Payment service providing method and system therefor

Abstract

Provided are a payment service providing method and a system therefor. The payment service providing method according to some embodiments may comprise the steps of: receiving a purchase request for at least one product from a terminal of a user; acquiring payment means-related information about the user in response to the purchase request; acquiring payment benefit information about at least some of a plurality of payment means; calculating a benefit amount for each of the plurality of payment means on the basis of the payment benefit information; and determining a purchase payment means for the at least one product among the plurality of payment means on the basis of the benefit amount. The method can eliminate the inconvenience of a user having to carefully select a payment means in consideration of payment benefits when purchasing a product, and solve the problem of the user not recognizing the benefits of some payment means and thus unintentionally missing out on the payment benefits.

Description

Method for providing payment services and its system

[0001] The present disclosure relates to a method for providing a payment service and a system thereof.

[0002] As e-commerce services become more popular, the majority of users are purchasing products online, and various payment methods are being used for purchasing products.

[0003] Meanwhile, since discounts vary depending on the payment method, even for the same product price, the discount amount may vary depending on the payment method. However, it can be quite cumbersome for users to constantly check their payment methods and their discounts and calculate the discount amount.

[0004] The technical problem to be solved through some embodiments of the present disclosure is to provide a method and a system for performing the method that can further improve user convenience in selecting a payment method.

[0005] Another technical problem to be solved through some embodiments of the present disclosure is to provide a method and a system for performing the method that can prevent a user from unintentionally missing out on payment benefits.

[0006] Another technical problem to be solved through some embodiments of the present disclosure is to provide a method and a system for performing the method that can provide a payment function using multiple payment methods for a single product purchase (so-called 'composite / split / mixed payment' function).

[0007] The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art of the present disclosure from the description below.

[0008] A method for providing a payment service according to some embodiments of the present disclosure for solving the above-described technical problem is a method performed in at least one computing device, the method including the steps of: receiving a purchase request for at least one product from a user's terminal; acquiring payment method-related information of the user in response to the purchase request, wherein the payment method-related information includes priorities of a plurality of pre-registered payment methods and the priorities are set by the user; acquiring payment benefit information for at least some of the plurality of payment methods; calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information; and determining a purchase payment method for the at least one product from among the plurality of payment methods based on the benefit amount and the priorities.

[0009] In some embodiments, the payment benefit information may include payment benefit information provided by an e-commerce service provider for the at least one product and payment benefit information provided by a payment method provider.

[0010] In some embodiments, the payment benefit information may include payment benefit information according to day of the week, date, and time.

[0011] In some embodiments, the step of determining a purchase payment method for the at least one product may include a step of determining the purchase payment method based on a maximum benefit amount for the plurality of payment methods based on a determination that the maximum benefit amount is greater than or equal to a reference value.

[0012] In some embodiments, the step of determining a purchase payment method for the at least one product may include a step of determining the purchase payment method according to the priority based on a determination that the maximum benefit amount for the plurality of payment methods is less than a threshold value.

[0013] In some embodiments, the payment method-related information includes a remaining limit amount calculated based on a payment limit amount set by the user, and the step of determining the purchase payment method according to the priority may include a step of determining the purchase payment method further based on the remaining limit amounts of the plurality of payment methods.

[0014] In some embodiments, the method further comprises providing a payment interface in which the determined purchase payment method is selected, wherein the payment interface may include an interface for selecting an additional purchase payment method from the user.

[0015] In some embodiments, the method further comprises providing a payment interface in which the determined purchase payment method is selected, wherein the payment interface may include an interface for registering a combination of two or more payment methods from the user or for retrieving a combination of pre-registered payment methods based on an input from the user.

[0016] In some embodiments, the payment method-related information includes a performance shortfall amount for each of the plurality of payment methods, and the payment service providing method may further include a step of determining another purchase payment method among the plurality of payment methods based on the performance shortfall amount.

[0017] In some embodiments, the payment method-related information includes a performance shortfall amount for each of the plurality of payment methods, the determined purchase payment method includes a first payment method and a second payment method, and the payment service providing method may further include a step of determining a payment amount for each of the first payment method and the second payment method based on the performance shortfall amount.

[0018] According to some embodiments of the present disclosure for solving the above-described technical problem, a payment service providing system may include a memory storing one or more processors and a computer program executed by the one or more processors, wherein the computer program may include instructions for receiving a purchase request for at least one product from a user's terminal, obtaining payment method-related information of the user in response to the purchase request, wherein the payment method-related information includes priorities of a plurality of pre-registered payment methods and the priorities are set by the user, obtaining payment benefit information for at least some of the plurality of payment methods, calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information, and determining a purchase payment method for the at least one product from among the plurality of payment methods based on the benefit amount and the priorities.

[0019] According to some embodiments of the present disclosure for solving the above-described technical problem, a computer program may be stored in a computer-readable recording medium to execute the steps of: receiving a purchase request for at least one product from a user's terminal, in response to the purchase request, obtaining payment method-related information of the user, wherein the payment method-related information includes priorities of a plurality of pre-registered payment methods and the priorities are set by the user; obtaining payment benefit information for at least some of the plurality of payment methods; calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information; and determining a purchase payment method for the at least one product from among the plurality of payment methods based on the benefit amount and the priorities.

[0020] According to some embodiments of the present disclosure, the payment method to be used for a product purchase (i.e., the purchase payment method) can be automatically determined based on payment benefit information for the user's previously registered payment methods. This eliminates the inconvenience of having to carefully select a payment method based on payment benefits when purchasing a product. Furthermore, the problem of users unintentionally missing out on payment benefits due to unawareness of the benefits of certain payment methods can be resolved. Consequently, user satisfaction with e-commerce and payment services can be significantly improved.

[0021] Additionally, the payment method for purchases can be determined based on the user's set priorities and payment limits for previously registered payment methods. In such cases, the payment method for purchases can be determined faithfully reflecting the user's explicit intentions (e.g., payment method preferences, payment method usage plans).

[0022] Additionally, the payment method for purchases can be determined based on the insufficient performance of previously registered payment methods. This increases the likelihood of the payment method achieving performance (i.e., the likelihood of receiving benefits based on performance achievement), further enhancing user satisfaction with e-commerce and payment services.

[0023] Additionally, users may be provided with the ability to use multiple payment methods for a single product purchase (so-called "composite / split / mixed payment" functionality). This allows users to freely purchase products using multiple payment methods, further enhancing user satisfaction with e-commerce and payment services.

[0024] Additionally, a deep learning model trained on payment history data (e.g., user information, product information, payment method information, etc.) from multiple users can be used to determine a user's payment method. The trained deep learning model can comprehensively predict a user's preferred payment method by considering factors such as product characteristics and user type. Therefore, in this case, the user's preferred payment method can be accurately determined as the purchase payment method.

[0025] The effects according to the technical idea of ​​the present disclosure are not limited to the effects mentioned above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0026] FIG. 1 is an exemplary configuration diagram illustrating a payment service providing system according to some embodiments of the present disclosure.

[0027] FIG. 2 is an exemplary flowchart illustrating a method for providing a payment service according to some embodiments of the present disclosure.

[0028] Figure 3 is an exemplary flowchart showing the detailed process of the benefit amount calculation step illustrated in Figure 2.

[0029] FIG. 4 illustrates a payment interface according to some embodiments of the present disclosure.

[0030] FIG. 5 illustrates a payment interface according to some other embodiments of the present disclosure.

[0031] FIG. 6 is an exemplary flowchart illustrating a method for providing a payment service according to some other embodiments of the present disclosure.

[0032] FIG. 7 is an exemplary flowchart illustrating a method for providing a payment service according to some other embodiments of the present disclosure.

[0033] FIG. 8 is an exemplary flowchart illustrating a method for providing a payment service according to some other embodiments of the present disclosure.

[0034] FIG. 9 and FIG. 10 are exemplary drawings for explaining the input / output, structure, and learning method of a deep learning model according to some embodiments of the present disclosure.

[0035] FIG. 11 is an exemplary flowchart illustrating a method for providing a payment service according to some other embodiments of the present disclosure.

[0036] FIG. 12 illustrates an exemplary computing device that can implement a payment service providing system according to some embodiments of the present disclosure.

[0037] Hereinafter, various embodiments of the present disclosure will be described in detail with reference to the attached drawings. The advantages and features of the present disclosure, and methods for achieving them, will become clear with reference to the embodiments described in detail below together with the attached drawings. However, the technical idea of ​​the present disclosure is not limited to the following embodiments and may be implemented in various different forms. The following embodiments are provided only to complete the technical idea of ​​the present disclosure and to fully inform those skilled in the art of the present disclosure of the scope of the present disclosure, and the technical idea of ​​the present disclosure is defined only by the scope of the claims.

[0038] In describing various embodiments of the present disclosure, if it is determined that a detailed description of a related known configuration or function may obscure the gist of the present disclosure, the detailed description will be omitted.

[0039] Unless otherwise defined, the terms (including technical and scientific terms) used in the following examples may be used with meanings commonly understood by those of ordinary skill in the art to which this disclosure pertains; however, this may vary depending on the intentions of engineers working in the relevant field, precedents, the emergence of new technologies, etc. The terminology used in this disclosure is for the purpose of describing the embodiments and is not intended to limit the scope of this disclosure.

[0040] In the following examples, singular expressions include plural concepts unless the context clearly specifies that they are singular. Furthermore, plural expressions include singular concepts unless the context clearly specifies that they are plural.

[0041] In addition, terms such as first, second, A, B, (a), (b), etc. used in the following embodiments are only used to distinguish certain components from other components, and the nature, order, or sequence of the components are not limited by the terms.

[0042] Hereinafter, various embodiments of the present disclosure will be described in detail with reference to the attached drawings.

[0043] FIG. 1 is an exemplary configuration diagram for explaining a payment service providing system (10) according to some embodiments of the present disclosure.

[0044] As illustrated in FIG. 1, the payment service providing system (10) according to the embodiments is a computing system that provides a payment service for e-commerce, and may be configured to include a service server (11) and a payment server (12). However, in some cases, the payment service providing system (10) may be named an 'e-commerce (or shopping, etc.) service providing system', and either of the service server (11) and the payment server (12) may be referred to as a 'payment service providing system'. Hereinafter, for the convenience of explanation, the payment service providing system (10) will be abbreviated as 'service system (10)'.

[0045] The service server (11) is a computing device / system that provides e-commerce (or shopping, etc.) services for various products. For example, the service server (11) can provide e-commerce services for various products via a web and / or app interface, and users can utilize the e-commerce services via a web browser and / or app installed on their terminal (13).

[0046] Additionally, the service server (11) can store and manage various information / data related to e-commerce services (e.g., information / data regarding products, users, payment methods registered by users, payment benefits, purchase / payment history, etc.) in a repository. Examples of such information / data will be described later.

[0047] Additionally, the service server (11) can automatically determine (e.g., recommend) payment methods for purchased products in various ways and provide a payment function using multiple payment methods (so-called "composite / split / mixed payment" function). By doing so, the convenience and satisfaction of users using e-commerce and payment services can be enhanced. This will be described in detail with reference to the drawings in FIG. 2 and below.

[0048] Next, the payment server (12) is a computing device / system responsible for payment processing (or approval) functions. For example, the payment server (12) may receive a payment request based on a specific payment method from the service server (11) and, in response, perform payment processing (e.g., approval) using the requested payment method. The payment server (12) may collectively refer to multiple payment servers responsible for payment processing functions for different payment methods. For example, the payment server (12) may include a first payment server responsible for payment processing functions for a first payment method and a second payment server responsible for payment processing functions for a second payment method.

[0049] In addition, the payment server (12) can store and manage various information / data (e.g., payment benefits, payment amount, performance amount, performance deficiency amount, payment history, etc.) related to payment methods, payment processing, etc. in a storage. In addition, the payment server (12) can also provide specific information / data to the service server (11) at the request of the service server (11).

[0050] The above-described service server (11) and payment server (12) may be implemented by at least one computing device. For example, all functions of the service server (11) may be implemented by a single computing device, or the first function of the service server (11) may be implemented by a first computing device and the second function may be implemented by a second computing device. Alternatively, specific functions of the service server (11) may be implemented by multiple computing devices.

[0051] A computing device may include any device equipped with computing capabilities. For an example of such a device, see FIG. 12. Since a computing device is a collection of interacting components (e.g., memory, processor, etc.), it may sometimes be referred to as a "computing system." Of course, the term "computing system" can also encompass the concept of a collection of interacting computing devices.

[0052] A user terminal (13) is a computing device (e.g., mobile computing device, fixed computing device) used by a user to access an e-commerce service. The user terminal (13) may be implemented using any computing device.

[0053] Users can access e-commerce service sites via terminals (13) to purchase products and can also pre-register frequently used payment methods. Users can also register a combination of two or more payment methods via terminals (13).

[0054] As illustrated, the service system (10) and the user terminal (13) can communicate via a network. Here, the network can be implemented as any type of wired / wireless network, such as a local area network (LAN), a wide area network (WAN), a mobile radio communication network, Wibro (Wireless Broadband Internet), etc.

[0055] So far, the configuration and operation of the service system (10) according to some embodiments of the present disclosure have been briefly described with reference to FIG. 1. Hereinafter, various methods that can be performed in the service system (10) will be described with reference to the drawings below FIG. 2.

[0056] For ease of understanding, the following description assumes that all steps / operations of the methods described below are performed primarily on the service server (11) in the environment illustrated in FIG. 1. Therefore, if the subject of a specific step / operation is omitted, it can be understood that it is performed on the service server (11). However, in an actual environment, some steps / operations of the methods described below may be performed on the payment server (12) or another computing device / system.

[0057] FIG. 2 is an exemplary flowchart illustrating a method for providing a payment service according to some embodiments of the present disclosure.

[0058] As illustrated in FIG. 2, the present embodiments relate to a method for automatically determining a purchase payment method (i.e., a payment method to be used for a purchase) based on payment benefit information.

[0059] The present embodiments may begin with step S21, which receives a purchase request for at least one product from a user's terminal. For example, if a user clicks a purchase button on a shopping cart page or product page, the user terminal (13) may transmit a purchase request to the service server (11). The at least one product may refer to a product subject to payment that belongs to a single purchase (e.g., a product in a shopping cart, etc.).

[0060] In step S22, information related to the user's payment method (i.e., information related to previously registered payment methods) may be acquired. For example, the service server (11) may obtain information on payment methods previously registered by the user by querying a repository (e.g., by querying with the user's ID, etc.) or may obtain information on payment methods (e.g., insufficient performance amount, etc.) from the payment server (12). The method by which the service server (11) obtains information related to payment methods may be any method. In the following description, the user's payment method may refer to a payment method previously registered by the user with the service server (11).

[0061] Information related to payment methods may include, but is not limited to, the type (category) of the payment method (e.g., rechargeable payment methods such as PayMoney, card, account, simple payment, etc.), the priority of the payment method set by the user, the limit amount of the payment method set by the user (e.g., monthly limit amount), the remaining limit amount (e.g., monthly limit amount - payment (usage) amount for the corresponding month), the payment amount (e.g., payment amount by payment method, total payment amount, etc.), the recharge amount (e.g., PayMoney amount), the performance amount (e.g., the monthly performance amount that must be achieved to receive card benefits), the performance deficiency amount (e.g., monthly performance amount - payment (usage) amount for the corresponding month), etc.

[0062] In step S23, payment benefit information for previously registered payment methods can be obtained. For example, the service server (11) may obtain payment benefit information applicable to a specific payment method from the payment server (12) or may obtain benefit information for a specific payment method by searching information on the Internet. In addition, the service server (11) may obtain payment benefit information provided by the service server's (11) business operator by searching a repository, product page, etc. The method by which the service server (11) obtains payment benefit information may be any method. In some cases, the service server (11) may obtain payment benefit information for other payment methods in addition to the user's previously registered payment methods.

[0063] Payment benefit information may include, without limitation, information on various economic benefits that can be obtained through payment, such as discounts (e.g., product price discounts, billing discounts on payment amounts), cashbacks, point (or pay money) accumulation, coupon issuance, etc.

[0064] In addition, the payment benefit information may include, for example, first payment benefit information provided by a business operator of an e-commerce service (i.e., a business operator of a service server (11)) and second payment benefit information provided by a business operator of a payment method (i.e., a business operator of a payment server (12)).

[0065] The first payment benefit information may include, but is not limited to, information such as benefits applicable to specific products (e.g., products in a specific category), benefits provided only to membership subscribers (e.g., discounts when paying with a specific payment method), and event-related benefits provided for a certain period of time.

[0066] Additionally, the second payment benefit information may include, but is not limited to, payment benefit information based on the day of the week, date, and time (e.g., discount benefits provided when making payments on a specific day of the week, date, and time).

[0067] In step S24, a benefit amount for each registered payment method can be calculated based on payment benefit information. The benefit amount may include, but is not limited to, a discount amount, a cashback amount, or an amount equivalent to accumulated points.

[0068] For example, as illustrated in FIG. 3, the service server (11) can calculate a day discount amount for a card that provides a discount benefit on the current day among the user's registered cards (S31, S32), and can similarly calculate corresponding discount amounts (e.g., time discount amount, date discount amount, product discount amount) for other cards (see S33 to S38).

[0069] In step S25, a payment method for at least one product may be determined based on the benefit amount. For example, the service server (11) may determine at least one payment method offering the maximum benefit amount as the purchase payment method. Here, the maximum benefit amount may refer to the maximum benefit amount calculated by considering whether benefits can be overlapped (aggregated). For example, if a first card offers a 10% discount on a monitor priced at 500,000 won in the shopping cart, and a second card offers a 5% discount on a laptop priced at 1,000,000 won, and both discounts can be applied concurrently, the maximum benefit amount may be calculated as 100,000 won. In this case, both the first and second cards may be determined as the purchase payment methods, and the payment amounts for the first and second cards may also be determined based on the maximum benefit amount.

[0070] A purchase payment method can be provided (e.g., recommended) to the user through a payment interface located on a payment page (e.g., checkout page). For example, the service server (11) may provide the user with a payment interface (e.g., see 41 of FIG. 4) in which a purchase payment method is selected. In some cases, the service server (11) may also provide the user with a purchase payment method through a separate interface (e.g., a pop-up payment method recommendation interface).

[0071] Meanwhile, the payment interface may be configured to accept multiple payment methods to provide a composite payment function. For ease of understanding, examples of such payment interfaces (i.e., user interfaces for payment) are briefly described below with reference to Figures 4 and 5.

[0072] FIG. 4 illustrates a payment interface (40) according to some embodiments of the present disclosure.

[0073] As illustrated in FIG. 4, the payment interface (40) may include a payment method selection interface (41, 43) and a payment amount input interface (42, 44). The payment method selection interface (e.g., 41) may be implemented as a drop-down list with the user's previously registered payment methods as selectable items, but the scope of the present disclosure is not limited thereto.

[0074] Additionally, the payment interface (40) may further include an interface (45, e.g., a button) for adding a payment method. When user input is received through the payment method addition interface (45), an interface (see 43, 44) for selecting an additional payment method may be further displayed within the payment interface (40) (e.g., the illustrated interfaces (43, 44) may be added by such user input).

[0075] In some embodiments, the initial value (i.e., the payment amount) of the payment amount interface (42, 44) may be automatically set. For example, the initial value of the payment amount interface (42, 44) may be set to an amount obtained by dividing the total payment amount by the number of selected (to be selected) payment methods (i.e., an equal division amount). Alternatively, if the number of selected (to be selected) payment methods and the number of products are the same, the initial value of the payment amount interface (42, 44) may be set to the amount of the corresponding individual product (e.g., if the number of current payment methods becomes the same as the number of products due to the addition of a payment method, the setting value may be changed from an equal division amount to an amount of the individual product).

[0076] FIG. 5 illustrates a payment interface (50) according to some other embodiments of the present disclosure.

[0077] As illustrated in FIG. 5, the payment interface (50) according to the present embodiments is designed in consideration of user input based on mobile gestures, and may be configured to include a first area (51) and a second area (52). Here, selected payment methods (53, 55) and a payment amount input interface (54, 56) may be displayed (located) in the first area (51), and the user's previously registered payment methods (57 to 59) may be displayed (located) in the second area (52).

[0078] In these embodiments, when a user input is received to drag a specific payment method (e.g., 58) displayed in the second area (52) to the first area (51), the selected payment method (e.g., 55) and a corresponding payment amount interface (e.g., 56) may be displayed (added) in the first area (51). In addition, when a user input is received to drag a specific payment method (e.g., 55) displayed in the first area (51) to the second area (52), the specific payment method (e.g., 55) and a corresponding payment amount interface (e.g., 56) may be removed from the first area (51). In this case, since the user can select (or deselect) a payment method through a simple input such as dragging, the user's convenience in selecting a payment method may be further improved.

[0079] Meanwhile, in some embodiments, the payment interface described above (see 40, 50) may include (provide) an interface for registering a combination of two or more payment methods or for retrieving a combination of pre-registered payment methods based on user input. For example, a user may pre-register a combination of frequently used payment methods (e.g., "PayMoney" and "a specific card") and quickly select multiple payment methods to be used for a purchased product by retrieving the combination from the payment interface.

[0080] Hereinafter, a payment service provision method according to some embodiments of the present disclosure has been described with reference to FIGS. 2 through 5. As described above, the payment method to be used for a product purchase (i.e., the purchase payment method) can be automatically determined based on payment benefit information for the user's previously registered payment methods. This eliminates the inconvenience of having to carefully select a payment method based on payment benefits when purchasing a product. Furthermore, the problem of users missing out on payment benefits due to unawareness of the payment benefits of some payment methods can be resolved. Consequently, user satisfaction with e-commerce services and payment services can be significantly improved.

[0081] Hereinafter, a payment service provision method according to several other embodiments of the present disclosure will be described with reference to FIG. 6. However, for clarity of the present disclosure, descriptions of content overlapping with previous embodiments will be omitted.

[0082] As illustrated in FIG. 6, the present embodiments relate to a method for determining a purchase payment method based on the priority and remaining limit of the payment method. As described above, the priorities and payment limits (e.g., monthly payment limits) of pre-registered payment methods can be set by the user (e.g., the user can set the priorities and payment limits of the first and second cards, respectively, as (1st priority, KRW 100,000) and (2nd priority, KRW 50,000)), and the remaining limit can be calculated based on the payment limit.

[0083] These embodiments may also begin with step S61, which involves receiving a purchase request for at least one product. For further details, please refer to the description of step S21 described above.

[0084] In step S62, information related to the user's payment method may be obtained. This payment method information may include the priority and remaining limit of the payment method set by the user. For further details on this step, please refer to the description of step S22 above.

[0085] In step S63, a payment method for at least one product may be determined based on the priority and remaining balance. The determined payment method may be provided to the user via a payment interface. For further details, please refer to the descriptions in step S25, Figures 4 and 5 described above.

[0086] For example, to explain further, if the remaining limit amount of the first payment method with the highest priority is greater than the payment amount of at least one product (i.e., the total payment amount), the service server (11) can determine the first payment method as the purchase payment method.

[0087] As another example, if the remaining limit amount of the first payment method with the highest priority is less than the payment amount of at least one product (i.e., the total payment amount), the service server (11) may determine the first payment method and the second payment method (i.e., the next highest priority payment method) as the purchase payment methods. In this case, the payment amount of the second payment method may be, for example, a value that is a limit value of the remaining limit amount of the first payment method minus the total payment amount; however, the scope of the present disclosure is not limited thereto.

[0088] The payment service provision method according to several other embodiments of the present disclosure has been described with reference to FIG. 6. As described above, the purchase payment method can be determined by faithfully reflecting the user's explicit intent (e.g., preference for payment method, payment method usage plan).

[0089] Hereinafter, a payment service provision method according to several other embodiments of the present disclosure will be described with reference to FIG. 7. However, for clarity of the present disclosure, descriptions of overlapping content from the previous embodiments will be omitted.

[0090] As illustrated in FIG. 7, the present embodiments relate to a method for determining a purchase payment method based on the payment method's performance shortfall amount.

[0091] These embodiments may also begin with step S71, which involves receiving a purchase request for at least one product. For further details, please refer to the description of step S21 described above.

[0092] In step S72, information related to the user's payment method may be obtained. This payment method information may include the outstanding balance of previously registered payment methods. For further details on this step, please refer to the description of step S22 above.

[0093] In step S73, a payment method for purchasing at least one product may be determined based on the outstanding balance. For example, the service server (11) may select a payment method among the previously registered payment methods with an outstanding balance exceeding a threshold (e.g., the payment method with the highest outstanding balance, multiple payment methods with outstanding balances exceeding the threshold) as the purchase payment method. The determined payment method may be provided to the user via a payment interface. For details, refer to the descriptions of step S25, FIGS. 4 and 5 described above.

[0094] In some embodiments, the payment amount for each payment method may be determined based on the outstanding balance. For example, assume that the first payment method and the second payment method are determined as the purchase payment methods. In this case, the service server (11) may determine the payment amounts for each of the first and second payment methods based on the outstanding balances of each of the first and second payment methods. For example, the service server (11) may calculate the payment amount for each payment method based on the ratio of the outstanding balances of the payment methods (e.g., payment amount for the first payment method = total payment amount of purchased goods * (outstanding balance of the first payment method / outstanding balance of the second payment method)). However, the scope of the present disclosure is not limited thereto.

[0095] So far, with reference to FIG. 7, a payment service provision method according to several other embodiments of the present disclosure has been described. As described above, since the likelihood of a payment method achieving performance (i.e., the likelihood of receiving benefits based on performance achievement) increases, user satisfaction with e-commerce services and payment services can be further enhanced.

[0096] Hereinafter, a payment service provision method according to several other embodiments of the present disclosure will be described with reference to FIG. 8. However, for clarity of the present disclosure, descriptions of overlapping content from the previous embodiments will be omitted.

[0097] As illustrated in FIG. 8, the present embodiments relate to a method for determining a purchase payment method using a deep learning model.

[0098] These embodiments may begin with step S81, which acquires a deep learning model trained using payment history data from multiple users. For ease of understanding, the structure and training method of an exemplary deep learning model will be described below with reference to FIGS. 9 and 10.

[0099] FIG. 9 illustrates the input and output of a deep learning model (90) according to some embodiments of the present disclosure.

[0100] As illustrated in FIG. 9, the deep learning model (90) according to the embodiments may be configured to receive user information, context information, product information, etc., and output (predict) a confidence score (i.e., probability value) for each payment method. In some cases, the deep learning model (90) may be configured to further receive information (e.g., ID, name, type, payment amount, etc.) of the N-1th payment method (where N is a value greater than or equal to 1) and output a confidence score for the Nth payment method. In addition, as described below, the deep learning model (90) may be configured to further output a confidence score for each type of payment method, or may be configured to receive only some of the information exemplified in FIG. 9.

[0101] User information may include, but is not limited to, demographic information such as gender, age group, membership status, etc. If such user information is explicitly provided, a deep learning model (90) can be trained to predict payment methods based on the user's type (or characteristics).

[0102] Next, context information may include, for example, general context information and payment context information.

[0103] General context information may include, but is not limited to, the time of payment, the day of the week, and the type of user terminal (e.g., mobile terminal, fixed terminal, etc.). If such general context information is explicitly provided, a deep learning model (90) can be trained to predict a payment method by taking into account the user's current context.

[0104] Payment context information may include, but is not limited to, the amount charged to PayMoney (i.e., a rechargeable payment method), the account amount, information on payment methods used for previous purchases (e.g., payment method, type of payment method, etc.), information related to previously registered payment methods (e.g., number, priority, remaining limit amount, insufficient performance amount, benefit amount, etc.), etc. If such payment context information is explicitly provided, the deep learning model (90) can be trained to predict the payment method by taking into account the context related to the user's previously registered payment method.

[0105] Next, product information may include, but is not limited to, information such as the product ID, name, category, price, and options. If such product information is explicitly provided, a deep learning model (90) can be trained to predict the payment method by considering the characteristics of the purchased product.

[0106] Below, the detailed structure and learning method of the deep learning model (90) will be described with reference to FIG. 10.

[0107] As illustrated in FIG. 10, a deep learning model (90) may be configured to include embeddings (101 to 104), an encoder (105), and predictors (106, 107). The number of embeddings (101 to 104) and predictors (106, 107) may vary depending on the case.

[0108] Embedders (101 to 104) can generate embeddings (e.g., embedding vectors) for input information. For example, the first embedding (101) can generate an embedding for user information, and the fourth embedding (104) can generate an embedding for product information. Each of the embeddings (101 to 104) may be implemented based on a neural network such as a multi-layer perceptron (MLP), but the scope of the present disclosure is not limited thereto.

[0109] Next, the encoder (105) can encode the embeddings generated by the embeddings (101 to 104). To analyze the correlation between various pieces of information and to compile the information based on the correlation, the encoder (105) can be implemented based on an attention module and MLP, but the scope of the present disclosure is not limited thereto.

[0110] Next, the predictors (106, 107) can perform a predetermined task based on the encoding result (i.e., the output of the encoder (105)). As a result, a confidence score for the task can be output. Each of the predictors (106, 107) may be implemented based on a neural network such as a fully-connected layer, but the scope of the present disclosure is not limited thereto.

[0111] Specifically, the first predictor (106) may be configured to output (predict) a confidence score for each type of payment method based on the encoding result, and the second predictor (107) may be configured to output (predict) a confidence score for each payment method based on the encoding result. Here, the type of payment method refers to a category (or group) to which payment methods having the same or similar characteristics belong. That is, the second predictor (107) may be understood to be different from the first predictor (106) in that it performs prediction by classifying each individual payment method into different classes (e.g., the second predictor (107) classifies 'card 1' and 'card 2' into different classes, but the first predictor (106) classifies 'card 1' and 'card 2' into the same class).

[0112] In some embodiments, as illustrated, the predictors (106, 107) may be configured to further input information on the (N-1)th (where N is a value greater than or equal to 1) payment method (i.e., a purchase payment method) and perform predictions related to the Nth payment method (e.g., payment method type prediction, payment method prediction, etc.). For example, if the payment history data includes composite payment samples (i.e., data of a case in which a single product was purchased through composite payment), the predictors (106, 107) may perform a task of predicting the Nth payment method when the (N-1)th payment method is selected using the composite payment samples.

[0113] The aforementioned deep learning model (90) can be trained by performing various tasks using payment history data. At this time, the payment history data may include user information (i.e., learning user information), product information, context information, and payment method information, as illustrated in FIG. 9, and at least a portion of the payment method information may be used as label information for learning.

[0114] For example, the deep learning model (90) may be trained by performing a first task of predicting the type of payment method (or the Nth payment method) through a first predictor (106). Alternatively, the deep learning model (90) may be trained by performing a second task of predicting the payment method (or the Nth payment method) through a second predictor (107). Of course, the deep learning model (90) may also be trained by performing the first task and the second task together.

[0115] In some embodiments, the deep learning model (90) may further include a third predictor (not shown). The third predictor (not shown) may be a neural network that predicts the number of payment methods used for a single product purchase, such as a classifier that predicts whether the number of payment methods is multiple. In the present embodiments, the deep learning model (90) may be trained by further performing a third task (e.g., predicting whether a multiple payment method is used) that predicts the number of payment methods through the third predictor (not shown).

[0116] In addition, in some embodiments, the deep learning model (90) may be trained using only data (samples) in which the maximum benefit amount is less than a threshold in the payment history data so that the deep learning model (90) can learn the payment method preferences of users with the minimal influence of the benefit amount. Alternatively, the deep learning model (90) may be trained in a manner that varies the sample weights (or learning strengths) in consideration of the maximum benefit amount and the payment method actually used for purchase (e.g., training is performed with a first weight for samples in which the maximum benefit amount is less than a threshold, training is performed with a second weight that is higher than the first weight for samples in which the maximum benefit amount is greater than the threshold but the payment method related to the benefit was not used as the payment method for purchase, training is performed with a third weight that is lower than the first weight for samples in which the maximum benefit amount is greater than the threshold and the payment method related to the benefit was used as the payment method for purchase, etc.).

[0117] This is explained again with reference to Figure 8.

[0118] In step S82, a purchase request for at least one product may be received from the user's terminal. For further details, please refer to the description of step S21 described above.

[0119] In step S83, information constituting the input of the deep learning model may be acquired. For example, the service server (11) may acquire user information, information on a requested product for purchase, and the user's current context information (e.g., general context, payment context). If necessary, the service server (11) may also acquire additional information that does not constitute the input of the deep learning model (e.g., some information related to previously registered payment methods).

[0120] In step S84, the acquired information can be input into a trained deep learning model to perform predictions regarding payment methods. For example, the service server (11) can input the previously exemplified information (see FIG. 9) into a trained deep learning model (90) to predict the type of payment method, the payment method, the number of payment methods, etc. Such predictions can be performed through corresponding predictors (e.g., 106, 107). Further reference is made to FIG. 10 and the description below for further details.

[0121] In step S85, a payment method for at least one product may be determined based on the prediction results. The determined payment method may be provided to the user through a payment interface.

[0122] For example, the service server (11) can predict the type of payment method through the first predictor (106) of the learned deep learning model (90). Then, the service server (11) can determine a payment method belonging to the predicted type (e.g., a type with a confidence score higher than a standard value) among a plurality of pre-registered payment methods as a purchase payment method.

[0123] As another example, the service server (11) can predict a payment method through the second predictor (107) of the trained deep learning model (90). In addition, if a predicted payment method (e.g., a payment method with a confidence score higher than a reference value) exists among a plurality of pre-registered payment methods, the service server (11) can determine the predicted payment method as a purchase payment method. If the predicted payment method does not exist among a plurality of pre-registered payment methods, the service server (11) can predict the type of payment method through the first predictor (106) of the trained deep learning model (90) and determine a payment method belonging to the predicted type as a purchase payment method. Alternatively, the service server (11) can also determine a purchase payment method in another manner (e.g., a manner exemplified in FIGS. 2 to 7).

[0124] As another example, the service server (11) can predict the number of payment methods through the third predictor (not shown) of the trained deep learning model (90). In addition, when the number of predicted payment methods is plural, the service server (11) can perform a prediction related to the Nth payment method by further inputting information on the (N-1)th payment method into the trained deep learning model (90). In addition, the service server (110) can determine the purchase payment method based on the prediction result. As a more specific example, the service server (11) can predict the first payment method by further inputting information indicating that it is the first payment method prediction (e.g., a null vector, a vector having a predefined value) into the second predictor (107). In addition, the service server (11) can predict the second payment method by further inputting information on the first payment method into the second predictor (107). This prediction process can be repeated a number of times predicted by a third predictor (not shown) or a preset number of times, and the predicted payment methods can be determined as the purchase payment methods. As another example, if the first purchase payment method is determined in another manner (e.g., user selection, the method exemplified in FIGS. 2 to 7, etc.), the service server (11) can further input information about the first purchase payment method into the predictors (106, 107) to perform a prediction regarding the second purchase payment method.

[0125] Meanwhile, in some embodiments, the payment amount for each payment method may be determined based on the confidence score for each payment method. For example, the service server (11) may determine payment methods with a confidence score above a threshold as purchase payment methods and determine the payment amount for each payment method based on the ratio of the confidence scores of the payment methods (i.e., the payment amount for each payment method is determined in proportion to the confidence score).

[0126] Heretofore, a payment service providing method according to several other embodiments of the present disclosure has been described with reference to FIGS. 8 to 10 . As described above, a user's purchase payment method can be determined using a deep learning model (90) trained on payment history data (e.g., user information, product information, payment method information, etc.) of multiple users. Since the trained deep learning model (90) can comprehensively consider the product characteristics, user type, etc. to predict the user's preferred payment method, in this case, the user's preferred payment method can be accurately determined as the purchase payment method.

[0127] The various embodiments of the payment service provision method described with reference to FIGS. 2 through 10 thus far can be combined in various forms. In other words, the service server (11) (or service system (10)) may provide a payment service based on various combinations of the above-described embodiments.

[0128] For example, as illustrated in FIG. 11, the service server (11) may determine a purchase payment method for at least one product based on the priority, remaining limit amount, and benefit amount of the user's pre-registered payment methods in response to a purchase request from the user terminal (13) (S111 to S117). Specifically, the service server (11) may determine a purchase payment method based on the maximum benefit amount based on a judgment that the maximum benefit amount is greater than or equal to a reference value (S115, S116), and may determine a purchase payment method based on the priority and remaining limit amount based on a judgment that the maximum benefit amount is less than the reference value (S115, S117).

[0129] As another example, if the maximum benefit amount is less than the standard, the service server (11) may determine the purchase payment method based on the predicted results of the learned deep learning model (90), the insufficient performance amount, etc.

[0130] As another example, if a first product is associated with a maximum benefit amount (i.e., applicable payment benefits exist) and a second product is unrelated to the maximum benefit amount (i.e., no applicable payment benefits exist), the service server (11) may determine the first payment method (i.e., the payment method associated with the maximum benefit amount) as the purchase payment method for the first product and the second payment method as the purchase payment method for the second product. In this case, the second payment method may be determined based on the priority, the remaining limit amount, the insufficient performance amount, the prediction results of the trained deep learning model (90), etc.

[0131] As another example, the service server (11) may determine a purchase payment method by comprehensively considering the priority of previously registered payment methods, the remaining limit amount, the insufficient performance amount, and the prediction result of the learned deep learning model (90).

[0132] Hereinafter, an exemplary computing device (120) capable of implementing a service system (10, e.g., service server (11), payment server (12)) according to some embodiments of the present disclosure will be described with reference to FIG. 12.

[0133] Figure 12 is an exemplary hardware configuration diagram showing a computing device (120).

[0134] As illustrated in FIG. 12, the computing device (120) may include one or more processors (121), a bus (123), a communication interface (124), a memory (122) for loading a computer program (126) executed by the processor (121), and a storage (125) for storing the computer program (126). However, only components related to the embodiment of the present disclosure are illustrated in FIG. 12. Therefore, a person skilled in the art to which the present disclosure pertains will appreciate that other general components may be included in addition to the components illustrated in FIG. 12. That is, the computing device (120) may further include various components in addition to the components illustrated in FIG. 12. In addition, in some cases, the computing device (120) may be configured in a form in which some of the components illustrated in FIG. 12 are omitted. Hereinafter, each component of the computing device (120) will be described.

[0135] The processor (121) can control the overall operation of each component of the computing device (120). The processor (121) can be configured to include at least one of a CPU (Central Processing Unit), an MPU (Micro Processor Unit), an MCU (Micro Controller Unit), a GPU (Graphics Processing Unit), an NPU (Neural Processing Unit), or any other type of processor well known in the art of the present disclosure. In addition, the processor (121) can perform operations for at least one application or program for executing operations / methods according to embodiments of the present disclosure. The computing device (120) can include one or more processors.

[0136] Next, the memory (122) can store various data, commands, and / or information. The memory (122) can load a computer program (126) from the storage (125) to execute operations / methods according to embodiments of the present disclosure. The memory (122) may be implemented as a volatile memory such as RAM, but the technical scope of the present disclosure is not limited thereto.

[0137] Next, the bus (123) can provide a communication function between components of the computing device (120). The bus (123) can be implemented as various types of buses such as an address bus, a data bus, and a control bus.

[0138] Next, the communication interface (124) can support wired and wireless Internet communication of the computing device (120). Furthermore, the communication interface (124) can also support various communication methods other than Internet communication. To this end, the communication interface (124) can be configured to include a communication module well known in the technical field of the present disclosure.

[0139] Next, the storage (125) can non-temporarily store one or more computer programs (126). The storage (125) can be configured to include non-volatile memory such as Read Only Memory (ROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), flash memory, a hard disk, a removable disk, or any form of computer-readable recording medium well known in the art to which the present disclosure pertains.

[0140] Next, the computer program (126) may include one or more instructions that cause the processor (121) to perform operations / methods according to various embodiments of the present disclosure when loaded into the memory (122). That is, the processor (121) may perform operations / methods according to various embodiments of the present disclosure by executing the one or more instructions.

[0141] For example, the computer program (126) may include instructions for performing an operation of receiving a purchase request for at least one product from a user's terminal, an operation of obtaining payment method-related information of the user in response to the purchase request, wherein the payment method-related information includes priorities of a plurality of pre-registered payment methods, and the priorities are set by the user, an operation of obtaining payment benefit information for at least some of the plurality of payment methods, an operation of calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information, and an operation of determining a purchase payment method for at least one product from among the plurality of payment methods based on the benefit amount and the priority.

[0142] As another example, the computer program (126) may include instructions to perform at least some of the steps / operations described with reference to FIGS. 1 through 11.

[0143] In the case as exemplified, a service system (10, eg, service server (11)) according to some embodiments of the present disclosure can be implemented through a computing device (120).

[0144] Meanwhile, in some embodiments, the computing device (120) illustrated in FIG. 12 may refer to a virtual machine implemented based on cloud technology. For example, the computing device (120) may be a virtual machine operating on one or more physical servers included in a server farm. In this case, at least some of the processor (121), memory (122), and storage (125) illustrated in FIG. 12 may be virtual hardware, and the communication interface (124) may also be implemented as a virtualized networking element, such as a virtual switch.

[0145] So far, an exemplary computing device (120) capable of implementing a service system (10) according to some embodiments of the present disclosure has been described with reference to FIG. 12.

[0146] Various embodiments of the present disclosure and effects according to the embodiments have been described with reference to FIGS. 1 through 12. The effects according to the technical concept of the present disclosure are not limited to the effects described above, and other effects not mentioned will be clearly understood by those skilled in the art from the description below.

[0147] Furthermore, even though the above embodiments have described multiple components as being combined or operating in combination, the technical concept of the present disclosure is not necessarily limited to these embodiments. That is, within the scope of the technical concept of the present disclosure, all of the components may be selectively combined and operated one or more times.

[0148] The technical concepts of the present disclosure described so far can be implemented as computer-readable code on a computer-readable recording medium. A computer program recorded on the computer-readable recording medium can be transmitted to another computing device via a network such as the Internet, installed on the device, and used therein.

[0149] Although the operations are depicted in a specific order in the drawings, it should not be understood that the operations must be performed in the specific order depicted, or in a sequential order, or that all depicted operations must be performed to achieve the desired result. In certain circumstances, multitasking and parallel processing may be advantageous. Although various embodiments of the present disclosure have been described above with reference to the attached drawings, those skilled in the art to which the present disclosure pertains will understand that the technical concepts of the present disclosure can be implemented in other specific forms without changing the technical concepts or essential characteristics thereof. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. The scope of protection of the present disclosure should be interpreted by the claims below, and all technical ideas within a scope equivalent thereto should be interpreted as being included in the scope of the technical ideas defined by the present disclosure.

Claims

1. A method performed on at least one computing device, A step of receiving a purchase request for at least one product from a user's terminal; In response to the purchase request, a step of obtaining payment method-related information of the user, wherein the payment method-related information includes priorities of a plurality of previously registered payment methods, and the priorities are set by the user; A step of obtaining payment benefit information for at least some of the above multiple payment methods; A step of calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information; and A step of determining a purchase payment method for at least one product among the plurality of payment methods based on the benefit amount and the priority, Method of providing payment services.

2. In paragraph 1, The above payment benefit information includes payment benefit information provided by an e-commerce service provider for at least one product and payment benefit information provided by a payment method provider. Method of providing payment services.

3. In paragraph 1, The above payment benefit information includes payment benefit information according to day of the week, date and time. Method of providing payment services.

4. In paragraph 1, The step of determining a payment method for the purchase of at least one product is as follows: A step of determining the purchase payment method based on the maximum benefit amount based on a judgment that the maximum benefit amount for the plurality of payment methods is greater than or equal to a reference value, Method of providing payment services.

5. In paragraph 1, The step of determining a payment method for the purchase of at least one product is as follows: Including a step of determining the purchase payment method according to the priority based on a judgment that the maximum benefit amount for the plurality of payment methods is less than a reference value. Method of providing payment services.

6. In paragraph 5, The above payment method related information includes the remaining limit amount calculated based on the payment limit amount set by the user, The step of determining the purchase payment method according to the above priority is: Including a step of determining the purchase payment method based on the remaining limit amount of the plurality of payment methods. Method of providing payment services.

7. In paragraph 6, The step of determining the purchase payment method further based on the remaining limit amount of the above multiple payment methods is as follows: A step of determining the first payment method and the second payment method as the purchase payment method based on a judgment that the remaining limit amount of the first payment method with the highest priority is less than the payment amount for the at least one product, wherein the second payment method is a payment method with the second highest priority after the first payment method. Method of providing payment services.

8. In paragraph 1, Further comprising a step of providing a payment interface in which the above-determined purchase payment method is selected, The above payment interface includes an interface for selecting an additional purchase payment method from the user. Method of providing payment services.

9. In paragraph 1, Further comprising a step of providing a payment interface in which the above-determined purchase payment method is selected, The payment interface includes an interface for registering a combination of two or more payment methods from the user or for retrieving a combination of pre-registered payment methods based on the user's input. Method of providing payment services.

10. In paragraph 1, The above payment method related information includes the amount of performance shortfall for each of the multiple payment methods, Further comprising a step of determining another purchase payment method among the plurality of payment methods based on the above performance shortfall amount. Method of providing payment services.

11. In paragraph 1, The above payment method related information includes the amount of performance shortfall for each of the multiple payment methods, The above-determined purchase payment method includes the first payment method and the second payment method, Further comprising a step of determining the payment amount of each of the first payment method and the second payment method based on the above performance shortfall amount. Method of providing payment services.

12. In paragraph 1, A step of obtaining a deep learning model trained using payment history data, wherein the payment history data includes user information for learning, product information for learning, and payment method information for learning; A step of inputting the user's information and the information of at least one product into the learned deep learning model to perform a prediction regarding the payment method; and Further comprising a step of determining another purchase payment method among the plurality of payment methods based on the result of the above prediction, The above deep learning model is trained by receiving the learning user information and the learning product information and performing a first task of predicting the type of payment method through a first predictor and a second task of predicting the payment method through a second predictor. Method of providing payment services.

13. In paragraph 12, The above deep learning model was trained by performing a third task of predicting the number of payment methods used to purchase a product through a third predictor. The step of performing prediction regarding the above payment method is: A step of predicting the number of payment methods for at least one product through the third predictor of the learned deep learning model; and In the case where the number of the predicted payment methods is plural, the step of further inputting information of the determined purchase payment method into the learned deep learning model and predicting the other purchase payment method through the second predictor of the learned deep learning model is included. Method of providing payment services.

14. One or more processors; and A memory storing a computer program executed by one or more processors, The above computer program: An action of receiving a purchase request for at least one product from a user's terminal; In response to the purchase request, an action of obtaining payment method-related information of the user, wherein the payment method-related information includes priorities of a plurality of previously registered payment methods, and the priorities are set by the user; An action of obtaining payment benefit information for at least some of the above multiple payment methods; An operation of calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information; and Including instructions for an operation of determining a purchase payment method for at least one product among the plurality of payment methods based on the benefit amount and the priority. Payment service provision system.

15. Combined with a computing device, A step of receiving a purchase request for at least one product from a user's terminal; In response to the purchase request, a step of obtaining payment method-related information of the user, wherein the payment method-related information includes priorities of a plurality of previously registered payment methods, and the priorities are set by the user; A step of obtaining payment benefit information for at least some of the above multiple payment methods; A step of calculating a benefit amount for each of the plurality of payment methods based on the payment benefit information; and In order to execute a step of determining a purchase payment method for at least one product among the plurality of payment methods based on the benefit amount and the priority, stored in a computer-readable recording medium, Computer program.

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