Payment data splitting method and device and storage medium

Abstract

The invention relates to the field of receipt processing, and discloses a payment data splitting method and device and a storage medium. The method comprises the steps of receiving N pieces of payment bill data and M pieces of externally pushed input bill data based on multiple threads; according to a preset Easpoi component, integrity verification of payee details, feature codes and payment types is carried out on the N pieces of payment bill data and the M pieces of input bill data, and multiple pieces of payment instance data are obtained; integrity complex verification and payment verification are carried out on the first application data and the second application data to obtain qualified application data, and integrity complex verification, payment verification and quota management and control verification are carried out on the quota data to obtain qualified quota data; and packaging the qualified application data and the qualified quota data to obtain an application form and a quota form. In the embodiment of the invention, the payment order and the entry order are classified and verified, so that the payment data splitting accuracy is improved, and the situation of manual intervention and adjustment is reduced.

Description

Technical Field

[0001] The present invention relates to the field of document processing, and in particular to a payment data splitting method, device and storage medium. Background Art

[0002] Payment data splitting in payment business is developing with the advancement of technology and the continuous changes in business demand scenarios. With the expansion of business and the growth of user numbers, the automation of data splitting has become a technical development direction.

[0003] Document splitting is a process where users fill in payment master document information and import payee details with simple data. There is no need to fill in duplicate data or manually determine the document type. This document splitting method can quickly split payment master document information, create detailed data, and establish associations. In automatic document splitting, users can complete document splitting operations through system selections, external system push, partial manual input, and import. This operation method not only reduces the workload and complexity of obtaining response data from other systems, but also makes full use of table tools to reduce manual data input.

[0004] In traditional order splitting, there is diversity in the data of payment order details, involving multiple parties, such as users, enterprises, units, etc. Maintaining the integrity, accuracy and consistency of the data requires manual judgment and processing, which is prone to quality problems. The detailed data in the payment business can be a single transaction or multiple transactions. In the case of multiple transactions, if it is necessary to manually sort and enter them in units of single items, then this data splitting method will consume a lot of time and increase repetitive work, affecting the progress of the payment business. There are data related to other systems in the payment order details. After one party modifies the traditional order splitting, the relevant personnel need to manually modify it before executing the order splitting operation, which will cause a time difference problem and lack of timeliness in the data. Therefore, in view of the technical problem that the current payment data splitting is not accurate enough and requires manual intervention, resulting in slow payment speed, a new technology is needed to solve the current problem. Summary of the invention

[0005] The main purpose of the present invention is to solve the technical problem that the current payment data splitting is not accurate enough and requires manual intervention, resulting in slow payment speed.

[0006] A first aspect of the present invention provides a payment data splitting method, the payment data splitting method comprising: Receive N payment order data and M externally pushed entry order data based on multi-threading, where N and M are both positive integers; According to the preset Easypoi component, the N payment order data and the M entry order data are subjected to integrity verification of payee details, feature codes, and payment types, and a plurality of payment instance data that pass the verification are obtained, wherein the payment types include: scientific research type and non-scientific research type; Splitting the payment instance data corresponding to the scientific research type into first application data, and splitting the payment instance data corresponding to the non-scientific research type into second application data and quota data; Performing integrity recheck and payment check on the first application data and the second application data to obtain qualified application data, and performing integrity recheck, payment check, and credit limit control check on the credit limit data to obtain qualified credit limit data; The qualified application data and the qualified quota data are packaged to obtain an application form and a quota form.

[0007] Optionally, in a first implementation of the first aspect of the present invention, the N payment order data and the M entry order data are subjected to integrity verification of payee details, feature codes, and payment types according to the preset Easypoi component, and multiple payment instance data that pass the verification are obtained, including: According to the preset Easypoi component, the N payment order data and the M entry order data are checked for integrity of the payment account number, the payee name, the payment amount, the batch feature code, the payment subject feature code, and the payment type, and multiple verification results are obtained; Determine whether there is a qualified mark in the verification result; When there is a qualified identification, the payment instance data corresponding to the verification result is determined as the payment instance data that has passed the verification.

[0008] Optionally, in a second implementation of the first aspect of the present invention, encapsulating the qualified application data and the qualified credit limit data to obtain an application form and a credit limit form includes: Based on the feature code, the qualified application data is associated with the N payment order data and the M entry order data to generate application association parameters; The application-related parameters are combined with the qualified application data to generate an application form.

[0009] Optionally, in a third implementation of the first aspect of the present invention, encapsulating the qualified application data and the qualified credit limit data to obtain an application form and a credit limit form further comprises: Based on the feature code, the qualified credit limit data is associated with the N payment order data and the M entry order data to generate credit limit association parameters; The credit limit associated parameters are combined with the qualified credit limit data to generate a credit limit list.

[0010] Optionally, in a fourth implementation manner of the first aspect of the present invention, the performing integrity recheck and payment check on the first application data and the second application data to obtain qualified application data includes: Performing integrity check on the format of the filled-in items, the length of the options, and the keywords of the first application data and the second application data to obtain preliminary qualified application data; The preliminary qualified application data is subjected to payment verification of payment channel and single payment amount to obtain qualified application data.

[0011] Optionally, in a fifth implementation of the first aspect of the present invention, performing integrity verification, payment verification, and quota control verification on the quota data to obtain qualified quota data includes: Perform integrity check on the entry format, option length, and keywords of the credit limit data to obtain preliminary qualified credit limit data; Performing payment verification on the payment channel and single payment amount of the preliminary qualified credit limit data to obtain re-inspected qualified credit limit data; The re-inspected qualified quota data is subjected to quota control verification of the total amount of the quota to obtain qualified quota data.

[0012] Optionally, in a sixth implementation of the first aspect of the present invention, after receiving N payment order data and M externally pushed entry order data based on multi-threading, before performing integrity verification of the payee details, feature code, and payment type on the N payment order data and the M entry order data according to the preset Easypoi component to obtain multiple payment instance data that pass the verification, it also includes: Reading the sending addresses of the N payment order data and the M entry order data; According to a preset legal address set, the sending address is subjected to a legality check to obtain an address check result; When the address verification result is unqualified, the payment order data and entry order data corresponding to the address verification result are eliminated.

[0013] Optionally, in a seventh implementation of the first aspect of the present invention, after encapsulating the qualified application data and the qualified credit limit data to obtain an application form and a credit limit form, the method further includes: According to the application form and the credit limit form, feedback adjustment processing is performed on the corresponding parameters of the integrity check, the corresponding parameters of the payment check, and the corresponding parameters of the credit limit control check.

[0014] A second aspect of the present invention provides a payment data splitting device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via a line; the at least one processor calls the instructions in the memory so that the payment data splitting device executes the above-mentioned payment data splitting method.

[0015] A third aspect of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, which, when executed on a computer, enable the computer to execute the above-mentioned payment data splitting method.

[0016] In an embodiment of the present invention, integrity checks are performed on the transmitted payment order data and entry order data, the document data with qualified integrity are parsed one by one, and classified into instance data corresponding to scientific research types and non-scientific research types, and then different secondary checks are performed on the classified instance data, and the instance data that pass the secondary check are classified and encapsulated, thereby improving the accuracy of payment data splitting, reducing the need for manual intervention and adjustment, and effectively solving the technical problem that the current payment data splitting is not accurate enough and requires manual intervention, resulting in slow payment speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A schematic diagram of an embodiment of a method for splitting payment data in an embodiment of the present invention; Figure 2 A schematic diagram of a data splitting framework of a payment data splitting method according to an embodiment of the present invention; Figure 3 A schematic diagram of a data verification framework of a payment data splitting method according to an embodiment of the present invention; Figure 4 A schematic diagram of an embodiment of a payment data splitting device in an embodiment of the present invention. DETAILED DESCRIPTION

[0018] Embodiments of the present invention provide a payment data splitting method, device and storage medium.

[0019] The embodiments disclosed in the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments disclosed in the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments disclosed in the present invention are only for exemplary purposes and are not intended to limit the scope of protection disclosed in the present invention.

[0020] In the description of the embodiments disclosed in the present invention, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0021] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 An embodiment of the payment data splitting method in the embodiment of the present invention includes: 101. Receive N payment order data and M externally pushed entry order data based on multi-threading, where N and M are both positive integers; In this embodiment, multiple payment order data and multiple entry order data are received in multiple threads, and the batch data processing function is performed in multiple threads. Different payment orders have different amounts of payee detail data. When the amount of input data exceeds a custom threshold, the current multi-thread setting will be triggered, and the established rules will be executed to generate and persist data in a short time.

[0022] 102. According to the preset Easypoi component, the N payment order data and the M entry order data are subjected to integrity verification of payee details, feature codes, and payment types, and a plurality of payment instance data that pass the verification are obtained, wherein the payment types include: scientific research type and non-scientific research type; In this embodiment, EasyPoi is a Java library based on Apache POI, which is used to simplify the import and export operations of Excel documents. The tool is used to parse the table and map the data in the table to each payment instance.

[0023] EasyPoi verifies the payee details, transaction identification code, and payment type of the payment order data and the entry order data. The main transaction determines whether the payment order data and the entry order data both have the fill-in data of the payee details, transaction identification code, and payment type. It should be noted that the payment order data is the data automatically generated by the system based on the transaction process, and the entry order data is the data manually filled in by the user according to the transaction process. Each payment order data and entry order data can have multiple transactions, and each transaction constitutes a payment instance. The EasyPoi component verifies and checks the payment instance data one by one, sorts the qualified data, and obtains multiple qualified payment instance data.

[0024] By judging and verifying the element information of the main payment order, the details of different payees are split according to the rules, and the payment order is automatically split into application order and quota order. It supports a variety of payment order types and can flexibly configure order splitting rules according to different business needs to improve the flexibility and applicability of order splitting.

[0025] Furthermore, after step 101 and before step 102, the method further includes: 1011. Read the sending addresses of the N payment order data and the M entry order data; 1012. Perform a validity check on the sending address according to a preset legal address set to obtain an address verification result; 1013. When the address verification result is unqualified, the payment order data and input order data corresponding to the address verification result are eliminated.

[0026] In steps 1011-1013, the sending addresses of the payment order data and the entry order data are read, and the sending addresses are matched in the pre-set legal address set. If the sending address is in the pre-set legal address set, it means that the sending address is qualified data. If the sending address is not in the pre-set legal address set, it means that the sending address is unqualified data. The payment order data and entry order data transmitted from the sending address are eliminated to avoid the intrusion of illegal data and ensure the security of data transmission.

[0027] Specifically, step 102 includes the following specific implementations: 1021. According to the preset Easypoi component, the N payment order data and the M entry order data are checked for integrity of the payment account number, the payee name, the payment amount, the batch feature code, the payment subject feature code, and the payment type, and multiple verification results are obtained; 1022. Determine whether there is a qualified mark in the verification result; 1023. When there is a qualified identifier, the payment instance data corresponding to the verification result is determined as the payment instance data that has passed the verification.

[0028] In steps 1021-1023, through the Easypoi component, N payment order data and M input order data are analyzed one by one to see whether there are payment and collection accounts, payee names, payment amounts, batch feature codes, payment subject feature codes, and payment type data. The payment and collection accounts include the receiving account and the payment account, the payee names include the payee name and the payee name, the payment amounts include the collection amount and the payment amount, the batch feature code can be the transaction code in the transaction process to confirm the serial number of the unique transaction, the payment subject feature code includes the code of the payment subject company and the code of the payment subject company, and the payment type includes the setting of scientific research type and non-scientific research type. The above data is checked for integrity to obtain multiple verification results corresponding to multiple payment instances. When the verification result is qualified, the payment instance data corresponding to the verification result is determined as the qualified payment instance data to achieve the verification of the payment instance.

[0029] 103. Split the payment instance data corresponding to the scientific research type into first application data, and split the payment instance data corresponding to the non-scientific research type into second application data and quota data; In this example, see Figure 2 , Figure 2 This is a schematic diagram of the data splitting framework of the payment data splitting method in an embodiment of the present invention. During the data splitting process, the payment instance data that has been identified as a scientific research type in step 102 is divided into first application data, and the payment instance data that has been identified as a non-scientific research type in step 102 is split into second application data and quota data, and the split completed data is placed in the next module program for verification.

[0030] 104. Perform integrity recheck and payment check on the first application data and the second application data to obtain qualified application data, and perform integrity recheck, payment check, and credit limit control check on the credit limit data to obtain qualified credit limit data; In this example, see Figure 3 , Figure 3 The data verification framework diagram of the payment data splitting method in the embodiment of the present invention is shown in the figure. The integrity of the split first application data and the second application data is rechecked. The second integrity check verifies the data format, length, keywords and other contents, and then verifies some parameters provided by the payment system such as the nature of payment. In addition to the integrity recheck and payment verification, the quota data also needs to be verified by the control unit rules. This verification involves other modules of the special funds. The basic logic is that the data of the control unit needs to be divided, classified, and verified.

[0031] Specifically, in step 104, "performing integrity recheck and payment check on the first application data and the second application data to obtain qualified application data" includes the following specific implementation methods: 1041. Perform integrity check on the format of the filled-in items, the length of the options, and the keywords of the first application data and the second application data to obtain preliminary qualified application data; 1042. Perform payment verification on the payment channel and single payment amount of the preliminary qualified application data to obtain qualified application data.

[0032] In steps 1041-1042, the first application data and the second application data are first checked for integrity in terms of the format of the filled items, the length of the options, and the contents of the keywords. Then, the single payment amount is checked to see if it exceeds the limit, and the payment channel is a designated channel for the transaction. When the single payment amount does not exceed the limit and the payment channel is a designated channel, the payment instance determined in the preliminary qualified application data is determined as qualified application data. The verification is performed one by one until all payment instances are verified, and all payment instances that have passed the verification are collected to obtain qualified application data.

[0033] Specifically, in step 104, "performing integrity recheck, payment check, and credit control check on the credit limit data to obtain qualified credit limit data" includes the following specific implementation methods: 1043. Perform integrity check on the entry format, option length, and keywords of the credit limit data to obtain preliminary qualified credit limit data; 1044. Perform payment verification on the payment channel and single payment amount of the preliminary qualified credit limit data to obtain re-inspected qualified credit limit data; 1045. Perform quota control verification on the total amount of the re-inspected qualified quota data to obtain qualified quota data.

[0034] In steps 1041-1042, the credit limit data is checked for completeness of the entry format, option length, and keywords, and the qualified payment instances in the credit limit data are determined as preliminary qualified credit limit data. The preliminary qualified credit limit data is checked for payment channels and single payment amounts, and the qualified payment instances in the preliminary qualified credit limit data are determined as re-inspected qualified credit limit data. The re-inspected qualified credit limit data is checked for credit limit control of the total credit amount, and the qualified payment instances in the re-inspected qualified credit limit data are determined as qualified credit limit data.

[0035] 105. Encapsulate the qualified application data and the qualified quota data to obtain an application form and a quota form.

[0036] In this embodiment, the qualified application data and qualified credit limit data that have been parsed, split, and verified are packaged, the qualified application data is packaged into an application form, and the qualified credit limit data is packaged into a credit limit form, thereby realizing the splitting and packaging of N payment form data and M entry form data into a table to obtain an application form and a credit limit form.

[0037] Specifically, step 105 includes the following specific implementation methods: 1051. Based on the feature code, the qualified application data is associated with the N payment order data and the M entry order data to generate application association parameters; 1052. Combine the application-related parameters with the qualified application data to generate an application form.

[0038] In steps 1051-1052, based on the batch feature code of the payment flow, the qualified application data is associated with the N payment order data and the M entry order data to obtain the application association parameter. Based on the application association parameter of the associated master order and the detail, the payment instances of the same payment order data or entry order data in the qualified application data are integrated, so as to realize the application form showing the details of the qualified payment instances corresponding to different payment orders or entry orders.

[0039] Specifically, step 105 also includes the following specific implementation methods: 1053. Based on the feature code, the qualified credit limit data is associated with the N payment order data and the M entry order data to generate credit limit association parameters; 1054. Combine the credit limit associated parameters with the qualified credit limit data to generate a credit limit list.

[0040] In steps 1053-1054, based on the batch feature code of the payment flow, the qualified amount data is associated with the N payment order data and the M entry order data to obtain the amount association parameters.

[0041] Furthermore, after step 105, the following specific implementations are also included: 106. According to the application form and the credit limit form, feedback adjustment processing is performed on the corresponding parameters of the integrity check, the corresponding parameters of the payment check, and the corresponding parameters of the credit limit control check.

[0042] In step 106, the parameters corresponding to the integrity check are the coding parameters of the association relationship between the main order and the details, as well as the parameters displayed to the outside by the detail order and the main order respectively; the parameters corresponding to the payment check are some parameters provided by the payment system, such as payment nature, payment channel, payment limit, etc.; the parameters corresponding to the limit control check are the parameter settings that exist separately for the limit, through which the data of other modules can be associated.

[0043] According to the data obtained in the application form and the credit limit form, feedback adjustment is performed on the corresponding parameters of the integrity verification, the corresponding parameters of the payment verification, and the corresponding parameters of the credit limit control verification. The feedback adjustment includes the credit limit adjustment of different unit entities, the integrity verification history record, the payment verification history record, etc.

[0044] In an embodiment of the present invention, integrity checks are performed on the transmitted payment order data and entry order data, the document data with qualified integrity are parsed one by one, and classified into instance data corresponding to scientific research types and non-scientific research types, and then different secondary checks are performed on the classified instance data, and the instance data that pass the secondary check are classified and encapsulated, thereby improving the accuracy of payment data splitting, reducing the need for manual intervention and adjustment, and effectively solving the technical problem that the current payment data splitting is not accurate enough and requires manual intervention, resulting in slow payment speed.

[0045] Figure 4 4 is a schematic diagram of the structure of a payment data splitting device provided by an embodiment of the present invention. The payment data splitting device 400 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 410 (for example, one or more processors) and a memory 420, and one or more storage media 430 (for example, one or more mass storage devices) storing application programs 433 or data 432. Among them, the memory 420 and the storage medium 430 can be short-term storage or permanent storage. The program stored in the storage medium 430 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the payment data splitting device 400. Furthermore, the processor 410 may be configured to communicate with the storage medium 430 to execute a series of instruction operations in the storage medium 430 on the payment data splitting device 400.

[0046] The payment data-based splitting device 400 may also include one or more power supplies 440, one or more wired or wireless network interfaces 450, one or more input and output interfaces 460, and / or one or more operating systems 431, such as Windows Serve, Mac OS X, Unix, Linux, Free BSD, etc. It will be appreciated by those skilled in the art that Figure 4 The illustrated payment data splitting device structure does not constitute a limitation on the payment data-based splitting device, and may include more or fewer components than illustrated, or a combination of certain components, or a different arrangement of components.

[0047] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the payment data splitting method.

[0048] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0049] In addition, although each operation is described in a specific order, this should be understood as requiring such operation to be performed in the specific order shown or in a sequential order, or requiring that all illustrated operations should be performed to obtain desired results. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single implementation in combination. On the contrary, the various features described in the context of a single implementation can also be implemented in multiple implementations individually or in any suitable sub-combination mode.

[0050] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A payment data splitting method, characterized in that: include: Receive N payment order data and M externally pushed entry order data based on multi-threading, where N and M are both positive integers; According to the preset Easypoi component, the N payment order data and the M entry order data are subjected to integrity verification of payee details, feature codes, and payment types, and a plurality of payment instance data that pass the verification are obtained, wherein the payment types include: scientific research type and non-scientific research type; Splitting the payment instance data corresponding to the scientific research type into first application data, and splitting the payment instance data corresponding to the non-scientific research type into second application data and quota data; Performing integrity recheck and payment check on the first application data and the second application data to obtain qualified application data, and performing integrity recheck, payment check, and credit limit control check on the credit limit data to obtain qualified credit limit data; The qualified application data and the qualified quota data are packaged to obtain an application form and a quota form.

2. The payment data splitting method according to claim 1, characterized in that: According to the preset Easypoi component, the N payment order data and the M entry order data are subjected to integrity verification of payee details, feature codes, and payment types, and multiple payment instance data that pass the verification are obtained, including: According to the preset Easypoi component, the N payment order data and the M entry order data are checked for integrity of the payment account number, the payee name, the payment amount, the batch feature code, the payment subject feature code, and the payment type, and multiple verification results are obtained; Determine whether there is a qualified mark in the verification result; When there is a qualified identification, the payment instance data corresponding to the verification result is determined as the payment instance data that has passed the verification.

3. The payment data splitting method according to claim 1, characterized in that: The step of encapsulating the qualified application data and the qualified credit limit data to obtain an application form and a credit limit form includes: Based on the feature code, the qualified application data is associated with the N payment order data and the M entry order data to generate application association parameters; The application-related parameters are combined with the qualified application data to generate an application form.

4. The payment data splitting method according to claim 1, characterized in that: The step of encapsulating the qualified application data and the qualified credit limit data to obtain an application form and a credit limit form further comprises: Based on the feature code, the qualified credit limit data is associated with the N payment order data and the M entry order data to generate credit limit association parameters; The credit limit associated parameters are combined with the qualified credit limit data to generate a credit limit list.

5. The payment data splitting method according to claim 1, characterized in that: The performing integrity recheck and payment check on the first application data and the second application data to obtain qualified application data comprises: Performing integrity check on the format of the filled-in items, the length of the options, and the keywords of the first application data and the second application data to obtain preliminary qualified application data; The preliminary qualified application data is subjected to payment verification of payment channel and single payment amount to obtain qualified application data.

6. The payment data splitting method according to claim 1, characterized in that: The integrity recheck, payment check, and credit control check of the credit limit data to obtain qualified credit limit data includes: Perform integrity check on the entry format, option length, and keywords of the credit limit data to obtain preliminary qualified credit limit data; Performing payment verification on the payment channel and single payment amount of the preliminary qualified credit limit data to obtain re-inspected qualified credit limit data; The re-inspected qualified quota data is subjected to quota control verification of the total amount of the quota to obtain qualified quota data.

7. The payment data splitting method according to claim 1, characterized in that: After receiving N payment order data and M externally pushed entry order data based on multithreading, and before performing integrity verification of payee details, feature codes, and payment types on the N payment order data and the M entry order data according to the preset Easypoi component, and obtaining multiple payment instance data that pass the verification, it also includes: Reading the sending addresses of the N payment order data and the M entry order data; According to a preset legal address set, the sending address is subjected to a legality check to obtain an address check result; When the address verification result is unqualified, the payment order data and entry order data corresponding to the address verification result are eliminated.

8. The payment data splitting method according to claim 1, characterized in that: After the qualified application data and the qualified credit limit data are packaged to obtain an application form and a credit limit form, the method further includes: According to the application form and the credit limit form, feedback adjustment processing is performed on the corresponding parameters of the integrity check, the corresponding parameters of the payment check, and the corresponding parameters of the credit limit control check.

9. A payment data splitting device, characterized in that: The payment data splitting device comprises: a memory and at least one processor, the memory stores instructions, and the memory and the at least one processor are interconnected via a line; The at least one processor calls the instruction in the memory to enable the payment data splitting device to perform the payment data splitting method according to any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the payment data splitting method according to any one of claims 1 to 8 is implemented.

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