CN118071345A - Payment account selection method, device, terminal equipment and storage medium - Google Patents
Payment account selection method, device, terminal equipment and storage medium Download PDFInfo
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Abstract
The application discloses a payment account selection method, a device, terminal equipment and a storage medium, and relates to the technical field of financial payment, wherein the payment account selection method comprises the following steps: receiving a payment request of a client, wherein the payment request comprises client information and information to be paid; determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid; arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for display. By adopting the technical scheme of the application, the user can better understand and trust the payment account selection decision, and the flexibility of the user payment account selection is improved.
Description
Technical Field
The present application relates to the field of financial payment technologies, and in particular, to a payment account selection method, device, terminal equipment, and storage medium.
Background
With the popularization of electronic payment and the continuous upgrading of electronic payment systems, people increasingly rely on electronic payment for daily consumption.
The user generally has a plurality of payable accounts, when paying, the user needs to select one or a plurality of payable accounts from the plurality of payable accounts according to different payment scenes to pay, but when paying, the user is difficult to comprehensively screen each account to select the most appropriate account to pay, which may cause economic loss of the user, while the traditional payment account selection mode usually carries out account arrangement based on a simple rule or a fixed sequence, lacks flexibility and adaptability, cannot provide the user with the best payment experience according to actual conditions, and is also unfavorable for the user to know the use condition of different payment accounts.
In summary, how to help users screen suitable payment accounts for payment during payment to improve the flexibility of user payment account selection is clearly a technical problem to be solved in the art.
Disclosure of Invention
The main purpose of the application is to provide a payment account selection method, a payment account selection device, a terminal device and a computer readable storage medium, which aim to improve flexibility of user payment account selection by helping the user to screen proper payment accounts for payment.
In order to achieve the above object, the present application provides a payment account selection method, including:
receiving a payment request of a client, wherein the payment request comprises client information and information to be paid;
Determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid;
And arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for displaying.
Optionally, the information to be paid includes an account to be paid and an amount to be paid, and the step of determining the payment priority of each payable account in the payable account list according to the information to be paid includes:
acquiring first account information of each payable account and second account information of the account to be paid in the payable account list;
Calculating transaction commission of the payable accounts according to the first account information, the second account information and the to-be-paid amount for each payable account;
Acquiring current value added service and historical transaction data of the payable account;
and determining the payment priority of the payable account according to the transaction commission, the current value-added service and the historical transaction data.
Optionally, the step of determining the payment priority of the payable account according to the transaction commission, the current value added service and the historical transaction data comprises:
Inputting the transaction commission, the current value-added service and the historical transaction data as input features into a pre-trained account selection model to obtain a payment score of the payable account;
and comparing the payment scores of the payable accounts, and arranging the payment priority of the payable accounts according to the order of the payment scores from high to low.
Optionally, the step of generating the payment policy interpretation report of the payable account list after receiving the query request and transmitting the payment policy interpretation report to the client for presentation includes:
after a query request is received, generating a feature interpretation graph and a feature influence diagram matched with the account selection model through a machine learning model interpretation tool, wherein the feature interpretation graph is used for representing the trend of the influence of the input features on the model output result along with the change of the feature value of the input features, and the feature influence diagram is used for representing the influence contribution degree of the input features on the model output result;
And generating a payment strategy interpretation report of the payable account list according to the characteristic interpretation graph and the characteristic influence diagram, and transmitting the payment strategy interpretation report to the client for presentation.
Optionally, before the step of determining the payment priority of each payable account in the payable account list according to the information to be paid, the method further comprises:
acquiring historical transaction data of each payable account in the payable account list;
Extracting target features from the historical transaction data, taking the target features as input of a deep reinforcement learning model, taking a historical selection account as output of the deep reinforcement learning model, and training the deep reinforcement learning model to learn an adaptive transaction strategy;
evaluating the deep reinforcement learning model based on a preset evaluation index to obtain an evaluation result;
If the evaluation result is qualified, selecting a payment account by taking the deep reinforcement learning model as an account selection model;
and if the evaluation result is unqualified, performing iterative training on the deep reinforcement learning model based on the historical transaction data until the evaluation result is qualified.
Optionally, after the step of generating a payment policy interpretation report of the payable account list after receiving the query request and transmitting the payment policy interpretation report to the client for presentation, the method further comprises:
And determining the characteristics to be adjusted in the account selection model according to the payment strategy interpretation report, and adjusting the parameters of the characteristics to be adjusted.
Optionally, after the step of determining a payable account list from the client information, the method further comprises:
Determining the number of accounts in the payable account list;
If the account number is greater than one, executing the step of determining the payment priority of each payable account in the payable account list according to the information to be paid and the subsequent steps;
And if the number of the accounts is equal to one, taking the accounts in the payable account list as payment accounts.
In addition, to achieve the above object, the present application also provides a payment account selecting device, including:
the system comprises a request receiving module, a request processing module and a payment processing module, wherein the request receiving module is used for receiving a payment request of a client, and the payment request comprises client information and information to be paid;
the priority determining module is used for determining a payable account list according to the client information and determining the payment priority of each payable account in the payable account list according to the information to be paid;
The account selection module is used for arranging the payable accounts according to the payment priority, taking the first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving the inquiry request, and transmitting the payment strategy interpretation report to the client for displaying.
In addition, to achieve the above object, the present application also provides a terminal device including: the system comprises a memory, a processor and a payment account selection program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the payment account selection method as described above.
In addition, in order to achieve the above object, the present application also proposes a storage medium, which is a computer-readable storage medium, on which a payment account selection program is stored, which when executed by a processor implements the steps of the payment account selection method as described above.
The embodiment of the application provides a payment account selection method, a device, terminal equipment and a storage medium, wherein the payment account selection method comprises the following steps: receiving a payment request of a client, wherein the payment request comprises client information and information to be paid; determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid; arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for display.
Compared with the traditional payment account selection method, the method has the advantages that the payment request sent by the client is received, the received payment request comprises the client information and the information to be paid, then the payable account list is determined according to the client information, the payment priority of each payable account in the payable account list is determined according to the information to be paid, finally each payable account is arranged according to the payment priority, the first payable account is arranged as the payment account, and the payment strategy interpretation report of each payable account is displayed after the inquiry request is received.
Therefore, the payment account is determined in the plurality of payable accounts based on the client information and the information to be paid, and the payment strategy interpretation report of each payable account is displayed, so that a user is helped to better understand and trust the payment account selection decision, and the flexibility of the user payment account selection is improved.
Drawings
Fig. 1 is a schematic device structure diagram of a hardware operating environment of a terminal device according to an embodiment of the present application;
FIG. 2 is a flow chart of a first embodiment of a payment account selection method according to the present application;
FIG. 3 is a flow chart of another embodiment of a payment account selection method according to the present application;
FIG. 4 is a schematic diagram of a flow chart of an embodiment of a payment account selection method according to the present application;
Fig. 5 is a schematic diagram of functional modules of an embodiment of a payment account selection device according to the present application.
The achievement of the objects, functional features and advantages of the present application will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
It should be noted that all directional indicators (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are merely used to explain the relative positional relationship, movement, etc. between the components in a particular posture (as shown in the drawings), and if the particular posture is changed, the directional indicator is changed accordingly.
In the present application, unless specifically stated and limited otherwise, the terms "connected," "affixed," and the like are to be construed broadly, and for example, "affixed" may be a fixed connection, a removable connection, or an integral body; can be mechanically or electrically connected; either directly or indirectly, through intermediaries, or both, may be in communication with each other or in interaction with each other, unless expressly defined otherwise. The specific meaning of the above terms in the present application can be understood by those of ordinary skill in the art according to the specific circumstances.
Furthermore, descriptions such as those referred to as "first," "second," and the like, are provided for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implying an order of magnitude of the indicated technical features in the present disclosure. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be considered to be absent and not within the scope of protection claimed in the present application.
The embodiment of the application provides terminal equipment, which can be a payment server.
As shown in fig. 1, fig. 1 is a schematic device structure diagram of a hardware operating environment of a terminal device according to an embodiment of the present application.
As shown in fig. 1, in a hardware operating environment of a terminal device, the terminal device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the terminal device structure shown in fig. 1 is not limiting of the device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and a payment account selection program may be included in a memory 1005, which is one type of computer storage medium.
In the device shown in fig. 1, the network interface 1004 is mainly used for connecting to a background server, and performing data communication with the background server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to call a payment account selection program stored in the memory 1005 and perform the following operations:
receiving a payment request of a client, wherein the payment request comprises client information and information to be paid;
Determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid;
And arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for displaying.
Optionally, the information to be paid includes an account to be paid and an amount to be paid, and the processor 1001 may be further configured to invoke a payment account selection program stored in the memory 1005, and perform the following operations:
acquiring first account information of each payable account and second account information of the account to be paid in the payable account list;
Calculating transaction commission of the payable accounts according to the first account information, the second account information and the to-be-paid amount for each payable account;
Acquiring current value added service and historical transaction data of the payable account;
and determining the payment priority of the payable account according to the transaction commission, the current value-added service and the historical transaction data.
Optionally, the processor 1001 may also be configured to invoke a payment account selection program stored in the memory 1005 and perform the following operations:
Inputting the transaction commission, the current value-added service and the historical transaction data as input features into a pre-trained account selection model to obtain a payment score of the payable account;
and comparing the payment scores of the payable accounts, and arranging the payment priority of the payable accounts according to the order of the payment scores from high to low.
Optionally, the processor 1001 may also be configured to invoke a payment account selection program stored in the memory 1005 and perform the following operations:
after a query request is received, generating a feature interpretation graph and a feature influence diagram matched with the account selection model through a machine learning model interpretation tool, wherein the feature interpretation graph is used for representing the trend of the influence of the input features on the model output result along with the change of the feature value of the input features, and the feature influence diagram is used for representing the influence contribution degree of the input features on the model output result;
And generating a payment strategy interpretation report of the payable account list according to the characteristic interpretation graph and the characteristic influence diagram, and transmitting the payment strategy interpretation report to the client for presentation.
Optionally, the processor 1001 may also be configured to invoke a payment account selection program stored in the memory 1005 and perform the following operations:
acquiring historical transaction data of each payable account in the payable account list;
Extracting target features from the historical transaction data, taking the target features as input of a deep reinforcement learning model, taking a historical selection account as output of the deep reinforcement learning model, and training the deep reinforcement learning model to learn an adaptive transaction strategy;
Evaluating the deep reinforcement learning model based on a preset evaluation index to obtain an evaluation result; if the evaluation result is qualified, selecting a payment account by taking the deep reinforcement learning model as an account selection model;
and if the evaluation result is unqualified, performing iterative training on the deep reinforcement learning model based on the historical transaction data until the evaluation result is qualified.
Optionally, the processor 1001 may also be configured to invoke a payment account selection program stored in the memory 1005 and perform the following operations:
And determining the characteristics to be adjusted in the account selection model according to the payment strategy interpretation report, and adjusting the parameters of the characteristics to be adjusted.
Optionally, the processor 1001 may also be configured to invoke a payment account selection program stored in the memory 1005 and perform the following operations:
Determining the number of accounts in the payable account list;
If the account number is greater than one, executing the step of determining the payment priority of each payable account in the payable account list according to the information to be paid and the subsequent steps;
And if the number of the accounts is equal to one, taking the accounts in the payable account list as payment accounts.
Based on the above hardware structure, the overall concept of the various embodiments of the payment account selection method of the present application is presented.
With the popularization of electronic payment and the continuous upgrading of electronic payment systems, people increasingly rely on electronic payment for daily consumption.
The user generally has a plurality of payable accounts, when paying, the user needs to select one or a plurality of payable accounts from the plurality of payable accounts according to different payment scenes to pay, but when paying, the user is difficult to comprehensively screen each account to select the most appropriate account to pay, which may cause economic loss of the user, while the traditional payment account selection mode usually carries out account arrangement based on a simple rule or a fixed sequence, lacks flexibility and adaptability, cannot provide the user with the best payment experience according to actual conditions, and is also unfavorable for the user to know the use condition of different payment accounts.
In summary, how to help users screen suitable payment accounts for payment during payment to improve the flexibility of user payment account selection is clearly a technical problem to be solved in the art.
In view of the above problems, an embodiment of the present application provides a payment account selection method, including: receiving a payment request of a client, wherein the payment request comprises client information and information to be paid; determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid; arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for display.
Compared with the traditional payment account selection method, the method has the advantages that the payment request sent by the client is received, the received payment request comprises the client information and the information to be paid, then the payable account list is determined according to the client information, the payment priority of each payable account in the payable account list is determined according to the information to be paid, finally each payable account is arranged according to the payment priority, the first payable account is arranged as the payment account, and the payment strategy interpretation report of each payable account is displayed after the inquiry request is received.
Therefore, the payment account is determined in the plurality of payable accounts based on the client information and the information to be paid, and the payment strategy interpretation report of each payable account is displayed, so that a user is helped to better understand and trust the payment account selection decision, and the flexibility of the user payment account selection is improved.
Based on the above general idea of the payment account selection method of the present application, various embodiments of the payment account selection method of the present application are presented.
Referring to fig. 2, fig. 2 is a flowchart illustrating a payment account selection method according to a first embodiment of the present application. It should be noted that although a logical order is depicted in the flowchart, in some cases the steps depicted or described may be performed in a different order than presented herein.
In this embodiment, for ease of understanding and explanation, the payment server is used as a direct execution body in this embodiment to explain the payment account selection method according to the present application.
As shown in fig. 2, in this embodiment, the payment account selection method of the present application may include:
step S10, receiving a payment request of a client, wherein the payment request comprises client information and information to be paid;
In this embodiment, the payment server receives a payment request of the client, where the payment request includes client information and information to be paid, where the client information is used to identify an identity or a payment source of the client, for example, the client may provide information such as an IP address, device information, a user agent character string, and the like, so that the payment server can identify and verify the authenticity and validity of the payment request; the information to be paid refers to information related to goods or services to be paid, which is included in the payment request, and is used for identifying a specific payment transaction, so that the server can correctly process the request and ensure the correctness and integrity of payment, and the information to be paid generally includes an order number, the name of goods or services, the payment mode, the amount to be paid, and the like.
It should be noted that, in this embodiment, the payment request received by the payment server may be a request initiated by the user through the third party payment platform; or the user pays through a banking system, the banking system sends a payment request to a server, and the server receives and processes the payment request; the user can pay through the mobile payment application, the mobile payment application sends a payment request to the server, and the server receives and processes the payment request; or the user pays after selecting the commodity in the mall or the website, the mall or the website sends the payment request to the server, and the server receives and processes the payment request.
Step S20, determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid;
In this embodiment, when a payment request is received by the payment server, the payment server identifies the identity and payment source of the client according to the client information in the payment request, so as to determine which payment accounts are available for the payment request of the client, and then the payment server screens out the determined payment accounts to form a payable account list, and determines the payment priority of each payable account in the payable account list according to the information to be paid in the payment request.
It should be noted that, in this embodiment, determining the payment priority of each payable account may specifically consider the preset payment rule, account balance, historical payment record, account credit, and other factors, and by comprehensively considering these factors, the payment server may be able to assign an appropriate priority to each payable account.
And step S30, arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for display.
In this embodiment, after determining the payment priority of each payable account, the payment server arranges each payable account according to the payment priority, so that the accounts with high priority are located at the front end of the list, so that the user can select the first payable account at the first time, and the first payable account is arranged as the payment account by default, so that the user can quickly and accurately make a decision when facing a plurality of payable accounts, and after receiving the inquiry request, the payment server generates a payment policy interpretation report of each payable account, and timely transmits the payment policy interpretation report to the client to be displayed to the user, so that the user can intuitively understand the payment policy of each account.
Further, in a possible embodiment, after the step of determining the payable account list according to the client information in the step S20, the payment account selection method of the present application may further include:
Step A10: determining the number of accounts in the payable account list;
in this embodiment, the payment server, after determining the payable account list, determines the number of accounts in the payable account list.
Step A20: if the account number is greater than one, executing the step of determining the payment priority of each payable account in the payable account list according to the information to be paid and the subsequent steps;
In this embodiment, the payment server determines whether the number of accounts is greater than one, if the number of accounts is greater than one, determines the payment priority of each payable account in the payable account list according to the payment information, then arranges each payable account according to the payment priority, uses the payable account with the first arranged payable account as the payment account, and generates a payment policy interpretation report of the payable account list after receiving the query request, and transmits the payment policy interpretation report to the client for display.
Step A30: and if the number of the accounts is equal to one, taking the accounts in the payable account list as payment accounts.
In this embodiment, the payment server determines whether the number of accounts is greater than one, and if the number of accounts is equal to one, which indicates that the client is associated with only one account, the account is used as a payment account to pay.
Therefore, the payment server flexibly selects the account with the highest payment priority from the accounts to pay by counting the number of the accounts associated with the current client in real time when the accounts exist, provides the best payment experience for the user according to the actual situation, takes the unique account as the payment account when only one account exists, and saves the calculation resources of the server.
In this embodiment, the embodiment of the present application receives a payment request of a client, where the payment request includes client information and information to be paid; determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid; arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for display.
In this way, the embodiment of the application determines the payment account among the plurality of payable accounts based on the client information and the information to be paid, and displays the payment strategy interpretation report of each payable account, thereby helping the user better understand and trust the payment account selection decision, and improving the flexibility of the user payment account selection.
Further, based on the first embodiment of the payment account selection method of the present application described above, a second embodiment of the payment account selection method of the present application is presented.
In this embodiment, the step of determining the payment priority of each payable account in the payable account list according to the information to be paid in the step S20 includes:
step S201: acquiring first account information of each payable account and second account information of the account to be paid in the payable account list;
Note that, in this embodiment, the information to be paid includes at least an account to be paid and an amount to be paid.
In this embodiment, the payment server obtains first account information of each payable account in the payable account list and second account information of the accounts to be paid, where the first account information refers to account balances of each payable account of the user, account opening rows and account opening places corresponding to the accounts, and the second account information refers to account opening rows and account opening places corresponding to the accounts of the accounts to be paid.
Step S202: calculating transaction commission of the payable accounts according to the first account information, the second account information and the to-be-paid amount for each payable account;
In this embodiment, the payment server calculates, for each payable account, a transaction fee for each payable account according to the first account information of the payable account, the second account information of the account to be paid, and the amount to be paid.
Specifically, the transfer between the payable account and the account to be paid can be divided into the same city and same line transfer, the same city and different place and same line transfer, transprovincially and different place and same line transfer and different place transfer, the charge rates of different transfer modes are different, the payment server can determine the transaction charge rates required by the accounts of the different payable accounts and the account to be paid through inquiring the charge rate table, and then calculate the transaction charge required by each payable account to be paid to the account to be paid according to the amount to be paid and the transaction charge rate obtained through searching.
Step S203: acquiring current value added service and historical transaction data of the payable account;
In this embodiment, the payment server further obtains current value-added services and historical transaction data of the payable account, wherein the current value-added services refer to additional value-added services and rewards available to the account, such as cash returns, shopping offers, point exchanges, and the like, and the historical transaction data refer to payment records of the account, such as historical transaction time, historical transaction place, historical transaction amount, historical transaction matters, and the like.
Step S204: and determining the payment priority of the payable account according to the transaction commission, the current value-added service and the historical transaction data.
In this embodiment, the payment server determines the payment priority of the payable account facing the current payment request according to the transaction fee, the current value-added service and the historical transaction data of each payable account, so as to reduce the time and effort of the user when selecting the payable account and improve the payment efficiency.
In addition, in a possible embodiment, the information to be paid may further include a payment channel, a payment item, and the like, wherein the payment item may be classified into daily consumption, investment, loan repayment, and the payment server may determine the payment priority of the payable account together according to the information to be paid.
Further, in one possible embodiment, the step S204 includes:
step S2041: inputting the transaction commission, the current value-added service and the historical transaction data as input features into a pre-trained account selection model to obtain a payment score of the payable account;
in this embodiment, the payment server takes important information such as transaction commission, current value-added service and historical transaction data as input features, and inputs the important information into a pre-trained account selection model, and the account selection model is trained by a large amount of data, so that the account selection model has the capability of identifying and evaluating account characteristics. The historical transaction data is used as an important index for measuring the transaction activity and reliability of the account, has an important influence on the judgment of the model, the current value-added service reflects the value-added potential and the added value of the account and is also an important basis for the evaluation of the model, the transaction commission is key information of account selection, the model can know the payment habit of the user and the characteristics and functions of each account by analyzing the data, and therefore the payment score of each payable account can be evaluated more accurately, and represents the comprehensive evaluation of the account payment capability of the model to each account and is also a key reference for the user when selecting the account.
In this way, in the embodiment, the payment server realizes accurate assessment of the payable account payment capability by using the pre-trained account selection model and the multidimensional input features, and provides more scientific and efficient account selection basis for users.
Step S2042: and comparing the payment scores of the payable accounts, and arranging the payment priority of the payable accounts according to the order of the payment scores from high to low.
In this embodiment, the payment server compares the respective payment scores of the payable accounts, and after the score comparison is completed, ranks the payment priorities of the payable accounts according to the order of the payment scores of the payable accounts from high to low. Specifically, the payment server sets the account with the high payment score at the front end of the payable account list to be the preferred payment account, and transmits the arranged payable account list to the client for display to the user. Therefore, the selection process of the user is simplified, the account with high payment priority is ensured to be prioritized, and the user can rapidly select a proper payment account according to the requirements and the preferences of the user, so that the payment efficiency and the user experience are greatly improved.
Further, in a possible embodiment, the step of generating the payment policy interpretation report of the payable account list after receiving the query request and transmitting the payment policy interpretation report to the client for presentation in the step S30 includes:
Step S301: after a query request is received, generating a feature interpretation graph and a feature influence diagram matched with the account selection model through a machine learning model interpretation tool, wherein the feature interpretation graph is used for representing the trend of the influence of the input features on the model output result along with the change of the feature value of the input features, and the feature influence diagram is used for representing the influence contribution degree of the input features on the model output result;
In this embodiment, after receiving a query request, the payment server generates, through a preconfigured machine learning model interpretation tool, a feature interpretation graph and a feature influence graph that are matched with an account selection model, where the feature interpretation graph is used to represent a trend that an influence of an input feature on an output result of the account selection model changes with a feature value of the input feature, and the feature influence graph is used to represent a contribution degree of the influence of the input feature on the output result of the account selection model.
It should be noted that, the machine learning model interpretation tool is an interpretable AI technology, such as SHAP (SHAPLEY ADDITIVE exPlanation additively interpretable model), local Interpretation Model (LIME), causal reasoning method, and the like, in this embodiment, the machine learning model interpretation tool is preferably SHAP, the payment server presents how the influence of the input features on the model output result changes with the feature values of the input features in an intuitive manner through the feature interpretation graph of SHAP, and by observing the feature interpretation graph, the user can know which features play a key role in the model, and how these features affect the final payment score, which helps the user to better understand the decision basis of the account selection model, thereby enhancing the trust degree on the model output; the characteristic influence force diagram further reveals the contribution degree of each input characteristic to the model output result, and a user can clearly see the specific effect of each characteristic on the formation of the payment score through the characteristic influence force diagram, so that more specific guidance is provided for the user when selecting the account, and the account configuration can be optimized more specifically.
Step S302: and generating a payment strategy interpretation report of the payable account list according to the characteristic interpretation graph and the characteristic influence diagram, and transmitting the payment strategy interpretation report to the client for presentation.
In this embodiment, the payment server generates a payment policy report of the payable account list according to the feature interpretation graph and the feature influence graph, and transmits the payment policy interpretation report to the client for presentation, so that the user performs payment account selection according to the output data of the account selection model and the payment policy interpretation report.
In this embodiment, as shown in fig. 4, after receiving a payment request of a client, a payment server outputs an account selection result according to client information and information to be paid in the payment request through an account selection model, and when receiving a query request, invokes a machine learning model interpretation tool to generate a payment policy interpretation report corresponding to the model output result, and transmits the payment policy interpretation report to the client for visual display, where the display form includes a graph, a chart, etc., so that a user can intuitively understand and trust the decision of the model, and select a payment account according to own requirements.
Further, in a possible embodiment, before the step of determining the payment priority of each payable account in the payable account list according to the information to be paid in the step S20, the payment account selection method of the present application may further include:
step B10: acquiring historical transaction data of each payable account in the payable account list;
In this embodiment, the payment server obtains historical transaction data of each payable account in the payable account list, wherein the historical transaction data includes information such as transaction time, transaction amount and account state, and after obtaining the historical transaction data, the payment server cleans and preprocesses the data to remove abnormal values and repeated data in the data, so as to ensure data accuracy and consistency.
Step B20: extracting target features from the historical transaction data, taking the target features as input of a deep reinforcement learning model, taking a historical selection account as output of the deep reinforcement learning model, and training the deep reinforcement learning model to learn an adaptive transaction strategy;
In this embodiment, the target feature is extracted from the historical transaction data processed by the payment server, the target feature is used as an input of a deep reinforcement learning model, the historical selection account is used as an output of the deep reinforcement learning model, and the deep reinforcement learning model is trained to learn the adaptive transaction strategy.
It should be noted that, in this embodiment, the deep reinforcement learning model may be an algorithm model such as Q-learning, SARSA, and the model is trained by using historical transaction data, parameters of the model are continuously and iteratively updated, and in the training process, the model is dynamically adjusted to adapt to different transaction scenes, payment requirements and states of accounts in combination with changes of market environments and new transaction data.
Step B30: evaluating the deep reinforcement learning model based on a preset evaluation index to obtain an evaluation result;
In this embodiment, the payment server may evaluate the deep reinforcement learning model based on preset evaluation indexes such as accuracy, stability, and interpretability, to obtain an evaluation result.
Specifically, the accuracy of the model under different conditions is assessed to ensure that the model is able to accurately predict and assess the payment capabilities of the account; evaluating the stability of the model to ensure that the model provides consistent output results independent of certain factors; the interpretability of the assessment model can help the user understand the reasons behind the model decisions so that by assessing the results, the advantages and disadvantages of the model can be understood and the necessary adjustments and optimizations made accordingly.
Step B40: if the evaluation result is qualified, selecting a payment account by taking the deep reinforcement learning model as an account selection model;
Step B50: and if the evaluation result is unqualified, performing iterative training on the deep reinforcement learning model based on the historical transaction data until the evaluation result is qualified.
In this embodiment, if the evaluation result of the model is qualified, the deep reinforcement learning model is used as an account selection model to select a payment account, and if the evaluation result of the model is unqualified, iterative training is performed on the model based on historical transaction data until the evaluation result is qualified.
Further, in a possible embodiment, after the step of generating the payment policy interpretation report of the payable account list after receiving the query request and transmitting the payment policy interpretation report to the client for presentation in the step S30, the payment account selection method of the present application may further include:
Step S40: and determining the characteristics to be adjusted in the account selection model according to the payment strategy interpretation report, and adjusting the parameters of the characteristics to be adjusted.
In this embodiment, the payment server may determine the feature to be adjusted in the account selection model according to the payment policy interpretation report, and adjust the parameter of the determined feature to be adjusted, specifically, when it is found in the payment policy interpretation report that the change of the feature value of a certain feature hardly affects the output result of the model, the weight of the feature may be appropriately reduced, and if it is found that the influence of the certain feature on the output result of the model is greater than the influence reflected in the bit influence diagram, the weight of the feature may be appropriately increased. Thus, the accuracy and the effectiveness of the model output result can be increased by adjusting the characteristic parameters in the model application process.
In this way, in the embodiment of the application, the account selection model is combined with the interpretable AI technology, the model adaptively learns the market environment transaction strategy to adapt to different transaction scenes, payment demands and states of payment accounts, and meanwhile, the decision result of the model is visually displayed by combining with the interpretable AI technology, so that a user can better understand and trust the payment account selection decision of the system, and the flexibility of the user payment account selection is improved.
In addition, the embodiment of the application also provides a payment account selection device.
Referring to fig. 5, the payment account selecting apparatus of the present application includes:
A request receiving module 10, configured to receive a payment request of a client, where the payment request includes client information and information to be paid;
the priority determining module 20 is configured to determine a payable account list according to the client information, and determine a payment priority of each payable account in the payable account list according to the information to be paid;
The account selection module 30 is configured to arrange the payable accounts according to the payment priority, use the first payable account arranged as a payment account, and generate a payment policy interpretation report of the payable account list after receiving a query request, and transmit the payment policy interpretation report to the client for display.
Optionally, the information to be paid includes an account to be paid and an amount to be paid, and the priority determining module 20 includes:
The first acquisition unit is used for acquiring first account information of each payable account in the payable account list and second account information of the accounts to be paid;
a calculating unit, configured to calculate, for each of the payable accounts, a transaction fee of the payable account according to the first account information, the second account information, and the amount to be paid;
a second obtaining unit, configured to obtain current value-added service and historical transaction data of the payable account;
and the priority determining unit is used for determining the payment priority of the payable account according to the transaction commission, the current value-added service and the historical transaction data.
Optionally, the priority determining unit is further configured to input the transaction commission, the current value-added service and the historical transaction data as input features to a pre-trained account selection model, so as to obtain a payment score of the payable account; and comparing the payment scores of the payable accounts, and arranging the payment priority of the payable accounts according to the order of the payment scores from high to low.
Optionally, the account selection module 30 includes:
the generation unit is used for generating a feature interpretation graph and a feature influence graph matched with the account selection model through a machine learning model interpretation tool after receiving a query request, wherein the feature interpretation graph is used for representing the trend that the influence of the input feature on the model output result changes along with the feature value of the input feature, and the feature influence graph is used for representing the influence contribution degree of the input feature on the model output result;
and the display unit is used for generating a payment strategy interpretation report of the payable account list according to the characteristic interpretation graph and the characteristic influence diagram, and transmitting the payment strategy interpretation report to the client for display.
Optionally, the payment account selection device of the present application may further include:
The model training module is used for acquiring historical transaction data of each payable account in the payable account list; extracting target features from the historical transaction data, taking the target features as input of a deep reinforcement learning model, taking a historical selection account as output of the deep reinforcement learning model, and training the deep reinforcement learning model to learn an adaptive transaction strategy; evaluating the deep reinforcement learning model based on a preset evaluation index to obtain an evaluation result; if the evaluation result is qualified, selecting a payment account by taking the deep reinforcement learning model as an account selection model; and if the evaluation result is unqualified, performing iterative training on the deep reinforcement learning model based on the historical transaction data until the evaluation result is qualified.
Optionally, the payment account selection device of the present application may further include:
And the parameter adjustment module is used for determining the characteristics to be adjusted in the account selection model according to the payment strategy interpretation report and adjusting the parameters of the characteristics to be adjusted.
Optionally, the account selection module 30 is further configured to: determining the number of accounts in the payable account list; if the account number is greater than one, executing the step of determining the payment priority of each payable account in the payable account list according to the information to be paid and the subsequent steps; and if the number of the accounts is equal to one, taking the accounts in the payable account list as payment accounts.
The function implementation of each module in the payment account selection device corresponds to each step in the payment account selection method embodiment, and the function and implementation process thereof are not described in detail herein.
In addition, the application also provides a storage medium, wherein the storage medium stores a program for selecting the payment account, and the payment account selecting program realizes the steps of the payment account selecting method according to the application when being executed by a processor.
The specific embodiments of the storage medium of the present application are substantially the same as the embodiments of the payment account selection method described above, and are not described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present application are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
The foregoing description is only of the preferred embodiments of the present application, and is not intended to limit the scope of the application, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. A payment account selection method, the payment account selection method comprising:
receiving a payment request of a client, wherein the payment request comprises client information and information to be paid;
Determining a payable account list according to the client information, and determining the payment priority of each payable account in the payable account list according to the information to be paid;
And arranging the payable accounts according to the payment priority, taking the arranged first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving a query request, and transmitting the payment strategy interpretation report to the client for displaying.
2. The payment account selection method as claimed in claim 1, wherein the information to be paid includes an account to be paid and an amount to be paid, and the step of determining a payment priority of each payable account in the payable account list according to the information to be paid includes:
acquiring first account information of each payable account and second account information of the account to be paid in the payable account list;
Calculating transaction commission of the payable accounts according to the first account information, the second account information and the to-be-paid amount for each payable account;
Acquiring current value added service and historical transaction data of the payable account;
and determining the payment priority of the payable account according to the transaction commission, the current value-added service and the historical transaction data.
3. The payment account selection method of claim 2, wherein the step of determining the payment priority of the payable account based on the transaction commission, the current value added service, and the historical transaction data comprises:
Inputting the transaction commission, the current value-added service and the historical transaction data as input features into a pre-trained account selection model to obtain a payment score of the payable account;
and comparing the payment scores of the payable accounts, and arranging the payment priority of the payable accounts according to the order of the payment scores from high to low.
4. The payment account selection method of claim 3, wherein the step of generating a payment policy interpretation report for the payable account list upon receipt of a query request is transmitted to the client for presentation, comprising:
after a query request is received, generating a feature interpretation graph and a feature influence diagram matched with the account selection model through a machine learning model interpretation tool, wherein the feature interpretation graph is used for representing the trend of the influence of the input features on the model output result along with the change of the feature value of the input features, and the feature influence diagram is used for representing the influence contribution degree of the input features on the model output result;
And generating a payment strategy interpretation report of the payable account list according to the characteristic interpretation graph and the characteristic influence diagram, and transmitting the payment strategy interpretation report to the client for presentation.
5. The payment account selection method of claim 1, wherein prior to the step of determining a payment priority for each payable account in the payable account list based on the information to be paid, the method further comprises:
acquiring historical transaction data of each payable account in the payable account list;
Extracting target features from the historical transaction data, taking the target features as input of a deep reinforcement learning model, taking a historical selection account as output of the deep reinforcement learning model, and training the deep reinforcement learning model to learn an adaptive transaction strategy;
evaluating the deep reinforcement learning model based on a preset evaluation index to obtain an evaluation result;
If the evaluation result is qualified, selecting a payment account by taking the deep reinforcement learning model as an account selection model;
and if the evaluation result is unqualified, performing iterative training on the deep reinforcement learning model based on the historical transaction data until the evaluation result is qualified.
6. The payment account selection method of claim 5, wherein after the step of generating a payment policy interpretation report for the payable account list upon receipt of a query request and transmitting to the client for presentation, the method further comprises:
And determining the characteristics to be adjusted in the account selection model according to the payment strategy interpretation report, and adjusting the parameters of the characteristics to be adjusted.
7. A payment account selection method as claimed in any one of claims 1 to 6, wherein after the step of determining a list of payable accounts from the client information, the method further comprises:
Determining the number of accounts in the payable account list;
If the account number is greater than one, executing the step of determining the payment priority of each payable account in the payable account list according to the information to be paid and the subsequent steps;
And if the number of the accounts is equal to one, taking the accounts in the payable account list as payment accounts.
8. A payment account selection device, the payment account selection device comprising:
the system comprises a request receiving module, a request processing module and a payment processing module, wherein the request receiving module is used for receiving a payment request of a client, and the payment request comprises client information and information to be paid;
the priority determining module is used for determining a payable account list according to the client information and determining the payment priority of each payable account in the payable account list according to the information to be paid;
The account selection module is used for arranging the payable accounts according to the payment priority, taking the first payable account as a payment account, generating a payment strategy interpretation report of the payable account list after receiving the inquiry request, and transmitting the payment strategy interpretation report to the client for displaying.
9. A terminal device, characterized in that the terminal device comprises: memory, a processor and a payment account selection program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the payment account selection method of any one of claims 1 to 7.
10. A storage medium, characterized in that the storage medium is a computer-readable storage medium, on which a payment account selection program is stored, which, when executed by a processor, implements the steps of the payment account selection method according to any one of claims 1 to 7.
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