Recommended payment methods, devices, and electronic equipment

Abstract

This application discloses a payment method recommendation method, apparatus, and electronic device. The method includes: receiving a request to pay for a target transaction order, wherein the target transaction order is a cross-border transaction order; determining multiple candidate payment methods; obtaining multiple decision factors of a multi-objective decision algorithm based on information of the target transaction order, wherein the multiple decision factors include: the country / region information of the payer user and the initiator information of the target transaction order; evaluating the multiple candidate payment methods based on the multiple decision factors; and determining recommended payment method information based on the evaluation results corresponding to the multiple candidate payment methods. This application embodiment helps to improve the overall payment conversion rate in cross-border transaction scenarios.

Description

Technical Field

[0001] This application relates to the field of order processing technology, and in particular to methods, apparatus and electronic devices for recommending payment methods. Background Technology

[0002] In cross-border commodity information service systems, transactions involve users from multiple different countries / regions, and most of these transactions occur between businesses—that is, a B2B (Business-to-Business) model. Therefore, compared to typical B2C (Business-to-Customer) or C2C (Customer-to-Customer) models, the payment methods involved are likely to be more diverse. However, buyers may find themselves unsure of which payment method to choose from when faced with numerous options.

[0003] To address the above situation, existing technologies typically rely on human experience to establish ranking rules for various payment methods. This allows for the sorting of payment methods according to these rules, and the selection of the top-ranked or other frequently mentioned methods can then be made to assist users in their choices. However, this rule-based decision-making based on expert experience has a certain lag and cannot meet the needs of refined recommendations in cross-border scenarios (especially cross-border B2B scenarios). Summary of the Invention

[0004] This application provides payment method recommendation methods, devices, and electronic devices, which are beneficial to improving payment conversion rates in cross-border scenarios (especially cross-border B2B scenarios) as a whole.

[0005] This application provides the following solution:

[0006] A payment method recommendation method includes:

[0007] Receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0008] Identify multiple candidate payment methods;

[0009] Based on the information of the target transaction order, multiple decision factors for a multi-objective decision-making algorithm are obtained; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order;

[0010] The various candidate payment methods are evaluated based on the aforementioned decision factors;

[0011] Based on the evaluation results of the various candidate payment methods, the recommended payment method information is determined.

[0012] The evaluation of the multiple candidate payment methods based on the multiple decision factors includes:

[0013] Based on the country information of the buyer users, a higher evaluation score is assigned to the payment method that the buyer users of that country are more likely to choose under this decision factor.

[0014] The evaluation of the multiple candidate payment methods based on the multiple decision factors includes:

[0015] Based on the initiator information of the target transaction order, the degree of uncertainty of the target transaction order is predicted, so as to assign a corresponding evaluation score to the candidate payment method under the decision factor according to the degree of uncertainty.

[0016] The step of predicting the degree of uncertainty of the target transaction order based on the initiator information of the target transaction order includes:

[0017] If the initiator of the target transaction order is the buyer user, the uncertainty of the target transaction order is determined to be high, and the candidate payment method with a shorter transfer path is assigned a higher evaluation score under this decision factor.

[0018] The step of predicting the degree of uncertainty of the target transaction order based on the initiator information of the target transaction order includes:

[0019] If the initiator of the target transaction order is the seller user, the uncertainty of the target transaction order is determined to be low, and the candidate payment method with higher payment certainty is assigned a higher evaluation score under this decision factor.

[0020] The various decision factors also include: the model information of the terminal device associated with the buyer user, so as to predict the payment success rate of the candidate payment methods in combination with the model information, and assign a higher evaluation score to the candidate payment methods with higher payment success rates.

[0021] If the buyer is not a first-time transaction user, the multiple decision factors also include: the buyer user's historical payment records for cross-border transaction orders;

[0022] The evaluation of the multiple candidate payment methods based on the multiple decision factors includes:

[0023] Based on the historical payment records, the candidate payment methods that the buyer user has historically selected and successfully paid for, or the candidate payment methods that have recently been selected and successfully paid for, are assigned a higher evaluation score under this decision factor.

[0024] The evaluation of the multiple candidate payment methods based on the multiple decision factors includes:

[0025] Based on the aforementioned multiple decision factors, the buyer's willingness to choose the candidate payment method and / or the payment success rate corresponding to the candidate payment method are predicted;

[0026] Based on the willingness to choose the candidate payment method and / or the payment success rate corresponding to the candidate payment method, the payment conversion rate corresponding to the candidate payment method is determined, and the candidate payment method is evaluated based on the payment conversion rate.

[0027] A payment method recommendation method includes:

[0028] Receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0029] The request is submitted to the server so that the server can determine multiple candidate payment methods. Based on the information of the target transaction order, the server obtains multiple decision factors of a multi-objective decision algorithm, evaluates the multiple candidate payment methods based on the multiple decision factors, and determines the recommended payment method based on the evaluation results of the multiple candidate payment methods. The multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order.

[0030] The target page displays the various candidate payment methods and provides information about the recommended payment method.

[0031] A payment method recommendation device, comprising:

[0032] A request receiving unit is used to receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0033] The candidate payment method determination unit is used to determine multiple candidate payment methods;

[0034] The decision factor acquisition unit is used to acquire multiple decision factors for a multi-objective decision algorithm based on the information of the target transaction order; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order;

[0035] An evaluation unit is used to evaluate the multiple candidate payment methods based on the multiple decision factors;

[0036] The recommendation unit is used to determine the recommended payment method information based on the evaluation results corresponding to the multiple candidate payment methods.

[0037] A payment method recommendation device, comprising:

[0038] A request receiving unit is used to receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0039] The request submission unit is used to submit the request to the server so that the server can determine multiple candidate payment methods, and after obtaining multiple decision factors of a multi-objective decision algorithm based on the information of the target transaction order, evaluate the multiple candidate payment methods based on the multiple decision factors, and determine the recommended payment method information based on the evaluation results of the multiple candidate payment methods; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order;

[0040] The display unit is used to display the various candidate payment methods on the target page and provide information about the recommended payment methods.

[0041] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of any of the preceding methods.

[0042] An electronic device, comprising:

[0043] One or more processors; and

[0044] A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any of the preceding descriptions.

[0045] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0046] Through the embodiments of this application, for cross-border transaction order payment requests, multiple candidate payment methods can be evaluated based on various decision factors such as the payer's country of origin and the initiator information of the target transaction order. Then, based on the evaluation results of the candidate payment methods, the preferred payment method can be determined. This approach, by considering factors such as country of origin and order initiator, is more suitable for predicting payment methods with higher payment conversion rates in cross-border transaction scenarios, thereby improving the overall payment conversion rate in cross-border transaction scenarios (especially cross-border B2B scenarios).

[0047] Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0048] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0049] Figure 1 This is a schematic diagram of the system architecture provided in the embodiments of this application;

[0050] Figure 2 This is a flowchart of the first method provided in the embodiments of this application;

[0051] Figure 3 This is a flowchart of the second method provided in the embodiments of this application;

[0052] Figure 4 This is a schematic diagram of the first device provided in the embodiments of this application;

[0053] Figure 5 This is a schematic diagram of the second device provided in the embodiments of this application;

[0054] Figure 6 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0055] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0056] First, it's important to clarify that to more effectively and promptly recommend payment methods to users, another approach is to use algorithms for decision-making, rather than relying on manually defined rules. However, existing recommendation algorithms are typically implemented in B2C or C2C scenarios. Since the actual buyers in B2C or C2C scenarios are usually individual users, these algorithms primarily recommend payment methods based on the buyer's historical payment records. In other words, in B2C or C2C scenarios, the specific consumption patterns are relatively simple, and the order amounts are usually small. Users choose payment methods mainly based on personal preferences. Furthermore, in these B2C or C2C scenarios, users' historical payment information is usually quite rich. Therefore, existing recommendation algorithms can use individual users' historical payment records to statistically analyze the payment methods users prefer and then recommend them. Of course, other decision-making strategies can be combined, including payment method promotion strategies, to provide a comprehensive recommendation result.

[0057] However, in cross-border transaction scenarios, especially cross-border B2B scenarios, there are at least the following differences compared to ordinary B2C or C2C scenarios: 1. Transactions mainly occur between enterprises, usually involving enterprise procurement transactions with relatively large amounts involved; 2. There are significant differences in the support for various payment methods across different countries / regions; 3. Transactions between buyers and sellers may not be as frequent as in B2C or C2C scenarios, and there may be a large number of new users who may not even have historical payment records, making it difficult to statistically analyze user preferences in payment methods; 4. When returns or exchanges are involved, due to the cross-border payment involved, the fund transfer path may be longer, and different payment methods will have significantly different fund transfer paths, etc.

[0058] Considering the above, in this embodiment, a decision algorithm can still be used to recommend payment methods in cross-border scenarios. However, the specific decision algorithm, when making recommendations, will no longer primarily consider personal preferences derived from the buyer's historical payment history, but rather factors such as the buyer's country / region and the initiator of the transaction order. This allows for prediction of the buyer's willingness to choose a specific payment method based on localized payment habits among users in the same country / region. Furthermore, in cross-border transactions, especially in B2B scenarios, orders can be initiated by either the buyer or the seller. Different initiators often mean different levels of uncertainty. For example, orders initiated by the buyer tend to have higher uncertainty, with a higher probability of cancellation or returns. Orders initiated by the seller, on the other hand, are usually initiated after a contract has been signed offline, resulting in lower uncertainty and a lower probability of cancellation or returns. Therefore, the recommended payment method can vary depending on the initiator of the transaction order. Of course, in practice, the specific implementation can also consider information such as the model of the buyer's terminal device and the historical payment records of buyers who are not first-time transactors, to make a comprehensive recommendation.

[0059] Regarding decision-making algorithms, since there are typically multiple decision factors, including the buyer's country / region, the order initiator, the device model, historical payment records, etc., the specific decision-making algorithm can be a multi-objective decision-making algorithm. Specifically, in the recommendation process, various candidate payment methods can be scored based on different decision factors. Then, according to the weights of each decision factor, the scores obtained by each candidate payment method under different decision factors are weighted and summed or weighted averaged to obtain the total score of the candidate payment methods. Subsequently, the candidate payment methods can be ranked according to this total score to determine the preferred payment method. The weights corresponding to each decision factor can be determined initially based on the algorithm's training results. Furthermore, during actual operation, the weights of each decision factor can be adjusted and optimized based on the user's actual choices, payment success or failure, etc.

[0060] From a system architecture perspective, such as Figure 1As shown, this application embodiment can provide a function to recommend payment methods to buyer users in a cross-border transaction-related commodity information service system. Specifically, the system can include a client and a server. The client is mainly used to receive specific payment requests through a front-end or independent "online cashier" page (the page entered after confirming payment for online purchases, or the page displayed when the seller generates a payment link after drafting an order and sends it to the buyer, and the buyer clicks on the payment link, etc.). The specific decision-making algorithm can be deployed on the server. After receiving the payment request, the client can submit it to the server. After receiving the payment request submitted by the client, the server can call the decision engine to use a specific intelligent recommendation decision-making algorithm (this algorithm can be generated by pre-selecting relevant features and training and iteratively optimizing using historical payment data) to determine information such as country / region, currency, customer payment habits, and market share of payment methods based on the specific buyer user situation, transaction order situation, etc., and make a comprehensive decision to provide a preferred payment method for the user to choose from. Of course, the server can also provide some fallback strategies, such as ranking payment methods based on preset rules. Additionally, the ranking of payment methods can be adjusted based on marketing needs, and so on. Finally, the recommended results can be returned to the client, who can then display the specific recommendations on the "Checkout" page.

[0061] The specific implementation schemes provided in the embodiments of this application will be described in detail below.

[0062] Example 1

[0063] First, from the perspective of the aforementioned server, Embodiment 1 of this application provides a payment method recommendation method, see [link to embodiment]. Figure 2 The method may include:

[0064] S201: Receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order.

[0065] Specifically, a payment request for a target transaction order can be initiated by a user through a client, which then sends the request to the server. In this embodiment, the focus is primarily on cross-border transactions, particularly cross-border B2B scenarios, where the transacting parties are from different countries / regions. Furthermore, the payment process can be initiated in various ways; either party can be the initiator of the transaction order. For example, similar to a C-end user, the buyer browses product information in the system, selects suitable products, places an order, and initiates payment. This is a transaction order initiated (or "drafted") by the buyer. Alternatively, the buyer and seller may have already signed a purchase contract offline, and the seller initiates (drafts) the transaction order online, sending a payment link to the buyer for payment. In both cases, the payment request is initiated by the buyer, but the transaction order can be drafted by either the buyer or the seller. For the client, after receiving a payment request, it can identify the user who initiated the transaction order. When submitting the payment request to the server, it can include the initiator's information. Alternatively, the server can identify the initiator of the specific transaction order, and so on.

[0066] S202: Identify multiple candidate payment methods.

[0067] Upon receiving a payment request, multiple candidate payment methods can be identified. These candidate methods may support cross-border payments. Specifically, some payment methods may be universally accepted in multiple countries / regions, while others may only be supported in certain countries / regions. Therefore, candidate payment methods can be determined based on country information. Additionally, some payment methods may be related to the buyer's terminal device model; therefore, candidate payment methods can be further filtered based on the terminal device model.

[0068] S203: Obtain multiple decision factors for the multi-objective decision algorithm based on the information of the target transaction order. The multiple decision factors include: the country / region information of the payer user and the initiator information of the target transaction order.

[0069] After identifying multiple candidate payment methods, various decision factors for a multi-objective decision-making algorithm can be obtained based on the information of the target transaction order. For example, specific decision factors may include: the country / region of the payer user, and the initiator information of the target transaction order. Additionally, in optional scenarios, decision factors may also include the model information of the buyer user's associated terminal device, historical payment records for cross-border transaction orders, and so on.

[0070] The country / region of the payer user can be used to determine the required currency and exchange rate, allowing for the evaluation and selection of candidate payment methods based on their support for that currency and exchange rate. Since the degree of uncertainty in orders initiated by the payer or payee differs, and the support for different candidate payment methods or the processing time may vary in reverse flows such as refunds and returns, the evaluation and selection of candidate payment methods can be based on whether the target transaction order was initiated by the payer or payee.

[0071] S204: Evaluate the various candidate payment methods based on the various decision factors.

[0072] After identifying multiple decision factors, various candidate payment methods can be evaluated based on these factors. For example, in one specific implementation, the multi-objective decision algorithm can be used to evaluate the multiple candidate payment methods. There can be various specific evaluation methods. For instance, in one typical approach, each candidate method can be scored based on different decision factors, and then the scores of the same candidate payment method under multiple different decision factors can be weighted and summed or weighted averaged to obtain the total score of the candidate payment method, and so on.

[0073] The multi-objective decision-making algorithm can be obtained through pre-training. Specifically, during algorithm training, historical payment records related to cross-border transactions (especially cross-border B2B transactions) for multiple users can be used as the training dataset. Furthermore, in this embodiment, since each candidate payment method needs to be evaluated based on multiple decision factors, during model training, multiple decision factors such as the buyer's country of origin and the order initiator can be extracted from the historical payment records in the training dataset. Additionally, further decision factors such as order amount, terminal device type, the buyer's historically frequently used payment methods, and the most recently used payment method can be extracted. Using this information as input to the model, and with the objective of ensuring that the highest-scoring payment method output matches the payment method actually selected and successfully paid by the user, the multi-objective decision-making algorithm model is trained. After training, this objective decision-making algorithm model can be used to recommend payment methods for specific payment requests.

[0074] Specifically, there are multiple ways to evaluate a candidate payment method. For example, one approach is to score the candidate payment methods and compare these scores to determine the best choice. Specifically, candidate payment methods can be scored under different decision factors first, and then the scores obtained for the same candidate payment method under multiple decision factors can be weighted and summed or weighted averaged to obtain the final score. When scoring candidate payment methods under a specific decision factor, one implementation can predict the user's willingness to choose a particular candidate payment method and the payment success rate after selection. Based on the prediction results, the payment conversion rate of the candidate payment method can be determined, and then the candidate payment method can be scored based on this conversion rate. In other words, in this embodiment, the potential payment conversion rate of a candidate payment method can be evaluated from both the user's willingness to choose and the payment success rate, rather than solely considering the payment success rate. Alternatively, in a more preferred approach, in addition to factors such as user preference and payment success rate, consideration can also be given to the specific transfer path, especially the transfer path in the event of a refund.

[0075] Specifically, when evaluating candidate payment methods based on the buyer's country / region, a higher score can be assigned to payment methods that are more likely to be chosen by buyers from that country / region under this decision factor. In other words, in cross-border transactions, users from the same country / region often show consistency in their choice of payment methods. For example, if a payment method is an online payment method developed by a developer in a particular country / region that supports cross-border transfers, and buyers from that country / region generally prefer this method, then this payment method can obtain a higher score under the country / region decision factor.

[0076] Additionally, candidate payment methods can be scored based on the initiator information of the target transaction order (i.e., information regarding whether the initiator is the payer or the payee). Specifically, the degree of uncertainty of the target transaction order can be predicted based on the initiator information, so that an evaluation score can be assigned to the candidate payment method under this decision factor according to the degree of uncertainty. As mentioned above, since the specific transaction order in this embodiment can be drafted by either the buyer or the seller, the degree of uncertainty of the transaction order will be different for different drafters. Accordingly, when recommending payment methods, the recommendation of payment methods can also be based on the degree of uncertainty.

[0077] For example, when the order is initiated by the buyer, since users typically only review product information online before placing an order, the uncertainty is usually quite high, and the probability of subsequent order cancellations, refunds, or returns is relatively high. In this case, candidate payment methods with shorter transfer paths (e.g., online credit payments) can be assigned a higher evaluation score under this decision factor. However, if the target transaction order is initiated by the seller, since this usually occurs after the buyer and seller have signed a contract offline, the uncertainty of the target transaction order can be determined to be lower, meaning the probability of subsequent order cancellations, refunds, or returns is relatively low. In this case, candidate payment methods with higher payment certainty (e.g., bank transfers) can be assigned a higher evaluation score under this decision factor.

[0078] In addition, various decision factors may include the model information of the buyer's associated terminal device. This allows for the prediction of the payment success rate of the candidate payment methods based on the device model information, assigning higher evaluation scores to candidate payment methods with higher success rates. In other words, some payment methods may require support from the terminal device; therefore, the terminal device model can be assessed to assign higher evaluation scores to payment methods currently supported by the terminal device, while unsupported payment methods can be directly filtered out.

[0079] Furthermore, if the buyer is not a first-time transaction user, the various decision factors may also include the buyer's historical payment records for cross-border transaction orders. This allows for the assignment of higher evaluation scores to candidate payment methods with high historical selection rates and successful payments, or to candidate payment methods that were recently selected and successfully paid for, based on these historical payment records. For new users making their first transaction, the specific payment method can be scored based on decision factors such as the buyer's country / region, the order initiator, and the type of terminal device.

[0080] In summary, using the methods described above, various candidate payment methods can obtain corresponding scores under multiple decision factors. Then, the final score of a candidate payment method can be determined by weighted summation or weighted averaging of these scores under different decision factors. Since the evaluation scores under each decision factor can be determined by considering factors such as the buyer's willingness to choose the candidate payment method and the payment success rate of the specific payment method, the calculated total score can represent the payment conversion rate achievable by the specific payment method.

[0081] S205: Based on the evaluation results corresponding to the various candidate payment methods, determine the recommended payment method information.

[0082] After obtaining the evaluation results of each candidate payment method, the candidate payment methods can be sorted to determine the preferred payment method. This recommendation information can then be returned to the client, who can display it on a webpage. This page can be called the "online cashier" page, that is, the page entered after confirming payment for an online purchase. This page displays the seller's name, the amount to be paid, and various available payment methods. In this embodiment, payment methods can be recommended while displaying multiple payment methods on the aforementioned page. Specifically, the preferred payment method can be selected by default. If the user confirms the use of this method, they can directly click the "Pay" button on the page to complete the payment. Of course, if the user needs to use other payment methods, they can also select other payment methods on the aforementioned page and then click the "Pay" button, and so on. Furthermore, in practical applications, after providing recommended payment methods, information on subsequent actions by the buyer can be collected to statistically analyze the performance of the decision-making algorithm. This data can then be used to optimize and adjust parameters within the algorithm (including the weights of various decision factors). Alternatively, an A / B test can be conducted, using the algorithm with some users and not with others, comparing payment conversion rates in both scenarios to test the algorithm's performance.

[0083] In summary, through the embodiments of this application, for cross-border transaction order payment requests, multiple candidate payment methods can be evaluated based on various decision factors such as the payer's country of origin and the initiator information of the target transaction order. Then, based on the evaluation results of the candidate payment methods, the preferred payment method can be determined. This approach, by considering factors such as country of origin and order initiator, is more suitable for predicting payment methods with higher payment conversion rates in cross-border transaction scenarios, thereby improving the overall payment conversion rate in cross-border transaction scenarios.

[0084] Example 2

[0085] This second embodiment corresponds to the first embodiment and provides a payment method recommendation method from the client's perspective. See [link to embodiment]. Figure 3 The method may include:

[0086] S301: Receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0087] S302: The request is submitted to the server so that the server can determine multiple candidate payment methods, and after obtaining multiple decision factors of the multi-objective decision algorithm based on the information of the target transaction order, evaluate the multiple candidate payment methods based on the multiple decision factors, and determine the recommended payment method information based on the evaluation results corresponding to the multiple candidate payment methods; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order;

[0088] S303: Display the multiple candidate payment methods on the target page and provide information about the recommended payment method.

[0089] The target page could be a payment confirmation page, etc. When providing information about the recommended payment methods, there can be various methods. For example, the recommended payment methods can be prioritized, highlighted, or given a special label (e.g., adding "Recommended" after the corresponding payment method), and so on.

[0090] For details not described in this second embodiment, please refer to the description in the first embodiment and other parts of this specification. They will not be repeated here.

[0091] It should be noted that the embodiments of this application may involve the use of user data. In practical applications, user-specific personal data may be used in the scheme described herein within the scope permitted by applicable laws and regulations, provided that it complies with the applicable laws and regulations of the country (e.g., with the user's explicit consent, with the user being properly notified, etc.).

[0092] Corresponding to the aforementioned method embodiment one, this application embodiment also provides a payment method recommendation device, see [link to embodiment one]. Figure 4 The device may include:

[0093] The request receiving unit 401 is used to receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0094] The candidate payment method determination unit 402 is used to determine multiple candidate payment methods;

[0095] The decision factor acquisition unit 403 is used to acquire multiple decision factors of the multi-objective decision algorithm based on the information of the target transaction order; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order;

[0096] Evaluation unit 404 is used to evaluate the multiple candidate payment methods based on the multiple decision factors;

[0097] The recommendation unit 405 is used to determine the preferred payment method information based on the evaluation results corresponding to the candidate payment methods.

[0098] Specifically, the evaluation unit can be used for:

[0099] Based on the country / region information of the buyer users, the payment methods most frequently chosen by buyer users in that country / region are assigned a higher evaluation score under this decision factor.

[0100] Alternatively, the evaluation unit can be used for:

[0101] Based on the initiator information of the target transaction order, the degree of uncertainty of the target transaction order is predicted, so as to assign an evaluation score to the candidate payment method under the decision factor according to the degree of uncertainty.

[0102] Specifically, if the initiator of the target transaction order is the buyer user, the target transaction order is determined to have a high degree of uncertainty, and candidate payment methods with shorter transfer paths are assigned higher evaluation scores under this decision factor.

[0103] Alternatively, if the initiator of the target transaction order is the seller user, the uncertainty of the target transaction order is determined to be low, and a higher evaluation score is assigned to the candidate payment method with higher payment certainty under this decision factor.

[0104] In addition, the multiple decision factors may also include: the model information of the terminal device associated with the buyer user, so as to predict the payment success rate corresponding to the candidate payment method in combination with the model information, and assign a higher evaluation score to the candidate payment method with a higher payment success rate.

[0105] If the buyer is not a first-time transaction user, the multiple decision factors also include: the buyer user's historical payment records for cross-border transaction orders;

[0106] At this point, the evaluation unit can specifically be used for:

[0107] Based on the historical payment records, the candidate payment methods that the buyer user has historically selected and successfully paid for, or the candidate payment methods that have recently been selected and successfully paid for, are assigned a higher evaluation score under this decision factor.

[0108] Specifically, the evaluation unit can be used for:

[0109] The multi-objective decision-making algorithm is used to predict the buyer's willingness to choose the candidate payment method and / or the payment success rate corresponding to the candidate payment method.

[0110] Based on the willingness to choose the candidate payment method and / or the payment success rate corresponding to the candidate payment method, the payment conversion rate corresponding to the candidate payment method is determined, and the candidate payment method is evaluated based on the payment conversion rate.

[0111] Corresponding to Embodiment 2, this application also provides a payment method recommendation device, see [link to embodiment]. Figure 5 The device may include:

[0112] The request receiving unit 501 is used to receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order;

[0113] The request submission unit 502 is used to submit the request to the server so that the server can determine multiple candidate payment methods, and after obtaining multiple decision factors of the multi-objective decision algorithm based on the information of the target transaction order, evaluate the multiple candidate payment methods based on the multiple decision factors, and determine the recommended payment method information based on the evaluation results corresponding to the multiple candidate payment methods; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order;

[0114] The display unit 503 is used to display the multiple candidate payment methods on the target page and provide information about the recommended payment methods.

[0115] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in any of the foregoing method embodiments.

[0116] And an electronic device, comprising:

[0117] One or more processors; and

[0118] A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any of the foregoing method embodiments.

[0119] in, Figure 6 The architecture of an electronic device is illustrated by example. For instance, device 600 may be a mobile phone, computer, digital broadcasting terminal, messaging device, game console, tablet device, medical device, fitness equipment, personal digital assistant, aircraft, etc.

[0120] Reference Figure 6The device 600 may include one or more of the following components: a processing component 602, a memory 604, a power supply component 606, a multimedia component 608, an audio component 610, an input / output (I / O) interface 612, a sensor component 614, and a communication component 616.

[0121] Processing component 602 typically controls the overall operation of device 600, such as operations associated with display, telephone calls, data communication, camera operation, and recording operations. Processing component 602 may include one or more processors 620 to execute instructions to perform all or part of the steps of the methods provided in this disclosure. Furthermore, processing component 602 may include one or more modules to facilitate interaction between processing component 602 and other components. For example, processing component 602 may include a multimedia module to facilitate interaction between multimedia component 608 and processing component 602.

[0122] Memory 604 is configured to store various types of data to support the operation of device 600. Examples of this data include instructions for any application or method operating on device 600, contact data, phonebook data, messages, pictures, videos, etc. Memory 604 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0123] Power supply component 606 provides power to various components of device 600. Power supply component 606 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to device 600.

[0124] Multimedia component 608 includes a screen that provides an output interface between device 600 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touchscreen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensors may sense not only the boundaries of touch or swipe actions but also the duration and pressure associated with the touch or swipe operation. In some embodiments, multimedia component 608 includes a front-facing camera and / or a rear-facing camera. When device 600 is in an operating mode, such as a shooting mode or a video mode, the front-facing camera and / or rear-facing camera may receive external multimedia data. Each front-facing camera and rear-facing camera may be a fixed optical lens system or have focal length and optical zoom capabilities.

[0125] Audio component 610 is configured to output and / or input audio signals. For example, audio component 610 includes a microphone (MIC) configured to receive external audio signals when device 600 is in an operating mode, such as call mode, recording mode, and voice recognition mode. The received audio signals may be further stored in memory 604 or transmitted via communication component 616. In some embodiments, audio component 610 also includes a speaker for outputting audio signals.

[0126] I / O interface 612 provides an interface between processing component 602 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include, but are not limited to, home buttons, volume buttons, power buttons, and lock buttons.

[0127] Sensor assembly 614 includes one or more sensors for providing status assessments of various aspects of device 600. For example, sensor assembly 614 may detect the on / off state of device 600, the relative positioning of components such as the display and keypad of device 600, changes in the position of device 600 or a component of device 600, the presence or absence of user contact with device 600, the orientation or acceleration / deceleration of device 600, and temperature changes of device 600. Sensor assembly 614 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. Sensor assembly 614 may also include a light sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, sensor assembly 614 may also include an accelerometer, a gyroscope, a magnetometer, a pressure sensor, or a temperature sensor.

[0128] Communication component 616 is configured to facilitate wired or wireless communication between device 600 and other devices. Device 600 can access wireless networks based on communication standards, such as WiFi, or mobile communication networks such as 2G, 3G, 4G / LTE, and 5G. In one exemplary embodiment, communication component 616 receives broadcast signals or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, communication component 616 also includes a near-field communication (NFC) module to facilitate short-range communication. For example, the NFC module may be implemented based on radio frequency identification (RFID) technology, Infrared Data Association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.

[0129] In an exemplary embodiment, device 600 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the methods described above.

[0130] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 604 including instructions, which can be executed by a processor 620 of device 600 to perform the method provided by the present disclosure. For example, the non-transitory computer-readable storage medium may be a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0131] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0132] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0133] The payment method, apparatus, and electronic device provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and its core ideas. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A payment method recommendation method, characterized in that, Commodity information service systems applied to cross-border transactions include: Receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order; Identify multiple candidate payment methods; Based on the information of the target transaction order, multiple decision factors for the multi-objective decision algorithm are obtained. These multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order. The various candidate payment methods are evaluated based on the multiple decision factors. Specifically, each candidate payment method is scored under different decision factors, and the evaluation result is obtained based on the evaluation scores obtained by the same candidate payment method under different decision factors. When scoring candidate payment methods using the initiator information as a decision factor, it is determined whether the initiator of the target transaction order is a buyer or a seller. If the initiator of the target transaction order is the buyer, the degree of uncertainty of the target transaction order is determined to be high, and a higher evaluation score is assigned to the candidate payment method with a shorter transfer path under this decision factor. If the initiator of the target transaction order is the seller, the degree of uncertainty of the target transaction order is determined to be low, and a higher evaluation score is assigned to the candidate payment method with higher payment certainty under this decision factor. Based on the evaluation results of the various candidate payment methods, the recommended payment method information is determined.

2. The method according to claim 1, characterized in that, The evaluation of the multiple candidate payment methods based on the multiple decision factors further includes: When evaluating a payment method based on the country / region of the payer, a higher evaluation score is assigned to the payment method that the buyer in that country / region is more likely to choose, according to the country / region of the buyer.

3. The method according to claim 1, characterized in that, The multiple decision factors also include: the model information of the terminal device associated with the buyer user, so as to predict the payment success rate corresponding to the candidate payment method in combination with the model information, and assign a higher evaluation score to the candidate payment method with a higher payment success rate.

4. The method according to claim 1, characterized in that, If the buyer is not a first-time transaction user, the multiple decision factors also include: the buyer user's historical payment records for cross-border transaction orders; The evaluation of the multiple candidate payment methods based on the multiple decision factors further includes: Based on the historical payment records, the candidate payment methods that the buyer user has historically selected and successfully paid for, or the candidate payment methods that have recently been selected and successfully paid for, are assigned a higher evaluation score under this decision factor.

5. The method according to any one of claims 1 to 4, characterized in that, The evaluation of the multiple candidate payment methods based on the multiple decision factors includes: Based on the aforementioned multiple decision factors, the buyer's willingness to choose the candidate payment methods and / or the payment success rate corresponding to the candidate payment methods are predicted. The payment conversion rate of the candidate payment method is determined based on the selection intention corresponding to the candidate payment method and / or the payment success rate corresponding to the candidate payment method, and the candidate payment method is evaluated based on the payment conversion rate.

6. A payment method recommendation method, characterized in that, Commodity information service systems applied to cross-border transactions include: Receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order; The request is submitted to the server so that the server can determine multiple candidate payment methods. Based on the information of the target transaction order, the server obtains multiple decision factors from a multi-objective decision-making algorithm, evaluates the multiple candidate payment methods based on these decision factors, and determines the recommended payment method based on the evaluation results. The multiple decision factors include: the country / region of the payer user and the initiator information of the target transaction order. Each candidate payment method is scored under different decision factors, and the evaluation scores obtained for the same candidate payment method under these different decision factors are used to determine the recommended payment method. The evaluation results of candidate payment methods are obtained. When scoring candidate payment methods using the initiator information as a decision factor, it is determined whether the initiator of the target transaction order is a buyer or a seller. If the initiator of the target transaction order is the buyer, the uncertainty of the target transaction order is determined to be high, and a higher evaluation score is assigned to the candidate payment method with a shorter transfer path under this decision factor. If the initiator of the target transaction order is the seller, the uncertainty of the target transaction order is determined to be low, and a higher evaluation score is assigned to the candidate payment method with higher payment certainty under this decision factor. The target page displays the various candidate payment methods and provides information about the recommended payment method.

7. A payment method recommendation device, characterized in that, Commodity information service systems applied to cross-border transactions include: A request receiving unit is used to receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order; The candidate payment method determination unit is used to determine multiple candidate payment methods; The decision factor acquisition unit is used to acquire multiple decision factors for a multi-objective decision algorithm based on the information of the target transaction order; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order; An evaluation unit is used to evaluate the various candidate payment methods based on the multiple decision factors. Specifically, it scores the candidate payment methods under different decision factors and obtains the evaluation result of the candidate payment method based on the evaluation scores obtained by the same candidate payment method under different decision factors. When scoring candidate payment methods using the initiator information as a decision factor, it determines whether the initiator of the target transaction order is a buyer or a seller. If the initiator of the target transaction order is the buyer, the non-determinism of the target transaction order is determined to be high, and a higher evaluation score is assigned to the candidate payment method with a shorter transfer path under this decision factor. If the initiator of the target transaction order is the seller, the non-determinism of the target transaction order is determined to be low, and a higher evaluation score is assigned to the candidate payment method with higher payment certainty under this decision factor. The recommendation unit is used to determine the recommended payment method information based on the evaluation results corresponding to the multiple candidate payment methods.

8. A payment method recommendation device, characterized in that, Commodity information service systems applied to cross-border transactions include: A request receiving unit is used to receive a request to make payment for a target transaction order, wherein the target transaction order is a cross-border transaction order; A request submission unit is used to submit the request to the server, so that the server can determine multiple candidate payment methods, and after obtaining multiple decision factors of a multi-objective decision algorithm based on the information of the target transaction order, evaluate the multiple candidate payment methods based on the multiple decision factors, and determine the recommended payment method information based on the evaluation results corresponding to the multiple candidate payment methods; wherein, the multiple decision factors include: the country / region information of the payer user, and the initiator information of the target transaction order; wherein, the candidate payment methods are scored under multiple different decision factors, and the scores obtained for the same candidate payment method under multiple different decision factors are used to determine the recommended payment method information. The evaluation scores are used to obtain the evaluation results of candidate payment methods. Among them, when scoring candidate payment methods using the initiator information as a decision factor, it is determined whether the initiator of the target transaction order is a buyer user or a seller user. If the initiator of the target transaction order is the buyer user, the degree of uncertainty of the target transaction order is determined to be high, and a higher evaluation score is assigned to the candidate payment method with a shorter transfer path under this decision factor. If the initiator of the target transaction order is the seller user, the degree of uncertainty of the target transaction order is determined to be low, and a higher evaluation score is assigned to the candidate payment method with higher payment certainty under this decision factor. The display unit is used to display the various candidate payment methods on the target page and provide information about the recommended payment methods.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the steps of the method described in any one of claims 1 to 6.

10. An electronic device, characterized in that, include: One or more processors; as well as A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method according to any one of claims 1 to 6.

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