JP2020166644A - Transaction support system, transaction support method, and transaction support program - Google Patents

Abstract

To provide a transaction support system, a transaction support method, and a transaction support program for supporting efficient transactions of users.SOLUTION: A control unit 21 of a support server 20 uses location information, timing information, and transaction content of transaction history recorded in a history information storage unit 23 to generate a prediction model that predicts transaction content from location and timing. Then, a control unit 11 of a user terminal 10 predicts the behavior of a user, from current location and present date and time, using the prediction model, specifies settlement means to be used for a transaction in the predicted behavior by using a personal information storage unit 15, specifies linkage information to be used for the transaction by the settlement means, and executes transaction processing with a transaction device 30.SELECTED DRAWING: Figure 1

Description

The present invention relates to a transaction support system, a transaction support method, and a transaction support program for supporting a user's transaction.

When a user makes a transaction, he / she may make a transaction using a payment card such as a cash card or a credit card. In this case, a technique for determining a card to be used for payment among a plurality of cards is being studied (see, for example, Patent Documents 1 and 2). In the technique described in Patent Document 1, the card usage history related to the card stored in the device is acquired, the information related to the payment environment of the device is acquired, and the information related to the acquired payment environment and the stored information are stored. The card used for payment is determined based on the card usage history, and the payment information related to the determined card is provided to the POS terminal.

Further, in the technique described in Patent Document 2, a plurality of credit card information corresponding to a plurality of credit card payment services is stored in a credit card information storage unit in a mobile terminal. The credit card priority storage unit stores the priority of each credit card type, and the credit card information selection unit selects the credit card type to be used according to the priority of the credit card priority storage unit. The credit card usage limit monitoring unit monitors whether the cumulative usage amount of the credit card type with the highest priority at that time exceeds the usage limit, and if so, the priority of the credit card priority storage unit. To change.

Japanese Unexamined Patent Publication No. 2014-44719 International Publication No. 2007/116521

However, the payment method to be selected may be changed depending on the behavior pattern of the user. Furthermore, efficient transactions may not be realized with card information alone. Furthermore, it may be necessary to provide user information at the time of transaction. However, if it takes time to provide user information, smooth transactions cannot be realized.

The transaction support system that solves the above problems includes a personal information storage unit that stores the user's payment means and linkage information, a history information storage unit that stores the user's transaction history, and a control unit that is connected to the transaction device. The control unit uses the location information, time information, and transaction content of the transaction history recorded in the history information storage unit to generate a prediction model that predicts the transaction content from the location and time, and from the current location and the current date and time, The prediction model is used to predict the user's behavior, the personal information storage unit is used to identify the payment means used for the transaction in the predicted behavior, and the personal information storage unit is used to perform the transaction by the payment means. The linkage information used for is specified, and transaction processing is executed with the transaction device.

According to the present invention, a user can efficiently carry out a transaction by using various payment means.

Explanatory drawing of the transaction support system of 1st Embodiment. The explanatory view of the hardware configuration of 1st Embodiment. The explanatory view of the processing procedure of 1st Embodiment. The explanatory view of the processing procedure of 1st Embodiment. Explanatory drawing of the transaction support system of 2nd Embodiment. The explanatory view of the processing procedure of 2nd Embodiment.

(First Embodiment)
Hereinafter, the first embodiment in which the transaction support system, the transaction support method, and the transaction support program are embodied will be described with reference to FIGS. 1 to 4.
Here, as shown in FIG. 1, a user terminal 10, a support server 20, and a trading device 30 are used.

(Explanation of hardware configuration)
The hardware configuration of the information processing apparatus H10 constituting the user terminal 10, the support server 20, and the trading apparatus 30 will be described with reference to FIG. The information processing device H10 includes a communication device H11, an input device H12, a display device H13, a storage unit H14, and a processor H15. This hardware configuration is an example, and can be realized by other hardware.

The communication device H11 is an interface that establishes a communication path with another device and executes data transmission / reception, such as a network interface card or a wireless interface.

The input device H12 is a device that receives input from a user or the like, such as a mouse or a keyboard. The display device H13 is a display or the like that displays various information.
The storage unit H14 is a storage device that stores data and various programs for executing various functions of the user terminal 10, the support server 20, and the trading device 30. An example of the storage unit H14 is a ROM, RAM, hard disk, or the like.

The processor H15 controls each process in the user terminal 10 and the support server 20 by using the programs and data stored in the storage unit H14. Examples of the processor H15 include a CPU, an MPU, and the like. The processor H15 expands a program stored in ROM or the like into RAM and executes various processes for each service.

The processor H15 is not limited to one that performs software processing for all the processing executed by itself. For example, the processor H15 may include a dedicated hardware circuit (for example, an integrated circuit for a specific application: ASIC) that performs hardware processing for at least a part of the processing executed by the processor H15. That is, the processor H15 is (1) one or more processors that operate according to a computer program (software), (2) one or more dedicated hardware circuits that execute at least a part of various processes, or ( 3) It can be configured as a circuitry including a combination thereof. The processor includes a CPU and memories such as RAM and ROM, and the memory stores a program code or a command configured to cause the CPU to execute a process. Memory or computer readable media includes any available medium accessible by a general purpose or dedicated computer.

(Explanation of each functional part)
The user terminal 10 is a computer terminal used by the user. The user terminal 10 includes a control unit 11, a payment means master storage unit 12, a linked information master storage unit 13, a learning result storage unit 14, and a personal information storage unit 15.

The control unit 11 performs each process such as a transaction support stage and a payment support stage. Therefore, the transaction support application (for the terminal) is stored in the user terminal 10. By activating the transaction support application, the control unit 11 functions as an information acquisition unit 111, an action prediction unit 112, and a user support unit 113.

The information acquisition unit 111 executes a process of acquiring the user's status. This situation includes the user's location, current time, user's wishes, and so on. Location information can be acquired from GPS (Global Positioning System) or beacon signals by wireless communication. Then, the information acquisition unit 111 holds the map information for identifying the store using the longitude / latitude information. The information acquisition unit 111 holds category information for specifying the location category from the specified store information. Further, the information acquisition unit 111 acquires the current time from the system timer in the user terminal 10.
The behavior prediction unit 112 executes a process of predicting the user's behavior using the prediction model according to the user situation.
The user support unit 113 executes a process of supporting the user's transaction.

The payment means master storage unit 12 records a payment means master record relating to the payment means that can be used for the transaction. This payment method master record is recorded when a payment method that can be used for a transaction is registered. Data regarding the payment method and available stores is recorded in the payment method master record.

In the payment means data area, data regarding an identifier for identifying each payment means is recorded.
In the available store data area, data regarding an identifier for identifying a store that can be traded is recorded using this payment means.

The linkage information master storage unit 13 records a linkage information master record relating to linkage information required at the time of transaction. This linkage information master record is recorded when the linkage information used at the time of transaction is registered. In the linkage information master record, data related to the linkage information item is recorded according to the transaction type.

In the transaction type data area, data relating to an identifier for identifying the transaction type is recorded. For example, the transaction type includes "purchase of cigarettes" and the like.
In the linkage information item data area, data relating to an identifier for specifying the linkage information used in the transaction of this transaction type is recorded. For example, as a linkage information item corresponding to "purchase of cigarettes", there is "an identification card that can confirm the age" and the like.

A prediction model for predicting the user's behavior is recorded in the learning result storage unit 14. This prediction model is recorded when downloaded from the support server 20. The details of the prediction model will be described later.

The personal information storage unit 15 records a personal information management record including payment means and linkage information held by the user. This personal information management record is recorded when the payment method and linkage information held by the user are registered. In the personal information management record, data related to detailed contents are recorded according to the information type.

In the information type data area, data related to an identifier for specifying the type of payment means and linkage information is recorded.
In the detailed content data area, data related to the detailed content of each information type is recorded. For example, as the detailed contents of the payment means, information on an account number, a credit card number, and a point card number can be used. As the detailed contents of the linkage information, a driver's license number, an address, work information, a health insurance card number, a medicine notebook number, an individual number of My Number, etc. can be used. In addition, a medical examination ticket number associated with the identification information of each medical institution, a user number associated with the identification information of each service used, a warranty card number associated with the identification information of the product used such as an electric appliance, and the like can be used.

The support server 20 is a computer system that generates a prediction model that predicts user behavior. The support server 20 includes a control unit 21, a user information storage unit 22, a history information storage unit 23, and a learning result storage unit 24.

The control unit 21 performs each process such as a user management stage and a learning stage. Therefore, the transaction support application (for the server) is stored in the user terminal 10. By activating the transaction support application, the control unit 21 functions as a user management unit 211 and a learning unit 212.

The user management unit 211 executes a process of managing each user.
The learning unit 212 executes a process of generating a prediction model that predicts the user's behavior based on the user's transaction history.

A user management record for each user is recorded in the user information storage unit 22. This user management record is recorded when user registration is performed. Data related to the user identifier, terminal identifier, home address, work address, contact information, personal information, etc. are recorded in the user management record.

In the user identifier data area, data regarding an identifier for identifying each user is recorded.
In the terminal identifier data area, an identifier for identifying the user terminal 10 used by this user is recorded.

In each data area of the home address and the work address, the longitude / latitude information of the user's place of residence and work place is recorded.
The contact data area records data about the user's contacts (eg, email addresses).
In the personal information data area, similarly to the personal information storage unit 15, data on the detailed contents of the payment means and the linkage information held by the user are recorded according to the information type.

The history information storage unit 23 records a history management record of the user's transaction history. This history management record is additionally recorded when the user makes a transaction. Data related to the user identifier, the transaction identifier, the transaction date and time, the business partner, the transaction position, and the transaction content are recorded in the history management record.

In the user identifier data area, data regarding an identifier for identifying each user is recorded.
In the legal entity data area, data regarding an identifier for identifying each transaction is recorded.

In the transaction date / time data area, data relating to the date and time when the user made a transaction is recorded.
In the customer data area, data regarding an identifier for identifying the store in which the transaction was made is recorded.

Data about the location where this transaction was made is recorded in the transaction position data area. As the trading place, for example, longitude and latitude can be used.
In the transaction content data area, data regarding an identifier for identifying the content of the transaction (for example, purchase of cigarettes, etc.) is recorded.

A prediction model for predicting the user's behavior is recorded in the learning result storage unit 24. This prediction model is recorded when machine learning is performed. This prediction model is recorded in association with the user identifier.

As the user identifier, data regarding the identifier for identifying each user is recorded.
The prediction model is a model for predicting the user's behavior according to the user's behavior pattern. This prediction model is recorded when machine learning is performed using the user's transaction history as teacher data. In this prediction model, for example, future user behavior is input by inputting location information (location location, location type, home address, work address, etc.) and time information (calendar day, time zone, etc.) regarding the user's situation. Output the forecast result of (transaction content). Here, as the location category, the type of location of the user (for example, a category such as a convenience store, a department store, a bank, or a hospital) can be used. As the calendar day, a date that characterizes the date of the transaction, such as the day of the week, the beginning of the month, the end of the month, and the end of the year, can be used. As the time zone, 6:00 to 8:00, morning / afternoon, lunch break time, etc. can be used. In the prediction model of each user, the home address and the work address are set as input values by default. Therefore, at the time of forecasting, the transaction content can be predicted by inputting location information (location information, location type), time information (calendar day, time zone), and the like.

The trading device 30 is a computer system that conducts transactions with users. The trading device 30 acquires payment means and linkage information from the user terminal 10 and conducts a transaction.

Next, the transaction support process will be described with reference to FIGS. 3 and 4. This transaction support process is composed of learning time processing and transaction time processing.
(Processing during learning)
The learning process will be described with reference to FIG. This learning processing is periodically specified and executed as a learning target user.
First, the control unit 21 of the support server 20 executes the purchase history specifying process (step S1-1). Specifically, the user management unit 211 of the control unit 21 identifies the user identifier of the learning target user, and extracts the history management record associated with the user identifier from the history information storage unit 23.

Next, the control unit 21 of the support server 20 executes the machine learning process (step S1-2). Specifically, the learning unit 212 of the control unit 21 acquires the home address and the work address of the learning target user from the user information storage unit 22. Next, the learning unit 212 identifies the time (calendar day, time zone) and location (location information of the transaction location, location category) when the transaction was performed using the history management record extracted from the history information storage unit 23. To do. Then, the learning unit 212 inputs teacher data that outputs transaction details (transaction type) by inputting time information (calendar day, time zone) and location information (location information, location category, home address, work address). Generate. Then, the learning unit 212 generates a prediction model by machine learning (for example, deep learning) using the teacher data. Then, the learning unit 212 records the generated prediction model in the learning result storage unit 24.

Next, the control unit 21 of the support server 20 executes the synchronization process (step S1-3). Specifically, the user management unit 211 of the control unit 21 specifies the terminal identifier recorded in the user management record of the user information storage unit 22. Next, the user management unit 211 provides the user terminal 10 with the prediction model recorded in the learning result storage unit 24 for the user terminal 10 having this terminal identifier. In this case, the user terminal 10 records the prediction model downloaded from the support server 20 in the learning result storage unit 14.

(Processing at the time of transaction)
Next, the transaction processing will be described with reference to FIG.
Here, the control unit 11 of the user terminal 10 executes the process of specifying the location of the user (step S2-1). Specifically, the information acquisition unit 111 of the control unit 11 acquires the position information of the current location. Longitude / latitude information by GPS (Global Positioning System) and beacon signals can be used for this position information. Further, the information acquisition unit 111 acquires the current date and time from the system timer. In this embodiment, it is assumed that the processes of steps S2-1 to S2-4 are automatically executed in the background even if the user does not intentionally start the application.

Next, the control unit 11 of the user terminal 10 executes a store entry identification process (step S2-2). Specifically, the information acquisition unit 111 of the control unit 11 specifies the store at the user's location. When using longitude / latitude information, use map information to identify stores that match the location. The store may be specified by accessing a map information site via the Internet and acquiring store information corresponding to longitude and latitude from this map information site. When beacon information is used, the store information included in the beacon is specified. Then, the information acquisition unit 111 specifies the location category by using the store information.

Next, the control unit 11 of the user terminal 10 executes a process for identifying available payment means candidates according to the entry into the store (step S2-3). Specifically, the user support unit 113 of the control unit 11 acquires the payment means that can be used in the specified store from the payment means master storage unit 12.

Next, the control unit 11 of the user terminal 10 executes the prediction processing of the user's behavior (step S2-4). Specifically, the action prediction unit 112 of the control unit 11 calculates the time zone and the calendar day using the current date and time. Then, the behavior prediction unit 112 inputs the current location (location information, location category), time zone, and calendar day into the prediction model recorded in the learning result storage unit 14, and the predicted transaction content (transaction type) at the location. Is output. For example, in the case of "convenience store near work place" (location information) and "before working hours" (time information), "tobacco purchase" is predicted as the transaction content.

Next, the control unit 11 of the user terminal 10 executes the display processing of the payment means candidate (step S2-5). Specifically, when the user makes a payment, the transaction support application is started. In this case, the user support unit 113 of the control unit 11 specifies the payment means owned by the user from the personal information storage unit 15. Then, the user support unit 113 compares the payment means owned by the user with the payment means specified in step S2-3, and identifies the payment means candidates that can be used by the user. Next, the user support unit 113 identifies payment means candidates in descending order of possibility of use according to the predicted transaction type. For example, the user support unit 113 acquires the transaction history for a predetermined period for the predicted transaction type for this user from the history information storage unit 23 of the support server 20. Then, the number of transactions is counted for each settlement means candidate, and the priority of the settlement means candidate is increased in descending order of frequency of use. Then, the user support unit 113 outputs a list of the specified payment means candidates to the display device.

Next, the control unit 11 of the user terminal 10 executes a payment means candidate selection process (step S2-6). Specifically, when the user conducts a transaction at this store, the user selects the payment method to be used for the transaction from the list of payment method candidates. In this case, the user support unit 113 of the control unit 11 specifies the payment means selected from the list of payment means candidates.

Next, the control unit 11 of the user terminal 10 executes the display processing of the linkage information candidate (step S2-7). Specifically, the user support unit 113 of the control unit 11 acquires the linkage information associated with the predicted transaction type as the linkage information candidate from the linkage information master storage unit 13. Then, the user support unit 113 outputs a list of the specified linkage information candidates to the display device. For example, in the case of tobacco purchases, include driver's license information to confirm age.

Next, the control unit 11 of the user terminal 10 executes the selection process of the linkage information candidate (step S2-8). Specifically, when the user conducts a transaction at this store, the user selects the linkage information to be used at the time of the transaction from the list of candidates for the linkage information. In this case, the user support unit 113 of the control unit 11 specifies the linkage information selected from the list of linkage information candidates.

Next, the control unit 11 of the user terminal 10 executes the process of providing the linkage information (step S2-9). Specifically, the user support unit 113 of the control unit 11 transmits the selected linkage information to the trading device 30. If the linkage information is not selected in the list of linkage information candidates, the linkage information provision process (step S2-9) is skipped.

Next, the control unit 11 of the user terminal 10 executes a transaction process by the payment means (step S2-10). Specifically, the user support unit 113 of the control unit 11 transmits a transaction instruction for using the selected payment means to the transaction device 30.
Then, the trading device 30 conducts a transaction using the linkage information and the payment means acquired from the user terminal 10. Then, the trading device 30 provides the trading result to the support server 20. In this case, the control unit 21 of the support server 20 generates a history management record for the transaction result and records it in the history information storage unit 23. This history management record is used in a new learning process.

As described above, according to the present embodiment, the following effects can be obtained.
(1-1) In the present embodiment, the control unit 21 of the support server 20 executes the purchase history identification process (step S1-1) and the machine learning process (step S1-2). As a result, the user's behavior can be predicted based on the purchase history.

(1-2) In the present embodiment, the control unit 21 of the support server 20 executes the synchronization process (step S1-3). As a result, the user's behavior can be predicted on the user terminal 10.

(1-3) In the present embodiment, the control unit 11 of the user terminal 10 is used according to the user's location identification process (step S2-1), store entry identification process (step S2-2), and store entry. The process of identifying a possible payment means candidate (step S2-3) is executed. Thereby, the payment means that can be used in the store can be specified.

(1-4) In the present embodiment, the control unit 11 of the user terminal 10 executes a user action prediction process (step S2-4) and a payment means candidate display process (step S2-5). As a result, it is possible to predict the behavior of the user in the store and predict the settlement means of the transaction according to this behavior.

(1-5) In the present embodiment, the control unit 11 of the user terminal 10 executes the display processing of the linkage information candidate (step S2-7). As a result, it is possible to predict the behavior of the user in the store and predict the linkage information required for the transaction according to this behavior.

(1-6) In the present embodiment, the control unit 11 of the user terminal 10 executes a link information provision process (step S2-9) and a transaction process by a settlement means (step S2-10). As a result, transaction settlement can be performed efficiently using the linkage information.

(Second Embodiment)
Next, the second embodiment will be described with reference to FIGS. 5 and 6. In the first embodiment, the user terminal 10 predicts a transaction and performs a process of supporting the user, but in the second embodiment, the support server 20 performs a process of supporting the user. Therefore, the same parts as those in the first embodiment are designated by the same reference numerals, and detailed description thereof will be omitted.

As shown in FIG. 5, also in this embodiment, the support server 20 includes a control unit 21, a user information storage unit 22, a history information storage unit 23, and a learning result storage unit 24. In the present embodiment, the control unit 21 of the support server 20 is provided with an information acquisition unit 213, an action prediction unit 214, and a user support unit 215 in addition to the user management unit 211 and the learning unit 212. The information acquisition unit 213, the action prediction unit 214, and the user support unit 215 execute the processes corresponding to the information acquisition unit 111, the behavior prediction unit 112, and the user support unit 113 in the first embodiment, respectively. Further, the support server 20 is provided with a payment means master storage unit 26, a linked information master storage unit 27, and a personal information storage unit 28. The payment means master storage unit 26, the linkage information master storage unit 27, and the personal information storage unit 28 correspond to the payment means master storage unit 12, the linkage information master storage unit 13, and the personal information storage unit 15 in the first embodiment, respectively. .. Further, in the personal information storage unit 28, in order to record the personal information of a plurality of users, the user identifier and the user authentication information are recorded in the personal information management record.

(Processing at the time of transaction)
The transaction processing will be described with reference to FIG.
First, the control unit 21 of the support server 20 executes the user identification process (step S3-1). Specifically, the user management unit 211 of the control unit 21 acquires user authentication information from the accessed user terminal 10 and performs personal authentication. The user identifier of the user is specified based on the result of this personal authentication.

Next, the control unit 21 of the support server 20 executes the user request acquisition process (step S3-2). Specifically, the information acquisition unit 213 of the control unit 21 acquires a user request from the user terminal 10. For example, a transaction request "reservation of a trip to a place (Kyoto) at the time (May consecutive holidays)" is obtained.

Next, the control unit 21 of the support server 20 executes the prediction process of the user's behavior (step S3-3). Specifically, the behavior prediction unit 214 of the control unit 21 predicts the user's behavior related to the user request. For example, in the prediction model, the time (May consecutive holidays) and the place (Kyoto) are input. Here, when the history information storage unit 23 records regular hospital visit information, it predicts the hospital visit during the trip. Further, when the refueling information of the automobile is recorded in the history information storage unit 23, the use of the automobile is predicted. Further, when the purchase information of the camera is recorded in the history information storage unit 23, the camera usage is predicted.

Next, the control unit 21 of the support server 20 executes the plan search process (step S3-4). Specifically, the user support unit 215 of the control unit 21 accesses the trading device 30 in response to a user request. Then, the user support unit 215 identifies a transaction candidate (travel plan) corresponding to the user request from the transaction device 30.

Next, the control unit 21 of the support server 20 executes a plan candidate display process according to the user's behavior prediction (step S3-5). Specifically, the user support unit 215 of the control unit 21 identifies a transaction candidate suitable for the user's behavior prediction among the identified transaction candidates. For example, in the case of a travel plan, the priority of the travel plan that includes accommodations close to the hospital is given in consideration of illness caused by regular hospital visits. In addition, when predicting the use of automobiles, the priority of travel plans for rental car use will be raised. Then, the user support unit 215 outputs a list of the specified plan candidates to the display device of the user terminal 10.

Next, the control unit 21 of the support server 20 executes the plan candidate selection process (step S3-6). Specifically, the user selects a desired plan candidate from the list of plan candidates displayed on the display device. In this case, the user support unit 215 of the control unit 21 acquires the plan candidate selected in the user terminal 10.

Next, the control unit 21 of the support server 20 executes the display processing of the linkage information candidates related to the selected plan (step S3-7). Specifically, the user support unit 215 of the control unit 21 acquires the linkage information candidate necessary for reserving the selected plan candidate from the personal information storage unit 28. For example, when the user's behavior prediction includes an outpatient visit, the insurance card information is specified as the linkage information. In addition, when a travel plan using a rental car is selected, the driver's license information is specified as linkage information. In addition, when the use of the camera is included in the behavior prediction of the user, the warranty card of the camera is specified as the linkage information.

Next, the control unit 21 of the support server 20 executes the selection process of the linkage information candidate (step S3-8). Specifically, the user support unit 215 of the control unit 21 acquires the linkage information necessary for the transaction of the plan from the information storage unit. For example, in the case of a plan that includes the use of a rental car, select the driver's license information.

Next, the control unit 21 of the support server 20 executes the process of providing the linkage information (step S3-9). Specifically, the user support unit 215 of the control unit 21 provides the specified linkage information to the trading device 30.

Next, the control unit 21 of the support server 20 executes the transaction processing of the plan (step S3-10). Specifically, the user support unit 215 of the control unit 21 conducts a transaction corresponding to the user request with the transaction device 30.

As described above, according to the present embodiment, the following effects can be obtained.
(2-1) In the present embodiment, the control unit 21 of the support server 20 executes a user request acquisition process (step S3-2) and a user action prediction process (step S3-3). As a result, the behavior of the user in response to the user request can be predicted.

(2-2) In the present embodiment, the control unit 21 of the support server 20 executes a plan search process (step S3-4) and a plan candidate display process (step S3-5) according to the user's action prediction. .. As a result, among the plan candidates in response to the user request, the plan candidate suitable for the predicted user behavior can be preferentially displayed.

(2-3) In the present embodiment, the control unit 21 of the support server 20 displays the linkage information candidate related to the selected plan (step S3-7) and provides the linkage information (step S3-9). To execute. As a result, it is possible to carry out transactions efficiently using the linkage information.

This embodiment can be modified and implemented as follows. The present embodiment and the following modified examples can be implemented in combination with each other within a technically consistent range.
-In the first embodiment, the user terminal 10 executes the transaction time processing. This transaction time processing may be executed on the support server 20. In this case, the user terminal 10 functions as an interface for the user and an interface for the trading device 30.

-In the first embodiment, the control unit 11 of the user terminal 10 executes a display process of payment means candidates (step S2-5). In this case, the user support unit 113 of the control unit 11 identifies the priority order that is likely to be used among the payment means candidates owned by the user and available at this store. The specification of the priority may be executed in step S2-3.

-In the first embodiment, the control unit 11 of the user terminal 10 executes a display process of payment means candidates (step S2-5). According to the predicted transaction type, payment method candidates are identified in descending order of frequency of use. Here, the priority is not limited to the case where the frequency of use is used. For example, it may be arranged and displayed in the order of payment means candidates that are advantageous to the user. In this case, the user terminal 10 acquires the transaction conditions of the payment means from the transaction device 30. For example, campaign information and privilege information can be used for this transaction condition. Then, in the acquired transaction conditions, the settlement means of the transaction conditions advantageous to the user is specified, and the priority of the settlement means of the advantageous conditions is raised.
In addition, the priority of the settlement means may be determined according to the amount of the expected transaction content. In this case, for example, the control unit 11 is made to hold a priority table for determining the priority of the payment means according to the amount of money. Then, the user support unit 113 of the control unit 11 determines the priority using the priority table according to the amount of money for the predicted transaction type.
In addition, the priority may be determined according to the balance of the payment means owned by the user and the latest usage amount. In this case, the control unit 11 holds a priority table for determining the priority of the payment means according to the balance and the usage amount. In this priority table, for example, a score is recorded according to the balance and the latest usage amount, and the priority is determined by the score of each payment method. Then, the user support unit 113 of the control unit 11 accesses the management server of each payment means and acquires the balance and the latest usage amount. Next, the user support unit 113 determines the priority order using the priority table according to the balance and the usage amount.
In addition, the priority may be determined according to the expiration date of the payment means owned by the user. For example, when payment can be made with the points owned by the user, the expiration date of the user's points is acquired from the point management server. Then, the priority of the points whose expiration date is near is raised.

-In the first embodiment, the control unit 21 of the support server 20 executes the purchase history identification process (step S1-1) and the machine learning process (step S1-2). The method of generating a prediction model for predicting a user's behavior is not limited to machine learning. For example, the information recorded in the history information storage unit may be used to recognize the pattern of the user's behavior.
-In the first embodiment, the control unit 11 of the user terminal 10 executes the display processing of the linkage information candidate (step S2-7). Here, the priority order of the linkage information may be changed according to the payment method selected in step S2-6. For example, the point card that can be used by the selected payment method is used as the linkage information to raise the priority.

-In the first embodiment, the control unit 11 of the user terminal 10 executes a process of providing linkage information (step S2-9). Further, in the second embodiment, the control unit 21 of the support server 20 executes the process of providing the linkage information (step S3-9). The destination of the linkage information is not limited to the trading device 30.

-In the first and second embodiments described above, the transaction was carried out using the settlement means and the linkage information. Only one of the information that can be used for the user's behavior predicted by using the prediction model may be provided.
-In the first and second embodiments described above, linkage information is specified in the purchase of cigarettes and the reservation of travel. Linkage information is diverse and not limited to these. For example, if the user's property (electrical appliances, etc.) is specified based on the user's history information and the repair request is specified as the user's behavior, the warranty card information may be provided. Here, when the user support unit predicts the delivery request of the repaired product, the user support unit may provide the home address as the linkage information as the delivery destination.

10 ... User terminal, 11 ... Control unit, 111,213 ... Information acquisition unit, 112,214 ... Behavior prediction unit, 113,215 ... User support unit, 12,26 ... Payment means master storage unit, 13,27 ... Linkage information Master storage unit, 14, 24 ... Learning result storage unit, 15, 28 ... Personal information storage unit, 20 ... Support server, 21 ... Control unit, 211 ... User management unit, 212 ... Learning unit, 22 ... User information storage unit, 23 ... History information storage unit, 30 ... Trading device.

Claims (8)

A personal information storage unit that stores the user's payment method and linkage information,
A history information storage unit that stores the user's transaction history,
A trading support system equipped with a control unit connected to a trading device.
The control unit
Using the location information, time information, and transaction content of the transaction history recorded in the history information storage unit, a prediction model that predicts the transaction content from the location and time is generated.
Predict the user's behavior from the current location and the current date and time using the prediction model.
Using the personal information storage unit, the payment method used for the transaction in the predicted behavior is specified.
A transaction support system characterized in that the personal information storage unit is used to specify linkage information used for transactions by the payment means, and transaction processing is executed with the transaction device. The transaction support system according to claim 1, wherein when the control unit identifies a plurality of payment means, a list of the payment means is displayed on a display device to prompt selection. The transaction support system according to claim 2, wherein the control unit rearranges and displays the specified payment means in an order advantageous to the user based on the current location and the transaction content. The transaction support according to any one of claims 1 to 3, wherein when the control unit identifies the linkage information for which the transaction is used, the list of the linkage information is displayed on the display device to prompt the selection. system. The transaction support system according to claim 4, wherein the control unit rearranges and displays the linkage information based on the current location, the transaction content, and the specified payment means. The control unit receives a user request from the user and receives a user request.
The transaction support system according to any one of claims 1 to 5, wherein a plan according to a user's behavior predicted based on the user request is specified and output. A personal information storage unit that stores the user's payment method and linkage information,
A history information storage unit that stores the user's transaction history,
It is a method for providing transaction support using a transaction support system equipped with a control unit connected to a transaction device.
The control unit
Using the location information, time information, and transaction content of the transaction history recorded in the history information storage unit, a prediction model that predicts the transaction content from the location and time is generated.
Predict the user's behavior from the current location and the current date and time using the prediction model.
Using the personal information storage unit, the payment method used for the transaction in the predicted behavior is specified.
A transaction support method characterized in that the personal information storage unit is used to specify linkage information used for transactions by the settlement means, and transaction processing is executed with the transaction device. A personal information storage unit that stores the user's payment method and linkage information,
A history information storage unit that stores the user's transaction history,
A program for providing transaction support using a transaction support system equipped with a control unit connected to a transaction device.
The control unit
Using the location information, time information, and transaction content of the transaction history recorded in the history information storage unit, a prediction model that predicts the transaction content from the location and time is generated.
Predict the user's behavior from the current location and the current date and time using the prediction model.
Using the personal information storage unit, the payment method used for the transaction in the predicted behavior is specified.
A transaction support program characterized in that the personal information storage unit is used to identify linkage information used for transactions by the settlement means and to function as a means for executing transaction processing with the transaction device.

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