A multi-source financial information data verification method, system, terminal and storage medium

Abstract

The present application provides a multi-source financial information data verification method, system, terminal and storage medium. The method includes: obtaining an index verification request; forwarding the index verification request to each data processing service corresponding to each data source, so that each data processing service generates a data extraction logic corresponding to each data source according to a preset data processing logic and the index verification request, and then extracts index data corresponding to the index verification request from each data source according to the data extraction logic; performing index comparison on each of the index data according to a preset comparison condition to generate an index comparison result, where the index comparison result includes an index list, whether the values of the same fields between each index data are consistent, an index similarity rate, the index data with comparison failures, and the data sources to which the index data with comparison failures belong, improving the accuracy and efficiency of data verification.

Description

Technical Field

[0001] The present application relates to the technical field of multi-source data processing, and particularly relates to a method, a system, a terminal and a storage medium for verifying multi-source financial information data. Background Art

[0002] In the development of financial operations, data from multiple data sources are often comprehensively applied. Financial industry information data comes from different data providers, with a wide range of sources, numerous indicators, and a large amount of data. There is a certain probability of defects in the indicator data provided by each data source, such as errors, omissions, and inconsistent standards. Therefore, it is necessary to verify the indicator data provided by each data source to ensure the accuracy and effectiveness of the data.

[0003] Currently, the common technical method for verifying indicator data is the sampling verification method, which extracts data of a certain time period of data indicators for manual or rule-based program verification. There are still some technical problems to be solved in this method: Firstly, the verification workload is large. If manual or rule-based program verification is used, it takes a lot of time to sort out the data from each source and various indicators, and the verification efficiency is low. Secondly, the dependence on verification experience is high. The process of rule sorting highly depends on financial business experience. When the staff has insufficient experience, the verification accuracy is not high, and at the same time, the verification efficiency will be further reduced. Summary of the Invention

[0004] In order to solve the above technical problems, the present application provides a method, a system, a terminal and a storage medium for verifying multi-source financial information data, so as to improve the accuracy and efficiency of data verification.

[0005] In a first aspect, an embodiment of the present application provides a method for verifying multi-source financial information data, including:

[0006] Obtaining an indicator verification request, where the indicator verification request includes an indicator name, a data fetching instruction corresponding to each data source, and a data fetching time;

[0007] Forwarding the indicator verification request to each data processing service corresponding to each data source, so that each data processing service generates a data fetching logic corresponding to each data source according to a preset data processing logic and the indicator verification request, and then extracts indicator data corresponding to the indicator verification request from each data source according to the data fetching logic;

[0008] According to preset comparison conditions, comparing the indicator data to generate an indicator comparison result, where the indicator comparison result includes an indicator list, whether the values of the same fields between each piece of indicator data are consistent, an indicator similarity rate, the indicator data with comparison failures, and the data sources to which the indicator data with comparison failures belong.

[0009] The embodiment of the present application provides a multi-source financial information data verification method. By forwarding the index verification request to each data processing service, each data processing service generates a data fetching logic corresponding to each data source, and then extracts index data with the same index name from different data sources respectively, and automatically verifies these index data. Compared with the prior art, the data verification method provided by the present application can be compatible with the index data of different data sources, can quickly verify the index data in each data source, and reduces the experience requirements for data verification personnel. At the same time, the present application sets data processing services specifically for each data source, ensuring the effective extraction of index data in each data source, and improving the data verification efficiency and accuracy.

[0010] Further, the index verification request is generated according to a preset unified index management table, and includes:

[0011] Obtain the index name to be verified;

[0012] Traverse the unified index management table according to the index name to determine the index row corresponding to the index name in the unified index management table. The unified index management table is constructed based on the index data in each data source and is updated in real time. The index row includes: index name, the code of the index in each data source, the data fetching instruction of the index in each data source, and the data source;

[0013] Generate an index verification request corresponding to the index name according to the index row.

[0014] In the embodiment of the present application, the index verification request is generated through a preset unified index management table. During each data verification process, the corresponding index row is located by retrieving from the unified index management table according to the index name to be verified, and the index name, the data fetching instruction of the index in each data source, and other parameters in the index row are assembled to generate the index verification request. The embodiment of the present application constructs the unified index management table based on the index data in each data source and updates it in real time, so that the corresponding index verification request can be quickly generated according to the unified index management table during each data verification process, realizing unified extraction and verification of each data source, and further improving the data verification efficiency and accuracy.

[0015] In a possible implementation manner, each data processing service generates a data fetching logic corresponding to each data source according to a preset data processing logic and the index verification request, including:

[0016] Determine the field name included in the data to be extracted, the message field assembly rule after data fetching, the consistency processing rule of the index data, and the corresponding data source access rule according to the preset data processing logic and the index verification request;

[0017] Combine the field names included in the data to be extracted, the message field assembly rules after data extraction, the consistency processing rules of the metric data, and the corresponding data source access rules to generate the data extraction logic corresponding to each data source.

[0018] In a possible implementation manner, each of the data processing services extracts the metric data corresponding to the metric verification request from each data source, including:

[0019] Extract the metric data corresponding to the metric verification request from the database type data source through the database processing service;

[0020] Extract the metric data corresponding to the metric verification request from the external interface request type data source through the external interface request processing service.

[0021] In the embodiment of the present application, each data source is further divided into a database type data source and an external interface request type data source, and the metric data in the database type data source is processed through the database processing service, and the metric data in the external interface request type data source is processed through the external interface request processing service. Classifying the data sources is beneficial to setting different data extraction instructions for different types of data sources. For example, database type data sources usually use SQL statements for data extraction, while external interface request type data sources usually need to construct a URL containing query parameters and then perform data extraction based on the HTTP GET method provided by the third-party interface. Therefore, in the embodiment of the present application, by separately setting the database processing service and the external interface request processing service for data extraction, the efficiency and accuracy of data extraction are further improved.

[0022] Further, when there are multiple database type data sources, each of the database type data sources regularly synchronizes its corresponding metric data to a preset multi-source database through a data synchronization tool, and the database processing service extracts and processes the metric data from the multi-source database.

[0023] In the embodiment of the present application, multiple database type data sources are first synchronously pre-stored in a preset multi-source database, so that the database processing service can directly extract the data of multiple data sources from the multi-source database, further improving the efficiency of data verification.

[0024] In a possible implementation manner, the metric comparison is performed on each of the metric data according to a preset comparison condition to generate a metric comparison result, including:

[0025] Obtain each of the metric data sent by each data processing service;

[0026] Compare whether the values of the same fields among the respective index data are consistent. If so, determine that the index similarity rate is 100%, and generate the corresponding index comparison result;

[0027] If there are inconsistent values in the same fields, determine the value with the largest proportion in each field as the reference value of the current field;

[0028] According to the reference values of each field, perform index comparison on each of the index data, and generate the corresponding index comparison result;

[0029] Display the index comparison result in a preset visualization platform.

[0030] Further, the performing index comparison on each of the index data according to the reference values of each field and generating the corresponding index comparison result includes:

[0031] Compare whether the values of each field among the respective index data are the reference values. When the value of a certain field in any first index data is not the reference value, determine that the first index data is the index data with comparison failure;

[0032] Determine the index similarity rate according to the number of index data with comparison failure, and further generate the corresponding index comparison result.

[0033] An embodiment of the present application provides a method for comparing index data. By comparing the field values of each index data, it is determined whether the index similarity rate of the current index is 100%. If so, the corresponding index comparison result can be directly generated, and there is no index data with comparison failure in the comparison result; if there are inconsistent values in the same fields, it is necessary to further determine the reference value of each field as the comparison basis, and then perform index comparison on each of the index data according to the reference values of each field, determine the index data with comparison failure from each index data, and display it as the comparison result. This enables the user to intuitively discover the index data with comparison failure and the data source to which the index data with comparison failure belongs from the comparison result, timely discover non-regular abnormal data and the corresponding data sources, and further improve the data verification efficiency and accuracy.

[0034] In a second aspect, the present application provides a multi-source financial information data verification system, including an acquisition module, a data extraction module, and an index comparison module;

[0035] Among them, the acquisition module is used to acquire an index verification request, and the index verification request includes an index name, a data extraction instruction corresponding to each data source, and a data extraction time;

[0036] The data extraction module is used to forward the index verification request to each data processing service corresponding to each data source, so that each data processing service generates a data extraction logic corresponding to each data source according to the preset data processing logic and the index verification request, and then extracts index data corresponding to the index verification request from each data source according to the data extraction logic;

[0037] The index comparison module is used to perform index comparison on each of the index data according to preset comparison conditions, and generate an index comparison result, where the index comparison result includes an index list, whether the values of the same fields between each index data are consistent, an index similarity rate, the index data with comparison failures, and the data sources to which the index data with comparison failures belong.

[0038] In a third aspect, the present application provides a terminal, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements any one of the multi-source financial information data verification methods described in the present application.

[0039] In a fourth aspect, the present application provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute any one of the multi-source financial information data verification methods described in the present application. Description of the Drawings

[0040] Figure 1 : It is a schematic flowchart of a multi-source financial information data verification method provided by an embodiment of the present application.

[0041] Figure 2 : It is a partial content schematic diagram of a unified index management table in a multi-source financial information data verification method provided by an embodiment of the present application.

[0042] Figure 3 : It is a schematic flowchart of specific steps of a multi-source financial information data verification method provided by an embodiment of the present application.

[0043] Figure 4 : It is a schematic diagram for displaying an index comparison result in a multi-source financial information data verification method provided by an embodiment of the present application.

[0044] Figure 5 : It is a schematic structural diagram of a multi-source financial information data verification system provided by an embodiment of the present application. Detailed Embodiments

[0045] Next, the technical solutions in the embodiments of the present application will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without making creative efforts shall fall within the protection scope of the present application.

[0046] It should be noted that the step numbers in the text are only for the convenience of explaining specific embodiments and do not serve to limit the execution order of the steps. In the description of the present application, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features.

[0047] Embodiment 1:

[0048] As Figure 1 shown, Embodiment 1 provides a multi-source financial information data verification method, including steps S1 - S3:

[0049] Step S1, obtain an index verification request, where the index verification request includes an index name, a data fetching instruction corresponding to each data source, and a data fetching time;

[0050] Step S2, forward the index verification request to each data processing service corresponding to each data source, so that each data processing service generates a data fetching logic corresponding to each data source according to a preset data processing logic and the index verification request, and then extracts index data corresponding to the index verification request from each data source according to the data fetching logic;

[0051] Step S3, perform index comparison on each of the index data according to a preset comparison condition to generate an index comparison result, where the index comparison result includes an index list, whether the values of the same fields between each index data are consistent, an index similarity rate, the index data with comparison failures, and the data sources to which the index data with comparison failures belong.

[0052] The embodiment of the present application provides a multi-source financial information data verification method. By forwarding the index verification request to each data processing service, each data processing service generates a data extraction logic corresponding to each data source, and then extracts index data with the same index name from different data sources respectively, and automatically verifies these index data. Compared with the prior art, the data verification method provided by the present application can be compatible with the index data of different data sources, can quickly verify the index data in each data source, and reduces the experience requirements for data verification personnel. At the same time, the present application sets data processing services for each data source specifically, ensuring the effective extraction of the index data in each data source, and improving the data verification efficiency and accuracy.

[0053] Further, the index verification request is generated according to a preset unified index management table, including:

[0054] Obtain the index name to be verified;

[0055] Traverse the unified index management table according to the index name to determine the index row corresponding to the index name in the unified index management table. Among them, the unified index management table is constructed based on the index data in each data source and is updated in real time. The index row includes: index name, the code of the index in each data source, the data extraction instruction of the index in each data source, and the data source;

[0056] Generate an index verification request corresponding to the index name according to the index row.

[0057] In the embodiment of the present application, the index verification request is generated through a preset unified index management table. During each data verification process, the corresponding index row is located by retrieving from the unified index management table according to the index name to be verified, and the index name, the data extraction instruction of the index in each data source, and other parameters in the index row are assembled to generate the index verification request. The embodiment of the present application constructs the unified index management table based on the index data in each data source and updates it in real time, so that the corresponding index verification request can be quickly generated according to the unified index management table during each data verification process, realizing the unified extraction and verification of each data source, and further improving the data verification efficiency and accuracy.

[0058] In a preferred embodiment, a unified index management table is managed and an index verification request is sent through a data index traffic interface management platform. The index verification request is forwarded to each data processing service through a DIFF index result comparison platform, and the index data returned by each data processing service is received and compared to generate an index comparison result. A partial content schematic diagram of the unified index management table is as Figure 2As shown in the figure, the first column is the indicator name, the second and third columns are the codes of the indicator in different data sources, the fourth and fifth columns are the data extraction instructions for the indicator, and the sixth column is the data source of the indicator. To further improve the data extraction efficiency, the data indicator traffic interface management platform can pre-traverse the unified indicator management table during idle periods. For each indicator row, an indicator interface request body corresponding to the indicator row is generated, and the content of the indicator interface request body is the same as that of the indicator verification request. When it is necessary to perform indicator data verification on a certain indicator, the corresponding indicator interface request body can be directly searched according to the name of the indicator to be verified, and then the indicator interface request body is packaged into an indicator verification request and forwarded to each data processing service. Taking the indicator name "Taiwan, China: Import and Export Amount: Month-on-Month Year-on-Year" as an example, when it is necessary to perform indicator data verification on the "Taiwan, China: Import and Export Amount: Month-on-Month Year-on-Year" indicator, the corresponding indicator interface request body is found from the pre-generated multiple indicator interface request bodies according to the indicator name. The interface request body may contain the following content:

[0059] Indicator Name: Taiwan, China: Import and Export Amount: Month-on-Month Year-on-Year

[0060] SQL for data extraction from Data Source A (sql_wind): SELECT TDATE, INDICATOR_NUM FROM YFDJJEDB where f2_4112 in (‘wind_code’) and tdate >= (‘start_date’)

[0061] Data extraction logic for third-party interface (GET_ifind): Assume that the third-party interface provides an HTTP GET method to obtain indicator data. We need to construct an appropriate URL and include the necessary query parameters. For example: {ifind_url} / api / v1 / economic-indicators?indicatorName=Taiwan, China: Import and Export Amount: Month-on-Month Year-on-Year&startDate=(‘start_date’)&ifindCode=(‘ifindID’)

[0062] Other parameters: start date, wind_code, ifindID

[0063] The HTTP form of the interface request body is:

[0064] {

[0065] "indicatorName":"Taiwan, China: Import and Export Amount: Month-on-Month Year-on-Year",

[0066] “start_date”:”20170131”,

[0067] "windcode": "A1115114",

[0068] "ifindID": "M002888099",

[0069] "sql_wind": "SELECT TDATE,INDICATOR_NUM FROM YFDJJEDB where f2_4112in(‘wind_code’)and tdate>=(‘start_date’)",

[0070] "GET_ifind":

[0071] “http: / / ifind.com.cn / api / v1 / economic-indicators?indicatorName=(‘indicatorName’)&startDate=(‘start_date’)&ifindCode=(‘ifindID’)”

[0072] }

[0073] The data indicator traffic management platform can send single or multiple indicator verification requests according to requirements. When multiple indicator verification requests need to be sent, several indicator verification requests are sent to the DIFF indicator result comparison platform in a multi-threaded manner. The threads are independent of each other and do not affect each other. Therefore, the embodiments of this application can verify multiple indicators simultaneously, further improving the data verification efficiency.

[0074] In a possible implementation manner, each of the data processing services generates data fetching logics corresponding to each data source according to preset data processing logics and the indicator verification requests, including:

[0075] Determine the field names included in the data to be extracted, the message field assembly rules after data fetching, the consistency processing rules for indicator data, and the corresponding data source access rules according to the preset data processing logics and the indicator verification requests;

[0076] Combine the field names included in the data to be extracted, the message field assembly rules after data fetching, the consistency processing rules for indicator data, and the corresponding data source access rules to generate data fetching logics corresponding to each data source.

[0077] In a possible implementation manner, each of the data processing services extracts indicator data corresponding to the indicator verification requests from each data source according to the data fetching logics, including:

[0078] Extract the metric data corresponding to the metric verification request from the database - type data source through the database processing service;

[0079] Extract the metric data corresponding to the metric verification request from the external - interface - request - type data source through the external - interface - request processing service.

[0080] In addition, according to the data - source type, the type of data - processing service can be further extended.

[0081] In the embodiments of the present application, each data source is further divided into a database - type data source and an external - interface - request - type data source. The metric data in the database - type data source is processed by the database processing service, and the metric data in the external - interface - request - type data source is processed by the external - interface - request processing service. Classifying the data sources is beneficial for setting different data - extraction instructions for different types of data sources. For example, the database - type data source usually uses SQL statements for data extraction, while the external - interface - request - type data source usually needs to construct a URL containing query parameters and then perform data extraction based on the HTTP GET method provided by the third - party interface. Therefore, in the embodiments of the present application, by separately setting the database processing service and the external - interface - request processing service for data extraction, the efficiency and accuracy of data extraction are further improved.

[0082] Further, when there are multiple database - type data sources, each of the database - type data sources synchronizes its corresponding metric data to a preset multi - source database regularly through a data synchronization tool, and the database processing service extracts and processes the metric data from the multi - source database.

[0083] In the embodiments of the present application, multiple database - type data sources are synchronized to a preset multi - source database in advance, so that the database processing service can directly extract the data of multiple data sources from the multi - source database, further improving the efficiency of data verification.

[0084] In a preferred embodiment, as Figure 3As shown in the figure, a data metric traffic interface management platform, a DIFF metric result comparison platform, a database processing service A, a database processing service B, and a multi-source database are set up to implement the method described in this application. Among them, the database processing service A is used to extract and process data in the multi-source database, and the database processing service B is used to extract and process data in the external interface request type data source. The database processing services A and B process different parameters in the requests sent by the DIFF platform according to the preset logic, and assemble them into a data fetching logic to obtain metric data from the multi-source database, external service interfaces, etc. Among them, the multi-source database synchronizes the data in the data sources A and B to the multi-source database regularly through a data synchronization tool. The preset logic includes the fields required by this service; the field assembly rules of this service message; consistency processing for different forms of the same metric in different sources, such as: different units, different precisions, etc.; the data source rules that different database processing services need to process.

[0085] In a possible implementation manner, the step of performing metric comparison on each of the metric data according to the preset comparison conditions to generate a metric comparison result includes:

[0086] Obtain each metric data sent by each data processing service;

[0087] Compare whether the values of the same fields between each metric data are consistent. If they are consistent, determine that the metric identity rate is 100%, and generate the corresponding metric comparison result;

[0088] If there are inconsistent values in the same fields, determine the value with the largest proportion in each field as the reference value of the current field;

[0089] Perform metric comparison on each of the metric data according to the reference values of each field, and generate the corresponding metric comparison result;

[0090] Display the metric comparison result in a preset visualization platform.

[0091] Furthermore, the metric comparison platform for performing metric comparison has a certain noise reduction function, such as ignoring the dynamically responsive data, spaces, line breaks, and differences in letter cases in the interface to improve the comparison efficiency.

[0092] Furthermore, the step of performing metric comparison on each of the metric data according to the reference values of each field to generate the corresponding metric comparison result includes:

[0093] Compare whether the values of each field between each metric data are the reference values. When the value of a certain field in any first metric data is not the reference value, determine that the first metric data is the metric data that fails the comparison;

[0094] Determine the index similarity rate based on the quantity of the index data with comparison failure, and then generate the corresponding index comparison result.

[0095] In a preferred embodiment, the schematic diagram for displaying the index comparison result in the visualization platform is as Figure 4 shown. The visualization platform records the index verification results of each index. Among them, each index verification result protects all the field names of the index, the verification failure rate, and the verification error type, and further counts the specific index data with verification failure under each index.

[0096] The embodiment of the present application provides a method for comparing index data. By comparing the field values of each index data, it is determined whether the index similarity rate of the current index is 100%. If so, the corresponding index comparison result can be directly generated, and there is no index data with comparison failure in the comparison result; if there are inconsistent values of the same fields, it is necessary to further determine the reference value of each field as the basis for comparison, and then according to the reference value of each field, perform index comparison on each of the index data, determine the index data with comparison failure from each index data, and display it as the comparison result. This enables users to intuitively discover the index data with comparison failure and the data source to which the index data with comparison failure belongs from the comparison result, timely discover non-regular abnormal data and the corresponding data sources, and further improve the data verification efficiency and accuracy.

[0097] Embodiment Two:

[0098] As Figure 5 shown, Embodiment Two provides a multi-source financial information data verification system, including an acquisition module 10, a data extraction module 20, and an index comparison module 30;

[0099] Among them, the acquisition module is used to acquire an index verification request, and the index verification request includes an index name, a data fetching instruction corresponding to each data source, and a data fetching time;

[0100] The data extraction module is used to forward the index verification request to each data processing service corresponding to each data source, so that each data processing service generates a data fetching logic corresponding to each data source according to the preset data processing logic and the index verification request, and then extracts the index data corresponding to the index verification request from each data source according to the data fetching logic;

[0101] The index comparison module is used to perform index comparison on each of the index data according to the preset comparison conditions, and generate an index comparison result. The index comparison result includes an index list, whether the values of the same fields between each index data are consistent, the index similarity rate, the index data with comparison failure, and the data source to which the index data with comparison failure belongs.

[0102] An embodiment of the present application provides a multi-source financial information data verification system. By forwarding an index verification request to each data processing service, each data processing service generates a data extraction logic corresponding to each data source, and then extracts index data with the same index name from different data sources respectively, and automatically verifies these index data. Compared with the prior art, the data verification system provided by the present application can be compatible with the index data of different data sources, can quickly verify the index data in each data source, and reduces the experience requirements for data verification personnel. At the same time, the present application sets up data processing services for each data source specifically to ensure the effective extraction of the index data in each data source, and improves the data verification efficiency and accuracy.

[0103] The more detailed working principle and step flow of this embodiment can, but are not limited to, refer to the relevant records of Embodiment 1.

[0104] Embodiment 3:

[0105] Embodiment 3 provides a terminal, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements any one of the multi-source financial information data verification methods described in the present application.

[0106] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor, or the processor may also be any conventional processor, etc. The processor is the control center of the terminal, and connects various parts of the entire terminal through various interfaces and lines.

[0107] The memory can be used to store the computer program. By running or executing the computer program stored in the memory and invoking the data stored in the memory, the processor realizes various functions of the terminal. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory can include high-speed random access memory, and can also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, at least one magnetic disk storage device, flash memory device, or other volatile solid-state storage devices.

[0108] Embodiment 4:

[0109] Embodiment 4 provides a computer-readable storage medium, which includes a stored computer program. When the computer program runs, it controls the device where the computer-readable storage medium is located to execute any one of the multi-source financial information data verification methods described in this application.

[0110] Among them, if the module integrated in the multi-source financial information data verification method is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the above embodiment methods of this application, it can also be completed by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0111] The specific embodiments described above further elaborate on the purpose, technical solutions, and beneficial effects of the present application. It should be understood that the above description is only for the specific embodiments of the present application and is not used to limit the protection scope of the present application. In particular, it is pointed out that for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A multi-source financial information data verification method, characterized in that: include: Obtain an indicator verification request, where the indicator verification request includes an indicator name, a data acquisition instruction corresponding to each data source, and a data acquisition time; The indicator verification request is generated according to a preset unified indicator management table, including: obtaining the name of the indicator to be verified; traversing the unified indicator management table according to the indicator name, and determining the indicator row corresponding to the indicator name in the unified indicator management table, wherein the unified indicator management table is constructed and obtained according to the indicator data in each of the data sources and updated in real time, and the indicator row includes: the indicator name, the code of the indicator in each data source, the data acquisition instruction of the indicator in each data source, and the data source; generating an indicator verification request corresponding to the indicator name according to the indicator row; Forwarding the indicator verification request to each data processing service corresponding to each data source, so that each data processing service generates a data acquisition logic corresponding to each data source according to a preset data processing logic and the indicator verification request, and then extracts the indicator data corresponding to the indicator verification request from each data source according to the data acquisition logic; According to the preset comparison conditions, each of the indicator data is compared to generate an indicator comparison result, which includes an indicator list, whether the values ​​of the same fields between the indicator data are consistent, the indicator similarity rate, the indicator data that failed to be compared, and the data source to which the indicator data that failed to be compared belongs.

2. A multi-source financial information data verification method as claimed in claim 1, characterized in that: Each data processing service generates data acquisition logic corresponding to each data source according to the preset data processing logic and the indicator verification request, including: Determine the field names contained in the data to be extracted, the message field assembly rules after data extraction, the consistency processing rules of the indicator data and the corresponding data source access rules according to the preset data processing logic and the indicator verification request; The field names contained in the data to be extracted, the message field assembly rules after data extraction, the consistency processing rules of the indicator data and the corresponding data source access rules are combined to generate data extraction logic corresponding to each data source.

3. A multi-source financial information data verification method as claimed in claim 1, characterized in that: The respective data processing services extract the indicator data corresponding to the indicator verification request from the respective data sources according to the data acquisition logic, including: Extracting the indicator data corresponding to the indicator verification request from the database data source through the database processing service; The indicator data corresponding to the indicator verification request is extracted from the external interface request class data source through the external interface request processing service.

4. A multi-source financial information data verification method as claimed in claim 3, characterized in that: When there are multiple database-type data sources, each of the database-type data sources periodically synchronizes its corresponding indicator data to a preset multi-source database through a data synchronization tool, and the database processing service extracts and processes the indicator data from the multi-source database.

5. A multi-source financial information data verification method as claimed in claim 1, characterized in that: The step of performing an indicator comparison on each of the indicator data according to the preset comparison conditions to generate an indicator comparison result includes: Get each indicator data sent by each data processing service; Compare the values ​​of the same fields between the indicator data to see if they are consistent, then determine that the indicator identical rate is 100%, and generate the corresponding indicator comparison result; If the values ​​of the same field are inconsistent, the value with the largest proportion in each field is determined as the benchmark value of the current field; According to the reference value of each field, the indicator data is compared to generate corresponding indicator comparison results; The indicator comparison results are displayed on a preset visualization platform.

6. A multi-source financial information data verification method as claimed in claim 5, characterized in that: The step of performing an indicator comparison on each of the indicator data according to the reference value of each field to generate a corresponding indicator comparison result includes: Comparing the values ​​of various fields between various indicator data to see whether they are reference values, and when a field value in any first indicator data is not the reference value, determining that the first indicator data is indicator data that has failed comparison; The indicator similarity rate is determined according to the number of indicator data that failed comparison, and then the corresponding indicator comparison results are generated.

7. A multi-source financial information data verification system, characterized in that: It includes acquisition module, data extraction module and indicator comparison module; The acquisition module is used to acquire an indicator verification request, wherein the indicator verification request includes an indicator name, a data acquisition instruction corresponding to each data source, and a data acquisition time; The indicator verification request is generated according to a preset unified indicator management table, including: obtaining the name of the indicator to be verified; traversing the unified indicator management table according to the indicator name, and determining the indicator row corresponding to the indicator name in the unified indicator management table, wherein the unified indicator management table is constructed and obtained according to the indicator data in each of the data sources and updated in real time, and the indicator row includes: the indicator name, the code of the indicator in each data source, the data acquisition instruction of the indicator in each data source, and the data source; generating an indicator verification request corresponding to the indicator name according to the indicator row; The data extraction module is used to forward the indicator verification request to each data processing service corresponding to each data source, so that each data processing service generates a data extraction logic corresponding to each data source according to the preset data processing logic and the indicator verification request, and then extracts the indicator data corresponding to the indicator verification request from each data source according to the data extraction logic; The indicator comparison module is used to perform indicator comparison on each of the indicator data according to preset comparison conditions to generate an indicator comparison result, wherein the indicator comparison result includes an indicator list, whether the values ​​of the same fields between the various indicator data are consistent, the indicator similarity rate, the indicator data that failed to be compared, and the data source to which the indicator data that failed to be compared belongs.

8. A terminal, characterized in that: It includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and when the processor executes the computer program, it implements a multi-source financial information data verification method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute a multi-source financial information data verification method as described in any one of claims 1 to 6.

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