Auditing management method, system and device based on knowledge graph and storage medium

Abstract

The invention provides an audit management method, system and device based on a knowledge graph and a storage medium. The audit management method comprises the steps of obtaining an audit task and a pre-constructed audit knowledge graph; obtaining element information of the audit task according to the audit task; matching audit data corresponding to the element information from the audit knowledge graph; and processing the audit task according to the audit data. According to the technical scheme, automatic processing and intelligent management of the auditing task are achieved through the knowledge graph technology and the intelligent processing method, the service requirement of the auditing task can be accurately known, auditing data matching of the auditing task is efficiently achieved, manual intervention is reduced, and the auditing efficiency is improved. The auditing efficiency is improved, the auditing quality is improved, the flexibility and adaptability are enhanced, and intelligent and automatic auditing management is realized.

Description

Technical Field

[0001] The present application relates to the field of audit management technology, and specifically, to an audit management method, system, device and computer-readable storage medium based on a knowledge graph. Background Art

[0002] Traditional audit management systems have many limitations, which seriously affect the efficiency and quality of audit work. These systems usually rely on manual audit process setting and manual data collection and analysis, resulting in long audit cycles and high costs. More importantly, they are difficult to adapt to the ever-changing regulatory environment and business needs, and lack the necessary flexibility and adaptability.

[0003] The audit management systems currently on the market are often limited to specific areas, with fixed functions and audit content, and cannot meet the requirements of flexible and fast audits. This rigid design makes it difficult for the system to cope with diverse audit tasks and evolving business environments. In addition, since the audit data structures and types of multiple data sources are different, it becomes extremely difficult to collect relevant audit data in tasks for different audit business types. This not only increases the workload of auditors, but may also lead to incomplete or inaccurate data analysis.

[0004] The existing audit management system also has obvious defects in the allocation of auditors. Most systems use a random allocation method, which does not take into account key factors such as the professional skills, experience, work efficiency and business saturation of different auditors. This extensive personnel allocation method not only fails to fully utilize the professional advantages of the audit team, but may also lead to uneven task allocation, thus affecting the overall audit efficiency and quality. Summary of the invention

[0005] In view of the above problems, the present invention provides a bank audit management method, system, device and storage medium based on knowledge graph to overcome the above problems or at least partially solve the above problems. The technical solution is as follows:

[0006] An audit management method based on knowledge graph, comprising:

[0007] Obtain audit tasks and pre-built audit knowledge graphs;

[0008] According to the audit task, element information of the audit task is obtained;

[0009] Matching the audit data corresponding to the element information from the audit knowledge graph;

[0010] The audit task is processed according to the audit data.

[0011] Furthermore, the present application also proposes that extracting the element information of the audit task according to the audit task includes: determining the business type corresponding to the audit task according to the audit task; generating a template based on the business type requirements corresponding to the business type, processing the audit task, and obtaining the element information corresponding to the audit task.

[0012] Furthermore, the present application also proposes that the business type demand generation template is pre-set.

[0013] Furthermore, the present application also proposes that the method of pre-constructing the audit knowledge graph includes: obtaining financial audit data and business type demand information from each data source; determining the first relationship data between the data corresponding to the financial audit data and the data; determining the second relationship data between the demand corresponding to the business type demand information and the demand; determining the third relationship data between the data corresponding to the financial audit data and the business type demand information and the demand; and generating the audit knowledge graph based on the first relationship data, the second relationship data and the third relationship data.

[0014] Furthermore, the present application also proposes that the processing of the audit task according to the audit data includes: allocating auditors according to the audit data and the business type requirements.

[0015] Furthermore, the present application also proposes that the audit data includes auditor capability model data and current workload data; and the business type requirements include audit task difficulty level data and priority level data.

[0016] Furthermore, the present application also proposes an audit management system based on a knowledge graph, including: an acquisition module, used to acquire audit tasks and a pre-built audit knowledge graph; a first processing module, used to obtain element information of the audit task based on the audit task; a second processing module, used to match the audit data corresponding to the element information based on the audit knowledge graph; and a third processing module, used to process the audit task based on the audit data.

[0017] Furthermore, the present application also proposes that the third processing module includes: an audit risk processing unit, used to identify potential risk points of the audit task based on the audit data; and an auditor allocation unit, used to allocate auditors based on the audit data and the business type requirements.

[0018] Furthermore, the present application also proposes an audit management device based on a knowledge graph, including a processor and a memory; the memory stores a computer program thereon; the processor is used to execute one or more programs stored in the memory to implement the steps of the above-mentioned audit management method based on the knowledge graph.

[0019] Furthermore, the present application also proposes a computer-readable storage medium, which stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the above-mentioned knowledge graph-based audit management method.

[0020] Beneficial Effects

[0021] The present invention provides an audit management method, system, device and storage medium based on knowledge graph, including obtaining an audit task and a pre-constructed audit knowledge graph; obtaining element information of the audit task according to the audit task; matching the audit data corresponding to the element information from the audit knowledge graph; and processing the audit task according to the audit data. The technical solution of the present invention realizes the automated processing and intelligent management of audit tasks by utilizing knowledge graph technology and intelligent processing methods, can accurately understand the business requirements of the audit task, efficiently realize audit data matching of the audit task, reduce manual intervention, improve audit efficiency, enhance audit quality, enhance flexibility and adaptability, and realize intelligent and automated audit management. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained like these drawings without paying creative work.

[0023] Figure 1 A flowchart of an audit management method based on knowledge graph according to an embodiment of the present invention;

[0024] Figure 2 The present invention is a schematic diagram of the structure of an audit management system based on knowledge graph according to an embodiment of the present invention. DETAILED DESCRIPTION

[0025] An audit management method based on a knowledge graph in an embodiment of the present application is described below in conjunction with the accompanying drawings. The terms used in the implementation method part of the present application are only used to explain the specific embodiments of the present application and are not intended to limit the present application.

[0026] The terms "first", "second" etc. in the present application are used to distinguish similar objects, and need not be used to describe a specific order or sequential order. It should be understood that the terms used in this way can be interchangeable in appropriate circumstances, and this is only to describe the distinction mode adopted by the objects of the same attributes when describing in the embodiments of the present application. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, so that the process, method, system, product or equipment comprising a series of units need not be limited to those units, but may include other units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0027] See also Figure 1 , a schematic diagram of an audit management method based on a knowledge graph is provided, the method can be applied to a network environment such as a server, a cloud service end, etc. of the prior art. This embodiment is described by taking the method applied to a server as an example. An audit management method based on a knowledge graph in this embodiment includes the following steps:

[0028] S101, obtain audit tasks and pre-built audit knowledge graph;

[0029] In this step, the audit task may be an audit task input by an external system connected to the current server, for example, an audit task submitted by the external system through a user interface or an application.

[0030] In actual applications, in banking systems, the audit task is usually definite, generally including the audit purpose, audit scope, audit standards and criteria, and audit business type. It can be presented in the form of a form or other existing methods, and there is no restriction here. The audit task is generally expressed in an unstructured natural language form.

[0031] In other embodiments, the present application also proposes a method for pre-constructing an audit knowledge graph: obtaining financial audit data and business type demand information from each data source; determining the first relationship data between the data corresponding to the financial audit data and the data; determining the second relationship data between the demand corresponding to the business type demand information and the demand; determining the third relationship data between the data corresponding to the financial audit data and the business type demand information and the demand; and generating an audit knowledge graph based on the first relationship data, the second relationship data, and the third relationship data.

[0032] In practical applications, obtaining financial audit data and business type demand information from various data sources is the basis. By determining the first relationship data between the data corresponding to the financial audit data and the data, the correlation between the financial data can be clarified; by determining the second relationship data between the demand corresponding to the business type demand information and the demand, the correlation between the business demand can be clarified; by determining the third relationship data between the data corresponding to the financial audit data and the business type demand information and the demand, the correlation between the financial data and the business demand can be realized. The audit knowledge graph constructed based on these relationship data can effectively integrate the financial audit data and the business type demand information, thereby solving the problem of how to construct an audit knowledge graph that can effectively integrate the financial audit data and the business type demand information.

[0033] Among them, obtaining financial audit data and business type demand information from each data source can be achieved in a variety of ways, for example, automatically grabbing data from different data sources through an API interface, and the data source can be an ERP system, a financial system, a database, etc., or entering the data into the system by manual import. Determining the first relationship data between the data corresponding to the financial audit data and the data can be achieved through data analysis and mining technology, for example, using an association rule mining algorithm to identify the correlation between financial data. Determining the second relationship data between the demand corresponding to the business type demand information and the demand can be achieved through business demand analysis and modeling technology, for example, using a demand matrix analysis method to identify the correlation between different business demands. Determining the third relationship data between the data corresponding to the financial audit data and the business type demand information and the demand can be achieved through multidimensional data association analysis technology, for example, using a multidimensional association analysis algorithm to identify the correlation between financial data and business demands. This application can achieve effective integration of financial audit data and business type demand information by generating an audit knowledge graph, solve the problem of data integration difficulties in traditional audit management systems, and improve audit efficiency and accuracy. Compared with the prior art, the advantage of this application is that it can automatically process and integrate multi-source data and provide a flexible and efficient audit solution.

[0034] S102, obtaining element information of the audit task according to the audit task;

[0035] In this step, the business type corresponding to the audit task is determined according to the audit task. A template is generated based on the business type requirements corresponding to the business type, and the audit task is processed to obtain element information corresponding to the audit task. The element information includes various types of data and requirements related to the audit task.

[0036] In other implementations, step S102 includes:

[0037] S112, determining the business type corresponding to the audit task according to the audit task;

[0038] S122. Generate a template based on the business type requirement corresponding to the business type, process the audit task, and obtain element information corresponding to the audit task.

[0039] In this step, the technical solution of the present application is implemented in the following manner: First, obtain the audit task and determine the business type corresponding to the audit task. Then, generate a template based on the business type requirements corresponding to the business type. Specifically, the corresponding template can be generated by a pre-set template library, or a template can be dynamically generated according to real-time requirements. Then, the audit task is processed using the generated template to obtain the element information corresponding to the audit task. As a preferred implementation, the generation of the template can take into account the characteristics and requirements of the business type to ensure the pertinence and effectiveness of the template.

[0040] The technical solution of this application effectively solves the problem of extracting element information from audit tasks by determining the business type and generating corresponding templates. Compared with the prior art, the advantages of this application are that it improves the efficiency and accuracy of audit task processing, reduces the necessity of manual intervention, adapts to the needs of different business types, and has strong flexibility and adaptability. Therefore, this application has important application value in the audit management system.

[0041] In other implementations, the business type demand generation template is preset.

[0042] In actual applications, corresponding templates have been pre-set for different business type requirements. These pre-set templates are called in the actual audit task processing, thereby improving the efficiency and accuracy of audit task processing. By pre-setting business type requirements to generate templates, different types of audit tasks can be quickly matched and processed, reducing the time and possible errors of manually setting templates. This pre-set template can be directly called when processing audit tasks, ensuring the consistency and standardization of audit task processing, thereby solving the technical problem of how to generate templates corresponding to business type requirements.

[0043] Specifically, the pre-set business type demand generation template may include but is not limited to a financial audit template, a compliance audit template, a performance audit template, etc. Each template contains the audit elements, audit standards, audit steps, etc. required for the business type. Generally, this can be achieved in the following ways:

[0044] 1. By analyzing historical audit data and business requirements, we can extract common requirements for different business types and pre-set corresponding templates;

[0045] 2. Use expert experience and industry standards to develop templates that meet the needs of specific business types;

[0046] 3. Automatically generate and optimize business type demand templates through machine learning algorithms.

[0047] In another embodiment, the preset business type requirement generation template can be dynamically adjusted and optimized according to actual needs. For example, if new requirements or problems are found during the audit process, the template can be updated in time to ensure the timeliness and accuracy of the template.

[0048] S103, matching the audit data corresponding to the element information from the audit knowledge graph;

[0049] In this step, the audit data corresponding to the element information is matched from the audit knowledge graph. The audit data includes information such as auditor capability model data and current workload data. Through matching, data related to the audit task can be quickly found for the next step of processing.

[0050] S104: Process the audit task according to the audit data.

[0051] In this step, the audit tasks are processed according to the audit data. Specifically, auditors can be assigned according to the audit data and business type requirements. For example, the assignment of auditors not only considers the difficulty level and priority level of the audit tasks, but also the auditors' professional skills, experience, work efficiency, and current workload. In this way, auditors can be assigned more scientifically and reasonably, improving audit efficiency.

[0052] In another embodiment, step S104 includes:

[0053] Auditors are assigned based on the audit data and the business type requirements.

[0054] In this step, auditors are assigned according to audit data and business type requirements. By matching audit data with business type requirements, auditors are reasonably assigned so that audit tasks can be completed efficiently. This technical solution uses information on audit data and business type requirements to ensure that the allocation of auditors is more scientific and reasonable, thereby improving audit efficiency and solving the problem of inefficiency caused by random allocation of auditors in traditional audit management systems.

[0055] In practical applications, this can be done in the following ways: One way is to assign auditors after comprehensive evaluation based on the auditors' competency model data and current workload data, combined with the difficulty level data and priority level data of the audit tasks. Another way is to generate a template using pre-set business type requirements, process the audit tasks, obtain the element information corresponding to the audit tasks, and then assign personnel. It is also possible to obtain financial audit data and business type requirement information from various data sources by constructing an audit knowledge graph, and generate an audit knowledge graph as the basis for assigning personnel.

[0056] In another embodiment, the audit data includes auditor capability model data and current workload data; the business type requirements include the audit task difficulty level data and priority level data.

[0057] In practical applications, auditor competency model data can be obtained by analyzing and modeling auditors' historical work records, professional skills, training experience and other data. Current workload data can be updated in real time through information such as the number of tasks currently being processed by auditors and the complexity of tasks. Audit task difficulty level data can be classified according to factors such as the complexity of the task and the business areas involved, and priority level data can be set according to factors such as the urgency of the task and business needs. For example, when assigning audit tasks, the system will first select auditors who meet the task requirements from the auditor competency model data based on the difficulty level and priority level of the audit task, and then select auditors with lower workloads for task assignment based on the current workload data. In this way, it is ensured that the assigned auditors not only have the ability to complete the task, but also can work under a reasonable workload, avoiding auditors from being overworked or wasting resources.

[0058] Compared with the traditional random allocation method, this application achieves a more scientific and reasonable allocation method for auditors by introducing auditor capability model data and current workload data, combined with audit task difficulty level data and priority level data. This can significantly improve audit efficiency and quality, and ensure that audit tasks can be completed in a timely and efficient manner.

[0059] In one embodiment, Figure 2 As shown, an audit management system based on knowledge graph is provided, including:

[0060] An acquisition module 501 is used to acquire audit tasks and pre-built audit knowledge graphs;

[0061] The first processing module 502 is used to obtain element information of the audit task according to the audit task;

[0062] The second processing module 503 is used to match the audit data corresponding to the element information based on the audit knowledge graph;

[0063] The third processing module 504 is used to process the audit task according to the audit data.

[0064] In practical applications, the acquisition module 501 acquires the audit task and the pre-built audit knowledge graph through external or internal data transmission. The first processing module 502 can extract key element information from the audit task described in text through natural language processing technology, and can use data cleaning and standardization technology to ensure the accuracy and consistency of element information. The second processing module 503 can use graph database technology to quickly and efficiently match data based on the pre-built audit knowledge graph. The third processing module 504 can combine machine learning algorithms to automatically generate audit reports or perform specific operation steps for audit tasks based on matched audit data.

[0065] The functions of each functional module of the knowledge graph-based audit management system provided in the above embodiments of the present application can be realized through the above-mentioned method steps. Therefore, the specific working process and beneficial effects of each unit in the knowledge graph-based audit management system provided in the embodiments of the present application will not be repeated here.

[0066] In other implementations, the third processing module 503 includes:

[0067] An audit risk processing unit 513, used to identify potential risk points of the audit task according to the audit data;

[0068] The auditor allocation unit 523 is used to allocate auditors according to the audit data and the business type requirements.

[0069] In practical applications, the implementation of the audit risk processing unit 513 may include training historical audit data through a machine learning algorithm, establishing a risk identification model, and inputting current audit data into the model for risk assessment. The auditor allocation unit 523 can automatically match the most suitable auditor based on preset rules or algorithms, taking into account factors such as the auditor's professional skills, experience, and current workload. For example, an auditor capability model can be constructed to dynamically adjust the allocation of auditors in combination with current workload data and business type requirements. This application realizes the identification of potential risk points in audit tasks and the reasonable allocation of auditors by introducing the audit risk processing unit 513 and the auditor allocation unit 523. Compared with the prior art, this application can more accurately identify risk points in audit tasks, avoid the subjectivity and uncertainty of manual judgment, and at the same time improve the efficiency and quality of audit work and reduce audit costs by reasonably allocating auditors.

[0070] The present invention also provides a server, comprising a processor and a memory;

[0071] The memory stores a computer program.

[0072] The processor is used to execute one or more programs stored in the memory to implement the steps of the knowledge graph-based audit management method in the above embodiment.

[0073] The present invention also provides a computer-readable storage medium, which stores one or more programs. The one or more programs can be executed by one or more processors to implement the steps of the knowledge graph-based audit management method in the above embodiment.

[0074] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0075] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0076] 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 can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, 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 of various embodiments of the present invention.

[0077] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An audit management method based on knowledge graph, characterized in that: include: Obtain audit tasks and pre-built audit knowledge graphs; According to the audit task, element information of the audit task is obtained; Matching the audit data corresponding to the element information from the audit knowledge graph; The audit task is processed according to the audit data.

2. The audit management method based on knowledge graph according to claim 1 is characterized in that: The extracting element information of the audit task according to the audit task includes: According to the audit task, determining the business type corresponding to the audit task; Based on the business type requirement generation template corresponding to the business type, the audit task is processed to obtain element information corresponding to the audit task.

3. The audit management method based on knowledge graph according to claim 2 is characterized in that: The business type demand generation template is preset.

4. The audit management method based on knowledge graph according to claim 2 is characterized in that: The method of pre-building the audit knowledge graph includes: Obtain financial audit data and business type demand information from various data sources; Determine first relationship data between data and data corresponding to the financial audit data; Determine the demand corresponding to the business type demand information and the second relationship data of the demand; Determine third relationship data between the data corresponding to the financial audit data and the business type requirement information and the requirement; The audit knowledge graph is generated based on the first relationship data, the second relationship data and the third relationship data.

5. The audit management method based on knowledge graph according to claim 1 is characterized in that: The processing of the audit task according to the audit data includes: Auditors are assigned based on the audit data and the business type requirements.

6. The audit management method based on knowledge graph according to claim 5 is characterized in that: The audit data includes auditor capability model data and current workload data; The business type requirements include the audit task difficulty level data and priority level data.

7. An audit management system based on knowledge graph, characterized in that: include: The acquisition module is used to obtain audit tasks and pre-built audit knowledge graphs; A first processing module, used for obtaining element information of the audit task according to the audit task; A second processing module is used to match the audit data corresponding to the element information based on the audit knowledge graph; The third processing module is used to process the audit task according to the audit data.

8. The knowledge graph-based audit management system according to claim 7, characterized in that: The third processing module comprises: An audit risk processing unit, used to identify potential risk points of the audit task based on the audit data; The auditor allocation unit is used to allocate auditors according to the audit data and the business type requirements.

9. An audit management device based on knowledge graph, characterized in that: Including processor and memory; The memory has a computer program stored thereon; The processor is used to execute one or more programs stored in the memory to implement the steps of the knowledge graph-based audit management method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the knowledge graph-based audit management method as described in any one of claims 1 to 6.

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