A data processing method and device, electronic equipment and storage medium

Abstract

The application discloses a data processing method and device, electronic equipment and storage medium. In the application, after obtaining financial data to be processed, the financial data to be processed is processed to obtain derived data according to submission requirement information of data submission tasks performed by a plurality of regulatory submission applications. Then, the derived data is subjected to data verification processing based on data verification rules corresponding to the plurality of regulatory submission applications to obtain verification data. Finally, the verification data is subjected to grouping processing according to the submission requirement information corresponding to the plurality of regulatory submission applications to obtain a plurality of data groups, so that the plurality of regulatory submission applications read corresponding submission data from the corresponding data groups and submit the read submission data to a data regulatory platform. The scheme provided in the application avoids repeated processing and verification of financial data, and improves the management efficiency of the financial data.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of data processing, and particularly relates to a data processing method and device, an electronic device, and a storage medium. BACKGROUND

[0002] In the financial field, it is usually necessary to analyze the relevant data of the financial industry according to the data supervision requirements of different data supervision platforms. Among them, the supervision reporting application processes the relevant data of the financial institutions, and reports the processed data to the data supervision platform.

[0003] Figure 1 The architecture diagram of the data reporting system in the related art is shown, which comprises Figure 1 It can be seen that the existing data reporting system uses the original data and integrated data in the data warehouse, cloud data warehouse, and data lake as the data source. Different supervision reporting applications are in independent computing clusters, respectively reference the data tables required for performing the data reporting task, construct their own detail layer, derivative layer, and application layer, store in their own distributed database cluster, and calculate the application layer data of each computing cluster to serve the respective supervision reporting application system.

[0004] However, when the financial data corresponding to the financial institutions changes, for example, the data in the customer information system changes, each supervision reporting application needs to reprocess and analyze the data in the respective data table. In the data processing process, each supervision application uses the same data processing method to process the same data, which causes repeated processing of the same data, increases the data management cost, and reduces the data supervision efficiency. SUMMARY

[0005] The embodiments of the present application provide a data processing method, device, electronic device, and storage medium, which can avoid repeated processing and verification of financial data, and improve the management efficiency of financial data.

[0006] In a first aspect, the embodiments of the present application provide a data processing method, which comprises: acquiring financial data to be processed; performing data processing on the financial data to be processed according to reporting requirement information of a plurality of supervision reporting applications performing data reporting tasks, to obtain derivative data, wherein the plurality of supervision reporting applications are used to report reporting data corresponding to the reporting requirement information to a data supervision platform; performing data verification processing on the derivative data based on data verification rules corresponding to the plurality of supervision reporting applications, to obtain verification data; and performing grouping processing on the verification data according to the reporting requirement information corresponding to the plurality of supervision reporting applications, to obtain a plurality of data groups, so that the plurality of supervision reporting applications read corresponding reporting data from the corresponding data groups, and report the read reporting data to the data supervision platform.

[0007] In a second aspect, an embodiment of the present application provides a data processing apparatus, comprising: a data acquisition module configured to acquire financial data to be processed; a data processing module configured to perform data processing on the financial data to be processed according to submission requirement information of a plurality of regulatory submission applications performing data submission tasks, to obtain derived data, wherein the plurality of regulatory submission applications are configured to submit submission data corresponding to the submission requirement information to a data regulatory platform; a data verification module configured to perform data verification processing on the derived data based on data verification rules corresponding to the plurality of regulatory submission applications, to obtain verification data; and a data submission module configured to perform grouping processing on the verification data according to the submission requirement information corresponding to the plurality of regulatory submission applications, to obtain a plurality of data groups, so that the plurality of regulatory submission applications read corresponding submission data from corresponding data groups and submit the read submission data to the data regulatory platform.

[0008] In a third aspect, an embodiment of the present application provides an electronic device, comprising: a processor and a memory storing computer program instructions; and the processor executes the computer program instructions to implement the data processing method according to the first aspect.

[0009] In a fourth aspect, an embodiment of the present application provides a computer readable storage medium, which stores computer program instructions, and the computer program instructions are executed by a processor to implement the data processing method according to the first aspect.

[0010] In a fifth aspect, an embodiment of the present application provides a computer program product, and instructions in the computer program product are executed by a processor of an electronic device to cause the electronic device to perform the data processing method according to the first aspect.

[0011] From the above, in the present application, in the process of performing data submission tasks, the financial data to be processed is uniformly processed, and then the plurality of regulatory submission applications perform data submission, which does not require the plurality of regulatory submission applications to independently perform data processing, thereby avoiding the problem of low data processing efficiency caused by the plurality of regulatory submission applications repeatedly processing the same data in the same way in the related art, and improving the management efficiency of the financial data.

[0012] Moreover, in the present application, the financial data to be processed is also uniformly verified to improve the data quality and further ensure the quality of data regulation. Compared with the data verification performed by each data submission application in the related art, the scheme provided in the present application can also avoid the problem of low data verification efficiency caused by each data submission application repeatedly verifying the same data in the same way, and further improves the management efficiency of the financial data. BRIEF DESCRIPTION OF DRAWINGS

[0013] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly introduced. Those drawings can help the ordinary skilled in the art to obtain other drawings without any creative effort.

[0014] Figure 1 is an architecture diagram of a data reporting system in the related art;

[0015] Figure 2 is a flow diagram of a data processing method provided by an embodiment of the present application;

[0016] Figure 3 is a flow architecture diagram of a data processing method provided by an embodiment of the present application;

[0017] Figure 4 is a structural diagram of a data processing apparatus provided by another embodiment of the present application;

[0018] Figure 5 is a structural diagram of an electronic device provided by yet another embodiment of the present application. DETAILED DESCRIPTION

[0019] The features and exemplary embodiments of various aspects of the present application will be described in detail below, in order to make the purposes, technical solutions and advantages of the present application more clear and apparent, the present application will be further described in detail below with reference to the drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain the present application, but not to limit the present application. The present application can be implemented without some of these specific details by those skilled in the art. The following description of the embodiments is only to provide a better understanding of the present application by showing examples of the present application.

[0020] It should be noted that, in this paper, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or device. Without more limitations, the elements defined by the statement "include" do not exclude the presence of other identical elements in the process, method, article or device including the elements.

[0021] It should be noted that the acquisition, storage, use, processing and the like of data in the embodiments of the present application comply with the relevant provisions of national laws and regulations.

[0022] For ease of understanding, before the scheme provided by the present application is explained and described, the background of the scheme provided by the present application is first explained and described.

[0023] Figure 1 The architecture diagram of the data reporting system in the related art is shown, which is obtained by Figure 1 It can be seen that in the related art, each regulatory reporting application independently processes data and stores the processed data into the corresponding storage area, so that the repeatedly processed data is stored in different storage areas, and multiple storage of a piece of data may bring inconsistency of the caliber indicators, therefore, before reporting the data, the data of each regulatory reporting application needs to be manually verified, which undoubtedly increases the management cost of the data (including the time cost and labor cost of data processing) and reduces the efficiency of data management.

[0024] In addition, it can be seen that Figure 1 each regulatory reporting application uses the same data source, therefore, when a certain regulatory reporting application modifies part of the data in the data source, it may affect the data reporting of other regulatory reporting applications, for example, when the data in the customer information system changes, the data reporting of each regulatory reporting application will be affected, and each regulatory reporting application needs to analyze and modify the data acquisition logic respectively.

[0025] In addition, due to the phenomenon of multi-head docking between each regulatory reporting application, for a problem of an upstream transaction system, each regulatory reporting application solves the problem repeatedly, and may cause disturbance to the transaction system due to different requirements.

[0026] In order to solve the above problems in the related art, the embodiments of the present application provide a data processing method, device, electronic equipment and storage medium. First, the data processing method provided by the embodiments of the present application is introduced.

[0027] Figure 2 The flowchart of the data processing method provided by one embodiment of the present application is shown. As Figure 2 shown, the method comprises the following steps:

[0028] Step S201, acquiring financial data to be processed.

[0029] In step S201, the financial data to be processed can come from the data corresponding to different financial businesses of a financial institution, for example, the financial data to be processed can include data obtained by collecting credit card data of a customer, or can include data obtained by collecting loan data of a user.

[0030] It should be noted that, in order to facilitate subsequent data processing, in the present application, the financial data to be processed has a certain data format, for example, the financial data to be processed can be structured data (for example, a table).

[0031] In step S202, the financial data to be processed is processed according to the reporting requirement information of the plurality of regulatory reporting applications performing the data reporting task to obtain derived data.

[0032] In step S202, the plurality of regulatory reporting applications are used to report the reporting data corresponding to the reporting requirement information to the data supervision platform. As an example, the data supervision platform issues data reporting requirements to each regulatory reporting application, for example, the requirements of statistical management information, financial basic data reporting requirements, customer risk information reporting requirements, regulatory standardized data reporting requirements, payment and settlement compliance supervision data reporting requirements, real-time monitoring of fund flow reporting requirements, foreign exchange information reporting requirements, and fund cross-border payment and receipt information management requirements. After receiving the data reporting requirements, each regulatory reporting application reports the corresponding data to the data supervision platform, for example, the regulatory reporting application SMIS (Statistic Management Information System) reports the related data of statistical management information to the data supervision platform; the regulatory reporting application EAST (Examination and Analysis System Technology) reports the regulatory standardized data to the data supervision platform.

[0033] In addition, in the present application, the regulatory reporting application can include but is not limited to SMIS, EAST, 1104 engineering system, FSDMS (Financial Service Data Management System), CRSS (Customer Risk Statics System), RCPMIS (RMB Cross Border Payment & Receipt Management Information System), payment and settlement compliance supervision data system RIDPM, fund flow real-time monitoring system N-FSP, new examination and analysis system N-EAST.

[0034] As an example, in this application, the data supervision platform applies different submission requirements for each supervision submission, so in the process of processing the financial data to be processed, the submission requirement information corresponding to all supervision submissions can be merged and processed, and the repeated submission requirements can be removed, and then the financial data to be processed is uniformly processed according to the merged submission requirement information.

[0035] It is worth noting that in this application, the data is not processed by each supervision submission application respectively, but the financial data to be processed is uniformly processed according to the submission requirements corresponding to all supervision submission applications, and when the financial data to be processed changes, only the financial data to be processed needs to be uniformly processed, thereby avoiding the problem of repeated processing of data by each supervision submission application, and improving the efficiency of data processing.

[0036] In step S203, the derived data is subjected to data verification processing based on the data verification rules corresponding to the plurality of supervision submission applications, to obtain verification data.

[0037] In step S203, the verification data is data that meets the data verification rules. As an example, before verifying the derived data, the data verification rules corresponding to all supervision submission applications can be obtained, and the data verification rules can be merged to remove duplicate data verification rules; then the derived data is uniformly verified using the merged data verification rules, thereby obtaining the verification data.

[0038] It should be noted that in order to enable each supervision submission application to correctly report data, after the data to be processed is uniformly processed, the processed data (i.e. derived data) also needs to be uniformly verified. Compared with the way in the related art that each supervision submission application verifies data respectively, the present application can effectively avoid repeated verification of data, improve the efficiency of data verification, and further improve the efficiency of data management.

[0039] In step S204, the verification data is subjected to grouping processing according to the submission requirement information corresponding to the plurality of supervision submission applications, to obtain a plurality of data groups, so that the plurality of supervision submission applications read corresponding submission data from corresponding data groups, and report the read submission data to the data supervision platform.

[0040] In step S204, since the data groups are obtained by dividing the verification data according to the submission requirement information corresponding to each supervision submission application, the data in each data group is the data required by the corresponding supervision submission application to perform a data submission task. In the process of performing the data submission task, the supervision submission application only needs to report the data in the corresponding data group to the data supervision platform, without the need to process the data, thereby improving the efficiency of data submission.

[0041] Based on the scheme defined in steps S201 to S204, it can be known that, in the present application, during the execution of the data reporting task, unified data processing is performed on the financial data to be processed, and then multiple supervision reporting applications perform data reporting. This process does not require multiple supervision reporting applications to independently perform data processing, thereby avoiding the problem of low data processing efficiency caused by multiple supervision reporting applications repeatedly processing the same data in the same way in the related art, and improving the management efficiency of financial data.

[0042] Moreover, in the present application, the financial data to be processed is also uniformly verified to improve data quality and thus ensure the quality of data supervision. Compared with the data verification performed by each data reporting application in the related art, the scheme provided in the present application can also avoid the problem of low data verification efficiency caused by multiple supervision reporting applications repeatedly verifying the same data using the same verification rules, and further improves the management efficiency of financial data.

[0043] As an example, Figure 3 The architecture diagram of the data processing method provided in the present application is shown, and the following Figure 3 The steps of the method provided in the present application are explained and described.

[0044] From Figure 3 It can be known that, before data processing of the financial data, the financial data to be processed needs to be obtained. Specifically, in response to a data reporting instruction of a data supervision platform, financial data corresponding to multiple financial businesses of a target financial institution is collected, and structured financial data is extracted from the financial data corresponding to the multiple financial businesses, to obtain the financial data to be processed.

[0045] As an example, the financial businesses of the target financial institution can include but are not limited to Figure 3 The institution employee information management business, the financial accounting information management business, the credit process management business, the private customer business, the public customer business, the credit card business, the private deposit business, the private credit business, the public deposit business, the financial market business, and the public credit business.

[0046] By collecting financial data of different financial businesses, a data lake can be formed. The data in the data lake includes real-time data and batch data, wherein the real-time data and the batch data can include data in multiple formats, such as structured data (for example, a table), unstructured data (for example, a picture, a voice, and a video), and semi-structured data (for example, invoice information).

[0047] Generally, the structured data contains data required by the data supervision platform to perform data supervision, and therefore, in this application, after forming the data lake, the structured data is extracted from the real-time data and the batch data to obtain the financial data to be processed.

[0048] Further, as shown in Figure 3 After obtaining the financial data to be processed, the financial data to be processed is processed to obtain derivative data.

[0049] Specifically, the submission requirement information of the plurality of supervision submission applications performing the data submission task is processed to obtain the supervision submission requirement information of the plurality of supervision submission applications and the common submission requirement information, the financial data corresponding to the supervision submission requirement information of the plurality of supervision submission applications is extracted from the financial data to be processed to obtain target financial data, the target financial data is processed according to the supervision submission requirement information of the plurality of supervision submission applications to obtain supervision derivative data, the financial data to be processed is processed according to the common submission requirement information to obtain common derivative data, and the derivative data is generated based on the supervision derivative data and the common derivative data.

[0050] It should be noted that the common submission requirement information described above is used to represent data that needs to be submitted by the plurality of supervision submission applications when performing the data submission task, that is, the common submission requirement information is used to represent common data that needs to be submitted by the plurality of supervision submission applications; the supervision submission requirement information is used to represent data that needs to be independently submitted by each supervision submission application when performing the data submission task, and different supervision submission applications correspond to different supervision submission requirement information, that is, the supervision submission requirement information is used to represent characteristic data that needs to be submitted by each supervision submission application.

[0051] As an example, taking the data range of a field in a data table as an example, the field corresponds to 1000 data, wherein the supervision submission application A only submits 100 data, the supervision submission application B only submits 50 data, the supervision submission application C only submits 70 data, and there are 40 data in the intersection of all data submitted by the three supervision submission applications. After performing set union processing on all data submitted by the three supervision submission applications, 120 set union data is obtained, then the common derivative data is the data obtained by processing the 1000 data, and the supervision derivative data is the data obtained by processing the 120 set union data.

[0052] As another example, taking a data item in a data table as an example, the data item in the data table is a loan balance, the common derived data is the loan balance of all financial businesses aggregated (i.e., common processing) for use by all departments of the financial institution, and the regulatory derived data is the loan balance of part of the financial businesses filtered according to the reporting requirements of different regulatory reporting applications. Among them, for the regulatory derived data, the loan balance of the corresponding financial business is processed according to the reporting requirements of different regulatory reporting applications, thereby obtaining different loan balances, and these processed loan balances are also only used for data regulation.

[0053] In addition, it also needs to be explained that, as shown in Figure 3 The essence of the generation process of the derived data is actually the data integration process of the cloud data warehouse. Similar to the data lake, the integrated data mainly includes real-time integrated data and batch integrated data, and the integrated data mainly includes derived data and detailed data. The derived data mainly includes common derived data, regulatory derived data, financial accounting derived data, etc., and the detailed data mainly includes transaction flow information of each financial business.

[0054] In addition, in the present application, the integrated data can also include graph data, for example, data obtained by constructing a knowledge graph for a loan customer.

[0055] Further, in order to ensure that the processed derived data can meet the reporting requirements of each regulatory reporting application, after the financial data to be processed is processed to obtain derived data, the derived data also needs to be verified.

[0056] Specifically, a target data set is constructed based on the derived data, then the data verification rules corresponding to the plurality of regulatory reporting applications are merged to obtain a verification rule set, and data satisfying all verification rules contained in the verification rule set is obtained from the target data set to obtain verification data.

[0057] In one example, the target data set can be generated by means of data authorization. Specifically, after obtaining the derived data, the derived data is stored in a target database, and according to the reporting requirement information corresponding to the plurality of regulatory reporting applications, the data access authority of each regulatory reporting application to access the target database is determined, and then the derived data stored in the target database is extracted according to the data access authority corresponding to the plurality of regulatory reporting applications to obtain the target data set.

[0058] As an example, the target database can be a database capable of realizing cross-cluster access, wherein different regulatory reporting applications have different data access permissions to the target database, and the data access permission corresponding to the regulatory reporting application is determined by the reporting requirement information corresponding to the regulatory reporting application, for example, the RCPMIS can only access data related to cross-border business, and the RIDPM can only access data related to payment settlement compliance.

[0059] Further, after extracting data from the target database according to the access permission of the different regulatory reporting applications to the target database to obtain a target data set, the data in the target data set can be verified to determine whether the derivative data passes the corresponding verification rule.

[0060] To avoid repeated verification of data and improve the efficiency of data verification, in the present application, instead of each regulatory reporting application verifying the derivative data, the verification rules of each regulatory reporting application are summarized from a business perspective or a technical perspective, and repeated verification rules are removed to obtain a verification rule set, and then the verification rules in the verification rule set are used to uniformly verify the data in the target data set.

[0061] It should be noted that in the present application, for the same data item, a strict handling method can be used to verify the data item, for example, multiple verification rules related to the data item in all rules of all regulatory reporting applications are used, and when the data item meets the multiple verification rules, it is determined that the data item passes the verification; if the data item does not meet at least one of the multiple verification rules, it is determined that the data item does not pass the verification.

[0062] For data that does not pass the verification, in the present application, further processing can be performed on the data that does not pass the verification according to the verification level.

[0063] Specifically, when it is detected that there is abnormal data in the target data set, the target verification rule that is not met by the abnormal data is determined; in the case where the verification level of the target verification rule is the first level, the abnormal data is adjusted so that the adjusted abnormal data meets the target verification rule; in the case where the verification level of the target verification rule is the second level, it is determined that the derivative data verification fails, and the multiple data regulatory platforms are prohibited from reporting data.

[0064] Wherein, the abnormal data is data that does not meet at least one verification rule in the verification rule set, the verification level is used to represent the importance of the abnormal data to the data reporting task, and the verification level at least includes the first level and the second level, and the importance of the first level is lower than that of the second level.

[0065] That is, in the present application, when it is detected that certain data does not pass the verification rule, and the influence of the verification rule on data reporting is small, the data can be modified according to the verification rule that the data does not meet, so that the modified data meets the verification rule, and then the regulatory reporting application can report the modified data to the data supervision platform; and when the influence of the verification rule on data reporting is large, it is directly determined that the derived data verification fails, and the derived data is no longer reported.

[0066] Further, as shown in Figure 3 , after completing data verification, the verification data can be grouped according to the reporting requirement information of each regulatory reporting application, so as to obtain the data group corresponding to each regulatory reporting application, for example, the data group corresponding to 1104 in Figure 3 , the data group corresponding to SMIS, the data group corresponding to FSDMS, the data group corresponding to CRSS, the data group corresponding to EAST5.0, and the data group corresponding to the one-table pass-through source layer reporting data.

[0067] After obtaining the result data (i.e. data group) of the regulatory reporting application in Figure 3 , various data services can be provided to each regulatory reporting application through the data service layer based on the result data, for example, risk application service, regulatory application service, anti-fraud application service, API (Application Programming Interface) service, real-time stream processing service, batch processing service, interactive query service, etc.

[0068] In addition, as shown in Figure 3 , the result data of the regulatory reporting application can also be archived to form historical archive data and stored in the data lake.

[0069] Further, when receiving the regulatory reporting requirement sent by the data supervision platform, each regulatory reporting application can provide corresponding regulatory services to the data supervision platform. In addition, as shown in Figure 3 , in the data application layer, N-CS can provide credit information to the regulatory reporting platform, and RIDPM, N-FSP, FIMS, N-EAST, SMIS, RCPMIS, FSDMS, etc. provide information related to supervision to the data supervision platform.

[0070] In one example, the scheme provided in the present application can also implement quality management of data. Specifically, after obtaining data satisfying all verification rules included in the verification rule set from the target data set, verification data is obtained, and the quality level corresponding to the financial data to be processed is determined according to the data proportion of abnormal data in the financial data to be processed and / or the data amount of abnormal data; in the case where the quality level is lower than the preset quality level, the abnormal financial business corresponding to the abnormal data is obtained, and the optimization demand information of data optimization of the financial data corresponding to the abnormal financial business is determined; and the financial data corresponding to the abnormal financial business is optimized based on the optimization demand information.

[0071] As an example, in the present application, the verification rules of each regulatory reporting application can be collected, the verification rules of each regulatory reporting application can be rule-extracted, and the extracted verification rules can be converted into verification rules in the regulatory market to improve the quality management of the regulatory market. In addition, the rationality of the verification rule business scenario can be verified, which is converted and extracted as the quality requirement of the data in the upstream data source, and the quality optimization demand is generated; then, the upstream quality optimization situation is continuously tracked, and the management of data quality is realized through the closed loop of "verification data quality-extraction-rational business scenario-conversion of upstream data optimization demand-upstream data optimization supply" to improve the quality of regulatory data.

[0072] Based on the above description and in combination with Figure 4 It can be seen that, in the scheme provided in the present application, the data in the data lake, the data warehouse, the cloud warehouse, the integrated data or the integrated data in the data lake, the data warehouse and the cloud warehouse are used as the data source, and the data in each data source is continuously supplemented to well understand the detailed data, increase the management of derivative data, and form a unified target data set for supervision through the data authorization mode.

[0073] In terms of data expression, the scheme provided in the present application organizes data from the regulatory reporting requirements, divides the data according to business, and connects the in-line and standard in the financial field and the regulatory standard, so that the data expression is close to the regulatory semantics. The in-line standard is a data standard defined by the financial institution from the perspective of operation management, and different financial institutions have corresponding in-line standards; the regulatory standard is a data standard uniformly defined from the perspective of national supervision.

[0074] In terms of data supplement, since each regulatory reporting application performs data reporting tasks through the target data set, when the regulatory reporting application needs to supplement data in the target data set and / or the data source, only one supplement is needed, and other regulatory reporting applications can use the supplemented data.

[0075] In the aspect of data verification, the scheme provided by the application avoids the problems of repeated rule verification and repeated data processing by supporting the verification rules of the regulatory reporting application, refining the unified verification rules for the target data set.

[0076] In the aspect of reporting task support, the regulatory reporting application in the application can be various regulatory applications such as financial statistics, national financial basic data statistics, 1104, EAST, and one-table reporting required by various financial institutions and regulatory agencies.

[0077] As can be seen from the above description, the scheme provided by the application can solve the problem of inconsistent data storage and inconsistent processing of indicators caused by the scattered and independent data of various regulatory reporting applications in the related art. At the same time, the scheme provided by the application breaks the data barriers of the data reporting system of various regulatory reporting applications, establishes consistent regulatory bottom-level basic data sets and consistent regulatory quality management mechanisms, improves the transparency of financial regulation, ensures the consistency of comparable indicators or detailed data between different sets of regulatory reports provided to the same regulatory department and different regulatory departments, reduces the cost of data management, and improves the efficiency of data management.

[0078] The embodiment of the application also provides a data processing apparatus, as shown in Figure 5 The apparatus comprises a data acquisition module 401, a data processing module 402, a data verification module 403, and a data reporting module 404.

[0079] The data acquisition module 401 is configured to acquire financial data to be processed.

[0080] The data processing module 402 is configured to perform data processing on the financial data to be processed according to reporting requirement information of a plurality of regulatory reporting applications performing data reporting tasks, to obtain derived data, wherein the plurality of regulatory reporting applications are configured to report reporting data corresponding to the reporting requirement information to a data regulatory platform.

[0081] The data verification module 403 is configured to perform data verification processing on the derived data based on data verification rules corresponding to the plurality of regulatory reporting applications, to obtain verification data.

[0082] The data reporting module 404 is configured to perform grouping processing on the verification data according to the reporting requirement information corresponding to the plurality of regulatory reporting applications, to obtain a plurality of data groups, so that the plurality of regulatory reporting applications read corresponding reporting data from corresponding data groups and report the read reporting data to the data regulatory platform.

[0083] It can be learned that, in the present application, the financial data to be processed is uniformly processed in the process of performing the data reporting task, and then the plurality of regulatory reporting applications perform data reporting. This process does not require the plurality of regulatory reporting applications to independently perform data processing, thereby avoiding the problem of low data processing efficiency caused by the plurality of regulatory reporting applications repeatedly processing the same data in the same way in the related art, and improving the management efficiency of the financial data.

[0084] Moreover, in the present application, the financial data to be processed is also uniformly verified to improve the data quality and further ensure the quality of data supervision. Compared with the data verification performed by each data reporting application in the related art, the scheme provided by the present application can also avoid the problem of low data verification efficiency caused by the plurality of regulatory reporting applications repeatedly verifying the same data in the same way, and further improve the management efficiency of the financial data.

[0085] In one example, the data acquisition module is specifically configured to collect financial data corresponding to a plurality of financial businesses of a target financial institution in response to a data reporting instruction of the data supervision platform; and extract structured financial data from the financial data corresponding to the plurality of financial businesses to obtain financial data to be processed.

[0086] In one example, the data processing module is specifically configured to perform merging processing on reporting requirement information of the plurality of regulatory reporting applications performing the data reporting task to obtain regulatory reporting requirement information of the plurality of regulatory reporting applications and common reporting requirement information, wherein the common reporting requirement information is used to represent data that needs to be reported by the plurality of regulatory reporting applications when performing the data reporting task, the regulatory reporting requirement information is used to represent data that needs to be independently reported by each regulatory reporting application when performing the data reporting task, and different regulatory reporting applications correspond to different regulatory reporting requirement information; extract financial data corresponding to the regulatory reporting requirement information of the plurality of regulatory reporting applications from the financial data to be processed to obtain target financial data; perform data processing on the target financial data according to the regulatory reporting requirement information of the plurality of regulatory reporting applications to obtain regulatory derived data; perform data processing on the financial data to be processed according to the common reporting requirement information to obtain common derived data; and generate derived data based on the regulatory derived data and the common derived data.

[0087] In one example, the data verification module includes a data construction module, a rule merging module, and a first verification module. The data construction module is configured to construct a target data set based on the derived data. The rule merging module is configured to perform merging processing on data verification rules corresponding to the plurality of regulatory reporting applications to obtain a verification rule set. The first verification module is configured to obtain data satisfying all verification rules included in the verification rule set from the target data set to obtain verification data.

[0088] In one example, the data verification module is specifically configured to store the derived data into the target database; determine data access permissions of each regulatory reporting application to access the target database according to reporting requirement information corresponding to the plurality of regulatory reporting applications; and perform data extraction from the derived data stored in the target database according to the data access permissions corresponding to the plurality of regulatory reporting applications, to obtain the target data set.

[0089] In one example, the data processing apparatus further comprises a first determination module, a data adjustment module, and a second determination module. The first determination module is configured to determine a target verification rule that is not satisfied by abnormal data when it is detected that the target data set contains abnormal data, wherein the abnormal data is data that does not satisfy at least one verification rule in the verification rule set. The data adjustment module is configured to perform data adjustment on the abnormal data to make the adjusted abnormal data satisfy the target verification rule when the verification level of the target verification rule is a first level, wherein the verification level is used to represent the importance of the abnormal data to the data reporting task, and the verification level at least includes the first level and a second level, and the importance of the first level is lower than that of the second level. The second determination module is configured to determine that the derived data verification fails and prohibit the plurality of data regulatory platforms to report data when the verification level of the target verification rule is the second level.

[0090] In one example, the data processing apparatus further comprises a level determination module, a requirement determination module, and a data optimization module. The level determination module is configured to determine a quality level corresponding to the to-be-processed financial data according to a data proportion of the abnormal data in the to-be-processed financial data and / or a data amount of the abnormal data. The requirement determination module is configured to obtain an abnormal financial business corresponding to the abnormal data and determine optimization requirement information of performing data optimization on financial data corresponding to the abnormal financial business when the quality level is lower than a preset quality level. The data optimization module is configured to perform data optimization on the financial data corresponding to the abnormal financial business based on the optimization requirement information.

[0091] The data processing apparatus provided by the embodiments of the present application can implement each process implemented by the foregoing method embodiments, and thus details are not repeated here.

[0092] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is taken as an example, and in actual application, the above functions can be completed by different functional units and modules according to needs, that is, the internal structure of the device is divided into different functional units or modules to complete all or part of the above described functions. Each functional unit and module in the embodiment can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of software functional unit. In addition, the specific names of each functional unit and module are only for convenient distinction, and do not limit the protection scope of the present application. The specific working process of the unit and module in the above system can refer to the corresponding process in the foregoing method embodiment, and will not be repeated here.

[0093] Figure 5 A hardware structure schematic diagram of an electronic device provided by an embodiment of the present application is shown.

[0094] The electronic device can include a processor 501 and a memory 502 storing computer program instructions.

[0095] Specifically, the processor 501 can include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or can be configured as one or more integrated circuits that implement one or more embodiments of the present application.

[0096] The memory 502 can include a mass storage for data or instructions. By way of example and not limitation, the memory 502 can include a hard disk drive (HDD), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 502 can include removable or non-removable (or fixed) media. Where appropriate, the memory 502 can be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, the memory 502 is a non-volatile solid-state memory.

[0097] The memory can include read-only memory (ROM), random access memory (RAM), magnetic disk storage mediums devices, optical storage mediums devices, flash memory devices, electrical, optical, or other physical / tangible memory storage devices. Thus, generally, the memory includes one or more tangible (non-transitory) computer-readable storage mediums (e.g., memory devices) encoded with software that includes computer-executable instructions that, when executed (e.g., by one or more processors), are operable to perform the operations described with reference to the methods according to an aspect of the present disclosure.

[0098] The processor 501 implements any one of the data processing methods in the above-described embodiments by reading and executing computer program instructions stored in the memory 502.

[0099] In one example, the electronic device can further include a communication interface 503 and a bus 510. Wherein, as shown in the figure, the processor 501, the memory 502, the communication interface 503 are connected through the bus 510 and complete the communication between each other. ​

[0100] The communication interface 503 is mainly used to realize the communication between each module, device, unit and / or equipment in the embodiments of the present application.

[0101] The bus 510 includes hardware, software or both to couple components of the electronic device to each other. By way of example, and not limitation, the bus can include an accelerated graphics port (AGP) or other graphics bus, an enhanced industry standard architecture (EISA) bus, a front-side bus (FSB), a HyperTransport (HT) interconnect, an industry standard architecture (ISA) bus, an infiniband interconnect, a low pin count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standards association local (VLB) bus, or other suitable bus or combination of two or more of these. Where appropriate, the bus 510 can include one or more buses. Although the present application describes and illustrates a particular bus, the present application contemplates any suitable bus or interconnect.

[0102] In addition, in combination with the data processing method in the above-described embodiments, the present application can provide a computer-readable storage medium to implement. The computer-readable storage medium has computer program instructions stored thereon; the computer program instructions are executed by the processor to implement any one of the data processing methods in the above-described embodiments.

[0103] ​In addition, in combination with the data processing method in the above embodiments, the embodiments of the present application can provide a computer program product for implementation. The instructions in the computer program product are executed by the processor of the electronic device, so that the electronic device executes the data processing method as described in any of the above embodiments.

[0104] It should be noted that the present application is not limited to the specific configurations and processes described above and shown in the drawings. For the sake of brevity, detailed descriptions of well-known methods are omitted. In the above embodiments, several specific steps are described and shown as examples. However, the method processes of the present application are not limited to the specific steps described and shown, and those skilled in the art can make various changes, modifications and additions, or change the order of the steps, after understanding the spirit of the present application.

[0105] The functional modules shown in the structural block diagram described above can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application specific integrated circuit (ASIC), appropriate firmware, a plug-in, a functional card, etc. When implemented in software, the elements of the present application are program or code segments used to perform the required tasks. The program or code segments can be stored in a machine-readable medium or transmitted through a data signal carried in a carrier wave over a transmission medium or communication link. The "machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, optical fiber media, radio frequency (RF) links, etc. The code segments can be downloaded via a computer network such as the Internet, an intranet, etc.

[0106] It should also be noted that the exemplary embodiments mentioned in the present application describe some methods or systems based on a series of steps or devices. However, the present application is not limited to the order of the above steps, that is, the steps can be executed in the order mentioned in the embodiments, or in an order different from the embodiments, or several steps can be executed simultaneously.

[0107] The computer program instructions can also be loaded onto a computer, other programmable data processing apparatus, or other processing device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other processing device to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0108] The above only specifically describes the embodiments of the present application. For the convenience and brevity of description, the specific working processes of the above-described system, module and unit can refer to the corresponding processes in the foregoing method embodiments, which will not be described herein. It should be understood that the protection scope of the present application is not limited in this way. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed in the present application, and these modifications or replacements should be covered within the protection scope of the present application.

Claims

1. A data processing method, characterized by, The method comprises the following steps: obtaining financial data to be processed; performing data processing on the financial data to be processed according to the reporting requirement information of the plurality of regulatory reporting applications for performing data reporting tasks, to obtain derivative data, wherein the plurality of regulatory reporting applications are used for reporting reporting data corresponding to the reporting requirement information to a data supervision platform; constructing a target data set based on the derivative data; merging the data verification rules corresponding to the plurality of regulatory reporting applications to obtain a verification rule set; obtaining data satisfying all verification rules contained in the verification rule set from the target data set to obtain verification data; grouping the verification data according to the reporting requirement information of the plurality of regulatory reporting applications to obtain a plurality of data groups, so that the plurality of regulatory reporting applications read corresponding reporting data from the corresponding data groups and report the read reporting data to the data supervision platform; performing data processing on the financial data to be processed according to the reporting requirement information of the plurality of regulatory reporting applications for performing data reporting tasks to obtain derivative data, comprising: merging the reporting requirement information of the plurality of regulatory reporting applications for performing data reporting tasks to obtain regulatory reporting requirement information of the plurality of regulatory reporting applications and common reporting requirement information, wherein the common reporting requirement information is used to represent data that needs to be reported when the plurality of regulatory reporting applications perform data reporting tasks, and the regulatory reporting requirement information is used to represent data that needs to be independently reported when each regulatory reporting application performs data reporting tasks, and different regulatory reporting applications correspond to different regulatory reporting requirement information; extracting financial data corresponding to the regulatory reporting requirement information of the plurality of regulatory reporting applications from the financial data to be processed to obtain target financial data; performing data processing on the target financial data according to the regulatory reporting requirement information of the plurality of regulatory reporting applications to obtain regulatory derivative data; performing data processing on the financial data to be processed according to the common reporting requirement information to obtain common derivative data; generating the derivative data based on the regulatory derivative data and the common derivative data.

2. The method of claim 1, wherein, Obtaining financial data to be processed, comprising: in response to a data reporting instruction of the data supervision platform, collecting financial data corresponding to a plurality of financial businesses of a target financial institution; extracting structured financial data from the financial data corresponding to the plurality of financial businesses to obtain the financial data to be processed.

3. The method of claim 1, wherein, Constructing a target data set based on the derivative data, comprising: storing the derivative data in a target database; determining data access permissions of each regulatory reporting application accessing the target database according to the reporting requirement information corresponding to the plurality of regulatory reporting applications; performing data extraction from the derivative data stored in the target database according to the data access permissions corresponding to the plurality of regulatory reporting applications to obtain the target data set.

4. The method of claim 1, wherein, After obtaining the verification data by obtaining data satisfying all verification rules contained in the verification rule set from the target data set, the method further comprises: In response to detecting that there is abnormal data in the target data set, a target verification rule that is not satisfied by the abnormal data is determined, wherein the abnormal data is data that does not satisfy at least one verification rule in the verification rule set; In response to the verification level of the target verification rule being a first level, the abnormal data is adjusted so that the adjusted abnormal data satisfies the target verification rule, wherein the verification level is used to represent the importance of the abnormal data to a data reporting task, and the verification level includes at least the first level and a second level, and the importance of the first level is lower than that of the second level; In response to the verification level of the target verification rule being the second level, it is determined that the derived data verification fails, and the multiple data supervision platforms are prohibited from reporting data.

5. The method of claim 4, wherein, After obtaining data that satisfies all verification rules included in the verification rule set from the target data set, the method further includes: determining a quality level corresponding to the financial data to be processed according to a data proportion of the abnormal data in the financial data to be processed and / or a data amount of the abnormal data; in response to the quality level being lower than a preset quality level, obtaining an abnormal financial business corresponding to the abnormal data, and determining optimization demand information for data optimization of financial data corresponding to the abnormal financial business; performing data optimization on the financial data corresponding to the abnormal financial business based on the optimization demand information.

6. A data processing apparatus, characterized by, The method includes: a data acquisition module configured to acquire financial data to be processed; a data processing module configured to perform data processing on the financial data to be processed according to reporting demand information of a plurality of supervision reporting applications that perform a data reporting task, to obtain derived data, wherein the plurality of supervision reporting applications are configured to report reporting data corresponding to the reporting demand information to a data supervision platform; a data construction module configured to construct a target data set based on the derived data; a rule merging module configured to merge data verification rules corresponding to the plurality of supervision reporting applications to obtain a verification rule set; a first verification module configured to obtain data that satisfies all verification rules included in the verification rule set from the target data set to obtain verification data; a data reporting module configured to group the verification data according to the reporting demand information of the plurality of supervision reporting applications to obtain a plurality of data groups, so that the plurality of supervision reporting applications read corresponding reporting data from corresponding data groups and report the read reporting data to the data supervision platform; and a second verification module configured to determine a target verification rule that is not satisfied by the abnormal data in response to detecting that there is abnormal data in the target data set, wherein the abnormal data is data that does not satisfy at least one verification rule in the verification rule set; in response to the verification level of the target verification rule being a first level, the abnormal data is adjusted so that the adjusted abnormal data satisfies the target verification rule, wherein the verification level is used to represent the importance of the abnormal data to a data reporting task, and the verification level includes at least the first level and a second level, and the importance of the first level is lower than that of the second level; in response to the verification level of the target verification rule being the second level, it is determined that the derived data verification fails, and the multiple data supervision platforms are prohibited from reporting data. The data processing module is configured to: perform merging processing on submission requirement information of the data submission tasks executed by the plurality of regulatory submission applications to obtain regulatory submission requirement information of the plurality of regulatory submission applications and common submission requirement information, wherein the common submission requirement information is used to represent data that needs to be submitted by the plurality of regulatory submission applications when executing the data submission tasks, and the regulatory submission requirement information is used to represent data that needs to be independently submitted by each regulatory submission application when executing the data submission tasks, and different regulatory submission applications correspond to different regulatory submission requirement information; extract, from the to-be-processed financial data, financial data corresponding to the regulatory submission requirement information of the plurality of regulatory submission applications to obtain target financial data; perform data processing on the target financial data according to the regulatory submission requirement information of the plurality of regulatory submission applications to obtain regulatory derived data; perform data processing on the to-be-processed financial data according to the common submission requirement information to obtain common derived data; and generate the derived data based on the regulatory derived data and the common derived data.

7. An electronic device, comprising: The electronic device comprises a processor and a memory storing computer program instructions; The processor executes the computer program instructions to implement the data processing method according to any one of claims 1-5.

8. A computer-readable storage medium, characterized in that, The computer program instructions stored on the computer readable storage medium are executed by the processor to implement the data processing method according to any one of claims 1-5.

9. A computer program product, characterised in that, The instructions in the computer program product are executed by the processor of the electronic device to enable the electronic device to execute the data processing method according to any one of claims 1-5.

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