CN110689336A - Payment channel decision method and device and electronic equipment - Google Patents
Payment channel decision method and device and electronic equipment Download PDFInfo
- Publication number
- CN110689336A CN110689336A CN201910897906.0A CN201910897906A CN110689336A CN 110689336 A CN110689336 A CN 110689336A CN 201910897906 A CN201910897906 A CN 201910897906A CN 110689336 A CN110689336 A CN 110689336A
- Authority
- CN
- China
- Prior art keywords
- payment
- candidate
- channels
- payment channel
- channel
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 63
- 238000012216 screening Methods 0.000 claims abstract description 16
- 238000004590 computer program Methods 0.000 claims description 18
- 238000003860 storage Methods 0.000 claims description 17
- 230000006870 function Effects 0.000 claims description 14
- 230000009466 transformation Effects 0.000 claims description 10
- 238000005065 mining Methods 0.000 claims description 5
- 238000010586 diagram Methods 0.000 description 13
- 230000008569 process Effects 0.000 description 11
- 238000012545 processing Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 6
- 230000004044 response Effects 0.000 description 6
- 230000008901 benefit Effects 0.000 description 3
- 238000006243 chemical reaction Methods 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000010276 construction Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000011022 operating instruction Methods 0.000 description 1
- 230000002093 peripheral effect Effects 0.000 description 1
- 230000001737 promoting effect Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012546 transfer Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/22—Payment schemes or models
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The embodiment of the specification provides a payment channel decision method, a payment channel decision device and electronic equipment, wherein the payment channel decision method comprises the following steps: determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user; screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene; scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels; selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
Description
Technical Field
The embodiment of the specification relates to the technical field of payment channels, in particular to a payment channel decision method and device and electronic equipment.
Background
With the access of the international mainstream credit card channel and the construction of the backup credit card channel, a plurality of available channels exist for one payment request. There are many factors influencing channel decision, and how to dynamically decide an optimal channel under the condition of satisfying service response makes the highest Success Rate (SR) a difficult problem. At present, the transaction amount borne by the E-commerce platform is increasingly huge, and the small SR promotion can bring remarkable economic benefits, and vice versa, so that the decision significance for promoting the transaction success rate is great, and great economic benefits can be brought.
The channel decision method in the prior art may include the following two ways: the method comprises the steps that firstly, channel routing rules are manually input and manually maintained and configured through accumulated historical experiences, but the road routing rules are easy to match in error, the manual operation efficiency is low, and the routing configuration cannot be updated according to the real-time condition; secondly, filtering available channels by a plurality of strategies/rules to find a channel which can meet the successful payment condition, however, a plurality of unknown factors for determining whether the payment is successful are not considered, so that the payment result is easy to fail. Therefore, the existing decision transaction has poor real-time performance and low success rate.
Disclosure of Invention
The embodiment of the specification provides a payment channel decision method, a payment channel decision device and electronic equipment, so as to solve the problems of poor decision transaction real-time performance and low success rate in the prior art.
The embodiment of the specification adopts the following technical scheme:
in a first aspect, a decision method for a payment channel is provided, which includes:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
In a second aspect, a decision device for a payment channel is provided, which includes:
the payment system comprises a determining module, a payment module and a payment module, wherein the determining module is used for determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
the screening module is used for screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
the scoring module is used for scoring the candidate payment channels in the candidate payment channel set based on historical payment statistical data of the candidate payment channels in the candidate payment channel set;
and the payment module is used for selecting a payment channel in the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
In a third aspect, an electronic device is provided, including: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
In a fourth aspect, a computer-readable storage medium is provided, having stored thereon a computer program which, when executed by a processor, performs the steps of:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
the method comprises the steps that a payment scene and an available payment channel set corresponding to the payment scene are determined based on key dimension information in an order payment request of a user, a candidate payment channel set is screened from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene, the available payment channel set can be selected in real time according to different payment scenes, the candidate payment channel set can be selected from the available payment channel set, real-time dynamic decision is realized, the phenomenon that a certain payment channel is overloaded is avoided, and the success rate of decision transaction is ensured; and then, based on historical payment statistical data of candidate payment channels in the candidate payment channel set, scoring is carried out on the candidate payment channels in the candidate payment channel set, based on scoring results of the candidate payment channels in the candidate payment channel set, payment channels are selected in the candidate payment channel set to pay the order payment request, the historical payment statistical data of the candidate payment channels can be directly utilized to score the candidate payment channels, the calculation complexity of a decision-making process is simplified, time is saved, and the effect of meeting the real-time requirement of business response is achieved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the specification and are incorporated in and constitute a part of this specification, illustrate embodiments of the specification and together with the description serve to explain the specification and not to limit the specification in a non-limiting sense. In the drawings:
FIG. 1 is a flow diagram of a payment channel decision method provided by one embodiment of the present description;
FIG. 2 is a flowchart illustrating a decision method for a payment channel in an actual application scenario according to an embodiment of the present invention;
FIG. 3 is a block diagram of a decision device of a payment channel provided in an embodiment of the present specification;
fig. 4 is a block diagram of an electronic device provided in an embodiment of the present specification.
Detailed Description
In order to make the objects, technical solutions and advantages of the present disclosure more clear, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments of the present disclosure and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments, which can be determined by one skilled in the art based on the embodiments in the present specification without any creative effort, shall fall within the protection scope of the present specification.
The embodiment of the specification provides a payment channel decision method, a payment channel decision device and electronic equipment, so as to solve the problems of poor decision transaction real-time performance and low success rate in the prior art. The embodiment of the present specification provides a decision method for a payment channel, and an execution subject of the method may be, but is not limited to, an electronic device or an apparatus capable of being configured to execute the method provided by the embodiment of the present specification.
For convenience of description, the following description will be made of an embodiment of the method by taking an electronic device as an example. It is to be understood that the implementation of the method as an electronic device is merely an exemplary illustration and should not be construed as a limitation of the method.
Fig. 1 is a flowchart of a decision method of a payment channel provided in an embodiment of the present specification, where the method of fig. 1 may be performed by an electronic device, and as shown in fig. 1, the method may include:
The order payment request may be a single order payment request or a combined order payment request. The order payment request may be a request received from a front end checkout counter that the user requires payment for an order.
The key dimension information may include the e-commerce platform to which the payment order belongs, the payer card number, the payee card number, the issuer country, the balance on the card, the payment terminal type, and so on.
The payment scenario may include payment time, trade order, trade style, trading platform, and the like. Since different transaction platforms may contract with different payment channel providers for their respective contracts. Therefore, there may be different sets of available payment channels depending on the payment scenario. Wherein, the payment channel can refer to financial institutions, such as GS bank, JS bank, etc.
For example, if the key dimension information includes the e-commerce platform a to which the payment order belongs, the payer card number is 621226000000000, the payee card number is 621700166000, and the payment terminal is a mobile phone B, it may be determined that the payment scenario is a payment order formed by the mobile phone B on the e-commerce platform a, a transfer may be made to the card number 621700166000 through the card number 621226000000000, and it may be determined that the set of available payment channels includes the business bank and the construction bank.
The steps can be realized as follows: receiving an order payment request of a user, wherein the order payment request comprises key dimension information; determining a payment scene and an available payment channel set corresponding to the payment scene based on the key dimension information.
And 120, screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene.
The payment policy may include a traffic distribution policy, a traffic control policy, a payment channel switch control period policy, and the like.
The wind control rules may include rules that allow a certain payment channel to perform payment operations, or rules that prevent a certain payment channel from performing payment operations, etc.
The steps can be realized as follows: and screening candidate payment channels meeting payment conditions from the available payment channel set, and constructing a candidate payment channel set, wherein the payment conditions are determined based on payment strategies and wind control rules corresponding to the payment scenes.
For example, assume that the set of available payment channels may include GS bank, JS bank, JT bank, ZG bank, ZS bank; the payment strategy can be that payment of a Monday GS bank is closed, payment of a Tuesday JS bank and a JT bank is closed, and payment of the Monday to Sunday GS bank, the JS bank, the JT bank, the ZG bank and the ZS bank can be opened; the wind control rules can be paid for the GS, JS and ZG banks on wednesday to sunday, then:
the payment conditions are that GS bank, JS bank, JT bank, ZG bank and ZS bank can pay for opening on the days of Monday and Monday, and GS bank, JS bank and ZG bank can pay for the days of Monday and Monday.
Based on the payment condition, the selected candidate payment channel is GS bank, JS bank or ZG bank from GS bank, JS bank, JT bank, ZG bank and ZS bank which are included in the available payment channel set, and the constructed candidate payment channel set comprises GS bank, JS bank and ZG bank.
The historical success rate may be a historical success rate within a predetermined time period. Such as historical success rates within one, three, or seven days prior to the current query time point.
The historical payment statistical data may be obtained by: historical payment statistical data of the candidate payment channels in the candidate payment channel set are inquired in the data warehouse platform, and the data warehouse platform can carry out statistics, collection and mining on the historical payment statistical data of the candidate payment channels in the candidate payment channel set. Of course, other methods may be adopted, and the embodiments of the present description are not specifically limited.
The steps can be realized as follows: inputting historical payment statistical data of the candidate payment channel into a conversion model, and outputting scores of the candidate payment channel by the conversion model, wherein the conversion model is obtained based on the historical payment statistical data of the candidate payment channel and the scores of the candidate payment channel through training; or obtaining the score of the candidate payment channel based on the historical payment statistical data of the candidate payment channel and the corresponding relation between the historical payment statistical data and the score.
And 140, selecting a payment channel in the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
The step can be specifically realized as follows: and selecting the candidate payment channel corresponding to the score meeting the threshold value as a payment channel based on the score of the candidate payment channel in the candidate payment channel set, and paying the order payment request through the payment channel. Of course, the standard for selecting the payment channel may be determined according to actual requirements, and the embodiment of the present specification is not specifically limited.
The method comprises the steps that a payment scene and an available payment channel set corresponding to the payment scene are determined based on key dimension information in an order payment request of a user, a candidate payment channel set is screened from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene, the available payment channel set can be selected in real time according to different payment scenes, the candidate payment channel set can be selected from the available payment channel set, real-time dynamic decision is realized, the phenomenon that a certain payment channel is overloaded is avoided, and the success rate of decision transaction is ensured; and then, based on historical payment statistical data of candidate payment channels in the candidate payment channel set, scoring is carried out on the candidate payment channels in the candidate payment channel set, based on scoring results of the candidate payment channels in the candidate payment channel set, payment channels are selected in the candidate payment channel set to pay the order payment request, the historical payment statistical data of the candidate payment channels can be directly utilized to score the candidate payment channels, the calculation complexity of a decision-making process is simplified, time is saved, and the effect of meeting the real-time requirement of business response is achieved.
Optionally, as an embodiment, before performing step 130, the method for deciding a payment channel provided in the embodiment of the present specification includes:
querying whether historical payment statistical data of candidate payment channels in the candidate payment channel set exist in a data warehouse platform, wherein the data warehouse platform is used for counting, collecting and mining data according to a preset time interval;
if so, scoring the candidate payment channels in the candidate payment channel set based on historical payment statistical data of the candidate payment channels in the candidate payment channel set;
wherein the historical payment statistics may include historical success rates; step 130 may be specifically implemented as:
and taking the historical success rate as the input of a transformation function to obtain the score of the candidate payment channel corresponding to the historical success rate, wherein the transformation function is used for converting the probability into the score. The transformation function may be any function that is capable of converting probabilities into scores as is known in the art. The transformation function can be enlarged or reduced by any times according to different calculation precisions, such as 10000 times. For example, suppose the transformation function is Y ═ AX, where Y is the score, X is the history success rate, and a is the transformation constant.
Alternatively, the first and second electrodes may be,
and scoring the candidate payment channel corresponding to the historical success rate based on the historical success rate and the corresponding relation between the historical success rate and the score. For example, assuming that the historical success rate of the candidate channel 1 is 70%, the historical success rate of the candidate channel 2 is 80%, and the historical success rate of the candidate channel 3 is 90%, and the historical success rate is 70% for 5 points, the historical success rate is 80% for 7 points, and the historical success rate is 90% for 9 points, the score of the candidate channel 1 is 5 points, the score of the candidate channel 2 is 7 points, and the score of the candidate channel 3 is 9 points.
In the embodiment of the specification, the candidate payment channels in the candidate payment channel set are scored by using the historical payment statistical data of the candidate payment channels in the candidate payment channel set, so that the probability of selecting the candidate payment channels as the payment channels can be predicted, and the success rate of decision making of each payment channel is greatly improved.
Of course, the manner of scoring the candidate payment channels in the candidate payment channel set may further include:
and if the historical payment statistical data of the candidate payment channels in the candidate payment channel set does not exist in the query number bin platform, randomly scoring the candidate payment channels in the candidate payment channel set. Illustratively, assuming that there are candidate channel 1, candidate channel 2, and candidate channel 3 in the candidate channel set, the candidate channel 1, candidate channel 2, and candidate channel 3 are respectively graded by 5, 3, and 9, or the candidate channel 1, candidate channel 2, and candidate channel 3 are respectively graded by 7, 9, and 5.
If the historical payment statistical data of the candidate payment channels in the candidate payment channel set does not exist in the query data warehouse platform, the average scores of the known payment channels are configured for the candidate payment channels in the candidate payment channel set, and the known payment channels are all the existing channels which have successfully paid. For example, assuming that a candidate channel 1, a candidate channel 2 and a candidate channel 3 exist in the candidate channel set, and the average score of the known channels is 8, the scores of the candidate channel 1, the candidate channel 2 and the candidate channel 3 are 8.
Optionally, as an embodiment, the step 140 may be specifically implemented as:
ranking the scores of the candidate payment channels in the candidate payment channel set based on the scoring results of the candidate payment channels in the candidate payment channel set;
and selecting the candidate payment channel with the highest score as a payment channel to pay the order payment request.
The candidate payment channel with the highest score in the candidate payment channel set is selected as the payment channel according to the score of the candidate payment channel in the candidate payment channel set, and the order payment request is paid through the payment channel.
In the embodiment of the specification, the candidate payment channel with the highest score is selected as the payment channel to pay the order payment request, so that the only payment channel is selected, and the uniqueness of the decision result is ensured.
Optionally, as an embodiment, after the step 140 is executed, the method for deciding a payment channel provided in the embodiment of the present specification includes:
generating a transaction log based on the payment channel and transaction information corresponding to the payment channel;
storing the transaction log in the binning platform.
In the embodiment of the specification, the payment channel and the corresponding transaction information of the payment channel are used for generating the transaction log and then the transaction log flows back to the data warehouse platform, the data warehouse platform classifies and stores the transaction log to generate a big data set required by data mining, historical payment statistical data of the payment channel is obtained through analysis and statistics, real-time decision on the payment channel is further achieved, and the overall transaction success rate is improved.
The method of the embodiments of the present invention will be further described with reference to specific embodiments.
FIG. 2 is a flowchart illustrating a decision method for a payment channel in an actual application scenario according to an embodiment of the present invention;
specifically, as shown in FIG. 2, at 210, an order payment request of a user is received, the order payment request including key dimension information;
at 220, determining a payment scenario and a set of available payment channels corresponding to the payment scenario based on the key dimension information; determining a payment scene and an available payment channel set corresponding to the payment scene based on the key dimension information;
at 230, screening a candidate payment channel set from the available payment channel set based on a payment policy and/or a wind control rule corresponding to the payment scenario;
at 240, querying whether historical payment statistical data of candidate payment channels in the candidate payment channel set exists in a data warehouse platform, wherein the data warehouse platform is used for counting, collecting and mining data according to a preset time interval; if so, go to step 250; if not, go to step 260;
at 250, scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
at 260, randomly scoring candidate payment channels in the set of candidate payment channels; or, configuring an average score of known payment channels for the candidate payment channels in the candidate payment channel set, wherein the known payment channels are all channels which have been successfully paid;
at 270, a payment channel is selected in the set of candidate payment channels to pay for the order payment request based on scoring results of the candidate payment channels in the set of candidate payment channels.
At 280, generating a transaction log based on the payment channel and transaction information corresponding to the payment channel;
at 290, the transaction log is stored in the binning platform, which is used to count, collect, and mine data at predetermined time intervals.
Specific implementation manners of each step in the embodiments of the present description and corresponding beneficial effects thereof can be seen in details in the embodiments of the present description, and are not described herein again.
The method comprises the steps that a payment scene and an available payment channel set corresponding to the payment scene are determined based on key dimension information in an order payment request of a user, a candidate payment channel set is screened from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene, the available payment channel set can be selected in real time according to different payment scenes, the candidate payment channel set can be selected from the available payment channel set, real-time dynamic decision is realized, the phenomenon that a certain payment channel is overloaded is avoided, and the success rate of decision transaction is ensured; and then, based on historical payment statistical data of candidate payment channels in the candidate payment channel set, scoring is carried out on the candidate payment channels in the candidate payment channel set, based on scoring results of the candidate payment channels in the candidate payment channel set, payment channels are selected in the candidate payment channel set to pay the order payment request, the historical payment statistical data of the candidate payment channels can be directly utilized to score the candidate payment channels, the calculation complexity of a decision-making process is simplified, time is saved, and the effect of meeting the real-time requirement of business response is achieved.
The method for deciding a payment channel according to the embodiment of the present disclosure is described in detail above with reference to fig. 1 and 2, and the device for deciding a payment channel according to the embodiment of the present disclosure is described in detail below with reference to fig. 3.
Fig. 3 is a schematic structural diagram of a decision device for a payment channel provided in an embodiment of the present disclosure, and as shown in fig. 3, the decision device 300 may include:
the determining module 301 is configured to determine a payment scenario and an available payment channel set corresponding to the payment scenario based on key dimension information in an order payment request of a user;
a screening module 302, configured to screen a candidate payment channel set from the available payment channel set based on a payment policy and/or a wind control rule corresponding to the payment scenario;
a first scoring module 303, configured to score candidate payment channels in the set of candidate payment channels based on historical payment statistics of the candidate payment channels in the set of candidate payment channels;
a payment module 304, configured to select a payment channel in the candidate payment channel set to pay the order payment request based on a scoring result of a candidate payment channel in the candidate payment channel set.
In an embodiment, the decision device 300 of the payment channel may include:
a query module 305, configured to query whether historical payment statistical data of candidate payment channels in the candidate payment channel set exists in a data warehouse platform, where the data warehouse platform is configured to perform statistics, collection, and mining on data according to a predetermined time interval;
the first scoring module 303 is configured to score the candidate payment channels in the candidate payment channel set based on historical payment statistical data of the candidate payment channels in the candidate payment channel set if historical payment statistical data of the candidate payment channels in the candidate payment channel set exists in the digital warehouse platform.
In an embodiment, the decision device 300 of the payment channel may include:
a second scoring module 306, configured to randomly score the candidate payment channels in the candidate payment channel set if historical payment statistics of the candidate payment channels in the candidate payment channel set does not exist in the number store platform, or configure an average score of known payment channels for the candidate payment channels in the candidate payment channel set, where the known payment channels are existing channels that have all been paid successfully.
In one embodiment, the historical payment statistics may include historical success rates, and the first scoring module 303 may include:
the first grading unit is used for taking the historical success rate as the input of a transformation function to obtain the grade of the candidate payment channel corresponding to the historical success rate, and the transformation function is used for converting the probability into the grade; alternatively, the first and second electrodes may be,
and the second scoring unit is used for scoring the candidate payment channel corresponding to the historical success rate based on the historical success rate and the corresponding relation between the historical success rate and the score.
In one embodiment, the payment module 304 may include:
the ranking unit is used for ranking the scores of the candidate payment channels in the candidate payment channel set based on the scoring results of the candidate payment channels in the candidate payment channel set;
and the payment unit is used for selecting the candidate payment channel with the highest score as a payment channel to pay the order payment request.
In an embodiment, the decision device 300 of the payment channel may include:
a generating module 307, configured to generate a transaction log based on the payment channel and the transaction information corresponding to the payment channel;
a storage module 308 for storing the transaction log in the warehousing platform.
In one embodiment, the historical success rate is a historical success rate within a predetermined time period.
The method comprises the steps that a payment scene and an available payment channel set corresponding to the payment scene are determined based on key dimension information in an order payment request of a user, a candidate payment channel set is screened from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene, the available payment channel set can be selected in real time according to different payment scenes, the candidate payment channel set can be selected from the available payment channel set, real-time dynamic decision is realized, the phenomenon that a certain payment channel is overloaded is avoided, and the success rate of decision transaction is ensured; and then, based on historical payment statistical data of candidate payment channels in the candidate payment channel set, scoring is carried out on the candidate payment channels in the candidate payment channel set, based on scoring results of the candidate payment channels in the candidate payment channel set, payment channels are selected in the candidate payment channel set to pay the order payment request, the historical payment statistical data of the candidate payment channels can be directly utilized to score the candidate payment channels, the calculation complexity of a decision-making process is simplified, time is saved, and the effect of meeting the real-time requirement of business response is achieved.
Fig. 4 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification. Referring to fig. 4, at a hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 4, but that does not indicate only one bus or one type of bus.
And the memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory to the memory and then runs the computer program to form the association device of the resource value-added object and the resource object on the logic level. The processor is used for executing the program stored in the memory and is specifically used for executing the following operations:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
The method comprises the steps that a payment scene and an available payment channel set corresponding to the payment scene are determined based on key dimension information in an order payment request of a user, a candidate payment channel set is screened from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene, the available payment channel set can be selected in real time according to different payment scenes, the candidate payment channel set can be selected from the available payment channel set, real-time dynamic decision is realized, the phenomenon that a certain payment channel is overloaded is avoided, and the success rate of decision transaction is ensured; and then, based on historical payment statistical data of candidate payment channels in the candidate payment channel set, scoring is carried out on the candidate payment channels in the candidate payment channel set, based on scoring results of the candidate payment channels in the candidate payment channel set, payment channels are selected in the candidate payment channel set to pay the order payment request, the historical payment statistical data of the candidate payment channels can be directly utilized to score the candidate payment channels, the calculation complexity of a decision-making process is simplified, time is saved, and the effect of meeting the real-time requirement of business response is achieved.
The method for deciding the payment channel disclosed in the embodiment of fig. 1 in this specification can be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in one or more embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with one or more embodiments of the present disclosure may be embodied directly in hardware, in a software module executed by a hardware decoding processor, or in a combination of the hardware and software modules executed by a hardware decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the decision method of the payment channel of fig. 1 executed by the decision device of the payment channel of fig. 3, which is not described herein again.
Of course, besides the software implementation, the electronic device in the present specification does not exclude other implementations, such as a logic device or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to a plurality of logic units, and may be hardware or a logic device.
Embodiments of the present disclosure further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the computer program implements the processes of the method embodiments, and can achieve the same technical effect, and in order to avoid repetition, the details are not repeated here. The computer-readable storage medium may be a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk.
As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, apparatus, or computer program product. Accordingly, the description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The description has been presented with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the description. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
The foregoing description describes certain embodiments of the specification. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
It should also be noted that 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 an … …" does not exclude the presence of other identical elements in the process, method, article, or apparatus that comprises the element.
The above description is only an example of the present specification, and is not intended to limit the present specification. Various modifications and alterations to this description will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification should be included in the scope of the claims of the present specification.
Claims (10)
1. A payment channel decision method, comprising:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
2. The method of claim 1, prior to scoring a candidate payment channel of the set of candidate payment channels based on historical payment statistics for the candidate payment channel of the set of candidate payment channels, comprising:
querying whether historical payment statistical data of candidate payment channels in the candidate payment channel set exist in a data warehouse platform, wherein the data warehouse platform is used for counting, collecting and mining data according to a preset time interval;
if so, scoring the candidate payment channels in the candidate payment channel set based on historical payment statistical data of the candidate payment channels in the candidate payment channel set.
3. The method of claim 2, comprising:
if not, randomly scoring the candidate payment channels in the candidate payment channel set, or configuring an average score of known payment channels for the candidate payment channels in the candidate payment channel set, wherein the known payment channels are all the existing channels which have been successfully paid.
4. The method of claim 1, the historical payment statistics comprising historical success rates;
the scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics of the candidate payment channels in the set of candidate payment channels includes:
taking the historical success rate as the input of a transformation function to obtain the score of the candidate payment channel corresponding to the historical success rate, wherein the transformation function is used for converting the probability into the score; alternatively, the first and second electrodes may be,
and scoring the candidate payment channel corresponding to the historical success rate based on the historical success rate and the corresponding relation between the historical success rate and the score.
5. The method of claim 1, the selecting a payment channel at the set of candidate payment channels to pay for the order payment request based on scoring results of candidate payment channels in the set of candidate payment channels comprising:
ranking the scores of the candidate payment channels in the candidate payment channel set based on the scoring results of the candidate payment channels in the candidate payment channel set;
and selecting the candidate payment channel with the highest score as a payment channel to pay the order payment request.
6. The method of claim 2, comprising, after selecting a payment channel from the set of candidate payment channels to pay for the order payment request based on scoring results of candidate payment channels in the set of candidate payment channels:
generating a transaction log based on the payment channel and transaction information corresponding to the payment channel;
storing the transaction log in the binning platform.
7. The method of claim 1, wherein the historical success rate is a historical success rate over a predetermined period of time.
8. A decision making device for a payment channel, comprising:
the payment system comprises a determining module, a payment module and a payment module, wherein the determining module is used for determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
the screening module is used for screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
the scoring module is used for scoring the candidate payment channels in the candidate payment channel set based on historical payment statistical data of the candidate payment channels in the candidate payment channel set;
and the payment module is used for selecting a payment channel in the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, the computer program when executed by the processor implementing the steps of:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
10. A computer-readable storage medium having a computer program stored thereon, which when executed by a processor, performs the steps of:
determining a payment scene and an available payment channel set corresponding to the payment scene based on key dimension information in an order payment request of a user;
screening a candidate payment channel set from the available payment channel set based on a payment strategy and/or a wind control rule corresponding to the payment scene;
scoring the candidate payment channels in the set of candidate payment channels based on historical payment statistics for the candidate payment channels in the set of candidate payment channels;
selecting a payment channel from the candidate payment channel set to pay the order payment request based on the scoring result of the candidate payment channel in the candidate payment channel set.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910897906.0A CN110689336A (en) | 2019-09-23 | 2019-09-23 | Payment channel decision method and device and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910897906.0A CN110689336A (en) | 2019-09-23 | 2019-09-23 | Payment channel decision method and device and electronic equipment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110689336A true CN110689336A (en) | 2020-01-14 |
Family
ID=69109947
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910897906.0A Pending CN110689336A (en) | 2019-09-23 | 2019-09-23 | Payment channel decision method and device and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110689336A (en) |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111612442A (en) * | 2020-05-28 | 2020-09-01 | 杭州一骑轻尘信息技术有限公司 | Payment route configuration method, device and system |
| CN111899014A (en) * | 2020-08-03 | 2020-11-06 | 北京口袋财富信息科技有限公司 | Payment channel selection method and device, readable storage medium and computing equipment |
| CN112328131A (en) * | 2020-09-30 | 2021-02-05 | 北京每日优鲜电子商务有限公司 | Information display method and device, electronic equipment and computer readable medium |
| CN113256284A (en) * | 2021-07-14 | 2021-08-13 | 蚂蚁智信(杭州)信息技术有限公司 | Payment processing method and device |
| CN113435871A (en) * | 2021-06-29 | 2021-09-24 | 未鲲(上海)科技服务有限公司 | Payment channel abnormity checking method and device, computing equipment and storage medium |
| CN113469806A (en) * | 2021-07-21 | 2021-10-01 | 上海浦东发展银行股份有限公司 | Payment channel determining method, device, equipment and storage medium |
| CN113516470A (en) * | 2020-04-09 | 2021-10-19 | 北京意锐新创科技有限公司 | Transaction channel selection method and device |
| CN114997879A (en) * | 2022-07-18 | 2022-09-02 | 南京希音电子商务有限公司 | Payment routing method, device, equipment and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107464108A (en) * | 2016-06-03 | 2017-12-12 | 上海点融信息科技有限责任公司 | The method and apparatus for automatically selecting channel of disbursement |
| CN107679849A (en) * | 2017-10-09 | 2018-02-09 | 马上消费金融股份有限公司 | Payment channel selection method and system and computer readable storage medium |
| CN107705118A (en) * | 2017-09-19 | 2018-02-16 | 深圳金融电子结算中心有限公司 | Transaction payment method, system, server and storage medium based on channel route |
| CN110245935A (en) * | 2019-05-06 | 2019-09-17 | 阿里巴巴集团控股有限公司 | Channel of disbursement recommended method, device and equipment |
-
2019
- 2019-09-23 CN CN201910897906.0A patent/CN110689336A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107464108A (en) * | 2016-06-03 | 2017-12-12 | 上海点融信息科技有限责任公司 | The method and apparatus for automatically selecting channel of disbursement |
| CN107705118A (en) * | 2017-09-19 | 2018-02-16 | 深圳金融电子结算中心有限公司 | Transaction payment method, system, server and storage medium based on channel route |
| CN107679849A (en) * | 2017-10-09 | 2018-02-09 | 马上消费金融股份有限公司 | Payment channel selection method and system and computer readable storage medium |
| CN110245935A (en) * | 2019-05-06 | 2019-09-17 | 阿里巴巴集团控股有限公司 | Channel of disbursement recommended method, device and equipment |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113516470A (en) * | 2020-04-09 | 2021-10-19 | 北京意锐新创科技有限公司 | Transaction channel selection method and device |
| CN111612442A (en) * | 2020-05-28 | 2020-09-01 | 杭州一骑轻尘信息技术有限公司 | Payment route configuration method, device and system |
| CN111899014A (en) * | 2020-08-03 | 2020-11-06 | 北京口袋财富信息科技有限公司 | Payment channel selection method and device, readable storage medium and computing equipment |
| CN112328131A (en) * | 2020-09-30 | 2021-02-05 | 北京每日优鲜电子商务有限公司 | Information display method and device, electronic equipment and computer readable medium |
| CN113435871A (en) * | 2021-06-29 | 2021-09-24 | 未鲲(上海)科技服务有限公司 | Payment channel abnormity checking method and device, computing equipment and storage medium |
| CN113256284A (en) * | 2021-07-14 | 2021-08-13 | 蚂蚁智信(杭州)信息技术有限公司 | Payment processing method and device |
| CN113469806A (en) * | 2021-07-21 | 2021-10-01 | 上海浦东发展银行股份有限公司 | Payment channel determining method, device, equipment and storage medium |
| CN114997879A (en) * | 2022-07-18 | 2022-09-02 | 南京希音电子商务有限公司 | Payment routing method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110689336A (en) | Payment channel decision method and device and electronic equipment | |
| CN108595157B (en) | Block chain data processing method, device, equipment and storage medium | |
| CN110245935B (en) | Payment channel recommendation method, device and equipment | |
| US11074350B2 (en) | Method and device for controlling data risk | |
| CN107122369B (en) | Service data processing method, device and system | |
| CN108711047B (en) | Automatic repayment method, system and terminal equipment | |
| CN113034274A (en) | Supply chain financial service system and method based on block chain and terminal equipment | |
| CN111539811B (en) | Risk account identification method and device | |
| CN111324867B (en) | Suspected risk transaction determination method, device and equipment | |
| CN111738852B (en) | Service data processing method, device and server | |
| CN110781971B (en) | Merchant type identification method, device, equipment and readable medium | |
| CN110188990B (en) | Resource request and fund request splitting method, device and equipment | |
| CN108694574B (en) | Resource transfer channel processing method, device and equipment | |
| CN109615389A (en) | Electronic-payment transaction risk control method, device, server and storage medium | |
| CN110264342A (en) | A kind of business audit method and device based on machine learning | |
| CN109034990B (en) | Accounting method and device and electronic equipment | |
| CN113205402A (en) | Account checking method and device, electronic equipment and computer readable medium | |
| CN114841801A (en) | Credit wind control method and device based on user behavior characteristics | |
| US11176506B2 (en) | Blockchain expense and resource utilization optimization | |
| CN101770626A (en) | Method, device and system for identifying agents with card-laundering behavior | |
| CN109614415B (en) | Data mining and processing method, device, equipment and medium | |
| CN109377206B (en) | Payment limit system, method, device and storage medium | |
| CN115293913A (en) | Early warning method and device for payment refusal risk of commercial draft acceptance person | |
| CN115375298A (en) | Receiving and paying processing method, system, terminal and medium considering service type | |
| US20210383469A1 (en) | Currency trading method based on blockchain and electronic device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20201012 Address after: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman, British Islands Applicant after: Innovative advanced technology Co.,Ltd. Address before: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman, British Islands Applicant before: Advanced innovation technology Co.,Ltd. Effective date of registration: 20201012 Address after: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman, British Islands Applicant after: Advanced innovation technology Co.,Ltd. Address before: A four-storey 847 mailbox in Grand Cayman Capital Building, British Cayman Islands Applicant before: Alibaba Group Holding Ltd. |
|
| TA01 | Transfer of patent application right | ||
| REG | Reference to a national code |
Ref country code: HK Ref legal event code: DE Ref document number: 40028290 Country of ref document: HK |
|
| TA01 | Transfer of patent application right |
Effective date of registration: 20240222 Address after: Guohao Times City # 20-01, 128 Meizhi Road, Singapore Applicant after: Advanced Nova Technology (Singapore) Holdings Ltd. Country or region after: Singapore Address before: Cayman Enterprise Centre, 27 Hospital Road, George Town, Grand Cayman, British Islands Applicant before: Innovative advanced technology Co.,Ltd. Country or region before: Cayman Islands |
|
| TA01 | Transfer of patent application right |