CN117689211A - Audit risk assessment method, audit risk assessment device, audit risk assessment computer equipment and audit risk assessment storage medium - Google Patents
Audit risk assessment method, audit risk assessment device, audit risk assessment computer equipment and audit risk assessment storage medium Download PDFInfo
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- 238000012550 audit Methods 0.000 title claims abstract description 201
- 238000012502 risk assessment Methods 0.000 title claims abstract description 96
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Abstract
The application relates to an audit risk assessment method, an audit risk assessment device, computer equipment and a storage medium, and belongs to the technical field of risk assessment, wherein the method comprises the following steps: audit risk assessment method, apparatus, computer device and storage medium, the method comprising: obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information; determining a business category corresponding to the first characteristic data based on a pre-constructed database; determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data; and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal. The method and the device can quantify the risk of the audit so as to improve the accuracy and the efficiency of the evaluation result and further achieve the expected effect.
Description
Technical Field
The present disclosure relates to the field of risk assessment technologies, and in particular, to an audit risk assessment method, an audit risk assessment device, a computer device, and a storage medium.
Background
The audit is a method and measure for identifying and checking risks on various layers such as planning, executing, maintaining and the like, in the prior art, the processing amount of safety audit data is large, massive flow is required to be identified and audited in the safety audit, more network resources and time are required to be occupied, and meanwhile, the same audit standard is not adopted according to different risk assessment results of audit data, so that the safety audit of design audit data which cannot meet part of high requirements is caused, and potential safety hazards are caused.
Along with the development of risk assessment technology, a technology for assessing the audit risk appears, but at present, when the audit risk is assessed, all the characteristics of audit data are generally input into a trained artificial intelligent machine learning model to obtain an audit risk assessment result, and when the audit risk is assessed by using the audit risk assessment result, the audit risk cannot be quantified, the accuracy is poor, the efficiency is low, and the expected effect cannot be achieved.
Therefore, there is a need to propose an audit risk assessment method, apparatus, computer device and storage medium that is efficient and accurate.
Disclosure of Invention
Based on this, it is necessary to provide an audit risk assessment method, apparatus, computer device and storage medium with high efficiency and high accuracy in view of the above technical problems.
In one aspect, there is provided an audit risk assessment method, the method comprising:
obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
determining a business category corresponding to the first characteristic data based on a pre-constructed database;
determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
Optionally, the determining, based on the pre-constructed database, the service class corresponding to the first feature data includes:
extracting keywords of the audit related data;
based on the keywords, matching a mapping set corresponding to the first characteristic data from the pre-constructed database;
and determining the business category corresponding to the first characteristic data based on the mapping set.
Optionally, the determining, according to the business category corresponding to the first feature data and the audit related data, a first evaluation value of an audit risk includes:
determining a node to be evaluated existing in the audit related data based on the business category corresponding to the first characteristic data;
based on the node to be evaluated, at least one risk assessment index is determined, wherein the risk assessment index comprises at least one of the following: reliability index and timeliness index;
acquiring a correlation coefficient between the risk assessment indexes;
and determining a weight coefficient of the risk assessment index according to the association coefficient, and further determining a first assessment value of the audit risk.
Optionally, the enterprise operation information includes at least one of: financial information, production quality and safety information, examination information, market information and human resource information, wherein the market environment information at least comprises economic situation information, and the calculation method of the reliability index comprises the following steps:
defining the state set corresponding to the audit related data as { a } 1 ,a 2 ,...a j Probability of excitation audit risk for each state { p } 1 ,p 2 ,...p j Risk state occurrence frequency corresponding to risk probability larger than preset threshold value { d } 1 ,d 2 ,...d i And the sum of the probabilities is equal to 1, the calculation formula of the reliability index of the audit related data is as follows:
wherein R represents an occurrence stateProbability of transition, N represents the number of nodes to be evaluated, R i A function representing the probability of the target node being in the target state over time, Z i Representing the data variation, U representing the time step;
the method for calculating the timeliness index comprises the following steps:
acquiring a time characteristic value of each piece of information in the audit related data, wherein the time characteristic value comprises initial acquisition time, acquisition time interval and final acquisition time;
based on the time feature value, determining the timeliness index includes:
wherein delta 1 、δ 2 Representing the time weighting coefficient, t 1 Representing initial acquisition time assignment, t 2 Representing final acquisition time assignment, t 3 Representing acquisition time interval assignments, t m The time quantization value is represented, T represents the time cost amount, n represents the information amount acquisition quantity, and s represents the adjustment coefficient.
Optionally, the acquiring the association coefficient between the risk assessment indexes includes:
calculating a correlation coefficient between the reliability index and the timeliness index using a correlation coefficient calculation function, the correlation coefficient calculation function comprising:
wherein Q represents a correlation coefficient, f (g) represents a correlation function, η 1 、η 2 All represent associated parameters, L represents a state change coefficient, and E represents a traffic class assignment.
Optionally, the determining, according to the association coefficient, a weight coefficient of the risk assessment indicator, and further determining the first assessment value of the audit risk includes:
in response to detecting that the association coefficient is greater than a first preset value, taking the association coefficient Q as a weight coefficient ratio of the reliability index to the timeliness index;
in response to detecting that the association coefficient is less than or equal to a first preset valueAs a weight coefficient ratio of the reliability index and the timeliness index;
calculating a first evaluation value of the audit risk based on the weight coefficient by using a risk evaluation model, wherein the risk evaluation model comprises:
wherein Q represents the first evaluation value, x represents the iteration coefficient, G 1 、G 2 Respectively represent the time-efficiency index weight coefficient and the reliability index weight coefficient, Y kh Representing the sum of audit related data assignments, F representing a correction function, U kh Representing the sum of the age assignments.
Optionally, determining an evaluation result of the audit risk based on the first evaluation value of the audit risk, and sending the evaluation result to the terminal includes:
judging that the auditing risk occurs in response to the fact that the first evaluation value is larger than a second preset value;
and sending an early warning signal to the terminal based on the audit risk judgment result.
In another aspect, there is provided an audit risk assessment apparatus, the apparatus comprising:
the data extraction module is used for obtaining audit related data and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
the first determining module is used for determining the business category corresponding to the first characteristic data based on a pre-constructed database;
the second determining module is used for determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and the third determining module is used for determining an evaluation result of the audit risk based on the first evaluation value of the audit risk and sending the evaluation result to the terminal.
In yet another aspect, a computer device is provided comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of:
obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
determining a business category corresponding to the first characteristic data based on a pre-constructed database;
determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
In yet another aspect, a computer readable storage medium is provided, having stored thereon a computer program which when executed by a processor performs the steps of:
obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
determining a business category corresponding to the first characteristic data based on a pre-constructed database;
determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
The audit risk assessment method, the audit risk assessment device, the computer equipment and the storage medium, wherein the audit risk assessment method comprises the following steps: obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information; determining a business category corresponding to the first characteristic data based on a pre-constructed database; determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data; based on the first evaluation value of the audit risk, an evaluation result of the audit risk is determined and sent to the terminal, and the method and the device can quantify the audit risk so as to improve the accuracy and the evaluation efficiency of the evaluation result and further achieve the expected effect.
Drawings
FIG. 1 is an application environment diagram of an audit risk assessment method in one embodiment;
FIG. 2 is a flow diagram of an audit risk assessment method in one embodiment;
FIG. 3 is a block diagram of an audit risk assessment apparatus in one embodiment;
fig. 4 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.
It should be understood that throughout this description, unless the context clearly requires otherwise, the words "comprise," "comprising," and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is, it is the meaning of "including but not limited to".
It should also be appreciated that the terms "first," "second," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Furthermore, in the description of the present application, unless otherwise indicated, the meaning of "a plurality" is two or more.
It should be noted that the terms "S1", "S2", and the like are used for the purpose of describing steps only, and are not intended to be limited to the order or sequence of steps or to limit the present application, but are merely used for convenience in describing the method of the present application and are not to be construed as indicating the sequence of steps. In addition, the technical solutions of the embodiments may be combined with each other, but it is necessary to base that the technical solutions can be realized by those skilled in the art, and when the technical solutions are contradictory or cannot be realized, the combination of the technical solutions should be regarded as not exist and not within the protection scope of the present application.
The audit risk assessment method provided by the application can be applied to an application environment shown in fig. 1. The terminal 102 communicates with a data processing platform disposed on the server 104 through a network, where the terminal 102 may be, but is not limited to, various personal computers, notebook computers, smartphones, tablet computers, and portable wearable devices, and the server 104 may be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
In one embodiment, as shown in fig. 2, an audit risk assessment method is provided, and the method is applied to the terminal in fig. 1 for illustration, and includes the following steps:
s1: obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
it should be noted that, the enterprise operation information includes at least one of the following: financial information, production quality and safety information, examination information, market information and human resource information, wherein the market environment information at least comprises economic situation information, the information can be obtained through a crawler, and the first characteristic data of the audit related data can be enterprise operation information, keywords or keywords in the market environment information.
S2: and determining the business category corresponding to the first characteristic data based on a pre-constructed database.
It should be noted that this step specifically includes:
extracting keywords of the audit related data;
based on the keywords, matching a mapping set corresponding to the first characteristic data from the pre-constructed database, wherein the mapping set comprises the keywords and corresponding service categories, and the service categories can be services such as financial management, human resource management, bid-and-bid purchase management and the like;
and determining the business category corresponding to the first characteristic data based on the mapping set.
S3: and determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data.
It should be noted that this step specifically includes:
determining nodes to be evaluated existing in the audit related data based on the business category corresponding to the first characteristic data, wherein different problem points appear in the audit related data of different business categories, and the problem points are the nodes to be evaluated;
based on the node to be evaluated, at least one risk assessment index is determined, wherein the risk assessment index comprises at least one of the following: reliability index and timeliness index;
acquiring a correlation coefficient between the risk assessment indexes;
and determining a weight coefficient of the risk assessment index according to the association coefficient, and further determining a first assessment value of the audit risk.
Specifically, the method for calculating the reliability index includes:
defining the state set corresponding to the audit related data as { a } 1 ,a 2 ,...a j Probability of excitation audit risk for each state { p } 1 ,p 2 ,...p j Risk state occurrence frequency corresponding to risk probability larger than preset threshold value { d } 1 ,d 2 ,...d i And the sum of the probabilities is equal to 1, the calculation formula of the reliability index of the audit related data is as follows:
wherein R represents the probability of occurrence of state transition, N represents the number of nodes to be evaluated, R i A function representing the probability of the target node being in the target state over time, Z i Representing the data variation, U representing the time step;
the method for calculating the timeliness index comprises the following steps:
acquiring a time characteristic value of each piece of information in the audit related data, wherein the time characteristic value comprises initial acquisition time, acquisition time interval and final acquisition time;
based on the time feature value, determining the timeliness index includes:
wherein delta 1 、δ 2 Representing the time weighting coefficient, t 1 Representing initial acquisition time assignment, t 2 Representing final acquisition time assignment, t 3 Representing acquisition time interval assignments, t m The time quantization value is represented, T represents the time cost amount, n represents the information amount acquisition quantity, and s represents the adjustment coefficient.
Further, the acquiring the association coefficient between the risk assessment indexes includes:
calculating a correlation coefficient between the reliability index and the timeliness index using a correlation coefficient calculation function, the correlation coefficient calculation function comprising:
wherein Q represents a correlation coefficient, f (g) represents a correlation function, η 1 、η 2 All represent associated parameters, L represents a state change coefficient, and E represents a traffic class assignment.
Further, the determining, according to the association coefficient, a weight coefficient of the risk assessment indicator, and further determining a first assessment value of the audit risk includes:
in response to detecting that the association coefficient is larger than a first preset value, taking the association coefficient Q as a weight coefficient ratio of the reliability index to the timeliness index, wherein the first preset value can be set according to actual requirements;
in response to detecting that the association coefficient is less than or equal to a first preset valueAs a weight coefficient ratio of the reliability index and the timeliness index;
calculating a first evaluation value of the audit risk based on the weight coefficient by using a risk evaluation model, wherein the risk evaluation model comprises:
wherein Q represents the first evaluation value, x represents the iteration coefficient, G 1 、G 2 Respectively represent the time-efficiency index weight coefficient and the reliability index weight coefficient, Y kh Representing the sum of audit related data assignments, F representing a correction function, U kh Representing the sum of the age assignments.
S4: and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
It should be noted that this step specifically includes:
judging that an audit risk occurs when the first evaluation value is larger than a second preset value in response to detection, wherein the second preset value can be set according to actual requirements;
and sending an early warning signal to the terminal based on the audit risk judgment result.
In the above audit risk assessment method, the method includes: obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information; determining a business category corresponding to the first characteristic data based on a pre-constructed database; determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data; based on the first evaluation value of the audit risk, an evaluation result of the audit risk is determined and sent to the terminal, and the method and the device can quantify the audit risk so as to improve the accuracy and the evaluation efficiency of the evaluation result and further achieve the expected effect.
It should be understood that, although the steps in the flowchart of fig. 2 are shown in sequence as indicated by the arrows, the steps are not necessarily performed in sequence as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily performed in sequence, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or other steps.
In one embodiment, as shown in fig. 3, there is provided an audit risk assessment apparatus comprising: the device comprises a data extraction module, a first determination module, a second determination module and a third determination module, wherein:
the data extraction module is used for obtaining audit related data and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
the first determining module is used for determining the business category corresponding to the first characteristic data based on a pre-constructed database;
the second determining module is used for determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and the third determining module is used for determining an evaluation result of the audit risk based on the first evaluation value of the audit risk and sending the evaluation result to the terminal.
As a preferred implementation manner, in the embodiment of the present invention, the first determining module is specifically configured to:
extracting keywords of the audit related data;
based on the keywords, matching a mapping set corresponding to the first characteristic data from the pre-constructed database;
and determining the business category corresponding to the first characteristic data based on the mapping set.
As a preferred implementation manner, in the embodiment of the present invention, the second determining module is specifically configured to:
determining a node to be evaluated existing in the audit related data based on the business category corresponding to the first characteristic data;
based on the node to be evaluated, at least one risk assessment index is determined, wherein the risk assessment index comprises at least one of the following: reliability index and timeliness index;
acquiring a correlation coefficient between the risk assessment indexes;
and determining a weight coefficient of the risk assessment index according to the association coefficient, and further determining a first assessment value of the audit risk.
As a preferred implementation manner, in the embodiment of the present invention, the second determining module is specifically further configured to:
the enterprise operation information includes at least one of: financial information, production quality and safety information, examination information, market information and human resource information, wherein the market environment information at least comprises economic situation information, and the calculation method of the reliability index comprises the following steps:
defining the state set corresponding to the audit related data as { a } 1 ,a 2 ,...a j Probability of excitation audit risk for each state { p } 1 ,p 2 ,...p j Risk state occurrence frequency corresponding to risk probability larger than preset threshold value { d } 1 ,d 2 ,...d i And the sum of the probabilities is equal to 1, the calculation formula of the reliability index of the audit related data is as follows:
wherein R represents the probability of occurrence of state transition, N represents the number of nodes to be evaluated, R i A function representing the probability of the target node being in the target state over time, Z i Representing the data variation, U representing the time step;
the method for calculating the timeliness index comprises the following steps:
acquiring a time characteristic value of each piece of information in the audit related data, wherein the time characteristic value comprises initial acquisition time, acquisition time interval and final acquisition time;
based on the time feature value, determining the timeliness index includes:
wherein delta 1 、δ 2 Representing the time weighting coefficient, t 1 Representing initial acquisition time assignment, t 2 Representing final acquisition time assignment, t 3 Representing acquisition time interval assignments, t m The time quantization value is represented, T represents the time cost amount, n represents the information amount acquisition quantity, and s represents the adjustment coefficient.
As a preferred implementation manner, in the embodiment of the present invention, the second determining module is specifically further configured to:
calculating a correlation coefficient between the reliability index and the timeliness index using a correlation coefficient calculation function, the correlation coefficient calculation function comprising:
wherein Q represents a correlation coefficient, f (g) represents a correlation function, η 1 、η 2 All represent associated parameters, L represents a state change coefficient, and E represents a traffic class assignment.
As a preferred implementation manner, in the embodiment of the present invention, the second determining module is specifically further configured to:
in response to detecting that the association coefficient is greater than a first preset value, taking the association coefficient Q as a weight coefficient ratio of the reliability index to the timeliness index;
in response to detecting that the association coefficient is less than or equal to a first preset valueAs a weight coefficient ratio of the reliability index and the timeliness index;
calculating a first evaluation value of the audit risk based on the weight coefficient by using a risk evaluation model, wherein the risk evaluation model comprises:
wherein Q represents the first evaluation value, x represents the iteration coefficient, G 1 、G 2 Respectively represent the time-efficiency index weight coefficient and the reliability index weight coefficient, Y kh Representing the sum of audit related data assignments, F representing a correction function, U kh Representing the sum of the age assignments.
In a preferred embodiment of the present invention, the third determining module is specifically configured to:
judging that the auditing risk occurs in response to the fact that the first evaluation value is larger than a second preset value;
and sending an early warning signal to the terminal based on the audit risk judgment result.
For specific limitations on the audit risk assessment apparatus, reference may be made to the above limitations on the audit risk assessment method, and no further description is given here. The various modules in the audit risk assessment apparatus described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
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. 4. 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 audit risk assessment 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.
Those skilled in the art will appreciate that the structures shown in FIG. 4 are block diagrams only and do not constitute a limitation of the computer device on which the present aspects apply, and that a particular computer device may include more or less components than those 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, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of when executing the computer program:
s1: obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
s2: determining a business category corresponding to the first characteristic data based on a pre-constructed database;
s3: determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
s4: and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
In one embodiment, the processor when executing the computer program further performs the steps of:
extracting keywords of the audit related data;
based on the keywords, matching a mapping set corresponding to the first characteristic data from the pre-constructed database;
and determining the business category corresponding to the first characteristic data based on the mapping set.
In one embodiment, the processor when executing the computer program further performs the steps of:
determining a node to be evaluated existing in the audit related data based on the business category corresponding to the first characteristic data;
based on the node to be evaluated, at least one risk assessment index is determined, wherein the risk assessment index comprises at least one of the following: reliability index and timeliness index;
acquiring a correlation coefficient between the risk assessment indexes;
and determining a weight coefficient of the risk assessment index according to the association coefficient, and further determining a first assessment value of the audit risk.
In one embodiment, the processor when executing the computer program further performs the steps of:
the enterprise operation information includes at least one of: financial information, production quality and safety information, examination information, market information and human resource information, wherein the market environment information at least comprises economic situation information, and the calculation method of the reliability index comprises the following steps:
defining the state set corresponding to the audit related data as { a } 1 ,a 2 ,...a j Probability of excitation audit risk for each state { p } 1 ,p 2 ,...p j Risk state occurrence frequency corresponding to risk probability larger than preset threshold value { d } 1 ,d 2 ,...d i And the sum of the probabilities is equal to 1, the calculation formula of the reliability index of the audit related data is as follows:
wherein R represents the probability of occurrence of state transition, N represents the number of nodes to be evaluated, R i A function representing the probability of the target node being in the target state over time, Z i Representing the data variation, U representing the time step;
the method for calculating the timeliness index comprises the following steps:
acquiring a time characteristic value of each piece of information in the audit related data, wherein the time characteristic value comprises initial acquisition time, acquisition time interval and final acquisition time;
based on the time feature value, determining the timeliness index includes:
wherein delta 1 、δ 2 Representing the time weighting coefficient, t 1 Representing initial acquisition time assignment, t 2 Representing final acquisition time assignment, t 3 Representing acquisition time interval assignments, t m The time quantization value is represented, T represents the time cost amount, n represents the information amount acquisition quantity, and s represents the adjustment coefficient.
In one embodiment, the processor when executing the computer program further performs the steps of:
calculating a correlation coefficient between the reliability index and the timeliness index using a correlation coefficient calculation function, the correlation coefficient calculation function comprising:
wherein Q represents a correlation coefficient, f (g) represents a correlation function, η 1 、η 2 All represent associated parametersL represents a state change coefficient and E represents a traffic class assignment.
In one embodiment, the processor when executing the computer program further performs the steps of:
in response to detecting that the association coefficient is greater than a first preset value, taking the association coefficient Q as a weight coefficient ratio of the reliability index to the timeliness index;
in response to detecting that the association coefficient is less than or equal to a first preset valueAs a weight coefficient ratio of the reliability index and the timeliness index;
calculating a first evaluation value of the audit risk based on the weight coefficient by using a risk evaluation model, wherein the risk evaluation model comprises:
wherein Q represents the first evaluation value, x represents the iteration coefficient, G 1 、G 2 Respectively represent the time-efficiency index weight coefficient and the reliability index weight coefficient, Y kh Representing the sum of audit related data assignments, F representing a correction function, U kh Representing the sum of the age assignments.
In one embodiment, the processor when executing the computer program further performs the steps of:
judging that the auditing risk occurs in response to the fact that the first evaluation value is larger than a second preset value;
and sending an early warning signal to the terminal based on the audit risk judgment result.
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:
s1: obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
s2: determining a business category corresponding to the first characteristic data based on a pre-constructed database;
s3: determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
s4: and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
In one embodiment, the computer program when executed by the processor further performs the steps of:
extracting keywords of the audit related data;
based on the keywords, matching a mapping set corresponding to the first characteristic data from the pre-constructed database;
and determining the business category corresponding to the first characteristic data based on the mapping set.
In one embodiment, the computer program when executed by the processor further performs the steps of:
determining a node to be evaluated existing in the audit related data based on the business category corresponding to the first characteristic data;
based on the node to be evaluated, at least one risk assessment index is determined, wherein the risk assessment index comprises at least one of the following: reliability index and timeliness index;
acquiring a correlation coefficient between the risk assessment indexes;
and determining a weight coefficient of the risk assessment index according to the association coefficient, and further determining a first assessment value of the audit risk.
In one embodiment, the computer program when executed by the processor further performs the steps of:
the enterprise operation information includes at least one of: financial information, production quality and safety information, examination information, market information and human resource information, wherein the market environment information at least comprises economic situation information, and the calculation method of the reliability index comprises the following steps:
defining the state set corresponding to the audit related data as { a } 1 ,a 2 ,...a j Probability of excitation audit risk for each state { p } 1 ,p 2 ,...p j Risk state occurrence frequency corresponding to risk probability larger than preset threshold value { d } 1 ,d 2 ,...d i And the sum of the probabilities is equal to 1, the calculation formula of the reliability index of the audit related data is as follows:
/>
wherein R represents the probability of occurrence of state transition, N represents the number of nodes to be evaluated, R i A function representing the probability of the target node being in the target state over time, Z i Representing the data variation, U representing the time step;
the method for calculating the timeliness index comprises the following steps:
acquiring a time characteristic value of each piece of information in the audit related data, wherein the time characteristic value comprises initial acquisition time, acquisition time interval and final acquisition time;
based on the time feature value, determining the timeliness index includes:
wherein delta 1 、δ 2 Representing the time weighting coefficient, t 1 Representing initial acquisition time assignment, t 2 Representing the final acquisition timeAssigning value between t 3 Representing acquisition time interval assignments, t m The time quantization value is represented, T represents the time cost amount, n represents the information amount acquisition quantity, and s represents the adjustment coefficient.
In one embodiment, the computer program when executed by the processor further performs the steps of:
calculating a correlation coefficient between the reliability index and the timeliness index using a correlation coefficient calculation function, the correlation coefficient calculation function comprising:
wherein Q represents a correlation coefficient, f (g) represents a correlation function, η 1 、η 2 All represent associated parameters, L represents a state change coefficient, and E represents a traffic class assignment.
In one embodiment, the computer program when executed by the processor further performs the steps of:
in response to detecting that the association coefficient is greater than a first preset value, taking the association coefficient Q as a weight coefficient ratio of the reliability index to the timeliness index;
in response to detecting that the association coefficient is less than or equal to a first preset valueAs a weight coefficient ratio of the reliability index and the timeliness index;
calculating a first evaluation value of the audit risk based on the weight coefficient by using a risk evaluation model, wherein the risk evaluation model comprises:
wherein Q represents the first evaluation value, x represents the iteration coefficient, G 1 、G 2 Respectively represent the time-efficiency index weight coefficient and the reliability index weight coefficient, Y kh Representing the sum of audit related data assignments, F representing a correction function, U kh Representing the sum of the age assignments.
In one embodiment, the computer program when executed by the processor further performs the steps of:
judging that the auditing risk occurs in response to the fact that the first evaluation value is larger than a second preset value;
and sending an early warning signal to the terminal based on the audit risk judgment result.
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 the various 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 DRAM (SLDRAM), memory bus 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 invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.
Claims (10)
1. An audit risk assessment method, comprising:
obtaining audit related data, and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
determining a business category corresponding to the first characteristic data based on a pre-constructed database;
determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and determining an audit risk assessment result based on the first audit risk assessment value, and sending the audit risk assessment result to a terminal.
2. The audit risk assessment method according to claim 1 wherein determining a traffic class corresponding to the first feature data based on a pre-constructed database includes:
extracting keywords of the audit related data;
based on the keywords, matching a mapping set corresponding to the first characteristic data from the pre-constructed database;
and determining the business category corresponding to the first characteristic data based on the mapping set.
3. The method of claim 2, wherein determining the first evaluation value of the audit risk according to the traffic class corresponding to the first feature data and the audit related data comprises:
determining a node to be evaluated existing in the audit related data based on the business category corresponding to the first characteristic data;
based on the node to be evaluated, at least one risk assessment index is determined, wherein the risk assessment index comprises at least one of the following: reliability index and timeliness index;
acquiring a correlation coefficient between the risk assessment indexes;
and determining a weight coefficient of the risk assessment index according to the association coefficient, and further determining a first assessment value of the audit risk.
4. The audit risk assessment method according to claim 3 wherein the enterprise operating information includes at least one of: financial information, production quality and safety information, examination information, market information and human resource information, wherein the market environment information at least comprises economic situation information, and the calculation method of the reliability index comprises the following steps:
defining the state set corresponding to the audit related data as { a } 1 ,a 2 ,...a j Probability of excitation audit risk for each state { p } 1 ,p 2 ,...p j Risk state occurrence frequency corresponding to risk probability larger than preset threshold value { d } 1 ,d 2 ,...d i And the sum of the probabilities is equal to 1, the calculation formula of the reliability index of the audit related data is as follows:
wherein R represents the probability of occurrence of state transition, N represents the number of nodes to be evaluated, R i A function representing the probability of the target node being in the target state over time, Z i Representing the data variation, U representing the time step;
the method for calculating the timeliness index comprises the following steps:
acquiring a time characteristic value of each piece of information in the audit related data, wherein the time characteristic value comprises initial acquisition time, acquisition time interval and final acquisition time;
based on the time feature value, determining the timeliness index includes:
wherein delta 1 、δ 2 Representing the time weighting coefficient, t 1 Representing initial acquisition time assignment, t 2 Representing final acquisition time assignment, t 3 Representing acquisition time interval assignments, t m The time quantization value is represented, T represents the time cost amount, n represents the information amount acquisition quantity, and s represents the adjustment coefficient.
5. The audit risk assessment method according to claim 4 wherein the obtaining of correlation coefficients between the risk assessment indicators includes:
calculating a correlation coefficient between the reliability index and the timeliness index using a correlation coefficient calculation function, the correlation coefficient calculation function comprising:
wherein Q represents a correlation coefficient, f (g) represents a correlation function, η 1 、η 2 All represent associated parameters, L represents a state change coefficient, and E represents a traffic class assignment.
6. The method of claim 5, wherein determining the weight coefficient of the risk assessment indicator according to the association coefficient, and further determining the first assessment value of the audit risk comprises:
in response to detecting that the association coefficient is greater than a first preset value, taking the association coefficient Q as a weight coefficient ratio of the reliability index to the timeliness index;
in response to detecting that the association coefficient is less than or equal to a first preset valueAs a weight coefficient ratio of the reliability index and the timeliness index;
calculating a first evaluation value of the audit risk based on the weight coefficient by using a risk evaluation model, wherein the risk evaluation model comprises:
wherein Q represents the first evaluation value, x represents the iteration coefficient, G 1 、G 2 Respectively represent the time-efficiency index weight coefficient and the reliability index weight coefficient, Y kh Representing the sum of audit related data assignments, F representing a correction function, U kh Representing the sum of the age assignments.
7. The method for evaluating an audit risk according to claim 6 wherein determining an evaluation result of the audit risk based on the first evaluation value of the audit risk and transmitting the evaluation result to a terminal includes:
judging that the auditing risk occurs in response to the fact that the first evaluation value is larger than a second preset value;
and sending an early warning signal to the terminal based on the audit risk judgment result.
8. An audit risk assessment apparatus, the apparatus comprising:
the data extraction module is used for obtaining audit related data and extracting first characteristic data of the audit related data, wherein the audit related data comprises at least one of the following: enterprise operation information, market environment information;
the first determining module is used for determining the business category corresponding to the first characteristic data based on a pre-constructed database;
the second determining module is used for determining a first evaluation value of the auditing risk according to the business category corresponding to the first characteristic data and the auditing related data;
and the third determining module is used for determining an evaluation result of the audit risk based on the first evaluation value of the audit risk and sending the evaluation result to the terminal.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method of any of claims 1 to 7 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 method of any of claims 1 to 7.
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