Change test method for risk control responsibility judgment data and related equipment

Abstract

The embodiment of the invention belongs to the field of data processing, and relates to a change test method for risk control responsibility judgment data, which comprises the following steps: acquiring risk control responsibility judgment data corresponding to a target business scene; analyzing the risk control responsibility judgment data, and establishing a global relationship network according to an analysis result; monitoring the risk control responsibility judgment data to obtain data change content and code change content; determining a data change influence range and a code change influence range according to the data change content, the code change content and the global relationship network; and performing accurate testing according to the data change influence range and the code change influence range to obtain a test result corresponding to the target business scene. The invention further provides a change testing device for risk control responsibility judgment data, computer equipment and a storage medium. In addition, the invention also relates to a block chain technology, and the risk control responsibility judgment data can be stored in a block chain. The objective of the invention is to evaluate and verify the influence range of the change of the risk control responsibility judgment data.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to a change testing method and related equipment for risk control accountability data. Background Art

[0002] The risk control accountability system can monitor business-related data through multiple judgment strategies, accurately identify and block potential high-risk behaviors. Generally speaking, the results of risk control accountability depend on risk control strategies, which in turn are highly dependent on feature information, which may reference other feature data or complete data. Therefore, when the risk control accountability system involves changes related to feature data, complete data, and code changes, testing is required to evaluate and verify the scope of the impact of data changes. Summary of the invention

[0003] The purpose of the embodiments of the present application is to propose a change testing method and related equipment for risk control accountability data, aiming to evaluate and verify the impact scope of changes in risk control accountability data.

[0004] In order to solve the above technical problems, the present application embodiment provides a method for testing changes in risk control accountability data, which adopts the following technical solutions:

[0005] A method for testing changes in risk control accountability data includes the following steps:

[0006] Obtain risk control and accountability data corresponding to the target business scenario;

[0007] Analyze the risk control and accountability data, and establish a global relationship network based on the analysis results;

[0008] Monitor the risk control and accountability data to obtain data change content and code change content;

[0009] Determine the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network;

[0010] Accurate testing is performed based on the impact scope of the data change and the impact scope of the code change to obtain test results corresponding to the target business scenario.

[0011] Furthermore, the step of determining the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network specifically includes:

[0012] According to the data change content, searching the global relationship network to obtain the impact scope of the data change;

[0013] According to the code change content, a mapping relationship between the completed data and the code of the risk control accountability data is established;

[0014] At every preset time period, identifying the associated completion data affected by the code change content according to the mapping relationship and the preset incremental code report;

[0015] The global relationship network is retrieved according to the associated completion data to obtain the impact scope of the code change.

[0016] Furthermore, the step of monitoring the risk control accountability data to obtain data change content and code change content specifically includes:

[0017] Actively poll the risk control accountability data to determine the content of the data changes;

[0018] The code change content is determined according to the change record corresponding to the associated code of the data change content.

[0019] Furthermore, the analysis result includes a reference relationship, the global relationship network includes a reference relationship tree and a referenced relationship tree, and the step of analyzing the risk control accountability data and establishing a global relationship network according to the analysis result specifically includes:

[0020] Performing one-way parsing on the strategy information, feature information and supplementary information in the risk control accountability data to obtain the reference relationship;

[0021] According to the reference relationship, a bidirectional reference relationship tree is formed;

[0022] The global relationship network is established according to the bidirectional reference relationship tree.

[0023] Further, after the step of performing accurate testing according to the data change impact scope and the code change impact scope to obtain the test result corresponding to the target business scenario, the method further includes:

[0024] The preset report template is filled in according to the test results to obtain a change test report corresponding to the risk control accountability data.

[0025] Furthermore, the step of obtaining the risk control accountability data corresponding to the target business scenario specifically includes:

[0026] Receiving a call instruction carrying call information, and calling the risk control and accountability system according to the call instruction;

[0027] According to the call information, the policy information, feature information and completion information of the target business scenario are obtained as the risk control accountability data.

[0028] Furthermore, it is characterized in that after the step of obtaining the risk control accountability data corresponding to the target business scenario, it also includes:

[0029] The risk control accountability data is stored in a preset blockchain node.

[0030] In order to solve the above technical problems, the embodiment of the present application further provides a device for testing changes in risk control accountability data, which adopts the following technical solution:

[0031] A device for testing changes in risk control accountability data, comprising:

[0032] The acquisition module is used to obtain the risk control and accountability data corresponding to the target business scenario;

[0033] An analysis module is used to analyze the risk control and accountability data and establish a global relationship network based on the analysis results;

[0034] A monitoring module is used to monitor the risk control judgment data and obtain data change content and code change content;

[0035] A determination module, used to determine the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network;

[0036] The test module is used to perform precise testing according to the impact scope of the data change and the impact scope of the code change to obtain the test results corresponding to the target business scenario.

[0037] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0038] A computer device includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the processor executes the computer-readable instructions, the steps of the change testing method for risk control accountability data as described above are implemented.

[0039] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0040] A computer-readable storage medium having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by a processor, implement the steps of the above-mentioned method for testing the change of risk control accountability data.

[0041] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0042] The change test method for risk control accountability data disclosed in the present application obtains the risk control accountability data corresponding to the target business scenario; analyzes the risk control accountability data, and establishes a global relationship network based on the analysis results; monitors the risk control accountability data to obtain data change content and code change content; determines the data change impact range and the code change impact range based on the data change content, the code change content and the global relationship network; performs precise testing based on the data change impact range and the code change impact range to obtain the test results corresponding to the target business scenario. The present application can automatically identify the change content of data and code through monitoring and analysis of risk control accountability data, thereby realizing the precise determination of the change impact range. By combining the data change content, the code change content and the global relationship network, the blind spots in the traditional testing method are avoided, and the coverage and accuracy of the change test are ensured; in addition, the highly targeted change test can efficiently allocate test resources, reduce irrelevant testing work, and improve the efficiency and quality of the test. It can not only timely discover potential risks or errors, but also effectively improve the overall effect of the risk control accountability data change test. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0044] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0045] Figure 2 It is a flow chart of an embodiment of a method for changing risk control accountability data according to the present application;

[0046] Figure 3 It is a structural schematic diagram of an embodiment of a device for testing changes in risk control accountability data according to the present application;

[0047] Figure 4 It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0048] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0049] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0050] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0051] like Figure 1 As shown, the system architecture 100 may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0052] Users can use terminal devices 101, 102, 103 to interact with server 105 through network 104 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 101, 102, 103, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0053] Terminal devices 101, 102, 103 can be various electronic devices with display screens and supporting web browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 (Moving Picture Experts Group Audio Layer III) players, MP4 (Moving Picture Experts Group Audio Layer IV) players, laptop computers, desktop computers, etc.

[0054] The server 105 may be a server that provides various services, such as a background server that provides support for web pages displayed on the terminal devices 101 , 102 , and 103 .

[0055] It should be noted that the change test method for risk control accountability data provided in the embodiment of the present application is generally executed by a terminal device, and accordingly, the change test device for risk control accountability data is generally arranged in the terminal device.

[0056] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0057] Continue to refer Figure 2 , shows a flow chart of an embodiment of a method for testing changes in risk control accountability data according to the present application. The method for testing changes in risk control accountability data comprises the following steps:

[0058] Step S201, obtaining risk control accountability data corresponding to the target business scenario.

[0059] In this embodiment, the electronic device (for example, Figure 1 The terminal device shown in the figure can send or receive data through a wired connection or a wireless connection. It should be noted that the above wireless connection methods may include but are not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future.

[0060] In this embodiment, in the risk control accountability system, each business scenario will have a corresponding set of risk control accountability data, which includes strategies, features, and supplementary information. By obtaining this data, it can be ensured that the test covers all key data related to the target business scenario. Assuming that the business scenario is "financial loan approval", the corresponding risk control accountability data may include loan applicant information, credit score, repayment history, guarantor information, etc. This method can also be applied to risk control systems in other industries, such as e-commerce payment risk control, financial fraud detection, etc., not limited to single scenarios such as loan approval.

[0061] Step S202: parse the risk control accountability data and establish a global relationship network based on the parsing results.

[0062] In this embodiment, the acquired risk control judgment data is parsed, and the reference relationship between the various elements (such as strategies, features, completion, etc.) is analyzed to establish a global relationship network. This relationship network can help clearly see the dependencies between data, and then identify which other data or business logic may be affected when the data changes. If a "credit score" feature is referenced by multiple risk control strategies, and a strategy references the "loan amount" feature, then the relationship between the two will be clearly identified, forming a reference chain between nodes.

[0063] Step S203: monitor the risk control accountability data to obtain data change content and code change content.

[0064] In this embodiment, in the risk control system, data and code may change at any time, which may be due to changes in business requirements, policy adjustments or code optimization. By monitoring these changes, it is possible to identify in time which data or code has changed, providing a basis for subsequent accurate testing. Assuming that a certain policy rule in the risk control system has been adjusted, resulting in the modification of the data of the "credit score" feature, then this part of the change needs to be captured in time. Similarly, if the developer optimizes the code or adds a new functional module, the tester also needs to be informed of the information of these code changes.

[0065] Step S204: determining the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network.

[0066] In this embodiment, when data or code changes, the previously established global relationship network is combined to identify which data or functions these changes may affect. The scope of data change usually refers to the changed data or related features, completions, etc., and the scope of code change refers to the functional modules or data processing logic related to the code change. If the calculation method of the "credit score" feature changes (data change), then according to the global relationship network, it may affect the evaluation of "loan amount" and "repayment ability" (code change). In this case, the tester needs to pay attention to these affected areas and conduct detailed verification.

[0067] Step S205 , performing precise testing according to the data change impact scope and the code change impact scope to obtain a test result corresponding to the target business scenario.

[0068] In this embodiment, the scope of impact of data and code changes is combined to determine which parts need in-depth testing, and the relevant test cases are executed through automated testing tools to verify the correctness and stability of the system after the data and code changes, and finally obtain the test results. Assuming that the change of the "credit score" feature will affect the decision logic of "loan approval", the tester needs to conduct a simulation test for this change to verify whether the loan approval is still in line with expectations under the new calculation method.

[0069] By monitoring and analyzing risk control and accountability data, this application can automatically identify changes in data and code, thereby accurately determining the scope of change impact. By combining data change content, code change content, and the global relationship network, it avoids blind spots in traditional testing methods and ensures the coverage and accuracy of change testing. In addition, highly targeted change testing can efficiently allocate testing resources, reduce irrelevant testing work, and improve testing efficiency and quality. It can not only detect potential risks or errors in a timely manner, but also effectively improve the overall effect of risk control and accountability data change testing.

[0070] In some optional implementations of this embodiment, the step of determining the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network specifically includes:

[0071] According to the data change content, searching the global relationship network to obtain the impact scope of the data change;

[0072] According to the code change content, a mapping relationship between the completed data and the code of the risk control accountability data is established;

[0073] At every preset time period, identifying the associated completion data affected by the code change content according to the mapping relationship and the preset incremental code report;

[0074] The global relationship network is retrieved according to the associated completion data to obtain the impact scope of the code change.

[0075] In this embodiment, when a data change is detected, the system will retrieve the global relationship network according to the specific content of the change, identify the scope of influence of the changed data in the global data structure, and trace back to other affected data, features or rules through the data dependency relationship in the global relationship network, and then determine the scope of influence of the data change. Assume that in the "loan approval" business scenario, the data change involves the modification of the "credit score" feature, and the global relationship network shows that this feature is closely related to strategies such as "loan amount" and "repayment ability". Therefore, after retrieving the global relationship network, it can be determined that the calculation rules of "loan amount" and "repayment ability" are also affected, and then the scope of influence of the data change is derived. Code changes may affect the processing method of risk control judgment data, especially the application of supplementary data (such as missing value filling, outlier processing, etc.) in data calculation. Therefore, after the code is changed, it is necessary to establish a mapping relationship to associate the functional modules in the code with the supplementary data, so as to accurately identify which supplementary data will be affected. Assume that the code updates the missing value processing method in the "credit score" calculation module, such as adding a more accurate missing value filling strategy. In this case, a mapping relationship can be established to ensure that the change affects the features involving missing values ​​in the risk control data (such as "income level" or "loan history"), and these completed data are tracked and monitored. The system will regularly check the incremental report of code changes at preset time intervals, and analyze the completed data that may be affected by each code update in combination with the previously established mapping relationship between code and completed data. The incremental code report will contain the modules, functions or classes involved in this code modification. This information can be used to timely identify the affected completed data. For example, the system automatically generates an incremental report after each code update and points out that some algorithms in the "credit score" calculation module have been modified. Based on the mapping relationship, the system can identify that the modification of these algorithms will affect the completed data of the "credit score" feature (such as filling in missing historical loan records). Therefore, these completed data need to be verified in detail. After identifying the affected completion data, the system will once again retrieve the relevant data dependencies through the global relationship network. Through the query of the global relationship network, the system can further determine other data or strategies related to these completion data, and finally determine the scope of the code change on the entire risk control judgment data and strategy. Assuming that the code change affects the completion data "missing value filling of credit score", according to the mapping relationship, this change affects the "credit score" feature. Further through the global relationship network, the system can identify that the "credit score" feature not only affects the calculation of the "loan amount", but is also closely related to the "overdue risk" assessment. Therefore, it is finally determined that the scope of the code change includes "loan amount", "overdue risk" and related strategy modules.

[0076] This application further improves the process of identifying the scope of change impact by combining data change content, code change content and the global relationship network; by retrieving the global relationship network and establishing a mapping relationship between the completed data and the risk control accountability data code, it can not only identify the impact of data changes, but also dynamically monitor the impact of code changes on risk control accountability data.

[0077] In some optional implementations of this embodiment, the above-mentioned step of monitoring the risk control accountability data to obtain data change content and code change content specifically includes:

[0078] Actively poll the risk control accountability data to determine the content of the data changes;

[0079] The code change content is determined according to the change record corresponding to the associated code of the data change content.

[0080] In this embodiment, the system will actively poll the risk control judgment data, that is, regularly check or monitor the changes in the data. By periodically querying or monitoring the data source (such as a database, real-time data stream, file, etc.), the system can detect the occurrence of data changes in a timely manner and determine the content of the data changes. Assuming that the "borrower credit score" data of the risk control system needs to be updated regularly, the system will regularly check the changes in the credit score field through active polling. If data updates (such as changes in credit scores) are found, the content of the data changes can be immediately determined. After determining the content of the data changes, the system will find the relevant code change records by analyzing the code modules or functions associated with the data changes. This process is usually implemented through logs, version control systems (such as Git) or other code management tools. Each time the code is updated, the developer usually indicates the relevant data fields or function modules in the submission record. The system can associate this information with specific code change records to understand the specific content of the code changes. Assuming that the "credit score" field in the risk control system has changed, the system first detects the change in the data; then, based on the content of the data change (such as the change in the "credit score" field), the system will query the change record in the version control system to see if the developer has modified the code related to the "credit score calculation logic". By checking the submission log or change record, the system can determine the code modification content related to the data change.

[0081] This application can capture data and code changes as soon as changes occur by actively polling and monitoring risk control and accountability data. It does not rely on passive detection mechanisms, but ensures real-time updates of data and code through active monitoring, greatly improving the timeliness and accuracy of change detection. By clearly identifying code records related to changes, testers can quickly locate the affected parts, thereby providing accurate basis for subsequent change testing and avoiding the omission of potential risks.

[0082] In some optional implementations of this embodiment, the above-mentioned parsing result includes a reference relationship, the above-mentioned global relationship network includes a reference relationship tree and a referenced relationship tree, and the above-mentioned step of parsing the risk control accountability data and establishing a global relationship network according to the parsing result specifically includes:

[0083] Performing one-way parsing on the strategy information, feature information and supplementary information in the risk control accountability data to obtain the reference relationship;

[0084] According to the reference relationship, a bidirectional reference relationship tree is formed;

[0085] The global relationship network is established according to the bidirectional reference relationship tree.

[0086] In this embodiment, when parsing the risk control judgment data, three types of key information need to be extracted from the data first: strategy information, which is usually the rules or standards used for risk control judgment decisions, such as "credit score not less than 650 can only approve loans"; feature information, which is the description data of the risk control object, such as the user's age, income, credit score, etc.; supplementary information, which is some supplementary data that may be missing but will affect the risk control judgment, such as historical behavior data, supplementary financial information, etc. One-way parsing of this information means that only one direction of dependency between data is considered during parsing. During the parsing process, the system will identify which data items depend on other data items to form a reference relationship. Strategy information may depend on feature information, such as credit score may determine whether a loan is approved. Here, strategy information (whether to approve a loan) depends on feature information (credit score). Completion information may have an impact on feature information, for example, supplementary financial information may affect the user's credit score. By analyzing the reference relationship, the system will construct a bidirectional reference relationship tree, which means not only recording the dependency between data, but also recording the mutual reference of data. Each node represents a data item, and the edge represents the reference relationship between data items. For example, one-way reference: data A references data B, indicating that A depends on B; two-way reference: data A and data B reference each other, indicating that they depend on each other, forming a two-way relationship. By constructing a two-way reference relationship tree, the system can clearly display the complex interdependencies between data items. Suppose there are two data items A (credit score) and B (loan approval), and there is a two-way reference relationship between them: A (credit score) affects B (loan approval); B (loan approval) may also affect A (for example, loan approval may affect credit score). This two-way dependency will be recorded in the reference relationship tree to help the system understand how to trace the impact when the data changes. After forming the two-way reference relationship tree, the system will expand it into a complete global relationship network. The global relationship network not only includes the reference relationship of risk control judgment data, but also covers the mutual influence and dependency between data items. This global relationship network can help the system comprehensively evaluate the impact scope and potential risks of changes when data or code changes. It provides a global view to help analyze the impact of data changes on the entire system. Through the relationship network, the system can identify complex dependencies between data, so as to conduct more accurate testing and ensure the decision-making accuracy of the risk control system. Assume that there are multiple interrelated data in the risk control and accountability system, such as credit score, loan approval, income data, debt data, etc. By analyzing the reference relationship of these data items, a complex relationship network is finally formed, which can clearly show the mutual influence between all data items. For example: credit score depends on income, debt, repayment history and other data; loan approval depends on credit score, income and other data; risk assessment needs to consider loan approval, credit score, user history and other data.Through the global relationship network, the system can quickly identify the impact scope of the change.

[0087] This application establishes a global relationship network based on reference relationships by parsing the strategies, features and completion information in the risk control and accountability data, thereby providing more systematic support for change testing; the construction of a bidirectional reference relationship tree makes the reference and referenced relationships between data more clear and traceable, and testers can clearly identify all affected nodes, thereby ensuring full coverage of the test, improving the operability and maintainability of the change test, and ensuring the integrity of data associations during the change test process.

[0088] In some optional implementations of this embodiment, after the above step of performing precise testing according to the data change impact scope and the code change impact scope to obtain the test result corresponding to the target business scenario, the following is further included:

[0089] The preset report template is filled in according to the test results to obtain a change test report corresponding to the risk control accountability data.

[0090] In this embodiment, once the precise test is completed and the test results (i.e., the scope of impact of data changes and code changes and their impact) are obtained, the system will fill the test results into the template according to the preset report template. The test report template usually includes multiple fields, such as test background, test objectives, test results, risk assessment, change impact analysis, conclusions, etc. The filling process is to present the test results in a standardized manner to ensure that all relevant information is clearly recorded. Assuming that the test is about the impact of credit score data changes on the loan approval process, the relevant fields in the template can be, Test background: Analyze the impact of credit score data changes on loan approval decisions; Test objectives: Evaluate whether the results of loan approval will be misjudged or misjudged after the credit score changes; Test results: The test shows that the change in credit score has led to the deviation of some loan approval decisions, and the approval algorithm needs to be further optimized; Risk assessment: It is recommended to strengthen the verification mechanism of credit score data to reduce the risk of misjudgment; Change impact analysis: Credit score changes will cause some high-risk users to be mistaken for low risk, which may lead to an increase in the risk of loan default; Conclusions and suggestions: It is recommended to adjust the risk control strategy and use multi-dimensional data for credit assessment to reduce reliance on a single data source. After completing the report filling, the system generates a complete change test report, which includes not only the test results, but also additional analysis and suggestions to help relevant departments make decisions on the test results. The test report should be customized according to the specific business scenario and test requirements to ensure its practicality and pertinence. The steps of generating reports ensure that all test results can be recorded, summarized and communicated. It is a bridge of communication that can help all parties (such as developers, testers, business personnel, and management) understand the impact and results of change testing.

[0091] This application generates a detailed risk control and accountability data change test report by automatically filling in preset report templates, which not only simplifies the report generation process, but also ensures the transparency and traceability of the test results. By combining the test results with the report template, clear document output can be quickly and accurately generated, providing a direct basis for subsequent decision-making and optimization, while improving the efficiency and compliance of the testing work.

[0092] In some optional implementations of this embodiment, the step of obtaining the risk control accountability data corresponding to the target business scenario specifically includes:

[0093] Receiving a call instruction carrying call information, and calling the risk control and accountability system according to the call instruction;

[0094] According to the call information, the policy information, feature information and completion information of the target business scenario are obtained as the risk control accountability data.

[0095] In this embodiment, the system first receives a call instruction, which carries call information about the target business scenario. The call instruction is usually initiated by other systems (such as business systems, external interfaces, automated testing tools, etc.) to request the system to provide relevant risk control judgment data. The call information may include the following: target business scenario identifier: This field indicates the specific business scenario of the current request, such as a loan approval scenario, credit assessment scenario, etc.; request parameters: different input data parameters may be required according to different scenarios, such as the customer's credit record, historical transaction data, etc.; timestamp information: ensure that the data obtained by the system is real-time or conforms to a specific time period; other metadata: such as the requested operation type (query, modification, etc.) or a specific set of rules, etc. Assuming that a risk control system is processing a loan approval request, the business system will send a call instruction, which contains the requested loan approval scenario identifier (such as "loan approval"), the applicant's credit history information, loan amount and other parameters. The system initiates a request based on the received call information to call the risk control accountability system. The risk control accountability system is a data system responsible for judging and generating risk control decisions. It will return the corresponding strategies, features, and completion information based on the input call information. Through this system, users can obtain the required risk control accountability data for the target business scenario. Assuming that the call instruction initiated by the business system requires the system to obtain the loan approval data of a specific customer, the system will send a request to the risk control accountability system based on the call information to query and obtain the risk control accountability data of the customer. The risk control accountability system performs strategy evaluation, feature extraction, data completion and other operations based on the request content, and finally returns the corresponding risk control data. Based on the call information, the risk control accountability system will return the risk control accountability data for the target business scenario. Specifically, it includes the following data types: strategy information: this is the strategy, rules or standards defined in the risk control and accountability system. For example, for a loan approval scenario, strategy information may include loan amount, interest rate, customer credit score evaluation criteria, etc.; feature information: this part of the data includes features or attributes related to the specific business, which are usually used for model calculations. For example, in credit assessment, feature information may include a customer's historical borrowing record, credit score, income level, etc.; completion information: completion information refers to data that needs to be filled in or updated. For example, some data items may be missing, and the system will infer or complete this information based on existing data to ensure the accuracy of risk control decisions; the process of obtaining data: the system calls the interface of the risk control and accountability system, and extracts relevant strategies, features and completion information from the system's internal database based on the incoming call information.

[0096] By receiving and processing call instructions, this application can flexibly obtain the risk control and accountability data corresponding to the target business scenario, and supports dynamic acquisition of required strategies, features and completion information through a flexible calling mechanism, thereby ensuring the real-time and relevance of the risk control and accountability data, and further optimizing the efficiency of data acquisition, so that the change test of the risk control and accountability data can adapt to different business scenarios and respond to various changes in a timely manner, ensuring the comprehensiveness and timeliness of the test.

[0097] In some optional implementations of this embodiment, after the above step of obtaining the risk control accountability data corresponding to the target business scenario, the following is further included:

[0098] The risk control accountability data is stored in a preset blockchain node.

[0099] In this embodiment, in the management of risk control accountability data, the security, transparency and immutability of data are crucial. Traditional storage methods (such as relational databases or file systems) may be subject to the risk of attack, tampering or loss, while blockchain technology provides a decentralized and tamper-proof storage solution that can ensure that risk control accountability data is not tampered with during storage, and all operations can be traced. Therefore, in the management and testing of risk control accountability data, storing data in the blockchain can provide additional trust guarantees to avoid data loss, tampering or abuse due to human or technical problems.

[0100] This application stores risk control and accountability data in blockchain nodes, which not only provides a secure and tamper-proof storage method for data, but also increases the transparency and reliability of test data. The introduction of blockchain technology provides powerful data protection and auditing capabilities for change testing of risk control and accountability data, ensuring that all data changes during the test process can be traced and verified, improving the security of data management, and also enhancing the data integrity and credibility during the test process, providing a reliable foundation for subsequent analysis and optimization.

[0101] It should be emphasized that in order to further ensure the privacy and security of the above-mentioned risk control and accountability data, the above-mentioned risk control and accountability data can also be stored in a node of a blockchain.

[0102] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0103] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0104] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0105] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0106] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0107] Further references Figure 3 , as a response to the above Figure 2 In order to realize the method shown in the figure, the present application provides an embodiment of a device for testing the change of risk control judgment data. Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0108] like Figure 3As shown, the change test device 300 for risk control accountability data described in this embodiment includes: an acquisition module 301, a parsing module 302, a monitoring module 303, a determination module 304 and a testing module 305. Among them:

[0109] The acquisition module 301 is used to acquire the risk control and accountability data corresponding to the target business scenario;

[0110] The analysis module 302 is used to analyze the risk control accountability data and establish a global relationship network based on the analysis results;

[0111] The monitoring module 303 is used to monitor the risk control judgment data to obtain data change content and code change content;

[0112] A determination module 304, configured to determine a data change impact scope and a code change impact scope according to the data change content, the code change content and the global relationship network;

[0113] The testing module 305 is used to perform precise testing according to the data change impact scope and the code change impact scope to obtain the test results corresponding to the target business scenario.

[0114] The change testing device for risk control accountability data provided in the present application can automatically identify the changes in data and code through monitoring and analysis of risk control accountability data, thereby accurately determining the scope of change impact. By combining data change content, code change content and the global relationship network, it avoids blind spots in traditional testing methods and ensures the coverage and accuracy of change testing. In addition, highly targeted change testing can efficiently allocate testing resources, reduce irrelevant testing work, and improve the efficiency and quality of testing. It can not only timely discover potential risks or errors, but also effectively improve the overall effect of risk control accountability data change testing.

[0115] In some optional implementations of this embodiment, the determination module 304 is further configured to:

[0116] According to the data change content, searching the global relationship network to obtain the impact scope of the data change;

[0117] According to the code change content, a mapping relationship between the completed data and the code of the risk control accountability data is established;

[0118] At every preset time period, identifying the associated completion data affected by the code change content according to the mapping relationship and the preset incremental code report;

[0119] The global relationship network is retrieved according to the associated completion data to obtain the impact scope of the code change.

[0120] The change testing device for risk control accountability data provided in this application further improves the identification process of the change impact scope by combining data change content, code change content and the global relationship network; by retrieving the global relationship network and establishing a mapping relationship between the completed data and the risk control accountability data code, it can not only identify the impact of data changes, but also dynamically monitor the impact of code changes on risk control accountability data.

[0121] In some optional implementations of this embodiment, the monitoring module 303 is further configured to:

[0122] Actively poll the risk control accountability data to determine the content of the data changes;

[0123] The code change content is determined according to the change record corresponding to the associated code of the data change content.

[0124] The change testing device for risk control and accountability data provided by the present application can capture data and code change content as soon as a change occurs by actively polling and monitoring risk control and accountability data. It does not rely on a passive detection mechanism, but ensures real-time updating of data and code through active monitoring, greatly improving the timeliness and accuracy of change detection. By clearly identifying code records related to the change, testers can quickly locate the affected parts, thereby providing an accurate basis for subsequent change testing and avoiding the omission of potential risks.

[0125] In some optional implementations of this embodiment, the parsing module 302 is further configured to:

[0126] Performing one-way parsing on the strategy information, feature information and supplementary information in the risk control accountability data to obtain the reference relationship;

[0127] According to the reference relationship, a bidirectional reference relationship tree is formed;

[0128] The global relationship network is established according to the bidirectional reference relationship tree.

[0129] The change testing device for risk control accountability data provided by the present application establishes a global relationship network based on reference relationships by parsing the strategies, features and completion information in the risk control accountability data, thereby providing more systematic support for change testing; the construction of a bidirectional reference relationship tree makes the reference and referenced relationships between data more clear and traceable, and testers can clearly identify all affected nodes, thereby ensuring full coverage of the test, improving the operability and maintainability of the change test, and ensuring the integrity of data associations during the change test process.

[0130] In some optional implementations of this embodiment, the testing module 305 is further configured to:

[0131] The preset report template is filled in according to the test results to obtain a change test report corresponding to the risk control accountability data.

[0132] The change testing device for risk control and accountability data provided in this application generates a detailed risk control and accountability data change test report by automatically filling in a preset report template, which not only simplifies the report generation process, but also ensures the transparency and traceability of the test results; by combining the test results with the report template, it can quickly and accurately form a clear document output, providing a direct basis for subsequent decision-making and optimization, while improving the efficiency and compliance of the testing work.

[0133] In some optional implementations of this embodiment, the acquisition module 301 is further used to:

[0134] Receiving a call instruction carrying call information, and calling the risk control and accountability system according to the call instruction;

[0135] According to the call information, the policy information, feature information and completion information of the target business scenario are obtained as the risk control accountability data.

[0136] The change testing device for risk control and accountability data provided in the present application can flexibly obtain the risk control and accountability data corresponding to the target business scenario by receiving and processing calling instructions, and supports dynamic acquisition of required strategies, features and completion information through a flexible calling mechanism, thereby ensuring the real-time and relevance of the risk control and accountability data, and further optimizing the efficiency of data acquisition, so that the change testing of the risk control and accountability data can adapt to different business scenarios and respond to various changes in a timely manner, thereby ensuring the comprehensiveness and timeliness of the test.

[0137] In some optional implementations of this embodiment, the acquisition module 301 is further used to:

[0138] The risk control accountability data is stored in a preset blockchain node.

[0139] The change testing device for risk control and accountability data provided in the present application, by storing the risk control and accountability data in the blockchain node, not only provides a secure and tamper-proof storage method for the data, but also increases the transparency and reliability of the test data. The introduction of blockchain technology provides powerful data protection and auditing capabilities for the change testing of risk control and accountability data, ensuring that all data changes during the test process can be traced and verified, thereby improving the security of data management, while also enhancing the data integrity and credibility during the test process, providing a reliable foundation for subsequent analysis and optimization.

[0140] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0141] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components 41-43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0142] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0143] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. equipped on the computer device 4. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions for the change test method of risk control judgment data, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0144] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run the computer-readable instructions stored in the memory 41 or process data, such as running the computer-readable instructions of the change test method for risk control accountability data.

[0145] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0146] The computer equipment provided in this application can automatically identify the changes in data and code through monitoring and analysis of risk control and accountability data, thereby accurately determining the scope of change impact. By combining data change content, code change content and the global relationship network, it avoids blind spots in traditional testing methods and ensures the coverage and accuracy of change testing. In addition, highly targeted change testing can efficiently allocate testing resources, reduce irrelevant testing work, and improve the efficiency and quality of testing. It can not only detect potential risks or errors in a timely manner, but also effectively improve the overall effect of risk control and accountability data change testing.

[0147] The present application also provides another embodiment, namely, providing a computer-readable storage medium, which stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the change testing method for risk control accountability data as described above.

[0148] The computer-readable storage medium provided by the present application can automatically identify the changes in data and code by monitoring and analyzing risk control and accountability data, thereby accurately determining the scope of change impact. By combining data change content, code change content, and the global relationship network, it avoids blind spots in traditional testing methods and ensures the coverage and accuracy of change testing. In addition, highly targeted change testing can efficiently allocate testing resources, reduce irrelevant testing work, and improve the efficiency and quality of testing. It can not only detect potential risks or errors in a timely manner, but also effectively improve the overall effect of risk control and accountability data change testing.

[0149] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0150] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for testing changes in risk control accountability data, characterized in that: The steps include: Obtain risk control and accountability data corresponding to the target business scenario; Analyze the risk control and accountability data, and establish a global relationship network based on the analysis results; Monitor the risk control and accountability data to obtain data change content and code change content; Determine the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network; Accurate testing is performed based on the impact scope of the data change and the impact scope of the code change to obtain test results corresponding to the target business scenario.

2. The method for changing risk control accountability data according to claim 1, characterized in that: The step of determining the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network specifically includes: According to the data change content, searching the global relationship network to obtain the impact scope of the data change; According to the code change content, a mapping relationship between the completed data and the code of the risk control accountability data is established; At every preset time period, identifying the associated completion data affected by the code change content according to the mapping relationship and the preset incremental code report; The global relationship network is retrieved according to the associated completion data to obtain the impact scope of the code change.

3. The change test method for risk control accountability data according to claim 1 is characterized in that: The step of monitoring the risk control accountability data to obtain data change content and code change content specifically includes: Actively poll the risk control accountability data to determine the content of the data changes; The code change content is determined according to the change record corresponding to the associated code of the data change content.

4. The method for changing risk control accountability data according to claim 1, characterized in that: The analysis result includes a reference relationship, the global relationship network includes a reference relationship tree and a referenced relationship tree, and the step of analyzing the risk control accountability data and establishing a global relationship network according to the analysis result specifically includes: Performing one-way parsing on the strategy information, feature information and supplementary information in the risk control accountability data to obtain the reference relationship; According to the reference relationship, a bidirectional reference relationship tree is formed; The global relationship network is established according to the bidirectional reference relationship tree.

5. The change test method for risk control accountability data according to claim 1, characterized in that: After the step of performing accurate testing according to the data change impact scope and the code change impact scope to obtain the test result corresponding to the target business scenario, the step further includes: The preset report template is filled in according to the test results to obtain a change test report corresponding to the risk control accountability data.

6. The method for changing risk control accountability data according to claim 1, characterized in that: The step of obtaining the risk control accountability data corresponding to the target business scenario specifically includes: Receiving a call instruction carrying call information, and calling the risk control and accountability system according to the call instruction; According to the call information, the policy information, feature information and completion information of the target business scenario are obtained as the risk control accountability data.

7. The method for changing risk control accountability data according to any one of claims 1 to 6, characterized in that: After the step of obtaining the risk control and accountability data corresponding to the target business scenario, the method further includes: The risk control accountability data is stored in a preset blockchain node.

8. A device for testing changes in risk control accountability data, characterized in that: include: The acquisition module is used to obtain the risk control and accountability data corresponding to the target business scenario; An analysis module is used to analyze the risk control and accountability data and establish a global relationship network based on the analysis results; A monitoring module is used to monitor the risk control judgment data and obtain data change content and code change content; A determination module, used to determine the data change impact scope and the code change impact scope according to the data change content, the code change content and the global relationship network; The test module is used to perform precise testing according to the impact scope of the data change and the impact scope of the code change to obtain the test results corresponding to the target business scenario.

9. A computer device, characterized in that: It includes a memory and a processor, the memory stores computer-readable instructions, and the processor implements the steps of the change testing method for risk control accountability data as described in any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, which, when executed by a processor, implement the steps of the method for changing risk control accountability data as described in any one of claims 1 to 7.

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