social forces to check and determine whether the transaction should proceed.

[1003] Additionally, the app uses an emotion recognition API to recognize a user's emotional state by analyzing their typing speed and the frequency of error messages. For example, if it determines that the user is feeling anxious, it will generate a message with a tone tailored to that emotional state.

[1004] The judgment result and emotion recognition result are integrated to generate a final answer message. This message is sent to the user's device and displayed to the user as an example:

[1005] The transaction is OK, but your address is in a sanctioned area. You seem to be concerned, so we need to do some additional verification.

[1006] If the user wants more information, they can ask a follow-up question, which is sent to the server, which uses the generative AI model to generate an appropriate answer and sends it back to the user.

[1007] The above is a specific example of the embodiment of the present invention. This system allows users to judge the reliability of their business partners with high accuracy, and provides a sense of security by receiving responses that correspond to their emotions.

[1008] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1009] Step 1:

[1010] The user enters the customer's name, address, and transaction details into the terminal.

[1011] The user enters the client name, address, and transaction details into the input form and clicks the "Confirm" button. An example of input is as follows:

[1012] Account Name: XYZ Corporation

[1013] Address: 456 Market Street, Tokyo, Japan

[1014] Transaction: Purchase of electronic components

[1015] The input data is sent from the terminal to the server.

[1016] Step 2:

[1017] The server receives the user input data and performs normalization and validation.

[1018] The server receives user-entered data sent from the terminal. The normalization process checks for address format consistency and appropriate client name strings to improve data consistency. The validation process checks whether all required fields are filled in and the data is accurate.

[1019] Input: User input data (client name, address, transaction details)

[1020] Output: Normalized and validated data

[1021] Step 3:

[1022] The server performs emotion recognition based on the input data.

[1023] The emotion recognition engine analyzes the user's emotional state based on data such as the user's input speed and the frequency of input error messages, and determines whether the user is feeling anxious or stressed, for example, based on the results of this analysis.

[1024] Input: Corrected user input data, input speed, frequency of error messages

[1025] Output: User's emotional state (e.g., anxious, calm, etc.)

[1026] Step 4:

[1027] The server accesses the regulatory information database and anti-social forces list to perform the check.

[1028] Using the normalized input data, the server accesses each country's regulatory information database and anti-social forces list and checks it against the user's input data. This check process verifies whether the customer name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1029] Input: Normalized user input data

[1030] Output: Verification result (e.g., transaction OK, transaction NG, cautions)

[1031] Step 5:

[1032] The server determines whether the transaction is possible and generates a result.

[1033] The server determines whether or not to allow the transaction based on the matching results. For example, if the client's name is on the sanctions list, the server determines that the transaction is "NG," but if all matching results are satisfactory, the server determines that the transaction is "OK." If the address is in a sanctions-targeted area, the server determines that the transaction is "OK, but with caution."

[1034] Input: Matching result

[1035] Output: Transaction availability determination result (e.g., transaction OK, transaction NG, cautions apply)

[1036] Step 6:

[1037] The server generates a response message based on the judgment result and emotion recognition result.

[1038] The server combines the transaction approval / disapproval judgment result with the emotion recognition result to generate a response message for the user. For example, if the transaction is OK but the user is feeling uneasy, the tone of the message is adjusted to generate a message such as, "The transaction is OK, but you seem to be feeling uneasy, so we will conduct further confirmation."

[1039] Input: Transaction approval / disapproval decision result, user's emotional state

[1040] Output: Tone-adjusted answer message

[1041] Step 7:

[1042] The server sends a response message to the terminal.

[1043] The generated response message is sent from the server to the user's terminal, where the judgment result and related points to note are displayed.

[1044] Input: Reply message

[1045] Output: Message displayed on the user's terminal

[1046] Step 8:

[1047] The user enters a follow-up question, and the server again uses the generation AI to generate an answer.

[1048] If the user enters a follow-up question, the question is sent to the server, which uses a generative AI model to generate an appropriate answer and sends it back to the user's device. For example, if the user enters, "I'd like to know more about sanctioned areas," the server might generate a response such as, "The area is on the sanctions list, and authorization is required for certain transactions."

[1049] Input: User's additional question

[1050] Output: Answer message from the generating AI

[1051] This series of processes allows users to quickly and accurately judge the reliability of their trading partners, allowing them to proceed with transactions with peace of mind. In addition, receiving responses that reflect their emotions improves the user experience.

[1052] 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.

[1053] 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.

[1054] 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.

[1055] [Third embodiment]

[1056] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1057] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1058] 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).

[1059] 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.

[1060] 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.

[1061] 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).

[1062] 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.

[1063] 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.

[1064] 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.

[1065] 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.

[1066] 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.

[1067] 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."

[1068] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, and can compare various regulatory information based on user input, and provide a decision on whether or not to proceed with a transaction and important points to note. Specific embodiments of the system of the present invention are described below.

[1069] Program Overview

[1070] This system consists of a terminal where users can input the name, address, and transaction details of their business partners, and a server that processes and collates this data.

[1071] 1. User Input

[1072] Device:

[1073] The user enters the name, address, and transaction details of the business partner into the form on the terminal and clicks the "Confirm" button. By doing so, the user provides the system with information about the company or organization with which the transaction is being made.

[1074] 2. Receiving and Preprocessing Input Data

[1075] server:

[1076] Receives user input data sent from the terminal, then normalizes and validates the received data, for example, checking that the address format is correct and that the customer name does not contain inappropriate characters.

[1077] 3. Regulatory information collation

[1078] server:

[1079] The system accesses regulatory information databases and lists of anti-social forces and compares them with the data entered by the user, specifically checking whether the name of the business partner is on a sanctions list or whether the address is in a restricted area.

[1080] 4. Transaction Approval Determination

[1081] server:

[1082] Based on the result of the check, a decision is made as to whether the transaction can be carried out. This decision is classified as follows:

[1083] Transactions prohibited: If the business partner is included in the sanctions list or anti-social forces list

[1084] Transaction OK: If all matching results are OK

[1085] OK, but be careful: If your address is in a sanctioned area, or if you need to be careful with the transaction

[1086] 5. Answer Generation

[1087] server:

[1088] Based on the results of the transaction approval / disapproval judgment, a response is generated for the user. For example, a message such as "Transaction not permitted," "Transaction OK," or "Transaction OK, but caution required" is generated, and further detailed warnings are also added.

[1089] 6. Submit your response

[1090] server:

[1091] The generated answer is sent to the user's device, where the user can check whether the transaction is possible and any important points to note.

[1092] 7. Answering questions

[1093] Terminals, Servers:

[1094] The device provides a text box for the user to enter additional questions, allowing the user to request more detailed information. The server accepts the additional questions, uses a generative AI to generate appropriate answers, and sends them back to the device.

[1095] Specific examples

[1096] User Input

[1097] user:

[1098] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button.

[1099] Receiving and Preprocessing Input Data

[1100] server:

[1101] Check the format of the data received, for example, to make sure "123 Main Street, Tokyo, Japan" is a valid address format.

[1102] Regulatory information verification

[1103] server:

[1104] It checks against regulatory information databases to see, for example, whether "ABC Corporation" is on a sanctions list or whether "123 Main Street, Tokyo, Japan" is in a restricted area.

[1105] Determination of whether or not a transaction is possible

[1106] server:

[1107] Based on the results of the comparison, it is determined that "ABC Corporation is OK, but the address is in a sanctioned area, so transactions are OK but caution is required."

[1108] Generate and submit answers

[1109] server:

[1110] Generate and send a message saying, "Transaction OK, but additional verification is required for the transaction as the address is in a sanctioned area."

[1111] Device:

[1112] Display a response message to the user.

[1113] Answering questions

[1114] user:

[1115] The user types in a question such as, "I'd like to know more about areas subject to economic sanctions."

[1116] server:

[1117] The system receives the additional question and uses a generation AI to generate a response that reads, "The relevant region is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." and sends this to the device.

[1118] Device:

[1119] The generated AI's answer is displayed on the user's screen.

[1120] In this way, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides a response, thereby providing users with an efficient means of verifying the trustworthiness of their trading partners.

[1121] The processing flow will be explained below.

[1122] Step 1:

[1123] User:

[1124] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[1125] Step 2:

[1126] Device:

[1127] The terminal transmits the user's input data to the server.

[1128] Step 3:

[1129] server:

[1130] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[1131] Step 4:

[1132] server:

[1133] The server uses the normalized input data to access the regulatory information database and the anti-social forces list, and obtains the latest regulatory information from the database.

[1134] Step 5:

[1135] server:

[1136] The server compares the obtained regulatory information with the user's input data, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1137] Step 6:

[1138] server:

[1139] The server determines whether or not to allow the transaction based on the results of the check. For example, if the customer's name is on the sanctions list, the transaction is denied; if all checks are OK, the transaction is allowed; and if the address is in a sanctions area, the transaction is allowed, but with caution.

[1140] Step 7:

[1141] server:

[1142] The server generates a response message for the user based on the transaction approval / disapproval decision and any related points of caution, such as "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1143] Step 8:

[1144] server:

[1145] The generated reply message is sent to the user's terminal.

[1146] Step 9:

[1147] Device:

[1148] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[1149] Step 10:

[1150] User:

[1151] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[1152] Step 11:

[1153] Device:

[1154] The terminal sends the user's follow-up question to the server.

[1155] Step 12:

[1156] server:

[1157] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[1158] Step 13:

[1159] server:

[1160] The answer to the generated question is sent to the user's terminal.

[1161] Step 14:

[1162] Device:

[1163] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[1164] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[1165] Example 1

[1166] 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."

[1167] The objective of this invention is to quickly and accurately evaluate the trustworthiness of a trading partner. Conventional methods have the problem of being inefficient, taking time to verify regulatory information and determine whether or not to allow a transaction. In addition, it is difficult to respond appropriately to follow-up questions from users, which can result in a decline in the trustworthiness of the transaction.

[1168] 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.

[1169] In this invention, the server includes: input means for a user to input the business name, location, and transaction details; data processing means for receiving the user's input data and standardizing the format and confirming its validity; data comparison means for accessing regulatory information databases and illegal force lists in multiple countries and comparing the data with the user's input data; transaction determination means for determining whether or not the transaction is possible based on the comparison results and generating the result; answer generation means for transmitting the determination result and related points to the user's terminal; and question response means for receiving follow-up questions from the user and generating answers using a generative AI model. This makes it possible to quickly and accurately evaluate the reliability of a business partner and appropriately respond to follow-up questions from the user.

[1170] "User" refers to a user who uses the system to evaluate the trustworthiness of business partners.

[1171] "Business name" is the name of the business partner that the user inputs as the target of evaluation.

[1172] "Location" is the physical address information of the business partner entered by the user.

[1173] "Transaction details" refers to information entered by the user regarding the specific details and nature of the transaction with the business partner.

[1174] "Input means" refers to an interface that allows a user to input the name, address, and transaction details of a business partner into the system.

[1175] The "data processing means" is a part that has the function of standardizing the format and validating the data received from the user.

[1176] "Format unification" is a process for unifying the format of received data.

[1177] "Validation" is a verification process to ensure that received data is accurate.

[1178] The "data comparison means" is a part that has the function of comparing the data entered by the user with the regulatory information database and the list of illegal forces.

[1179] The "Regulatory Information Database" is a database containing information on sanctioned areas and restricted areas of each country.

[1180] The "List of Illegal Forces" is a list of information on anti-social forces and organizations subject to sanctions.

[1181] The "transaction determination means" is a part having a function for determining whether or not a transaction is permitted based on the result of the verification and generating a determination result.

[1182] The "answer generation means" is a part that has a function of generating a message to notify the user of the transaction judgment result and related points to note.

[1183] The "question response means" is the part that has the function of accepting additional questions from users and generating answers using a generative AI model.

[1184] A "generative AI model" is a model that uses AI to generate appropriate answers to questions in natural language.

[1185] This invention is a system for evaluating the reliability of trading partners, collating various regulatory information based on the business name, location, and transaction details entered by the user, and providing the propriety of the transaction and important points to note. This system handles user input, receives and preprocesses data, collates regulatory information, determines whether the transaction is permitted, generates and transmits answers, and responds to follow-up questions.

[1186] System Configuration

[1187] 1. Input Method

[1188] Users use their own devices (PC, smartphone, tablet, etc.) to enter the business name, address, and transaction details into a dedicated form, thereby providing the system with information about the company or organization with which the user is conducting business.

[1189] 2. Data processing means

[1190] The server receives the user's input data. The received data undergoes formatting and validation checks. For example, it standardizes the address format and removes inappropriate characters. It also checks whether the input data is in the correct format.

[1191] 3. Data verification methods

[1192] The server accesses databases of regulatory information from multiple countries (e.g., OFAC sanctions lists) and illegal power lists and checks the data entered by the user to see if the entity name is on a sanctions list or if its location is in a restricted area.

[1193] 4. Transaction Judgment Method

[1194] The server determines whether to allow the transaction based on the verification result. This determination is categorized as follows:

[1195] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[1196] Transaction OK: If there are no problems with the matching results.

[1197] OK, but with caveats: If you need to be careful with the transaction, for example, if your location is in a sanctioned area.

[1198] 5. Answer generation means

[1199] The server generates a response to the user based on the transaction judgment result, such as a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1200] 6. Method of sending responses

[1201] The server then sends the generated response to the user's device, where the user can check whether the transaction is possible and any important points to note.

[1202] 7. How to respond to questions

[1203] Users can use a text box to enter additional questions. The server accepts the user's additional questions, generates an appropriate answer using a generative AI model (e.g., ChatGPT), and sends it back to the user's device. For example, it might generate an answer like, "The region in question is included in Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to official guidelines for detailed regulations."

[1204] Specific examples

[1205] Let's say a user enters the information "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button. The server receives this information and verifies that the address format is correct. It then checks against a regulatory database to see if "Company A" is on a sanctions list and if "123 Main Street, Tokyo, Japan" is in a restricted area.

[1206] Based on the matching results, the server determines that "the transaction is OK, but caution is required, as the address is in a sanctioned area," and generates and sends a message to the user stating, "The transaction is OK, but additional confirmation is required as the address is in a sanctioned area."

[1207] When the user enters an additional question such as "I would like to know more about areas subject to economic sanctions," the server uses a generative AI model to generate an answer: "The area in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." This answer is then sent to the user's device.

[1208] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1209] Step 1: User Input

[1210] User: The user uses input means to enter the business name, address, and transaction details into the dedicated form on their device. For example, the user enters "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and clicks the "Confirm" button. In this step, the entered data is sent to the system.

[1211] Step 2: Receiving and Preprocessing Data

[1212] Server: The server receives input data sent from the terminal. The received data is checked for format consistency and validity. Specifically, it checks whether the address format is correct and whether the business name contains inappropriate characters. For example, it checks whether "123 Main Street, Tokyo, Japan" is a valid address format. The server stores the input data (business name, address, transaction details) in an organized format in an internal database.

[1213] Step 3: Regulatory information verification

[1214] Server: The server compares the data stored in the internal database with the regulatory information database. Specifically, it checks whether the business name is on a sanctions list or whether its location is in a restricted area. In this process, it accesses regulatory information databases from multiple countries (e.g., OFAC lists) and illegal force lists. For example, it checks to see if "Company A" is on a sanctions list. It then saves the comparison results in the internal database.

[1215] Step 4: Determine whether to proceed with the transaction

[1216] Server: Based on the verification result, the server determines whether the transaction is allowed or not. The criteria are as follows:

[1217] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[1218] Transaction OK: If there are no problems with the matching results.

[1219] OK, but with caveats: If the location is in a sanctioned area, you may need to be careful with the transaction.

[1220] For example, it may determine that "Company A is OK, but its location is in a sanctioned area, so transactions are OK but caution is required." It then generates a message to inform the user of the determination result.

[1221] Step 5: Generate an answer

[1222] Server: The server generates a response message for the user based on the transaction judgment result. For example, it generates a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction." The generated message is then stored in an internal database.

[1223] Step 6: Submit your response

[1224] Server: The server generates a response message and sends it to the user's device, where it is displayed.

[1225] On the device: The user sees a message on their device screen saying, "Transaction OK, but because you are located in a sanctioned area, additional verification is required to complete the transaction."

[1226] Step 7: Answer questions

[1227] User: The user uses a text box on the device to enter a follow-up question, for example, "I'd like to know more about sanctioned areas."

[1228] Server: The server receives the user's additional question and generates an appropriate answer using the generative AI model. For example, it generates a message such as, "The region in question is included in the Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to the official guidelines for detailed regulations." The generated answer message is then sent to the user's device.

[1229] Terminal: The user sees the AI's response message on the terminal screen, such as, "The region is included in the Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to the official guidelines for detailed regulations."

[1230] Through these steps, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides an answer. It can also respond to additional questions from users, improving the reliability of transactions.

[1231] (Application example 1)

[1232] 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."

[1233] In commercial transactions, it is extremely important to quickly and accurately assess the trustworthiness and regulatory compliance of trading partners. However, traditional methods rely heavily on manual verification, which is time-consuming and labor-intensive and prone to errors. Furthermore, it is difficult to timely collate multiple regulatory information and lists, resulting in a lack of reliability and efficiency in determining transaction risk. This has created a need for improved business reliability and reduced transaction risk.

[1234] 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.

[1235] In this invention, the server includes: input means for a user to input the name, address, and transaction details of a business partner; data processing means for receiving the user's input data and standardizing and verifying it; inspection means for accessing regulatory information sources and lists of anti-social forces in each country and comparing them with the user's input data; evaluation means for evaluating the feasibility of a transaction based on the comparison results and generating the results; answer generation means for transmitting the evaluation results and related points of caution to the user's device; response means for accepting additional questions from the user and generating answers again using a generation AI; and auxiliary means for comparing the user's business partner's name and address with regulatory information sources and evaluating and generating the feasibility of a transaction and points of caution in real time, thereby enabling the reliability of a business partner to be evaluated quickly and accurately and making transaction decisions based on the results of the comparison with regulatory information.

[1236] A "user" is a person or company that uses the system to input information about a business partner and request a reliability evaluation.

[1237] "Commercial name" is the name of the company or organization with which you are conducting business.

[1238] "Location" refers to information that indicates the specific address or geographic location of a business partner.

[1239] "Transaction details" refers to information about the products or services that the user plans to trade and details of the transaction.

[1240] The "input means" is an interface for the user to input the name, address, and transaction details of the business partner.

[1241] "Data Processing Means" means means for standardizing and verifying the accuracy of data received from users.

[1242] "Standardization" is the process of converting input information into a unified format.

[1243] "Validation" is the process of ensuring that input data is accurate.

[1244] "Regulatory Information Source" is a database that collects information on the laws and regulations of each country.

[1245] The "List of Anti-Social Forces" is a list of organizations and individuals that engage in anti-social activities.

[1246] "Testing means" refers to means for checking user-entered data against regulatory information sources and lists of anti-social forces.

[1247] The "evaluation means" is a means for determining whether or not a transaction can be carried out based on the result of the comparison.

[1248] The "answer generation means" is a means for generating evaluation results and related points of attention and providing them to the user.

[1249] A "response means" is a means of accepting additional questions from users and generating answers using a generation AI.

[1250] The "auxiliary means" refers to a means of comparing the name and location of the user's commercial counterparty with regulatory information sources, and generating a real-time assessment of whether a transaction is possible and what precautions need to be taken.

[1251] "Generative AI" is an artificial intelligence model that generates appropriate answers to user questions.

[1252] This invention is a system that allows users to quickly and accurately evaluate the trustworthiness of their business partners, providing real-time evaluation of whether or not to do business with them based on regulatory information sources and lists of anti-social forces in each country. This system mainly consists of the following components:

[1253] Hardware Configuration

[1254] User device: A device such as a smartphone or PC on which the user enters business partner information and receives evaluation results.

[1255] Server: A high-performance computing device for data processing, matching, evaluation, and answer generation.

[1256] Software Configuration

[1257] Input means: An interface through which a user inputs the name, address, and transaction details of a business partner. For example, this would be an input form on a smartphone application.

[1258] Data processing means: A program to normalize the data received from users and check its format. Specifically, a web framework such as Python's Flask is used.

[1259] Verification method: A program that checks user-entered data against regulatory information sources and lists of anti-social forces. It accesses external regulatory databases using APIs.

[1260] Evaluation method: Logic for determining whether or not a transaction is possible based on the matching results. A decision is made based on various conditions and a result is generated.

[1261] Answer generation means: A program for generating answers that combine the evaluation results and related points of attention and sending them to the user.

[1262] Response method: A function to accept additional questions from the user and generate answers again using generative AI. Possible generative AI models include OpenAI's GPT-3.

[1263] Auxiliary tool: A program that checks regulatory information in real time based on the user's commercial partner's name and location, and generates a transaction approval / disapproval and warnings.

[1264] Processing Flow

[1265] The user's terminal provides an interface for inputting the name, address, and transaction details of the business partner. This input is sent to the server, where the data processing means normalizes and verifies it. Then, based on the collated data, the inspection means accesses external regulatory information sources and lists of anti-social forces for collation.

[1266] The evaluation means determines whether or not the transaction is possible based on the collation result and generates an evaluation result. Based on this result, the answer generation means transmits to the user's terminal whether or not the transaction is possible and any necessary precautions.

[1267] If the user enters additional questions, the server's response mechanism will utilize AI generation to generate appropriate answers and send them to the user's device. In addition, the assistance mechanism will perform real-time verification to support quick and accurate trading decisions.

[1268] Specific examples

[1269] For example, a user enters a "general company name" as the business destination, a "general address" as the location, and "purchase of goods" as the transaction details. The server receives the information, and after the data processing means correctly formats it, the inspection means checks it against a regulatory information database and a list of anti-social forces. The evaluation means then determines that "the general company name is OK, but the general address requires caution," and the answer generation means notifies the user of the result. If the user adds a more detailed question, the response means uses a generation AI to respond, "Confirmation is required as specific regulations apply to general areas."

[1270] Prompt Sentence Examples

[1271] "Based on user input, check the regulatory information for companies and addresses and evaluate whether or not to allow transactions. Input example: 'General company name', 'General address'"

[1272] In this way, the system quickly and accurately evaluates the reliability of trading partners, and helps users make effective trading decisions.

[1273] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1274] Step 1:

[1275] User enters business name, address, and transaction details

[1276] The user uses the interface of their device (such as a smartphone or PC) to enter the name, address, and transaction details of the commercial partner. Once the input is complete, they press the "Confirm" button and the data is sent to the server. The input data is entered directly into the text box.

[1277] Input: Name of business partner, address, transaction details

[1278] Output: Input data (commercial name, address, transaction details)

[1279] Step 2:

[1280] Normalizing and validating data received by the server

[1281] The server receives input data sent by the user. The received data is first normalized. For example, commas and spaces are standardized, and address formats are checked to ensure they are correct. Next, the data is validated to ensure there are no errors in the input. If improperly formatted data or missing required fields are detected, an error message is generated and sent back to the user.

[1282] Input: Input data (business partner name, address, transaction details)

[1283] Output: Normalized and validated data, or error messages

[1284] Step 3:

[1285] The server accesses regulatory information sources and lists of anti-social forces and performs cross-checking.

[1286] After normalization and validation are complete, the server accesses regulatory information sources and anti-social forces lists to verify the data. Specifically, it checks whether the customer's name is on a sanctions list or whether the customer's location is in a restricted area. This verification is performed in real time through API communication with external databases.

[1287] Input: Normalized and validated data

[1288] Output: Matching result (whether the transaction is possible or not, points to note)

[1289] Step 4:

[1290] The server evaluates whether the transaction is possible based on the matching results and generates a result.

[1291] The server evaluates whether the transaction is possible or not based on the matching results. The evaluation is classified as follows: No transaction (if the business destination is on the sanctions list), OK transaction (if all matching results are OK), OK but with cautions (if the location is in a sanctions-listed area but the business destination itself is OK). Based on this evaluation, a result including detailed cautions is generated.

[1292] Input: Matching result (transaction possibility, points to note)

[1293] Output: Evaluation result (transaction possibility, points to note)

[1294] Step 5:

[1295] The server notifies the user of the evaluation results and related precautions.

[1296] The server uses the response generation means to send an appropriate message to the user's device based on the generated evaluation results and points to note. The message includes whether the transaction is OK, NG, OK with points to note, and specific points to note.

[1297] Input: Evaluation result (transaction possibility, points to note)

[1298] Output: A message to be sent to the user

[1299] Step 6:

[1300] Handling follow-up questions from the user

[1301] If the user wants more detailed information, an interface is provided for entering additional questions. Once the user enters and submits the question, the server receives the question and uses a generative AI model (e.g., GPT-3) to generate an appropriate answer. The generated answer is then sent back to the user.

[1302] Input: Additional question text

[1303] Output: The answer from the generative AI model and its transmission

[1304] Through the above steps, this system quickly and accurately evaluates the reliability of trading partners and helps users make effective trading decisions.

[1305] 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.

[1306] The present invention is a system that quickly and accurately evaluates the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to consider, thereby helping users to proceed with transactions with peace of mind. Furthermore, by combining the system with an emotion engine that recognizes user emotions and responds appropriately based on those emotions, the user experience can be improved. Specific embodiments of the system of the present invention are described below.

[1307] Program Overview

[1308] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server for processing and collating this data, and an emotion engine for recognizing the user's emotions.

[1309] 1. User Input

[1310] Device:

[1311] The user enters the name, address, and transaction details into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[1312] 2. Receiving and Preprocessing Input Data

[1313] server:

[1314] Receives user input data sent from the terminal and normalizes and validates it. For example, it checks whether the address format is correct or whether the customer name contains inappropriate characters, and corrects any inappropriate parts.

[1315] 3. Emotional Recognition

[1316] server:

[1317] The emotion engine analyzes the user's input data (e.g., typing speed, number of input errors, etc.) to recognize the user's emotional state, for example, determining whether they are feeling anxious or stressed.

[1318] 4. Regulatory information collation

[1319] server:

[1320] Using the normalized input data, the regulatory information database and anti-social forces list are accessed to obtain the latest regulatory information.

[1321] 5. Matching

[1322] server:

[1323] The system compares the obtained regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1324] 6. Transaction Approval Determination

[1325] server:

[1326] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[1327] 7. Answer Generation

[1328] server:

[1329] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1330] 8. Submitting your response

[1331] server:

[1332] The generated response message is sent to the user's terminal.

[1333] 9. View Answers

[1334] Device:

[1335] The received response message will be displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[1336] 10. Answering questions

[1337] Terminals, Servers:

[1338] If a user wants more detailed information, they can enter additional questions. These questions are sent to the server, which uses a generative AI to generate an appropriate answer and sends it back to the device. For example, if a user enters the question, "I'd like to know more about areas subject to economic sanctions," the server will generate the answer, "The relevant areas are included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[1339] Specific examples

[1340] User Input and Emotion Recognition

[1341] user:

[1342] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "purchasing electronic components," and presses the "Confirm" button. At this time, the emotion engine recognizes that the user is feeling anxious based on the speed of input and the frequency of error messages.

[1343] Answer generation and message sending

[1344] server:

[1345] Based on the results of the comparison, the server determines that the transaction is OK, but there are some caveats, and generates a message stating, "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction." In addition, the emotion engine detects the user's anxiety and adjusts the tone of the message to be softer.

[1346] Device:

[1347] Display the generated message on the user's screen.

[1348] In this way, the system quickly and accurately compares various regulatory information based on user input to determine whether a transaction can be carried out, and furthermore, by appropriately recognizing and responding to user emotions using an emotion engine, it improves the user experience.

[1349] The processing flow will be explained below.

[1350] Step 1:

[1351] User:

[1352] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[1353] Step 2:

[1354] Device:

[1355] The terminal transmits the user's input data to the server.

[1356] Step 3:

[1357] server:

[1358] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[1359] Step 4:

[1360] server:

[1361] The server sends the normalized input data to the emotion engine.

[1362] Step 5:

[1363] server:

[1364] The emotion engine analyzes the user's input data and recognizes the user's emotional state based on the input speed, frequency of error messages, etc. For example, if a user makes many input errors in a short period of time, it can determine that the user is feeling anxious or stressed.

[1365] Step 6:

[1366] server:

[1367] The server uses the normalized input data to access the regulatory information database and the anti-social forces list to obtain the latest regulatory information.

[1368] Step 7:

[1369] server:

[1370] The system compares the acquired regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1371] Step 8:

[1372] server:

[1373] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[1374] Step 9:

[1375] server:

[1376] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1377] Step 10:

[1378] server:

[1379] The generated reply message is sent to the user's terminal.

[1380] Step 11:

[1381] Device:

[1382] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[1383] Step 12:

[1384] User:

[1385] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[1386] Step 13:

[1387] Device:

[1388] The terminal sends the user's follow-up question to the server.

[1389] Step 14:

[1390] server:

[1391] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[1392] Step 15:

[1393] server:

[1394] The answer to the generated question is sent to the user's terminal.

[1395] Step 16:

[1396] Device:

[1397] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[1398] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[1399] Example 2

[1400] 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."

[1401] Conventional systems for evaluating the trustworthiness of business partners only evaluate basic information about business partners and do not take into account the user's emotional state, making it impossible to reduce user stress and anxiety. Furthermore, determining whether or not to transact based solely on the results of verification does not provide sufficient information on specific points to note or when additional confirmation is required. This does not adequately provide an environment in which users can proceed with transactions with peace of mind.

[1402] 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.

[1403] In this invention, the server includes: input means for a user to input the name, address, and transaction details of the business partner; data processing means for receiving the user's input data and normalizing and validating it; emotion recognition means for analyzing the user's emotions and recognizing their emotional state; comparison means for accessing regulatory information databases and anti-social forces lists in each country and comparing the user's input data with them; determination means for determining whether or not to allow a transaction based on the comparison results and generating the result; answer generation means for adjusting the determination result and related precautions based on the user's emotional state and transmitting them to the user's terminal; and question response means for receiving additional questions from the user and generating answers again using a generation AI. This enables appropriate responses that take the user's emotional state into consideration, allowing the user to proceed with the transaction with peace of mind.

[1404] "Input means" refers to a device or interface that allows a user to input the name, address, and transaction details of a business partner.

[1405] A "data processing means" is a system that has the functionality to receive user input data and normalize and validate that data.

[1406] An "emotion recognition means" is a system that has the function of analyzing a user's input behavior and data and identifying the user's emotional state.

[1407] The "matching means" is a system that has the function of matching the user's input data with each country's regulatory information database and anti-social forces list.

[1408] The "determination means" is a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[1409] The "answer generation means" is a system that has the function of adjusting the judgment results and related points of attention based on the user's emotional state and transmitting them to the user's terminal.

[1410] The "question response means" is a system that accepts additional questions from users, uses generation AI to generate appropriate answers, and provides them to the user again.

[1411] "Generative AI" is an artificial intelligence model that generates appropriate answers in natural language to users' questions.

[1412] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to note. It also improves the user experience by recognizing the user's emotions and responding appropriately based on those emotions. Specific embodiments of the present invention are described below.

[1413] System Overview

[1414] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server that processes this data and recognizes emotions, and a database that collates regulatory information.It also uses a generative AI model to generate appropriate answers to follow-up questions from users.

[1415] 1. User Input

[1416] Device:

[1417] The user enters the name, address, and transaction details of the customer into a web form on their device, for example, "XYZ Corporation," "456 Main Street, New York, USA," and "Sales of Electronics," and clicks the "Confirm" button. This input is then sent to the server.

[1418] 2. Data Reception and Preprocessing

[1419] server:

[1420] The server receives input data sent from the terminal. First, it normalizes the data and checks that the input format matches. For example, if the address format is incorrect or if an inappropriate character string is included in the customer name, the server can correct that part.

[1421] 3. Emotional Recognition

[1422] server:

[1423] The emotion engine analyzes the user's input data (e.g., input speed, number of input errors, etc.) and recognizes the user's emotional state. For example, if the input speed is slow and there are many input errors, it will recognize that the user is feeling anxious.

[1424] 4. Regulatory information collation

[1425] server:

[1426] The server uses the normalized input data to access regulatory information databases and anti-social forces lists to obtain the latest regulatory information, such as from the Office of Foreign Assets Control (OFAC) and Interpol databases.

[1427] 5. Matching and Judging

[1428] server:

[1429] The system compares the acquired regulatory information with the user's input data to check whether the business partner's name is included on a sanctions list or anti-social forces list. It also checks whether the address is in a specific restricted area. Based on the comparison results, the system determines whether the transaction is "NG," "OK," or "OK ​​but with caution."

[1430] 6. Answer Generation

[1431] server:

[1432] The server generates a response message for the user based on the result of the judgment and the user's emotional state. For example, the message might say, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction," and is written in a tone that takes the user's emotions into consideration.

[1433] 7. Submitting and Viewing Your Answers

[1434] server:

[1435] The generated response message is sent to the user's terminal.

[1436] Device:

[1437] The response message received by the terminal is displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[1438] 8. Answering questions

[1439] Terminals, Servers:

[1440] If the user wants more information, they can enter a follow-up question. The follow-up question is sent to the server, and a generative AI model (e.g., GPT-4) generates an appropriate answer and sends it back to the device. For example, if the prompt is "I'd like to know more about the area under economic sanctions," a detailed answer will be generated: "The area is subject to economic sanctions, and authorization is required for certain transactions."

[1441] In this way, the system quickly and accurately compares various regulatory information based on user input and determines whether a transaction can be carried out. It also uses an emotion engine to recognize user emotions and respond appropriately, enhancing the user's sense of security.

[1442] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1443] Step 1:

[1444] Input: The user enters the customer name, address, and transaction details.

[1445] What happens: A user enters information into a web form on their device, such as "XYZ Corporation," "456 Main Street, New York, USA," and "Electronics Sales," and clicks the "Confirm" button.

[1446] Output: User input data is sent from the device to the server.

[1447] Step 2:

[1448] Input: User input data received from the device.

[1449] Specific operation: The server receives the data sent from the terminal and normalizes and validates the data. For example, it checks whether there are any inappropriate characters in the address format or the customer name. If there are any inappropriate parts, it automatically corrects them.

[1450] Output: Normalized and validated data.

[1451] Step 3:

[1452] Input: Normalized and validated user input data.

[1453] Specific operation: The server's emotion engine analyzes the input speed of input data and the frequency of error messages to recognize the user's emotional state. For example, if the input speed is slower than usual and an error message appears three or more times, it will determine that the user is feeling "anxiety" or "stressed."

[1454] Output: User's emotional state (e.g., anxiety, stress).

[1455] Step 4:

[1456] Input: Normalized and validated user input data.

[1457] Specific operation: The server accesses regulatory information databases (e.g., OFAC lists, Interpol lists) and obtains the latest regulatory information.

[1458] Output: Latest regulatory information.

[1459] Step 5:

[1460] Input: Up-to-date regulatory information and normalized user input data.

[1461] Specific operation: The server compares the obtained regulatory information with the user's input data, for example, checking whether the customer name is on a sanctions list or anti-social forces list, or whether the address is in a specific restricted area.

[1462] Output: Verification result (e.g., no problem, transaction not accepted, caution required).

[1463] Step 6:

[1464] Input: Match result.

[1465] Specific operation: The server determines whether or not to allow a transaction based on the matching results. For example, if the customer name is included in the sanctions list, the transaction is denied. If all matching results are OK, the transaction is allowed. If the address is included in a sanctions area, the transaction is allowed, but with caution.

[1466] Output: Transaction approval / disapproval result.

[1467] Step 7:

[1468] Input: Transaction decision result and user's emotional state.

[1469] Specific operation: The server adjusts the judgment result and related points of caution based on the user's emotional state and generates a response message to the user. For example, if the transaction is OK but the address is in an area subject to economic sanctions, the server will create a message in a softer tone, sensing the user's anxiety, such as "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1470] Output: The reply message.

[1471] Step 8:

[1472] Input: The answer message.

[1473] Specific operation: The server sends the generated response message to the user's terminal.

[1474] Output: The reply message is sent to the user's terminal.

[1475] Step 9:

[1476] Input: The answer message sent to the user's device.

[1477] Specific operation: The device displays the received response message on the user's screen.

[1478] Output: Message displayed to the user regarding whether the transaction is possible or not and important points to note.

[1479] Step 10:

[1480] Input: Any additional questions from the user.

[1481] How it works: If a user wants more information, they enter an additional question on their device and send it to the server. The server uses a generative AI model (e.g., GPT-4) to generate an appropriate answer and send it back to the device. For example, if a user asks, "I'd like to know more about areas subject to economic sanctions," the generative AI model will generate the answer, "The area in question is subject to economic sanctions, and authorization is required for certain transactions."

[1482] Output: The generated answers to the follow-up questions are sent to the user's device and displayed.

[1483] (Application example 2)

[1484] 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."

[1485] Conventional supplier evaluation systems determine whether to approve a transaction by checking against a regulatory information database, but they often leave users feeling uneasy about the evaluation because they lack appropriate responses that reflect the user's emotional state. Furthermore, the lack of consideration for emotional recognition can sometimes impair the user experience, which is an issue.

[1486] The identification processing 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: input means through which a user inputs the name, address, and transaction details of the business partner; data processing means that receives the user's input data and normalizes and validates it; comparison means that accesses regulatory information databases and anti-social forces lists in various countries and compares the user's input data with the data; determination means that determines whether the transaction is permitted based on the comparison results and generates the result; answer generation means that transmits the determination result and related precautions to the user's terminal; question response means that accepts additional questions from the user and generates answers using a new generation AI; emotion recognition means that recognizes the user's emotional state based on the input speed and number of errors; and tone-adjusted message generation means that generates messages with the tone adjusted based on the user's emotional state. This makes it possible to provide appropriate responses that take the user's emotional state into consideration and improve the reliability of transaction decisions.

[1487] "Input means" refers to the device or software that allows a user to input the name, address, and transaction details of the customer.

[1488] "Data Processing Means" refers to the systems and algorithms that receive, normalize, and validate user input data.

[1489] "Matching means" refers to a system that has the ability to access regulatory information databases and anti-social force lists in each country and match them with user-entered data.

[1490] "Determination means" refers to a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[1491] "Answer generation means" refers to a system that has the function of transmitting the judgment results and related points of caution to the user's terminal.

[1492] "Question response means" refers to a system that has the function of accepting additional questions from users and generating answers again using generation AI.

[1493] "Emotion recognition means" refers to systems or algorithms that recognize a user's emotional state based on input speed or frequency of error messages.

[1494] "Tone-adjusted message generator" refers to a system or algorithm for generating tone-adjusted messages based on emotional state.

[1495] The present invention provides a system that enables a user to quickly and accurately evaluate the reliability of a trading partner and proceed with a transaction with peace of mind. Specific embodiments of the system of the present invention will be described below.

[1496] System Configuration

[1497] This system mainly consists of the following elements:

[1498] 1. Device:

[1499] The user is provided with input means for inputting the name, address, and transaction details of the business partner.

[1500] Specific devices that can be used include smartphones, computers, tablets, etc.

[1501] 2. Server:

[1502] A data processing means is provided for receiving user input data and for normalizing and validating the data.

[1503] It is equipped with a means of comparison that accesses regulatory information databases and anti-social force lists in each country and compares them with user-entered data.

[1504] The system includes a determination means for determining whether or not a transaction is possible based on the result of the verification and generating the result.

[1505] The system is provided with an answer generation means for transmitting the judgment result and related points of caution to the user's terminal.

[1506] It is equipped with a question response function that accepts additional questions from users and generates answers using the generation AI again.

[1507] The system is equipped with an emotion recognition means that recognizes the user's emotional state based on input speed and frequency of error messages.

[1508] The device includes a tone-adjusted message generating means for generating a message with a tone adjusted based on the emotional state.

[1509] 3. Software and Services Used:

[1510] Use Python as the programming language.

[1511] Use requests, a Python library for handling HTTP requests.

[1512] Use an emotion recognition engine API (e.g. emotionrecognition API) for emotion recognition.

[1513] Use regulatory information database APIs (e.g., regulatoryinfo API) to query regulatory information.

[1514] Processing flow

[1515] The user uses the terminal to enter the name of the business partner, address, and transaction details, and then clicks the "Confirm" button. An example of input is as follows:

[1516] Account Name: XYZ Corporation

[1517] Address: 456 Market Street, Tokyo, Japan

[1518] Transaction: Purchase of electronic components

[1519] The terminal sends the user's input data to the server, which first normalizes and validates the data, then accesses a regulatory information database and a list of anti-social forces to check and determine whether the transaction should proceed.

[1520] Additionally, the app uses an emotion recognition API to recognize a user's emotional state by analyzing their typing speed and the frequency of error messages. For example, if it determines that the user is feeling anxious, it will generate a message with a tone tailored to that emotional state.

[1521] The judgment result and emotion recognition result are integrated to generate a final answer message. This message is sent to the user's device and displayed to the user as an example:

[1522] The transaction is OK, but your address is in a sanctioned area. You seem to be concerned, so we need to do some additional verification.

[1523] If the user wants more information, they can ask a follow-up question, which is sent to the server, which uses the generative AI model to generate an appropriate answer and sends it back to the user.

[1524] The above is a specific example of the embodiment of the present invention. This system allows users to judge the reliability of their business partners with high accuracy, and provides a sense of security by receiving responses that correspond to their emotions.

[1525] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1526] Step 1:

[1527] The user enters the customer's name, address, and transaction details into the terminal.

[1528] The user enters the client name, address, and transaction details into the input form and clicks the "Confirm" button. An example of input is as follows:

[1529] Account Name: XYZ Corporation

[1530] Address: 456 Market Street, Tokyo, Japan

[1531] Transaction: Purchase of electronic components

[1532] The input data is sent from the terminal to the server.

[1533] Step 2:

[1534] The server receives the user input data and performs normalization and validation.

[1535] The server receives user-entered data sent from the terminal. The normalization process checks for address format consistency and appropriate client name strings to improve data consistency. The validation process checks whether all required fields are filled in and the data is accurate.

[1536] Input: User input data (client name, address, transaction details)

[1537] Output: Normalized and validated data

[1538] Step 3:

[1539] The server performs emotion recognition based on the input data.

[1540] The emotion recognition engine analyzes the user's emotional state based on data such as the user's input speed and the frequency of input error messages, and determines whether the user is feeling anxious or stressed, for example, based on the results of this analysis.

[1541] Input: Corrected user input data, input speed, frequency of error messages

[1542] Output: User's emotional state (e.g., anxious, calm, etc.)

[1543] Step 4:

[1544] The server accesses the regulatory information database and anti-social forces list to perform the check.

[1545] Using the normalized input data, the server accesses each country's regulatory information database and anti-social forces list and checks it against the user's input data. This check process verifies whether the customer name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1546] Input: Normalized user input data

[1547] Output: Verification result (e.g., transaction OK, transaction NG, cautions)

[1548] Step 5:

[1549] The server determines whether the transaction is possible and generates a result.

[1550] The server determines whether or not to allow the transaction based on the matching results. For example, if the client's name is on the sanctions list, the server determines that the transaction is "NG," but if all matching results are satisfactory, the server determines that the transaction is "OK." If the address is in a sanctions-targeted area, the server determines that the transaction is "OK, but with caution."

[1551] Input: Matching result

[1552] Output: Transaction availability determination result (e.g., transaction OK, transaction NG, cautions apply)

[1553] Step 6:

[1554] The server generates a response message based on the judgment result and emotion recognition result.

[1555] The server combines the transaction approval / disapproval judgment result with the emotion recognition result to generate a response message for the user. For example, if the transaction is OK but the user is feeling uneasy, the tone of the message is adjusted to generate a message such as, "The transaction is OK, but you seem to be feeling uneasy, so we will conduct further confirmation."

[1556] Input: Transaction approval / disapproval decision result, user's emotional state

[1557] Output: Tone-adjusted answer message

[1558] Step 7:

[1559] The server sends a response message to the terminal.

[1560] The generated response message is sent from the server to the user's terminal, where the judgment result and related points to note are displayed.

[1561] Input: Reply message

[1562] Output: Message displayed on the user's terminal

[1563] Step 8:

[1564] The user enters a follow-up question, and the server again uses the generation AI to generate an answer.

[1565] If the user enters a follow-up question, the question is sent to the server, which uses a generative AI model to generate an appropriate answer and sends it back to the user's device. For example, if the user enters, "I'd like to know more about sanctioned areas," the server might generate a response such as, "The area is on the sanctions list, and authorization is required for certain transactions."

[1566] Input: User's additional question

[1567] Output: Answer message from the generating AI

[1568] This series of processes allows users to quickly and accurately judge the reliability of their trading partners, allowing them to proceed with transactions with peace of mind. In addition, receiving responses that reflect their emotions improves the user experience.

[1569] 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.

[1570] 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.

[1571] 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.

[1572] [Fourth embodiment]

[1573] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1574] 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.

[1575] 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).

[1576] 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.

[1577] 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.

[1578] 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).

[1579] 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.

[1580] 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.

[1581] 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.

[1582] 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.

[1583] 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.

[1584] 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.

[1585] 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."

[1586] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, and can compare various regulatory information based on user input, and provide a decision on whether or not to proceed with a transaction and important points to note. Specific embodiments of the system of the present invention are described below.

[1587] Program Overview

[1588] This system consists of a terminal where users can input the name, address, and transaction details of their business partners, and a server that processes and collates this data.

[1589] 1. User Input

[1590] Device:

[1591] The user enters the name, address, and transaction details of the business partner into the form on the terminal and clicks the "Confirm" button. By doing so, the user provides the system with information about the company or organization with which the transaction is being made.

[1592] 2. Receiving and Preprocessing Input Data

[1593] server:

[1594] Receives user input data sent from the terminal, then normalizes and validates the received data, for example, checking that the address format is correct and that the customer name does not contain inappropriate characters.

[1595] 3. Regulatory information collation

[1596] server:

[1597] The system accesses regulatory information databases and lists of anti-social forces and compares them with the data entered by the user, specifically checking whether the name of the business partner is on a sanctions list or whether the address is in a restricted area.

[1598] 4. Transaction Approval Determination

[1599] server:

[1600] Based on the result of the check, a decision is made as to whether the transaction can be carried out. This decision is classified as follows:

[1601] Transactions prohibited: If the business partner is included in the sanctions list or anti-social forces list

[1602] Transaction OK: If all matching results are OK

[1603] OK, but be careful: If your address is in a sanctioned area, or if you need to be careful with the transaction

[1604] 5. Answer Generation

[1605] server:

[1606] Based on the results of the transaction approval / disapproval judgment, a response is generated for the user. For example, a message such as "Transaction not permitted," "Transaction OK," or "Transaction OK, but caution required" is generated, and further detailed warnings are also added.

[1607] 6. Submit your response

[1608] server:

[1609] The generated answer is sent to the user's device, where the user can check whether the transaction is possible and any important points to note.

[1610] 7. Answering questions

[1611] Terminals, Servers:

[1612] The device provides a text box for the user to enter additional questions, allowing the user to request more detailed information. The server accepts the additional questions, uses a generative AI to generate appropriate answers, and sends them back to the device.

[1613] Specific examples

[1614] User Input

[1615] user:

[1616] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button.

[1617] Receiving and Preprocessing Input Data

[1618] server:

[1619] Check the format of the data received, for example, to make sure "123 Main Street, Tokyo, Japan" is a valid address format.

[1620] Regulatory information verification

[1621] server:

[1622] It checks against regulatory information databases to see, for example, whether "ABC Corporation" is on a sanctions list or whether "123 Main Street, Tokyo, Japan" is in a restricted area.

[1623] Determination of whether or not a transaction is possible

[1624] server:

[1625] Based on the results of the comparison, it is determined that "ABC Corporation is OK, but the address is in a sanctioned area, so transactions are OK but caution is required."

[1626] Generate and submit answers

[1627] server:

[1628] Generate and send a message saying, "Transaction OK, but additional verification is required for the transaction as the address is in a sanctioned area."

[1629] Device:

[1630] Display a response message to the user.

[1631] Answering questions

[1632] user:

[1633] The user types in a question such as, "I'd like to know more about areas subject to economic sanctions."

[1634] server:

[1635] The system receives the additional question and uses a generation AI to generate a response that reads, "The relevant region is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." and sends this to the device.

[1636] Device:

[1637] The generated AI's answer is displayed on the user's screen.

[1638] In this way, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides a response, thereby providing users with an efficient means of verifying the trustworthiness of their trading partners.

[1639] The processing flow will be explained below.

[1640] Step 1:

[1641] User:

[1642] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[1643] Step 2:

[1644] Device:

[1645] The terminal transmits the user's input data to the server.

[1646] Step 3:

[1647] server:

[1648] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[1649] Step 4:

[1650] server:

[1651] The server uses the normalized input data to access the regulatory information database and the anti-social forces list, and obtains the latest regulatory information from the database.

[1652] Step 5:

[1653] server:

[1654] The server compares the obtained regulatory information with the user's input data, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1655] Step 6:

[1656] server:

[1657] The server determines whether or not to allow the transaction based on the results of the check. For example, if the customer's name is on the sanctions list, the transaction is denied; if all checks are OK, the transaction is allowed; and if the address is in a sanctions area, the transaction is allowed, but with caution.

[1658] Step 7:

[1659] server:

[1660] The server generates a response message for the user based on the transaction approval / disapproval decision and any related points of caution, such as "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1661] Step 8:

[1662] server:

[1663] The generated reply message is sent to the user's terminal.

[1664] Step 9:

[1665] Device:

[1666] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[1667] Step 10:

[1668] User:

[1669] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[1670] Step 11:

[1671] Device:

[1672] The terminal sends the user's follow-up question to the server.

[1673] Step 12:

[1674] server:

[1675] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[1676] Step 13:

[1677] server:

[1678] The answer to the generated question is sent to the user's terminal.

[1679] Step 14:

[1680] Device:

[1681] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[1682] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[1683] Example 1

[1684] 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."

[1685] The objective of this invention is to quickly and accurately evaluate the trustworthiness of a trading partner. Conventional methods have the problem of being inefficient, taking time to verify regulatory information and determine whether or not to allow a transaction. In addition, it is difficult to respond appropriately to follow-up questions from users, which can result in a decline in the trustworthiness of the transaction.

[1686] 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.

[1687] In this invention, the server includes: input means for a user to input the business name, location, and transaction details; data processing means for receiving the user's input data and standardizing the format and confirming its validity; data comparison means for accessing regulatory information databases and illegal force lists in multiple countries and comparing the data with the user's input data; transaction determination means for determining whether or not the transaction is possible based on the comparison results and generating the result; answer generation means for transmitting the determination result and related points to the user's terminal; and question response means for receiving follow-up questions from the user and generating answers using a generative AI model. This makes it possible to quickly and accurately evaluate the reliability of a business partner and appropriately respond to follow-up questions from the user.

[1688] "User" refers to a user who uses the system to evaluate the trustworthiness of business partners.

[1689] "Business name" is the name of the business partner that the user inputs as the target of evaluation.

[1690] "Location" is the physical address information of the business partner entered by the user.

[1691] "Transaction details" refers to information entered by the user regarding the specific details and nature of the transaction with the business partner.

[1692] "Input means" refers to an interface that allows a user to input the name, address, and transaction details of a business partner into the system.

[1693] The "data processing means" is a part that has the function of standardizing the format and validating the data received from the user.

[1694] "Format unification" is a process for unifying the format of received data.

[1695] "Validation" is a verification process to ensure that received data is accurate.

[1696] The "data comparison means" is a part that has the function of comparing the data entered by the user with the regulatory information database and the list of illegal forces.

[1697] The "Regulatory Information Database" is a database containing information on sanctioned areas and restricted areas of each country.

[1698] The "List of Illegal Forces" is a list of information on anti-social forces and organizations subject to sanctions.

[1699] The "transaction determination means" is a part having a function for determining whether or not a transaction is permitted based on the result of the verification and generating a determination result.

[1700] The "answer generation means" is a part that has a function of generating a message to notify the user of the transaction judgment result and related points to note.

[1701] The "question response means" is the part that has the function of accepting additional questions from users and generating answers using a generative AI model.

[1702] A "generative AI model" is a model that uses AI to generate appropriate answers to questions in natural language.

[1703] This invention is a system for evaluating the reliability of trading partners, collating various regulatory information based on the business name, location, and transaction details entered by the user, and providing the propriety of the transaction and important points to note. This system handles user input, receives and preprocesses data, collates regulatory information, determines whether the transaction is permitted, generates and transmits answers, and responds to follow-up questions.

[1704] System Configuration

[1705] 1. Input Method

[1706] Users use their own devices (PC, smartphone, tablet, etc.) to enter the business name, address, and transaction details into a dedicated form, thereby providing the system with information about the company or organization with which the user is conducting business.

[1707] 2. Data processing means

[1708] The server receives the user's input data. The received data undergoes formatting and validation checks. For example, it standardizes the address format and removes inappropriate characters. It also checks whether the input data is in the correct format.

[1709] 3. Data verification methods

[1710] The server accesses databases of regulatory information from multiple countries (e.g., OFAC sanctions lists) and illegal power lists and checks the data entered by the user to see if the entity name is on a sanctions list or if its location is in a restricted area.

[1711] 4. Transaction Judgment Method

[1712] The server determines whether to allow the transaction based on the verification result. This determination is categorized as follows:

[1713] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[1714] Transaction OK: If there are no problems with the matching results.

[1715] OK, but with caveats: If you need to be careful with the transaction, for example, if your location is in a sanctioned area.

[1716] 5. Answer generation means

[1717] The server generates a response to the user based on the transaction judgment result, such as a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1718] 6. Method of sending responses

[1719] The server then sends the generated response to the user's device, where the user can check whether the transaction is possible and any important points to note.

[1720] 7. How to respond to questions

[1721] Users can use a text box to enter additional questions. The server accepts the user's additional questions, generates an appropriate answer using a generative AI model (e.g., ChatGPT), and sends it back to the user's device. For example, it might generate an answer like, "The region in question is included in Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to official guidelines for detailed regulations."

[1722] Specific examples

[1723] Let's say a user enters the information "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and presses the "Confirm" button. The server receives this information and verifies that the address format is correct. It then checks against a regulatory database to see if "Company A" is on a sanctions list and if "123 Main Street, Tokyo, Japan" is in a restricted area.

[1724] Based on the matching results, the server determines that "the transaction is OK, but caution is required, as the address is in a sanctioned area," and generates and sends a message to the user stating, "The transaction is OK, but additional confirmation is required as the address is in a sanctioned area."

[1725] When the user enters an additional question such as "I would like to know more about areas subject to economic sanctions," the server uses a generative AI model to generate an answer: "The area in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations." This answer is then sent to the user's device.

[1726] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1727] Step 1: User Input

[1728] User: The user uses input means to enter the business name, address, and transaction details into the dedicated form on their device. For example, the user enters "Company A," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components," and clicks the "Confirm" button. In this step, the entered data is sent to the system.

[1729] Step 2: Receiving and Preprocessing Data

[1730] Server: The server receives input data sent from the terminal. The received data is checked for format consistency and validity. Specifically, it checks whether the address format is correct and whether the business name contains inappropriate characters. For example, it checks whether "123 Main Street, Tokyo, Japan" is a valid address format. The server stores the input data (business name, address, transaction details) in an organized format in an internal database.

[1731] Step 3: Regulatory information verification

[1732] Server: The server compares the data stored in the internal database with the regulatory information database. Specifically, it checks whether the business name is on a sanctions list or whether its location is in a restricted area. In this process, it accesses regulatory information databases from multiple countries (e.g., OFAC lists) and illegal force lists. For example, it checks to see if "Company A" is on a sanctions list. It then saves the comparison results in the internal database.

[1733] Step 4: Determine whether to proceed with the transaction

[1734] Server: Based on the verification result, the server determines whether the transaction is allowed or not. The criteria are as follows:

[1735] No transactions: If the trading partner is included on a sanctions list or illegal forces list.

[1736] Transaction OK: If there are no problems with the matching results.

[1737] OK, but with caveats: If the location is in a sanctioned area, you may need to be careful with the transaction.

[1738] For example, it may determine that "Company A is OK, but its location is in a sanctioned area, so transactions are OK but caution is required." It then generates a message to inform the user of the determination result.

[1739] Step 5: Generate an answer

[1740] Server: The server generates a response message for the user based on the transaction judgment result. For example, it generates a message saying, "The transaction is OK, but because your location is in an area subject to economic sanctions, additional confirmation is required for the transaction." The generated message is then stored in an internal database.

[1741] Step 6: Submit your response

[1742] Server: The server generates a response message and sends it to the user's device, where it is displayed.

[1743] On the device: The user sees a message on their device screen saying, "Transaction OK, but because you are located in a sanctioned area, additional verification is required to complete the transaction."

[1744] Step 7: Answer questions

[1745] User: The user uses a text box on the device to enter a follow-up question, for example, "I'd like to know more about sanctioned areas."

[1746] Server: The server receives the user's additional question and generates an appropriate answer using the generative AI model. For example, it generates a message such as, "The region in question is included in the Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to the official guidelines for detailed regulations." The generated answer message is then sent to the user's device.

[1747] Terminal: The user sees the AI's response message on the terminal screen, such as, "The region is included in the Japanese government and international sanctions lists, and certain transactions require authorization. Please refer to the official guidelines for detailed regulations."

[1748] Through these steps, the system quickly and accurately compares various regulatory information based on user input, determines whether a transaction can be carried out, and provides an answer. It can also respond to additional questions from users, improving the reliability of transactions.

[1749] (Application example 1)

[1750] 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."

[1751] In commercial transactions, it is extremely important to quickly and accurately assess the trustworthiness and regulatory compliance of trading partners. However, traditional methods rely heavily on manual verification, which is time-consuming and labor-intensive and prone to errors. Furthermore, it is difficult to timely collate multiple regulatory information and lists, resulting in a lack of reliability and efficiency in determining transaction risk. This has created a need for improved business reliability and reduced transaction risk.

[1752] 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.

[1753] In this invention, the server includes: input means for a user to input the name, address, and transaction details of a business partner; data processing means for receiving the user's input data and standardizing and verifying it; inspection means for accessing regulatory information sources and lists of anti-social forces in each country and comparing them with the user's input data; evaluation means for evaluating the feasibility of a transaction based on the comparison results and generating the results; answer generation means for transmitting the evaluation results and related points of caution to the user's device; response means for accepting additional questions from the user and generating answers again using a generation AI; and auxiliary means for comparing the user's business partner's name and address with regulatory information sources and evaluating and generating the feasibility of a transaction and points of caution in real time, thereby enabling the reliability of a business partner to be evaluated quickly and accurately and making transaction decisions based on the results of the comparison with regulatory information.

[1754] A "user" is a person or company that uses the system to input information about a business partner and request a reliability evaluation.

[1755] "Commercial name" is the name of the company or organization with which you are conducting business.

[1756] "Location" refers to information that indicates the specific address or geographic location of a business partner.

[1757] "Transaction details" refers to information about the products or services that the user plans to trade and details of the transaction.

[1758] The "input means" is an interface for the user to input the name, address, and transaction details of the business partner.

[1759] "Data Processing Means" means means for standardizing and verifying the accuracy of data received from users.

[1760] "Standardization" is the process of converting input information into a unified format.

[1761] "Validation" is the process of ensuring that input data is accurate.

[1762] "Regulatory Information Source" is a database that collects information on the laws and regulations of each country.

[1763] The "List of Anti-Social Forces" is a list of organizations and individuals that engage in anti-social activities.

[1764] "Testing means" refers to means for checking user-entered data against regulatory information sources and lists of anti-social forces.

[1765] The "evaluation means" is a means for determining whether or not a transaction can be carried out based on the result of the comparison.

[1766] The "answer generation means" is a means for generating evaluation results and related points of attention and providing them to the user.

[1767] A "response means" is a means of accepting additional questions from users and generating answers using a generation AI.

[1768] The "auxiliary means" refers to a means of comparing the name and location of the user's commercial counterparty with regulatory information sources, and generating a real-time assessment of whether a transaction is possible and what precautions need to be taken.

[1769] "Generative AI" is an artificial intelligence model that generates appropriate answers to user questions.

[1770] This invention is a system that allows users to quickly and accurately evaluate the trustworthiness of their business partners, providing real-time evaluation of whether or not to do business with them based on regulatory information sources and lists of anti-social forces in each country. This system mainly consists of the following components:

[1771] Hardware Configuration

[1772] User device: A device such as a smartphone or PC on which the user enters business partner information and receives evaluation results.

[1773] Server: A high-performance computing device for data processing, matching, evaluation, and answer generation.

[1774] Software Configuration

[1775] Input means: An interface through which a user inputs the name, address, and transaction details of a business partner. For example, this would be an input form on a smartphone application.

[1776] Data processing means: A program to normalize the data received from users and check its format. Specifically, a web framework such as Python's Flask is used.

[1777] Verification method: A program that checks user-entered data against regulatory information sources and lists of anti-social forces. It accesses external regulatory databases using APIs.

[1778] Evaluation method: Logic for determining whether or not a transaction is possible based on the matching results. A decision is made based on various conditions and a result is generated.

[1779] Answer generation means: A program for generating answers that combine the evaluation results and related points of attention and sending them to the user.

[1780] Response method: A function to accept additional questions from the user and generate answers again using generative AI. Possible generative AI models include OpenAI's GPT-3.

[1781] Auxiliary tool: A program that checks regulatory information in real time based on the user's commercial partner's name and location, and generates a transaction approval / disapproval and warnings.

[1782] Processing Flow

[1783] The user's terminal provides an interface for inputting the name, address, and transaction details of the business partner. This input is sent to the server, where the data processing means normalizes and verifies it. Then, based on the collated data, the inspection means accesses external regulatory information sources and lists of anti-social forces for collation.

[1784] The evaluation means determines whether or not the transaction is possible based on the collation result and generates an evaluation result. Based on this result, the answer generation means transmits to the user's terminal whether or not the transaction is possible and any necessary precautions.

[1785] If the user enters additional questions, the server's response mechanism will utilize AI generation to generate appropriate answers and send them to the user's device. In addition, the assistance mechanism will perform real-time verification to support quick and accurate trading decisions.

[1786] Specific examples

[1787] For example, a user enters a "general company name" as the business destination, a "general address" as the location, and "purchase of goods" as the transaction details. The server receives the information, and after the data processing means correctly formats it, the inspection means checks it against a regulatory information database and a list of anti-social forces. The evaluation means then determines that "the general company name is OK, but the general address requires caution," and the answer generation means notifies the user of the result. If the user adds a more detailed question, the response means uses a generation AI to respond, "Confirmation is required as specific regulations apply to general areas."

[1788] Prompt Sentence Examples

[1789] "Based on user input, check the regulatory information for companies and addresses and evaluate whether or not to allow transactions. Input example: 'General company name', 'General address'"

[1790] In this way, the system quickly and accurately evaluates the reliability of trading partners, and helps users make effective trading decisions.

[1791] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1792] Step 1:

[1793] User enters business name, address, and transaction details

[1794] The user uses the interface of their device (such as a smartphone or PC) to enter the name, address, and transaction details of the commercial partner. Once the input is complete, they press the "Confirm" button and the data is sent to the server. The input data is entered directly into the text box.

[1795] Input: Name of business partner, address, transaction details

[1796] Output: Input data (commercial name, address, transaction details)

[1797] Step 2:

[1798] Normalizing and validating data received by the server

[1799] The server receives input data sent by the user. The received data is first normalized. For example, commas and spaces are standardized, and address formats are checked to ensure they are correct. Next, the data is validated to ensure there are no errors in the input. If improperly formatted data or missing required fields are detected, an error message is generated and sent back to the user.

[1800] Input: Input data (business partner name, address, transaction details)

[1801] Output: Normalized and validated data, or error messages

[1802] Step 3:

[1803] The server accesses regulatory information sources and lists of anti-social forces and performs cross-checking.

[1804] After normalization and validation are complete, the server accesses regulatory information sources and anti-social forces lists to verify the data. Specifically, it checks whether the customer's name is on a sanctions list or whether the customer's location is in a restricted area. This verification is performed in real time through API communication with external databases.

[1805] Input: Normalized and validated data

[1806] Output: Matching result (whether the transaction is possible or not, points to note)

[1807] Step 4:

[1808] The server evaluates whether the transaction is possible based on the matching results and generates a result.

[1809] The server evaluates whether the transaction is possible or not based on the matching results. The evaluation is classified as follows: No transaction (if the business destination is on the sanctions list), OK transaction (if all matching results are OK), OK but with cautions (if the location is in a sanctions-listed area but the business destination itself is OK). Based on this evaluation, a result including detailed cautions is generated.

[1810] Input: Matching result (transaction possibility, points to note)

[1811] Output: Evaluation result (transaction possibility, points to note)

[1812] Step 5:

[1813] The server notifies the user of the evaluation results and related precautions.

[1814] The server uses the response generation means to send an appropriate message to the user's device based on the generated evaluation results and points to note. The message includes whether the transaction is OK, NG, OK with points to note, and specific points to note.

[1815] Input: Evaluation result (transaction possibility, points to note)

[1816] Output: A message to be sent to the user

[1817] Step 6:

[1818] Handling follow-up questions from the user

[1819] If the user wants more detailed information, an interface is provided for entering additional questions. Once the user enters and submits the question, the server receives the question and uses a generative AI model (e.g., GPT-3) to generate an appropriate answer. The generated answer is then sent back to the user.

[1820] Input: Additional question text

[1821] Output: The answer from the generative AI model and its transmission

[1822] Through the above steps, this system quickly and accurately evaluates the reliability of trading partners and helps users make effective trading decisions.

[1823] 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.

[1824] The present invention is a system that quickly and accurately evaluates the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to consider, thereby helping users to proceed with transactions with peace of mind. Furthermore, by combining the system with an emotion engine that recognizes user emotions and responds appropriately based on those emotions, the user experience can be improved. Specific embodiments of the system of the present invention are described below.

[1825] Program Overview

[1826] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server for processing and collating this data, and an emotion engine for recognizing the user's emotions.

[1827] 1. User Input

[1828] Device:

[1829] The user enters the name, address, and transaction details into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[1830] 2. Receiving and Preprocessing Input Data

[1831] server:

[1832] Receives user input data sent from the terminal and normalizes and validates it. For example, it checks whether the address format is correct or whether the customer name contains inappropriate characters, and corrects any inappropriate parts.

[1833] 3. Emotional Recognition

[1834] server:

[1835] The emotion engine analyzes the user's input data (e.g., typing speed, number of input errors, etc.) to recognize the user's emotional state, for example, determining whether they are feeling anxious or stressed.

[1836] 4. Regulatory information collation

[1837] server:

[1838] Using the normalized input data, the regulatory information database and anti-social forces list are accessed to obtain the latest regulatory information.

[1839] 5. Matching

[1840] server:

[1841] The system compares the obtained regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1842] 6. Transaction Approval Determination

[1843] server:

[1844] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[1845] 7. Answer Generation

[1846] server:

[1847] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1848] 8. Submitting your response

[1849] server:

[1850] The generated response message is sent to the user's terminal.

[1851] 9. View Answers

[1852] Device:

[1853] The received response message will be displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[1854] 10. Answering questions

[1855] Terminals, Servers:

[1856] If a user wants more detailed information, they can enter additional questions. These questions are sent to the server, which uses a generative AI to generate an appropriate answer and sends it back to the device. For example, if a user enters the question, "I'd like to know more about areas subject to economic sanctions," the server will generate the answer, "The relevant areas are included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[1857] Specific examples

[1858] User Input and Emotion Recognition

[1859] user:

[1860] The user enters the information "ABC Corporation," "123 Main Street, Tokyo, Japan," and "purchasing electronic components," and presses the "Confirm" button. At this time, the emotion engine recognizes that the user is feeling anxious based on the speed of input and the frequency of error messages.

[1861] Answer generation and message sending

[1862] server:

[1863] Based on the results of the comparison, the server determines that the transaction is OK, but there are some caveats, and generates a message stating, "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction." In addition, the emotion engine detects the user's anxiety and adjusts the tone of the message to be softer.

[1864] Device:

[1865] Display the generated message on the user's screen.

[1866] In this way, the system quickly and accurately compares various regulatory information based on user input to determine whether a transaction can be carried out, and furthermore, by appropriately recognizing and responding to user emotions using an emotion engine, it improves the user experience.

[1867] The processing flow will be explained below.

[1868] Step 1:

[1869] User:

[1870] The user enters the name, address, and transaction details of the business partner into the input form on the terminal and clicks the "Confirm" button. For example, the user enters information such as "ABC Corporation," "123 Main Street, Tokyo, Japan," and "Purchase of electronic components."

[1871] Step 2:

[1872] Device:

[1873] The terminal transmits the user's input data to the server.

[1874] Step 3:

[1875] server:

[1876] The server receives the received user input data and performs normalization and validation of the data, for example, checking that the address format is correct or that the customer name does not contain any invalid characters, and correcting any inappropriate parts.

[1877] Step 4:

[1878] server:

[1879] The server sends the normalized input data to the emotion engine.

[1880] Step 5:

[1881] server:

[1882] The emotion engine analyzes the user's input data and recognizes the user's emotional state based on the input speed, frequency of error messages, etc. For example, if a user makes many input errors in a short period of time, it can determine that the user is feeling anxious or stressed.

[1883] Step 6:

[1884] server:

[1885] The server uses the normalized input data to access the regulatory information database and the anti-social forces list to obtain the latest regulatory information.

[1886] Step 7:

[1887] server:

[1888] The system compares the acquired regulatory information with the data entered by the user, specifically checking whether the client's name is on a sanctions list or anti-social forces list, and whether the address is in a specific restricted area.

[1889] Step 8:

[1890] server:

[1891] Based on the results of the check, a decision is made as to whether or not the transaction is possible. For example, if the name of the business partner is on the sanctions list, the transaction is "not permitted," if all check results are satisfactory, the transaction is "OK," and if the address is in a sanctions-targeted area, the transaction is "OK, but with caution."

[1892] Step 9:

[1893] server:

[1894] Based on the transaction approval / disapproval decision and the user's emotional state as recognized by the emotion engine, a response message is generated for the user. For example, a message with a tailored tone may be created, such as, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1895] Step 10:

[1896] server:

[1897] The generated reply message is sent to the user's terminal.

[1898] Step 11:

[1899] Device:

[1900] The terminal displays the received response message on the user's screen, allowing the user to check information regarding whether the transaction is possible and important points to note.

[1901] Step 12:

[1902] User:

[1903] If the user wants more information, they can enter a follow-up question, such as "I'd like to know more about areas under economic sanctions."

[1904] Step 13:

[1905] Device:

[1906] The terminal sends the user's follow-up question to the server.

[1907] Step 14:

[1908] server:

[1909] The server receives the additional questions and uses a generation AI to generate an appropriate answer, such as, "The region in question is included on Japanese government and international sanctions lists, and authorization is required for certain transactions. Please refer to official guidelines for detailed regulations."

[1910] Step 15:

[1911] server:

[1912] The answer to the generated question is sent to the user's terminal.

[1913] Step 16:

[1914] Device:

[1915] The device will then display the answers to the received questions on the user's screen, allowing the user to obtain the necessary detailed information.

[1916] This allows the user to obtain the result of the transaction approval / disapproval decision and additional information, providing the user with the information they need to make a decision about whether or not to proceed with the transaction with confidence.

[1917] Example 2

[1918] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1919] Conventional systems for evaluating the trustworthiness of business partners only evaluate basic information about business partners and do not take into account the user's emotional state, making it impossible to reduce user stress and anxiety. Furthermore, determining whether or not to transact based solely on the results of verification does not provide sufficient information on specific points to note or when additional confirmation is required. This does not adequately provide an environment in which users can proceed with transactions with peace of mind.

[1920] 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.

[1921] In this invention, the server includes: input means for a user to input the name, address, and transaction details of the business partner; data processing means for receiving the user's input data and normalizing and validating it; emotion recognition means for analyzing the user's emotions and recognizing their emotional state; comparison means for accessing regulatory information databases and anti-social forces lists in each country and comparing the user's input data with them; determination means for determining whether or not to allow a transaction based on the comparison results and generating the result; answer generation means for adjusting the determination result and related precautions based on the user's emotional state and transmitting them to the user's terminal; and question response means for receiving additional questions from the user and generating answers again using a generation AI. This enables appropriate responses that take the user's emotional state into consideration, allowing the user to proceed with the transaction with peace of mind.

[1922] "Input means" refers to a device or interface that allows a user to input the name, address, and transaction details of a business partner.

[1923] A "data processing means" is a system that has the functionality to receive user input data and normalize and validate that data.

[1924] An "emotion recognition means" is a system that has the function of analyzing a user's input behavior and data and identifying the user's emotional state.

[1925] The "matching means" is a system that has the function of matching the user's input data with each country's regulatory information database and anti-social forces list.

[1926] The "determination means" is a system for determining whether or not a transaction can be carried out based on the result of the verification and generating the result.

[1927] The "answer generation means" is a system that has the function of adjusting the judgment results and related points of attention based on the user's emotional state and transmitting them to the user's terminal.

[1928] The "question response means" is a system that accepts additional questions from users, uses generation AI to generate appropriate answers, and provides them to the user again.

[1929] "Generative AI" is an artificial intelligence model that generates appropriate answers in natural language to users' questions.

[1930] The present invention is a system for quickly and accurately evaluating the trustworthiness of a trading partner, collating various regulatory information based on user input, and providing information on whether a transaction is possible and important points to note. It also improves the user experience by recognizing the user's emotions and responding appropriately based on those emotions. Specific embodiments of the present invention are described below.

[1931] System Overview

[1932] The system consists of a terminal where users can input the name, address, and transaction details of their business partners, a server that processes this data and recognizes emotions, and a database that collates regulatory information.It also uses a generative AI model to generate appropriate answers to follow-up questions from users.

[1933] 1. User Input

[1934] Device:

[1935] The user enters the name, address, and transaction details of the customer into a web form on their device, for example, "XYZ Corporation," "456 Main Street, New York, USA," and "Sales of Electronics," and clicks the "Confirm" button. This input is then sent to the server.

[1936] 2. Data Reception and Preprocessing

[1937] server:

[1938] The server receives input data sent from the terminal. First, it normalizes the data and checks that the input format matches. For example, if the address format is incorrect or if an inappropriate character string is included in the customer name, the server can correct that part.

[1939] 3. Emotional Recognition

[1940] server:

[1941] The emotion engine analyzes the user's input data (e.g., input speed, number of input errors, etc.) and recognizes the user's emotional state. For example, if the input speed is slow and there are many input errors, it will recognize that the user is feeling anxious.

[1942] 4. Regulatory information collation

[1943] server:

[1944] The server uses the normalized input data to access regulatory information databases and anti-social forces lists to obtain the latest regulatory information, such as from the Office of Foreign Assets Control (OFAC) and Interpol databases.

[1945] 5. Matching and Judging

[1946] server:

[1947] The system compares the acquired regulatory information with the user's input data to check whether the business partner's name is included on a sanctions list or anti-social forces list. It also checks whether the address is in a specific restricted area. Based on the comparison results, the system determines whether the transaction is "NG," "OK," or "OK ​​but with caution."

[1948] 6. Answer Generation

[1949] server:

[1950] The server generates a response message for the user based on the result of the judgment and the user's emotional state. For example, the message might say, "The transaction is OK, but because your address is in an area subject to economic sanctions, additional confirmation is required for the transaction," and is written in a tone that takes the user's emotions into consideration.

[1951] 7. Submitting and Viewing Your Answers

[1952] server:

[1953] The generated response message is sent to the user's terminal.

[1954] Device:

[1955] The response message received by the terminal is displayed on the user's screen, where the user can check information regarding whether the transaction is possible and important points to note.

[1956] 8. Answering questions

[1957] Terminals, Servers:

[1958] If the user wants more information, they can enter a follow-up question. The follow-up question is sent to the server, and a generative AI model (e.g., GPT-4) generates an appropriate answer and sends it back to the device. For example, if the prompt is "I'd like to know more about the area under economic sanctions," a detailed answer will be generated: "The area is subject to economic sanctions, and authorization is required for certain transactions."

[1959] In this way, the system quickly and accurately compares various regulatory information based on user input and determines whether a transaction can be carried out. It also uses an emotion engine to recognize user emotions and respond appropriately, enhancing the user's sense of security.

[1960] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1961] Step 1:

[1962] Input: The user enters the customer name, address, and transaction details.

[1963] What happens: A user enters information into a web form on their device, such as "XYZ Corporation," "456 Main Street, New York, USA," and "Electronics Sales," and clicks the "Confirm" button.

[1964] Output: User input data is sent from the device to the server.

[1965] Step 2:

[1966] Input: User input data received from the device.

[1967] Specific operation: The server receives the data sent from the terminal and normalizes and validates the data. For example, it checks whether there are any inappropriate characters in the address format or the customer name. If there are any inappropriate parts, it automatically corrects them.

[1968] Output: Normalized and validated data.

[1969] Step 3:

[1970] Input: Normalized and validated user input data.

[1971] Specific operation: The server's emotion engine analyzes the input speed of input data and the frequency of error messages to recognize the user's emotional state. For example, if the input speed is slower than usual and an error message appears three or more times, it will determine that the user is feeling "anxiety" or "stressed."

[1972] Output: User's emotional state (e.g., anxiety, stress).

[1973] Step 4:

[1974] Input: Normalized and validated user input data.

[1975] Specific operation: The server accesses regulatory information databases (e.g., OFAC lists, Interpol lists) and obtains the latest regulatory information.

[1976] Output: Latest regulatory information.

[1977] Step 5:

[1978] Input: Up-to-date regulatory information and normalized user input data.

[1979] Specific operation: The server compares the obtained regulatory information with the user's input data, for example, checking whether the customer name is on a sanctions list or anti-social forces list, or whether the address is in a specific restricted area.

[1980] Output: Verification result (e.g., no problem, transaction not accepted, caution required).

[1981] Step 6:

[1982] Input: Match result.

[1983] Specific operation: The server determines whether or not to allow a transaction based on the matching results. For example, if the customer name is included in the sanctions list, the transaction is denied. If all matching results are OK, the transaction is allowed. If the address is included in a sanctions area, the transaction is allowed, but with caution.

[1984] Output: Transaction approval / disapproval result.

[1985] Step 7:

[1986] Input: Transaction decision result and user's emotional state.

[1987] Specific operation: The server adjusts the judgment result and related points of caution based on the user's emotional state and generates a response message to the user. For example, if the transaction is OK but the address is in an area subject to economic sanctions, the server will create a message in a softer tone, sensing the user's anxiety, such as "The transaction is OK, but because the address is in an area subject to economic sanctions, additional confirmation is required for the transaction."

[1988] Output: The reply message.

[1989] Step 8:

[1990] Input: The answer message.

[1991] Specific operation: The server sends the generated response message to the user's terminal.

[1992] Output: The reply message is sent to the user's terminal.

[1993] Step 9:

[1994] Input: The answer message sent to the user's device.

[1995] Specific operation: The device displays the received response message on the user's screen.

[1996] Output: Message displayed to the user regarding whether the transaction is possible or not and important points to note.

[1997] Step 10:

[1998] Input: Any additional questions from the user.

[1999] How it works: If a user wants more information, they enter an additional question on their device and send it to the server. The server uses a generative AI model (e.g., GPT-4) to generate an appropriate answer and send it back to the device. For example, if a user asks, "I'd like to know more about areas subject to economic sanctions," the generative AI model will generate the answer, "The area in question is subject to economic sanctions, and authorization is required for certain transactions."

[2000] Output: The generated answers to the follow-up questions are sent to the user's device and displayed.

[2001] (Application example 2)

[2002] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2003] Conventional supplier evaluation systems determine whether to approve a transaction by checking against a regulatory information database, but they often leave users feeling uneasy about the evaluation because they lack appropriate responses that reflect the user's emotional state. Furthermore, the lack of consideration for emotional recognition can sometimes impair the user experience, which is an issue.

[2004] The...

Claims

1. an input means for a user to input the name, address, and transaction details of a business partner; data processing means for receiving, normalizing and validating said user input data; A means for accessing regulatory information databases and anti-social forces lists in each country and comparing them with user-entered data; a determination means for determining whether or not a transaction is possible based on the result of the verification and generating the result; An answer generation means for transmitting the judgment result and related points to be noted to the user's terminal; A question response method that accepts additional questions from users and generates answers using the generation AI again; A system including:

2. 10. The system of claim 1, wherein the system notifies the user that additional verification is required if the address entered by the user is in a sanctioned area.

3. 2. The system according to claim 1, wherein the checking means refers to a list of anti-social forces and a list of economic sanctions based on the inputted name of the business partner.

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