CN114840527A - Data processing method, device and computer readable storage medium - Google Patents
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Abstract
The application discloses a data processing method, a data processing device and a computer readable storage medium. Relates to the field of financial science and technology, wherein the method comprises the following steps: the method comprises the steps of obtaining account data to be checked, wherein the account data at least comprises a business scene mark, and the business scene mark is used for representing a business scene when the account data is generated; dividing the account data to be checked into at least one account set to be checked according to the business scene identification; performing multiple rounds of reconciliation on the accounting data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, wherein the first reconciliation result at least comprises abnormal data occurring in each round of reconciliation; and determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each set to be checked. The method and the device solve the technical problem that when a large amount of accounting data are checked, abnormal data positioning is inaccurate due to the fact that checking dimensions are too single.
Description
Technical Field
The present application relates to the field of financial technology, and in particular, to a data processing method, apparatus, and computer-readable storage medium.
Background
When the accounting system of the prior bank performs accounting, the accounting related applications need to be docked firstly, and then daily accounting data is accurately counted through accounting detailed files provided by the accounting related applications so as to accurately and quickly locate accounting problems.
In the prior art, an IBM (international business machines) host system is mainly used for performing account checking, a reference transaction detail is obtained by completely importing account checking detail files provided by various account-related applications into a database, and then transaction data and bill data in the reference transaction detail are read line by line and compared line by line, and finally abnormal account data is found out.
However, since the IBM host system performs the comparison according to one reconciliation dimension in the line-by-line comparison process, when the daily accounting data has a large data volume, the IBM host system has difficulty in accurately locating the abnormal accounting data in time, for example, determining the website or trader corresponding to the abnormal accounting data.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the application provides a data processing method, a data processing device and a computer-readable storage medium, which are used for at least solving the technical problem of inaccurate positioning of abnormal data caused by single account checking dimension when a large amount of account data is checked.
According to an aspect of an embodiment of the present application, there is provided a data processing method, including: the method comprises the steps of obtaining account data to be checked, wherein the account data at least comprises a business scene mark, and the business scene mark is used for representing a business scene when the account data is generated; dividing the account data to be checked into at least one account set to be checked according to the business scene identification; performing multiple rounds of reconciliation on the accounting data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, wherein the first reconciliation result at least comprises abnormal data occurring in each round of reconciliation; and determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each set to be checked.
Further, the data processing method further comprises: the financial data to be checked at least comprises a plurality of transaction data and a plurality of bill data, and each transaction data and each bill data at least comprises a business scene identifier; each account to be checked set comprises at least one piece of transaction data and at least one piece of bill data, and the service scene identification of the at least one piece of transaction data is the same as the service scene identification of the at least one piece of bill data.
Further, the data processing method further comprises: before dividing account data to be checked into at least one account set to be checked according to business scene identification, at least one data storage table is pre-created in a distributed system according to the business scene identification, wherein each data storage table corresponds to one business scene identification.
Further, the data processing method further comprises: storing each transaction data and each bill data into a corresponding data storage table according to the service scene identification; and determining the transaction data and the bill data in each data storage table as a to-be-checked set so as to obtain at least one to-be-checked set.
Further, the data processing method further comprises: after the accounting data to be checked is divided into at least one accounting set to be checked according to the business scene identification, parallel accounting processing is carried out on the at least one accounting set to be checked based on a parallel processing mechanism of the distributed system, and a first accounting result corresponding to each accounting set to be checked is obtained.
Further, the data processing method further comprises: checking at least one piece of transaction data and at least one piece of bill data according to the first checking dimension to obtain first transaction data and first bill data which are successfully checked, and second transaction data and second bill data which are unsuccessfully checked; checking the second transaction data and the second bill data according to a second checking dimension to obtain third transaction data and third bill data which are successfully checked, and fourth transaction data and fourth bill data which are failed to be checked, wherein the checking precision of the first checking dimension is greater than that of the second checking dimension; generating a first reconciliation result based on the second transaction data, the second billing data, the fourth transaction data, and the fourth billing data.
Further, the data processing method further comprises: determining second transaction data and second bill data as first abnormal data occurring in the first wheel account checking process; determining that the fourth transaction data and the fourth bill data are second abnormal data occurring in the second wheel account aligning process; and generating a first reconciliation result based on the first abnormal data and the second abnormal data.
Further, the data processing method further comprises: after the first transaction data and the first bill data which are successfully checked are obtained, deleting the first transaction data and the first bill data from the to-be-checked set; and after the third transaction data and the third bill data which are successfully checked are obtained, deleting the third transaction data and the third bill data from the to-be-checked set.
Further, the data processing method further comprises: and counting all first reconciliation results corresponding to at least one to-be-reconciled set to obtain a target reconciliation result, wherein the target reconciliation result at least comprises abnormal data, a service scene identifier corresponding to the abnormal data and a reconciliation dimension corresponding to the abnormal data.
According to another aspect of the embodiments of the present application, there is also provided a data processing apparatus, including: the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring the financial data to be verified, the financial data at least comprises a business scene identifier, and the business scene identifier is used for representing a business scene when the financial data is generated; the system comprises a dividing module, a checking module and a checking module, wherein the dividing module is used for dividing the financial data to be checked into at least one account set to be checked according to a business scene identifier; the reconciliation module is used for performing multiple rounds of reconciliation on the accounting data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, wherein the first reconciliation result at least comprises abnormal data generated in each round of reconciliation; and the determining module is used for determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each set to be checked.
According to another aspect of embodiments of the present application, there is also provided a computer-readable storage medium having a computer program stored therein, wherein the computer program is configured to execute the above-mentioned data processing method when running.
According to another aspect of embodiments of the present application, there is also provided an electronic device including one or more processors and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the data processing method described above.
In the embodiment of the application, a mode of performing multiple rounds of reconciliation according to different reconciliation dimensions on account data in each set to be reconciled is adopted, after the account data to be reconciled is acquired, the account data to be reconciled is divided into at least one set to be reconciled according to a business scene identifier, then multiple rounds of reconciliation are performed on the account data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, and finally a target reconciliation result corresponding to the account data to be reconciled is determined based on the first reconciliation result corresponding to each set to be reconciled. The accounting data at least comprises a business scene identifier, and the business scene identifier is used for representing a business scene when the accounting data is generated; the first reconciliation result at least comprises abnormal data which appears in each round of reconciliation.
According to the content, account data to be checked is divided into at least one account checking set to be checked according to the business scene identification, and multiple rounds of account checking are carried out according to different account checking dimensions aiming at the account data in each account checking set to be checked, so that in the account checking process, under the condition that the business scene of the account data is clear, each round of account checking is carried out according to different account checking dimensions, abnormal data appearing in each account checking dimension can be obtained, the purpose of positioning corresponding abnormal data in each account checking dimension and each business scene is further achieved, the effect of timely and accurately determining the account checking dimensions and the business scene corresponding to the abnormal data when the abnormal data appear is achieved, and the processing efficiency of workers on the abnormal data is improved.
Therefore, according to the technical scheme, the purpose of determining the abnormal account data according to different account checking dimensions is achieved, the technical effects of improving the positioning accuracy and the positioning efficiency of the abnormal data are achieved, and the technical problem that the abnormal data are inaccurate in positioning due to the fact that the account checking dimensions are too single when a large amount of account data are checked is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of an alternative data processing method according to an embodiment of the present application;
FIG. 2 is a schematic diagram of an alternative business scenario according to an embodiment of the present application;
FIG. 3 is a flow chart of an alternative data processing method according to an embodiment of the present application;
FIG. 4 is a flow chart of an alternative data processing method according to an embodiment of the present application;
FIG. 5 is a schematic diagram of an alternative data processing apparatus according to an embodiment of the present application;
FIG. 6 is a schematic diagram of an alternative electronic device according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present application without making any creative effort shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
In addition, it should be noted that the relevant information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for presentation, analyzed data, etc.) referred to in the present disclosure are information and data authorized by the user or sufficiently authorized by each party. For example, an interface is provided between the system and the relevant user or organization, before obtaining the relevant information, an obtaining request needs to be sent to the user or organization through the interface, and after receiving the consent information fed back by the user or organization, the relevant information is obtained.
Example 1
In accordance with an embodiment of the present application, there is provided a method embodiment of a data processing method, it should be noted that the steps illustrated in the flowchart of the figure may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than that herein.
In addition, it should be further noted that an accounting analysis system may be used as an execution subject of the data processing method in the embodiment of the present application.
Fig. 1 is a flow chart of an alternative data processing method according to an embodiment of the present application, as shown in fig. 1, the method includes the following steps:
step S101, acquiring account data to be checked.
In step S101, the accounting data at least includes a service scenario identifier, where the service scenario identifier is used to represent a service scenario when the accounting data is generated. The financial data to be checked at least comprises a plurality of transaction data and a plurality of bill data, and each transaction data and each bill data at least comprises a business scene identifier. As shown in fig. 2, the business scenario includes at least an equity business, a personal finance business, a bank card business, a financing business, and other businesses.
Additionally, the plurality of transaction data and the plurality of billing data may be from a plurality of reconciliation applications, for example, the transaction data may be sales transaction data provided by an e-commerce platform and the billing data may be transaction billing data provided by a bank. Specifically, the user a purchases a commodity in a certain e-commerce platform by using the bank card 1, the e-commerce platform generates a piece of sales transaction data 1 based on the transaction, and the card issuing bank of the bank card generates a piece of transaction bill data 1 for the transaction. In the abnormal case, the information on the sales transaction data 1 and the transaction bill data 1 should be matched, for example, the transaction amounts are identical. If the information does not match, it indicates that the sales transaction data 1 and the transaction bill data 1 are abnormal data.
Step S102, dividing the account data to be checked into at least one account checking set according to the business scene identification.
In step S102, the accounting analysis system divides the accounting data to be checked into a to-be-checked set according to the service scene identifier. For example, the accounting data to be checked includes three pieces of transaction data, which are transaction data 1, transaction data 2, and transaction data 3. Meanwhile, the account data to be checked further includes three bill data, which are respectively bill data 1, bill data 2 and bill data 3. On this basis, the business scene identifiers of the transaction data 1, the transaction data 2, the bill data 1 and the bill data 2 are identifiers of the public business, so that the accounting analysis system divides the transaction data 1, the transaction data 2, the bill data 2 and the bill data 1 into a to-be-checked set a, and corresponds to the business scene of the public business. And if the service scene identifications of the rest transaction data 3 and the rest bill data 3 are the identifications of the private service, the accounting analysis system divides the transaction data 3 and the bill data 3 into a to-be-reconciled set B, and the service scene of the private service is correspondingly set.
Therefore, the financial data to be checked is divided into at least one account set to be checked according to the business scene identification, so that the effect of dividing the financial data to be checked under the dimensionality of the business scene is realized, and the financial analysis system can timely and accurately acquire the business scene corresponding to the abnormal data when the abnormal data occurs in the follow-up process.
And S103, performing multiple rounds of reconciliation on the accounting data in each to-be-reconciled set according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each to-be-reconciled set.
In step S103, the first reconciliation result at least includes abnormal data occurring in each round of reconciliation. Wherein, in the account analysis system of this application, the reconciliation dimension has a plurality ofly, and is specific, and the reconciliation dimension includes: a trade search number, a trader code, an associated event number, a trade code, a website code, an area code, a currency code, and the like. In addition, different reconciliation dimensions have different checking accuracies, and according to a preset checking dimensionality range (namely checking accuracy) of the financial data, the financial analysis system can set a plurality of reconciliation dimensions to be A-Z gradients from high to low according to the checking accuracy, for example, the reconciliation dimension A is a transaction retrieval number, the reconciliation dimension B is a trader code, and the reconciliation dimension C is a website code, wherein the checking accuracy of the transaction retrieval number is higher than that of the trader code, and the checking accuracy of the trader code is higher than that of the website code. In the account checking process, the accounting analysis system firstly checks each transaction data and each bill data according to a transaction retrieval number, a first round of account checking and reconciliation is completed, if abnormal data with uneven borrowing appears in the first round of account checking, a second round of account checking and reconciliation is carried out on the abnormal data according to the reconciliation dimensionality of a trader code, if the abnormal data still appears in the second round of account checking, a third round of account checking and reconciliation is carried out on the abnormal data according to the reconciliation dimensionality of a website code until multiple rounds of account checking are completed, and a first account checking result corresponding to each account checking set to be checked is obtained.
It should be noted that when each round of reconciliation is performed according to different reconciliation dimensions, as long as abnormal data occurs, the accounting system records the reconciliation dimension corresponding to the abnormal data, so as to implement accurate positioning of the abnormal data, for example, determining a trader, a transaction search number or a website corresponding to the abnormal data.
And step S104, determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each set to be checked.
In step S104, after obtaining the first reconciliation result corresponding to each to-be-reconciled collection, the accounting analysis system may count all the first reconciliation results, thereby obtaining a target reconciliation result corresponding to the accounting data to be reconciled. The target account checking result at least comprises abnormal data occurring in the account checking process, account checking dimensions corresponding to the abnormal data and business scene identifications corresponding to the abnormal data.
Based on the contents of the above steps S101 to S104, in this embodiment of the application, a manner of performing multiple rounds of reconciliation on account data in each to-be-reconciled set according to different reconciliation dimensions is adopted, after the account data to be reconciled is obtained, the account data to be reconciled is divided into at least one to-be-reconciled set according to a service scene identifier, then, multiple rounds of reconciliation are performed on the account data in each to-be-reconciled set according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each to-be-reconciled set, and finally, a target reconciliation result corresponding to the to-be-reconciled account data is determined based on the first reconciliation result corresponding to each to-be-reconciled set. The financial data at least comprises a business scene identifier, and the business scene identifier is used for representing a business scene when the financial data is generated; the first reconciliation result at least comprises abnormal data which appears in each round of reconciliation.
According to the content, account data to be checked is divided into at least one account checking set to be checked according to the business scene identification, and multiple rounds of account checking are carried out according to different account checking dimensions aiming at the account data in each account checking set to be checked, so that in the account checking process, under the condition that the business scene of the account data is clear, each round of account checking is carried out according to different account checking dimensions, abnormal data appearing in each account checking dimension can be obtained, the purpose of positioning corresponding abnormal data in each account checking dimension and each business scene is further achieved, the effect of timely and accurately determining the account checking dimensions and the business scene corresponding to the abnormal data when the abnormal data appear is achieved, and the processing efficiency of workers on the abnormal data is improved.
Therefore, according to the technical scheme, the purpose of determining the abnormal account data according to different account checking dimensions is achieved, the technical effects of improving the positioning accuracy and the positioning efficiency of the abnormal data are achieved, and the technical problem that the abnormal data are inaccurate in positioning due to the fact that the account checking dimensions are too single when a large amount of account data are checked is solved.
In an optional embodiment, each account to be checked set includes at least one piece of transaction data and at least one piece of billing data, and the service scenario identifier of the at least one piece of transaction data is the same as the service scenario identifier of the at least one piece of billing data.
In an optional embodiment, before dividing the accounting data to be checked into at least one accounting set to be checked according to the service scene identifier, the accounting analysis system creates at least one data storage table in advance in the distributed system according to the service scene identifier, where each data storage table corresponds to one service scene identifier.
Optionally, the accounting analysis system at least includes a hadoop (hadoop) big data platform and a kafka message transmission system. The hadoop big data platform is a distributed system, and a worker can set a plurality of business scene identifications in the accounting analysis system in advance according to business relevance, so that the accounting analysis system creates a plurality of hadoop data storage tables in the hadoop big data platform according to the business scene identifications, and each hadoop data storage table corresponds to one business scene identification.
In an optional embodiment, according to the service scene identifier, the accounting analysis system first stores each piece of transaction data and each piece of billing data into a corresponding data storage table, and then determines the transaction data and the billing data in each data storage table as a to-be-checked set to obtain at least one to-be-checked set.
Optionally, the accounting analysis system may connect the accounting application and the hadoop big data platform through the kafka message transmission system, so that the accounting data is timely obtained from the multiple accounting applications by using the high efficiency of the kafka message transmission system in message transmission. Meanwhile, the accounting analysis system can also use the kafka message transmission system to preprocess the accounting data so that the accounting data enters the hadoop big data platform according to a uniform format, and then the preprocessed accounting data is persisted through the hadoop big data platform.
In addition, according to a partitioning mechanism of the hadoop big data platform, the accounting analysis system stores each transaction data and each bill data in the accounting data into a corresponding hadoop data storage table in real time according to the business scene identification, so that account checking sets of different business types are formed. For example, the business scene identifier of the transaction data 1 and the bill data 1 is an anti-public business, and the transaction data 1 and the bill data 1 are stored in the data storage table 1 according to the business scene identifier, wherein the data storage table 1 is created according to the business scene identifier of the anti-public business, and the data storage table 1 only stores the account data of the anti-public business.
It should be noted that, in the prior art, when performing accounting checking by using an IBM host system, because daily accounting data exists in a final-day file, the IBM host system first needs to convert the final-day file into a host file, then writes program logic using a host language, and finally performs data processing by the written program logic. When the data volume of daily account data is large, the process of converting the daily final file into the host file needs long conversion time, so that the problems that abnormal data cannot be found in time and the abnormal data cannot be located in time are caused. In addition, the IBM host system has huge use cost, the system construction and subsequent maintenance cost is too high, and the host language learning and use cost is also very high, so that the requirement of quick iteration cannot be met.
Compared with the prior art that data are transmitted through a daily end file, the kafka message transmission system with higher timeliness is used by introducing the hadoop big data platform and the kafka message transmission system, so that the limitation of file conversion is eliminated, the effect of real-time transmission is achieved, the timeliness of data transmission is improved, and the efficiency of financial monitoring and financial processing of a bank is improved.
In an optional embodiment, after the accounting data to be checked is divided into at least one accounting set to be checked according to the service scene identifier, parallel accounting processing is performed on the at least one accounting set to be checked based on a parallel processing mechanism of the distributed system, so as to obtain a first accounting result corresponding to each accounting set to be checked.
Optionally, when the accounting analysis system performs account checking on the accounting data in the to-be-checked set, the parallel account checking processing may be performed on each to-be-checked set by using the distributed processing capability of the hadoop big data platform. Compared with the serial account checking of the existing IBM host system, the account data checking method has the advantages that the business scene is subdivided, the concurrent processing capacity of the hadoop big data platform is adopted, and the account data under different business scenes are processed in parallel, so that abnormal data can be accurately positioned through multi-time and multi-batch debit and account checking, and the account processing capacity of a bank is improved.
In an optional embodiment, for the accounting data in each to-be-reconciled set, the accounting analysis system may perform multiple rounds of reconciliation according to different reconciliation dimensions, so as to obtain a first reconciliation result corresponding to each to-be-reconciled set. Specifically, the accounting analysis system checks at least one transaction data and at least one bill data according to a first checking dimension to obtain a first transaction data and a first bill data which are successfully checked, and a second transaction data and a second bill data which are unsuccessfully checked, and then the accounting analysis system checks the second transaction data and the second bill data according to a second checking dimension to obtain a third transaction data and a third bill data which are successfully checked, and a fourth transaction data and a fourth bill data which are unsuccessfully checked, wherein the checking accuracy of the first checking dimension is greater than that of the second checking dimension. Finally, the accounting analysis system generates a first reconciliation result based on the second transaction data, the second billing data, the fourth transaction data, and the fourth billing data.
Optionally, as shown in fig. 3, firstly, the accounting analysis system obtains the accounting data of the service type a, the accounting data of the service type B, and the accounting data of the service type C according to the service scene identifier, and then the kafka message transmission system stores the three types of accounting data into corresponding data storage tables in the hadoop big data platform, so as to form three sets to be reconciled. In the account checking process, the accounting analysis system firstly obtains at least one piece of transaction data and at least one piece of bill data from a data storage table according to a first account checking dimension of 'region + network point + currency + transaction retrieval number', associates the corresponding bill data and the transaction data according to the first account checking dimension, performs a first round of account checking and reconciliation on the debit and the credit, and stores abnormal data (namely, second transaction data and second bill data) with uneven debit and credit into a preset storage table D. And then the accounting analysis system acquires transaction data and bill data from a preset storage table D according to a second account checking dimension of 'region + network point + currency + associated event number', performs a second round of loan reconciliation according to the bill data and the transaction data corresponding to the second account checking dimension, and finally stores abnormal data (namely fourth transaction data and fourth bill data) with uneven loan into a preset storage table E.
It should be noted that, in fig. 3, a third round of reconciliation is also shown, that is, the accounting analysis system obtains data from the preset storage table E according to a third reconciliation dimension of "region + site + currency type + transaction code", and performs table-associated reconciliation according to the third reconciliation dimension, and performs a third round of reconciliation by loan and difference reconciliation, and after processing abnormal data with uneven loan, the abnormal data is pushed to the accounting monitoring system through the kafka message service system in real time, so that the accounting monitoring system pushes the abnormal data to the corresponding business processing personnel.
It can be seen that the first reconciliation dimension and the second reconciliation dimension in the present application are only an example illustration, so that the logic of performing multiple rounds of reconciliation with different reconciliation dimensions in the present application can be better understood by the skilled person. In fig. 3, since the checking accuracy of checking the account through the transaction search number is greater than the checking accuracy of checking the account through the associated event number, and the checking accuracy of checking the account through the associated event number is greater than the checking accuracy of checking the account through the transaction code, the checking accuracy in fig. 3 is sorted from high to low, and the checking accuracy is respectively a first reconciliation dimension, a second reconciliation dimension, and a third reconciliation dimension.
It should be noted that, compared with the prior art that account checking is performed only through one account checking dimension, in the account checking process in the application, under the condition that the service scene of the account data is made clear, account checking is performed for each round according to different account checking dimensions, so that abnormal data appearing in each account checking dimension can be obtained, the purpose of positioning corresponding abnormal data in each account checking dimension and each service scene is achieved, and the effect of timely and accurately determining the account checking dimension and the service scene corresponding to the abnormal data when the abnormal data appear is achieved.
In an optional embodiment, the accounting analysis system determines the second transaction data and the second billing data as first abnormal data occurring in the first wheel reconciliation process; and determining that the fourth transaction data and the fourth bill data are second abnormal data occurring in the second wheel reconciliation process, and finally generating a first reconciliation result based on the first abnormal data and the second abnormal data.
Optionally, in the reconciliation process, the accounting analysis system records abnormal data occurring in each round of reconciliation, and generates a first reconciliation result corresponding to each reconciliation set according to the abnormal data occurring in each round, so that when a worker needs to locate and trace the abnormal data, it can be determined in which reconciliation dimension the abnormal data occurs. For example, for the accounting data F, if reconciliation is performed in the reconciliation dimension of the associated event number, the accounting data F is absent of abnormal data, but if reconciliation is performed in the reconciliation dimension of the transaction search number, the accounting data F is present of abnormal data. On this basis, when special conditions such as checking false accounts occur, due to the fact that abnormal data in account checking under each account checking dimension are recorded in the accounting analysis system, account checking personnel can timely acquire the change information of the abnormal data under different account checking dimensions, and therefore whether special conditions such as checking false accounts exist is determined.
In an optional embodiment, after obtaining the first transaction data and the first bill data which are successfully checked, the accounting analysis system deletes the first transaction data and the first bill data from the to-be-reconciled set; after the third transaction data and the third bill data which are successfully checked are obtained, the accounting analysis system deletes the third transaction data and the third bill data from the to-be-checked set.
Optionally, in the reconciliation process of each wheel, the accounting analysis system deletes normal data balanced with loan from the reconciliation set to be checked, and the deleted data does not occupy the storage space of the distributed system any more, so that the storage space utilization rate of the distributed system is improved.
In an optional embodiment, the accounting analysis system counts all first reconciliation results corresponding to at least one to-be-reconciled set to obtain a target reconciliation result, where the target reconciliation result at least includes the abnormal data, the service scene identifier corresponding to the abnormal data, and the reconciliation dimension corresponding to the abnormal data.
Optionally, as shown in fig. 3, after obtaining the first reconciliation result corresponding to each to-be-reconciled set, the accounting analysis system performs statistics on the plurality of first reconciliation results, so as to obtain a target reconciliation result. Since each first reconciliation result is obtained based on different business scenarios, the abnormal data in the target reconciliation result can determine not only the corresponding reconciliation dimension but also the corresponding business scenario.
In an alternative embodiment, fig. 4 is a flowchart illustrating an alternative data processing method according to an embodiment of the present application, and as shown in fig. 4, a worker first sets a service type in an accounting analysis system according to service relevance or loan relations between services, and presets a service scenario identifier based on the service type. Then, the staff needs to preset a checking dimension range (i.e. checking accuracy) of the accounting data in the accounting analysis system, and a plurality of a-Z reconciliation dimensions are set successively from high to low according to the checking accuracy. And then the accounting analysis system acquires the accounting data of each account-related application in a fixed time period through the kafka message transmission system, and performs data persistence by using the capacity of the hadoop big data platform.
In addition, after obtaining the accounting data, the accounting analysis system divides the accounting data into a plurality of batches according to the relevance between the transaction data and the bill data, and then enters the first field check process. And performing a first round of debit and credit netting reconciliation on the transaction data and the bill data with the same service scene identification according to the reconciliation dimension A. And (4) continuing to perform a second round of differential borrowing and differential reconciliation according to the reconciliation dimension B on the abnormal data with uneven borrowing in the first round of differential borrowing and differential reconciliation, and deleting the normal data with balanced borrowing in the first round of differential borrowing and differential reconciliation from the hadoop big data platform. And determining the data which is still uneven after multi-round account checking through a plurality of account checking dimensions as the last abnormal data, and pushing the abnormal data occurring in the account checking process of each account in real time to an accounting monitoring system through a kafka message transmission system. The steps are carried out in parallel among the account data of different business scene identifications, and quasi-real-time account checking and abnormal data positioning are achieved.
Compared with the existing IBM host reconciliation system, the method has the advantages of obvious timeliness improvement, accurate abnormal accounting positioning and huge cost advantage. Compared with an IBM reconciliation system, the method and the system have the advantages that the kafka message transmission system with higher timeliness is used for transmitting data through the daily final file, the limitation of the file is eliminated, the real-time transmission timeliness is achieved, and the customer experience is greatly improved for the financial monitoring and financial processing of a bank. Finally, compared with the serial account checking of the IBMK account checking system, the method and the system subdivide the service types, carry out parallel processing of the account checking process through the concurrent processing capacity of the hadoop system, carry out loan-bound account checking in multiple batches through multiple fields, can accurately position abnormal data, and greatly improve the account processing capacity. And finally, compared with the huge cost of IBM construction and maintenance, the construction and maintenance cost of the hadoop big data platform is lower, and a large amount of operation cost can be saved for enterprises.
Example 2
The embodiment of the present application further provides a data processing apparatus, and it should be noted that the data processing apparatus according to the embodiment of the present application may be used to execute the data processing method according to embodiment 1 of the present application. The following describes a data processing apparatus according to an embodiment of the present application.
FIG. 5 is a schematic diagram of an alternative data processing apparatus according to an embodiment of the present application. As shown in fig. 5, the apparatus includes: an obtaining module 501, configured to obtain account data to be checked, where the account data at least includes a service scene identifier, and the service scene identifier is used to represent a service scene when the account data is generated; a dividing module 502, configured to divide the accounting data to be checked into at least one accounting set to be checked according to the service scene identifier; the reconciliation module 503 is configured to perform, for the accounting data in each to-be-reconciled set, multiple rounds of reconciliation according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each to-be-reconciled set, where the first reconciliation result at least includes abnormal data occurring during each round of reconciliation; the determining module 504 is configured to determine, based on the first reconciliation result corresponding to each to-be-reconciled set, a target reconciliation result corresponding to the accounting data to be reconciled.
Optionally, the financial data to be checked at least includes multiple pieces of transaction data and multiple pieces of bill data, and each piece of transaction data and each piece of bill data at least includes a service scene identifier; each account to be checked set comprises at least one piece of transaction data and at least one piece of bill data, and the service scene identification of the at least one piece of transaction data is the same as the service scene identification of the at least one piece of bill data.
Optionally, the data processing apparatus further includes: the creating module is used for creating at least one data storage table in advance in the distributed system according to the service scene identification, wherein each data storage table corresponds to one service scene identification.
Optionally, the dividing module further includes: the device comprises a storage module and a first determination module. The storage module is used for storing each piece of transaction data and each piece of bill data into a corresponding data storage table according to the service scene identification; the first determining module is used for determining the transaction data and the bill data in each data storage table into a to-be-checked set so as to obtain at least one to-be-checked set.
Optionally, the data processing apparatus further includes: and the parallel reconciliation processing module is used for carrying out parallel reconciliation processing on at least one to-be-reconciled set based on a parallel processing mechanism of the distributed system to obtain a first reconciliation result corresponding to each to-be-reconciled set.
Optionally, the reconciliation module further includes: the account checking device comprises a first account checking module, a second account checking module and a generating module. The first reconciliation module is used for reconciling at least one piece of transaction data and at least one piece of bill data according to the first reconciliation dimension to obtain successfully collated first transaction data and first bill data, and unsuccessfully collated second transaction data and second bill data; the second reconciliation module is used for reconciling the second transaction data and the second bill data according to a second reconciliation dimension to obtain third transaction data and third bill data which are successfully reconciled and fourth transaction data and fourth bill data which are unsuccessfully reconciled, wherein the reconciliation precision of the first reconciliation dimension is greater than that of the second reconciliation dimension; and the generating module is used for generating a first reconciliation result based on the second transaction data, the second bill data, the fourth transaction data and the fourth bill data.
Optionally, the generating module further includes: the device comprises a second determining module, a third determining module and a first generating module. The second determining module is used for determining that the second transaction data and the second bill data are first abnormal data occurring in the first wheel-to-bill process; the third determining module is used for determining that the fourth transaction data and the fourth bill data are second abnormal data occurring in the second wheel-to-bill process; and the first generation module is used for generating a first reconciliation result based on the first abnormal data and the second abnormal data.
Optionally, the data processing apparatus further includes: the device comprises a first deleting module and a second deleting module. The first deleting module is used for deleting the first transaction data and the first bill data from the to-be-checked set after the first transaction data and the first bill data which are successfully checked are obtained; and the second deleting module is used for deleting the third transaction data and the third bill data from the to-be-reconciled set after the third transaction data and the third bill data which are successfully verified are obtained.
Optionally, the determining module further includes: and the counting module is used for counting all first reconciliation results corresponding to at least one reconciliation set to be checked to obtain a target reconciliation result, wherein the target reconciliation result at least comprises abnormal data, a service scene identifier corresponding to the abnormal data and a reconciliation dimension corresponding to the abnormal data.
Example 3
According to another aspect of the embodiments of the present application, there is also provided a computer-readable storage medium, in which a computer program is stored, wherein the computer program is configured to execute the data processing method in embodiment 1 when running.
Example 4
According to another aspect of embodiments of the present application, there is also provided an electronic device including one or more processors and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the data processing method in embodiment 1 described above.
As shown in fig. 6, an embodiment of the present application provides an electronic device, where the device includes a processor, a memory, and a program stored in the memory and executable on the processor, and the processor executes the program to implement the following steps: the method comprises the steps of obtaining account data to be checked, wherein the account data at least comprises a business scene mark, and the business scene mark is used for representing a business scene when the account data is generated; dividing the account data to be checked into at least one account set to be checked according to the business scene identification; performing multiple rounds of reconciliation on the accounting data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, wherein the first reconciliation result at least comprises abnormal data occurring in each round of reconciliation; and determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each set to be checked.
Further, the processor executes the program to implement the following steps: the financial data to be checked at least comprises a plurality of transaction data and a plurality of bill data, and each transaction data and each bill data at least comprises a business scene identifier; each account to be checked set comprises at least one piece of transaction data and at least one piece of bill data, and the service scene identification of the at least one piece of transaction data is the same as the service scene identification of the at least one piece of bill data.
Further, the processor executes the program to implement the following steps: before dividing account data to be checked into at least one account set to be checked according to business scene identification, at least one data storage table is pre-created in a distributed system according to the business scene identification, wherein each data storage table corresponds to one business scene identification.
Further, the processor executes the program to implement the following steps: storing each transaction data and each bill data into a corresponding data storage table according to the service scene identification; and determining the transaction data and the bill data in each data storage table as a to-be-checked set so as to obtain at least one to-be-checked set.
Further, the processor executes the program to implement the following steps: after the accounting data to be checked is divided into at least one accounting set to be checked according to the service scene identification, parallel accounting processing is performed on the at least one accounting set to be checked based on a parallel processing mechanism of the distributed system, so that a first accounting result corresponding to each accounting set to be checked is obtained.
Further, the processor executes the program to implement the following steps: checking at least one piece of transaction data and at least one piece of bill data according to the first checking dimension to obtain first transaction data and first bill data which are successfully checked, and second transaction data and second bill data which are unsuccessfully checked; checking the second transaction data and the second bill data according to a second checking dimension to obtain third transaction data and third bill data which are successfully checked, and fourth transaction data and fourth bill data which are failed to be checked, wherein the checking precision of the first checking dimension is greater than that of the second checking dimension; generating a first reconciliation result based on the second transaction data, the second billing data, the fourth transaction data, and the fourth billing data.
Further, the processor executes the program to implement the following steps: determining second transaction data and second bill data as first abnormal data occurring in the first wheel account checking process; determining that the fourth transaction data and the fourth bill data are second abnormal data occurring in the second wheel account aligning process; and generating a first reconciliation result based on the first abnormal data and the second abnormal data.
Further, the processor executes the program to implement the following steps: after the first transaction data and the first bill data which are successfully checked are obtained, deleting the first transaction data and the first bill data from the to-be-checked set; and after the third transaction data and the third bill data which are successfully checked are obtained, deleting the third transaction data and the third bill data from the to-be-checked set.
Further, the processor executes the program to implement the following steps: and counting all first reconciliation results corresponding to at least one to-be-reconciled set to obtain a target reconciliation result, wherein the target reconciliation result at least comprises abnormal data, a service scene identifier corresponding to the abnormal data and a reconciliation dimension corresponding to the abnormal data.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit may be a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or may not be executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (12)
1. A data processing method, comprising:
the method comprises the steps of obtaining account data to be checked, wherein the account data at least comprises a business scene mark, and the business scene mark is used for representing a business scene when the account data is generated;
dividing the account data to be checked into at least one account checking set according to the business scene identification;
performing multiple rounds of reconciliation on the accounting data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, wherein the first reconciliation result at least comprises abnormal data occurring in each round of reconciliation;
and determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each reconciliation set to be checked.
2. The method of claim 1, wherein the accounting data to be checked comprises at least a plurality of transaction data and a plurality of billing data, each transaction data and each billing data comprising at least the business scenario identifier; each account to be checked set comprises at least one piece of transaction data and at least one piece of bill data, and the service scene identification of the at least one piece of transaction data is the same as the service scene identification of the at least one piece of bill data.
3. The method of claim 2, wherein before dividing the accounting data to be checked into at least one accounting set to be checked according to the business scenario identifier, the method further comprises:
and at least one data storage table is pre-created in the distributed system according to the service scene identification, wherein each data storage table corresponds to one service scene identification.
4. The method of claim 3, wherein dividing the accounting data to be checked into at least one accounting set to be checked according to the service scenario identifier comprises:
storing each piece of transaction data and each piece of bill data into a corresponding data storage table according to the service scene identification;
and determining the transaction data and the bill data in each data storage table as one to-be-checked set so as to obtain at least one to-be-checked set.
5. The method of claim 3, wherein after dividing the accounting data to be checked into at least one accounting set to be checked according to the business scenario identifier, the method further comprises:
and performing parallel reconciliation on at least one to-be-reconciled set based on a parallel processing mechanism of the distributed system to obtain a first reconciliation result corresponding to each to-be-reconciled set.
6. The method of claim 2, wherein performing multiple rounds of reconciliation on the accounting data in each to-be-reconciled set according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each to-be-reconciled set comprises:
checking the at least one piece of transaction data and the at least one piece of bill data according to a first checking dimension to obtain first transaction data and first bill data which are successfully checked, and second transaction data and second bill data which are failed to be checked;
checking the second transaction data and the second bill data according to a second checking dimension to obtain third transaction data and third bill data which are successfully checked, and fourth transaction data and fourth bill data which are failed to be checked, wherein the checking accuracy of the first checking dimension is greater than that of the second checking dimension;
generating the first reconciliation result based on the second transaction data, the second billing data, the fourth transaction data, and the fourth billing data.
7. The method of claim 6, wherein generating the first reconciliation result based on the second transaction data, the second billing data, the fourth transaction data, and the fourth billing data comprises:
determining the second transaction data and the second bill data as first abnormal data occurring in a first wheel-to-bill process;
determining that the fourth transaction data and the fourth bill data are second abnormal data occurring in a second wheel reconciliation process;
generating the first reconciliation result based on the first and second anomaly data.
8. The method of claim 6, further comprising:
after the first transaction data and the first bill data which are successfully checked are obtained, deleting the first transaction data and the first bill data from the to-be-checked set;
and after the third transaction data and the third bill data which are successfully checked are obtained, deleting the third transaction data and the third bill data from the to-be-checked set.
9. The method according to claim 1, wherein determining a target reconciliation result corresponding to the accounting data to be reconciled based on the first reconciliation result corresponding to each reconciliation set comprises:
and counting all first reconciliation results corresponding to at least one to-be-reconciled set to obtain the target reconciliation result, wherein the target reconciliation result at least comprises the abnormal data, the business scene identification corresponding to the abnormal data and the reconciliation dimension corresponding to the abnormal data.
10. A data processing apparatus, comprising:
the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring the financial data to be verified, the financial data at least comprises a business scene identifier, and the business scene identifier is used for representing a business scene when the financial data is generated;
the dividing module is used for dividing the financial data to be checked into at least one account checking set according to the business scene identification;
the reconciliation module is used for performing multiple rounds of reconciliation on the accounting data in each set to be reconciled according to different reconciliation dimensions to obtain a first reconciliation result corresponding to each set to be reconciled, wherein the first reconciliation result at least comprises abnormal data occurring in each round of reconciliation;
and the determining module is used for determining a target reconciliation result corresponding to the accounting data to be checked based on the first reconciliation result corresponding to each set to be checked.
11. A computer-readable storage medium, in which a computer program is stored, wherein the computer program is arranged to execute the data processing method of any one of claims 1 to 9 when executed.
12. An electronic device comprising one or more processors and memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data processing method of any one of claims 1 to 9.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115660659A (en) * | 2022-11-03 | 2023-01-31 | 五八畅生活(北京)信息技术有限公司 | Bill deduction method and device, electronic equipment and storage medium |
| CN116188190A (en) * | 2023-04-21 | 2023-05-30 | 梅州客商银行股份有限公司 | Multi-batch semi-real-time reconciliation method and system for high-concurrency payment system |
| CN116205614A (en) * | 2023-05-04 | 2023-06-02 | 无锡锡商银行股份有限公司 | Business reconciliation management system and method for distributed scene |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115660659A (en) * | 2022-11-03 | 2023-01-31 | 五八畅生活(北京)信息技术有限公司 | Bill deduction method and device, electronic equipment and storage medium |
| CN116188190A (en) * | 2023-04-21 | 2023-05-30 | 梅州客商银行股份有限公司 | Multi-batch semi-real-time reconciliation method and system for high-concurrency payment system |
| CN116205614A (en) * | 2023-05-04 | 2023-06-02 | 无锡锡商银行股份有限公司 | Business reconciliation management system and method for distributed scene |
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