CN118261564A - Intelligent auditing authentication management method, system, equipment and medium - Google Patents
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Abstract
The application relates to an intelligent auditing authentication management method, system, equipment and medium. The method is executed by an intelligent audit authentication management system, which comprises the following steps: the system comprises an application acceptance module, an authentication task management module, an audit authentication management module, an audit report management module, an authentication certificate management module and an audit case management module. The method can support the authentication auditor to carry out on-site audit work, automatically judge whether audit findings filled by the auditor accord with standard regulations according to historical audit cases in the audit authentication process, guide the canonical expression of audit findings according to the judgment results, furthest reduce the phenomenon of audit inaccuracy caused by insufficient personal ability of the auditor and insufficient understanding of standard clauses, and improve the effectiveness of audit authentication results.
Description
Technical Field
The application relates to the technical field of audit authentication, in particular to an intelligent audit authentication management method, system, equipment and medium.
Background
Along with the deep fusion and application of the new generation information technology in various fields, the auditing and authentication modes of the traditional management system, products and services are remarkably changed, and the auditing and authentication work gradually tends to standardization, flow and intellectualization. By developing auditing software, a standard auditing authentication standard, a standardized workflow and a matched informationized business system are formed, and the process is gradually changed from relying on professional knowledge and auditing experience of people to relying on professional auditing tools to realize automatic and intelligent auditing. On one hand, the method can assist auditors to quickly and accurately judge problems and risks faced by enterprises; on the other hand, the automatic statistical analysis is carried out on the audit data, so that the efficiency and the quality of audit and authentication work can be effectively improved, and the comprehensive development of the audit and authentication work is supported; and the auditing data of different clients can be subjected to centralized analysis and benchmarking, so that technical support is provided for an auditing operation long-acting mechanism.
However, the research of the related technology of intelligent audit certification is still in a starting stage, and many development designs are not perfect and deep enough. At present, during the verification and authentication process, when an authentication auditor carries out on-site verification work, the phenomenon of non-fair verification caused by insufficient personal ability of the auditor and insufficient understanding of verification clauses can occur, meanwhile, the conventional intelligent verification and authentication process does not require standardized filling of verification findings, dynamic verification is not carried out on formed verification cases, updating is carried out at all times, verification findings are automatically judged by not applying the verification cases during the verification process, and therefore verification effectiveness and verification creditability are reduced, and verification results are affected.
Disclosure of Invention
Based on the above, it is necessary to provide an intelligent audit authentication management method, system, device and medium for solving the above technical problems.
An intelligent audit certification management system, the system comprising: the system comprises an application acceptance module, an authentication task management module, an audit authentication management module, an audit report management module, an authentication certificate management module and an audit case management module;
The application acceptance module is used for accepting authentication applications submitted by organizations and performing autonomous review;
the certification task management module is used for making and checking a certification scheme according to the certification application after the review passes, selecting a checking group owner and a checking group member, making a detailed checking plan and checking the checking plan;
The auditing certification management module is used for enabling an auditor to carry out auditing work, filling auditing discovery in a standardized way, constructing and training an auditing discovery classification model based on supervised learning according to historical auditing cases to analyze and calculate the auditing discovery, automatically judging whether the auditing discovery meets standard rules or not, and feeding back a judging result to the auditor for rechecking when the judging result is that the auditing discovery does not meet the standard rules; when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed;
the audit report management module is used for automatically generating audit reports according to audit findings after the audit work is finished, transmitting the audit reports to authentication decision staff of the authentication mechanism for confirmation, and transmitting the audit reports to the authentication certificate management module after the confirmation is correct;
The authentication certificate management module is used for automatically generating an authentication certificate according to the audit report;
and the auditing case management module is used for when the auditor does not agree with the judging result of auditing discovery or when a certain period is reserved, organizing experts to review the historical auditing case, classifying and optimizing the historical auditing case by combining cluster analysis and reinforcement learning algorithm, performing iterative calculation, and gradually optimizing the same-category problems to judge.
In one embodiment, the authentication task management module is specifically configured to:
An audit group owner and an audit team member are designated to carry out audit work according to the establishment and audit certification scheme of the certification application; after logging in the personal account, the auditing group owner checks the authentication scheme and formulates an auditing plan, sends the auditing plan to an authentication project manager of the authentication institution for confirmation, and sends the auditing plan to the personal account of the appointed auditing group owner after confirmation, and the auditing group owner obtains the auditing plan and the historical auditing condition through logging in the personal account.
In one embodiment, constructing and training an audit discovery classification model based on supervised learning according to historical audit cases to analyze and calculate audit discovery, automatically judging whether the audit discovery meets standard specifications, and comprising the following steps:
Constructing an audit discovery classification model based on supervised learning; the audit discovery classification model comprises an audit discovery preprocessing unit, a marking unit and a classification unit, wherein the audit discovery preprocessing unit is used for extracting audit discovery characteristics in historical audit cases and carrying out data cleaning, data standardization or normalization processing; the marking unit is used for marking the auditing discovery as two types of labels of compliance and non-compliance according to whether the auditing discovery of the historical auditing case accords with the standard regulation; the classifying unit is used for judging the label to which the auditing discovery feature belongs;
Training and optimizing the audit discovery classification model through learning the mapping relation between the audit discovery features and the labels to obtain a trained audit discovery classification model;
And extracting the characteristics of the new audit discovery through the trained audit discovery classification model and automatically classifying to judge whether the new audit discovery accords with the standard specification.
In one embodiment, the method for classifying and optimizing the historical auditing case by combining the cluster analysis and the reinforcement learning algorithm and performing iterative computation to gradually optimize the same class problem for judgment comprises the following steps:
Carrying out data preprocessing on the historical auditing case;
applying a cluster analysis algorithm to perform initial classification on the preprocessed historical auditing cases, and generating a cluster center for each category obtained by the initial classification;
Constructing and training a reinforcement learning model in the reinforcement learning environment, adjusting the distribution and the category division of the current historical auditing case by the reinforcement learning model at each time step, updating the distribution and the category division of the historical auditing case by the reinforcement learning environment according to expert auditing feedback, feeding back rewards to the reinforcement learning model, and updating an adjusting strategy of the category division of the historical auditing case by the reinforcement learning model according to rewards;
After a certain training round or reaching a preset condition, the optimal adjustment strategy obtained by applying the reinforcement learning model is used for reclassifying the historical auditing cases, and the auditing discovery classification model is retrained, adjusted and optimized according to the historical auditing cases of different categories;
And the organizing expert reviews the current audit discovery classification model according to a preset period, provides a reward function for updating the reinforcement learning environment according to the review result, and continuously optimizes the classification of the historical audit cases and the audit discovery classification model according to the reward function.
In one embodiment, the system further comprises an audit criteria management module for updating and maintaining audit criteria.
In one embodiment, the system further comprises an auditing certification personnel management module, which is used for performing professional classification on the organization types which can be audited by the auditor according to the profession, the title, the working experience and the auditing experience of the auditor, and performing technical classification on the auditing post where the auditor is located.
In one embodiment, the system further comprises an audit quality analysis module for statistically analyzing the number of severely non-conforming and generally non-conforming items found in all authentication audit tasks, and continuously tracking audit quality conditions.
An intelligent audit authentication management method, the method is executed by the intelligent audit authentication management system, and the method comprises the following steps:
The application acceptance module accepts an authentication application submitted by an organization and performs autonomous review;
after the review passes, an authentication scheme is established and audited through the authentication task management module according to the authentication application, an audit group owner and an audit group member are selected, a detailed audit plan is established, and audit plan approval is carried out;
carrying out auditing work through an auditing certification management module, standardizing filling auditing discovery, constructing and training an auditing discovery classification model based on supervised learning according to historical auditing cases to analyze and calculate the auditing discovery, automatically judging whether the auditing discovery accords with standard regulations, and feeding back a judging result to an auditor for rechecking when the auditing discovery does not accord with the standard regulations; when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed;
after the auditing work is finished, automatically generating an auditing report in an auditing report management module according to auditing discovery, transmitting the auditing report to an authentication decision maker of an authentication institution for confirmation, transmitting the auditing report to an authentication certificate management module after confirmation is correct, and automatically generating an authentication certificate in the authentication certificate management module according to the auditing report;
and when the auditor does not agree with the judgment result of the audit discovery, or when a certain period is reserved, the audit case management module organizes experts to review the historical audit cases, and the historical audit cases are classified, optimized and iteratively calculated by combining cluster analysis and reinforcement learning algorithm, so that the same-category problems are gradually optimized to judge.
A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:
The application acceptance module accepts an authentication application submitted by an organization and performs autonomous review;
after the review passes, an authentication scheme is established and audited through the authentication task management module according to the authentication application, an audit group owner and an audit group member are selected, a detailed audit plan is established, and audit plan approval is carried out;
carrying out auditing work through an auditing certification management module, standardizing filling auditing discovery, constructing and training an auditing discovery classification model based on supervised learning according to historical auditing cases to analyze and calculate the auditing discovery, automatically judging whether the auditing discovery accords with standard regulations, and feeding back a judging result to an auditor for rechecking when the auditing discovery does not accord with the standard regulations; when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed;
after the auditing work is finished, automatically generating an auditing report in an auditing report management module according to auditing discovery, transmitting the auditing report to an authentication decision maker of an authentication institution for confirmation, transmitting the auditing report to an authentication certificate management module after confirmation is correct, and automatically generating an authentication certificate in the authentication certificate management module according to the auditing report;
and when the auditor does not agree with the judgment result of the audit discovery, or when a certain period is reserved, the audit case management module organizes experts to review the historical audit cases, and the historical audit cases are classified, optimized and iteratively calculated by combining cluster analysis and reinforcement learning algorithm, so that the same-category problems are gradually optimized to judge.
A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
The application acceptance module accepts an authentication application submitted by an organization and performs autonomous review;
after the review passes, an authentication scheme is established and audited through the authentication task management module according to the authentication application, an audit group owner and an audit group member are selected, a detailed audit plan is established, and audit plan approval is carried out;
The auditing personnel develop auditing work through an auditing certification management module, the auditing findings are filled in a standardized way, an auditing finding classification model based on supervision learning is constructed and trained according to historical auditing cases to analyze and calculate the auditing findings, whether the auditing findings meet standard regulations or not is automatically judged, and when the judging result is that the auditing findings do not meet the standard regulations, the judging result is fed back to the auditing personnel to review; when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed;
after the auditing work is finished, automatically generating an auditing report in an auditing report management module according to auditing discovery, transmitting the auditing report to an authentication decision maker of an authentication institution for confirmation, transmitting the auditing report to an authentication certificate management module after confirmation is correct, and automatically generating an authentication certificate in the authentication certificate management module according to the auditing report;
and when the auditor does not agree with the judgment result of the audit discovery, or when a certain period is reserved, the audit case management module organizes experts to review the historical audit cases, and the historical audit cases are classified, optimized and iteratively calculated by combining cluster analysis and reinforcement learning algorithm, so that the same-category problems are gradually optimized to judge.
The application provides an intelligent auditing and authentication management method, system, equipment and medium. The application acceptance module and the authentication task management module can automatically accept and review authentication applications and formulate an authentication scheme and an audit plan according to the authentication applications, so that the acceptance efficiency of the authentication applications is improved. In the process of auditing and authenticating, on-site auditing work is carried out through an auditing and authenticating management module, auditing findings are filled in a standardized manner, and an auditing finding classification model based on supervised learning is constructed and trained according to historical auditing cases to automatically judge whether the auditing findings filled by auditors meet standard regulations or not, and the normative expression of the auditing findings is guided according to the judging result, so that the phenomena of auditing and unfairness caused by insufficient personal ability of the auditors and insufficient understanding of standard clauses can be reduced to the greatest extent, and the effectiveness of auditing and authenticating results is improved. And the auditing case management module is used for carrying out classification optimization and iterative computation on the historical auditing case according to feedback of auditors or by periodically combining clustering analysis and reinforcement learning algorithm, so that the accuracy of the historical auditing case can be maintained, and the accuracy and the efficiency of standard standardization judgment of auditing discovery can be improved. Further, after the auditing is finished, an auditing report and an authentication certificate are automatically generated through an auditing report management module and an authentication certificate management module, so that the intelligent auditing and authentication efficiency is improved, and the auditing cost is reduced.
Drawings
FIG. 1 is a schematic diagram of an embodiment of an intelligent audit authentication management system;
FIG. 2 is an internal block diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
In one embodiment, as shown in FIG. 1, an intelligent audit certification management system is provided, the system comprising: the system comprises an application acceptance module 101, an authentication task management module 102, an audit authentication management module 103, an audit report management module 104, an authentication certificate management module 105 and an audit case management module 106.
The application acceptance module 101 is configured to accept an authentication application submitted by an organization and perform an autonomous review.
And the certification task management module 102 is used for making and checking a certification scheme according to the certification application, selecting a checking group owner and a checking group member, making a detailed checking plan and checking the checking plan after the review is passed.
Specifically, an authentication scheme is formulated and audited according to the authentication application, and an audit group owner and an audit group member are designated to carry out audit work; after logging in the personal account, the auditing group owner checks the authentication scheme and formulates an auditing plan, sends the auditing plan to an authentication project manager of the authentication institution for confirmation, and sends the auditing plan to the personal account of the appointed auditing group owner after confirmation, and the auditing group owner obtains the auditing plan and the historical auditing condition through logging in the personal account.
It can be understood that by automatically accepting the review certification application and making and checking the certification scheme according to the certification application, the certification auditor can be supported to carry out on-site checking work, and the acceptance efficiency of the certification application is improved.
The audit certification management module 103 is used for enabling an auditor to carry out audit work, filling audit discovery in a standardized manner, constructing and training an audit discovery classification model based on supervised learning according to historical audit cases to analyze and calculate the audit discovery, automatically judging whether the audit discovery meets standard rules, and feeding back a judgment result to the auditor for rechecking when the judgment result is that the audit discovery does not meet the standard rules; and when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed.
The method comprises the steps of constructing and training an audit discovery classification model based on supervised learning according to historical audit cases to analyze and calculate audit discovery, automatically judging whether the audit discovery accords with standard regulations, and comprising the following steps:
(1) Constructing an audit discovery classification model based on supervised learning; the audit discovery classification model comprises an audit discovery preprocessing unit, a marking unit and a classification unit, wherein the audit discovery preprocessing unit is used for extracting audit discovery characteristics in historical audit cases and carrying out data cleaning, data standardization or normalization processing; the marking unit is used for marking the auditing discovery as two types of labels of compliance and non-compliance according to whether the auditing discovery of the historical auditing case accords with the standard regulation; the classifying unit is used for judging the label to which the audit discovery feature belongs.
Specifically, the extracted audit discovery features comprise the type, severity, involved business links, frequency of violations, difficulty of rectification and the like of the audit discovery, so that the features can be ensured to effectively reflect the essential attributes of the audit discovery and the association of the essential attributes with compliance. Data cleansing includes processing missing values (filling, deleting, etc.), outliers (identifying and correcting or culling), duplicate values (removing), ensuring data quality. The purpose of the data normalization or normalization process is to make features of different scales comparable.
(2) And training and optimizing the audit discovery classification model through learning the mapping relation between the audit discovery features and the labels to obtain a trained audit discovery classification model.
In particular, the audit discovery features are partitioned into training and validation sets (or further partitioned into test sets), typically using a cross-validation approach to avoid overfitting.
The training set is trained using a logistic regression model. The goal of the model is to learn the mapping between the audit found features and the tags, i.e. find a function f (X) =p (y= 1|X), where X represents the feature vector of audit found, y represents whether a tag (0 or 1) is compliant, and P (y= 1|X) represents the probability of audit found compliance given feature X.
The model performance is evaluated on a validation set, and commonly used evaluation indexes include accuracy, recall, F1 score, AUC-ROC curve, and the like. Model optimization is performed by evaluating results to adjust model parameters (such as regularization coefficients, learning rates, etc.) or to try different feature combinations, and by verifying performance feedback on the set.
(3) And extracting the characteristics of the new audit discovery through the trained audit discovery classification model and automatically classifying to judge whether the new audit discovery accords with the standard specification.
Specifically, for new audit findings, the same audit finding features are extracted and input into a trained logistic regression model, which outputs the probability of compliance of the audit finding. And converting the probability into category judgment (compliance or non-compliance) according to a set threshold (such as 0.5) or in combination with service experience, and using the probability as a prediction result for judging whether the new audit discovery meets the standard regulation.
It can be understood that through the audit discovery classification model based on supervised learning, the newly-appeared audit discovery can be effectively analyzed and calculated by using the historical audit case, so that an auditor can be assisted to judge whether the audit discovery meets the standard regulation, the phenomenon of inaccurate audit caused by insufficient personal ability of the auditor and insufficient understanding of standard clauses can be reduced to the greatest extent, and the effectiveness of audit authentication results is improved.
And the audit report management module 104 is configured to automatically generate an audit report according to audit discovery after the audit work is finished, send the audit report to a certification decider of the certification authority for confirmation, and send the audit report to the certification certificate management module 105 after the confirmation is correct.
The authentication certificate management module 105 is configured to automatically generate an authentication certificate according to the audit report.
It can be understood that after the auditing is finished, the auditing report and the authentication certificate are automatically generated, so that the intelligent auditing and authentication efficiency is improved, and the auditing cost is reduced.
And the auditing case management module 106 is used for when the auditor does not agree with the judging result of auditing discovery or when a certain period is reserved, the organization expert reviews the historical auditing case, and the historical auditing case is classified, optimized and iteratively calculated by combining the cluster analysis and the reinforcement learning algorithm to gradually optimize the same-category problems for judging.
Specifically, the method combines cluster analysis and reinforcement learning algorithm to classify, optimize and iterate the historical auditing case, gradually optimize and judge the same class of problems, and comprises the following steps:
(1) Performing data preprocessing on the historical auditing case, including preprocessing operations such as feature extraction, data cleaning, standardization/normalization and the like;
(2) And (3) carrying out initial classification on the preprocessed historical auditing cases by using a cluster analysis algorithm (such as K-means, DBSCAN (clustering algorithm based on density), spectral clustering and the like), and generating a cluster center (or a representative case) for each class obtained by the initial classification as a typical characteristic description of the class. The clustering algorithm automatically classifies the historical auditing cases into a plurality of categories according to the similarity (determined by the characteristics) among the cases.
(3) Constructing and training a reinforcement learning model in the reinforcement learning environment, adjusting the distribution and the category division of the current historical auditing case by the reinforcement learning model at each time step, updating the distribution and the category division of the historical auditing case by the reinforcement learning environment according to expert auditing feedback, feeding back rewards to the reinforcement learning model, and updating the adjustment strategy of the category division of the historical auditing case by the reinforcement learning model according to rewards.
Specifically, the reinforcement learning environment construction includes:
first, a reinforcement learning environment is designed, wherein the state space of the reinforcement learning environment is all the historical auditing cases (or the feature vectors thereof), and the action space of the reinforcement learning environment is the possibility set for adjusting the categories of the historical auditing cases (such as transferring cases from one category to another category).
And setting a reward function, and giving positive or negative rewards according to the adjustment of the classification of the historical auditing case by the expert auditing result. For example, positive values are awarded when the expert deems that a case is properly categorized or adjusted to be more realistic; conversely, a negative prize is awarded.
Specifically, reinforcement learning model construction and training includes:
First, a reinforcement learning model (such as Q-learning, DQN (deep Q network), SAC (Soft activator-Critic), etc.) is initialized, and the objective of the model is to learn what action (adjusting case type) is taken in the current state to obtain the maximum long-term rewards.
Then, iterative training is performed in a reinforcement learning environment, the model selects actions (adjusting case categories) according to the current state (case distribution and category division) at each time step, the reinforcement learning environment updates the state according to expert review feedback and returns rewards, and the model updates its adjustment strategy according to the rewards.
(4) And after a certain training round or reaching a preset condition, the historical auditing cases are reclassified by applying an optimal adjustment strategy obtained by the reinforcement learning model, and the auditing discovery classification model (such as a logistic regression model) is retrained and adjusted and optimized according to the historical auditing cases of different categories so as to improve the judgment accuracy of similar problems.
(5) And organizing experts according to a preset period (such as quarterly, half year or one year), carrying out review on the current audit discovery classification model, providing a reward function for updating the reinforcement learning environment according to the review result, and continuously optimizing the classification of the historical audit cases and the audit discovery classification model according to the reward function.
It can be understood that the above clustering analysis and reinforcement learning algorithm is used for classifying and optimizing the historical auditing cases and performing iterative computation to gradually optimize the same-category problems for judgment, so that when the auditor does not agree on auditing findings to obtain a judgment result or periodically reviews, the historical auditing cases can be dynamically classified and optimized, and the auditing finding classification model of the same-category problems is iteratively computed, thereby continuously improving the accuracy and adaptability of the judgment and being beneficial to improving the accuracy and efficiency of standard standardization judgment of auditing findings.
Further, the system also includes an audit criteria management module 107 for updating and maintaining audit criteria.
It can be appreciated that the auditing criteria are updated and maintained so that the auditor can master the latest auditing criterion.
Further, the system further includes an audit certification personnel management module 108, configured to perform professional classification on the organization types that can be audited by the auditor according to the information of the auditor, such as professionals, job titles, working experiences, audit experiences, and the like, and perform technical classification on audit posts where the auditor is located (including audit group length, audit group member, technical expert, and the like).
It can be understood that by classifying and managing auditors, the audit resources can be utilized more effectively, and the audit authentication efficiency and the audit authentication quality can be improved.
Further, the system further includes an audit quality analysis module 109 for statistically analyzing the number of serious non-compliance and general non-compliance items found in all authentication audit tasks (including the number of serious non-compliance and general non-compliance items found by each auditor and averaging the information about the number of serious non-compliance and general non-compliance items found by each task sheet), and continuously tracking audit quality conditions.
In one embodiment, an intelligent audit authentication management method is provided, the method is executed by the intelligent audit authentication management system, and the method comprises the following steps:
First, an authentication application submitted by an organization is accepted and autonomously reviewed by the application acceptance module 101.
After the review is passed, the certification plan is formulated and audited by the certification task management module 102 according to the certification application, the audit group length and audit group members are selected, a detailed audit plan is formulated, and audit plan approval is performed.
Then, carrying out audit work through an audit certification management module 103, filling audit discovery in a standardized manner, constructing and training an audit discovery classification model based on supervised learning according to historical audit cases to analyze and calculate the audit discovery, automatically judging whether the audit discovery accords with standard rules, and feeding back a judgment result to an auditor for rechecking when the judgment result is that the audit discovery does not accord with the standard rules; and when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed.
After the auditing work is finished, an auditing report is automatically generated in the auditing report management module 104 according to auditing findings, the auditing report is sent to an authentication decision person of an authentication institution for confirmation, the auditing report is sent to the authentication certificate management module 105 after confirmation is correct, and an authentication certificate is automatically generated in the authentication certificate management module 105 according to the auditing report.
And when the auditor does not agree with the judgment result of the audit discovery, or at certain intervals, the audit case management module 106 organizes experts to review the historical audit cases, and combines the cluster analysis and the reinforcement learning algorithm to classify, optimize and iterate the historical audit cases, gradually optimize the same-category problems and judge.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure of which may be as shown in fig. 2. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements an intelligent audit authentication management method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by persons skilled in the art that the architecture shown in fig. 2 is merely a block diagram of some of the architecture relevant to the present inventive arrangements and is not limiting as to the computer device to which the present inventive arrangements are applicable, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:
First, an authentication application submitted by an organization is accepted and autonomously reviewed by the application acceptance module 101.
After the review is passed, the certification plan is formulated and audited by the certification task management module 102 according to the certification application, the audit group length and audit group members are selected, a detailed audit plan is formulated, and audit plan approval is performed.
Then, carrying out audit work through an audit certification management module 103, filling audit discovery in a standardized manner, constructing and training an audit discovery classification model based on supervised learning according to historical audit cases to analyze and calculate the audit discovery, automatically judging whether the audit discovery accords with standard rules, and feeding back a judgment result to an auditor for rechecking when the judgment result is that the audit discovery does not accord with the standard rules; and when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed.
After the auditing work is finished, an auditing report is automatically generated in the auditing report management module 104 according to auditing findings, the auditing report is sent to an authentication decision person of an authentication institution for confirmation, the auditing report is sent to the authentication certificate management module 105 after confirmation is correct, and an authentication certificate is automatically generated in the authentication certificate management module 105 according to the auditing report.
And when the auditor does not agree with the judgment result of the audit discovery, or at certain intervals, the audit case management module 106 organizes experts to review the historical audit cases, and combines the cluster analysis and the reinforcement learning algorithm to classify, optimize and iterate the historical audit cases, gradually optimize the same-category problems and judge.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
First, an authentication application submitted by an organization is accepted and autonomously reviewed by the application acceptance module 101.
After the review is passed, the certification plan is formulated and audited by the certification task management module 102 according to the certification application, the audit group length and audit group members are selected, a detailed audit plan is formulated, and audit plan approval is performed.
Then, carrying out audit work through an audit certification management module 103, filling audit discovery in a standardized manner, constructing and training an audit discovery classification model based on supervised learning according to historical audit cases to analyze and calculate the audit discovery, automatically judging whether the audit discovery accords with standard rules, and feeding back a judgment result to an auditor for rechecking when the judgment result is that the audit discovery does not accord with the standard rules; and when the judgment result is that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed.
After the auditing work is finished, an auditing report is automatically generated in the auditing report management module 104 according to auditing findings, the auditing report is sent to an authentication decision person of an authentication institution for confirmation, the auditing report is sent to the authentication certificate management module 105 after confirmation is correct, and an authentication certificate is automatically generated in the authentication certificate management module 105 according to the auditing report.
And when the auditor does not agree with the judgment result of the audit discovery, or at certain intervals, the audit case management module 106 organizes experts to review the historical audit cases, and combines the cluster analysis and the reinforcement learning algorithm to classify, optimize and iterate the historical audit cases, gradually optimize the same-category problems and judge.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. An intelligent audit certification management system, the system comprising: the system comprises an application acceptance module, an authentication task management module, an audit authentication management module, an audit report management module, an authentication certificate management module and an audit case management module;
the application acceptance module is used for accepting authentication applications submitted by organizations and performing autonomous review;
the certification task management module is used for making and checking a certification scheme according to the certification application after the review passes, selecting a checking group owner and a checking group member, making a detailed checking plan and checking the checking plan;
The auditing certification management module is used for enabling an auditor to carry out auditing work, standardizing filling auditing discovery, constructing and training an auditing discovery classification model based on supervised learning according to historical auditing cases to analyze and calculate the auditing discovery, automatically judging whether the auditing discovery accords with standard regulation, and feeding back the judging result to the auditor for rechecking when the judging result is that the auditing discovery does not accord with the standard regulation; when the judgment result shows that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed;
The audit report management module is used for automatically generating an audit report according to the audit discovery after the audit work is finished, transmitting the audit report to an authentication decision maker of an authentication mechanism for confirmation, and transmitting the audit report to the authentication certificate management module after the confirmation is correct;
The authentication certificate management module is used for automatically generating an authentication certificate according to the audit report;
And the auditing case management module is used for evaluating the historical auditing case by an organization expert when the auditor does not agree with the judging result of the auditing discovery or when a certain period is reserved, classifying and optimizing the historical auditing case by combining cluster analysis and reinforcement learning algorithm, and performing iterative calculation to gradually optimize the same-category problems for judging.
2. The system of claim 1, wherein the authentication task management module is specifically configured to:
Establishing and auditing certification schemes according to the certification application, and designating auditing group owners and auditing group operators to carry out auditing work; after logging in the personal account, the auditing group owner checks the authentication scheme and formulates an auditing plan, sends the auditing plan to an authentication project manager of the authentication mechanism for confirmation, and sends the auditing plan to the personal account of the appointed auditing group owner after confirmation, and the auditing group owner obtains the auditing plan and the historical auditing condition through logging in the personal account.
3. The system of claim 1, wherein constructing and training a supervised learning based audit discovery classification model from historical audit cases to analyze and calculate the audit findings, automatically determining whether the audit findings meet a standard specification, comprises:
Constructing an audit discovery classification model based on supervised learning; the audit discovery classification model comprises an audit discovery preprocessing unit, a marking unit and a classification unit, wherein the audit discovery preprocessing unit is used for extracting audit discovery characteristics in historical audit cases and carrying out data cleaning, data standardization or normalization processing; the marking unit is used for marking the auditing discovery as two types of labels of compliance and non-compliance according to whether the auditing discovery of the historical auditing case accords with the standard regulation; the classifying unit is used for judging the label to which the auditing discovery feature belongs;
training and optimizing the audit discovery classification model by learning the mapping relation between the audit discovery features and the labels to obtain a trained audit discovery classification model;
And extracting the characteristics of the new audit discovery through the trained audit discovery classification model and automatically classifying to judge whether the new audit discovery accords with the standard regulation.
4. The system of claim 1, wherein the combination of cluster analysis and reinforcement learning algorithm performs classification optimization and iterative computation on the historical audit case, and gradually optimizes the same class problem to determine, comprising:
Carrying out data preprocessing on the historical auditing case;
applying a cluster analysis algorithm to perform initial classification on the preprocessed historical auditing cases, and generating a cluster center for each category obtained by the initial classification;
Constructing and training a reinforcement learning model in a reinforcement learning environment, wherein the reinforcement learning model adjusts the distribution and the category division of the current historical auditing case at each time step, the reinforcement learning environment updates the distribution and the category division of the historical auditing case according to expert auditing feedback and feeds back rewards to the reinforcement learning model, and the reinforcement learning model updates an adjustment strategy of the category division of the historical auditing case according to the rewards;
After a certain training round or reaching a preset condition, the historical auditing cases are reclassified by applying an optimal adjustment strategy obtained by the reinforcement learning model, and the auditing discovery classification model is retrained, adjusted and optimized according to the historical auditing cases of different categories;
And the current audit discovery classification model is reviewed by an organization expert according to a preset period, a reward function for updating the reinforcement learning environment is provided according to a review result, and the classification of the historical audit case and the audit discovery classification model are continuously optimized according to the reward function.
5. The system of claim 1, further comprising an audit criteria management module for updating maintenance of audit criteria.
6. The system of claim 1, further comprising an audit certification personnel management module for professionally classifying the type of organization that the auditor can audit and for technically classifying the audit post at which the auditor is located, based on the auditor's profession, title, work experience, and audit experience.
7. The system of claim 1, further comprising an audit quality analysis module for statistically analyzing the number of severe and general non-compliance items found in all certification audit tasks, and continuously tracking audit quality conditions.
8. An intelligent audit certification management method, wherein the method is performed by an intelligent audit certification management system according to any of claims 1-7, the method comprising:
The application acceptance module accepts an authentication application submitted by an organization and performs autonomous review;
after the review passes, establishing and checking a certification scheme, selecting a checking group owner and a checking group member according to the certification application through a certification task management module, establishing a detailed checking plan and checking the checking plan;
An auditing certification management module auditors conduct auditing work, audit findings are filled in a standardized mode, an audit finding classification model based on supervised learning is constructed and trained according to historical audit cases to analyze and calculate the audit findings, whether the audit findings meet standard specifications is automatically judged, and when the judgment result is that the audit findings do not meet the standard specifications, the judgment result is fed back to the auditors for rechecking; when the judgment result shows that the auditing finding accords with the standard rule, continuing auditing work until auditing of all clauses is completed;
After the auditing work is finished, automatically generating an auditing report in an auditing report management module according to the auditing discovery, transmitting the auditing report to an authentication decision maker of an authentication institution for confirmation, transmitting the auditing report to an authentication certificate management module after confirmation is correct, and automatically generating an authentication certificate in the authentication certificate management module according to the auditing report;
and when the auditor does not agree with the judgment result of the audit discovery, or when a certain period is reserved, organizing experts through an audit case management module to review the historical audit case, classifying and optimizing the historical audit case by combining cluster analysis and reinforcement learning algorithm, performing iterative calculation, and gradually optimizing the same-category problems to judge.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of claim 8 when executing the computer program.
10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of claim 8.
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