system

Abstract

Provide a system. [Solution] a means of recording payment history; a means of assessing the regularity of the recorded payment history; A means for storing and querying payer attribute information; A means for determining whether to skip the delinquency examination based on the regularity of the payment history and the attribute information of the payer; A system including:

Description

[Technical Field]

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

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

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

[0004] Conventional delinquent payment screening systems require the same screening procedures for all delinquent payers without taking into account their individual payment history or attribute information, which results in time and effort. Furthermore, uniform screening is also required for payers with regular payment patterns and high reliability, which leads to unnecessary delays and costs. [Means for solving the problem]

[0005] The present invention provides a system including a means for recording payment histories, a means for evaluating the regularity of the recorded payment histories, a means for saving and referencing payer attribute information, and a means for determining whether to omit delinquency screening based on the regularity of the payment histories and the payer attribute information. This allows for efficient delinquency screening for payers with regular payment patterns or highly reliable attribute information, thereby reducing time and costs.

[0006] A "payment history" is a record of information about the date, time, and amount of past payments made by a payer.

[0007] "Means for recording" refers to a device or program for storing the payer's payment information in a database or the like.

[0008] A "means for assessing regularity" is a device or program for analyzing recorded payment history and determining whether the payment pattern follows a certain rule.

[0009] "Payer attribute information" is data including specific information about the payer, such as occupation, company affiliation, credit information, etc.

[0010] The "means for storing and querying" refers to a device or program for storing the payer's attribute information in a database or the like and retrieving the information as needed.

[0011] A "delinquency review" is a process to verify whether a payer is properly fulfilling their payment obligations.

[0012] The "means for determining whether to omit the delinquency examination" is a device or program for determining whether to omit the delinquency examination based on the regularity of the payment history and the attribute information of the payer.

[0013] "System" refers to a series of devices and programs that record and evaluate payment history, manage payer attribute information, and improve the efficiency of delinquent payment screening.

[0014] "Payment interval" means the time difference between the dates of each payment, usually expressed in days. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] As an embodiment of the present invention, a system for managing payment history and attribute information of a payer will be described first.

[0037] Payer Registration

[0038] The "user" enters the payer's information. The payer's name and attribute information (such as occupation and company) are also registered, and the "server" stores this information in a database. In particular, if the payer is an employee of a listed company, that information is also stored.

[0039] Recording payments

[0040] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" saves the received payment date in a database and records it as payment history.

[0041] Checking regular payments

[0042] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if a payer makes payments on January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval is within the range of 85 to 95 days.

[0043] Delinquent payment review decision

[0044] The "Server" determines whether to exempt the "User" from the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a listed company, the "Server" will omit the delinquency screening. In this case, the system notifies the "User" via the "Terminal" that the "User" does not need to undergo the delinquency screening.

[0045] Specific examples

[0046] For example, suppose a payer, who is a "user," is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information and checks the regularity of the payments. As a result, it is confirmed that "Yamada Taro" makes payments regularly every three months. The "server" also confirms that "Yamada Taro" is an employee of a listed company. As a result, the "server" displays on the "terminal" that the delinquency review will be omitted, and notifies the "user."

[0047] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on the regularity of payment history and payer attribute information. This system can significantly reduce time and costs compared to conventional methods.

[0048] The processing flow will be explained below.

[0049] Step 1:

[0050] The "user" enters payer information (name and attribute information) into the system, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database.

[0051] Step 2:

[0052] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[0053] Step 3:

[0054] The "server" retrieves the payment history from the database and calculates the intervals between payment dates to check for regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date (in this case, each interval is approximately 90 days).

[0055] Step 4:

[0056] The Server evaluates the payment history for regularity, and if it determines that the payments are regular, it stores that result, as well as if they are not regular.

[0057] Step 5:

[0058] The "server" retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. If the payer belongs to a listed company based on the attribute information, the result is also saved.

[0059] Step 6:

[0060] The "server" determines whether to skip the delinquency check based on the evaluation results of regular payments and the evaluation results of the payer's attribute information. If either one is true, the delinquency check is skipped.

[0061] Step 7:

[0062] The "server" sends the results of the delinquency review to the "terminal." The "terminal" receives the results and notifies the "user." For example, if the delinquency review is omitted, the "user" displays a message indicating that the delinquency review is not required.

[0063] Step 8:

[0064] The "user" reviews the results and decides on the next action if necessary, such as creating a new payment plan.

[0065] Example 1

[0066] 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."

[0067] In the conventional system, the confirmation of payment history patterns and the decision on delinquency based on the payer's attribute information were done manually, which took a lot of time and cost.In addition, there was also the problem that it was difficult to automatically determine preferential treatment for employees of listed companies, which made it prone to errors.

[0068] 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.

[0069] In this invention, the server includes a means for inputting payer information and saving payer attribute information, a means for inputting payment dates and recording payment histories, a means for evaluating the regularity of the recorded payment histories based on the interval between payment dates, a means for determining whether to omit delinquency screening based on the regularity of the payment history and the payer attribute information, and a notification means, thereby enabling the automation and efficiency of delinquency screening.

[0070] "Payer Information" means basic data about the person or entity making a payment for a service or product, including name, address, contact details, occupation, and company affiliation.

[0071] "Payer attribute information" refers to information that describes the payer's personal or professional characteristics or attributes, including, for example, occupation, company affiliation, income level, credit information, etc.

[0072] "Payment Date" means the date on which payment is made for a particular service or product.

[0073] "Payment History" means a record of each payment made by a Payer, including the date of each payment.

[0074] "Regularity" refers to consistency or patterns in data or events, in this case assessing whether payment intervals fall within a certain range.

[0075] "Evaluating the regularity of the payment history" means calculating the interval between payment dates from the accumulated payment history and determining whether the interval falls within a predetermined range.

[0076] "Delinquent payment review" is the process of evaluating the reasons for the late payment and the payer's credit standing when a payer fails to make a payment on time, and determining the next steps to take.

[0077] "Notification" refers to the act of informing other devices or individuals of information about a particular event or result, and in this context refers to the transmission of information from the server to the user.

[0078] The present invention is a system that manages payment history and attribute information of payers and automates delinquent payment screening. This system operates through the exchange of data between a server, a terminal, and a user. The following describes an embodiment of the present invention.

[0079] Payer Registration

[0080] First, the user inputs the payer's information. Using a terminal, the user inputs the payer's attribute information, such as their name, occupation, and the company they work for. The terminal temporarily stores this information in its memory and then sends it to the server. The server stores the received information in a database. Through this process, the payer is registered in the system.

[0081] Examples:

[0082] The user enters payer information such as name "Ichiro Tanaka," company "XYZ Corporation," and occupation "engineer," and sends it from the terminal to the server, which then stores it in a database.

[0083] Recording payments

[0084] Next, when the user makes a payment, he or she inputs the payment date. The user inputs the payment date using the terminal, which temporarily stores it and sends it to the server. The server stores the received payment date in a database and records it as payment history.

[0085] Examples:

[0086] The user enters "January 1, 2023" as the payment date, sends it from the terminal to the server, and the server saves it in the database.

[0087] Checking regular payments

[0088] The server analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if payments were made on January 1st, April 1st, and July 1st, the server evaluates whether the interval between each payment is regular.

[0089] Examples:

[0090] If a payer makes payments on January 1st, April 1st, and July 1st, the server evaluates the intervals as 90 days regular.

[0091] Delinquent payment review decision

[0092] The server determines whether to exempt the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a specific company, the server will omit the delinquency screening. The result is notified to the user via the terminal.

[0093] Examples:

[0094] The server evaluates the regularity of the payments, and if it is confirmed that the payer is an employee of a specific company, it notifies the user that the delinquency screening will be waived.

[0095] Example prompts to input to the generative AI model

[0096] Below is an example of a prompt sentence to input to the generative AI model.

[0097] Example prompt:

[0098] "Write a program for a system that manages user payment history and attribute information. It takes as input the payer's name, attribute information (such as occupation and company), and multiple payment dates, evaluates whether the payment interval is between 85 and 95 days, and outputs the result. It also checks whether the payer is an employee of a specific company and determines whether to exempt them from delinquency screening."

[0099] This invention realizes automation and efficiency of delinquent payment screening based on payment history regularity and attribute information, which enables significant reductions in time and cost compared to conventional manual screening.

[0100] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0101] Step 1: Enter payer information

[0102] The "user" opens the payer registration screen and enters information such as the payer's name, occupation, and company. The input data may include information such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation." The "terminal" temporarily stores this input data in its memory.

[0103] Step 2: Submit payer information

[0104] The terminal sends the temporarily saved payer information to the server. The data sent includes attribute information such as name, occupation, and company affiliation.

[0105] Step 3: Save payer information

[0106] The "server" stores the received payer information in a database. For example, entries such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation" are added to the database.

[0107] Step 4: Enter payment date

[0108] The "user" opens the payment screen and enters the payment date. For example, they enter "January 1, 2023." The "terminal" temporarily stores this payment date in its memory.

[0109] Step 5: Submit payment date information

[0110] The "terminal" transmits the temporarily stored payment date information to the "server." The transmitted data includes the payment date information.

[0111] Step 6: Save the payment date

[0112] The "server" saves the received payment date information in the database and records it as payment history. For example, a record of "January 1, 2023" is added to the payment history of "Ichiro Tanaka."

[0113] Step 7: Get your payment history

[0114] The "server" retrieves the accumulated payment history from the database. For example, it retrieves the past payment history of "Ichiro Tanaka" such as "January 1, 2023," "April 1, 2023," and "July 1, 2023."

[0115] Step 8: Calculate payment intervals

[0116] Based on the payment history obtained by the "server," the interval between each payment date is calculated. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[0117] Step 9: Evaluate regularities

[0118] The server evaluates whether the intervals between payment dates calculated by the server are within a predetermined range (for example, 85 to 95 days). For example, the payment dates of January 1st, April 1st, and July 1st are all 90 days apart, so they are evaluated as regular.

[0119] Step 10: Verify payer demographics

[0120] The server retrieves the payer's attribute information from the database again and includes it in the verification. For example, it verifies that "Ichiro Tanaka" is an employee of "XYZ Corporation."

[0121] Step 11: Delinquency Review Judgment

[0122] The server determines whether to exempt the payment from the delinquency review based on the payment history regularity and the payer's attribute information. For example, since "Ichiro Tanaka" pays regularly and is an employee of a specific company, the server determines that he should be exempt from the delinquency review.

[0123] Step 12: Notification of results

[0124] The "server" sends the results of the delinquency review to the "terminal." The "terminal" displays the results to the "user." For example, it displays "Delinquency review has been exempted."

[0125] This series of steps enables automatic and efficient delinquency screening based on the regularity of the payer's payment history and attribute information.

[0126] (Application example 1)

[0127] 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."

[0128] Conventional electronic payment systems have the problem that they do not efficiently screen users for delinquency, resulting in cumbersome procedures and a heavy burden on users. Furthermore, they uniformly screen users who make regular payments or have a high credit rating, which is inconvenient for these users as well. This reduces the efficiency of the entire payment process and causes stress for system users.

[0129] 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.

[0130] In this invention, the server includes a means for recording payment histories, a means for evaluating the regularity of the recorded payment histories, and a means for saving and querying the attribute information of the payer. This makes it possible to efficiently perform delinquency screening based on the regularity of the payment histories and the attribute information of the payer, and to quickly execute electronic payments for particularly reliable users.

[0131] "Payment history" is a record of payments made by a user in the past.

[0132] The "means for assessing the regularity of recorded payment history" is a mechanism for analyzing the intervals and patterns of payments within a certain period of time and assessing the regularity of payment behavior.

[0133] "Payer attribute information" is information that indicates individual characteristics such as the user's occupation, the company where the user is located, and whether or not the company is listed on the stock exchange.

[0134] "Means for storage and inquiry" refers to a system that safely stores recorded data and allows that data to be searched and retrieved as needed.

[0135] "Delinquent payment screening" is a process of assessing the user's reliability by checking whether the user is making payments on time and whether there have been any past defaults in payments in the past.

[0136] The "means for determining whether to skip the delinquency review" is a mechanism for determining whether or not a delinquency review needs to be conducted on a user based on the regularity of the payment history and the payer's attribute information.

[0137] "Electronic payments" refers to the transfer of funds or transactions that users make over the Internet.

[0138] "Quick execution means" refers to a mechanism that allows payment processing to be completed in a short time, enabling users to use the service without waiting.

[0139] As a specific embodiment of the present invention, a system for managing a user's payment history and attribute information and for promptly reviewing delinquency based on the information will be described. This system is realized using the following hardware and software.

[0140] Hardware and Software Configuration

[0141] Server: Contains the central database and analysis functions for this system. It stores payment history and payer attribute information and performs delinquent payment screening.

[0142] Terminal: The device where the user enters payment information and sees the results. This could be a smartphone, tablet, or PC.

[0143] Database: Use a database management system (DBMS) such as SQLite to store payment history and payer attribute information.

[0144] Analysis module: Analyzes payment history for regularities and attribute information using algorithms implemented in programming languages ​​such as Python.

[0145] Front-end technologies: HTML, CSS, JavaScript, and other technologies for building user interfaces. The Flask framework can also be used to build web applications.

[0146] System Operation

[0147] 1. User Registration:

[0148] The user enters the payer information (name, occupation, company affiliation, etc.) on the terminal.

[0149] The server receives this and stores it in a database.

[0150] The server also stores attributes such as whether the company is listed or not.

[0151] 2. Payment History Record:

[0152] The user inputs information such as the payment date and payment amount from the terminal.

[0153] This information is temporarily stored on the device and then sent to the server.

[0154] The server receives this and stores it in a database.

[0155] 3. Regular payment confirmation:

[0156] The server analyzes the payment history in the database.

[0157] The interval between payment dates is calculated and evaluated to see if it falls within a preset range.

[0158] 4. Delinquency Review Judgment:

[0159] The server then performs a delinquent payment review based on the analyzed payment history regularity and the payer's attribute information.

[0160] If regular payments are confirmed or the payer is affiliated with a listed company, the delinquency review will be waived.

[0161] The result of this determination is sent to the terminal and notified to the user.

[0162] 5. Faster electronic payment execution:

[0163] The server issues instructions to the user who has been determined to be omitted to quickly execute electronic payment.

[0164] Specific examples

[0165] For example, suppose a payer is registered in the system as a "sales representative" belonging to a publicly listed company. If this payer makes payments on January 1st, April 1st, and July 1st, the server records each payment date in the database and checks the regularity of the payments. It verifies that the payment intervals are approximately every three months (85 to 95 days). Furthermore, because the payer belongs to a publicly listed company, the server notifies the user by displaying a message on the terminal that the payer is exempt from delinquency screening.

[0166] Generative AI model prompt example

[0167] Register the user "Salesperson" as an employee of a listed company

[0168] The server checks the payment history and determines whether payments are being made regularly.

[0169] Analyze payment records to assess whether delinquency screening is necessary

[0170] If exempt, notify the user of the exemption result

[0171] This system will significantly streamline the electronic payment process and enable faster service delivery to users.

[0172] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0173] Step 1:

[0174] The user registers the payer information.

[0175] Input: The user enters information such as name, occupation, and company affiliation into the device.

[0176] The server receives the input information and stores it in a database. At this time, JSON format data is sent as input data.

[0177] Data processing: The server converts the received information into an appropriate format and generates an insert query to the database.

[0178] Output: The user information is saved in the database and a message indicating registration is complete is returned to the terminal.

[0179] Step 2:

[0180] The user enters payment date information.

[0181] Input: The user enters information such as payment date and payment amount into the terminal.

[0182] The terminal sends the entered payment information to the server, along with information such as the payment date and amount in JSON format.

[0183] Data processing: The server analyzes the received payment information and generates a query to store it in the database as a payment record.

[0184] Output: The server saves the payment information in the database and sends a message to the terminal indicating that the payment has been recorded.

[0185] Step 3:

[0186] The server evaluates whether the payment is regular.

[0187] Input: Payment history information for a specific user in the database.

[0188] The server retrieves payment information associated with the specific user ID from the database.

[0189] Data calculation: The acquired payment date information is sorted in chronological order, and each payment interval is calculated. This evaluates whether the payment interval is within a set range (for example, 85 to 95 days).

[0190] Output: A decision is made on the server as to whether the payment is regular or not.

[0191] Step 4:

[0192] The server determines whether or not a delinquent payment review is necessary.

[0193] Input: Regular payment evaluation results and payer attribute information.

[0194] The server queries the database for the evaluation results of regular payments and whether the payer belongs to a listed company, and makes a comprehensive judgment.

[0195] Data calculation: Comprehensively analyzes payment history patterns and attribute information to determine whether or not a delinquency review is applicable.

[0196] Output: A decision is made as to whether a delinquency review is required or exempt.

[0197] Step 5:

[0198] The server notifies the terminal of the determination result.

[0199] Input: Decision result of delinquency review.

[0200] The server sends the result of the judgment to the terminal in JSON format.

[0201] Output: The user can check the result on the terminal. If exemption is granted, a notification will be displayed stating that the delinquency review has been exempted.

[0202] Step 6:

[0203] The server performs the fast electronic payment.

[0204] Input: Payment information for users who are exempt from delinquency screening.

[0205] The server verifies the payment information of the user who has been exempted from delinquency screening and generates instructions for electronic payment.

[0206] Data processing: The server calls the payment processing API and performs the procedures to quickly execute the electronic payment.

[0207] Output: If the electronic payment is successful, the result is notified to the terminal.

[0208] This series of processes allows users to make electronic payments quickly and efficiently, reduces the workload of overdue payments screening, and improves overall system performance.

[0209] 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.

[0210] As an embodiment of the present invention, a system that manages payment history and payer attribute information and further combines it with an emotion engine that recognizes user emotions will be described.

[0211] Payer Registration

[0212] The "user" inputs the payer's information, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database. In particular, if the payer is an employee of a listed company, that information is also stored in detail.

[0213] Recording payments

[0214] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[0215] Checking regular payments

[0216] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks the regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval falls within a certain range.

[0217] Emotion recognition by emotion engine

[0218] The "terminal" collects voice and facial expression data and sends it to the emotion engine. The "server" analyzes the received data and recognizes the user's emotions. For example, it analyzes whether the user is feeling stressed when making a payment.

[0219] Adjusting ratings based on emotions

[0220] The server then adjusts the evaluation of the user's payment history based on the perceived emotion. For example, if the user is stressed but still paying regularly, the server may adjust the evaluation to waive the overdue payment review to reflect that effort.

[0221] Delinquent payment review decision

[0222] The "server" determines whether to exempt the delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the delinquency screening is omitted. If this result is reached, the "server" sends the result to the "terminal."

[0223] Screen display and user notification

[0224] The "terminal" receives the judgment result from the "server" and displays it to the "user." For example, if the delinquency examination is omitted, the "user" is notified of this.

[0225] Specific examples

[0226] For example, suppose a "user" payer is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information, checks the regularity of the payments, and confirms that the payer is an employee of the listed company. Furthermore, the emotion engine analyzes Yamada Taro's voice data and facial expression data acquired by the "terminal" to recognize emotions such as stress.

[0227] The "server" decides whether to exempt the overdue payment review based on payment history, attribute information, and recognized emotions. The result is then displayed on the "terminal" and notified to the "user." As a result, if Yamada Taro is exempted from the overdue payment review, Yamada Taro can plan his next actions with peace of mind.

[0228] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on payment history patterns, payer attribute information, and user sentiment. This system significantly reduces time and costs compared to conventional methods, and reduces the burden on users.

[0229] The processing flow will be explained below.

[0230] Step 1:

[0231] The "user" enters payer information (name and attribute information) into the system. The "terminal" receives the information and sends it to the "server." The "server" saves the received payer information in a database. For example, it registers that the payer is Yamada Taro, who works for a listed company.

[0232] Step 2:

[0233] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, saves it in a database, and updates the payment history. For example, payments made on January 1st, April 1st, and July 1st are recorded.

[0234] Step 3:

[0235] The "server" analyzes the accumulated payment history, calculating the interval between each payment date and checking whether it is between 85 and 95 days. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[0236] Step 4:

[0237] The "server" evaluates the regularity of the recorded payment history. The "server" checks that the interval between each payment date is within a certain range and determines that the payment is regular. The result is stored in the database.

[0238] Step 5:

[0239] The server retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. This information is also saved as the evaluation result.

[0240] Step 6:

[0241] When a "user" makes a payment, the "terminal" transmits the user's voice and facial expressions to the emotion engine. The "server" receives this and uses the emotion engine to analyze the user's emotional state. For example, it evaluates whether the "user" is feeling stressed or relieved.

[0242] Step 7:

[0243] The Server adjusts the evaluation of the payment history based on the emotions recognized by the emotion engine, for example, if the User is stressed but still makes payments regularly, it takes into account their efforts.

[0244] Step 8:

[0245] The server determines whether to exempt the payment from the delinquency check based on the payment history regularity, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the payment from the delinquency check is omitted.

[0246] Step 9:

[0247] The "server" sends the result of the delinquency review to the "terminal." The "terminal" receives the result and notifies the "user." For example, it displays a message that the delinquency review has been waived.

[0248] Step 10:

[0249] The user checks the results. If the overdue payment screening is waived, the user can make their next payment plan and live their life with peace of mind.

[0250] As described above, the system of the present invention can efficiently conduct delinquency screening based on the regularity of payment history, the payer's attribute information, and the user's emotional state, thereby reducing the burden on the user.

[0251] Example 2

[0252] 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."

[0253] Conventional payment history management systems screen for delinquency based on payment history and payer attribute information, but do not consider the user's emotions. As a result, they often ignore the anxiety and stress users feel about payments, and a more human-like approach is needed. Furthermore, evaluating patterns and checking attribute information requires a lot of time and effort, making them inefficient. A new system that solves these issues is needed.

[0254] 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.

[0255] In this invention, the server includes a means for recording payment history, a means for evaluating the regularity of the recorded payment history, a means for saving and referencing the attributes of the payer, a means for recognizing the user's emotions, and a means for determining whether to skip the delinquency review based on the regularity of the payment history, the attributes of the payer, and the user's emotions. This enables a more humane and efficient delinquency review that takes into account the user's emotions in addition to the regularity of the payment history and the attribute information of the payer.

[0256] A "payment history" is a detailed record of the series of payments made by a user.

[0257] The "recording means" is a technique or device for storing the user's payment history in a storage device such as a database.

[0258] A "means for assessing regularity" is a technique or device that analyzes time intervals in recorded payment history and determines regularity based on certain patterns.

[0259] "Payer attributes" refers to basic information and details about the payer, including, for example, occupation and company affiliation.

[0260] "Means for storing and querying" refers to technology or equipment that can store payer attribute information in a database or the like and retrieve that information as needed.

[0261] "User emotions" refer to the psychological state or feeling a user has regarding a payment, and include, for example, stress or relief.

[0262] The "recognition means" refers to a technology or device for analyzing the user's voice and facial expression data and identifying their emotions.

[0263] "Delinquency screening" is the process of determining whether payments are likely to be delinquent based on the regularity of payment history and the attributes of the payer.

[0264] The "means for determining" is a technology or device that comprehensively evaluates the regularity of the payment history, the attributes of the payer, and the user's emotions, and determines whether or not to conduct a delinquency review.

[0265] The system of the present invention is designed to manage payment history and review delinquency efficiently and humanly. This system is composed of the following main components:

[0266] 1. A way to record payment history

[0267] This means records information about payments made by users (such as payment date and amount) and stores it in a database. Specifically, the payment information entered into the terminal is sent to a server, which then stores it in a database.

[0268] 2. A means of assessing the regularity of recorded payment history

[0269] This method analyzes the recorded payment history and evaluates the regularity of payments. Specifically, the server calculates the interval between each payment date and checks whether the interval falls within a certain range.

[0270] 3. Means for storing and querying payer attributes

[0271] This method stores basic information about the payer (e.g., company affiliation, occupation, etc.) in a database, making it possible to retrieve that information as needed. The attribute information entered by the terminal is sent to the server, which then stores it.

[0272] 4. How to Recognize User Emotions

[0273] This method captures and analyzes data such as voice and facial expressions to recognize the emotions the user feels when making a payment. For example, a camera or microphone installed on the terminal captures the user's voice and facial expressions and sends them to the emotion engine.

[0274] 5. How to determine whether to waive delinquency screening

[0275] This means determines whether to waive the overdue payment review based on the regularity of the payment history, the payer's attributes, and the user's sentiment. Specifically, the server comprehensively evaluates this information and decides whether to waive the overdue payment review.

[0276] Specific examples

[0277] For example, a user enters the payer information as "Yamada Taro" who belongs to "ABC Co., Ltd." Suppose Yamada Taro makes payments on January 1st, April 1st, and July 1st. This information is sent from the device to the server and stored in a database. The server verifies that the payment dates are three months apart. The device also acquires Yamada Taro's facial expressions and voice, and the emotion engine recognizes stress. Based on this information, the server decides to exempt Yamada Taro from the overdue payment screening because he makes payments regularly. This allows Yamada Taro to plan his next actions with peace of mind.

[0278] Prompt Sentence Examples

[0279] A prompt that explains, "A system in which users register their payer information and then screen for delinquent payments based on their payment history and sentiment":

[0280] Design a system that registers payer information and performs delinquent payment screening based on payment history and sentiment. Please provide a description including the names of specific hardware and software, and the process flow.

[0281] With the above configuration, the present invention makes it possible to realize a more humane and efficient delinquency screening process that takes into account the user's emotions in addition to the regularity of payment history and the payer's attribute information.

[0282] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0283] Step 1:

[0284] Enter and submit payer information

[0285] The user inputs the payer information, including name, address, company, occupation, etc., and this information is entered into the terminal.

[0286] Input: Payer information (name, address, company, occupation, etc.)

[0287] How it works: The device receives this information and checks its consistency.

[0288] Output: The verified payer information is sent to the server.

[0289] Step 2:

[0290] Payer information storage

[0291] The server receives the payer information sent from the terminal and stores it in a database.

[0292] Input: Validated payer information

[0293] Operation: The server confirms receipt of the data and records it in a database. It also registers whether the person is an employee of a publicly listed company.

[0294] Output: Payer information stored in the database

[0295] Step 3:

[0296] Enter and submit payment date information

[0297] When a user makes a payment, the user inputs the payment date.

[0298] Input: Payment information (payment date, amount, etc.)

[0299] How it works: The device temporarily stores the payment date information, checks to make sure the data is not lost, and then sends it to the server.

[0300] Output: Payment date information sent to the server

[0301] Step 4:

[0302] Save payment date information and update history

[0303] The server receives the payment date information, stores it in a database, and updates the payment history.

[0304] Input: Payment date information

[0305] Operation: The server adds the received payment date information to the database and updates the accumulated payment history.

[0306] Output: Updated payment history

[0307] Step 5:

[0308] Evaluating payment history regularity

[0309] The server analyzes the accumulated payment history and calculates the interval between payment dates to verify payment regularity.

[0310] Input: Updated payment history

[0311] How it works: The server calculates the time interval between each payment date and evaluates whether it falls within a certain range. For example, if payments are made on January 1st, April 1st, and July 1st, it verifies that the interval between each payment is approximately 3 months.

[0312] Output: Regularity evaluation result

[0313] Step 6:

[0314] Acquiring and analyzing emotion data

[0315] The device acquires emotional data such as the user's voice and facial expressions and sends it to the server, which then uses an emotion engine to recognize the user's emotions.

[0316] Input: User voice and facial expression data

[0317] How it works: The device collects this data and sends it to a server, which uses an emotion engine to analyze emotions and recognize feelings such as stress or relief.

[0318] Output: Recognized user emotion data

[0319] Step 7:

[0320] Adjusting ratings based on emotions

[0321] The server adjusts the evaluation of the payment history based on the recognized emotion. For example, if a user is stressed but still makes regular payments, the server will evaluate their efforts and ease the screening process for delinquency.

[0322] Input: Regularity evaluation results, recognized user emotion data

[0323] How it works: The server aggregates this data and adjusts the ratings to take into account payment regularity and emotional influence.

[0324] Output: Adjusted evaluation results

[0325] Step 8:

[0326] Final decision on delinquency review

[0327] The server performs a delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion, and determines whether to exempt the screening.

[0328] Input: Adjusted assessment results, payer attribute information

[0329] Action: Conduct a final delinquency review and determine the outcome.

[0330] Output: Final result of delinquency review

[0331] Step 9:

[0332] Displaying and notifying results

[0333] The terminal receives the result of the delinquency examination from the server and notifies the user.

[0334] Input: Final result of delinquency review

[0335] Behavior: The result is displayed to the user in an easy-to-understand manner. For example, a specific message such as "Your delinquent payment has been waived" is displayed.

[0336] Output: The result displayed to the user

[0337] The above processing steps realize efficient and human-like delinquency screening that takes into account the user's emotions and payment history.

[0338] (Application example 2)

[0339] 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."

[0340] Conventional payment management systems perform delinquency screening based solely on payment history and payer attribute information, and are therefore unable to take into account the stress and anxiety felt by users. This makes accurate screening difficult, and alleviating users' psychological burden has been an issue.

[0341] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recording payment history, means for evaluating the regularity of the recorded payment history, means for saving and referencing the payer's attribute information, emotion engine means for analyzing the acquired emotion data, means for determining whether to skip the delinquency review based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data, and means for notifying the user of the result of the delinquency review. This enables more accurate delinquency review that takes into account not only the payment history and attribute information but also the user's emotions.

[0342] A "payment history recording means" is a system or device that digitally stores information about each payment made by a user.

[0343] The "means for evaluating the regularity of the recorded payment history" is a system or device that extracts patterns of payment dates and payment intervals from the stored payment history and analyzes the regularity of those patterns.

[0344] "Means for storing and querying payer attribute information" refers to a system or device that stores data such as the payer's personal information, occupation, and company affiliation in a database and can retrieve that information as needed.

[0345] The "emotion engine means for analyzing acquired emotion data" is a system or device that analyzes data such as the user's voice and facial expression, and identifies the emotional state at that time.

[0346] The "means for determining whether to skip the delinquency review" is a system or device that determines whether or not a delinquency review needs to be conducted based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data.

[0347] The "means for notifying the user of the results of the delinquency review" refers to a system or device that receives the results of the review from the server and displays or notifies the results on the user's terminal.

[0348] To implement this invention, a server, a terminal, and a series of operations by the user are required. This system is realized using the following hardware and software.

[0349] Hardware

[0350] 1. Device:

[0351] Smartphones (e.g. iPhone(R), ANDROID(R))

[0352] Devices with a camera and microphone

[0353] 2. Server:

[0354] Cloud servers (e.g., AWS (registered trademark), Google (registered trademark) Cloud) and on-premise servers

[0355] software

[0356] 1. Smartphone app:

[0357] Applications that input and record payment information and collect emotional data

[0358] Speech and facial recognition software (e.g., Amazon Rekognition, Google Cloud Speech-to-Text)

[0359] 2. Server-side software:

[0360] Database management systems (e.g., MySQL, PostgreSQL)

[0361] Analysis Engine

[0362] Notification System

[0363] Data processing and calculation

[0364] 1. Payment History Record:

[0365] When a user enters payment information (date, amount, etc.) through a smartphone app, the app saves this information and sends it to a server, which then stores the received payment information in a database.

[0366] 2. Payment Regularity Assessment:

[0367] The server analyzes the payment history stored in the database and evaluates its regularity by calculating the interval between payment dates, which allows for the identification of payment patterns.

[0368] 3. Acquiring and analyzing emotion data:

[0369] The device's camera and microphone are used to capture the user's voice and facial expression data, which are then sent to the emotion engine, which determines whether the user is feeling stressed and sends the result to the server.

[0370] 4. Delinquency Review Judgment:

[0371] The server determines whether a delinquent payment review is necessary based on the regularity of the payment history, the payer's attribute information (e.g., type of workplace), and emotional data. The server notifies the smartphone app of the result of this determination and displays the result to the user.

[0372] Adding specific examples

[0373] For example, suppose a user enters payment information, including voice data, into the app on July 1st. The app sends the collected voice and payment information to the server. The server compares the user's past payment history and evaluates the payment interval. At the same time, the emotion engine analyzes the voice data and detects that the user is feeling stressed. Based on this information, the server decides to skip the overdue payment review and notifies the user of the result.

[0374] Prompt Sentence Examples

[0375] "Please develop a system that analyzes users' payment history and emotional data through a smartphone app and automatically exempts them from overdue payments. The emotional data includes facial expressions and voice data."

[0376] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0377] Step 1:

[0378] A user inputs payment information using a smartphone app. This input information includes payment date, amount, payee, etc. The terminal temporarily stores this input data and sends it to the server. The date and amount are sent as input data, and the server stores them in a database as data processing. The output is a payment record stored in the database.

[0379] Step 2:

[0380] The terminal captures voice and facial expression data. While the user is entering payment information, the camera and microphone are activated to collect the user's facial expression data and voice data. The voice and facial expression data captured as input data is sent to the emotion engine, where emotion analysis is performed as data calculation. The output is the user's emotional state.

[0381] Step 3:

[0382] The server evaluates the regularity of the payment history. It analyzes the payment history stored in the database and calculates the interval between payment dates. The timestamp of each payment date is used as input data, and the calculation of the time interval is performed as data processing. The output is the result of the payment regularity evaluation.

[0383] Step 4:

[0384] The server queries the payer's attribute information. It retrieves the payer's attribute information stored in the database and checks the user's occupation, company affiliation, etc. The payer ID is used as input data, and attribute information is extracted as data processing. The output is the payer's attribute information.

[0385] Step 5:

[0386] The server combines all the information and makes a decision on whether or not to conduct a delinquent payment review. It decides whether or not to conduct a delinquent payment review based on the results of the regularity evaluation of the payment history, the payer's attribute information, and emotional data. The regularity evaluation results, attribute information, and emotional state are used as input data, and conditional judgments are performed as data calculations. The output is the decision on whether or not to conduct a delinquent payment review.

[0387] Step 6:

[0388] The user is notified of the results of the delinquency review. The server sends the results of the delinquency review to the terminal, which then displays the results to the user. The results of the delinquency review are used as input data, and notification data is generated as data processing. The output is notification information displayed to the user.

[0389] 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.

[0390] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (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.

[0391] 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.

[0392] [Second embodiment]

[0393] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0394] 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.

[0395] 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).

[0396] 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.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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."

[0405] As an embodiment of the present invention, a system for managing payment history and attribute information of a payer will be described first.

[0406] Payer Registration

[0407] The "user" enters the payer's information. The payer's name and attribute information (such as occupation and company) are also registered, and the "server" stores this information in a database. In particular, if the payer is an employee of a listed company, that information is also stored.

[0408] Recording payments

[0409] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" saves the received payment date in a database and records it as payment history.

[0410] Checking regular payments

[0411] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if a payer makes payments on January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval is within the range of 85 to 95 days.

[0412] Delinquent payment review decision

[0413] The "Server" determines whether to exempt the "User" from the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a listed company, the "Server" will omit the delinquency screening. In this case, the system notifies the "User" via the "Terminal" that the "User" does not need to undergo the delinquency screening.

[0414] Specific examples

[0415] For example, suppose a payer, who is a "user," is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information and checks the regularity of the payments. As a result, it is confirmed that "Yamada Taro" makes payments regularly every three months. The "server" also confirms that "Yamada Taro" is an employee of a listed company. As a result, the "server" displays on the "terminal" that the delinquency review will be omitted, and notifies the "user."

[0416] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on the regularity of payment history and payer attribute information. This system can significantly reduce time and costs compared to conventional methods.

[0417] The processing flow will be explained below.

[0418] Step 1:

[0419] The "user" enters payer information (name and attribute information) into the system, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database.

[0420] Step 2:

[0421] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[0422] Step 3:

[0423] The "server" retrieves the payment history from the database and calculates the intervals between payment dates to check for regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date (in this case, each interval is approximately 90 days).

[0424] Step 4:

[0425] The Server evaluates the payment history for regularity, and if it determines that the payments are regular, it stores that result, as well as if they are not regular.

[0426] Step 5:

[0427] The "server" retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. If the payer belongs to a listed company based on the attribute information, the result is also saved.

[0428] Step 6:

[0429] The "server" determines whether to skip the delinquency check based on the evaluation results of regular payments and the evaluation results of the payer's attribute information. If either one is true, the delinquency check is skipped.

[0430] Step 7:

[0431] The "server" sends the results of the delinquency review to the "terminal." The "terminal" receives the results and notifies the "user." For example, if the delinquency review is omitted, the "user" displays a message indicating that the delinquency review is not required.

[0432] Step 8:

[0433] The "user" reviews the results and decides on the next action if necessary, such as creating a new payment plan.

[0434] Example 1

[0435] 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."

[0436] In the conventional system, the confirmation of payment history patterns and the decision on delinquency based on the payer's attribute information were done manually, which took a lot of time and cost.In addition, there was also the problem that it was difficult to automatically determine preferential treatment for employees of listed companies, which made it prone to errors.

[0437] 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.

[0438] In this invention, the server includes a means for inputting payer information and saving payer attribute information, a means for inputting payment dates and recording payment histories, a means for evaluating the regularity of the recorded payment histories based on the interval between payment dates, a means for determining whether to omit delinquency screening based on the regularity of the payment history and the payer attribute information, and a notification means, thereby enabling the automation and efficiency of delinquency screening.

[0439] "Payer Information" means basic data about the person or entity making a payment for a service or product, including name, address, contact details, occupation, and company affiliation.

[0440] "Payer attribute information" refers to information that describes the payer's personal or professional characteristics or attributes, including, for example, occupation, company affiliation, income level, credit information, etc.

[0441] "Payment Date" means the date on which payment is made for a particular service or product.

[0442] "Payment History" means a record of each payment made by a Payer, including the date of each payment.

[0443] "Regularity" refers to consistency or patterns in data or events, in this case assessing whether payment intervals fall within a certain range.

[0444] "Evaluating the regularity of the payment history" means calculating the interval between payment dates from the accumulated payment history and determining whether the interval falls within a predetermined range.

[0445] "Delinquent payment review" is the process of evaluating the reasons for the late payment and the payer's credit standing when a payer fails to make a payment on time, and determining the next steps to take.

[0446] "Notification" refers to the act of informing other devices or individuals of information about a particular event or result, and in this context refers to the transmission of information from the server to the user.

[0447] The present invention is a system that manages payment history and attribute information of payers and automates delinquent payment screening. This system operates through the exchange of data between a server, a terminal, and a user. The following describes an embodiment of the present invention.

[0448] Payer Registration

[0449] First, the user inputs the payer's information. Using a terminal, the user inputs the payer's attribute information, such as their name, occupation, and the company they work for. The terminal temporarily stores this information in its memory and then sends it to the server. The server stores the received information in a database. Through this process, the payer is registered in the system.

[0450] Examples:

[0451] The user enters payer information such as name "Ichiro Tanaka," company "XYZ Corporation," and occupation "engineer," and sends it from the terminal to the server, which then stores it in a database.

[0452] Recording payments

[0453] Next, when the user makes a payment, he or she inputs the payment date. The user inputs the payment date using the terminal, which temporarily stores it and sends it to the server. The server stores the received payment date in a database and records it as payment history.

[0454] Examples:

[0455] The user enters "January 1, 2023" as the payment date, sends it from the terminal to the server, and the server saves it in the database.

[0456] Checking regular payments

[0457] The server analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if payments were made on January 1st, April 1st, and July 1st, the server evaluates whether the interval between each payment is regular.

[0458] Examples:

[0459] If a payer makes payments on January 1st, April 1st, and July 1st, the server evaluates the intervals as 90 days regular.

[0460] Delinquent payment review decision

[0461] The server determines whether to exempt the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a specific company, the server will omit the delinquency screening. The result is notified to the user via the terminal.

[0462] Examples:

[0463] The server evaluates the regularity of the payments, and if it is confirmed that the payer is an employee of a specific company, it notifies the user that the delinquency screening will be waived.

[0464] Example prompts to input to the generative AI model

[0465] Below is an example of a prompt sentence to input to the generative AI model.

[0466] Example prompt:

[0467] "Write a program for a system that manages user payment history and attribute information. It takes as input the payer's name, attribute information (such as occupation and company), and multiple payment dates, evaluates whether the payment interval is between 85 and 95 days, and outputs the result. It also checks whether the payer is an employee of a specific company and determines whether to exempt them from delinquency screening."

[0468] This invention realizes automation and efficiency of delinquent payment screening based on payment history regularity and attribute information, which enables significant reductions in time and cost compared to conventional manual screening.

[0469] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0470] Step 1: Enter payer information

[0471] The "user" opens the payer registration screen and enters information such as the payer's name, occupation, and company. The input data may include information such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation." The "terminal" temporarily stores this input data in its memory.

[0472] Step 2: Submit payer information

[0473] The terminal sends the temporarily saved payer information to the server. The data sent includes attribute information such as name, occupation, and company affiliation.

[0474] Step 3: Save payer information

[0475] The "server" stores the received payer information in a database. For example, entries such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation" are added to the database.

[0476] Step 4: Enter payment date

[0477] The "user" opens the payment screen and enters the payment date. For example, they enter "January 1, 2023." The "terminal" temporarily stores this payment date in its memory.

[0478] Step 5: Submit payment date information

[0479] The "terminal" transmits the temporarily stored payment date information to the "server." The transmitted data includes the payment date information.

[0480] Step 6: Save the payment date

[0481] The "server" saves the received payment date information in the database and records it as payment history. For example, a record of "January 1, 2023" is added to the payment history of "Ichiro Tanaka."

[0482] Step 7: Get your payment history

[0483] The "server" retrieves the accumulated payment history from the database. For example, it retrieves the past payment history of "Ichiro Tanaka" such as "January 1, 2023," "April 1, 2023," and "July 1, 2023."

[0484] Step 8: Calculate payment intervals

[0485] Based on the payment history obtained by the "server," the interval between each payment date is calculated. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[0486] Step 9: Evaluate regularities

[0487] The server evaluates whether the intervals between payment dates calculated by the server are within a predetermined range (for example, 85 to 95 days). For example, the payment dates of January 1st, April 1st, and July 1st are all 90 days apart, so they are evaluated as regular.

[0488] Step 10: Verify payer demographics

[0489] The server retrieves the payer's attribute information from the database again and includes it in the verification. For example, it verifies that "Ichiro Tanaka" is an employee of "XYZ Corporation."

[0490] Step 11: Delinquency Review Judgment

[0491] The server determines whether to exempt the payment from the delinquency review based on the payment history regularity and the payer's attribute information. For example, since "Ichiro Tanaka" pays regularly and is an employee of a specific company, the server determines that he should be exempt from the delinquency review.

[0492] Step 12: Notification of results

[0493] The "server" sends the results of the delinquency review to the "terminal." The "terminal" displays the results to the "user." For example, it displays "Delinquency review has been exempted."

[0494] This series of steps enables automatic and efficient delinquency screening based on the regularity of the payer's payment history and attribute information.

[0495] (Application example 1)

[0496] 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."

[0497] Conventional electronic payment systems have the problem that they do not efficiently screen users for delinquency, resulting in cumbersome procedures and a heavy burden on users. Furthermore, they uniformly screen users who make regular payments or have a high credit rating, which is inconvenient for these users as well. This reduces the efficiency of the entire payment process and causes stress for system users.

[0498] 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.

[0499] In this invention, the server includes a means for recording payment histories, a means for evaluating the regularity of the recorded payment histories, and a means for saving and querying the attribute information of the payer. This makes it possible to efficiently perform delinquency screening based on the regularity of the payment histories and the attribute information of the payer, and to quickly execute electronic payments for particularly reliable users.

[0500] "Payment history" is a record of payments made by a user in the past.

[0501] The "means for assessing the regularity of recorded payment history" is a mechanism for analyzing the intervals and patterns of payments within a certain period of time and assessing the regularity of payment behavior.

[0502] "Payer attribute information" is information that indicates individual characteristics such as the user's occupation, the company where the user is located, and whether or not the company is listed on the stock exchange.

[0503] "Means for storage and inquiry" refers to a system that safely stores recorded data and allows that data to be searched and retrieved as needed.

[0504] "Delinquent payment screening" is a process of assessing the user's reliability by checking whether the user is making payments on time and whether there have been any past defaults in payments in the past.

[0505] The "means for determining whether to skip the delinquency review" is a mechanism for determining whether or not a delinquency review needs to be conducted on a user based on the regularity of the payment history and the payer's attribute information.

[0506] "Electronic payments" refers to the transfer of funds or transactions that users make over the Internet.

[0507] "Quick execution means" refers to a mechanism that allows payment processing to be completed in a short time, enabling users to use the service without waiting.

[0508] As a specific embodiment of the present invention, a system for managing a user's payment history and attribute information and for promptly reviewing delinquency based on the information will be described. This system is realized using the following hardware and software.

[0509] Hardware and Software Configuration

[0510] Server: Contains the central database and analysis functions for this system. It stores payment history and payer attribute information and performs delinquent payment screening.

[0511] Terminal: The device where the user enters payment information and sees the results. This could be a smartphone, tablet, or PC.

[0512] Database: Use a database management system (DBMS) such as SQLite to store payment history and payer attribute information.

[0513] Analysis module: Analyzes payment history for regularities and attribute information using algorithms implemented in programming languages ​​such as Python.

[0514] Front-end technologies: HTML, CSS, JavaScript, and other technologies for building user interfaces. You can also build web applications using the Flask framework.

[0515] System Operation

[0516] 1. User Registration:

[0517] The user enters the payer information (name, occupation, company affiliation, etc.) on the terminal.

[0518] The server receives this and stores it in a database.

[0519] The server also stores attributes such as whether the company is listed or not.

[0520] 2. Payment History Record:

[0521] The user inputs information such as the payment date and payment amount from the terminal.

[0522] This information is temporarily stored on the device and then sent to the server.

[0523] The server receives this and stores it in a database.

[0524] 3. Regular payment confirmation:

[0525] The server analyzes the payment history in the database.

[0526] The interval between payment dates is calculated and evaluated to see if it falls within a preset range.

[0527] 4. Delinquency Review Judgment:

[0528] The server then performs a delinquent payment review based on the analyzed payment history regularity and the payer's attribute information.

[0529] If regular payments are confirmed or the payer is affiliated with a listed company, the delinquency review will be waived.

[0530] The result of this determination is sent to the terminal and notified to the user.

[0531] 5. Faster electronic payment execution:

[0532] The server issues instructions to the user who has been determined to be omitted to quickly execute electronic payment.

[0533] Specific examples

[0534] For example, suppose a payer is registered in the system as a "sales representative" belonging to a publicly listed company. If this payer makes payments on January 1st, April 1st, and July 1st, the server records each payment date in the database and checks the regularity of the payments. It verifies that the payment intervals are approximately every three months (85 to 95 days). Furthermore, because the payer belongs to a publicly listed company, the server notifies the user by displaying a message on the terminal that the payer is exempt from delinquency screening.

[0535] Generative AI model prompt example

[0536] Register the user "Salesperson" as an employee of a listed company

[0537] The server checks the payment history and determines whether payments are being made regularly.

[0538] Analyze payment records to assess whether delinquency screening is necessary

[0539] If exempt, notify the user of the exemption result

[0540] This system will significantly streamline the electronic payment process and enable faster service delivery to users.

[0541] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0542] Step 1:

[0543] The user registers the payer information.

[0544] Input: The user enters information such as name, occupation, and company affiliation into the device.

[0545] The server receives the input information and stores it in a database. At this time, JSON format data is sent as input data.

[0546] Data processing: The server converts the received information into an appropriate format and generates an insert query to the database.

[0547] Output: The user information is saved in the database and a message indicating registration is complete is returned to the terminal.

[0548] Step 2:

[0549] The user enters payment date information.

[0550] Input: The user enters information such as payment date and payment amount into the terminal.

[0551] The terminal sends the entered payment information to the server, along with information such as the payment date and amount in JSON format.

[0552] Data processing: The server analyzes the received payment information and generates a query to store it in the database as a payment record.

[0553] Output: The server saves the payment information in the database and sends a message to the terminal indicating that the payment has been recorded.

[0554] Step 3:

[0555] The server evaluates whether the payment is regular.

[0556] Input: Payment history information for a specific user in the database.

[0557] The server retrieves payment information associated with the specific user ID from the database.

[0558] Data calculation: The acquired payment date information is sorted in chronological order, and each payment interval is calculated. This evaluates whether the payment interval is within a set range (for example, 85 to 95 days).

[0559] Output: A decision is made on the server as to whether the payment is regular or not.

[0560] Step 4:

[0561] The server determines whether or not a delinquent payment review is necessary.

[0562] Input: Regular payment evaluation results and payer attribute information.

[0563] The server queries the database for the evaluation results of regular payments and whether the payer belongs to a listed company, and makes a comprehensive judgment.

[0564] Data calculation: Comprehensively analyzes payment history patterns and attribute information to determine whether or not a delinquency review is applicable.

[0565] Output: A decision is made as to whether a delinquency review is required or exempt.

[0566] Step 5:

[0567] The server notifies the terminal of the determination result.

[0568] Input: Decision result of delinquency review.

[0569] The server sends the result of the judgment to the terminal in JSON format.

[0570] Output: The user can check the result on the terminal. If exemption is granted, a notification will be displayed stating that the delinquency review has been exempted.

[0571] Step 6:

[0572] The server performs the fast electronic payment.

[0573] Input: Payment information for users who are exempt from delinquency screening.

[0574] The server verifies the payment information of the user who has been exempted from delinquency screening and generates instructions for electronic payment.

[0575] Data processing: The server calls the payment processing API and performs the procedures to quickly execute the electronic payment.

[0576] Output: If the electronic payment is successful, the result is notified to the terminal.

[0577] This series of processes allows users to make electronic payments quickly and efficiently, reduces the workload of overdue payments screening, and improves overall system performance.

[0578] 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.

[0579] As an embodiment of the present invention, a system that manages payment history and payer attribute information and further combines it with an emotion engine that recognizes user emotions will be described.

[0580] Payer Registration

[0581] The "user" inputs the payer's information, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database. In particular, if the payer is an employee of a listed company, that information is also stored in detail.

[0582] Recording payments

[0583] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[0584] Checking regular payments

[0585] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks the regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval falls within a certain range.

[0586] Emotion recognition by emotion engine

[0587] The "terminal" collects voice and facial expression data and sends it to the emotion engine. The "server" analyzes the received data and recognizes the user's emotions. For example, it analyzes whether the user is feeling stressed when making a payment.

[0588] Adjusting ratings based on emotions

[0589] The server then adjusts the evaluation of the user's payment history based on the perceived emotion. For example, if the user is stressed but still paying regularly, the server may adjust the evaluation to waive the overdue payment review to reflect that effort.

[0590] Delinquent payment review decision

[0591] The "server" determines whether to exempt the delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the delinquency screening is omitted. If this result is reached, the "server" sends the result to the "terminal."

[0592] Screen display and user notification

[0593] The "terminal" receives the judgment result from the "server" and displays it to the "user." For example, if the delinquency examination is omitted, the "user" is notified of this.

[0594] Specific examples

[0595] For example, suppose a "user" payer is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information, checks the regularity of the payments, and confirms that the payer is an employee of the listed company. Furthermore, the emotion engine analyzes Yamada Taro's voice data and facial expression data acquired by the "terminal" to recognize emotions such as stress.

[0596] The "server" decides whether to exempt the overdue payment review based on payment history, attribute information, and recognized emotions. The result is then displayed on the "terminal" and notified to the "user." As a result, if Yamada Taro is exempted from the overdue payment review, Yamada Taro can plan his next actions with peace of mind.

[0597] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on payment history patterns, payer attribute information, and user sentiment. This system significantly reduces time and costs compared to conventional methods, and reduces the burden on users.

[0598] The processing flow will be explained below.

[0599] Step 1:

[0600] The "user" enters payer information (name and attribute information) into the system. The "terminal" receives the information and sends it to the "server." The "server" saves the received payer information in a database. For example, it registers that the payer is Yamada Taro, who works for a listed company.

[0601] Step 2:

[0602] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, saves it in a database, and updates the payment history. For example, payments made on January 1st, April 1st, and July 1st are recorded.

[0603] Step 3:

[0604] The "server" analyzes the accumulated payment history, calculating the interval between each payment date and checking whether it is between 85 and 95 days. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[0605] Step 4:

[0606] The "server" evaluates the regularity of the recorded payment history. The "server" checks that the interval between each payment date is within a certain range and determines that the payment is regular. The result is stored in the database.

[0607] Step 5:

[0608] The server retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. This information is also saved as the evaluation result.

[0609] Step 6:

[0610] When a "user" makes a payment, the "terminal" transmits the user's voice and facial expressions to the emotion engine. The "server" receives this and uses the emotion engine to analyze the user's emotional state. For example, it evaluates whether the "user" is feeling stressed or relieved.

[0611] Step 7:

[0612] The Server adjusts the evaluation of the payment history based on the emotions recognized by the emotion engine, for example, if the User is stressed but still makes payments regularly, it takes into account their efforts.

[0613] Step 8:

[0614] The server determines whether to exempt the payment from the delinquency check based on the payment history regularity, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the payment from the delinquency check is omitted.

[0615] Step 9:

[0616] The "server" sends the result of the delinquency review to the "terminal." The "terminal" receives the result and notifies the "user." For example, it displays a message that the delinquency review has been waived.

[0617] Step 10:

[0618] The user checks the results. If the overdue payment screening is waived, the user can make their next payment plan and live their life with peace of mind.

[0619] As described above, the system of the present invention can efficiently conduct delinquency screening based on the regularity of payment history, the payer's attribute information, and the user's emotional state, thereby reducing the burden on the user.

[0620] Example 2

[0621] 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."

[0622] Conventional payment history management systems screen for delinquency based on payment history and payer attribute information, but do not consider the user's emotions. As a result, they often ignore the anxiety and stress users feel about payments, and a more human-like approach is needed. Furthermore, evaluating patterns and checking attribute information requires a lot of time and effort, making them inefficient. A new system that solves these issues is needed.

[0623] 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.

[0624] In this invention, the server includes a means for recording payment history, a means for evaluating the regularity of the recorded payment history, a means for saving and referencing the attributes of the payer, a means for recognizing the user's emotions, and a means for determining whether to skip the delinquency review based on the regularity of the payment history, the attributes of the payer, and the user's emotions. This enables a more humane and efficient delinquency review that takes into account the user's emotions in addition to the regularity of the payment history and the attribute information of the payer.

[0625] A "payment history" is a detailed record of the series of payments made by a user.

[0626] The "recording means" is a technique or device for storing the user's payment history in a storage device such as a database.

[0627] A "means for assessing regularity" is a technique or device that analyzes time intervals in recorded payment history and determines regularity based on certain patterns.

[0628] "Payer attributes" refers to basic information and details about the payer, including, for example, occupation and company affiliation.

[0629] "Means for storing and querying" refers to technology or equipment that can store payer attribute information in a database or the like and retrieve that information as needed.

[0630] "User emotions" refer to the psychological state or feeling a user has regarding a payment, and include, for example, stress or relief.

[0631] The "recognition means" refers to a technology or device for analyzing the user's voice and facial expression data and identifying their emotions.

[0632] "Delinquency screening" is the process of determining whether payments are likely to be delinquent based on the regularity of payment history and the attributes of the payer.

[0633] The "means for determining" is a technology or device that comprehensively evaluates the regularity of the payment history, the attributes of the payer, and the user's emotions, and determines whether or not to conduct a delinquency review.

[0634] The system of the present invention is designed to manage payment history and review delinquency efficiently and humanly. This system is composed of the following main components:

[0635] 1. A way to record payment history

[0636] This means records information about payments made by users (such as payment date and amount) and stores it in a database. Specifically, the payment information entered into the terminal is sent to a server, which then stores it in a database.

[0637] 2. A means of assessing the regularity of recorded payment history

[0638] This method analyzes the recorded payment history and evaluates the regularity of payments. Specifically, the server calculates the interval between each payment date and checks whether the interval falls within a certain range.

[0639] 3. Means for storing and querying payer attributes

[0640] This method stores basic information about the payer (e.g., company affiliation, occupation, etc.) in a database, making it possible to retrieve that information as needed. The attribute information entered by the terminal is sent to the server, which then stores it.

[0641] 4. How to Recognize User Emotions

[0642] This method captures and analyzes data such as voice and facial expressions to recognize the emotions the user feels when making a payment. For example, a camera or microphone installed on the terminal captures the user's voice and facial expressions and sends them to the emotion engine.

[0643] 5. How to determine whether to waive delinquency screening

[0644] This means determines whether to waive the overdue payment review based on the regularity of the payment history, the payer's attributes, and the user's sentiment. Specifically, the server comprehensively evaluates this information and decides whether to waive the overdue payment review.

[0645] Specific examples

[0646] For example, a user enters the payer information as "Yamada Taro" who belongs to "ABC Co., Ltd." Suppose Yamada Taro makes payments on January 1st, April 1st, and July 1st. This information is sent from the device to the server and stored in a database. The server verifies that the payment dates are three months apart. The device also acquires Yamada Taro's facial expressions and voice, and the emotion engine recognizes stress. Based on this information, the server decides to exempt Yamada Taro from the overdue payment screening because he makes payments regularly. This allows Yamada Taro to plan his next actions with peace of mind.

[0647] Prompt Sentence Examples

[0648] A prompt that explains, "A system in which users register their payer information and then screen for delinquent payments based on their payment history and sentiment":

[0649] Design a system that registers payer information and performs delinquent payment screening based on payment history and sentiment. Please provide a description including the names of specific hardware and software, and the process flow.

[0650] With the above configuration, the present invention makes it possible to realize a more humane and efficient delinquency screening process that takes into account the user's emotions in addition to the regularity of payment history and the payer's attribute information.

[0651] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0652] Step 1:

[0653] Enter and submit payer information

[0654] The user inputs the payer information, including name, address, company, occupation, etc., and this information is entered into the terminal.

[0655] Input: Payer information (name, address, company, occupation, etc.)

[0656] How it works: The device receives this information and checks its consistency.

[0657] Output: The verified payer information is sent to the server.

[0658] Step 2:

[0659] Payer information storage

[0660] The server receives the payer information sent from the terminal and stores it in a database.

[0661] Input: Validated payer information

[0662] Operation: The server confirms receipt of the data and records it in a database. It also registers whether the person is an employee of a publicly listed company.

[0663] Output: Payer information stored in the database

[0664] Step 3:

[0665] Enter and submit payment date information

[0666] When a user makes a payment, the user inputs the payment date.

[0667] Input: Payment information (payment date, amount, etc.)

[0668] How it works: The device temporarily stores the payment date information, checks to make sure the data is not lost, and then sends it to the server.

[0669] Output: Payment date information sent to the server

[0670] Step 4:

[0671] Save payment date information and update history

[0672] The server receives the payment date information, stores it in a database, and updates the payment history.

[0673] Input: Payment date information

[0674] Operation: The server adds the received payment date information to the database and updates the accumulated payment history.

[0675] Output: Updated payment history

[0676] Step 5:

[0677] Evaluating payment history regularity

[0678] The server analyzes the accumulated payment history and calculates the interval between payment dates to verify payment regularity.

[0679] Input: Updated payment history

[0680] How it works: The server calculates the time interval between each payment date and evaluates whether it falls within a certain range. For example, if payments are made on January 1st, April 1st, and July 1st, it verifies that the interval between each payment is approximately 3 months.

[0681] Output: Regularity evaluation result

[0682] Step 6:

[0683] Acquiring and analyzing emotion data

[0684] The device acquires emotional data such as the user's voice and facial expressions and sends it to the server, which then uses an emotion engine to recognize the user's emotions.

[0685] Input: User voice and facial expression data

[0686] How it works: The device collects this data and sends it to a server, which uses an emotion engine to analyze emotions and recognize feelings such as stress or relief.

[0687] Output: Recognized user emotion data

[0688] Step 7:

[0689] Adjusting ratings based on emotions

[0690] The server adjusts the evaluation of the payment history based on the recognized emotion. For example, if a user is stressed but still makes regular payments, the server will evaluate their efforts and ease the screening process for delinquency.

[0691] Input: Regularity evaluation results, recognized user emotion data

[0692] How it works: The server aggregates this data and adjusts the ratings to take into account payment regularity and emotional influence.

[0693] Output: Adjusted evaluation results

[0694] Step 8:

[0695] Final decision on delinquency review

[0696] The server performs a delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion, and determines whether to exempt the screening.

[0697] Input: Adjusted assessment results, payer attribute information

[0698] Action: Conduct a final delinquency review and determine the outcome.

[0699] Output: Final result of delinquency review

[0700] Step 9:

[0701] Displaying and notifying results

[0702] The terminal receives the result of the delinquency examination from the server and notifies the user.

[0703] Input: Final result of delinquency review

[0704] Behavior: The result is displayed to the user in an easy-to-understand manner. For example, a specific message such as "Your delinquent payment has been waived" is displayed.

[0705] Output: The result displayed to the user

[0706] The above processing steps realize efficient and human-like delinquency screening that takes into account the user's emotions and payment history.

[0707] (Application example 2)

[0708] 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."

[0709] Conventional payment management systems perform delinquency screening based solely on payment history and payer attribute information, and are therefore unable to take into account the stress and anxiety felt by users. This makes accurate screening difficult, and alleviating users' psychological burden has been an issue.

[0710] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recording payment history, means for evaluating the regularity of the recorded payment history, means for saving and referencing the payer's attribute information, emotion engine means for analyzing the acquired emotion data, means for determining whether to skip the delinquency review based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data, and means for notifying the user of the result of the delinquency review. This enables more accurate delinquency review that takes into account not only the payment history and attribute information but also the user's emotions.

[0711] A "payment history recording means" is a system or device that digitally stores information about each payment made by a user.

[0712] The "means for evaluating the regularity of the recorded payment history" is a system or device that extracts patterns of payment dates and payment intervals from the stored payment history and analyzes the regularity of those patterns.

[0713] "Means for storing and querying payer attribute information" refers to a system or device that stores data such as the payer's personal information, occupation, and company affiliation in a database and can retrieve that information as needed.

[0714] The "emotion engine means for analyzing acquired emotion data" is a system or device that analyzes data such as the user's voice and facial expression, and identifies the emotional state at that time.

[0715] The "means for determining whether to skip the delinquency review" is a system or device that determines whether or not a delinquency review needs to be conducted based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data.

[0716] The "means for notifying the user of the results of the delinquency review" refers to a system or device that receives the results of the review from the server and displays or notifies the results on the user's terminal.

[0717] To implement this invention, a server, a terminal, and a series of operations by the user are required. This system is realized using the following hardware and software.

[0718] Hardware

[0719] 1. Device:

[0720] Smartphone (e.g. iPhone, Android)

[0721] Devices with a camera and microphone

[0722] 2. Server:

[0723] Cloud servers (e.g. AWS, Google Cloud) and on-premise servers

[0724] software

[0725] 1. Smartphone app:

[0726] Applications that input and record payment information and collect emotional data

[0727] Speech and facial recognition software (e.g., Amazon Rekognition, Google Cloud Speech-to-Text)

[0728] 2. Server-side software:

[0729] Database management systems (e.g., MySQL, PostgreSQL)

[0730] Analysis Engine

[0731] Notification System

[0732] Data processing and calculation

[0733] 1. Payment History Record:

[0734] When a user enters payment information (date, amount, etc.) through a smartphone app, the app saves this information and sends it to a server, which then stores the received payment information in a database.

[0735] 2. Payment Regularity Assessment:

[0736] The server analyzes the payment history stored in the database and evaluates its regularity by calculating the interval between payment dates, which allows for the identification of payment patterns.

[0737] 3. Acquiring and analyzing emotion data:

[0738] The device's camera and microphone are used to capture the user's voice and facial expression data, which are then sent to the emotion engine, which determines whether the user is feeling stressed and sends the result to the server.

[0739] 4. Delinquency Review Judgment:

[0740] The server determines whether a delinquent payment review is necessary based on the regularity of the payment history, the payer's attribute information (e.g., type of workplace), and emotional data. The server notifies the smartphone app of the result of this determination and displays the result to the user.

[0741] Adding specific examples

[0742] For example, suppose a user enters payment information, including voice data, into the app on July 1st. The app sends the collected voice and payment information to the server. The server compares the user's past payment history and evaluates the payment interval. At the same time, the emotion engine analyzes the voice data and detects that the user is feeling stressed. Based on this information, the server decides to skip the overdue payment review and notifies the user of the result.

[0743] Prompt Sentence Examples

[0744] "Please develop a system that analyzes users' payment history and emotional data through a smartphone app and automatically exempts them from overdue payments. The emotional data includes facial expressions and voice data."

[0745] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0746] Step 1:

[0747] A user inputs payment information using a smartphone app. This input information includes payment date, amount, payee, etc. The terminal temporarily stores this input data and sends it to the server. The date and amount are sent as input data, and the server stores them in a database as data processing. The output is a payment record stored in the database.

[0748] Step 2:

[0749] The terminal captures voice and facial expression data. While the user is entering payment information, the camera and microphone are activated to collect the user's facial expression data and voice data. The voice and facial expression data captured as input data is sent to the emotion engine, where emotion analysis is performed as data calculation. The output is the user's emotional state.

[0750] Step 3:

[0751] The server evaluates the regularity of the payment history. It analyzes the payment history stored in the database and calculates the interval between payment dates. The timestamp of each payment date is used as input data, and the calculation of the time interval is performed as data processing. The output is the result of the payment regularity evaluation.

[0752] Step 4:

[0753] The server queries the payer's attribute information. It retrieves the payer's attribute information stored in the database and checks the user's occupation, company affiliation, etc. The payer ID is used as input data, and attribute information is extracted as data processing. The output is the payer's attribute information.

[0754] Step 5:

[0755] The server combines all the information and makes a decision on whether or not to conduct a delinquent payment review. It decides whether or not to conduct a delinquent payment review based on the results of the regularity evaluation of the payment history, the payer's attribute information, and emotional data. The regularity evaluation results, attribute information, and emotional state are used as input data, and conditional judgments are performed as data calculations. The output is the decision on whether or not to conduct a delinquent payment review.

[0756] Step 6:

[0757] The user is notified of the results of the delinquency review. The server sends the results of the delinquency review to the terminal, which then displays the results to the user. The results of the delinquency review are used as input data, and notification data is generated as data processing. The output is notification information displayed to the user.

[0758] 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.

[0759] 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.

[0760] 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.

[0761] [Third embodiment]

[0762] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0763] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0764] 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).

[0765] 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.

[0766] 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.

[0767] 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).

[0768] 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.

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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."

[0774] As an embodiment of the present invention, a system for managing payment history and attribute information of a payer will be described first.

[0775] Payer Registration

[0776] The "user" enters the payer's information. The payer's name and attribute information (such as occupation and company) are also registered, and the "server" stores this information in a database. In particular, if the payer is an employee of a listed company, that information is also stored.

[0777] Recording payments

[0778] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" saves the received payment date in a database and records it as payment history.

[0779] Checking regular payments

[0780] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if a payer makes payments on January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval is within the range of 85 to 95 days.

[0781] Delinquent payment review decision

[0782] The "Server" determines whether to exempt the "User" from the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a listed company, the "Server" will omit the delinquency screening. In this case, the system notifies the "User" via the "Terminal" that the "User" does not need to undergo the delinquency screening.

[0783] Specific examples

[0784] For example, suppose a payer, who is a "user," is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information and checks the regularity of the payments. As a result, it is confirmed that "Yamada Taro" makes payments regularly every three months. The "server" also confirms that "Yamada Taro" is an employee of a listed company. As a result, the "server" displays on the "terminal" that the delinquency review will be omitted, and notifies the "user."

[0785] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on the regularity of payment history and payer attribute information. This system can significantly reduce time and costs compared to conventional methods.

[0786] The processing flow will be explained below.

[0787] Step 1:

[0788] The "user" enters payer information (name and attribute information) into the system, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database.

[0789] Step 2:

[0790] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[0791] Step 3:

[0792] The "server" retrieves the payment history from the database and calculates the intervals between payment dates to check for regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date (in this case, each interval is approximately 90 days).

[0793] Step 4:

[0794] The Server evaluates the payment history for regularity, and if it determines that the payments are regular, it stores that result, as well as if they are not regular.

[0795] Step 5:

[0796] The "server" retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. If the payer belongs to a listed company based on the attribute information, the result is also saved.

[0797] Step 6:

[0798] The "server" determines whether to skip the delinquency check based on the evaluation results of regular payments and the evaluation results of the payer's attribute information. If either one is true, the delinquency check is skipped.

[0799] Step 7:

[0800] The "server" sends the results of the delinquency review to the "terminal." The "terminal" receives the results and notifies the "user." For example, if the delinquency review is omitted, the "user" displays a message indicating that the delinquency review is not required.

[0801] Step 8:

[0802] The "user" reviews the results and decides on the next action if necessary, such as creating a new payment plan.

[0803] Example 1

[0804] 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."

[0805] In the conventional system, the confirmation of payment history patterns and the decision on delinquency based on the payer's attribute information were done manually, which took a lot of time and cost.In addition, there was also the problem that it was difficult to automatically determine preferential treatment for employees of listed companies, which made it prone to errors.

[0806] 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.

[0807] In this invention, the server includes a means for inputting payer information and saving payer attribute information, a means for inputting payment dates and recording payment histories, a means for evaluating the regularity of the recorded payment histories based on the interval between payment dates, a means for determining whether to omit delinquency screening based on the regularity of the payment history and the payer attribute information, and a notification means, thereby enabling the automation and efficiency of delinquency screening.

[0808] "Payer Information" means basic data about the person or entity making a payment for a service or product, including name, address, contact details, occupation, and company affiliation.

[0809] "Payer attribute information" refers to information that describes the payer's personal or professional characteristics or attributes, including, for example, occupation, company affiliation, income level, credit information, etc.

[0810] "Payment Date" means the date on which payment is made for a particular service or product.

[0811] "Payment History" means a record of each payment made by a Payer, including the date of each payment.

[0812] "Regularity" refers to consistency or patterns in data or events, in this case assessing whether payment intervals fall within a certain range.

[0813] "Evaluating the regularity of the payment history" means calculating the interval between payment dates from the accumulated payment history and determining whether the interval falls within a predetermined range.

[0814] "Delinquent payment review" is the process of evaluating the reasons for the late payment and the payer's credit standing when a payer fails to make a payment on time, and determining the next steps to take.

[0815] "Notification" refers to the act of informing other devices or individuals of information about a particular event or result, and in this context refers to the transmission of information from the server to the user.

[0816] The present invention is a system that manages payment history and attribute information of payers and automates delinquent payment screening. This system operates through the exchange of data between a server, a terminal, and a user. The following describes an embodiment of the present invention.

[0817] Payer Registration

[0818] First, the user inputs the payer's information. Using a terminal, the user inputs the payer's attribute information, such as their name, occupation, and the company they work for. The terminal temporarily stores this information in its memory and then sends it to the server. The server stores the received information in a database. Through this process, the payer is registered in the system.

[0819] Examples:

[0820] The user enters payer information such as name "Ichiro Tanaka," company "XYZ Corporation," and occupation "engineer," and sends it from the terminal to the server, which then stores it in a database.

[0821] Recording payments

[0822] Next, when the user makes a payment, he or she inputs the payment date. The user inputs the payment date using the terminal, which temporarily stores it and sends it to the server. The server stores the received payment date in a database and records it as payment history.

[0823] Examples:

[0824] The user enters "January 1, 2023" as the payment date, sends it from the terminal to the server, and the server saves it in the database.

[0825] Checking regular payments

[0826] The server analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if payments were made on January 1st, April 1st, and July 1st, the server evaluates whether the interval between each payment is regular.

[0827] Examples:

[0828] If a payer makes payments on January 1st, April 1st, and July 1st, the server evaluates the intervals as 90 days regular.

[0829] Delinquent payment review decision

[0830] The server determines whether to exempt the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a specific company, the server will omit the delinquency screening. The result is notified to the user via the terminal.

[0831] Examples:

[0832] The server evaluates the regularity of the payments, and if it is confirmed that the payer is an employee of a specific company, it notifies the user that the delinquency screening will be waived.

[0833] Example prompts to input to the generative AI model

[0834] Below is an example of a prompt sentence to input to the generative AI model.

[0835] Example prompt:

[0836] "Write a program for a system that manages user payment history and attribute information. It takes as input the payer's name, attribute information (such as occupation and company), and multiple payment dates, evaluates whether the payment interval is between 85 and 95 days, and outputs the result. It also checks whether the payer is an employee of a specific company and determines whether to exempt them from delinquency screening."

[0837] This invention realizes automation and efficiency of delinquent payment screening based on payment history regularity and attribute information, which enables significant reductions in time and cost compared to conventional manual screening.

[0838] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0839] Step 1: Enter payer information

[0840] The "user" opens the payer registration screen and enters information such as the payer's name, occupation, and company. The input data may include information such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation." The "terminal" temporarily stores this input data in its memory.

[0841] Step 2: Submit payer information

[0842] The terminal sends the temporarily saved payer information to the server. The data sent includes attribute information such as name, occupation, and company affiliation.

[0843] Step 3: Save payer information

[0844] The "server" stores the received payer information in a database. For example, entries such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation" are added to the database.

[0845] Step 4: Enter payment date

[0846] The "user" opens the payment screen and enters the payment date. For example, they enter "January 1, 2023." The "terminal" temporarily stores this payment date in its memory.

[0847] Step 5: Submit payment date information

[0848] The "terminal" transmits the temporarily stored payment date information to the "server." The transmitted data includes the payment date information.

[0849] Step 6: Save the payment date

[0850] The "server" saves the received payment date information in the database and records it as payment history. For example, a record of "January 1, 2023" is added to the payment history of "Ichiro Tanaka."

[0851] Step 7: Get your payment history

[0852] The "server" retrieves the accumulated payment history from the database. For example, it retrieves the past payment history of "Ichiro Tanaka" such as "January 1, 2023," "April 1, 2023," and "July 1, 2023."

[0853] Step 8: Calculate payment intervals

[0854] Based on the payment history obtained by the "server," the interval between each payment date is calculated. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[0855] Step 9: Evaluate regularities

[0856] The server evaluates whether the intervals between payment dates calculated by the server are within a predetermined range (for example, 85 to 95 days). For example, the payment dates of January 1st, April 1st, and July 1st are all 90 days apart, so they are evaluated as regular.

[0857] Step 10: Verify payer demographics

[0858] The server retrieves the payer's attribute information from the database again and includes it in the verification. For example, it verifies that "Ichiro Tanaka" is an employee of "XYZ Corporation."

[0859] Step 11: Delinquency Review Judgment

[0860] The server determines whether to exempt the payment from the delinquency review based on the payment history regularity and the payer's attribute information. For example, since "Ichiro Tanaka" pays regularly and is an employee of a specific company, the server determines that he should be exempt from the delinquency review.

[0861] Step 12: Notification of results

[0862] The "server" sends the results of the delinquency review to the "terminal." The "terminal" displays the results to the "user." For example, it displays "Delinquency review has been exempted."

[0863] This series of steps enables automatic and efficient delinquency screening based on the regularity of the payer's payment history and attribute information.

[0864] (Application example 1)

[0865] 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."

[0866] Conventional electronic payment systems have the problem that they do not efficiently screen users for delinquency, resulting in cumbersome procedures and a heavy burden on users. Furthermore, they uniformly screen users who make regular payments or have a high credit rating, which is inconvenient for these users as well. This reduces the efficiency of the entire payment process and causes stress for system users.

[0867] 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.

[0868] In this invention, the server includes a means for recording payment histories, a means for evaluating the regularity of the recorded payment histories, and a means for saving and querying the attribute information of the payer. This makes it possible to efficiently perform delinquency screening based on the regularity of the payment histories and the attribute information of the payer, and to quickly execute electronic payments for particularly reliable users.

[0869] "Payment history" is a record of payments made by a user in the past.

[0870] The "means for assessing the regularity of recorded payment history" is a mechanism for analyzing the intervals and patterns of payments within a certain period of time and assessing the regularity of payment behavior.

[0871] "Payer attribute information" is information that indicates individual characteristics such as the user's occupation, the company where the user is located, and whether or not the company is listed on the stock exchange.

[0872] "Means for storage and inquiry" refers to a system that safely stores recorded data and allows that data to be searched and retrieved as needed.

[0873] "Delinquent payment screening" is a process of assessing the user's reliability by checking whether the user is making payments on time and whether there have been any past defaults in payments in the past.

[0874] The "means for determining whether to skip the delinquency review" is a mechanism for determining whether or not a delinquency review needs to be conducted on a user based on the regularity of the payment history and the payer's attribute information.

[0875] "Electronic payments" refers to the transfer of funds or transactions that users make over the Internet.

[0876] "Quick execution means" refers to a mechanism that allows payment processing to be completed in a short time, enabling users to use the service without waiting.

[0877] As a specific embodiment of the present invention, a system for managing a user's payment history and attribute information and for promptly reviewing delinquency based on the information will be described. This system is realized using the following hardware and software.

[0878] Hardware and Software Configuration

[0879] Server: Contains the central database and analysis functions for this system. It stores payment history and payer attribute information and performs delinquent payment screening.

[0880] Terminal: The device where the user enters payment information and sees the results. This could be a smartphone, tablet, or PC.

[0881] Database: Use a database management system (DBMS) such as SQLite to store payment history and payer attribute information.

[0882] Analysis module: Analyzes payment history for regularities and attribute information using algorithms implemented in programming languages ​​such as Python.

[0883] Front-end technologies: HTML, CSS, JavaScript, and other technologies for building user interfaces. You can also build web applications using the Flask framework.

[0884] System Operation

[0885] 1. User Registration:

[0886] The user enters the payer information (name, occupation, company affiliation, etc.) on the terminal.

[0887] The server receives this and stores it in a database.

[0888] The server also stores attributes such as whether the company is listed or not.

[0889] 2. Payment History Record:

[0890] The user inputs information such as the payment date and payment amount from the terminal.

[0891] This information is temporarily stored on the device and then sent to the server.

[0892] The server receives this and stores it in a database.

[0893] 3. Regular payment confirmation:

[0894] The server analyzes the payment history in the database.

[0895] The interval between payment dates is calculated and evaluated to see if it falls within a preset range.

[0896] 4. Delinquency Review Judgment:

[0897] The server then performs a delinquent payment review based on the analyzed payment history regularity and the payer's attribute information.

[0898] If regular payments are confirmed or the payer is affiliated with a listed company, the delinquency review will be waived.

[0899] The result of this determination is sent to the terminal and notified to the user.

[0900] 5. Faster electronic payment execution:

[0901] The server issues instructions to the user who has been determined to be omitted to quickly execute electronic payment.

[0902] Specific examples

[0903] For example, suppose a payer is registered in the system as a "sales representative" belonging to a publicly listed company. If this payer makes payments on January 1st, April 1st, and July 1st, the server records each payment date in the database and checks the regularity of the payments. It verifies that the payment intervals are approximately every three months (85 to 95 days). Furthermore, because the payer belongs to a publicly listed company, the server notifies the user by displaying a message on the terminal that the payer is exempt from delinquency screening.

[0904] Generative AI model prompt example

[0905] Register the user "Salesperson" as an employee of a listed company

[0906] The server checks the payment history and determines whether payments are being made regularly.

[0907] Analyze payment records to assess whether delinquency screening is necessary

[0908] If exempt, notify the user of the exemption result

[0909] This system will significantly streamline the electronic payment process and enable faster service delivery to users.

[0910] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0911] Step 1:

[0912] The user registers the payer information.

[0913] Input: The user enters information such as name, occupation, and company affiliation into the device.

[0914] The server receives the input information and stores it in a database. At this time, JSON format data is sent as input data.

[0915] Data processing: The server converts the received information into an appropriate format and generates an insert query to the database.

[0916] Output: The user information is saved in the database and a message indicating registration is complete is returned to the terminal.

[0917] Step 2:

[0918] The user enters payment date information.

[0919] Input: The user enters information such as payment date and payment amount into the terminal.

[0920] The terminal sends the entered payment information to the server, along with information such as the payment date and amount in JSON format.

[0921] Data processing: The server analyzes the received payment information and generates a query to store it in the database as a payment record.

[0922] Output: The server saves the payment information in the database and sends a message to the terminal indicating that the payment has been recorded.

[0923] Step 3:

[0924] The server evaluates whether the payment is regular.

[0925] Input: Payment history information for a specific user in the database.

[0926] The server retrieves payment information associated with the specific user ID from the database.

[0927] Data calculation: The acquired payment date information is sorted in chronological order, and each payment interval is calculated. This evaluates whether the payment interval is within a set range (for example, 85 to 95 days).

[0928] Output: A decision is made on the server as to whether the payment is regular or not.

[0929] Step 4:

[0930] The server determines whether or not a delinquent payment review is necessary.

[0931] Input: Regular payment evaluation results and payer attribute information.

[0932] The server queries the database for the evaluation results of regular payments and whether the payer belongs to a listed company, and makes a comprehensive judgment.

[0933] Data calculation: Comprehensively analyzes payment history patterns and attribute information to determine whether or not a delinquency review is applicable.

[0934] Output: A decision is made as to whether a delinquency review is required or exempt.

[0935] Step 5:

[0936] The server notifies the terminal of the determination result.

[0937] Input: Decision result of delinquency review.

[0938] The server sends the result of the judgment to the terminal in JSON format.

[0939] Output: The user can check the result on the terminal. If exemption is granted, a notification will be displayed stating that the delinquency review has been exempted.

[0940] Step 6:

[0941] The server performs the fast electronic payment.

[0942] Input: Payment information for users who are exempt from delinquency screening.

[0943] The server verifies the payment information of the user who has been exempted from delinquency screening and generates instructions for electronic payment.

[0944] Data processing: The server calls the payment processing API and performs the procedures to quickly execute the electronic payment.

[0945] Output: If the electronic payment is successful, the result is notified to the terminal.

[0946] This series of processes allows users to make electronic payments quickly and efficiently, reduces the workload of overdue payments screening, and improves overall system performance.

[0947] 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.

[0948] As an embodiment of the present invention, a system that manages payment history and payer attribute information and further combines it with an emotion engine that recognizes user emotions will be described.

[0949] Payer Registration

[0950] The "user" inputs the payer's information, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database. In particular, if the payer is an employee of a listed company, that information is also stored in detail.

[0951] Recording payments

[0952] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[0953] Checking regular payments

[0954] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks the regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval falls within a certain range.

[0955] Emotion recognition by emotion engine

[0956] The "terminal" collects voice and facial expression data and sends it to the emotion engine. The "server" analyzes the received data and recognizes the user's emotions. For example, it analyzes whether the user is feeling stressed when making a payment.

[0957] Adjusting ratings based on emotions

[0958] The server then adjusts the evaluation of the user's payment history based on the perceived emotion. For example, if the user is stressed but still paying regularly, the server may adjust the evaluation to waive the overdue payment review to reflect that effort.

[0959] Delinquent payment review decision

[0960] The "server" determines whether to exempt the delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the delinquency screening is omitted. If this result is reached, the "server" sends the result to the "terminal."

[0961] Screen display and user notification

[0962] The "terminal" receives the judgment result from the "server" and displays it to the "user." For example, if the delinquency examination is omitted, the "user" is notified of this.

[0963] Specific examples

[0964] For example, suppose a "user" payer is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information, checks the regularity of the payments, and confirms that the payer is an employee of the listed company. Furthermore, the emotion engine analyzes Yamada Taro's voice data and facial expression data acquired by the "terminal" to recognize emotions such as stress.

[0965] The "server" decides whether to exempt the overdue payment review based on payment history, attribute information, and recognized emotions. The result is then displayed on the "terminal" and notified to the "user." As a result, if Yamada Taro is exempted from the overdue payment review, Yamada Taro can plan his next actions with peace of mind.

[0966] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on payment history patterns, payer attribute information, and user sentiment. This system significantly reduces time and costs compared to conventional methods, and reduces the burden on users.

[0967] The processing flow will be explained below.

[0968] Step 1:

[0969] The "user" enters payer information (name and attribute information) into the system. The "terminal" receives the information and sends it to the "server." The "server" saves the received payer information in a database. For example, it registers that the payer is Yamada Taro, who works for a listed company.

[0970] Step 2:

[0971] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, saves it in a database, and updates the payment history. For example, payments made on January 1st, April 1st, and July 1st are recorded.

[0972] Step 3:

[0973] The "server" analyzes the accumulated payment history, calculating the interval between each payment date and checking whether it is between 85 and 95 days. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[0974] Step 4:

[0975] The "server" evaluates the regularity of the recorded payment history. The "server" checks that the interval between each payment date is within a certain range and determines that the payment is regular. The result is stored in the database.

[0976] Step 5:

[0977] The server retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. This information is also saved as the evaluation result.

[0978] Step 6:

[0979] When a "user" makes a payment, the "terminal" transmits the user's voice and facial expressions to the emotion engine. The "server" receives this and uses the emotion engine to analyze the user's emotional state. For example, it evaluates whether the "user" is feeling stressed or relieved.

[0980] Step 7:

[0981] The Server adjusts the evaluation of the payment history based on the emotions recognized by the emotion engine, for example, if the User is stressed but still makes payments regularly, it takes into account their efforts.

[0982] Step 8:

[0983] The server determines whether to exempt the payment from the delinquency check based on the payment history regularity, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the payment from the delinquency check is omitted.

[0984] Step 9:

[0985] The "server" sends the result of the delinquency review to the "terminal." The "terminal" receives the result and notifies the "user." For example, it displays a message that the delinquency review has been waived.

[0986] Step 10:

[0987] The user checks the results. If the overdue payment screening is waived, the user can make their next payment plan and live their life with peace of mind.

[0988] As described above, the system of the present invention can efficiently conduct delinquency screening based on the regularity of payment history, the payer's attribute information, and the user's emotional state, thereby reducing the burden on the user.

[0989] Example 2

[0990] 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."

[0991] Conventional payment history management systems screen for delinquency based on payment history and payer attribute information, but do not consider the user's emotions. As a result, they often ignore the anxiety and stress users feel about payments, and a more human-like approach is needed. Furthermore, evaluating patterns and checking attribute information requires a lot of time and effort, making them inefficient. A new system that solves these issues is needed.

[0992] 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.

[0993] In this invention, the server includes a means for recording payment history, a means for evaluating the regularity of the recorded payment history, a means for saving and referencing the attributes of the payer, a means for recognizing the user's emotions, and a means for determining whether to skip the delinquency review based on the regularity of the payment history, the attributes of the payer, and the user's emotions. This enables a more humane and efficient delinquency review that takes into account the user's emotions in addition to the regularity of the payment history and the attribute information of the payer.

[0994] A "payment history" is a detailed record of the series of payments made by a user.

[0995] The "recording means" is a technique or device for storing the user's payment history in a storage device such as a database.

[0996] A "means for assessing regularity" is a technique or device that analyzes time intervals in recorded payment history and determines regularity based on certain patterns.

[0997] "Payer attributes" refers to basic information and details about the payer, including, for example, occupation and company affiliation.

[0998] "Means for storing and querying" refers to technology or equipment that can store payer attribute information in a database or the like and retrieve that information as needed.

[0999] "User emotions" refer to the psychological state or feeling a user has regarding a payment, and include, for example, stress or relief.

[1000] The "recognition means" refers to a technology or device for analyzing the user's voice and facial expression data and identifying their emotions.

[1001] "Delinquency screening" is the process of determining whether payments are likely to be delinquent based on the regularity of payment history and the attributes of the payer.

[1002] The "means for determining" is a technology or device that comprehensively evaluates the regularity of the payment history, the attributes of the payer, and the user's emotions, and determines whether or not to conduct a delinquency review.

[1003] The system of the present invention is designed to manage payment history and review delinquency efficiently and humanly. This system is composed of the following main components:

[1004] 1. A way to record payment history

[1005] This means records information about payments made by users (such as payment date and amount) and stores it in a database. Specifically, the payment information entered into the terminal is sent to a server, which then stores it in a database.

[1006] 2. A means of assessing the regularity of recorded payment history

[1007] This method analyzes the recorded payment history and evaluates the regularity of payments. Specifically, the server calculates the interval between each payment date and checks whether the interval falls within a certain range.

[1008] 3. Means for storing and querying payer attributes

[1009] This method stores basic information about the payer (e.g., company affiliation, occupation, etc.) in a database, making it possible to retrieve that information as needed. The attribute information entered by the terminal is sent to the server, which then stores it.

[1010] 4. How to Recognize User Emotions

[1011] This method captures and analyzes data such as voice and facial expressions to recognize the emotions the user feels when making a payment. For example, a camera or microphone installed on the terminal captures the user's voice and facial expressions and sends them to the emotion engine.

[1012] 5. How to determine whether to waive delinquency screening

[1013] This means determines whether to waive the overdue payment review based on the regularity of the payment history, the payer's attributes, and the user's sentiment. Specifically, the server comprehensively evaluates this information and decides whether to waive the overdue payment review.

[1014] Specific examples

[1015] For example, a user enters the payer information as "Yamada Taro" who belongs to "ABC Co., Ltd." Suppose Yamada Taro makes payments on January 1st, April 1st, and July 1st. This information is sent from the device to the server and stored in a database. The server verifies that the payment dates are three months apart. The device also acquires Yamada Taro's facial expressions and voice, and the emotion engine recognizes stress. Based on this information, the server decides to exempt Yamada Taro from the overdue payment screening because he makes payments regularly. This allows Yamada Taro to plan his next actions with peace of mind.

[1016] Prompt Sentence Examples

[1017] A prompt that explains, "A system in which users register their payer information and then screen for delinquent payments based on their payment history and sentiment":

[1018] Design a system that registers payer information and performs delinquent payment screening based on payment history and sentiment. Please provide a description including the names of specific hardware and software, and the process flow.

[1019] With the above configuration, the present invention makes it possible to realize a more humane and efficient delinquency screening process that takes into account the user's emotions in addition to the regularity of payment history and the payer's attribute information.

[1020] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1021] Step 1:

[1022] Enter and submit payer information

[1023] The user inputs the payer information, including name, address, company, occupation, etc., and this information is entered into the terminal.

[1024] Input: Payer information (name, address, company, occupation, etc.)

[1025] How it works: The device receives this information and checks its consistency.

[1026] Output: The verified payer information is sent to the server.

[1027] Step 2:

[1028] Payer information storage

[1029] The server receives the payer information sent from the terminal and stores it in a database.

[1030] Input: Validated payer information

[1031] Operation: The server confirms receipt of the data and records it in a database. It also registers whether the person is an employee of a publicly listed company.

[1032] Output: Payer information stored in the database

[1033] Step 3:

[1034] Enter and submit payment date information

[1035] When a user makes a payment, the user inputs the payment date.

[1036] Input: Payment information (payment date, amount, etc.)

[1037] How it works: The device temporarily stores the payment date information, checks to make sure the data is not lost, and then sends it to the server.

[1038] Output: Payment date information sent to the server

[1039] Step 4:

[1040] Save payment date information and update history

[1041] The server receives the payment date information, stores it in a database, and updates the payment history.

[1042] Input: Payment date information

[1043] Operation: The server adds the received payment date information to the database and updates the accumulated payment history.

[1044] Output: Updated payment history

[1045] Step 5:

[1046] Evaluating payment history regularity

[1047] The server analyzes the accumulated payment history and calculates the interval between payment dates to verify payment regularity.

[1048] Input: Updated payment history

[1049] How it works: The server calculates the time interval between each payment date and evaluates whether it falls within a certain range. For example, if payments are made on January 1st, April 1st, and July 1st, it verifies that the interval between each payment is approximately 3 months.

[1050] Output: Regularity evaluation result

[1051] Step 6:

[1052] Acquiring and analyzing emotion data

[1053] The device acquires emotional data such as the user's voice and facial expressions and sends it to the server, which then uses an emotion engine to recognize the user's emotions.

[1054] Input: User voice and facial expression data

[1055] How it works: The device collects this data and sends it to a server, which uses an emotion engine to analyze emotions and recognize feelings such as stress or relief.

[1056] Output: Recognized user emotion data

[1057] Step 7:

[1058] Adjusting ratings based on emotions

[1059] The server adjusts the evaluation of the payment history based on the recognized emotion. For example, if a user is stressed but still makes regular payments, the server will evaluate their efforts and ease the screening process for delinquency.

[1060] Input: Regularity evaluation results, recognized user emotion data

[1061] How it works: The server aggregates this data and adjusts the ratings to take into account payment regularity and emotional influence.

[1062] Output: Adjusted evaluation results

[1063] Step 8:

[1064] Final decision on delinquency review

[1065] The server performs a delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion, and determines whether to exempt the screening.

[1066] Input: Adjusted assessment results, payer attribute information

[1067] Action: Conduct a final delinquency review and determine the outcome.

[1068] Output: Final result of delinquency review

[1069] Step 9:

[1070] Displaying and notifying results

[1071] The terminal receives the result of the delinquency examination from the server and notifies the user.

[1072] Input: Final result of delinquency review

[1073] Behavior: The result is displayed to the user in an easy-to-understand manner. For example, a specific message such as "Your delinquent payment has been waived" is displayed.

[1074] Output: The result displayed to the user

[1075] The above processing steps realize efficient and human-like delinquency screening that takes into account the user's emotions and payment history.

[1076] (Application example 2)

[1077] 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."

[1078] Conventional payment management systems perform delinquency screening based solely on payment history and payer attribute information, and are therefore unable to take into account the stress and anxiety felt by users. This makes accurate screening difficult, and alleviating users' psychological burden has been an issue.

[1079] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recording payment history, means for evaluating the regularity of the recorded payment history, means for saving and referencing the payer's attribute information, emotion engine means for analyzing the acquired emotion data, means for determining whether to skip the delinquency review based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data, and means for notifying the user of the result of the delinquency review. This enables more accurate delinquency review that takes into account not only the payment history and attribute information but also the user's emotions.

[1080] A "payment history recording means" is a system or device that digitally stores information about each payment made by a user.

[1081] The "means for evaluating the regularity of the recorded payment history" is a system or device that extracts patterns of payment dates and payment intervals from the stored payment history and analyzes the regularity of those patterns.

[1082] "Means for storing and querying payer attribute information" refers to a system or device that stores data such as the payer's personal information, occupation, and company affiliation in a database and can retrieve that information as needed.

[1083] The "emotion engine means for analyzing acquired emotion data" is a system or device that analyzes data such as the user's voice and facial expression, and identifies the emotional state at that time.

[1084] The "means for determining whether to skip the delinquency review" is a system or device that determines whether or not a delinquency review needs to be conducted based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data.

[1085] The "means for notifying the user of the results of the delinquency review" refers to a system or device that receives the results of the review from the server and displays or notifies the results on the user's terminal.

[1086] To implement this invention, a server, a terminal, and a series of operations by the user are required. This system is realized using the following hardware and software.

[1087] Hardware

[1088] 1. Device:

[1089] Smartphone (e.g. iPhone, Android)

[1090] Devices with a camera and microphone

[1091] 2. Server:

[1092] Cloud servers (e.g. AWS, Google Cloud) and on-premise servers

[1093] software

[1094] 1. Smartphone app:

[1095] Applications that input and record payment information and collect emotional data

[1096] Speech and facial recognition software (e.g., Amazon Rekognition, Google Cloud Speech-to-Text)

[1097] 2. Server-side software:

[1098] Database management systems (e.g., MySQL, PostgreSQL)

[1099] Analysis Engine

[1100] Notification System

[1101] Data processing and calculation

[1102] 1. Payment History Record:

[1103] When a user enters payment information (date, amount, etc.) through a smartphone app, the app saves this information and sends it to a server, which then stores the received payment information in a database.

[1104] 2. Payment Regularity Assessment:

[1105] The server analyzes the payment history stored in the database and evaluates its regularity by calculating the interval between payment dates, which allows for the identification of payment patterns.

[1106] 3. Acquiring and analyzing emotion data:

[1107] The device's camera and microphone are used to capture the user's voice and facial expression data, which are then sent to the emotion engine, which determines whether the user is feeling stressed and sends the result to the server.

[1108] 4. Delinquency Review Judgment:

[1109] The server determines whether a delinquent payment review is necessary based on the regularity of the payment history, the payer's attribute information (e.g., type of workplace), and emotional data. The server notifies the smartphone app of the result of this determination and displays the result to the user.

[1110] Adding specific examples

[1111] For example, suppose a user enters payment information, including voice data, into the app on July 1st. The app sends the collected voice and payment information to the server. The server compares the user's past payment history and evaluates the payment interval. At the same time, the emotion engine analyzes the voice data and detects that the user is feeling stressed. Based on this information, the server decides to skip the overdue payment review and notifies the user of the result.

[1112] Prompt Sentence Examples

[1113] "Please develop a system that analyzes users' payment history and emotional data through a smartphone app and automatically exempts them from overdue payments. The emotional data includes facial expressions and voice data."

[1114] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1115] Step 1:

[1116] A user inputs payment information using a smartphone app. This input information includes payment date, amount, payee, etc. The terminal temporarily stores this input data and sends it to the server. The date and amount are sent as input data, and the server stores them in a database as data processing. The output is a payment record stored in the database.

[1117] Step 2:

[1118] The terminal captures voice and facial expression data. While the user is entering payment information, the camera and microphone are activated to collect the user's facial expression data and voice data. The voice and facial expression data captured as input data is sent to the emotion engine, where emotion analysis is performed as data calculation. The output is the user's emotional state.

[1119] Step 3:

[1120] The server evaluates the regularity of the payment history. It analyzes the payment history stored in the database and calculates the interval between payment dates. The timestamp of each payment date is used as input data, and the calculation of the time interval is performed as data processing. The output is the result of the payment regularity evaluation.

[1121] Step 4:

[1122] The server queries the payer's attribute information. It retrieves the payer's attribute information stored in the database and checks the user's occupation, company affiliation, etc. The payer ID is used as input data, and attribute information is extracted as data processing. The output is the payer's attribute information.

[1123] Step 5:

[1124] The server combines all the information and makes a decision on whether or not to conduct a delinquent payment review. It decides whether or not to conduct a delinquent payment review based on the results of the regularity evaluation of the payment history, the payer's attribute information, and emotional data. The regularity evaluation results, attribute information, and emotional state are used as input data, and conditional judgments are performed as data calculations. The output is the decision on whether or not to conduct a delinquent payment review.

[1125] Step 6:

[1126] The user is notified of the results of the delinquency review. The server sends the results of the delinquency review to the terminal, which then displays the results to the user. The results of the delinquency review are used as input data, and notification data is generated as data processing. The output is notification information displayed to the user.

[1127] 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.

[1128] 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.

[1129] 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.

[1130] [Fourth embodiment]

[1131] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1132] 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.

[1133] 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).

[1134] 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.

[1135] 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.

[1136] 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).

[1137] 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.

[1138] 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.

[1139] 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.

[1140] 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.

[1141] 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.

[1142] 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.

[1143] 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."

[1144] As an embodiment of the present invention, a system for managing payment history and attribute information of a payer will be described first.

[1145] Payer Registration

[1146] The "user" enters the payer's information. The payer's name and attribute information (such as occupation and company) are also registered, and the "server" stores this information in a database. In particular, if the payer is an employee of a listed company, that information is also stored.

[1147] Recording payments

[1148] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" saves the received payment date in a database and records it as payment history.

[1149] Checking regular payments

[1150] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if a payer makes payments on January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval is within the range of 85 to 95 days.

[1151] Delinquent payment review decision

[1152] The "Server" determines whether to exempt the "User" from the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a listed company, the "Server" will omit the delinquency screening. In this case, the system notifies the "User" via the "Terminal" that the "User" does not need to undergo the delinquency screening.

[1153] Specific examples

[1154] For example, suppose a payer, who is a "user," is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information and checks the regularity of the payments. As a result, it is confirmed that "Yamada Taro" makes payments regularly every three months. The "server" also confirms that "Yamada Taro" is an employee of a listed company. As a result, the "server" displays on the "terminal" that the delinquency review will be omitted, and notifies the "user."

[1155] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on the regularity of payment history and payer attribute information. This system can significantly reduce time and costs compared to conventional methods.

[1156] The processing flow will be explained below.

[1157] Step 1:

[1158] The "user" enters payer information (name and attribute information) into the system, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database.

[1159] Step 2:

[1160] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[1161] Step 3:

[1162] The "server" retrieves the payment history from the database and calculates the intervals between payment dates to check for regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date (in this case, each interval is approximately 90 days).

[1163] Step 4:

[1164] The Server evaluates the payment history for regularity, and if it determines that the payments are regular, it stores that result, as well as if they are not regular.

[1165] Step 5:

[1166] The "server" retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. If the payer belongs to a listed company based on the attribute information, the result is also saved.

[1167] Step 6:

[1168] The "server" determines whether to skip the delinquency check based on the evaluation results of regular payments and the evaluation results of the payer's attribute information. If either one is true, the delinquency check is skipped.

[1169] Step 7:

[1170] The "server" sends the results of the delinquency review to the "terminal." The "terminal" receives the results and notifies the "user." For example, if the delinquency review is omitted, the "user" displays a message indicating that the delinquency review is not required.

[1171] Step 8:

[1172] The "user" reviews the results and decides on the next action if necessary, such as creating a new payment plan.

[1173] Example 1

[1174] 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."

[1175] In the conventional system, the confirmation of payment history patterns and the decision on delinquency based on the payer's attribute information were done manually, which took a lot of time and cost.In addition, there was also the problem that it was difficult to automatically determine preferential treatment for employees of listed companies, which made it prone to errors.

[1176] 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.

[1177] In this invention, the server includes a means for inputting payer information and saving payer attribute information, a means for inputting payment dates and recording payment histories, a means for evaluating the regularity of the recorded payment histories based on the interval between payment dates, a means for determining whether to omit delinquency screening based on the regularity of the payment history and the payer attribute information, and a notification means, thereby enabling the automation and efficiency of delinquency screening.

[1178] "Payer Information" means basic data about the person or entity making a payment for a service or product, including name, address, contact details, occupation, and company affiliation.

[1179] "Payer attribute information" refers to information that describes the payer's personal or professional characteristics or attributes, including, for example, occupation, company affiliation, income level, credit information, etc.

[1180] "Payment Date" means the date on which payment is made for a particular service or product.

[1181] "Payment History" means a record of each payment made by a Payer, including the date of each payment.

[1182] "Regularity" refers to consistency or patterns in data or events, in this case assessing whether payment intervals fall within a certain range.

[1183] "Evaluating the regularity of the payment history" means calculating the interval between payment dates from the accumulated payment history and determining whether the interval falls within a predetermined range.

[1184] "Delinquent payment review" is the process of evaluating the reasons for the late payment and the payer's credit standing when a payer fails to make a payment on time, and determining the next steps to take.

[1185] "Notification" refers to the act of informing other devices or individuals of information about a particular event or result, and in this context refers to the transmission of information from the server to the user.

[1186] The present invention is a system that manages payment history and attribute information of payers and automates delinquent payment screening. This system operates through the exchange of data between a server, a terminal, and a user. The following describes an embodiment of the present invention.

[1187] Payer Registration

[1188] First, the user inputs the payer's information. Using a terminal, the user inputs the payer's attribute information, such as their name, occupation, and the company they work for. The terminal temporarily stores this information in its memory and then sends it to the server. The server stores the received information in a database. Through this process, the payer is registered in the system.

[1189] Examples:

[1190] The user enters payer information such as name "Ichiro Tanaka," company "XYZ Corporation," and occupation "engineer," and sends it from the terminal to the server, which then stores it in a database.

[1191] Recording payments

[1192] Next, when the user makes a payment, he or she inputs the payment date. The user inputs the payment date using the terminal, which temporarily stores it and sends it to the server. The server stores the received payment date in a database and records it as payment history.

[1193] Examples:

[1194] The user enters "January 1, 2023" as the payment date, sends it from the terminal to the server, and the server saves it in the database.

[1195] Checking regular payments

[1196] The server analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment and checks whether the interval is within a certain range (e.g., 85 to 95 days). For example, if payments were made on January 1st, April 1st, and July 1st, the server evaluates whether the interval between each payment is regular.

[1197] Examples:

[1198] If a payer makes payments on January 1st, April 1st, and July 1st, the server evaluates the intervals as 90 days regular.

[1199] Delinquent payment review decision

[1200] The server determines whether to exempt the delinquency screening based on the regularity of the payment history and the payer's attribute information. If the payer makes payments regularly or is an employee of a specific company, the server will omit the delinquency screening. The result is notified to the user via the terminal.

[1201] Examples:

[1202] The server evaluates the regularity of the payments, and if it is confirmed that the payer is an employee of a specific company, it notifies the user that the delinquency screening will be waived.

[1203] Example prompts to input to the generative AI model

[1204] Below is an example of a prompt sentence to input to the generative AI model.

[1205] Example prompt:

[1206] "Write a program for a system that manages user payment history and attribute information. It takes as input the payer's name, attribute information (such as occupation and company), and multiple payment dates, evaluates whether the payment interval is between 85 and 95 days, and outputs the result. It also checks whether the payer is an employee of a specific company and determines whether to exempt them from delinquency screening."

[1207] This invention realizes automation and efficiency of delinquent payment screening based on payment history regularity and attribute information, which enables significant reductions in time and cost compared to conventional manual screening.

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

[1209] Step 1: Enter payer information

[1210] The "user" opens the payer registration screen and enters information such as the payer's name, occupation, and company. The input data may include information such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation." The "terminal" temporarily stores this input data in its memory.

[1211] Step 2: Submit payer information

[1212] The terminal sends the temporarily saved payer information to the server. The data sent includes attribute information such as name, occupation, and company affiliation.

[1213] Step 3: Save payer information

[1214] The "server" stores the received payer information in a database. For example, entries such as "Ichiro Tanaka," "Engineer," and "XYZ Corporation" are added to the database.

[1215] Step 4: Enter payment date

[1216] The "user" opens the payment screen and enters the payment date. For example, they enter "January 1, 2023." The "terminal" temporarily stores this payment date in its memory.

[1217] Step 5: Submit payment date information

[1218] The "terminal" transmits the temporarily stored payment date information to the "server." The transmitted data includes the payment date information.

[1219] Step 6: Save the payment date

[1220] The "server" saves the received payment date information in the database and records it as payment history. For example, a record of "January 1, 2023" is added to the payment history of "Ichiro Tanaka."

[1221] Step 7: Get your payment history

[1222] The "server" retrieves the accumulated payment history from the database. For example, it retrieves the past payment history of "Ichiro Tanaka" such as "January 1, 2023," "April 1, 2023," and "July 1, 2023."

[1223] Step 8: Calculate payment intervals

[1224] Based on the payment history obtained by the "server," the interval between each payment date is calculated. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[1225] Step 9: Evaluate regularities

[1226] The server evaluates whether the intervals between payment dates calculated by the server are within a predetermined range (for example, 85 to 95 days). For example, the payment dates of January 1st, April 1st, and July 1st are all 90 days apart, so they are evaluated as regular.

[1227] Step 10: Verify payer demographics

[1228] The server retrieves the payer's attribute information from the database again and includes it in the verification. For example, it verifies that "Ichiro Tanaka" is an employee of "XYZ Corporation."

[1229] Step 11: Delinquency Review Judgment

[1230] The server determines whether to exempt the payment from the delinquency review based on the payment history regularity and the payer's attribute information. For example, since "Ichiro Tanaka" pays regularly and is an employee of a specific company, the server determines that he should be exempt from the delinquency review.

[1231] Step 12: Notification of results

[1232] The "server" sends the results of the delinquency review to the "terminal." The "terminal" displays the results to the "user." For example, it displays "Delinquency review has been exempted."

[1233] This series of steps enables automatic and efficient delinquency screening based on the regularity of the payer's payment history and attribute information.

[1234] (Application example 1)

[1235] 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."

[1236] Conventional electronic payment systems have the problem that they do not efficiently screen users for delinquency, resulting in cumbersome procedures and a heavy burden on users. Furthermore, they uniformly screen users who make regular payments or have a high credit rating, which is inconvenient for these users as well. This reduces the efficiency of the entire payment process and causes stress for system users.

[1237] 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.

[1238] In this invention, the server includes a means for recording payment histories, a means for evaluating the regularity of the recorded payment histories, and a means for saving and querying the attribute information of the payer. This makes it possible to efficiently perform delinquency screening based on the regularity of the payment histories and the attribute information of the payer, and to quickly execute electronic payments for particularly reliable users.

[1239] "Payment history" is a record of payments made by a user in the past.

[1240] The "means for assessing the regularity of recorded payment history" is a mechanism for analyzing the intervals and patterns of payments within a certain period of time and assessing the regularity of payment behavior.

[1241] "Payer attribute information" is information that indicates individual characteristics such as the user's occupation, the company where the user is located, and whether or not the company is listed on the stock exchange.

[1242] "Means for storage and inquiry" refers to a system that safely stores recorded data and allows that data to be searched and retrieved as needed.

[1243] "Delinquent payment screening" is a process of assessing the user's reliability by checking whether the user is making payments on time and whether there have been any past defaults in payments in the past.

[1244] The "means for determining whether to skip the delinquency review" is a mechanism for determining whether or not a delinquency review needs to be conducted on a user based on the regularity of the payment history and the payer's attribute information.

[1245] "Electronic payments" refers to the transfer of funds or transactions that users make over the Internet.

[1246] "Quick execution means" refers to a mechanism that allows payment processing to be completed in a short time, enabling users to use the service without waiting.

[1247] As a specific embodiment of the present invention, a system for managing a user's payment history and attribute information and for promptly reviewing delinquency based on the information will be described. This system is realized using the following hardware and software.

[1248] Hardware and Software Configuration

[1249] Server: Contains the central database and analysis functions for this system. It stores payment history and payer attribute information and performs delinquent payment screening.

[1250] Terminal: The device where the user enters payment information and sees the results. This could be a smartphone, tablet, or PC.

[1251] Database: Use a database management system (DBMS) such as SQLite to store payment history and payer attribute information.

[1252] Analysis module: Analyzes payment history for regularities and attribute information using algorithms implemented in programming languages ​​such as Python.

[1253] Front-end technologies: HTML, CSS, JavaScript, and other technologies for building user interfaces. You can also build web applications using the Flask framework.

[1254] System Operation

[1255] 1. User Registration:

[1256] The user enters the payer information (name, occupation, company affiliation, etc.) on the terminal.

[1257] The server receives this and stores it in a database.

[1258] The server also stores attributes such as whether the company is listed or not.

[1259] 2. Payment History Record:

[1260] The user inputs information such as the payment date and payment amount from the terminal.

[1261] This information is temporarily stored on the device and then sent to the server.

[1262] The server receives this and stores it in a database.

[1263] 3. Regular payment confirmation:

[1264] The server analyzes the payment history in the database.

[1265] The interval between payment dates is calculated and evaluated to see if it falls within a preset range.

[1266] 4. Delinquency Review Judgment:

[1267] The server then performs a delinquent payment review based on the analyzed payment history regularity and the payer's attribute information.

[1268] If regular payments are confirmed or the payer is affiliated with a listed company, the delinquency review will be waived.

[1269] The result of this determination is sent to the terminal and notified to the user.

[1270] 5. Faster electronic payment execution:

[1271] The server issues instructions to the user who has been determined to be omitted to quickly execute electronic payment.

[1272] Specific examples

[1273] For example, suppose a payer is registered in the system as a "sales representative" belonging to a publicly listed company. If this payer makes payments on January 1st, April 1st, and July 1st, the server records each payment date in the database and checks the regularity of the payments. It verifies that the payment intervals are approximately every three months (85 to 95 days). Furthermore, because the payer belongs to a publicly listed company, the server notifies the user by displaying a message on the terminal that the payer is exempt from delinquency screening.

[1274] Generative AI model prompt example

[1275] Register the user "Salesperson" as an employee of a listed company

[1276] The server checks the payment history and determines whether payments are being made regularly.

[1277] Analyze payment records to assess whether delinquency screening is necessary

[1278] If exempt, notify the user of the exemption result

[1279] This system will significantly streamline the electronic payment process and enable faster service delivery to users.

[1280] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1281] Step 1:

[1282] The user registers the payer information.

[1283] Input: The user enters information such as name, occupation, and company affiliation into the device.

[1284] The server receives the input information and stores it in a database. At this time, JSON format data is sent as input data.

[1285] Data processing: The server converts the received information into an appropriate format and generates an insert query to the database.

[1286] Output: The user information is saved in the database and a message indicating registration is complete is returned to the terminal.

[1287] Step 2:

[1288] The user enters payment date information.

[1289] Input: The user enters information such as payment date and payment amount into the terminal.

[1290] The terminal sends the entered payment information to the server, along with information such as the payment date and amount in JSON format.

[1291] Data processing: The server analyzes the received payment information and generates a query to store it in the database as a payment record.

[1292] Output: The server saves the payment information in the database and sends a message to the terminal indicating that the payment has been recorded.

[1293] Step 3:

[1294] The server evaluates whether the payment is regular.

[1295] Input: Payment history information for a specific user in the database.

[1296] The server retrieves payment information associated with the specific user ID from the database.

[1297] Data calculation: The acquired payment date information is sorted in chronological order, and each payment interval is calculated. This evaluates whether the payment interval is within a set range (for example, 85 to 95 days).

[1298] Output: A decision is made on the server as to whether the payment is regular or not.

[1299] Step 4:

[1300] The server determines whether or not a delinquent payment review is necessary.

[1301] Input: Regular payment evaluation results and payer attribute information.

[1302] The server queries the database for the evaluation results of regular payments and whether the payer belongs to a listed company, and makes a comprehensive judgment.

[1303] Data calculation: Comprehensively analyzes payment history patterns and attribute information to determine whether or not a delinquency review is applicable.

[1304] Output: A decision is made as to whether a delinquency review is required or exempt.

[1305] Step 5:

[1306] The server notifies the terminal of the determination result.

[1307] Input: Decision result of delinquency review.

[1308] The server sends the result of the judgment to the terminal in JSON format.

[1309] Output: The user can check the result on the terminal. If exemption is granted, a notification will be displayed stating that the delinquency review has been exempted.

[1310] Step 6:

[1311] The server performs the fast electronic payment.

[1312] Input: Payment information for users who are exempt from delinquency screening.

[1313] The server verifies the payment information of the user who has been exempted from delinquency screening and generates instructions for electronic payment.

[1314] Data processing: The server calls the payment processing API and performs the procedures to quickly execute the electronic payment.

[1315] Output: If the electronic payment is successful, the result is notified to the terminal.

[1316] This series of processes allows users to make electronic payments quickly and efficiently, reduces the workload of overdue payments screening, and improves overall system performance.

[1317] 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.

[1318] As an embodiment of the present invention, a system that manages payment history and payer attribute information and further combines it with an emotion engine that recognizes user emotions will be described.

[1319] Payer Registration

[1320] The "user" inputs the payer's information, and the "terminal" receives the information and sends it to the "server." The "server" stores the received payer information in a database. In particular, if the payer is an employee of a listed company, that information is also stored in detail.

[1321] Recording payments

[1322] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores this information and sends it to the "server." The "server" receives the payment date information, stores it in a database, and updates the payment history.

[1323] Checking regular payments

[1324] The "server" analyzes the accumulated payment history and evaluates the regularity of payments. Specifically, it calculates the interval between each payment date and checks the regularity. For example, if the payment dates are January 1st, April 1st, and July 1st, the "server" calculates the interval between each payment date and evaluates whether the interval falls within a certain range.

[1325] Emotion recognition by emotion engine

[1326] The "terminal" collects voice and facial expression data and sends it to the emotion engine. The "server" analyzes the received data and recognizes the user's emotions. For example, it analyzes whether the user is feeling stressed when making a payment.

[1327] Adjusting ratings based on emotions

[1328] The server then adjusts the evaluation of the user's payment history based on the perceived emotion. For example, if the user is stressed but still paying regularly, the server may adjust the evaluation to waive the overdue payment review to reflect that effort.

[1329] Delinquent payment review decision

[1330] The "server" determines whether to exempt the delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the delinquency screening is omitted. If this result is reached, the "server" sends the result to the "terminal."

[1331] Screen display and user notification

[1332] The "terminal" receives the judgment result from the "server" and displays it to the "user." For example, if the delinquency examination is omitted, the "user" is notified of this.

[1333] Specific examples

[1334] For example, suppose a "user" payer is registered in the system as "Yamada Taro" (an employee of a listed company) and makes payments on January 1st, April 1st, and July 1st. The "server" records this payment information, checks the regularity of the payments, and confirms that the payer is an employee of the listed company. Furthermore, the emotion engine analyzes Yamada Taro's voice data and facial expression data acquired by the "terminal" to recognize emotions such as stress.

[1335] The "server" decides whether to exempt the overdue payment review based on payment history, attribute information, and recognized emotions. The result is then displayed on the "terminal" and notified to the "user." As a result, if Yamada Taro is exempted from the overdue payment review, Yamada Taro can plan his next actions with peace of mind.

[1336] As described above, the system of the present invention efficiently judges and implements delinquent payment screening based on payment history patterns, payer attribute information, and user sentiment. This system significantly reduces time and costs compared to conventional methods, and reduces the burden on users.

[1337] The processing flow will be explained below.

[1338] Step 1:

[1339] The "user" enters payer information (name and attribute information) into the system. The "terminal" receives the information and sends it to the "server." The "server" saves the received payer information in a database. For example, it registers that the payer is Yamada Taro, who works for a listed company.

[1340] Step 2:

[1341] When a "user" makes a payment, they input the payment date. The "terminal" temporarily stores the payment date and sends it to the "server." The "server" receives the payment date information, saves it in a database, and updates the payment history. For example, payments made on January 1st, April 1st, and July 1st are recorded.

[1342] Step 3:

[1343] The "server" analyzes the accumulated payment history, calculating the interval between each payment date and checking whether it is between 85 and 95 days. For example, the interval between January 1st and April 1st is 90 days, and the interval between April 1st and July 1st is also 90 days.

[1344] Step 4:

[1345] The "server" evaluates the regularity of the recorded payment history. The "server" checks that the interval between each payment date is within a certain range and determines that the payment is regular. The result is stored in the database.

[1346] Step 5:

[1347] The server retrieves the payer's attribute information from the database and checks whether the payer is an employee of a listed company. This information is also saved as the evaluation result.

[1348] Step 6:

[1349] When a "user" makes a payment, the "terminal" transmits the user's voice and facial expressions to the emotion engine. The "server" receives this and uses the emotion engine to analyze the user's emotional state. For example, it evaluates whether the "user" is feeling stressed or relieved.

[1350] Step 7:

[1351] The Server adjusts the evaluation of the payment history based on the emotions recognized by the emotion engine, for example, if the User is stressed but still makes payments regularly, it takes into account their efforts.

[1352] Step 8:

[1353] The server determines whether to exempt the payment from the delinquency check based on the payment history regularity, the payer's attribute information, and the recognized emotion. If any one of the conditions is met, the payment from the delinquency check is omitted.

[1354] Step 9:

[1355] The "server" sends the result of the delinquency review to the "terminal." The "terminal" receives the result and notifies the "user." For example, it displays a message that the delinquency review has been waived.

[1356] Step 10:

[1357] The user checks the results. If the overdue payment screening is waived, the user can make their next payment plan and live their life with peace of mind.

[1358] As described above, the system of the present invention can efficiently conduct delinquency screening based on the regularity of payment history, the payer's attribute information, and the user's emotional state, thereby reducing the burden on the user.

[1359] Example 2

[1360] 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."

[1361] Conventional payment history management systems screen for delinquency based on payment history and payer attribute information, but do not consider the user's emotions. As a result, they often ignore the anxiety and stress users feel about payments, and a more human-like approach is needed. Furthermore, evaluating patterns and checking attribute information requires a lot of time and effort, making them inefficient. A new system that solves these issues is needed.

[1362] 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.

[1363] In this invention, the server includes a means for recording payment history, a means for evaluating the regularity of the recorded payment history, a means for saving and referencing the attributes of the payer, a means for recognizing the user's emotions, and a means for determining whether to skip the delinquency review based on the regularity of the payment history, the attributes of the payer, and the user's emotions. This enables a more humane and efficient delinquency review that takes into account the user's emotions in addition to the regularity of the payment history and the attribute information of the payer.

[1364] A "payment history" is a detailed record of the series of payments made by a user.

[1365] The "recording means" is a technique or device for storing the user's payment history in a storage device such as a database.

[1366] A "means for assessing regularity" is a technique or device that analyzes time intervals in recorded payment history and determines regularity based on certain patterns.

[1367] "Payer attributes" refers to basic information and details about the payer, including, for example, occupation and company affiliation.

[1368] "Means for storing and querying" refers to technology or equipment that can store payer attribute information in a database or the like and retrieve that information as needed.

[1369] "User emotions" refer to the psychological state or feeling a user has regarding a payment, and include, for example, stress or relief.

[1370] The "recognition means" refers to a technology or device for analyzing the user's voice and facial expression data and identifying their emotions.

[1371] "Delinquency screening" is the process of determining whether payments are likely to be delinquent based on the regularity of payment history and the attributes of the payer.

[1372] The "means for determining" is a technology or device that comprehensively evaluates the regularity of the payment history, the attributes of the payer, and the user's emotions, and determines whether or not to conduct a delinquency review.

[1373] The system of the present invention is designed to manage payment history and review delinquency efficiently and humanly. This system is composed of the following main components:

[1374] 1. A way to record payment history

[1375] This means records information about payments made by users (such as payment date and amount) and stores it in a database. Specifically, the payment information entered into the terminal is sent to a server, which then stores it in a database.

[1376] 2. A means of assessing the regularity of recorded payment history

[1377] This method analyzes the recorded payment history and evaluates the regularity of payments. Specifically, the server calculates the interval between each payment date and checks whether the interval falls within a certain range.

[1378] 3. Means for storing and querying payer attributes

[1379] This method stores basic information about the payer (e.g., company affiliation, occupation, etc.) in a database, making it possible to retrieve that information as needed. The attribute information entered by the terminal is sent to the server, which then stores it.

[1380] 4. How to Recognize User Emotions

[1381] This method captures and analyzes data such as voice and facial expressions to recognize the emotions the user feels when making a payment. For example, a camera or microphone installed on the terminal captures the user's voice and facial expressions and sends them to the emotion engine.

[1382] 5. How to determine whether to waive delinquency screening

[1383] This means determines whether to waive the overdue payment review based on the regularity of the payment history, the payer's attributes, and the user's sentiment. Specifically, the server comprehensively evaluates this information and decides whether to waive the overdue payment review.

[1384] Specific examples

[1385] For example, a user enters the payer information as "Yamada Taro" who belongs to "ABC Co., Ltd." Suppose Yamada Taro makes payments on January 1st, April 1st, and July 1st. This information is sent from the device to the server and stored in a database. The server verifies that the payment dates are three months apart. The device also acquires Yamada Taro's facial expressions and voice, and the emotion engine recognizes stress. Based on this information, the server decides to exempt Yamada Taro from the overdue payment screening because he makes payments regularly. This allows Yamada Taro to plan his next actions with peace of mind.

[1386] Prompt Sentence Examples

[1387] A prompt that explains, "A system in which users register their payer information and then screen for delinquent payments based on their payment history and sentiment":

[1388] Design a system that registers payer information and performs delinquent payment screening based on payment history and sentiment. Please provide a description including the names of specific hardware and software, and the process flow.

[1389] With the above configuration, the present invention makes it possible to realize a more humane and efficient delinquency screening process that takes into account the user's emotions in addition to the regularity of payment history and the payer's attribute information.

[1390] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1391] Step 1:

[1392] Enter and submit payer information

[1393] The user inputs the payer information, including name, address, company, occupation, etc., and this information is entered into the terminal.

[1394] Input: Payer information (name, address, company, occupation, etc.)

[1395] How it works: The device receives this information and checks its consistency.

[1396] Output: The verified payer information is sent to the server.

[1397] Step 2:

[1398] Payer information storage

[1399] The server receives the payer information sent from the terminal and stores it in a database.

[1400] Input: Validated payer information

[1401] Operation: The server confirms receipt of the data and records it in a database. It also registers whether the person is an employee of a publicly listed company.

[1402] Output: Payer information stored in the database

[1403] Step 3:

[1404] Enter and submit payment date information

[1405] When a user makes a payment, the user inputs the payment date.

[1406] Input: Payment information (payment date, amount, etc.)

[1407] How it works: The device temporarily stores the payment date information, checks to make sure the data is not lost, and then sends it to the server.

[1408] Output: Payment date information sent to the server

[1409] Step 4:

[1410] Save payment date information and update history

[1411] The server receives the payment date information, stores it in a database, and updates the payment history.

[1412] Input: Payment date information

[1413] Operation: The server adds the received payment date information to the database and updates the accumulated payment history.

[1414] Output: Updated payment history

[1415] Step 5:

[1416] Evaluating payment history regularity

[1417] The server analyzes the accumulated payment history and calculates the interval between payment dates to verify payment regularity.

[1418] Input: Updated payment history

[1419] How it works: The server calculates the time interval between each payment date and evaluates whether it falls within a certain range. For example, if payments are made on January 1st, April 1st, and July 1st, it verifies that the interval between each payment is approximately 3 months.

[1420] Output: Regularity evaluation result

[1421] Step 6:

[1422] Acquiring and analyzing emotion data

[1423] The device acquires emotional data such as the user's voice and facial expressions and sends it to the server, which then uses an emotion engine to recognize the user's emotions.

[1424] Input: User voice and facial expression data

[1425] How it works: The device collects this data and sends it to a server, which uses an emotion engine to analyze emotions and recognize feelings such as stress or relief.

[1426] Output: Recognized user emotion data

[1427] Step 7:

[1428] Adjusting ratings based on emotions

[1429] The server adjusts the evaluation of the payment history based on the recognized emotion. For example, if a user is stressed but still makes regular payments, the server will evaluate their efforts and ease the screening process for delinquency.

[1430] Input: Regularity evaluation results, recognized user emotion data

[1431] How it works: The server aggregates this data and adjusts the ratings to take into account payment regularity and emotional influence.

[1432] Output: Adjusted evaluation results

[1433] Step 8:

[1434] Final decision on delinquency review

[1435] The server performs a delinquency screening based on the regularity of the payment history, the payer's attribute information, and the recognized emotion, and determines whether to exempt the screening.

[1436] Input: Adjusted assessment results, payer attribute information

[1437] Action: Conduct a final delinquency review and determine the outcome.

[1438] Output: Final result of delinquency review

[1439] Step 9:

[1440] Displaying and notifying results

[1441] The terminal receives the result of the delinquency examination from the server and notifies the user.

[1442] Input: Final result of delinquency review

[1443] Behavior: The result is displayed to the user in an easy-to-understand manner. For example, a specific message such as "Your delinquent payment has been waived" is displayed.

[1444] Output: The result displayed to the user

[1445] The above processing steps realize efficient and human-like delinquency screening that takes into account the user's emotions and payment history.

[1446] (Application example 2)

[1447] 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."

[1448] Conventional payment management systems perform delinquency screening based solely on payment history and payer attribute information, and are therefore unable to take into account the stress and anxiety felt by users. This makes accurate screening difficult, and alleviating users' psychological burden has been an issue.

[1449] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for recording payment history, means for evaluating the regularity of the recorded payment history, means for saving and referencing the payer's attribute information, emotion engine means for analyzing the acquired emotion data, means for determining whether to skip the delinquency review based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data, and means for notifying the user of the result of the delinquency review. This enables more accurate delinquency review that takes into account not only the payment history and attribute information but also the user's emotions.

[1450] A "payment history recording means" is a system or device that digitally stores information about each payment made by a user.

[1451] The "means for evaluating the regularity of the recorded payment history" is a system or device that extracts patterns of payment dates and payment intervals from the stored payment history and analyzes the regularity of those patterns.

[1452] "Means for storing and querying payer attribute information" refers to a system or device that stores data such as the payer's personal information, occupation, and company affiliation in a database and can retrieve that information as needed.

[1453] The "emotion engine means for analyzing acquired emotion data" is a system or device that analyzes data such as the user's voice and facial expression, and identifies the emotional state at that time.

[1454] The "means for determining whether to skip the delinquency review" is a system or device that determines whether or not a delinquency review needs to be conducted based on the regularity of the payment history, the payer's attribute information, and the recognized emotion data.

[1455] The "means for notifying the user of the results of the delinquency review" refers to a system or device that receives the results of the review from the server and displays or notifies the results on the user's terminal.

[1456] To implement this invention, a server, a terminal, and a series of operations by the user are required. This system is realized using the following hardware and software.

[1457] Hardware

[1458] 1. Device:

[1459] Smartphone (e.g. iPhone, Android)

[1460] Devices with a camera and microphone

[1461] 2. Server:

[1462] Cloud servers (e.g. AWS, Google Cloud) and on-premise servers

[1463] software

[1464] 1. Smartphone app:

[1465] Applications that input and record payment information and collect emotional data

[1466] Speech and facial recognition software (e.g., Amazon Rekognition, Google Cloud Speech-to-Text)

[1467] 2. Server-side software:

[1468] Database management systems (e.g., MySQL, PostgreSQL)

[1469] Analysis Engine

[1470] Notification System

[1471] Data processing and calculation

[1472] 1. Payment History Record:

[1473] When a user enters payment information (date, amount, etc.) through a smartphone app, the app saves this information and sends it to a server, which then stores the received payment information in a database.

[1474] 2. Payment Regularity Assessment:

[1475] The server analyzes the payment history stored in the database and evaluates its regularity by calculating the interval between payment dates, which allows for the identification of payment patterns.

[1476] 3. Acquiring and analyzing emotion data:

[1477] The device's camera and microphone are used to capture the user's voice and facial expression data, which are then sent to the emotion engine, which determines whether the user is feeling stressed and sends the result to the server.

[1478] 4. Delinquency Review Judgment:

[1479] The server determines whether a delinquent payment review is necessary based on the regularity of the payment history, the payer's attribute information (e.g., type of workplace), and emotional data. The server notifies the smartphone app of the result of this determination and displays the result to the user.

[1480] Adding specific examples

[1481] For example, suppose a user enters payment information, including voice data, into the app on July 1st. The app sends the collected voice and payment information to the server. The server compares the user's past payment history and evaluates the payment interval. At the same time, the emotion engine analyzes the voice data and detects that the user is feeling stressed. Based on this information, the server decides to skip the overdue payment review and notifies the user of the result.

[1482] Prompt Sentence Examples

[1483] "Please develop a system that analyzes users' payment history and emotional data through a smartphone app and automatically exempts them from overdue payments. The emotional data includes facial expressions and voice data."

[1484] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1485] Step 1:

[1486] A user inputs payment information using a smartphone app. This input information includes payment date, amount, payee, etc. The terminal temporarily stores this input data and sends it to the server. The date and amount are sent as input data, and the server stores them in a database as data processing. The output is a payment record stored in the database.

[1487] Step 2:

[1488] The terminal captures voice and facial expression data. While the user is entering payment information, the camera and microphone are activated to collect the user's facial expression data and voice data. The voice and facial expression data captured as input data is sent to the emotion engine, where emotion analysis is performed as data calculation. The output is the user's emotional state.

[1489] Step 3:

[1490] The server evaluates the regularity of the payment history. It analyzes the payment history stored in the database and calculates the interval between payment dates. The timestamp of each payment date is used as input data, and the calculation of the time interval is performed as data processing. The output is the result of the payment regularity evaluation.

[1491] Step 4:

[1492] The server queries the payer's attribute information. It retrieves the payer's attribute information stored in the database and checks the user's occupation, company affiliation, etc. The payer ID is used as input data, and attribute information is extracted as data processing. The output is the payer's attribute information.

[1493] Step 5:

[1494] The server combines all the information and makes a decision on whether or not to conduct a delinquent payment review. It decides whether or not to conduct a delinquent payment review based on the results of the regularity evaluation of the payment history, the payer's attribute information, and emotional data. The regularity evaluation results, attribute information, and emotional state are used as input data, and conditional judgments are performed as data calculations. The output is the decision on whether or not to conduct a delinquent payment review.

[1495] Step 6:

[1496] The user is notified of the results of the delinquency review. The server sends the results of the delinquency review to the terminal, which then displays the results to the user. The results of the delinquency review are used as input data, and notification data is generated as data processing. The output is notification information displayed to the user.

[1497] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice 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 voice data.

[1498] 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.

[1499] 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 robot 414.

[1500] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1501] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1502] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1503] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1504] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1505] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1506] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1507] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1508] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1509] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1510] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1511] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1512] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1513] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1514] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1515] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1516] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1517] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1518] The following is further disclosed regarding the above embodiment.

[1519] (Claim 1)

[1520] a means of recording payment history;

[1521] a means of assessing the regularity of the recorded payment history;

[1522] A means for storing and querying payer attribute information;

[1523] A means for determining whether to skip the delinquency examination based on the regularity of the payment history and the attribute information of the payer;

[1524] A system including:

[1525] (Claim 2)

[1526] 2. The system of claim 1, wherein the means for evaluating the regularity of the recorded payment history evaluates the regularity based on intervals between payment dates.

[1527] (Claim 3)

[1528] The system according to claim 1, wherein the attribute information of the payer includes whether the payer is an employee of a publicly traded company.

[1529] "Example 1"

[1530] (Claim 1)

[1531] A means for inputting payer information and storing payer attribute information;

[1532] a means for entering payment dates and recording payment history;

[1533] a means for assessing the regularity of the recorded payment history based on intervals between payment dates;

[1534] A means for determining whether to skip the delinquency examination based on the regularity of the payment history and the attribute information of the payer;

[1535] Notification means;

[1536] A system including:

[1537] (Claim 2)

[1538] 2. The system of claim 1, wherein the means for evaluating the regularity of the recorded payment history includes means for evaluating the regularity based on intervals between payment dates.

[1539] (Claim 3)

[1540] 2. The system of claim 1, wherein the payer's attribute information includes whether the payer is an employee of a particular company.

[1541] "Application Example 1"

[1542] (Claim 1)

[1543] a means of recording payment history;

[1544] a means of assessing the regularity of the recorded payment history;

[1545] A means for storing and querying payer attribute information;

[1546] A means for determining whether to skip the delinquency examination based on the regularity of the payment history and the attribute information of the payer;

[1547] a means for quickly executing electronic payment using the determination result;

[1548] A system including:

[1549] (Claim 2)

[1550] 2. The system of claim 1, wherein the means for evaluating the regularity of the recorded payment history evaluates the regularity based on intervals between payment dates.

[1551] (Claim 3)

[1552] The system according to claim 1, wherein the attribute information of the payer includes whether the payer is an employee of a publicly traded company.

[1553] "Example 2: Combining Emotion Engines"

[1554] (Claim 1)

[1555] a means of recording payment history;

[1556] a means of assessing the regularity of the recorded payment history;

[1557] A means for storing and querying attributes of a payer;

[1558] means for recognizing a user's emotion;

[1559] a means for determining whether to skip the delinquency examination based on the regularity of the payment history, the attributes of the payer, and the user's feelings;

[1560] A system including:

[1561] (Claim 2)

[1562] 2. The system of claim 1, wherein the means for evaluating the regularity of the recorded payment history evaluates the regularity based on intervals between payment dates.

[1563] (Claim 3)

[1564] 2. The system of claim 1, wherein the attributes of the payer include whether the payer is an employee of a particular company.

[1565] "Application example 2 when combining emotion engines"

[1566] (Claim 1)

[1567] a means of recording payment history;

[1568] a means of assessing the regularity of the recorded payment history;

[1569] A means for storing and querying payer attribute information;

[1570] emotion engine means for analyzing the acquired emotion data;

[1571] a means for determining whether to omit the delinquency examination based on the regularity of the payment history, the attribute information of the payer, and the recognized emotion data;

[1572] A means for notifying the user of the result of the delinquency examination;

[1573] A system including:

[1574] (Claim 2)

[1575] 2. The system of claim 1, wherein the means for evaluating the regularity of the recorded payment history evaluates the regularity based on intervals between payment dates.

[1576] (Claim 3)

[1577] The system according to claim 1, wherein the attribute information of the payer includes whether the payer is an employee of a publicly traded company. [Explanation of symbols]

[1578] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means of recording payment history; a means of assessing the regularity of the recorded payment history; A means for storing and querying payer attribute information; A means for determining whether to skip the delinquency examination based on the regularity of the payment history and the attribute information of the payer; A system including:

2. 2. The system of claim 1, wherein the means for evaluating the regularity of the recorded payment history evaluates the regularity based on intervals between payment dates.

3. The system according to claim 1 , wherein the attribute information of the payer includes whether the payer is an employee of a publicly traded company.

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