Data verification method and device, equipment and storage medium

Abstract

The invention discloses a data verification method and device, equipment and a storage medium, and relates to the technical field of data processing, and the data verification method comprises the steps: obtaining target submitted data, matching the target submitted data with a preset verification rule configuration table, determining a verification rule list corresponding to the target submitted data, and sending the verification rule list to a server; and checking the target submitted data based on the checking rule list to generate a checking result table. The verification rule list corresponding to the target submitted data is matched by setting the preset verification rule configuration table, so that business personnel can centrally manage full verification rules only by simply configuring the preset verification rule configuration table, additional development is not needed, the rule change cost is greatly reduced, and the verification efficiency is improved. The change and deployment process is greatly simplified, so that maintenance and updating are facilitated, and the efficiency and flexibility of data verification are effectively improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a data verification method, device, equipment and storage medium. Background Art

[0002] At present, the general reporting data development process is that each upstream business team independently generates the data they are responsible for, while the downstream team is responsible for overall integration and external reporting. Among them, the data production methods of each upstream team are different. Some rely on online systems to generate data at the end of the day or in scheduled tasks, some use data warehouses for batch processing, and some combine the advantages of both to meet different reporting data requirements. Although the development strategies are different, all data must eventually be centrally integrated and released to the outside through the downstream team in the core data warehouse.

[0003] In order to ensure the quality of data reported to regulators, currently, verification rules are basically deployed after data is generated to check whether there are any anomalies in the data to be reported, and the data is finally reported after the verification is passed. However, this method has several significant disadvantages: first, each addition or modification of a verification rule requires corresponding program development, which consumes a lot of manpower and time; second, the verification rules lack effective management, and there is no unified platform to view and master the deployed verification rules; finally, as the number of verification rules increases, the complexity of the verification program increases sharply, and the maintenance difficulty increases. Summary of the invention

[0004] The main purpose of the present application is to provide a data verification method, device, equipment and storage medium, aiming to address the problems of large development workload and high management cost in existing solutions.

[0005] To achieve the above purpose, the present application proposes a data verification method, which includes:

[0006] Obtain target reporting data;

[0007] Matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data;

[0008] Based on the verification rule list, the target reported data is verified to generate a verification result table.

[0009] In one embodiment, matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data includes:

[0010] Determine the matching indexes of all first verification rules in the preset verification rule configuration table;

[0011] Matching the target reported data with the matching index of each of the first verification rules to determine a second verification rule corresponding to the target reported data;

[0012] The second verification rules are associated and combined to generate a verification rule list.

[0013] In one embodiment, the target reported data is verified based on the verification rule list to generate a verification result table, including:

[0014] Determine the rule importance scores and execution strategies of all second verification rules in the verification rule list based on the data features corresponding to the target reported data;

[0015] Sorting the rule importance scores of each of the second verification rules to obtain the execution priority of each of the second verification rules;

[0016] Based on the execution priority and execution strategy corresponding to each of the second verification rules, the target reported data is verified to generate a verification result table.

[0017] In one embodiment, after verifying the target submitted data based on the verification rule list and generating a verification result table, the method further includes:

[0018] Read the abnormal verification results in the verification result table, and block the verification and reporting process of the target reported data;

[0019] Obtain the warning responsible person corresponding to the abnormal verification result;

[0020] The abnormal verification result is pushed to the warning person in charge for verification by the warning person in charge.

[0021] In one embodiment, after reading the abnormal verification result in the verification result table, the method further includes:

[0022] Inputting the abnormal verification result into a verification rule generation model to obtain a third verification rule output by the verification rule generation model;

[0023] Verifying and evaluating the third verification rule to determine whether to add the third verification rule to the preset verification rule configuration table;

[0024] If not, a rule evaluation log is generated based on the third verification rule.

[0025] In one embodiment, the training process of the verification rule generation model includes:

[0026] Obtaining several groups of historical submission data and historical verification rules corresponding to each of the historical submission data;

[0027] Based on the preset data knowledge base, knowledge is injected into the initial verification rule generation model;

[0028] The historical reporting data and the historical verification rules are input into the initial verification rule generation model after knowledge injection for iterative training to obtain the verification rule generation model.

[0029] In one embodiment, after the abnormal verification result is pushed to the warning person in charge for verification by the warning person in charge, the method further includes:

[0030] Obtain the verification results of the warning responsible personnel;

[0031] If the verification and verification status is completed, the verification and reporting process of the target reported data is restored.

[0032] In addition, to achieve the above purpose, the present application also proposes a data verification device, the data verification device comprising:

[0033] The acquisition module is used to obtain the target reporting data;

[0034] A matching module, used to match the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data;

[0035] The verification module is used to verify the target reported data based on the verification rule list and generate a verification result table.

[0036] In addition, to achieve the above-mentioned purpose, the present application also proposes a data verification device, which includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the data verification method described above.

[0037] In addition, to achieve the above-mentioned purpose, the present application also proposes a storage medium, which is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by the processor, the steps of the data verification method described above are implemented.

[0038] In addition, to achieve the above-mentioned purpose, the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the steps of the data verification method described above are implemented.

[0039] The present application provides a data verification method, apparatus, device and storage medium. The data verification method obtains target reported data, matches the target reported data with a preset verification rule configuration table, determines a verification rule list corresponding to the target reported data, and then verifies the target reported data based on the verification rule list to generate a verification result table, so that business personnel can centrally manage all verification rules by simply configuring the preset verification rule configuration table, without the need for additional development, thereby greatly reducing the cost of rule changes, greatly simplifying the change and deployment process, thereby facilitating maintenance and updating, and effectively improving the efficiency and flexibility of data verification. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0041] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0042] Figure 1 A schematic diagram of a process flow provided for the first embodiment of the data verification method of this application;

[0043] Figure 2 A schematic diagram of a flow chart provided for the second embodiment of the data verification method of this application;

[0044] Figure 3 A flowchart of the third embodiment of the data verification method of this application is provided;

[0045] Figure 4 A flowchart of the fourth embodiment of the data verification method of the present application is provided;

[0046] Figure 5 This is a schematic diagram of the module structure of the data verification device according to an embodiment of the present application;

[0047] Figure 6 Schematic diagram of the device structure of the hardware operating environment involved in the data verification method in the embodiment of the present application.

[0048] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0049] It should be understood that the specific embodiments described herein are only used to explain the technical solutions of the present application and are not used to limit the present application.

[0050] In order to better understand the technical solution of the present application, a detailed description will be given below in conjunction with the accompanying drawings and specific implementation methods.

[0051] It should be noted that the execution subject of this embodiment can be a computing service device with data processing, network communication and program running functions, such as a tablet computer, a personal computer, a mobile phone, etc., or an electronic device capable of realizing the above functions, a big data service platform, a data verification system, etc. The following takes the data verification system as an example to illustrate this embodiment and the following embodiments.

[0052] Based on this, the present application embodiment provides a data verification method, referring to Figure 1 , Figure 1 A flowchart diagram of the first embodiment of the data verification method of the present application is provided.

[0053] In this embodiment, the data verification method includes steps S11 to S13:

[0054] Step S11, obtaining target reporting data;

[0055] It should be noted that the target reporting data refers to the data that the enterprise needs to report to the other party, including financial statements, transaction records, customer information, risk assessment reports, etc. There is no restriction here and it can be set according to actual conditions.

[0056] Step S12, matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data;

[0057] It should be noted that the preset verification rule configuration table refers to a database table or configuration file, which contains rules and standards for verifying the target reported data, such as data format, range, logical relationship, etc., wherein the preset verification rule configuration table can be based on the dimension of data block number + verification rule number to save the full amount of verification rules. Please refer to Table 1, which is the definition parameters of the preset verification rule configuration table in one embodiment. In addition, the user can enter specific verification data on the system, including the table name, field name, verification rule description, verification SQL and other related information that need to be verified. The core data warehouse will synchronize the full amount of verification rules into the preset verification rule configuration table within the preset time period, and perform subsequent unified data processing, so that there is no need to modify the batch running script of the data warehouse. You only need to enter the relevant information of the verification rule on the interface to automatically take effect, and perform subsequent automatic verification of data and early warning.

[0058] Table 1

[0059]

[0060]

[0061] It should be further explained that the verification rule list refers to a set of specific verification rules obtained by matching the data reported to a specific target according to a preset verification rule configuration table.

[0062] Specifically, the matching indexes of all first verification rules in the preset verification rule configuration table are determined, and then the target reported data is matched with the matching indexes of each of the first verification rules, and the second verification rule corresponding to the target reported data is determined, so as to associate and combine each of the second verification rules to generate a verification rule list.

[0063] Step S13, based on the verification rule list, verify the target reported data and generate a verification result table.

[0064] It should be noted that the verification result table refers to a database table or file that records the results of the verification operation, which is used to record the execution results of each verification rule in detail, including the rule name, execution status (pass or fail), failure reason, specific location of the error data, etc. Please refer to Table 2, which is the definition parameters of the verification result table in one embodiment.

[0065] Table 2

[0066]

[0067]

[0068] Specifically, based on the data features corresponding to the target reported data, the rule importance scores and execution strategies of all the second verification rules in the verification rule list are determined, and then the rule importance scores of each second verification rule are sorted to obtain the execution priority of each second verification rule, thereby verifying the target reported data based on the execution priority and execution strategy corresponding to each second verification rule to generate a verification result table.

[0069] This embodiment obtains the target reported data, and then matches the target reported data with a preset verification rule configuration table, determines a verification rule list corresponding to the target reported data, and then verifies the target reported data based on the verification rule list to generate a verification result table, so that business personnel can centrally manage all the verification rules by simply configuring the preset verification rule configuration table, without the need for additional development, thereby greatly reducing the cost of rule changes, greatly simplifying the change and deployment process, thereby facilitating maintenance and updates, and effectively improving the efficiency and flexibility of data verification.

[0070] Based on this, the present application embodiment provides a data verification method, referring to Figure 2, Figure 2 A flow chart of the second embodiment of the data verification method of the present application is provided.

[0071] In a feasible implementation manner, matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data includes:

[0072] Step S21, determining the matching indexes of all first verification rules in the preset verification rule configuration table;

[0073] It should be noted that the first verification rule refers to a verification rule in a set of all verification rules in a preset verification rule configuration table.

[0074] It should be further explained that the matching index is used to quickly find and match the identifier or key of the target reported data with the corresponding verification rule. The matching index can be a simple keyword, a complex query expression, or a set of field values ​​​​for locating specific rules, thereby optimizing the search process of verification rules, so that the system can quickly find the rules applicable to specific data from a large number of verification rules without having to compare each rule one by one.

[0075] Specifically, when creating the preset verification rule configuration table, the matching indexes of all first verification rules are simultaneously established.

[0076] Step S22, matching the target reported data with the matching index of each of the first verification rules to determine a second verification rule corresponding to the target reported data;

[0077] It should be noted that the second verification rule refers to the verification rule that complies with the target reported data.

[0078] Specifically, the target reported data is matched with the matching index of each of the first verification rules to determine the second verification rule corresponding to the target reported data. In addition, parallel processing technology can be used to distribute the rule matching tasks to multiple processors for simultaneous execution, thereby further improving the rule matching speed.

[0079] Step S23: associate and combine the second verification rules to generate a verification rule list.

[0080] This embodiment determines the matching indexes of all first verification rules in the preset verification rule configuration table, and then matches the target reported data with the matching indexes of each first verification rule, determines the second verification rule corresponding to the target reported data, and then associates and combines each second verification rule to generate a verification rule list, and then quickly locates the relevant verification rules through index matching, reducing unnecessary comparisons and calculations, thereby effectively improving matching efficiency and accuracy, reducing mismatches and missed matches, and thus reducing computing resource consumption. In addition, the index method allows the system to easily add new verification rules by simply updating the index without having to reconstruct the entire verification rule configuration table.

[0081] Based on this, the present application embodiment provides a data verification method, referring to Figure 3 , Figure 3 A flowchart diagram of the third embodiment of the data verification method of this application is provided.

[0082] In a feasible implementation manner, the target reported data is verified based on the verification rule list to generate a verification result table, including:

[0083] Step S31, determining the rule importance scores and execution strategies of all second verification rules in the verification rule list based on the data features corresponding to the target reported data;

[0084] It should be noted that the data characteristics refer to the attributes or characteristics that can be observed and measured in the target reported data, such as data type, data consistency, data format, and business-related characteristics (characteristics related to specific business logic, such as whether the transaction amount is consistent with the user's consumption habits), etc., which are not restricted here.

[0085] It should be further explained that the rule importance score refers to the score of each verification rule on the quality of the target reported data, compliance requirements, historical error frequency, etc. The execution strategy refers to the specific plan or method of how to execute the verification rules, including the timing of verification (such as verification when data enters the system, verification when data changes, regular batch verification, etc.) and verification method (automatic verification, triggered verification, etc.).

[0086] Specifically, by extracting features from the target reported data, key attributes such as data type, range, format, historical error rate, and business-related characteristics are identified, and then using data analysis techniques such as machine learning or statistical analysis to evaluate the correlation and historical performance between each second verification rule and data features, the importance score of each rule is determined, and the execution strategy of each second verification rule is read.

[0087] Step S32, sorting the rule importance scores of each of the second verification rules to obtain the execution priority of each of the second verification rules;

[0088] It should be noted that the execution priority refers to the order of execution of verification rules determined according to the rule importance score and other factors (such as business needs, compliance urgency, etc.), among which rules with higher priority will be executed first, so that the most important verification rules are processed first under limited resources.

[0089] Specifically, the rule importance scores of each of the second verification rules are sorted in reverse order to obtain the execution priority of each of the second verification rules.

[0090] Step S33: Based on the execution priority and execution strategy corresponding to each of the second verification rules, the target reported data is verified to generate a verification result table.

[0091] Specifically, the execution order of each of the second verification rules is determined according to the execution priority corresponding to each of the second verification rules, and then according to the execution strategy corresponding to the second verification rule, the target reported data is verified in the execution order to generate a verification result table.

[0092] This embodiment determines the rule importance scores and execution strategies of all the second verification rules in the verification rule list based on the data features corresponding to the target reported data, and then sorts the rule importance scores of each second verification rule to obtain the execution priority of each second verification rule, thereby verifying the target reported data based on the execution priority and execution strategy corresponding to each second verification rule, generating a verification result table, and then preferentially allocating resources to process the most important verification rules, thereby optimizing resource utilization efficiency, improving data processing speed, and thus improving the accuracy, effectiveness, flexibility and adaptability of verification.

[0093] Based on this, the present application embodiment provides a data verification method, referring to Figure 4 , Figure 4 A flowchart diagram of the fourth embodiment of the data verification method of this application is provided.

[0094] In a feasible implementation manner, after verifying the target reported data based on the verification rule list and generating a verification result table, the method further includes:

[0095] Step S41, reading the abnormal verification results in the verification result table, and blocking the verification and reporting process of the target reported data;

[0096] It should be noted that the verification abnormality result refers to the data items or data sets that do not conform to the preset verification rules after the target reported data is verified. This may be due to data errors, omissions, incorrect formats, violations of business logic or regulatory requirements, etc. The verification abnormality result usually includes the following information: the specific content of the abnormal data: which data items or records do not conform to the rules; the abnormality type: which type of verification rules the data does not conform to, such as format errors, range out of range, logical contradictions, etc.; the abnormal location: the specific location or identification of the data in the reported data set; the severity of the abnormality: the degree of impact of the abnormality on the data quality; the abnormality cause: the possible cause of the abnormality; the verification rule details: the specific content of the verification rule that triggers the abnormality, etc.

[0097] It should be further explained that the verification and reporting process refers to the entire workflow from data preparation, verification, exception handling to final data reporting.

[0098] Specifically, according to the preset abnormality standards, the verification result table is scanned to identify any data items that do not meet the regulations or trigger the verification rules. Once an abnormality is detected, the system will automatically mark the data and trigger the alarm mechanism, and then execute the preset blocking logic, such as modifying the status mark of the data reporting process, setting process control points, or directly intervening in the data flow to ensure that any abnormal data will not be further processed or reported.

[0099] Step S42, obtaining the warning responsible person corresponding to the abnormal verification result;

[0100] Specifically, the system reads the pre-configured warning responsible person information related to the target reporting data to perform message warning.

[0101] Step S43, pushing the abnormal verification result to the warning person in charge for verification by the warning person in charge.

[0102] Specifically, the abnormal verification result is pushed to the early warning person in charge for verification by the early warning person in charge. According to the numbers of the business person in charge and the development person in charge, their internal communication methods and mobile phone numbers are obtained, and then the abnormal verification result is pushed.

[0103] Furthermore, taking into account the difference between holidays and weekdays, using only internal communication tools may not be able to provide adequate notifications on holidays. Therefore, in addition to using internal communication tools to trigger relevant warning push notifications, the push method can also simultaneously notify through telephone, text messages, APP notifications, mini-programs, and public accounts to avoid omissions and improve the timeliness of verification.

[0104] This embodiment reads the abnormal verification result in the verification result table, blocks the verification and reporting process of the target reported data, and then obtains the warning responsible person corresponding to the abnormal verification result, and then pushes the abnormal verification result to the warning responsible person for verification by the warning responsible person, so as to respond to the abnormal data in a timely and rapid manner, reduce the impact of erroneous data on subsequent processes, and prevent erroneous data from being further processed or reported, thereby effectively improving the accuracy of data reporting and improving data verification efficiency.

[0105] In a feasible implementation manner, after reading the abnormal verification result in the verification result table, the method further includes:

[0106] Step S51, inputting the abnormal verification result into a verification rule generation model to obtain a third verification rule output by the verification rule generation model;

[0107] It should be noted that the verification rule generation model is used to identify abnormal patterns in data and create or update verification rules accordingly to improve the automation of data verification, reduce manual intervention, and improve the accuracy and adaptability of verification rules.

[0108] It should be further explained that the third verification rule refers to an updateable verification rule automatically created or recommended by the verification rule generation model based on the verification abnormality results, so as to capture data problems that were not previously covered by the existing verification rules, as well as optimize and supplement the existing rules.

[0109] Step S52, verifying and evaluating the third verification rule, and determining whether to add the third verification rule to the preset verification rule configuration table;

[0110] Specifically, in one embodiment, the third verification rule is applied to a set of historical data or test data sets to ensure its logical correctness and effectiveness, and then the data quality indicators before and after the rule application, such as error rate and outlier ratio, are compared to evaluate its actual impact on data quality. At the same time, it is necessary to check whether the new rules comply with business logic and regulatory requirements, as well as the impact on the existing data reporting process, including performance impact and potential interference with other verification rules, in order to identify the risks that may be caused by the introduction of new rules.

[0111] Furthermore, the results of comprehensive testing, effect evaluation, compliance check, impact analysis, and risk assessment are used to decide whether to add the third verification rule to the preset verification rule configuration table. If the rule is considered effective, compliant, and risk-controllable, it can be added; otherwise, it can be returned to the rule generation model for optimization, and the entire evaluation process and decision basis can be recorded in the rule evaluation log for future auditing and backtracking, thereby ensuring that only strictly verified verification rules are applied to actual data verification, improving the accuracy and reliability of data reporting, while reducing the risk of introducing errors or unnecessary rules.

[0112] Step S53: if not, generate a rule evaluation log based on the third verification rule.

[0113] It should be noted that the rule evaluation log refers to a third verification rule log that records the failure of rule verification and evaluation.

[0114] Specifically, if the third verification rule is not added to the preset verification rule configuration table, the third verification rule will be associated and combined with information such as verification abnormality results to generate a rule evaluation log to serve as a data basis for subsequent rule evaluations, and the rule evaluation log can be used as a model training set for model training, thereby improving the robustness of the model.

[0115] This embodiment obtains a third verification rule output by the verification rule generation model by inputting the verification abnormality result into the verification rule generation model, and then verifies and evaluates the third verification rule, and determines whether to add the third verification rule to the preset verification rule configuration table. If not, a rule evaluation log is generated based on the third verification rule, and then the verification abnormality result is analyzed through a large model, and the verification rules are continuously optimized and updated, so as to improve the accuracy and effectiveness of data verification, thereby reducing the risks caused by data errors, and being able to adapt to changes in data characteristics and automatically adjust the verification rules to adapt to new data patterns.

[0116] In a feasible implementation manner, the training process of the verification rule generation model includes:

[0117] Step S61, obtaining several groups of historical submission data and historical verification rules corresponding to each of the historical submission data;

[0118] It should be noted that the historical reporting data refers to data records that have been formally submitted or reported to regulatory agencies, tax authorities or other relevant departments in the past period of time, and the historical verification rules refer to a series of rules and standards used to verify the accuracy and compliance of the reported data in the past period of time.

[0119] Step S62, based on the preset data knowledge base, knowledge injection is performed on the initial verification rule generation model;

[0120] It should be noted that the preset data knowledge base refers to a pre-set database storing specific data verification rules, and the preset verification rule database can be continuously adjusted and updated to maintain the accuracy and timeliness of the rules.

[0121] It should be further explained that the initial verification rule generation model refers to an initial template framework that has not been trained, and is used to obtain the verification rule generation model after iterative training.

[0122] Specifically, the preset data knowledge base is injected into the initial verification rule generation model through a supervised learning algorithm, wherein prompt words can be generated based on the knowledge, and prompt words and answer pairs can be designed to be fed into the large model. There is no limitation here and it can be set according to actual conditions, so as to integrate specific domain knowledge or external knowledge into the pre-trained model, so that the model can achieve excellent training results in specific tasks or fields, thereby enhancing the model's understanding of the terms, concepts and relationships of specific types of data verification, thereby improving the generalization ability and robustness of model training.

[0123] Step S63, inputting each of the historical submission data and each of the historical verification rules into the initial verification rule generation model after knowledge injection for iterative training to obtain the verification rule generation model.

[0124] Specifically, data preprocessing is performed on each of the historical reporting data, each of the historical verification rules, and the corresponding sample labels, such as data cleaning and normalization, so that each of the historical reporting data, each of the historical verification rules, and the corresponding sample labels are input into the initial verification rule generation model after knowledge injection, and the predicted value output by the initial verification rule generation model after knowledge injection is obtained, and then the model loss value is calculated based on the predicted value and the sample label using the loss function. In this embodiment, the loss function can be set according to actual needs and is not specifically limited here. After the model loss value is calculated, the training process ends, and the error back propagation algorithm is used to update the model parameters in the initial verification rule generation model after knowledge injection, and then the next training is performed. During the training process, it is determined whether the updated initial verification rule generation model after knowledge injection meets the preset training end condition. If it does, the updated initial verification rule generation model after knowledge injection is used as the verification rule generation model. If it does not meet the condition, the model training continues, wherein the preset training end condition includes loss convergence and reaching the maximum iteration number threshold.

[0125] This embodiment obtains several groups of historical reporting data and historical verification rules corresponding to each of the historical reporting data, and then injects knowledge into the initial verification rule generation model based on a preset data knowledge base, thereby inputting each of the historical reporting data and each of the historical verification rules into the initial verification rule generation model after knowledge injection for iterative training to obtain the verification rule generation model, thereby significantly improving the quality, accuracy and efficiency of generating verification rules, and through knowledge injection, the model can learn the characteristics of verification rules corresponding to different data types, so as to better adapt to specific needs in different scenarios, generate verification rules that better meet user needs, and effectively improve data verification efficiency and accuracy.

[0126] In a feasible implementation manner, after the abnormal verification result is pushed to the early warning person in charge for verification by the early warning person in charge, the method further includes:

[0127] Step S71, obtaining the verification status of the warning responsible person;

[0128] It should be noted that the verification status refers to the record of the status and results after manual verification of abnormal verification results in the data reporting process, including verification status, verification results (for example, data is corrected, confirmed as a false alarm, or other processing measures), verification personnel, verification time, verification actions (such as data correction, rule adjustment, anomaly elimination, etc.), verification opinions, verification detailed records, etc.

[0129] Specifically, the verification and examination status configured by the warning responsible person in the interface is obtained. There is no restriction on the acquisition method, and it can be set according to the actual situation.

[0130] Step S72: If the verification is complete, the verification and submission process of the target submitted data is restored.

[0131] Specifically, when the early warning responsible personnel complete the verification of the abnormal verification results, the system will automatically identify whether the verification status has changed to "verification completed". When the system confirms the verification status, it will automatically trigger the mechanism to resume the verification and reporting process of the target reporting data that was previously suspended due to abnormalities, ensuring that the data that has been manually verified and corrected can continue to circulate in the reporting system, so that the data can be successfully verified and reported to the relevant regulatory authorities or other recipients according to the established schedule and requirements.

[0132] This embodiment obtains the verification status of the warning responsible person, and if the verification status is completed, the verification and reporting process of the target reported data is restored, thereby ensuring the accuracy of data verification and the completeness of the process execution, while ensuring the continuity and reliability of data reporting.

[0133] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0134] This application also provides a data verification device, please refer to Figure 5 , the data verification device comprises:

[0135] The acquisition module 51 is used to acquire target reporting data;

[0136] A matching module 52, used to match the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data;

[0137] The verification module 53 is used to verify the target reported data based on the verification rule list and generate a verification result table.

[0138] The data verification device is also used for:

[0139] Determine the matching indexes of all first verification rules in the preset verification rule configuration table;

[0140] Matching the target reported data with the matching index of each of the first verification rules to determine a second verification rule corresponding to the target reported data;

[0141] The second verification rules are associated and combined to generate a verification rule list.

[0142] The data verification device is also used for:

[0143] Determine the rule importance scores and execution strategies of all second verification rules in the verification rule list based on the data features corresponding to the target reported data;

[0144] Sorting the rule importance scores of each of the second verification rules to obtain the execution priority of each of the second verification rules;

[0145] Based on the execution priority and execution strategy corresponding to each of the second verification rules, the target reported data is verified to generate a verification result table.

[0146] The data verification device is also used for:

[0147] Read the abnormal verification results in the verification result table, and block the verification and reporting process of the target reported data;

[0148] Obtain the warning responsible person corresponding to the abnormal verification result;

[0149] The abnormal verification result is pushed to the warning person in charge for verification by the warning person in charge.

[0150] The data verification device is also used for:

[0151] Inputting the abnormal verification result into a verification rule generation model to obtain a third verification rule output by the verification rule generation model;

[0152] Verifying and evaluating the third verification rule to determine whether to add the third verification rule to the preset verification rule configuration table;

[0153] If not, a rule evaluation log is generated based on the third verification rule.

[0154] The data verification device is also used for:

[0155] Obtaining several groups of historical submission data and historical verification rules corresponding to each of the historical submission data;

[0156] Based on the preset data knowledge base, knowledge is injected into the initial verification rule generation model;

[0157] The historical reporting data and the historical verification rules are input into the initial verification rule generation model after knowledge injection for iterative training to obtain the verification rule generation model.

[0158] The data verification device is also used for:

[0159] Obtain the verification results of the warning responsible personnel;

[0160] If the verification and verification status is completed, the verification and reporting process of the target reported data is restored.

[0161] The data verification device provided by the present application adopts the data verification method in the above embodiment, which can solve the technical problems in the background technology. Compared with the prior art, the beneficial effects of the data verification device provided by the present application are the same as the beneficial effects of the data verification method provided by the above embodiment, and the other technical features in the data verification device are the same as the features disclosed in the above embodiment method, which will not be repeated here.

[0162] The present application provides a data verification device, which includes: at least one processor; and a memory that is communicatively connected to the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the data verification method in the above-mentioned embodiment one.

[0163] Reference below Figure 6, which shows a schematic diagram of the structure of a data verification device suitable for implementing an embodiment of the present application. The data verification device in the embodiment of the present application may include but is not limited to mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Descriptions), PMPs (Portable Media Players), vehicle-mounted terminals (such as vehicle-mounted navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 6 The data verification device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0164] like Figure 6 As shown, the data verification device may include a processing device 1001 (e.g., a central processing unit, a graphics processor, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM: Read Only Memory) 1002 or a program loaded from a storage device 1003 to a random access memory (RAM: Random Access Memory) 1004. In RAM1004, various programs and data required for the operation of the data verification device are also stored. The processing device 1001, ROM1002, and RAM1004 are connected to each other through a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Generally, the following systems can be connected to the I / O interface 1006: an input device 1007 including, for example, a touch screen, a touch pad, a keyboard, a mouse, an image sensor, a microphone, an accelerometer, a gyroscope, etc.; an output device 1008 including, for example, a liquid crystal display (LCD: Liquid Crystal Display), a speaker, a vibrator, etc.; a storage device 1003 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 1009. The communication device 1009 can allow the data verification device to communicate with other devices wirelessly or by wire to exchange data. Although the data verification device with various systems is shown in the figure, it should be understood that it is not required to implement or have all the systems shown. More or fewer systems can be implemented or have alternatively.

[0165] In particular, according to the embodiments disclosed in the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present application include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device, or installed from a storage device 1003, or installed from a ROM 1002. When the computer program is executed by the processing device 1001, the above-mentioned functions defined in the method of the embodiment disclosed in the present application are executed.

[0166] The data verification device provided by the present application adopts the data verification method in the above embodiment, which can solve the technical problems in the background technology. Compared with the prior art, the beneficial effects of the data verification device provided by the present application are the same as the beneficial effects of the data verification method provided by the above embodiment, and the other technical features in the data verification device are the same as the features disclosed in the method of the previous embodiment, which will not be repeated here.

[0167] It should be understood that the various parts disclosed in this application can be implemented by hardware, software, firmware or a combination thereof. In the description of the above embodiments, specific features, structures, materials or characteristics can be combined in any one or more embodiments or examples in a suitable manner.

[0168] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0169] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, wherein the computer-readable program instructions are used to execute the data verification method in the above-mentioned embodiment.

[0170] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0171] The computer-readable storage medium may be included in the data verification device; or may exist independently without being assembled into the data verification device.

[0172] The computer-readable storage medium carries one or more programs. When the one or more programs are executed by the data verification device, the data verification device:

[0173] Obtain target reporting data;

[0174] Matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data;

[0175] Based on the verification rule list, the target reported data is verified to generate a verification result table.

[0176] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0177] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0178] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0179] The readable storage medium provided in this application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned data verification method, and can solve the technical problems in the background technology. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as the beneficial effects of the data verification method provided in the above-mentioned embodiment, and will not be repeated here.

[0180] An embodiment of the present application provides a computer program product, including a computer program, which implements the steps of the above-mentioned data verification method when executed by a processor.

[0181] The computer program product provided in this application can solve the technical problems in the background technology. Compared with the prior art, the beneficial effects of the computer program product provided in the embodiment of this application are the same as the beneficial effects of the data verification method provided in the above embodiment, which will not be repeated here.

[0182] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A data verification method, characterized in that: include: Obtain target reporting data; Matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data; Based on the verification rule list, the target reported data is verified to generate a verification result table.

2. The data verification method according to claim 1, characterized in that: The step of matching the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data includes: Determine the matching indexes of all first verification rules in the preset verification rule configuration table; Matching the target reported data with the matching index of each of the first verification rules to determine a second verification rule corresponding to the target reported data; The second verification rules are associated and combined to generate a verification rule list.

3. The data verification method according to claim 1, characterized in that: The step of verifying the target submitted data based on the verification rule list and generating a verification result table includes: Determine the rule importance scores and execution strategies of all second verification rules in the verification rule list based on the data features corresponding to the target reported data; Sorting the rule importance scores of each of the second verification rules to obtain the execution priority of each of the second verification rules; Based on the execution priority and execution strategy corresponding to each of the second verification rules, the target reported data is verified to generate a verification result table.

4. The data verification method according to claim 1, characterized in that: After verifying the target submitted data based on the verification rule list and generating a verification result table, the method further includes: Read the abnormal verification results in the verification result table, and block the verification and reporting process of the target reported data; Obtain the warning responsible person corresponding to the abnormal verification result; The abnormal verification result is pushed to the warning person in charge for verification by the warning person in charge.

5. The data verification method according to claim 4, characterized in that: After reading the abnormal verification result in the verification result table, the method further includes: Inputting the abnormal verification result into a verification rule generation model to obtain a third verification rule output by the verification rule generation model; Verifying and evaluating the third verification rule to determine whether to add the third verification rule to the preset verification rule configuration table; If not, a rule evaluation log is generated based on the third verification rule.

6. The data verification method according to claim 5, characterized in that: The training process of the verification rule generation model includes: Obtaining several groups of historical submission data and historical verification rules corresponding to each of the historical submission data; Based on the preset data knowledge base, knowledge is injected into the initial verification rule generation model; The historical reporting data and the historical verification rules are input into the initial verification rule generation model after knowledge injection for iterative training to obtain the verification rule generation model.

7. The data verification method according to claim 4, characterized in that: After the abnormal verification result is pushed to the early warning person in charge for verification by the early warning person in charge, the method further includes: Obtain the verification results of the warning responsible personnel; If the verification and verification status is completed, the verification and reporting process of the target reported data is restored.

8. A data verification device, characterized in that: include: The acquisition module is used to obtain the target reporting data; A matching module, used to match the target reported data with a preset verification rule configuration table to determine a verification rule list corresponding to the target reported data; The verification module is used to verify the target reported data based on the verification rule list and generate a verification result table.

9. A data verification device, characterized in that: The data verification device comprises: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program is configured to implement the steps of the data verification method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, the steps of the data verification method according to any one of claims 1 to 7 are implemented.

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