CN109583931B

CN109583931B - Transaction data processing method, device, electronic equipment and readable storage medium

Info

Publication number: CN109583931B
Application number: CN201811146923.2A
Authority: CN
Inventors: 皮龙娇
Original assignee: Advanced New Technologies Co Ltd
Current assignee: Advanced New Technologies Co Ltd; Advantageous New Technologies Co Ltd
Priority date: 2018-09-29
Filing date: 2018-09-29
Publication date: 2024-02-02
Anticipated expiration: 2038-09-29
Also published as: CN109583931A

Abstract

The embodiment of the specification provides a transaction data processing method, which is used for determining a rewarding strategy corresponding to a transaction based on server information contained in the transaction in target transaction data and a prestored server information base, further acquiring configuration information of a corresponding rewarding strategy from a prestored configuration file base, and further calculating a rewarding result of the transaction corresponding to the rewarding strategy based on the configuration information of the corresponding rewarding strategy. The method can be used for processing transaction data under different scenes to obtain corresponding rewarding results, has strong applicability and saves cost and resources.

Description

Transaction data processing method, device, electronic equipment and readable storage medium

Technical Field

Embodiments of the present disclosure relate to the field of data processing technologies, and in particular, to a transaction data processing method, apparatus, electronic device, and readable storage medium.

Background

With the development of the electronic commerce industry, competition is also more and more intense. In order to promote service popularization, an e-commerce public can cooperate with each service provider and formulate corresponding rewarding policies based on different industries, different stages and different scenes, so that the service provider can be better stimulated to popularize the service. However, since the transaction data related to the service provider is numerous, and the rewarding conditions and the rewarding result calculation modes of different rewarding policies may be different, a method for processing the transaction data to obtain the corresponding rewarding result with high applicability is highly needed.

Disclosure of Invention

The embodiment of the specification provides a transaction data processing method, a transaction data processing device, electronic equipment and a readable storage medium.

In a first aspect, embodiments of the present disclosure provide a transaction data processing method, including: acquiring target transaction data, wherein the target transaction data comprises a plurality of transactions; matching the service provider information corresponding to each transaction in the target transaction data with a pre-stored service provider information base, and determining the rewarding strategy corresponding to each transaction, wherein the service provider information base stores a plurality of service provider information and associated information of the corresponding rewarding strategy; acquiring configuration information of each rewarding strategy corresponding to the target transaction data from a pre-stored configuration file library, wherein the configuration file library stores configuration information of one or more rewarding strategies, and the configuration information comprises strategy attribute information, rewarding judgment rules and rewarding calculation rules; counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the corresponding transaction of each rewarding strategy, and calculating the rewarding result of the counting result according to the corresponding strategy attribute information and the rewarding calculation rule.

In a second aspect, embodiments of the present disclosure provide a transaction data processing apparatus, comprising: the device comprises a first acquisition module, a determination module, a second acquisition module and a calculation module. The first acquisition module is used for acquiring target transaction data, wherein the target transaction data comprises a plurality of transactions. The determining module is used for matching the service provider information corresponding to each transaction in the target transaction data with a pre-stored service provider information base and determining the rewarding strategy corresponding to each transaction, wherein the service provider information base stores a plurality of service provider information and associated information of the corresponding rewarding strategy. The second acquisition module is used for acquiring configuration information of each rewarding strategy corresponding to the target transaction data from a pre-stored configuration file library, wherein the configuration file library stores configuration information of one or more rewarding strategies, and the configuration information comprises strategy attribute information, rewarding judgment rules and rewarding calculation rules; and the calculation module is used for counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the transactions corresponding to each rewarding strategy, and calculating the rewarding result of the counting result according to the corresponding strategy attribute information and the rewarding calculation rule.

In a third aspect, embodiments of the present disclosure provide an electronic device, including: a memory; one or more processors; and a computer program stored on a memory and executable on a processor, the processor implementing the steps of the transaction data processing method provided in the first aspect above when the program is executed.

In a fourth aspect, embodiments of the present specification provide a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the transaction data processing method provided in the first aspect described above.

The embodiment of the specification has the following beneficial effects:

according to the transaction data processing method provided by the embodiment of the specification, the rewarding strategy corresponding to the transaction is determined based on the server information contained in the transaction in the target transaction data and the pre-stored server information base, so that the configuration information of the corresponding rewarding strategy is obtained from the pre-stored configuration file base, and further, the rewarding result of the transaction corresponding to the rewarding strategy is calculated based on the configuration information of the corresponding rewarding strategy. In the processing process, since the configuration information of the rewarding strategy is read from the pre-stored configuration file library, the scheme can be used for processing the transaction data in different scenes, and the rewarding result of the corresponding transaction data can be obtained only by pre-storing the configuration information of the rewarding strategy corresponding to the required scene in the configuration file library, so that the applicability is high, and the cost and the resources are saved.

Drawings

Fig. 1 is a schematic view of an application scenario in an embodiment of the present disclosure;

FIG. 2 is a flow chart of a transaction data processing method provided in a first aspect of an embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a transaction data processing device according to a second aspect of the embodiments of the present disclosure;

fig. 4 is a schematic structural diagram of an electronic device according to a third aspect of the embodiments of the present disclosure.

Detailed Description

In order to promote service promotion, an e-commerce public can cooperate with a service provider, and based on different industries, different scenes and different stages of service development, a corresponding rewarding policy is formulated with the service provider, and a corresponding rewarding protocol is signed, so that the service provider is better stimulated to promote the service of a corresponding transaction platform. The industry, the scene and the business development can be divided according to the actual requirements of a transaction platform. For example, industries may be divided into medical, educational, travel, etc., phases into coverage phases, pin movement phases, motivation phases, etc., and scenes into on-line and off-line scenes. In addition, the service development stage should have a sequence, and for the three stages of coverage, movable sales and excitation, taking a payment transaction platform such as a payment bank as an example, a service provider should be encouraged to introduce a merchant using the transaction platform for transaction for the transaction platform, which is the coverage stage; then hope the service provider to operate the commercial tenant, make the commercial tenant trade, this is a movable sales stage; finally, it is desirable that the transaction be able to grow, which is the incentive phase.

Based on this, for the transaction data brought by the service provider, the transaction platform needs to process the transaction data, that is, obtain the rewarding results corresponding to the transaction data according to the rewarding agreement signed by the service provider, so as to rewards the service provider according to the obtained rewarding results.

Considering that each rewarding policy explicitly prescribes a calculation mode, a calculation condition and the like of a rewarding result, and the calculation modes, the calculation conditions and the like of the rewarding results of different rewarding policies are not identical, the embodiment of the present disclosure provides a transaction data processing method, which includes: acquiring target transaction data, wherein the target transaction data comprises a plurality of transactions; matching the service provider information corresponding to each transaction in the target transaction data with a pre-stored service provider information base, and determining the rewarding strategy corresponding to each transaction, wherein the service provider information base stores a plurality of service provider information and associated information of the corresponding rewarding strategy; acquiring configuration information of each rewarding strategy corresponding to the target transaction data from a pre-stored configuration file library, wherein the configuration file library stores configuration information of one or more rewarding strategies, and the configuration information comprises strategy attribute information, rewarding judgment rules and rewarding calculation rules; counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the corresponding transaction of each rewarding strategy, and calculating the rewarding result of the counting result according to the corresponding strategy attribute information and the rewarding calculation rule. The method can be used for processing transaction data in different scenes, has strong applicability and is beneficial to saving cost and resources.

It should be noted that, in the embodiment of the present disclosure, there may be a plurality of specific rewarding manners, for example, a commission returning manner may be adopted. The return commission refers to a return commission amount corresponding to the transaction data from the service provider, which is returned to the service provider as an incentive amount.

In order to better understand the technical solutions described above, the technical solutions of the embodiments of the present specification are described in detail below through the accompanying drawings and the specific embodiments, and it should be understood that the specific features of the embodiments of the present specification and the specific features of the embodiments of the present specification are detailed descriptions of the technical solutions of the embodiments of the present specification, and not limit the technical solutions of the present specification, and the technical features of the embodiments of the present specification may be combined without conflict. Herein, the term "and/or" is merely an association relation describing an association object, and means that three kinds of relations may exist, for example, a and/or B may mean: a exists alone, A and B exist together, and B exists alone.

FIG. 1 is a schematic diagram of an operating environment suitable for use in the transaction data processing method provided in the embodiments of the present disclosure. As shown in fig. 1, one or more user terminals 100 (only one shown in fig. 1) may be connected to one or more servers 300 (only one shown in fig. 1) through a network 200 for data communication or interaction. The user terminal 100 may be a personal computer (PersonalComputer, PC), a notebook computer, a tablet computer, a smart phone, or other smart devices with network functions.

In the embodiment of the present disclosure, the client of the transaction platform installed in the user terminal 100 corresponds to a Server (Server) and provides transaction services such as payment transaction, purchase transaction or group purchase transaction for the user. The client installed on the user terminal 100 may be an APP or a website for implementing a service based on the internet, and provides an operation interface for the transaction service for the user, and the user sends the transaction data executed on the transaction platform by the service provider to the server. The server gathers the transaction data from each user, stores the transaction data in the data warehouse, and processes the transaction data in the data warehouse through a preset transaction data processing method to obtain corresponding rewarding results.

In a first aspect, an embodiment of the present disclosure provides a transaction data processing method, which is applied to a server side of a transaction platform. In this embodiment, the above-described rewarding method is mainly described as an example of the commission returning, and the other rewarding methods are similar to the commission returning process, and will not be described in detail. When the rewarding mode is a return commission mode, the rewarding policy is specifically a return commission policy, the rewarding judgment rule is a return commission judgment rule, the rewarding calculation rule is specifically a return commission amount calculation rule, the rewarding transaction is specifically a return commission transaction, the rewarding result is specifically a return commission amount, and the rewarding bill is specifically a return commission bill. Referring to fig. 2, the method at least includes the following steps S201 to S204.

Step S201, target transaction data is obtained, wherein the target transaction data comprises a plurality of transactions;

the data warehouse of the server stores transaction data fed back by the corresponding client of the transaction platform, and the target transaction data need to be read from the transaction data. It will be appreciated that the target transaction data should be transactions brought about by the facilitator. For example, in some applications, the transaction data in the data warehouse is a transaction carried by a service provider, and at this time, the transaction data may be used as target transaction data to calculate a subsequent commission amount. For another example, in other application scenarios, the transaction data in the data warehouse may include both a transaction carried by the service provider and a transaction directly carried out by the user and the transaction platform, where the transaction carried by the service provider needs to be screened from the transaction data in the data warehouse as target transaction data, and the calculation of the subsequent return commission amount is performed. As an alternative, the transaction carried by the service provider and the transaction directly carried out by the user and the transaction platform can be distinguished by whether the transaction is carried with the identity of the service provider, and the transaction carried by the service provider and the transaction directly carried out by the user and the transaction platform are not carried with the identity of the service provider.

Additionally, as an alternative embodiment, dynamic delineation of targeted transaction data may also be implemented. At this time, a commission returning policy configuration step is required to be performed before step S201 is performed, that is, a commission returning policy related to the actual commission returning amount calculation is configured, and configuration information of the commission returning policy is stored in a pre-constructed configuration file library, so that in a processing process of the subsequent transaction data, the corresponding configuration information can be read as required. For example, assuming that the rebate policies involved in the actual rebate amount calculation include 10 rebate policies, it is necessary to configure the rebate policies corresponding to the 10 rebate policies, and store configuration information of all of the configured 10 rebate policies in the profile library.

In a specific application scenario, the medical industry is divided into two-level industries such as a pharmacy and a vaccine, and a certain payment platform can respectively establish a commission returning policy for on-line and off-line scenes in three business stages of coverage, movable sales and excitation aiming at a certain two-level industry.

For example, for the overlay business phase, the commission policy formulated in the on-line scenario: (1) the commission calculation rule may include: transactions that occur in a secondary industry through life numbers or applets in the paymate client; an effective transaction (effective transaction: non-cheating, non-cashing, non-money laundering transaction) in which the transaction amount (payment amount-refund amount) is 1 or more; the number of the monthly transactions of merchants meeting the conditions is more than or equal to 3000; one merchant is extended by multiple servers and the return commission is halved. (2) the settlement rate is 5000/merchant. (3) the rebate calculation formula includes: the commission returning object is a service provider; the commission amount of the service provider is the sum of commission amounts of the downhome up-to-standard merchants; up to standard merchant commission amount = 5000 yuan/expand the number of service providers of this merchant at the same time; non-compliant merchants return amount = 0.

And (3) making a commission returning policy in the coverage business stage and the on-line scene: (1) the commission calculation rule may include: transactions that occur in a secondary industry through life numbers or applets in the paymate client; an effective transaction (effective transaction: non-cheating, non-cashing, non-money laundering transaction) in which the transaction amount (payment amount-refund amount) is 1 or more; the number of the monthly transactions of merchants meeting the conditions is more than or equal to 3000; one merchant is extended by multiple servers and the return commission is halved. (2) the settlement rate is 5000/merchant. (3) the rebate calculation formula includes: the commission returning object is a service provider; the commission amount of the service provider is the sum of commission amounts of the downhome up-to-standard merchants; up to standard merchant commission amount = 5000 yuan/expand the number of service providers of this merchant at the same time; non-compliant merchants return amount = 0.

For the commission policy formulated in the dynamic sales business stage and offline scenario: (1) the commission calculation rule may include: paying the transaction occurring in a certain secondary industry on the surface through a payment platform client; the effective transaction amount (payment amount-refund amount) for the non-cheating, non-cashing, non-money laundering transaction. (2) the settlement rate is: 0.05%. (3) the rebate calculation formula includes: the effective transaction amount is a settlement rate.

For the commission policy formulated in the incentive business stage and offline scenario: (1) the commission calculation rule may include: paying the transaction occurring in a certain secondary industry on the surface through a payment platform client; the transaction amount (payment amount-refund amount) is greater than or equal to 0.5 yuan of effective transaction amount (effective transaction: non-cheating, non-cashing, non-money laundering transaction); month effective transaction increment = transaction number satisfying the above conditions for the present month-effective number satisfying the conditions 1, 2 for the previous month. (2) settlement rates include: the effective increment number of the month is 0-3 ten thousand, and the increment is 1 yuan/pen; the effective increment number of the month is 3-6 ten thousand, and the increment exceeds 3 ten thousand by 1.5 yuan per pen; when the number of effective increment per month is more than 6 ten thousand, the increment exceeds 2 yuan per pen for 6 ten thousand parts. (3) the rebate calculation formula includes: when the increment of the effective transaction number in the month is less than or equal to 30000, the return commission amount=1 yuan of increment of the effective transaction number in the month; 30000< when the month effective trading volume increment is less than or equal to 60000, the commission amount=30000×1+ (month effective trading volume increment-30000) ×1.5 yuan; 60000< effective transaction amount per month increment, commission = 30000 x 1+ (60000-3000) x 1.5+ (effective transaction amount per month increment-60000) x 2.

In particular, the configuration information of the commission return policy may include: policy attribute information, return evaluation rules, and return amount calculation rules.

Policy attribute information is used to uniquely identify a rebate policy, as determined by the particular rebate policy. Taking the payment platform formulated commission return policy as an example, the policy attribute information may include a policy ID, commission settlement rate, commission return scenario, transaction receipt product information, industry pool identification, and the like. Specifically, the settlement rate is determined by a corresponding commission policy, which may be 1 yuan/transaction or 5000 yuan/merchant, for example, or, when the commission amount calculation rule is calculated based on the transaction amount, the calculation formula is as follows: when the transaction amount is 0.0005, 0.0005 is the settlement rate. Each of the commission policies is set for a different commission scenario, e.g., the commission scenario may be determined by the industry, business stage, and scenario (online or offline) to which the commission policy corresponds. The order product information is one of merchant subscription contents, including pay-as-you-go (APP code scanning payment), WAP payment (PC end code scanning payment) and the like.

The return evaluation rules may include a plurality of sub-rules for assessing whether the transaction meets return conditions of the corresponding return policy, which may be determined in accordance with the return calculation rules. When the transaction meets the commission evaluation rule of the commission strategy, namely meets all sub-rules included in the commission evaluation rule, the transaction is judged to meet the commission condition of the commission strategy, and the transaction can participate in the commission amount settlement in the commission strategy. The rebate calculation rules are used to calculate rebate amounts for transactions that satisfy rebate conditions of the respective rebate policies.

Specifically, the commission policy configuration step may include: receiving a policy configuration instruction, wherein the policy configuration instruction is generated based on a configuration operation performed by a user in a configuration page, and comprises configuration information of a newly added commission returning policy; and adding the configuration information into the configuration file library. It should be noted that, in the policy configuration process, the user refers to a maintainer related to the transaction platform, and is not a user who performs a transaction on the transaction platform through the service provider in the foregoing.

Specifically, the configuration information of the newly added commission policy includes: policy attribute information input by the user on the configuration page; the user selects and/or inputs a commission judgment rule on the configuration page; and the user selects or inputs the commission amount calculation rule on the configuration page.

It should be noted that the newly added commission policy may be one or more. When there are a plurality of newly added commission strategies, the user needs to configure a page at the front end of the server for each newly added commission strategy, namely, configuring corresponding strategy attribute information, commission evaluation rules and commission amount calculation rules.

Because some general sub-rules may exist in the return evaluation rules of different return policies, in order to simplify the configuration process, a return evaluation rule base for storing the sub-rules may be constructed, and an index label may be set for each sub-rule, where, when configuring the return evaluation rule of the newly added return policy, the user may determine the label of the sub-rule corresponding to the corresponding return evaluation rule first. For the labels which can be found in the commission return judgment rule base, the corresponding sub-rules can be configured directly by selecting the labels; for the tags which cannot be found in the commission returning judgment rule base, the user is required to input the corresponding tags and the corresponding sub rules, and the corresponding tags and the corresponding sub rules which are input by the user are added into the commission returning judgment rule base, so that the configuration of the commission returning judgment rule can be quickly realized when the commission returning policy is newly added or modified later. Thus, as an alternative, after receiving the policy configuration instruction, it further comprises: when the configuration information of the newly added commission strategy comprises the commission judgment rule input by the user, the commission judgment rule input by the user is added into a preset commission judgment rule library.

After the configuration file library is configured, the target transaction data can be further defined. The process of delineating the target transaction data may specifically include: determining a target commission returning strategy, wherein the target commission returning strategy belongs to a commission returning strategy corresponding to the configuration file library; and acquiring the transaction data to be processed, and screening the target transaction data from the transaction data to be processed based on preset screening conditions corresponding to the target commission returning strategy, namely screening the transaction data applicable to the target commission returning strategy from the transaction data to be processed.

In particular, there are a variety of ways to determine the targeted return policy. For example, all of the rebate policies configured in the profile library may be targeted rebate policies. For another example, the user may select a commission policy currently requiring settlement of a commission amount from among all configured commission policies in the profile library as a target commission policy according to actual needs. Specifically, the selection may be based on policy attribute information of the commission policy, such as policy ID, commission scenario, etc.

Specifically, the screening conditions may be set based on policy attribute information of the target commission policy, and may be specifically configured according to actual needs. For example, when the policy attribute information of the target commission policy each includes a policy ID, a commission settlement rate, a commission scenario, transaction receipt product information, and a merchant industry pool identification, etc., a filter condition may be set based on the transaction receipt product information and/or the merchant industry pool identification.

It should be noted that, in the above step S201, each transaction includes transaction flow information, that is, transaction detail data.

For example, in one particular application scenario, the trading platform is embodied as a paymate platform that prepares a return policy for each industry, each scenario, each business stage, and then formulates a return agreement in accordance with the policy. The payment platform then signs a return commission agreement with one or more service providers, which then despreads the operating merchant and directs the merchant to the payment signing order agreement, indicating that the merchant supports payment with the payment platform, etc. Each facilitator is extended with more than or equal to one next merchant, at which time the transaction details data may include: payment serial number, transaction type, false identification, order product information, transaction initiator, transaction recipient, transaction amount, marketing amount, transaction creation source, transaction payment channel, transaction merchant ID, facilitator ID, etc. Wherein the false identification is used to identify whether the transaction is a false transaction, such as a cheating, cashing or money laundering transaction.

As an alternative embodiment, when the transaction detail data includes order receipt information and the policy attribute information also includes order receipt information, the screening condition may be set based on the transaction order receipt information. At this time, the screening the target transaction data from the transaction data to be processed based on the preset screening condition corresponding to the target commission policy may specifically include: acquiring the information of the receipt products corresponding to the target commission returning strategy to form a receipt product set; and determining the transaction data of the collection product information in the transaction data to be processed, wherein the collection product information belongs to the collection product set, and determining the target transaction data based on the determined transaction data.

As an alternative, determining the target transaction data based on the determined transaction data may specifically include: and taking the determined transaction data as target transaction data.

In the scenario that the transaction platform is a payment platform, the industry identifier corresponding to each transaction to be processed can be determined according to the merchant ID contained in the transaction detail data and a prestored merchant information base. And the merchant information base stores merchant information of all merchants operated by each service provider of the payment platform by taking the merchant ID as an index. The merchant information may specifically include a merchant name, a primary industry identification, a secondary industry identification, a contracted contract number, a contracted policy, a contracted expiration date, and the like. The first-level industry identification and the second-level industry identification are set by the payment platform based on practical application conditions, for example, the medical industry is used as the first-level industry, and the medical industry comprises second-level industries such as a pharmacy, a vaccine and the like.

Based on this, as another alternative, when the policy attribute information further includes an industry pool identifier of the merchant, determining the target transaction data based on the determined transaction data may specifically include: acquiring the industry pool identifier corresponding to the target commission returning strategy to form an industry pool set; and screening transaction data of industry pools corresponding to the industry pool sets from the determined transaction data, wherein the industry identifiers belong to the industry pools and serve as the target transaction data.

Because the screening conditions can be configured and modified according to actual needs, the embodiment of the specification can realize dynamic delineation of target transaction data.

Step S202, matching the service provider information corresponding to each transaction in the target transaction data with a pre-stored service provider information base, and determining a commission returning strategy corresponding to each transaction;

it will be appreciated that the transaction details for each transaction in the target transaction data include the facilitator information, namely the facilitator ID. Specifically, the server information base stores a plurality of server IDs and subscription information corresponding to each server, and the subscription information includes policy IDs of the commission returning policies corresponding to the server. That is, the server information base stores a plurality of pieces of server information and associated information of corresponding commission returning strategies. Of course, the subscription information may include, in addition to the policy ID, a name of a service provider, a primary industry identifier, a secondary industry identifier, a subscription contract number, a contract validity period, and the like. As an optional implementation manner, in addition to determining the commission returning policy corresponding to each transaction, step S202 above may further supplement other relevant information of the service provider corresponding to each transaction, such as a name of the service provider, a first-level industry identifier, a second-level industry identifier, a contracted number, a contract validity period, and the like.

In addition, in an application scenario where the service provider operates more than one merchant, as an optional implementation manner, before performing the following step S203, the information of the merchant corresponding to each transaction, such as the merchant name, the primary industry identifier, the secondary industry identifier, the contract signing number, the contract validity period, and the like, may be further supplemented, in addition to other relevant information of the service provider corresponding to each transaction. Specifically, the merchant information to be supplemented can be searched and obtained in a pre-stored merchant information base based on the merchant ID contained in each transaction, so as to obtain detailed data of merchants and service providers corresponding to each transaction in the dimension of the transaction number. In this way, the related merchant data and service provider data can be directly read conveniently when the commission judgment rule matching is carried out for each transaction and the corresponding commission bill is generated.

Step S203, obtaining configuration information of each commission returning strategy corresponding to the target transaction data from a pre-stored configuration file library, where the configuration file library stores configuration information of one or more commission returning strategies, and the configuration information includes strategy attribute information, commission returning evaluation rules and commission returning amount calculation rules.

After determining the commission returning policy corresponding to each transaction in the target transaction data in step S203, the configuration information of the corresponding commission returning policy may be obtained from the configuration file library. For example, assuming that the target transaction data includes 10 tens of thousands of transactions, after counting the commission strategies corresponding to the 10 tens of thousands of transactions respectively, it is determined that the 10 tens of thousands of transactions correspond to 20 commission strategies in total, and at this time, for each commission strategy of the 20 commission strategies, corresponding configuration information needs to be obtained from the configuration file library. The specific configuration process of the commission return strategy in the configuration file library is described in detail above, and will not be described here again.

Step S204, counting the return transaction conforming to the corresponding return judgment rule in the corresponding transaction of each return strategy, and calculating the return amount of the counting result according to the corresponding strategy attribute information and the return amount calculation rule.

It will be appreciated that each commission policy may sign up for one or more facilitators. When each return policy can sign up for a service provider, transaction data corresponding to each return policy is transaction data of the corresponding service provider, and at this time, return transactions conforming to return evaluation rules of the return policy need to be counted in transactions corresponding to each return policy; and obtaining the commission amount of the corresponding transaction of the corresponding service provider according to the policy attribute information of the commission policy and the commission amount calculation rule.

When each commission returning strategy signs up for a plurality of service providers, after the commission returning strategy corresponding to each transaction and the service provider information in the target transaction data are determined, the transaction data corresponding to each service provider under each commission returning strategy corresponding to the target transaction data can be determined, and transaction summary data under multiple dimensions (including commission returning strategy dimension, service provider dimension and transaction number dimension) can be obtained. Specifically, the step S204 may include: for each of the commission return policies, performing the steps of: counting the commission return transaction conforming to the commission return judgment rule of the commission return strategy in the corresponding transaction of each service provider; and calculating the commission amount of the corresponding transaction of each service provider according to the strategy attribute information of the commission strategy and the commission amount calculation rule.

For example, when the target transaction data corresponds to three types of commission policies, P1, P2, and P3, respectively, P1 corresponds to 3 service providers, F11, F12, and F13, respectively, P2 corresponds to 2 service providers, F21 and F22, respectively, and P3 corresponds to 2 service providers, F31 and F32, respectively. It should be noted that the service providers corresponding to different commission strategies may overlap, i.e., one service provider may correspond to more than one commission strategy. At this time, for the return policy P1, the return transactions conforming to the return evaluation rule of the return policy may be counted among the transactions corresponding to the service provider F11, the service provider F12, and the service provider F13, respectively; further, the return amounts of the transactions corresponding to the service providers F11, F12, and F13 are calculated based on the policy attribute information of the return policy and the return fee calculation rule. Similarly, the return amounts of the transactions corresponding to the service providers F21 and F22 under the return policy P2 and the return amounts of the transactions corresponding to the service providers F31 and F32 under the return policy P3 can be obtained, respectively.

Specifically, the process of counting the commission transactions corresponding to each commission policy and conforming to the commission evaluation rule may include: judging whether each transaction corresponding to each commission strategy accords with a commission judgment rule of the commission strategy corresponding to the transaction; and counting the return transactions conforming to the corresponding return judgment rules in the transactions corresponding to each return strategy according to the judgment result, and recording the abnormal reasons of the abnormal transactions not conforming to the corresponding return judgment rules in the transactions corresponding to each return strategy.

It will be appreciated that the return evaluation rules for a return policy are determined by the evaluation rules formulated in the particular return policy. For example, in an application scenario where the transaction platform is a paymate and more than one merchant is operated by each facilitator subscribed to the paymate, a return evaluation rule for a return policy may include a plurality of sub-rules, which may include, but are not limited to: whether transaction numbers are returned under the dimension of merchants, whether service provider dimension increment numbers are returned, whether small program transactions are excluded, whether industry identifiers corresponding to the transactions meet a merchant industry pool corresponding to the returned policies, service provider contract judgment corresponding to the transactions, merchant contract judgment corresponding to the transactions and the like. If the current transaction accords with the return judgment rule of the corresponding return strategy, namely accords with all sub rules of the return judgment rule, judging that the transaction is the return transaction corresponding to the return strategy, wherein the transaction is capable of participating in the return strategy, if one sub rule is not met, judging that the transaction does not belong to the return transaction corresponding to the return strategy, and the transaction is incapable of participating in the return settlement in the return strategy, namely the abnormal transaction. For abnormal transactions in the target transaction data, recording an abnormal reason, namely, recording which sub rule is not satisfied, so as to be convenient as a settlement basis of the return commission, and avoiding disputes with the return commission problem of the service provider as much as possible.

To further increase the calculation efficiency of the commission amount and simplify the configuration of the commission policy, as an alternative implementation, the embodiment of the present specification may further include a preprocessing step before matching the server information corresponding to each transaction in the target transaction data with a pre-stored server information base. The preprocessing step may include: preprocessing the target transaction data to obtain transaction index information of each transaction in the target transaction data, so that in the subsequent step S204, the related transaction index information can be directly read in the process of calculating the commission amount. At this time, the calculating the commission amount of the statistics according to the corresponding policy attribute information and the commission amount calculation rule includes: and calculating the commission amount corresponding to the statistical result according to the corresponding strategy attribute information, the commission amount calculation rule and the transaction index information.

For example, taking the above-mentioned commission return policy configured in the mobile-sale business stage and offline scenario for a certain secondary industry of the medical industry as an example, the effective transaction amount may be directly read from the transaction index information of the transaction data, and the settlement rate may be obtained from the policy attribute information of the commission return policy, and then substituted into the commission return amount calculation formula included in the corresponding commission return amount calculation rule: the effective transaction amount settles the rate and obtains the corresponding commission amount of the commission strategy.

In particular, the transaction index information may be selected by analyzing a commission settlement basis for a commission policy currently involved in the transaction platform. For example, taking a commission return policy related to a paymate as an example, the commission return settlement basis may include, but is not limited to, an effective transaction amount, a transaction amount (payment amount-refund amount), an order amount, and the like, and accordingly, the transaction index information may include: effective transaction amount, order amount, and the like. The effective transaction amount can be obtained according to the payment amount, refund amount, cheating amount and marketing amount of the transaction. In addition, the effective transaction amount of the transaction is 0 when the effective transaction amount of the transaction is less than or equal to 0, and the effective transaction amount of the transaction is 1 when the effective transaction amount of the transaction is greater than 0.

Further, as an optional implementation manner, after calculating the commission amount of the statistics according to the corresponding policy attribute information and the commission amount calculation rule, the method further includes a commission bill generation step. Specifically, the commission return bill generation step includes: searching a bill format of each commission returning strategy corresponding to the target transaction data in a pre-stored bill format library, wherein the bill format library stores the associated information of each commission returning strategy in the configuration file library and the corresponding bill format; and outputting a commission bill of each commission strategy corresponding to the target transaction data according to the search result.

Each commission policy may correspond to an inherent billing format. The billing format library may store billing formats for each of the commission back policies in the profile library, indexed by the policy ID of the commission back policy. The billing format can be set according to actual needs. In one specific application scenario, the billing format may include a billing output manner, a header element, and a body element. For example, the bill output mode is a separate output mode of a service provider, under the same commission return strategy, each service provider corresponds to a sub bill, each sub bill comprises a header part and a table body part, the header part comprises header elements which can include, but are not limited to, a service provider name, a service provider ID, months distributed by transaction data, commission return strategy names, commission return amounts and the like, and the table body part can be a transaction commission return condition of a corresponding merchant under the service provider, for example, the table body elements can include, but are not limited to, a service period, a merchant ID, a merchant name, a valid transaction amount corresponding to the merchant, a valid transaction number corresponding to the merchant, a settlement basis, a settlement rate, a settlement state, a settlement amount, a remark and the like. Note here that the reason why the settlement state is no, that is, the reason why settlement of the commission amount is not performed is described.

According to the found bill formats and the obtained corresponding element values, after the corresponding commission bill corresponding to the corresponding commission strategy is packaged, the commission bill can be output to a settlement workbench for relevant financial staff to check and approve, and after the approval is passed, the sub bill corresponding to each service provider in the commission bill is sent to the corresponding service provider.

In summary, in the transaction data processing method provided in the embodiments of the present disclosure, the configuration information of the return policy is read from the pre-stored configuration file library, so that the present disclosure can be used to process transaction data in different scenarios, and the return amount of the corresponding transaction data can be obtained only by pre-storing the configuration information of the return policy corresponding to the required scenario in the configuration file library, thereby having strong applicability and saving cost and resources.

Further, when a plurality of commission strategies corresponding to different commission scenes are pre-configured in the configuration file library, the commission amount of transaction data corresponding to the different commission strategies can be calculated in batches, and further, commission bills can be produced in batches; transaction data in different scenes can be processed simultaneously, and return bills corresponding to various different scenes are output simultaneously, so that bill production efficiency is greatly improved. In addition, the scheme can also configure the configuration information of the newly added commission strategy or modify the configuration information of the commission strategy in the configuration file library according to actual needs, so that the maintainability of the system is ensured.

In a second aspect, based on the same inventive concept, the embodiments of the present disclosure further provide a transaction data processing device 30, please refer to fig. 3, including:

a first obtaining module 31, configured to obtain target transaction data, where the target transaction data includes a plurality of transactions;

a determining module 32, configured to match the server information corresponding to each transaction in the target transaction data with a pre-stored server information base, and determine a rewarding policy corresponding to each transaction, where the server information base stores a plurality of server information and associated information of corresponding rewarding policies;

a second obtaining module 33, configured to obtain configuration information of each rewarding policy corresponding to the target transaction data from a pre-stored configuration file library, where the configuration file library stores configuration information of one or more rewarding policies, and the configuration information includes policy attribute information, a rewarding evaluation rule and a rewarding calculation rule;

and the calculating module 34 is configured to count rewards transactions conforming to the corresponding rewards evaluation rule in the transactions corresponding to each rewards policy, and calculate a rewards result of the counted result according to the corresponding policy attribute information and the rewards amount calculating rule.

As an alternative embodiment, the above device further comprises: the preprocessing module 35 is configured to preprocess the target transaction data to obtain transaction index information of each transaction in the target transaction data. At this time, the calculation module 34 specifically is configured to: and calculating a reward result corresponding to the statistical result according to the corresponding strategy attribute information, the reward calculation rule and the transaction index information.

As an alternative embodiment, the first obtaining module 31 includes:

a determining submodule 311, configured to determine a target rewarding policy, where the target rewarding policy belongs to a rewarding policy corresponding to the configuration file library;

and a screening sub-module 312, configured to obtain the transaction data to be processed, and screen the target transaction data from the transaction data to be processed based on a preset screening condition corresponding to the target rewarding policy.

As an optional implementation manner, the policy attribute information includes product information, where the filtering sub-module 312 is specifically configured to: acquiring the information of the order-receiving products corresponding to the target rewarding strategy to form an order-receiving product set; and determining the transaction data of the collection product information in the transaction data to be processed, wherein the collection product information belongs to the collection product set, and determining the target transaction data based on the determined transaction data.

As an alternative implementation, the policy attribute information further includes an industry pool identifier of the merchant, and the screening sub-module 312 is further configured to: acquiring the industry pool identifier corresponding to the target rewarding strategy to form an industry pool set; and screening transaction data of industry pools corresponding to the industry pool sets from the determined transaction data, wherein the industry identifiers belong to the industry pools and serve as the target transaction data.

As an alternative embodiment, the above device further comprises: and (5) configuring a module. The configuration module comprises: the receiving sub-module is used for receiving a strategy configuration instruction, wherein the strategy configuration instruction is generated based on configuration operation executed by a user in a configuration page, and comprises configuration information of a newly added rewarding strategy; and the first adding sub-module is used for adding the configuration information into the configuration file library.

As an optional implementation manner, the configuration information of the newly added rewards policy includes: policy attribute information input by the user on the configuration page; the user selects and/or inputs rewards judgment rules on the configuration page; and the user selects or inputs the rewards calculation rule on the configuration page.

As an alternative embodiment, the configuration module further includes: and the second adding sub-module is used for adding the reward evaluation rule input by the user into a preconfigured reward evaluation rule library when the configuration information of the newly added reward strategy comprises the reward evaluation rule input by the user.

As an alternative embodiment, the calculation module 34 is specifically configured to: for each rewarding strategy, the following steps are executed: counting rewarding transactions conforming to rewarding judgment rules of the rewarding strategy in the transactions corresponding to each service provider; and calculating the rewarding result of the transaction corresponding to each service provider according to the strategy attribute information of the rewarding strategy and the rewarding calculation rule.

As an alternative embodiment, the calculation module 34 is specifically configured to: judging whether each transaction corresponding to each rewarding strategy accords with rewarding judgment rules of the rewarding strategy corresponding to the transaction; counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the transactions corresponding to each rewarding strategy according to the judgment result, and recording the abnormal reasons of the abnormal transactions not conforming to the corresponding rewarding judgment rule in the transactions corresponding to each rewarding strategy.

As an alternative embodiment, the above device further comprises: bill output module 36 for: searching a bill format of each rewarding strategy corresponding to the target transaction data in a pre-stored bill format library, wherein the bill format library stores the associated information of each rewarding strategy and the corresponding bill format in the configuration file library; and outputting a reward bill of each reward strategy corresponding to the target transaction data according to the search result.

It should be noted that, in the transaction data processing device 30 provided in the embodiment of the present disclosure, the specific manner in which the respective modules perform the operations has been described in detail in the above method embodiment, and will not be described in detail herein.

In a third aspect, based on the same inventive concept as the transaction data processing method in the previous embodiment, the present invention further provides an electronic device, as shown in fig. 4, including a memory 404, one or more processors 402, and a computer program stored on the memory 404 and executable on the processor 402, where the processor 402 implements the steps of the transaction data processing method described above when executing the program.

Where in FIG. 4 a bus architecture (represented by bus 400), bus 400 may comprise any number of interconnected buses and bridges, with bus 400 linking together various circuits, including one or more processors, represented by processor 402, and memory, represented by memory 404. Bus 400 may also link together various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., as are well known in the art and, therefore, will not be described further herein. Bus interface 405 provides an interface between bus 400 and receiver 401 and transmitter 403. The receiver 401 and the transmitter 403 may be the same element, i.e. a transceiver, providing a means for communicating with various other apparatus over a transmission medium. The processor 402 is responsible for managing the bus 400 and general processing, while the memory 404 may be used to store data used by the processor 402 in performing operations.

It will be appreciated that the configuration shown in fig. 4 is merely illustrative, and that the electronic device described above may also include more or fewer components than shown in fig. 4, or have a different configuration than shown in fig. 4. The components shown in fig. 4 may be implemented in hardware, software, or a combination thereof.

In a fourth aspect, based on the inventive concept of the transaction data processing method as in the previous embodiments, the present invention further provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of any of the transaction data processing methods as described above.

The present description is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the specification. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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.

While preferred embodiments of the present description have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the disclosure.

It will be apparent to those skilled in the art that various modifications and variations can be made in the present specification without departing from the spirit or scope of the specification. Thus, if such modifications and variations of the present specification fall within the scope of the claims and the equivalents thereof, the present specification is also intended to include such modifications and variations.

Claims

1. A transaction data processing method, comprising:

acquiring target transaction data, wherein the target transaction data comprises a plurality of transactions;

matching the service provider information corresponding to each transaction in the target transaction data with a pre-stored service provider information base, and determining the rewarding strategy corresponding to each transaction, wherein the service provider information base stores a plurality of service provider information and associated information of the corresponding rewarding strategy;

acquiring configuration information of each rewarding strategy corresponding to the target transaction data from a pre-stored configuration file library, wherein the configuration file library stores configuration information of a plurality of rewarding strategies, the configuration information comprises strategy attribute information, rewarding judgment rules and rewarding calculation rules, the plurality of rewarding strategies are set based on different industries, different scenes and different stages of business development, each rewarding strategy signs one or more service providers, and the rewarding strategy configuration step of the configuration file library comprises the following steps: receiving a strategy configuration instruction generated by configuration operation executed by a user in a configuration page, and adding configuration information of a newly-added rewarding strategy included in the strategy configuration instruction into the configuration file library;

Counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the corresponding transaction of each rewarding strategy, and calculating the rewarding result of the counting result according to the corresponding strategy attribute information and the rewarding calculation rule, wherein the method comprises the following steps: counting rewards transaction conforming to rewards judgment rules of each rewards strategy in the corresponding transactions of each service provider aiming at each rewards strategy; calculating the rewarding result of the transaction corresponding to each service provider according to the strategy attribute information of the rewarding strategy and the rewarding calculation rule;

searching a bill format of each rewarding strategy corresponding to the target transaction data in a pre-stored bill format library, and outputting a rewarding bill of each rewarding strategy corresponding to the target transaction data according to a searching result, wherein the bill format library stores the associated information of each rewarding strategy and a corresponding bill format in the configuration file library, under the same rewarding strategy, each service provider corresponds to a part of sub-bill, each part of sub-bill comprises a header part and a table body part, and the header elements contained in the header part comprise a service provider name, a rewarding strategy name and a rewarding amount.

2. The method of claim 1, further comprising, before the matching the server information corresponding to each transaction in the target transaction data with a pre-stored server information base:

preprocessing the target transaction data to obtain transaction index information of each transaction in the target transaction data;

the calculating the rewarding result of the statistical result according to the corresponding strategy attribute information and the rewarding calculation rule comprises the following steps:

and calculating a reward result corresponding to the statistical result according to the corresponding strategy attribute information, the reward calculation rule and the transaction index information.

3. The method of claim 1, the obtaining target transaction data comprising:

determining a target rewarding strategy, wherein the target rewarding strategy belongs to a rewarding strategy corresponding to the configuration file library;

and acquiring transaction data to be processed, and screening the target transaction data from the transaction data to be processed based on preset screening conditions corresponding to the target rewarding strategy.

4. The method of claim 3, wherein the policy attribute information includes order product information, and wherein the screening the target transaction data from the transaction data to be processed based on a preset screening condition corresponding to the target rewards policy includes:

Acquiring the information of the order-receiving products corresponding to the target rewarding strategy to form an order-receiving product set;

and determining the transaction data of the collection product information in the transaction data to be processed, wherein the collection product information belongs to the collection product set, and determining the target transaction data based on the determined transaction data.

5. The method of claim 4, the policy attribute information further comprising an industry pool identification of a merchant, the determining the target transaction data based on the determined transaction data comprising:

acquiring the industry pool identifier corresponding to the target rewarding strategy to form an industry pool set;

and screening transaction data of industry pools corresponding to the industry pool sets from the determined transaction data, wherein the industry identifiers belong to the industry pools and serve as the target transaction data.

6. The method of claim 1, the configuration information of the newly added rewards policy comprising:

policy attribute information input by the user on the configuration page;

the user selects and/or inputs rewards judgment rules on the configuration page; and

and the user selects or inputs the rewards calculation rule on the configuration page.

7. The method of claim 6, after receiving the policy configuration instruction generated by the configuration operation performed by the user in the configuration page, further comprising:

When the configuration information of the newly added rewarding strategy comprises the rewarding judgment rule input by the user, adding the rewarding judgment rule input by the user into a pre-configured rewarding judgment rule library.

8. The method according to claim 1, wherein counting the rewards transactions conforming to the respective rewards evaluation rule among the transactions corresponding to each rewards policy includes:

judging whether each transaction corresponding to each rewarding strategy accords with rewarding judgment rules of the rewarding strategy corresponding to the transaction;

counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the transactions corresponding to each rewarding strategy according to the judgment result, and recording the abnormal reasons of the abnormal transactions not conforming to the corresponding rewarding judgment rule in the transactions corresponding to each rewarding strategy.

9. A transaction data processing apparatus comprising:

the first acquisition module is used for acquiring target transaction data, wherein the target transaction data comprises a plurality of transactions;

the determining module is used for matching the service provider information corresponding to each transaction in the target transaction data with a pre-stored service provider information base and determining the rewarding strategy corresponding to each transaction, wherein the service provider information base stores a plurality of service provider information and associated information of the corresponding rewarding strategy;

The second obtaining module is configured to obtain configuration information of each rewarding policy corresponding to the target transaction data from a pre-stored configuration file library, where the configuration file library stores configuration information of multiple rewarding policies, the configuration information includes policy attribute information, a rewarding evaluation rule and a rewarding calculation rule, the multiple rewarding policies are set based on different industries, different scenes and different stages of service development, each rewarding policy signs one or more service providers, and the rewarding policy configuration step of the configuration file library includes: receiving a strategy configuration instruction generated by configuration operation executed by a user in a configuration page, and adding configuration information of a newly-added rewarding strategy included in the strategy configuration instruction into the configuration file library;

the calculation module is used for counting the rewarding transaction conforming to the corresponding rewarding judgment rule in the transactions corresponding to each rewarding strategy, and calculating the rewarding result of the counting result according to the corresponding strategy attribute information and the rewarding calculation rule, and comprises the following steps: counting rewards transaction conforming to rewards judgment rules of each rewards strategy in the corresponding transactions of each service provider aiming at each rewards strategy; calculating the rewarding result of the transaction corresponding to each service provider according to the strategy attribute information of the rewarding strategy and the rewarding calculation rule;

The bill output module is used for searching a bill format of each rewarding strategy corresponding to the target transaction data in a pre-stored bill format library, wherein the bill format library stores the associated information of each rewarding strategy and the corresponding bill format in the configuration file library; outputting a reward bill of each reward strategy corresponding to the target transaction data according to the search result, wherein under the same reward strategy, each server corresponds to a part of sub-bill, each part of sub-bill comprises a header part and a body part, and the header elements contained in the header part comprise a server name, a reward strategy name and a reward amount.

10. The apparatus of claim 9, further comprising: the preprocessing module is used for preprocessing the target transaction data to obtain transaction index information of each transaction in the target transaction data;

the computing module is specifically configured to: and calculating a reward result corresponding to the statistical result according to the corresponding strategy attribute information, the reward calculation rule and the transaction index information.

11. The apparatus of claim 9, the first acquisition module comprising:

The determining submodule is used for determining a target rewarding strategy, and the target rewarding strategy belongs to a rewarding strategy corresponding to the configuration file library;

and the screening sub-module is used for acquiring the transaction data to be processed and screening the target transaction data from the transaction data to be processed based on preset screening conditions corresponding to the target rewarding strategy.

12. The apparatus of claim 11, the policy attribute information comprising order product information, the screening submodule to:

13. The apparatus of claim 12, the policy attribute information further comprising an industry pool identification of a merchant, the screening submodule being specifically configured to:

14. The apparatus of claim 9, further comprising: a configuration module, the configuration module comprising:

the receiving sub-module is used for receiving a strategy configuration instruction, wherein the strategy configuration instruction is generated based on configuration operation executed by a user in a configuration page, and comprises configuration information of a newly added rewarding strategy;

and the first adding sub-module is used for adding the configuration information into the configuration file library.

15. The apparatus of claim 14, the configuration information of the newly added rewards policy comprising:

policy attribute information input by the user on the configuration page;

16. The apparatus of claim 15, the configuration module further comprising:

and the second adding sub-module is used for adding the reward evaluation rule input by the user into a preconfigured reward evaluation rule library when the configuration information of the newly added reward strategy comprises the reward evaluation rule input by the user.

17. The apparatus of claim 9, the computing module being specifically configured to:

18. An electronic device, comprising:

a memory;

one or more processors; and

Computer program stored on a memory and executable on a processor, said processor implementing the steps of the method according to any one of claims 1-8 when said program is executed.

19. A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method of any of claims 1-8.