Information processor, information processing method, and program

Abstract

To improve a service by reducing the frequency of inquiries.SOLUTION: An information processor comprises: an acquiring unit that acquires information for determination, including payment history information of a user in an electronic payment service and history information of inquiries made by the user to a business operator of the electronic payment service; and a determination unit which inputs the information for determination into a learned model generated based on training data including payment history information of the user in the electronic payment service and the history information of inquiries made by the user to the business operator of the electronic payment service, and on teacher data indicating whether the user has made inquiries to the business operator, thereby outputting a determination result indicating whether the user pertaining to the information for determination is expected to make inquiries to the business operator in the future.SELECTED DRAWING: Figure 7

Description

[Technical field]

[0001] The present invention relates to an information processing device, an information processing method, and a program. [Background technology]

[0002] Conventionally, in the field of electronic commerce, the task of answering user inquiries has been carried out by setting up call centers or departments that respond to inquiries via email (including both human and automated responses) (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2014-42158 A Summary of the Invention [Problem to be solved by the invention]

[0004] The current response to inquiries is passive, and the basic approach is to wait for inquiries from users. The occurrence of inquiries can lead to various problems, such as higher operational costs for electronic payment operators, slower operational speed, and difficulty in creating new services using data held by electronic payment operators. For example, outsourcing to call centers requires a large amount of cost, and reducing this cost would allow investment in further services. Regarding automatic responses, although there are methods that automatically segment the content and send notifications, there was nothing that could realistically solve the issues users felt.

[0005] The present invention has been made in consideration of the above circumstances, and one of its objectives is to provide an information processing device, an information processing method, and a program that can improve service by reducing the frequency of inquiries. [Means for solving the problem]

[0006] One aspect of the present invention is an information processing device that includes an acquisition unit that acquires judgment information including payment history information of a user in an electronic payment service and history information of inquiries made by the user to a provider of the electronic payment service, and a judgment unit that inputs the judgment information into a trained model generated based on learning data including the payment history information of the user in the electronic payment service and history information of inquiries made by the user to the provider of the electronic payment service, and teacher data indicating whether the user has made an inquiry to the provider, and outputs a judgment result indicating whether the user related to the judgment information is expected to make an inquiry to the provider in the future. Effect of the Invention

[0007] According to one aspect of the present invention, it is possible to improve service by reducing the frequency of inquiries. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram showing an example of a configuration for realizing an electronic payment service. [Diagram 2] This is a sequence diagram (part 1) illustrating the general flow of electronic payment. [Diagram 3] This is a sequence diagram (part 2) illustrating the general flow of electronic payment. [Figure 4] 1 is a configuration diagram of a payment server 100 according to a first embodiment. [Diagram 5] FIG. 13 is a diagram showing an example of the contents of user information 172. [Figure 6] FIG. 13 is a diagram showing an example of the contents of affiliated store / store information 176. [Figure 7] FIG. 2 is a diagram illustrating a configuration of an information processing device 200. [Figure 8] FIG. 2 is a diagram conceptually showing the processing of a preprocessing unit 220 and a model generating unit 230. [Figure 9] 13 is a flowchart showing an example of a process flow in an inference stage. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, with reference to the drawings, an embodiment of an information processing device, an information processing method, and a program of the present invention will be described. In the following description, an application program and a payment server work together to provide an electronic payment service. In the following description, the application program is referred to as a payment application. The electronic payment service is a service that supports payments related to the purchase of goods and services at a store. The store is, for example, a physical store (real store) existing in real space, but may also include a virtual store of electronic commerce. The virtual store may also include a store provided by an entity different from the operator of the electronic payment service. In that case, when making a payment for shopping at the virtual store, the screen is controlled to transition to an interface screen of the electronic payment service. In the electronic payment service, the store is treated as belonging to, for example, an affiliated store (brand), and processing such as payment when a purchase is made at the store is mainly performed between the user and the affiliated store. Alternatively, processing such as payment may be performed between the user and the store.

[0010] [Electronic payment service] Fig. 1 is a diagram showing an example of a configuration for realizing an electronic payment service. The electronic payment service is realized mainly by a payment server 100. The payment server 100 communicates with, for example, one or more user terminal devices 10, one or more first store terminal devices 50, and one or more second store terminal devices 70 via a network NW. The network NW includes, for example, the Internet, a LAN (Local Area Network), a wireless base station, a provider device, and the like.

[0011] The user terminal device 10 is, for example, a portable terminal device such as a smartphone or a tablet terminal. The user terminal device 10 is a computer device having at least an optical reading function, a communication function, a display function, an input reception function, and a program execution function. In the following description, components for realizing these functions are referred to as a camera, a communication device, a touch panel, a CPU (Central Processing Unit), etc. In the user terminal device 10, a processor such as a CPU executes a payment application 20, thereby operating to provide an electronic payment service to a user in cooperation with a payment server 100. The payment application 20 is installed in the user terminal device 10 from, for example, an application store, and controls the camera, communication device, touch panel, etc.

[0012] The first store terminal device 50 is installed, for example, in a store. The first store terminal device 50 is a computer device having at least a product price acquisition function, an optical reading function, a program execution function, and a communication function. The first store terminal device 50 includes a so-called POS (Point of Sale) device, and the product price acquisition function and the optical reading function may be realized by the POS device. The store code image 60 is placed in the store, and is a code image such as a QR code (registered trademark) printed on a paper or plastic medium. The store code image 60 may be displayed on a display placed in the store (which may be the display of a terminal device such as a smartphone).

[0013] The second store terminal device 70 is used by the operator of the affiliated store. The second store terminal device 70 is a smartphone, a tablet terminal, a personal computer, or the like. An interface 72 for affiliated stores runs on the second store terminal device 70. The interface 72 for affiliated stores may be an app for affiliated stores or a browser. The interface 72 for affiliated stores accepts coupon settings and the like made by the operator of the affiliated store and transmits them to the payment server 100. The second store terminal device 70, which is a smartphone, has the function of displaying a code image corresponding to a store code image and reading a code image displayed by the user terminal device 10 by executing the app for affiliated stores.

[0014] The payment server 100 realizes electronic payment based on payment information received from the user terminal device 10 or the first store terminal device 50. The first store terminal device 50 may include a POS device and an affiliated store server, in which case the payment information is sent from the POS device via the affiliated store server to the payment server 100. In the following explanation, no distinction is made between these two and it is assumed that the payment information is sent from the first store terminal device 50.

[0015] 2 and 3 are sequence diagrams illustrating the general flow of electronic payment. There may be two patterns of electronic payment: pattern 1 and pattern 2.

[0016] In the case of pattern 1 (hereinafter referred to as user scan) shown in FIG. 2, the user terminal device 10 with the payment application 20 activated decodes the store code image 60 by the optical reading function (S1). The store code image 60 includes store URL (Uniform Resource Locator) information. This store URL is an electronic payment service domain to which store-identifying information is added, and is associated with an affiliated store ID, a store ID, etc. in the payment server 100 (described later). The payment application 20 transmits the first payment information including the store URL and the account ID to the payment server 100 (S2). The payment server 100 searches for store information (described later) from the affiliated store ID and the store ID corresponding to the store URL, acquires the affiliated store name and the store name information (S3), and transmits it to the payment application 20 (S4). The user inputs the payment amount into the user terminal device 10 on the screen on which the affiliated store name and the store name are displayed (S5). Then, the user terminal device 10 generates second payment information including at least the payment amount, and transmits it to the payment server 100 (S6). The payment server 100 performs electronic payment based on the received second payment information (S7). The payment server 100 then transmits a payment completion notice (information for displaying a payment completion screen) to the payment application 20 (S8), and the payment application 20 displays the payment completion screen (S9). Note that when the store code image 60 is displayed on a display installed in the store, the store code image 60 may include not only the store URL but also information on the payment amount. In this case, the procedure in which the user inputs the payment amount is omitted, and the information on the payment amount is included in the first payment information and transmitted to the payment server 100. Information on the affiliated store name and the store name may be included in the payment completion screen and displayed.

[0017] In the case of pattern 2 (hereinafter referred to as store scan) shown in FIG. 3, when the payment application 20 is started, when a payment operation is performed in the payment application 20, when an automatic update timing (e.g., every minute) occurs, and at other timings, the payment application 20 transmits a request for issuing a one-time code to the payment server 100 (S11). The payment server 100 generates a one-time code (S12) and transmits it to the payment application 20 (S13). The payment application 20 displays a code image such as a QR code or a barcode generated based on the one-time code (S14). The user holds (presents) the display surface of the user terminal device 10 over the first store terminal device 50, and the first store terminal device 50 decodes the code image by an optical reading function and obtains the one-time code, etc. (S15). The first store terminal device 50 then generates payment information including the one-time code, payment amount, affiliated store ID, store ID, etc., and transmits it to the payment server 100 (S16). The payment amount information is acquired in advance by reading a barcode or manually entering it. The payment server 100 identifies the user corresponding to the one-time code based on the received information and performs electronic payment (S17). The payment server 100 then transmits a payment completion notice to the payment application 20 (S18), and the payment application 20 displays a payment completion screen (S19).

[0018] Note that electronic payment may be performed using only one of the above patterns. Furthermore, the "account ID" described in FIG. 2 may be other information (e.g., a phone number) that can be used as user identification information. Furthermore, issuance of a one-time code may be omitted in the store scan, and the payment application 20 may display a code image generated based on the user's account ID. In this case, the payment server 100 identifies the user corresponding to the account ID instead of identifying the user corresponding to the one-time code.

[0019] In addition, the payment server 100 transmits various information to the information processing device 200 and acquires processing results of the information processing device 200. Although the information processing device 200 and the payment server 100 are shown as separate devices in FIG. 1, the information processing device 200 may be an internal function of the payment server 100.

[0020] [Payment server] FIG. 4 is a configuration diagram of the payment server 100 according to the first embodiment. The payment server 100 includes, for example, a communication unit 110, a payment content providing unit 120, a payment processing unit 130, an information management unit 140, an automatic response unit 150, and a storage unit 170. The components other than the communication unit 110 and the storage unit 170 are realized by, for example, a hardware processor such as a CPU executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or a GPU (Graphics Processing Unit), or may be realized by cooperation between software and hardware. The program may be stored in advance in a storage device (a storage device with a non-transient storage medium) such as an HDD (Hard Disk Drive) or flash memory, or may be stored in a removable storage medium (non-transient storage medium) such as a DVD or CD-ROM, and installed in the storage device by inserting the storage medium into a drive device.

[0021] The storage unit 170 is a HDD, a flash memory, a RAM (Random Access Memory), etc. The storage unit 170 may be a NAS (Network Attached Storage) device that the payment server 100 can access via a network. The storage unit 170 stores information such as user information 172, payment content information 174, and affiliated store / shop information 176.

[0022] The communication unit 110 is a communication interface for connecting to the network NW. The communication unit 110 is, for example, a network interface card.

[0023] The payment content providing unit 120 has, for example, a function of a Web server, and provides information (content) for displaying various screens of the electronic payment service to the user terminal device 10. The payment content providing unit 120 appropriately reads necessary content from the payment content information 174 and provides it to the user terminal device 10. The user terminal device 10 accepts various inputs by the user while the content is being played by the payment application 20, and transmits the above-mentioned payment information and the like to the payment server 100.

[0024] The payment processing unit 130 performs payment processing based on the payment information transmitted by the user terminal device 10 or the first store terminal device 50. The payment processing unit 130 performs payment processing while referring to the user information 172.

[0025] FIG. 5 is a diagram showing an example of the contents of the user information 172. The user information 172 is an example of the registration information of a user. The user information 172 is, for example, a user URL, an account ID, a telephone number, a password, as well as information associated with an email address, a user ID, a name, an address, a date of birth, a registration date, a charge balance, a post-payment setting, a post-payment limit, a post-payment usage amount, a post-payment available amount, a payment method setting, a bank account, a credit card number, a charge history information, and a payment history information. The user URL is used for a remittance process between users. When registering for the electronic payment service, it is necessary to register a telephone number and a password. The account ID is issued to the user by the payment server 100, and the user ID is an ID that can be set by the user at will (does not have to be set). Similarly, the email address, and the name, address, and date of birth are information that can be set by the user at will (does not have to be set). The registration date is the date on which the user registered for the electronic payment service (the date on which the account was created). Hereinafter, the user's instance (electronic payment account) to which this information is associated will be referred to as an account.

[0026] The charge balance is information indicating the balance of electronic money that is set by a user by transferring money to an account in advance. Methods of transfer include transfer from an ATM (Automatic Teller Machine) of a designated business (bank) and transfer from a registered bank account. The deferred payment setting is information indicating whether or not the setting for enabling deferred electronic payment has been completed, and is set to either "completed" or "not completed." The payment method setting is setting information indicating whether the user will make electronic payment from the charge balance or deferred payment at that time. The bank account and credit card number are information on a bank account or credit card number (account number, card number) that can be deposited into an electronic payment service. The charge history information is a history of the user transferring money to an electronic payment service in advance to increase the charge balance. The payment history information is information indicating the details of the payment made by the user (date and time, store ID of the store where the purchase was made, payment amount, payment method, etc.) for each payment.

[0027] The FAQ inquiry history is information indicating inquiries made by users in response to FAQs (Frequently Asked Questions) entered into a website provided by payment application 20 or payment server 100, and a history of responses thereto by automatic response unit 150. The automatic response inquiry history is information indicating inquiries made by users by free text entered into a website provided by payment application 20 or payment server 100, and a history of responses thereto by automatic response unit 150.

[0028] 6 is a diagram showing an example of the contents of affiliated store / store information 176. The affiliated store / store information 176 includes, for example, a first table 176A in which an affiliated store ID and a store ID are associated with a store URL, a second table 176B in which an affiliated store name and sales amount (described above) are associated with an affiliated store ID, and a third table 176C in which a store ID is associated with a store ID. In addition to this information, the affiliated store / store information 176 may also include information such as the category of the affiliated store or store, the location of the store, and payment patterns.

[0029] The information management unit 140 manages user information 172 and affiliated store / store information 176 based on information acquired from the user terminal device 10 and the second store terminal device 70. The information management unit 140 adds new records to, edits, and deletes the user information 172 and affiliated store / store information 176.

[0030] In response to an inquiry via FAQ, the automatic response unit 150 returns a predetermined response to the user terminal device 10. In addition, in response to an inquiry via free text, the automatic response unit 150 performs morphological analysis, semantic interpretation, etc. to categorize the inquiry, and returns a predetermined response to the categorized inquiry to the user terminal device 10.

[0031] [Electronic payment] When payment information is acquired from the user terminal device 10 or the first store terminal device 50, the payment processing unit 130 refers to the user information 172 to acquire the "payment method setting" of the user. For a user whose "payment method setting" is set to "charge balance", the payment processing unit 130 performs electronic payment as follows. For example, the payment processing unit 130 performs electronic payment by decreasing the charge balance managed in association with the user ID and increasing the item value of the affiliated store's sales. The item value of the affiliated store's sales is not used as electronic money itself, for example, and an amount corresponding to the item value of the sales is transferred to a bank account in a cycle according to an agreement between the affiliated store and the electronic payment service.

[0032] The payment processing unit 130 performs electronic payment for users whose "setting information" is set to "deferred payment" as follows. Deferred payment is set separately from "credit payment" in cooperation with a credit card company, which is a separate entity from the operator of the electronic payment service, and the operator of the electronic payment service acts as a creditor and allows electronic payment that is not dependent on the charge balance within the deferred payment limit. In order to receive the deferred payment service, a credit card provided by the operator of the electronic payment service may be required. The amount used for deferred payment is settled on the payment date of the following month, for example, by debiting from a bank account, for one month. In this case, the payment processing unit 130 performs provisional payment by adding the payment amount to the deferred payment amount and subtracting the same amount from the available deferred payment amount, and when the closing date comes, it performs processing to debit the payment for the current month on the payment date of the following month as described above, or requests the operator of the credit card company to perform such processing. In addition, if the payment amount exceeds the available deferred payment amount at the time of provisional payment, an error notification is returned to the payment application 20.

[0033] [Information processing device] FIG. 7 is a configuration diagram of the information processing device 200. The information processing device 200 includes, for example, an acquisition unit 210, a model generation unit 230, a determination unit 240, a guidance unit 250, and a storage unit 270. The acquisition unit 210 includes a preprocessing unit 220. The components other than the storage unit 270 are realized by, for example, a hardware processor such as a CPU executing a program (software). Some or all of these components may be realized by hardware (including circuitry) such as an LSI, ASIC, FPGA, or GPU, or may be realized by cooperation between software and hardware. The program may be stored in advance in a storage device such as an HDD or flash memory (a storage device having a non-transient storage medium), or may be stored in a removable storage medium such as a DVD or CD-ROM (a non-transient storage medium), and may be installed in the storage device by mounting the storage medium in a drive device.

[0034] The storage unit 270 is a HDD, a flash memory, a RAM (Random Access Memory), etc. The storage unit 270 may be a NAS device that the information processing device 200 can access via a network. The storage unit 270 stores information such as a training dataset 272, model setting information 274, and a trained model 276.

[0035] [Learning stage] The functions of each unit of the information processing device 200 will be described below, divided into a learning stage and an inference stage. In the learning stage, the acquisition unit 210 acquires various data that will be the original data of the learning dataset 272 from the payment server 100 or the like. The original data includes, for example, payment history information of the user in the electronic payment service and history information of inquiries made by the user to the electronic payment service provider. The original data may further include various information acquired via the payment application 20 (application data such as version data of the payment application 20, web browsing history acquired by the payment application 20 in cooperation with a browser, SNS data, location data, personal information of the user held by the electronic payment service, etc.). When some of these are used, it is preferable to obtain the consent of the user. The learning dataset 272 is obtained by associating the learning data 272A with the teacher data 272B (described in detail later).

[0036] The preprocessing unit 220 performs preprocessing on the original data to generate a learning dataset 272. FIG. 8 is a diagram conceptually showing the processing of the preprocessing unit 220 and the model generation unit 230. The preprocessing unit 220 first classifies the original data into data that is to be subjected to normalization processing and data that is to be subjected to label encoding processing. Note that there may be original data that is to be subjected to both normalization processing and label encoding processing. Furthermore, when a user makes an inquiry to a business operator of an electronic payment service, the original data may be limited to information collected at a timing prior to the inquiry.

[0037] Normalization processing involves multiplying or dividing original data expressed as numbers, such as the number of payment errors or correlation with campaign timing, so that the data has a distribution with a mean of zero and a standard deviation of one.

[0038] The label encoding process is to set a flag, such as 1 if the original data represents a certain event, or zero if the original data does not represent a certain event, as the value of a specific element in a vector constituting the learning data 272A. For example, if the data obtained by categorizing FAQ data or automatic response data corresponds to "an inquiry about XX was made", the preprocessing unit 220 sets the value of an element corresponding to the event in the vector to 1. Similarly, if the user opinion data collected from users corresponds to "an opinion about XX was posted", the preprocessing unit 220 sets the value of an element corresponding to the event in the vector to 1. Specifically, the above-mentioned "event" includes situations such as a failure of payment at a shopping business affiliated with an electronic payment service, not receiving points in a campaign, and not being able to make a payment when switching cards affiliated with an electronic payment service.

[0039] Then, the preprocessing unit 220 generates learning data 272A for each user by concatenating the vector obtained as a result of the normalization process with the vector obtained as a result of the label encoding process. The learning data 272A thus created includes payment history information of the user in the electronic payment service and history information of inquiries made by the user to the electronic payment service provider. The learning data 272A may further include various information acquired via the payment application 20.

[0040] The model generation unit 230 generates a trained model 276 based on training data 272A for each user and training data 272B for the same user. Training data 272B is data indicating whether or not the user has made an inquiry to the electronic payment service provider. In this case, "inquiry" includes some or all of telephone responses by an operator, automatic responses, and FAQs. The number of elements in the training data 272A is equal to the number of input nodes specified by the model setting information 274. The model setting information 274 is information that specifies the number of input nodes, the number of output nodes, the connection state of intermediate nodes, and the like of the machine learning model that is the basis of the trained model 276.

[0041] The model generation unit 230 learns the parameters of the machine learning model by a method such as backpropagation so that the output of the machine learning model when the learning data 272A is used as input data approaches the teacher data 272B. The output of the machine learning model is a value indicating the probability that the user will make the above-mentioned "inquiry" in the future. The model generation unit 230 learns the parameters of the machine learning model so that the output of the machine learning model approaches 1 for users who have made an "inquiry" and approaches 0 for users who have not made an "inquiry." For example, the machine learning model at the time when the above process has been executed a specified number of times is determined as the trained model 276.

[0042] [Inference stage] The acquisition unit 210 acquires information for determination for a user to be determined by the determination unit 240. The information for determination is information obtained by performing the same processing as described above by the preprocessing unit 220 on the basis of the same original data as the learning data 272A.

[0043] The judgment unit 240 inputs judgment information into the trained model 276 generated by the model generation unit 230, and outputs a judgment result (probability of making an inquiry) indicating whether or not the user related to the judgment information is expected to make an inquiry to the electronic payment service provider in the future.

[0044] When the determination unit 240 outputs a determination result (e.g., a probability equal to or greater than a threshold) indicating that an inquiry is expected to be made to an electronic payment service provider, the guidance unit 250 outputs information to the user terminal device 10 of the user related to the determination result, which provides information on an inquiry method that does not require a response from an operator. The guidance unit 250 transmits identification information of the user to be guided to the payment server 100, and the payment content providing unit 120 displays the above guidance on the payment application 20. This display mode can be various modes, such as push notification and display within the interface screen of the payment application 20. At this time, the guidance unit 250 may switch the content of the guidance (which mode of inquiry is recommended) according to the attributes of the user (such as age group). For example, a relatively easy-to-use FAQ may be push-notified to the elderly.

[0045] FIG. 9 is a flowchart showing an example of the flow of the processing in the inference stage. The processing of this flowchart is executed for multiple users at once, for example, about once a day. First, the acquisition unit 210 acquires the original data of the information for judgment (S300). Next, the preprocessing unit 220 performs normalization processing and label encoding processing to generate information for judgment (S302). Next, the judgment unit 240 inputs the information for judgment to the trained model 276 (S304). Next, the guidance unit 250 judges whether the output of the trained model 276 is equal to or greater than a threshold (S306). If the output of the trained model 276 is equal to or greater than the threshold, the guidance unit 250 causes the payment application 20 of the user terminal device 10 of the user related to the judgment result to output information informing about an inquiry method that does not require a response from an operator (S308).

[0046] By carrying out such processing, the frequency of inquiries can be reduced, and the electronic payment service can be improved. As described above, the trained model 276 is generated so that the output of the machine learning model approaches 1 for users who have made an "inquiry" and approaches 0 for users who have not made an "inquiry." The trained data used includes payment history information of the user in the electronic payment service and history information of inquiries made by the user to the electronic payment service provider, and therefore the model is expected to be capable of outputting significant results. As a result, by inputting judgment information into the trained model 276, it is possible to estimate with high accuracy whether or not the user will make an "inquiry," and it is also possible to provide various kinds of guidance to users who are likely to make an "inquiry" in advance. As a result, the frequency of inquiries can be reduced as described above, and the electronic payment service can be improved.

[0047] The above describes the form for carrying out the present invention using an embodiment, but the present invention is not limited to such an embodiment, and various modifications and substitutions can be made within the scope that does not deviate from the gist of the present invention. [Explanation of symbols]

[0048] 10 User terminal device 20. Payment App 100 Payment Server 120 Payment Contents Provider 130 Payment processing unit 140 Information Management Department 150 Auto-Response Unit 200 Information processing device 210 Acquisition Department 220 Pretreatment section 230 Model Generation Unit 240 Judgment section 250 Information Department 270 Storage section 272 Training Dataset 274 Model setting information 276 trained models

Claims

1. An acquisition unit that acquires determination information including the user's payment history information in an electronic payment service and the history information of inquiries made by the user to the provider of the electronic payment service, A determination unit that outputs a determination result indicating the probability of whether or not the user related to the determination information is expected to make an inquiry to the business operator in the future, based on the payment history information and the inquiry history information included in the determination information; The system includes a guidance unit that, when the determination unit outputs a determination result indicating a high probability, causes the guidance unit to output guidance information to the terminal device of the user related to that determination result. The guidance unit switches the content of the guidance information according to the user's attributes. Information processing device.

2. The user's attributes include information indicating the user's age group, The guidance unit, when the user's age group is elderly, will output the guidance information to the user's terminal device in a manner appropriate for the elderly. The information processing apparatus according to claim 1.

3. The guidance unit outputs the guidance information to the user's terminal device by push notification or display on the interface screen of an application executed on the user's terminal device. The information processing apparatus according to claim 1.

4. The payment history information includes information indicating at least one of the following: that a payment at a shopping business partnered with the electronic payment service failed, that points were not awarded in a campaign, and that a payment could not be made when switching cards partnered with the electronic payment service. The information processing apparatus according to claim 1.

5. The inquiry includes, in part or in whole, telephone support by an operator, automated response, and FAQ. The information processing apparatus according to claim 1.

6. The determination unit outputs the determination result by inputting the determination information into a trained model generated based on training data including the user's payment history information in the electronic payment service and the history information of inquiries made by the user to the provider of the electronic payment service, and training data indicating whether or not the user has made an inquiry to the provider. The information processing apparatus according to claim 1.

7. Information processing device, The system acquires determination information that includes the user's payment history information in the electronic payment service and the history information of inquiries the user has made to the provider of the electronic payment service. Based on the payment history information and inquiry history information included in the determination information, a determination result indicating the probability of whether or not the user related to the determination information is expected to make an inquiry to the business operator in the future is output. If a judgment result indicating a high probability is output, the terminal device of the user to which the judgment result relates will be instructed to output guidance information. The content of the guidance information is switched according to the attributes of the user. Information processing methods.

8. In the processor of the information processing device, The system obtains determination information that includes the user's payment history information in the electronic payment service and the history information of inquiries the user has made to the provider of the electronic payment service. Based on the payment history information and inquiry history information included in the determination information, a determination result indicating the probability of whether or not the user related to the determination information is expected to make an inquiry to the business operator in the future is output. If a judgment result indicating a high probability is output, the terminal device of the user to which the judgment result relates will be instructed to output guidance information. The content of the guidance information is switched according to the attributes of the user. A program for that purpose.

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