Work order anomaly detection method, device and processor
By automating the detection of anomalies in operation and maintenance change management work orders, the problem of low efficiency and error-proneness in manual identification in existing technologies has been solved, achieving efficient and accurate operation and maintenance change management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CCB FINTECH CO LTD
- Filing Date
- 2022-09-29
- Publication Date
- 2026-07-07
AI Technical Summary
In the existing operation and maintenance change management process, the identification of operation and maintenance change management work orders is done manually, which is inefficient and prone to errors, resulting in losses.
This paper provides a method for detecting anomalies in bank operation and maintenance change management work orders. By automatically acquiring the content of operation and maintenance change management work orders, and using preset rules and risk assessment values, the method judges the work order anomalies, including change type, implementer information, time verification, etc., to achieve automated anomaly detection.
This improved the efficiency of operation and maintenance change management work orders, reduced the probability of detection errors, and ensured the compliance and accuracy of operation and maintenance change management.
Smart Images
Figure CN115409420B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of data analysis technology, specifically to a method for detecting anomalies in bank operation and maintenance change management work orders, a device for detecting anomalies in bank operation and maintenance change management work orders, a machine-readable storage medium, and a processor. Background Technology
[0002] Operations change management refers to the management of operational risks in a production environment to ensure the stable operation of information systems. The object of operations change management is the change orders submitted by daily operations personnel. It also manages the workflow of major and routine change plans on the IT service management platform, as well as the technical upgrades and modifications made on the IT service management platform. This ensures that operations change management activities begin when the information system is officially put into production and end when the system is taken offline. The goal of operations change management is to ensure the stable operation of information systems. This management involves not only the technology department but also relevant business operations departments and other support departments.
[0003] In the current operation and maintenance change management process, anomaly identification of operation and maintenance change management work orders is mostly done manually. This identification is inefficient and prone to human error, resulting in losses. Summary of the Invention
[0004] The purpose of this application is to provide a work order anomaly detection method, device, and processor. This method can automatically acquire operation and maintenance change management work orders and perform anomaly detection, with high detection efficiency and effectively reducing the probability of detection errors.
[0005] To achieve the above objectives, the first aspect of this application provides a method for detecting anomalies in bank operation and maintenance change management work orders, the method comprising:
[0006] Obtain the content of the operation and maintenance change management work order filled in by the user;
[0007] Verify whether the operation and maintenance change management work order is abnormal based on the content of the operation and maintenance change management work order and the first preset rule;
[0008] The operation and maintenance change management work order content shall at least include: a first change type and change risk factors.
[0009] When verifying whether the operation and maintenance change management work order is abnormal, it is determined whether the first change type is a major change or a routine change; if it is neither a major change nor a routine change, the verification ends.
[0010] If it is a major change or a routine change, then the second change type shall be determined based on the aforementioned change risk factors;
[0011] Compare the second change type with the first change type; if they are inconsistent, the operation and maintenance change management work order is deemed abnormal. The change type entered in the operation and maintenance change management work order must be consistent with the change risk factors. The change type is related to the assessment of various risks of operation and maintenance changes. By detecting the change type, the accuracy of the change type is ensured, and incorrect change types may affect the focus of the operation and maintenance change executor and reviewer in verifying the change.
[0012] In this embodiment of the application, determining the second change type based on the change risk factors includes:
[0013] Calculate the risk assessment value based on the aforementioned risk factors and the second preset rule;
[0014] If the risk assessment value is greater than or equal to the preset score, the second change type is determined to be a major change; otherwise, it is determined to be a routine change. Operational changes are categorized into major and routine changes based on their risk assessment values, and the different types of changes are quantified for easy differentiation.
[0015] In this embodiment of the application, the step of calculating the risk assessment value based on the changed risk factors and the second preset rule includes:
[0016] The scores for different risk factors are determined based on the aforementioned risk factors and preset evaluation rules;
[0017] The risk assessment value is obtained by weighting and summing the scores of different risk factors according to their respective weights.
[0018] In this embodiment of the application, the content of the operation and maintenance change management work order includes at least: information of the person implementing the change and information of the person reviewing the change;
[0019] Verify whether the maintenance change management work order is abnormal based on the content of the maintenance change management work order and the first preset rule, including:
[0020] Retrieve the actual implementer and reviewer information of the operation and maintenance changes corresponding to the change management work orders from the change implementation database;
[0021] The system compares the information of the actual implementer with that of the changed implementer, and the information of the actual reviewer with that of the changed reviewer. If any of these are inconsistent, the operation and maintenance change management work order is deemed abnormal. According to the operation and maintenance change management requirements, anomalies in the information of the change implementer and change reviewer constitute a serious violation under both change management and regulatory requirements. By checking the information of the change implementer and change reviewer, violations can be quickly identified.
[0022] In this embodiment of the application, comparing whether the information of the actual implementer is consistent with the information of the changed implementer, and whether the information of the actual reviewer is consistent with the information of the changed reviewer, includes:
[0023] Compare the names of the actual implementer and the changed implementer, and the names of the actual reviewer and the changed reviewer; if any of them are inconsistent, it is determined that the operation and maintenance change management work order is abnormal.
[0024] If all are consistent, then compare the group of the actual implementer with the group of the change implementer, and the group of the actual reviewer with the group of the change reviewer. If any one of them is inconsistent, then the operation and maintenance change management work order is considered abnormal. Duplicate names are common in enterprises. When detecting change implementers and change reviewers, adding group detection can quickly verify the change implementers and reviewers, effectively avoiding errors in detection results due to identical names.
[0025] In this embodiment of the application, the content of the operation and maintenance change management work order includes at least: the planned change time;
[0026] Verify whether the maintenance change management work order is abnormal based on the content of the maintenance change management work order and the first preset rule, including:
[0027] Get the current NTP server time;
[0028] Compare the current NTP server time with the planned change time entered by the user. If the planned change time is earlier than the current NTP server time, the maintenance change management work order is considered abnormal. The planned change time is the execution time of the planned change, and the change can only be executed after the work order is approved. Therefore, the planned change time can only be the future time at the time the work order is entered, not the past time. Verifying the planned change time can effectively reduce the violation of executing the change before submitting the work order application.
[0029] In this embodiment of the application, the content of the operation and maintenance change management work order includes at least: the approval process time and the actual change time;
[0030] Verify whether the maintenance change management work order is abnormal based on the content of the maintenance change management work order and the first preset rule, including:
[0031] By comparing the approval process time and the actual change time, if the actual change time is earlier than the approval process time, the operation and maintenance change management work order is considered abnormal. Change execution requires approval; therefore, the actual change time must be a future time of the approval process time. Verifying the approval process time and the actual change time can effectively reduce violations such as applying for and executing operation and maintenance changes simultaneously, or executing operation and maintenance changes before approval.
[0032] In this embodiment of the application, the method further includes:
[0033] When an anomaly is detected in the operation and maintenance change management work order, an anomaly alarm is triggered and the abnormal data is recorded.
[0034] A second aspect of the present invention provides a device for detecting anomalies in bank operation and maintenance change management work orders, the device comprising:
[0035] The data acquisition module is used to acquire the content of the operation and maintenance change management work order filled in by the user;
[0036] The anomaly verification module is used to verify whether the operation and maintenance change management work order is abnormal based on the content of the operation and maintenance change management work order and the first preset rule;
[0037] The operation and maintenance change management work order content shall at least include: a first change type and change risk factors.
[0038] When verifying whether the operation and maintenance change management work order is abnormal, the anomaly verification module determines whether the first change type is a major change or a routine change; if it is neither a major change nor a routine change, the verification ends.
[0039] If it is a major change or a routine change, then the second change type shall be determined based on the aforementioned change risk factors;
[0040] The system compares the second change type with the first change type; if they are inconsistent, the maintenance change management work order is deemed abnormal. This device can automatically acquire maintenance change management work orders and perform anomaly detection, achieving high efficiency and effectively reducing the probability of detection errors. Change types are related to various risk assessments of maintenance changes; detecting change types ensures their accuracy and prevents incorrect change types from affecting the focus of the maintenance change executor and reviewer's verification.
[0041] A third aspect of the present invention provides a processor configured to execute the aforementioned bank operation and maintenance change management work order anomaly detection method.
[0042] A fourth aspect of the present invention provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the bank operation and maintenance change management work order anomaly detection method.
[0043] The fifth aspect of the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method for detecting anomalies in bank operation and maintenance change management work orders.
[0044] The above technical solution provides a method for detecting anomalies in bank operation and maintenance change management work orders. This method automatically detects anomalies in work orders by acquiring different work order contents at different nodes according to the workflow of the operation and maintenance change management work order, thereby identifying anomalies in the work orders. The detection efficiency is high and the probability of detection errors is effectively reduced.
[0045] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description
[0046] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:
[0047] Figure 1 This is a flowchart of a bank operation and maintenance change management work order anomaly detection method provided by one embodiment of the present invention;
[0048] Figure 2 This is a flowchart of the change type anomaly detection method in the bank operation and maintenance change management work order anomaly detection method provided by one embodiment of the present invention;
[0049] Figure 3 This is a block diagram of a bank operation and maintenance change management work order filling anomaly detection device provided in one embodiment of the present invention. Detailed Implementation
[0050] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.
[0051] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.
[0052] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.
[0053] The method for detecting anomalies in bank operation and maintenance change management work orders provided in this application is applied in the operation and maintenance change management system to obtain operation and maintenance change management work orders from the operation and maintenance change management system for anomaly detection.
[0054] Figure 1 This is a flowchart of a bank operation and maintenance change management work order anomaly detection method provided by one embodiment of the present invention, as follows: Figure 1 As shown, the method includes:
[0055] Step 1: Obtain the content of the operation and maintenance change management work order filled in by the user.
[0056] Step 2: Verify whether the operation and maintenance change management work order is abnormal based on the content of the operation and maintenance change management work order and the first preset rule.
[0057] Operation and maintenance change management work orders are filled out by users on the operation and maintenance change management platform, then circulate to the change executor, who executes the change, and finally circulates to the change reviewer to complete the change and close the work order. The operation and maintenance change management work order anomaly detection method provided in this application obtains the content of the operation and maintenance change management work orders filled out by users from different nodes, and then performs anomaly detection.
[0058] The operation and maintenance change management work order is first filled out by the change initiator. During the process of filling out the work order, the initiator will fill in the planned change time. Therefore, at the initiator node, the operation and maintenance change management work order content that this application method needs to obtain includes: the planned change time.
[0059] During the anomaly detection process for planned time changes, the first step is to obtain the current time from the NTP server. An NTP server, or Network Time Protocol server, allows computers to synchronize with their server or clock source, providing highly accurate time correction. Therefore, the NTP server's time can be considered the standard time for the current moment.
[0060] Then, the current NTP server time is compared with the planned change time entered by the user. If the planned change time is earlier than the current NTP server time, the maintenance change management work order is considered abnormal. The planned change time is the execution time of the planned change, and the change can only be executed after the work order is approved. Therefore, the planned change time can only be a future time as of the time the work order is entered, not a past time. For example, if the current NTP server time is T, then if the maintenance personnel enter any time T-1 when filling out the maintenance change management work order, it is considered abnormal. Verifying the planned change time can effectively reduce the violation of executing the change before filling out the work order application.
[0061] In this embodiment, comparing the current NTP server time requires comparing both the time and date. Regular expressions are used in this embodiment to check for any time anomalies.
[0062] When the operations and maintenance initiator completes the operations and maintenance change management work order, they also fill in the change type and change risk factors. In this embodiment, the change type is divided into major change, routine change, standard change, and emergency change. Standard change and emergency change do not involve change risk factors; therefore, this application mainly focuses on whether major changes and routine changes are consistent with change risk factors. The user fills in the change type by selecting preset items. In this application, for ease of distinction, the change type filled in by the user is referred to as the first change type, and the change type obtained based on the change risk factors is referred to as the second change type.
[0063] When performing change type anomaly detection, such as Figure 2 As shown, first, the first change type and change risk factor on the operation and maintenance change management work order are obtained, and then it is determined whether the first change type is a major change or a routine change; if it is not a major change and is not a routine change, the verification ends.
[0064] If it is a major change or a routine change, then the second change type shall be determined based on the aforementioned change risk factors;
[0065] Compare the second change type with the first change type; if they are inconsistent, the operation and maintenance change management work order is deemed abnormal. The change type entered in the operation and maintenance change management work order must be consistent with the change risk factors.
[0066] In this embodiment, different change risk factors are set to measure change risk and thus determine the change type. Specific change risk factors include: business impact scope, business impact degree, probability of change success, rollback time, change implementation time (downtime required for implementation), change complexity, and number of customer IT users (affected by implementation or cancellation). Specifically, the business impact scope is scored based on the number of customer business modules that the change may affect; the business impact degree is scored based on the duration of customer service disruption and whether the impact actually occurs; the probability of change success is scored based on the test results and maturity of the changed portion; the rollback time is scored based on the rollback duration and ease of rollback; the change implementation time is scored based on the change duration; the change complexity is scored based on the amount of business support required for the change; and the number of customer IT users is scored based on the number of customers affected by the change and the number of their IT users.
[0067] In one embodiment of this application, the weight of business impact is 20%, the weight of business impact degree is 35%, the weight of the probability of successful change is 10%, the weight of rollback time is 10%, the weight of change implementation time is 10%, the weight of change complexity is 10%, and the weight of the number of customer IT users is 5%.
[0068] It should be noted that the scoring criteria and weights mentioned above are set based on operational and maintenance change experience, and the scoring criteria and weights need to be updated in a timely manner according to changes in services and needs.
[0069] In this embodiment of the application, determining the second change type based on the change risk factors includes:
[0070] Calculate the risk assessment value based on the aforementioned risk factors and the second preset rule;
[0071] If the risk assessment value is greater than or equal to the preset score, the second change type is determined to be a major change; otherwise, the second change type is determined to be a routine change. In one embodiment of this application, the maximum weighted total score of each change risk factor is 3 points, while the preset score is 2 points. When the risk assessment value is greater than or equal to 2 points, the risk level is high, and the change type is a major change. When the risk assessment value is between 0 and 2 points, the risk level is medium, and the change type is a routine change. The different risk assessment values divide the operation and maintenance change type into major changes and routine changes, quantifying the different changes for easy differentiation.
[0072] In this embodiment of the application, the step of calculating the risk assessment value based on the changed risk factors and the second preset rule includes:
[0073] The scores for different risk factors are determined based on the aforementioned risk factors and preset evaluation rules;
[0074] The scores of different risk factors are weighted and summed according to their respective weights to obtain the risk assessment value.
[0075] After the operations and maintenance initiator completes the operations and maintenance change management work order, it will be processed at different nodes. First, it will be processed by the operations and maintenance change implementer. At this node, it is necessary to obtain the change implementer information in the operations and maintenance change management work order content, and then obtain the actual implementer information of the operations and maintenance change corresponding to the change management work order from the change implementation database. The actual implementer information is compared with the change implementer information. If they are inconsistent, it is determined that the operations and maintenance change management work order is abnormal.
[0076] After an operation and maintenance change is implemented, it needs to be reviewed. The operation and maintenance change management work order is transferred to the review node. At this node, it is necessary to obtain the change reviewer information in the operation and maintenance change management work order content, and then obtain the real reviewer information of the operation and maintenance change corresponding to the change management work order from the change implementation database. The real reviewer information is compared with the change reviewer information. If they are inconsistent, it is determined that the operation and maintenance change management work order is abnormal.
[0077] In comparing whether the information of the actual implementer is consistent with the information of the changed implementer, and whether the information of the actual reviewer is consistent with the information of the changed reviewer, firstly, the name of the actual implementer is compared with the name of the changed implementer, and the name of the actual reviewer is compared with the name of the changed reviewer; if one of them is inconsistent, it is determined that the operation and maintenance change management work order is abnormal.
[0078] If all are consistent, then compare the group of the actual implementer with the group of the change implementer, and the group of the actual reviewer with the group of the change reviewer. If any one of them is inconsistent, then the operation and maintenance change management work order is considered abnormal. Duplicate names are common in enterprises. When detecting change implementers and change reviewers, adding group detection can quickly verify the change implementers and reviewers, effectively avoiding errors in detection results due to identical names.
[0079] According to the requirements for operation and maintenance change management, abnormalities in the implementer and reviewer of the change constitute serious violations of the change management and regulatory requirements. By testing the implementer and reviewer of the change, violations can be quickly identified.
[0080] After an operational change is completed, the system saves the actual change time. At this point, the system retrieves the approval process time and the actual change time displayed on the work order and compares them. If the actual change time is earlier than the approval process time, the operational change management work order is considered abnormal. Change execution requires approval; therefore, the actual change time must be a future time of the approval process time. Verifying the approval process time and the actual change time effectively reduces violations such as applying for and executing operational changes simultaneously, or executing operational changes before approval.
[0081] The above method can automatically detect anomalies in operation and maintenance change management work orders, improving the detection efficiency. In this method, operation and maintenance change management work orders deemed abnormal cannot be processed or closed, while those without anomalies can be processed and closed normally.
[0082] When an anomaly is detected in the operation and maintenance change management work order, an anomaly alarm can be triggered and abnormal data can be recorded. This allows the current operator to promptly correct any errors in the form and rectify mistakes in the execution and approval processes of operation and maintenance changes, thereby ensuring the compliance and accuracy of the bank's operation and maintenance change management.
[0083] like Figure 3 The image shows a bank operation and maintenance change management work order anomaly detection device provided by one embodiment of the present invention. The device includes:
[0084] The data acquisition module is used to acquire the content of the operation and maintenance change management work order filled in by the user;
[0085] The anomaly verification module is used to verify whether the operation and maintenance change management work order is abnormal based on the content of the operation and maintenance change management work order and the first preset rule;
[0086] The operation and maintenance change management work order content shall at least include: a first change type and change risk factors.
[0087] When verifying whether the operation and maintenance change management work order is abnormal, the anomaly verification module determines whether the first change type is a major change or a routine change; if it is neither a major change nor a routine change, the verification ends.
[0088] If it is a major change or a routine change, then the second change type shall be determined based on the aforementioned change risk factors;
[0089] The system compares the second change type with the first change type; if they do not match, the maintenance change management work order is deemed abnormal. This device can automatically acquire maintenance change management work orders and perform anomaly detection, resulting in high detection efficiency and effectively reducing the probability of detection errors.
[0090] In some embodiments, the data acquisition module specifically includes: a maintenance change management work order content acquisition module and an auxiliary data acquisition module.
[0091] The Operation and Maintenance Change Management Work Order Content Acquisition Module is used to acquire the planned change time, change implementer information, change reviewer information, approval process time, actual change time, first change type, and change risk factors;
[0092] The auxiliary data acquisition module is used to obtain the NTP server time, the actual implementer information, and the actual reviewer information when the user fills out the work order.
[0093] In some embodiments, the anomaly verification module includes at least a risk assessment value calculation module, used to determine the scores of different risk factors according to the changed risk factors and the judgment rules; and to perform a weighted summation of the scores of different risk factors according to the weights of different risk factors to obtain a risk assessment value.
[0094] The bank operation and maintenance change management work order anomaly detection device provided in this application can realize the compliance and accuracy check of bank operation and maintenance changes, improve the accuracy and efficiency of the inspection, and is simple to implement.
[0095] The present invention also provides a processor configured to execute the aforementioned bank operation and maintenance change management work order anomaly detection method.
[0096] The present invention also provides a machine-readable storage medium storing instructions that, when executed by a processor, configure the processor to perform the aforementioned bank operation and maintenance change management work order anomaly detection method.
[0097] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned method for detecting anomalies in bank operation and maintenance change management work orders.
[0098] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.
[0099] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.
[0100] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.
[0101] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.
[0102] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.
[0103] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.
[0104] Computer-readable media include both permanent and non-permanent, removable and non-removable media, which can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.
[0105] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.
[0106] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.
Claims
1. A method for detecting anomalies in bank operation and maintenance change management work orders, characterized in that, The method includes: Obtain the content of the operation and maintenance change management work order filled in by the user; Verify whether the operation and maintenance change management work order is abnormal based on the content of the operation and maintenance change management work order and the first preset rule; The operation and maintenance change management work order content shall at least include: a first change type and change risk factors. When verifying whether the operation and maintenance change management work order is abnormal, it is determined whether the first change type is a major change or a routine change; if it is neither a major change nor a routine change, the verification ends. If it is a major change or a routine change, then the second change type shall be determined based on the aforementioned change risk factors; Compare whether the second change type is consistent with the first change type; if they are inconsistent, determine that the operation and maintenance change management work order is abnormal. The step of determining the second change type based on the aforementioned change risk factors includes: Calculate the risk assessment value based on the aforementioned risk factors and the second preset rule; If the risk assessment value is greater than or equal to the preset score, the second change type is determined to be a major change; otherwise, the second change type is determined to be a routine change. The step of calculating the risk assessment value based on the changed risk factors and the second preset rule includes: The scores for different risk factors are determined based on the aforementioned risk factors and evaluation rules; The scores of different risk factors are weighted and summed according to their respective weights to obtain the risk assessment value.
2. The method for detecting anomalies in bank operation and maintenance change management work orders according to claim 1, characterized in that, The operation and maintenance change management work order content shall include at least: information of the person implementing the change and information of the person reviewing the change; Verify whether the maintenance change management work order is abnormal based on the content of the maintenance change management work order and the first preset rule, including: Retrieve the actual implementer and reviewer information of the operation and maintenance changes corresponding to the change management work orders from the change implementation database; Compare the information of the actual implementer with the information of the changed implementer, and the information of the actual reviewer with the information of the changed reviewer. If any of them are inconsistent, it is determined that the operation and maintenance change management work order is abnormal.
3. The method for detecting anomalies in bank operation and maintenance change management work orders according to claim 2, characterized in that, The comparison of whether the information of the actual implementer is consistent with the information of the changed implementer, and whether the information of the actual reviewer is consistent with the information of the changed reviewer, includes: Compare the names of the actual implementer and the changed implementer, and the names of the actual reviewer and the changed reviewer; if any of them are inconsistent, it is determined that the operation and maintenance change management work order is abnormal. If all are consistent, then compare whether the group of the actual implementer is consistent with the group of the change implementer, and whether the group of the actual reviewer is consistent with the group of the change reviewer. If one of them is inconsistent, then it is determined that the operation and maintenance change management work order is abnormal.
4. The method for detecting anomalies in bank operation and maintenance change management work orders according to claim 1, characterized in that, The content of the operation and maintenance change management work order shall at least include: the planned change time; Verify whether the maintenance change management work order is abnormal based on the content of the maintenance change management work order and the first preset rule, including: Get the current NTP server time; Compare the current NTP server time with the planned change time entered by the user. If the planned change time is earlier than the current NTP server time, then the operation and maintenance change management work order is considered abnormal.
5. The method for detecting anomalies in bank operation and maintenance change management work orders according to claim 1, characterized in that, The content of the operation and maintenance change management work order shall at least include: the approval process time and the actual change time; Verify whether the maintenance change management work order is abnormal based on the content of the maintenance change management work order and the first preset rule, including: Compare the approval process time with the actual change time. If the actual change time is earlier than the approval process time, then the operation and maintenance change management work order is considered to be abnormal.
6. The method for detecting anomalies in bank operation and maintenance change management work orders according to claim 1, characterized in that, The method further includes: When an anomaly is detected in the operation and maintenance change management work order, an anomaly alarm is triggered and the abnormal data is recorded.
7. A device for detecting anomalies in bank operation and maintenance change management work orders, characterized in that, The device includes: The data acquisition module is used to acquire the content of the operation and maintenance change management work order filled in by the user; The anomaly verification module is used to verify whether the operation and maintenance change management work order is abnormal based on the content of the operation and maintenance change management work order and the first preset rule; The operation and maintenance change management work order content shall at least include: a first change type and change risk factors. When verifying whether the operation and maintenance change management work order is abnormal, the anomaly verification module determines whether the first change type is a major change or a routine change; if it is neither a major change nor a routine change, the verification ends. If it is a major change or a routine change, then the second change type shall be determined based on the aforementioned change risk factors; Compare whether the second change type is consistent with the first change type; if they are inconsistent, determine that the operation and maintenance change management work order is abnormal. The step of determining the second change type based on the aforementioned change risk factors includes: Calculate the risk assessment value based on the aforementioned risk factors and the second preset rule; If the risk assessment value is greater than or equal to the preset score, the second change type is determined to be a major change; otherwise, the second change type is determined to be a routine change. The step of calculating the risk assessment value based on the changed risk factors and the second preset rule includes: The scores for different risk factors are determined based on the aforementioned risk factors and evaluation rules; The scores of different risk factors are weighted and summed according to their respective weights to obtain the risk assessment value.
8. A processor, characterized in that, The method is configured to perform the bank operation and maintenance change management work order anomaly detection method as described in any one of claims 1 to 6.
9. A machine-readable storage medium storing instructions thereon, characterized in that, When executed by the processor, this instruction causes the processor to be configured to perform the bank operation and maintenance change management work order anomaly detection method according to any one of claims 1 to 6.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the bank operation and maintenance change management work order anomaly detection method according to any one of claims 1 to 6.