CN111951101B - Data checking method and device - Google Patents
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Abstract
The application provides a data checking method and device, and relates to the field of big data. The data checking method comprises the following steps: dividing the host account details and the platform account details into a plurality of groups according to dates; sequencing the host account details and platform account details in each group according to the unique service detail identification fields; dividing the host account details and the platform account details in each sorted group into a plurality of data segments; and carrying out parallel check on the data segments corresponding to the host account details and the platform account subdivision in each group. The application can reduce the system consumption and the host pressure, and can also improve the checking efficiency and accuracy.
Description
Technical Field
The application relates to the technical field of computers, in particular to the technical field of big data, and particularly relates to a data checking method and device.
Background
In recent years, with the development of bank informatization technology, a large commercial bank gradually changes from a traditional large-scale host centralized architecture to a development platform distributed architecture, and bank system transfer and remittance gradually evolves into a distributed system.
In a distributed system, the platform transfer details need to be consistent with the host account details. In the traditional method, a server downloads a file to check with a platform instruction, or a platform calls a host interface to inquire the details of a host account for checking, and the business details of the platform with large daily data volume are checked stroke by stroke, so that the resource consumption is very large. Due to the time difference between the platform and the host, the platform can not find the details of the host account, and the account is checked by the platform transfer remittance to be misreported.
Therefore, there is a need for an accounting checking method that ensures consistency of account details.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a data checking method and a data checking device, and provides the following technical scheme:
in a first aspect, the present application provides a data collation method, comprising:
dividing the host account details and the platform account details into a plurality of groups according to dates;
sequencing the host account details and platform account details in each group according to the unique service detail identification fields;
dividing the host account details and the platform account details in each sorted group into a plurality of data segments;
and carrying out parallel check on the data segments corresponding to the host account details and the platform account subdivision in each group.
Further, the method further comprises the following steps: starting a secondary rechecking operation according to the checking result;
and if the secondary check operation passes, the mark check passing mark, and if the secondary check operation does not pass, the mark check not passing mark.
Wherein, the checking includes:
searching a host account detail data source from the platform account detail, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from the platform account detail, searching whether the host account detail has records or not according to the event number of the enterprise platform account detail transaction success instruction and the bank reply time, and naming the data without records as an error type A2;
finding out the host account details of the reply time according to the platform account details unique identification channel event numbering rules, and reversely searching whether a record exists in the T day instruction table; the data without record is named as an error type A3;
and searching the host account detail data according to the platform account detail unique identification channel event numbering rule to calculate whether the total sum and the total sum of the reply time are consistent with the total sum and the total sum of successful transaction of the platform account detail instruction, and naming the inconsistent record as an error type A4.
Further, the method further comprises the following steps:
and acquiring data corresponding to the mark which is marked as the mark which does not pass the verification, and transmitting the acquired data to a manual verification system.
In a second aspect, the present application provides a data collation apparatus comprising:
the dividing unit divides the host account details and the platform account details into a plurality of groups according to the dates respectively;
the ordering unit is used for ordering the host account details and the platform account details in each group according to the unique service detail identification fields;
the data section unit is used for dividing the host account details and the platform account details in each sorted group into a plurality of data sections;
and the first checking unit is used for performing parallel checking according to the data segments corresponding to the host account details and the platform account subdivision in each group.
Further, the method further comprises the following steps:
a second checking unit for starting a secondary checking operation according to the checking result;
and if the secondary check operation passes, the mark check passing mark, and if the secondary check operation does not pass, the mark check not passing mark.
Wherein, the checking includes:
searching a host account detail data source from the platform account detail, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from the platform account detail, searching whether the host account detail has records or not according to the event number of the enterprise platform account detail transaction success instruction and the bank reply time, and naming the data without records as an error type A2;
finding out the host account details of the reply time according to the platform account details unique identification channel event numbering rules, and reversely searching whether a record exists in the T day instruction table; the data without record is named as an error type A3;
and searching the host account detail data according to the platform account detail unique identification channel event numbering rule to calculate whether the total sum and the total sum of the reply time are consistent with the total sum and the total sum of successful transaction of the platform account detail instruction, and naming the inconsistent record as an error type A4.
Further, the method further comprises the following steps:
and the sending unit is used for acquiring the data corresponding to the mark marked as the mark which does not pass the verification and sending the acquired data to the manual verification system.
In a third aspect, the present application provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the data collation method when executing the program.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the data collation method.
According to the technical scheme, the application provides a data checking method and a data checking device, wherein a host account detail and a platform account detail are respectively divided into a plurality of groups according to dates; sequencing the host account details and platform account details in each group according to the unique service detail identification fields; dividing the host account details and the platform account details in each sorted group into a plurality of data segments; and carrying out parallel check on the data segments corresponding to the host account details and platform account subdivision in each group, so that the system consumption can be reduced, the host pressure can be reduced, and the check efficiency and accuracy can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a first flow chart of a data checking method according to an embodiment of the application.
Fig. 2 is a second flow chart of the data checking method according to the embodiment of the application.
Fig. 3 is a third flow chart of the data checking method according to the embodiment of the application.
Fig. 4 is a general flowchart of a data collation method in the embodiment of the present application.
FIG. 5 is a diagram of a money transfer and reconciliation for an enterprise network banking in a data reconciliation method in accordance with an embodiment of the application.
Fig. 6 is a diagram of a secondary reconciliation of corporate internet banking transfer remittance in a data reconciliation method in accordance with an embodiment of the application.
Fig. 7 is a schematic diagram of a data collation apparatus in the embodiment of the present application.
Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The application provides an embodiment of a data checking method, referring to fig. 1, the data checking method specifically comprises the following steps:
s101: dividing the host account details and the platform account details into a plurality of groups according to dates;
in the step, the host account details start from a host account detail table, a service detail unique identification field and a key service element field are arranged and exported into a file according to the working date and the unique identification ascending order, and batch operation is conducted into a data lake;
the platform account details are transaction details of the enterprise network bank transfer remittance platform, the enterprise network bank transfer remittance platform registers a plurality of databases when registering transaction details data, the efficiency of inquiring data export files is improved according to date partitions, and a plurality of batch operations are used for importing the export files of the enterprise network bank transfer remittance platform into a data lake in parallel.
S102: sequencing the host account details and platform account details in each group according to the unique service detail identification fields;
in the step, the unique identification field or the channel event number or the account number of the receiver/payer is parallelly exported into a file according to the bank reply time in ascending order.
S103: dividing the host account details and the platform account details in each sorted group into a plurality of data segments;
s104: and carrying out parallel check on the data segments corresponding to the host account details and the platform account subdivision in each group.
In the step, concurrent checking is used, and matching checking is carried out on the data source data at two sides according to the unique identification field or the enterprise network banking channel event number;
and according to the matching result, the data of existence host account details of the enterprise network bank, existence of the host account details of the enterprise network bank and inconsistent transaction elements, existence of the host account details of the enterprise network bank and inconsistent total amount of the enterprise network bank are exported to the enterprise network bank.
The parallel collation includes:
searching a host account detail data source from the platform account detail, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from the platform account detail, searching whether the host account detail has records or not according to the event number of the enterprise platform account detail transaction success instruction and the bank reply time, and naming the data without records as an error type A2;
finding out the host account details of the reply time according to the platform account details unique identification channel event numbering rules, and reversely searching whether a record exists in the T day instruction table; the data without record is named as an error type A3;
and searching the host account detail data according to the platform account detail unique identification channel event numbering rule to calculate whether the total sum and the total sum of the reply time are consistent with the total sum and the total sum of successful transaction of the platform account detail instruction, and naming the inconsistent record as an error type A4.
As can be seen from the above description, the present application provides a data collation method by dividing a host account detail and a platform account detail into a plurality of groups according to dates, respectively; sequencing the host account details and platform account details in each group according to the unique service detail identification fields; dividing the host account details and the platform account details in each sorted group into a plurality of data segments; and carrying out parallel check on the data segments corresponding to the host account details and platform account subdivision in each group, so that the system consumption can be reduced, the host pressure can be reduced, and the check efficiency and accuracy can be improved.
In a specific embodiment of the present application, referring to fig. 2, after step S104 of the data checking method, the method specifically further includes:
s105: starting a secondary rechecking operation according to the checking result;
and if the secondary check operation passes, the mark check passing mark, and if the secondary check operation does not pass, the mark check not passing mark.
In this embodiment, error data in the result of the verification is determined, the error data is subjected to secondary verification, a mark that passes the verification is set when the verification passes, and a mark that does not pass the verification is marked when the verification does not pass, so that the false alarm rate is reduced.
In a specific embodiment of the present application, referring to fig. 3, after step S104 of the data checking method, the method specifically further includes:
s106: and acquiring data corresponding to the mark which is marked as the mark which does not pass the verification, and transmitting the acquired data to a manual verification system.
In this embodiment, after traversing all the data of the check result, it is determined whether there is any check failed data, and the acquired data is sent to the manual check system to notify the manual intervention.
As can be seen from the above description, the present application provides a method for checking the money transfer accounts of the enterprise network bank, which reduces the system overhead, and improves the checking accuracy to reduce false alarm. The enterprise network bank transfer instruction data and the host account detail data are imported into the big data lake by batch operation, the data source is divided, multiple error types are checked in parallel, the checking efficiency is improved, the error data checked by the big data lake are imported into the enterprise network bank platform, and the accuracy of the error data is improved by secondary checking through batch operation. Therefore, the accounting checking method with high bank efficiency and accuracy is realized. Has the following effects and advantages:
first, reduce system consumption, reduce host pressure: the method adopts a batch operation lake entering method, reduces the pressure of calling a host interface by a platform, and reduces the system consumption of downloading files by the host ftp server.
And (II) the efficiency is high, and the expansibility is high: the method of the application is adopted in large data lake checking, the data sources are cut and segmented, the segmentation and parallel checking are carried out on various error types, the time cost is greatly reduced, the expandability is provided for other data sources, and other data sources entering the lake can also be checked by adopting the principle of the method.
And (III) the accuracy is high: false alarm data caused by a platform can be reduced through secondary rechecking, manual rechecking is reduced, checking accuracy is improved, and manual workload is reduced.
Fourth, the notification is high: the method can inform the manual intervention in real time after the secondary review, and reduces the acquisition result of manual active query.
In order to further explain the scheme, the application provides a full-flow embodiment of a data checking method, which specifically comprises the following steps:
the following detailed description is made with reference to the accompanying drawings:
fig. 4 is a general flow chart of a data collation method.
Step 1, starting from a host account list, according to the working date, leading out a service list unique identification field and a key service element field according to the unique identification ascending order to form a file, and leading in a data lake by batch operation;
step 2, registering mass data into a plurality of databases during enterprise online banking transfer, and partitioning according to date, so that the efficiency of inquiring data and exporting files is improved;
step 3, key business element fields such as a unique identification field channel event number, a receiver/payer account number and the like are parallelly exported into a file according to the bank reply time, and a plurality of batch operations parallelly import the enterprise network banking export reconciliation file into a data lake;
step 4, matching and checking the data of the two sides of the data source according to the unique identification field or the enterprise network banking channel event numbering rule by using multiple types of concurrent checks;
and step 5, according to the matching result, the data of the existence host account details of the enterprise network bank, the existence of the host account details of the enterprise network bank and the inconsistency of the related transaction elements, the existence of the total amount and the inconsistency of the total amount are led out to the enterprise network bank.
And 6, carrying out secondary check on error data by transferring money through the enterprise network banking, setting a check passing mark if the check passes, setting the check fail if the check fails, and reducing the false alarm rate.
Fig. 5 is a diagram of an enterprise banking transfer money transfer reconciliation.
Because the data quantity of the data sources on both sides is large, the piece-by-piece checking is quite inefficient, and each checking type sequentially performs checking, the time cost is large. In order to improve the checking efficiency and reduce the expenditure, because the two data are partitioned according to the date, the host account details of the T and T-1 days are searched according to the unique identification channel event number of the enterprise network bank and the bank reply time T, so that the searching range is reduced, and the efficiency is improved.
(1) Selecting a single-side data source with multiple data, uniformly dividing the single-side data source into a plurality of data segments { Qd1, qd2, & gt..A.. Qdn }, and distributing a starting position identifier Li to each segmented data segment, wherein the starting position set of the whole data source is { L1, L2,......... Ln };
(2) According to the association identification channel event number between the enterprise network bank and the host account detail data source, comparing the following types:
searching a host account detail data source from an enterprise network bank transfer instruction data source, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from an enterprise bank transfer instruction data source, searching whether the host account detail is recorded or not according to the event number and bank reply time of an enterprise bank channel transaction success instruction, and naming the data without record as an error type A2;
finding out the details of a host account on the T day according to the event numbering rule of the unique identification channel of the enterprise network bank, and reversely finding out whether a record exists in the T day instruction table; the data without record is named as an error type A3;
searching the account detail data of the host according to the event numbering rule of the unique identification channel of the enterprise bank, calculating whether the total sum of the T day and the total sum are consistent with the total sum and the total sum of the successful transaction of the enterprise bank instruction, and naming the inconsistent record as an error type A4;
(3) Concurrent searching of { L1, L2, & gt..Ln } section data is carried out on another side data source, and efficiency of piece-by-piece comparison is improved;
(4) And simultaneously concurrent search checks for error types { A1, A2, A3, A4} in each segment of small data sources { L1, L2, & gt.
(5) And checking account error data to be exported and importing the account error data into an enterprise network bank platform through batch operation, so that the enterprise network bank can analyze the correctness of transfer money and remittance transaction and funds.
Fig. 6 is a diagram of an enterprise network banking transfer money transfer secondary reconciliation.
Because the host account details of the enterprise network bank instructions on the T day are generated on the T-1 day due to the fact that the different system day tangent points are inconsistent, the situation that the host account details cannot be found by the enterprise network bank instructions on the T day can occur, the problem can be solved by inquiring the T-1 account details in the step 2 of fig. 5, but because the enterprise network bank does not enter the lake on the T day, the host account details cannot find the enterprise network bank instruction data on the T-1 day, and therefore secondary review is needed on the enterprise network bank platform side.
Step 1, after an error file is imported at the enterprise network bank side, starting a secondary rechecking operation;
step 2, taking batch daily error type A3 error type data of the database;
and step 3, traversing the command, searching whether the command exists in the enterprise bank transfer and remittance command through the key field, if so, checking the flag to pass, and if not, checking the flag bit to fail, thereby reducing manual checking.
And step 4, after traversing the complete data, judging whether the check failed data exist, and if so, sending a mail to notify manual intervention.
As can be seen from the above description, the data verification method provided by the embodiment of the application can reduce system consumption, reduce host pressure, and improve verification efficiency and accuracy.
An embodiment of the present application provides a specific implementation manner of a data collation apparatus capable of implementing all contents in the data collation method, referring to fig. 7, the data collation apparatus specifically includes:
a dividing unit 10 for dividing the host account details and the platform account details into a plurality of groups according to the date;
a sorting unit 20, configured to sort the host account details and the platform account details in each of the groups according to the service detail unique identifier fields;
a data segment unit 30, configured to divide the host account details and the platform account details in each of the sorted groups into a plurality of data segments;
a first checking unit 40, configured to perform parallel checking according to the data segments corresponding to the host account details and the platform account details in each of the groups.
Further, the method further comprises the following steps:
a second checking unit for starting a secondary checking operation according to the checking result;
and if the secondary check operation passes, the mark check passing mark, and if the secondary check operation does not pass, the mark check not passing mark.
Wherein, the checking includes:
searching a host account detail data source from the platform account detail, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from the platform account detail, searching whether the host account detail has records or not according to the event number of the enterprise platform account detail transaction success instruction and the bank reply time, and naming the data without records as an error type A2;
finding out the host account details of the reply time according to the platform account details unique identification channel event numbering rules, and reversely searching whether a record exists in the T day instruction table; the data without record is named as an error type A3;
and searching the host account detail data according to the platform account detail unique identification channel event numbering rule to calculate whether the total sum and the total sum of the reply time are consistent with the total sum and the total sum of successful transaction of the platform account detail instruction, and naming the inconsistent record as an error type A4.
Further, the method further comprises the following steps:
and the sending unit is used for acquiring the data corresponding to the mark marked as the mark which does not pass the verification and sending the acquired data to the manual verification system.
The embodiment of the data checking device provided by the application can be specifically used for executing the processing flow of the embodiment of the data checking method in the embodiment, and the functions of the embodiment of the data checking device are not repeated herein, and reference can be made to the detailed description of the embodiment of the method.
As can be seen from the above description, the data checking device provided by the embodiment of the present application divides the host account details and the platform account details into a plurality of groups according to the dates; sequencing the host account details and platform account details in each group according to the unique service detail identification fields; dividing the host account details and the platform account details in each sorted group into a plurality of data segments; and carrying out parallel check on the data segments corresponding to the host account details and platform account subdivision in each group, so that the system consumption can be reduced, the host pressure can be reduced, and the check efficiency and accuracy can be improved.
The application provides an embodiment of an electronic device for realizing all or part of contents in a fixed asset abnormality monitoring and reminding method, which specifically comprises the following contents:
a processor (processor), a memory (memory), a communication interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete communication with each other through the bus; the communication interface is used for realizing information transmission between related devices; the electronic device may be a desktop computer, a tablet computer, a mobile terminal, etc., and the embodiment is not limited thereto. In this embodiment, the electronic device may be implemented with reference to an embodiment for implementing the method for monitoring and reminding a fixed asset abnormality and an embodiment for implementing the device for monitoring and reminding a fixed asset abnormality, and the contents thereof are incorporated herein and are not repeated here.
Fig. 8 is a schematic block diagram of a system configuration of an electronic device 9600 according to an embodiment of the present application. As shown in fig. 8, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 8 is exemplary; other types of structures may also be used in addition to or in place of the structures to implement telecommunications functions or other functions.
In one embodiment, the fixed asset anomaly monitoring and alert functions may be integrated into the central processor 9100. The central processor 9100 may be configured to perform the following control:
dividing the host account details and the platform account details into a plurality of groups according to dates;
sequencing the host account details and platform account details in each group according to the unique service detail identification fields;
dividing the host account details and the platform account details in each sorted group into a plurality of data segments;
and carrying out parallel check on the data segments corresponding to the host account details and the platform account subdivision in each group.
As can be seen from the above description, the electronic device provided by the embodiment of the present application divides the host account details and the platform account details into a plurality of groups according to dates; sequencing the host account details and platform account details in each group according to the unique service detail identification fields; dividing the host account details and the platform account details in each sorted group into a plurality of data segments; and carrying out parallel check on the data segments corresponding to the host account details and platform account subdivision in each group, so that the system consumption can be reduced, the host pressure can be reduced, and the check efficiency and accuracy can be improved.
In another embodiment, the fixed asset anomaly monitoring and alert device may be configured separately from the central processor 9100, for example, the fixed asset anomaly monitoring and alert device may be configured as a chip connected to the central processor 9100, and the fixed asset anomaly monitoring and alert function is implemented under the control of the central processor.
As shown in fig. 8, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 need not include all of the components shown in fig. 8; in addition, the electronic device 9600 may further include components not shown in fig. 8, and reference may be made to the related art.
As shown in fig. 8, the central processor 9100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, which central processor 9100 receives inputs and controls the operation of the various components of the electronic device 9600.
The memory 9140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information about failure may be stored, and a program for executing the information may be stored. And the central processor 9100 can execute the program stored in the memory 9140 to realize information storage or processing, and the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, but not limited to, an LCD display.
The memory 9140 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), SIM card, etc. But also a memory which holds information even when powered down, can be selectively erased and provided with further data, an example of which is sometimes referred to as EPROM or the like. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 storing application programs and function programs or a flow for executing operations of the electronic device 9600 by the central processor 9100.
The memory 9140 may also include a data store 9143, the data store 9143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, address book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. A communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, as in the case of conventional mobile communication terminals.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, etc., may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and to receive audio input from the microphone 9132 to implement usual telecommunications functions. The audio processor 9130 can include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100 so that sound can be recorded locally through the microphone 9132 and sound stored locally can be played through the speaker 9131.
An embodiment of the present application also provides a computer-readable storage medium capable of implementing all the steps of the data collation method in the above embodiment, the computer-readable storage medium storing thereon a computer program which, when executed by a processor, implements all the steps of the data collation method in the above embodiment, for example, the processor implementing the steps of:
dividing the host account details and the platform account details into a plurality of groups according to dates;
sequencing the host account details and platform account details in each group according to the unique service detail identification fields;
dividing the host account details and the platform account details in each sorted group into a plurality of data segments;
and carrying out parallel check on the data segments corresponding to the host account details and the platform account subdivision in each group.
As can be seen from the above description, the computer-readable storage medium according to the embodiments of the present application divides the host account details and the platform account details into a plurality of groups according to dates, respectively; sequencing the host account details and platform account details in each group according to the unique service detail identification fields; dividing the host account details and the platform account details in each sorted group into a plurality of data segments; and carrying out parallel check on the data segments corresponding to the host account details and platform account subdivision in each group, so that the system consumption can be reduced, the host pressure can be reduced, and the check efficiency and accuracy can be improved.
Although the application provides method operational steps as described in the examples or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive labor. The order of steps recited in the embodiments is merely one way of performing the order of steps and does not represent a unique order of execution. When implemented by an actual device or client product, the instructions may be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment) as shown in the embodiments or figures.
It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, apparatus (system) or computer program product. Accordingly, the present specification embodiments may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. 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.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The present application is not limited to any single aspect, nor to any single embodiment, nor to any combination and/or permutation of these aspects and/or embodiments. Moreover, each aspect and/or embodiment of the application may be used alone or in combination with one or more other aspects and/or embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application, and are intended to be included within the scope of the appended claims and description.
Claims (8)
1. A data collation method, characterized by comprising:
dividing the host account details and the platform account details into a plurality of groups according to dates;
sequencing the host account details and platform account details in each group according to the unique service detail identification fields;
dividing the host account details and the platform account details in each sorted group into a plurality of data segments;
performing parallel check according to the data segments corresponding to the host account details and the platform account details in each group;
wherein the collation includes:
searching a host account detail data source from the platform account detail, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from the platform account detail, searching whether the host account detail has records or not according to the event number of the enterprise platform account detail transaction success instruction and the bank reply time, and naming the data without records as an error type A2;
finding out the host account details of the reply time according to the platform account details unique identification channel event numbering rules, and reversely searching whether a record exists in the T day instruction table; the data without record is named as an error type A3;
and searching the host account detail data according to the platform account detail unique identification channel event numbering rule to calculate whether the total sum and the total sum of the reply time are consistent with the total sum and the total sum of successful transaction of the platform account detail instruction, and naming the inconsistent record as an error type A4.
2. The data collation method according to claim 1, further comprising: starting a secondary rechecking operation according to the checking result;
and if the secondary check operation passes, the mark check passing mark, and if the secondary check operation does not pass, the mark check not passing mark.
3. The data collation method according to claim 1, further comprising:
and acquiring data corresponding to the mark which is marked as the mark which does not pass the verification, and transmitting the acquired data to a manual verification system.
4. A data collation apparatus, characterized by comprising:
the dividing unit divides the host account details and the platform account details into a plurality of groups according to the dates respectively;
the ordering unit is used for ordering the host account details and the platform account details in each group according to the unique service detail identification fields;
the data section unit is used for dividing the host account details and the platform account details in each sorted group into a plurality of data sections;
the first checking unit is used for performing parallel checking according to the data segments corresponding to the host account details and the platform account details in each group;
wherein the collation includes:
searching a host account detail data source from the platform account detail, and comparing whether the account number, the amount and the currency of a payee are consistent or not, wherein inconsistent data are named as error type A1;
searching a host account detail data source from the platform account detail, searching whether the host account detail has records or not according to the event number of the enterprise platform account detail transaction success instruction and the bank reply time, and naming the data without records as an error type A2;
finding out the host account details of the reply time according to the platform account details unique identification channel event numbering rules, and reversely searching whether a record exists in the T day instruction table; the data without record is named as an error type A3;
and searching the host account detail data according to the platform account detail unique identification channel event numbering rule to calculate whether the total sum and the total sum of the reply time are consistent with the total sum and the total sum of successful transaction of the platform account detail instruction, and naming the inconsistent record as an error type A4.
5. The data collation device according to claim 4, further comprising:
a second checking unit for starting a secondary checking operation according to the checking result;
and if the secondary check operation passes, the mark check passing mark, and if the secondary check operation does not pass, the mark check not passing mark.
6. The data collation device according to claim 4, further comprising:
and the sending unit is used for acquiring the data corresponding to the mark marked as the mark which does not pass the verification and sending the acquired data to the manual verification system.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the data collation method according to any one of claims 1 to 3 when the program is executed.
8. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the data collation method according to any one of claims 1 to 3.
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| CN112767122B (en) * | 2021-01-14 | 2024-10-29 | 中国工商银行股份有限公司 | Account checking method, device, computer system and storage medium |
| CN112801767B (en) * | 2021-01-22 | 2024-11-01 | 中信银行股份有限公司 | Accounting data processing method and device for newly added channel |
| CN113157787A (en) * | 2021-04-06 | 2021-07-23 | 中信百信银行股份有限公司 | Accounting processing method and device, electronic equipment and readable storage medium |
| CN113269554B (en) * | 2021-05-12 | 2022-11-18 | 河北幸福消费金融股份有限公司 | Data comparison method, system and storage medium |
| CN113342795B (en) * | 2021-06-23 | 2023-04-28 | 杭州米络星科技(集团)有限公司 | Data checking method and device in application program, electronic equipment and storage medium |
| CN113421153A (en) * | 2021-06-30 | 2021-09-21 | 中国工商银行股份有限公司 | Checking method and device for automatically checking machine account |
| CN113763166B (en) * | 2021-08-09 | 2024-08-06 | 中国银联股份有限公司 | A method and device for data verification |
| CN113837877B (en) * | 2021-08-10 | 2024-02-23 | 深圳市高腾科技服务有限公司 | Automatic check method, device, equipment and storage medium for transaction holding warehouse |
| CN115269708A (en) * | 2022-08-10 | 2022-11-01 | 中国工商银行股份有限公司 | Data reconciliation processing method and device |
| CN115545688A (en) * | 2022-09-22 | 2022-12-30 | 中国农业银行股份有限公司 | Accounting processing method and device |
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