CN117456288B - Intelligent audit supervision early warning system and method - Google Patents
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
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- G06T3/00—Geometric image transformation in the plane of the image
- G06T3/40—Scaling the whole image or part thereof
- G06T3/4038—Scaling the whole image or part thereof for image mosaicing, i.e. plane images composed of plane sub-images
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- G06V10/62—Extraction of image or video features relating to a temporal dimension, e.g. time-based feature extraction; Pattern tracking
Abstract
The invention provides an intelligent audit supervision early warning system and method, which belong to the technical field of audit supervision, wherein the system comprises: the image generation module is used for generating an operation flow chart of each audit index based on the to-be-audited data of the audit object; the image association module is used for generating a macroscopic audit graph of each macroscopic audit target based on the operation flow diagrams of all audit indexes; the abnormality determining module is used for determining an abnormality root of the auditing object based on the macroscopic audit graphs under all macroscopic audit targets; the abnormality early warning module is used for generating early warning information based on an abnormality root cause; the method is used for tracing the abnormal root of the audit object based on the macroscopic audit graph representing the audit operation process of a plurality of macroscopic audit targets, thereby realizing abnormal accurate positioning and efficient accurate early warning in the operation and management process of the audit object, and facilitating subsequent maintenance and improvement of abnormal conditions obtained by a supervision and early warning system.
Description
Technical Field
The invention relates to the technical field of audit supervision, in particular to an intelligent audit supervision early warning system and method.
Background
At present, with the development of digital and intelligent auditing systems, the auditing process is gradually replaced by the digital and intelligent auditing systems. The intelligent audit system covers multidimensional data information of the audit object, analyzes the attribute of the original audit object through collected data and quantitative statistical analysis of groups, finds out the requirements of different types of audit objects according to the attributes of core business, asset scale, service area and the like, further shows an audit mode, and finally forms accurate positioning of audit risk and deep analysis of result application. The more and more clear the attribute data and audit indexes of the audit object, the more the core problem of the audit object can be solved, the customized audit mode is provided by subdividing the audit object, the more the digital audit application characteristics are met, and the improvement of the audit efficiency and effect is facilitated. Also suitable for the intelligent audit system is a system with supervision function and/or early warning function for the intelligent audit system.
However, most of the existing intelligent audit supervision early warning systems locate abnormal conditions of audit objects only through audit indexes obtained in an audit process, so that tracing of abnormal sources cannot be realized, namely, the locating and early warning of the abnormal conditions found in the audit process are not accurate enough, and therefore follow-up maintenance and improvement of the abnormal conditions obtained by the supervision early warning system are inconvenient.
Therefore, the invention provides an intelligent audit supervision early warning system and method.
Disclosure of Invention
The invention provides an intelligent audit supervision early warning system and method, which are used for tracing the abnormal source of an audit object based on a macroscopic audit graph representing the audit operation process of a plurality of macroscopic audit targets, so that the abnormal accurate positioning and high-efficiency accurate early warning in the audit object management process are realized, and the follow-up maintenance and improvement of the abnormal situation obtained by the supervision early warning system are facilitated.
The invention provides an intelligent audit supervision early warning system, which comprises:
the image generation module is used for generating an operation flow chart of each audit index based on the to-be-audited data of the audit object;
the image association module is used for generating a macroscopic audit graph of each macroscopic audit target based on the operation flow diagrams of all audit indexes;
the abnormality determining module is used for determining an abnormality root of the auditing object based on the macroscopic audit graphs under all macroscopic audit targets;
and the abnormality early warning module is used for generating early warning information based on an abnormality root.
Preferably, the image generation module includes:
the index item determining submodule is used for determining index items required by all macroscopic audit targets as audit indexes based on macroscopic audit rules of all macroscopic audit targets;
the data extraction sub-module is used for extracting the data required by auditing of the auditing indexes from the data to be audited of the auditing objects based on the preset auditing rules of each auditing index;
the index operation sub-module is used for carrying out operation based on preset audit rules of each audit index and data required by audit to obtain all operation intermediate quantities and audit index values of the audit index;
and the flow drawing submodule is used for generating an operation flow chart of each audit index based on the data required by the audit of each audit index, the operation intermediate quantity and the audit index value.
Preferably, the image association module includes:
the required index determination submodule is used for determining an audit index required by each macroscopic audit target in all audit indexes based on the macroscopic audit rule of each macroscopic audit target;
the flow chart connection sub-module is used for generating a macroscopic audit chart under each macroscopic audit target based on each macroscopic audit rule and an operation flow chart of the audit indexes required by the corresponding macroscopic audit target.
Preferably, the flowchart connects sub-modules, including:
the macro audit operation unit is used for calculating the audit index value of the audit index determined by the operation flow chart of the audit index required by each macro audit target based on the macro audit rule to obtain the macro audit result of the macro audit target;
the primary connection unit is used for carrying out primary connection on a macroscopic audit result of the macroscopic audit target and an operation flow chart of an audit index required by the macroscopic audit target based on each macroscopic audit rule, so as to obtain a primary operation chart of each macroscopic audit target;
the operation level determining unit is used for determining the operation level of the audit indexes required by each macroscopic audit target in the macroscopic audit rule;
and the variable merging unit is used for merging the data required by the coincident audit and the operation intermediate quantity in the operation flow chart of the audit indexes of the same operation level in the audit indexes required by each macroscopic audit target, and the macroscopic audit chart under each macroscopic audit target.
Preferably, the anomaly determination module includes:
the deviation rate determination submodule is used for determining the deviation rate of the macroscopic audit result and the standard audit result of all the macroscopic audit targets in the corresponding macroscopic audit graphs;
the splicing fitting sub-module is used for carrying out dimensionality splicing fitting on the deviation values of all macroscopic audit targets based on a plurality of preset dimensionalities, and obtaining a macroscopic deviation characterization diagram of the audit objects in each preset dimensionalities;
the abnormality determination sub-module is used for determining an abnormality root of the audit object based on the macroscopic deviation characterization graph of each preset dimension and the macroscopic audit graphs under all macroscopic audit targets.
Preferably, the splice fitting sub-module includes:
the target classification summarizing unit is used for determining and summarizing all macroscopic audit targets with time sequence change characteristics from all macroscopic audit targets to serve as time-varying characteristic target groups;
the deviation value fitting unit is used for determining time sequence change characteristics among all macroscopic audit targets in the time-varying characteristic target group, and performing curve fitting on deviation values of all macroscopic audit targets in the corresponding time-varying characteristic target group based on the time sequence change characteristics to obtain a deviation time sequence change diagram;
the time sequence change diagram alignment unit is used for performing time sequence alignment on all deviation time sequence change diagrams to obtain a macroscopic deviation characterization diagram of an auditing object in a time dimension;
the deviation splicing fitting unit is used for splicing the deviation values of all macroscopic audit targets based on the space dimension to obtain a macroscopic deviation characterization diagram of the audit object in the space dimension;
the preset dimension comprises a time dimension and a space dimension.
Preferably, the bias splice fitting unit includes:
the target classification summarizing subunit is used for determining and summarizing all macroscopic audit targets with spatial distribution change characteristics among all macroscopic audit targets to be used as a spatial distribution change characteristic target group;
the deviation value splicing subunit is used for determining the spatial distribution change characteristics among all macroscopic audit targets in the spatial distribution change characteristic target group, and splicing the deviation values of all macroscopic audit targets in the corresponding spatial distribution change characteristic target group based on the spatial distribution change characteristics to obtain a deviation spatial distribution map;
and the spatial distribution diagram alignment subunit is used for carrying out spatial alignment on all deviation spatial distribution diagrams to obtain a macroscopic deviation characterization diagram of the auditing object in the spatial dimension.
Preferably, the abnormality determination submodule includes:
the weight determining unit is used for determining the dimension abnormal weight of each preset dimension based on the macroscopic deviation characterization graph of each preset dimension;
the root source tracing unit is used for tracing abnormal root sources of all macroscopic audit graphs of all macroscopic audit targets corresponding to the macroscopic deviation characterization graph based on the dimension abnormal weight, and determining the abnormal root source of the audit object.
Preferably, the anomaly tracing unit includes:
the abnormal judgment value calculation subunit is used for calculating the abnormal judgment value of all data required by audit based on the dimension abnormal weight and the standard audit value corresponding to the sum of all operation intermediate quantities in the macroscopic audit graphs of all macroscopic audit targets corresponding to the macroscopic deviation characterization graph;
and the abnormal root cause determining unit is used for determining the abnormal root cause of the auditing object based on the abnormal judgment values of all the data required by the auditing.
The invention provides an intelligent audit supervision and early warning method, which comprises the following steps:
s1: generating an operation flow chart of each audit index based on the to-be-audited data of the audit object;
s2: generating a macroscopic audit map of each macroscopic audit target based on the operation flow diagrams of all audit indexes;
s3: determining an abnormal root of an audit object based on the macroscopic audit graphs under all macroscopic audit targets;
s4: and generating early warning information based on the abnormal root cause.
The invention has the beneficial effects different from the prior art that: the abnormal root of the auditing object is traced back based on the macroscopic audit graph representing the auditing operation process of a plurality of macroscopic auditing targets, so that the abnormal accurate positioning and high-efficiency accurate early warning in the auditing object operation management process are realized, and the follow-up maintenance and improvement of the abnormal situation obtained by the supervision and early warning system are facilitated.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities particularly pointed out in the specification.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a schematic diagram of an intelligent audit supervision and early warning system in an embodiment of the invention;
FIG. 2 is a diagram of a macroscopic audit trail of an audit object in an embodiment of the present invention;
fig. 3 is a flowchart of an intelligent audit supervision and early warning method in an embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1
The invention provides an intelligent audit supervision early warning system, referring to figures 1 and 2, comprising:
the image generating module is used for generating each audit index (namely, a more specific audit operation index item obtained in the process of obtaining an audit result of a macroscopic audit target in the operation process, such as a task index, an asset liability rate, a main business income increasing rate, a business income profit rate and the like) based on to-be-audited data (namely, attribute data of the audit object used in the process of auditing the audit object or data generated in the operation and running process, such as transaction data or financial activity data of the enterprise) of the audit object (namely, a flow chart of the whole operation process from the attribute data (namely, data required by audit) of the audit object to the specific index value obtained by operation);
the image association module is configured to generate a macro audit chart (i.e., a flowchart including an entire operation process from attribute data of an audit object (i.e., data required for audit) to an audit result obtained by operation of the audit macro object) of each macro audit target (i.e., the audit target at a macro angle, refer to fig. 2, such as planned budget, social responsibility, marketing, power supply reliability, labor productivity, engineering construction, operation index, security management, planned budget, etc.);
the anomaly determination module is used for determining an anomaly root of the audit object (namely, anomaly data existing in attribute data of the audit object (namely, data required by audit) or items or departments for which the anomaly data are aimed, and the like) based on the macroscopic audit graphs under all macroscopic audit targets;
the abnormality early warning module is used for generating early warning information (namely prompt information which contains relevant information of the abnormality source and is used as an early warning function) based on the abnormality source.
According to the embodiment, the abnormal root of the auditing object is traced back based on the macroscopic audit diagram representing the auditing operation process of a plurality of macroscopic auditing targets, so that the abnormal accurate positioning and high-efficiency accurate early warning in the auditing object management process are realized, and the follow-up maintenance and improvement of the abnormal situation obtained by the supervision early warning system are facilitated.
Example 2
On the basis of embodiment 1, the image generation module includes:
the index item determining submodule is used for determining index items required by all macroscopic audit targets (namely more specific audit operation index items such as task indexes, asset liability rates, main service income increasing rates, service income profit rates and the like which are obtained in the process of obtaining the audit results of the macroscopic audit targets in the operation process) based on macroscopic audit rules (namely operation rules comprising how to calculate from the audit indexes to obtain the audit results of the macroscopic audit targets) of all macroscopic audit targets;
the data extraction sub-module is used for extracting the required data of the audit index (namely the attribute data of the audit object required for calculating the audit index value of the audit index) from the data to be audited of the audit object based on the preset audit rule of each audit index (namely the operation rule comprising how to obtain the specific index value of the audit index from the attribute data of the audit object (namely the required data of the audit) to be audited);
the index operation sub-module is used for carrying out operation based on preset audit rules and audit required data of each audit index to obtain all operation intermediate quantities of the audit index (namely, intermediate variables obtained in the whole operation process from the audit required data to the audit index value of the calculated audit index, for example, the operation intermediate quantities of the audit index of the task index have the per-year profit and receipt completion rate) and the audit index value (namely, the audit result of the audit object calculated based on the audit required data for the audit index, for example, the asset liability rate is forty percent);
the flow drawing sub-module is used for generating an operation flow chart of each audit index based on the data required by the audit of each audit index, the operation intermediate quantity and the audit index value (namely, the operation flow chart is obtained by sequentially connecting the data required by the audit of the audit index, the operation intermediate quantity and the finally obtained audit index value according to the obtaining sequence in the operation process).
From the macroscopic audit rule of the macroscopic audit target to the audit index, from the preset audit rule of the audit index to the process of determining the required data of the audit, the accurate positioning from the macroscopic target to the microscopic data is realized, the required data of the audit is further determined, the operation rule and the required data of the audit are utilized to gradually calculate and obtain the audit result of the macroscopic target, an operation flow chart is generated, the extraction of the required data of the audit and the operation of the audit index value and the macroscopic audit target are realized in the whole process, and the operation process is characterized by utilizing the operation flow chart, so that the transparency and the intuitiveness of the audit operation process are realized.
Example 3
On the basis of embodiment 1, the image association module includes:
the required index determination submodule is used for determining an audit index required by each macroscopic audit target in all audit indexes based on the macroscopic audit rule of each macroscopic audit target;
the flow chart connection sub-module is used for generating a macroscopic audit chart under each macroscopic audit target based on each macroscopic audit rule and an operation flow chart of the audit indexes required by the corresponding macroscopic audit target.
The process generates a macroscopic audit graph which comprises the whole operation process from the attribute data of the audit object (namely data required by audit) to the operation to obtain the audit result of the macroscopic audit object, and realizes the transparency and the visualization of the operation process of the macroscopic audit object.
Example 4
On the basis of embodiment 3, the flowchart connects sub-modules, including:
the macro audit operation unit is used for calculating the audit index value of the audit index determined by the operation flow chart of the audit index required by each macro audit target based on the macro audit rule to obtain the macro audit result of the macro audit target;
the primary connection unit is used for carrying out primary connection on a macroscopic audit result of the macroscopic audit target and an operation flow chart of an audit index required by the macroscopic audit target based on each macroscopic audit rule, so as to obtain a primary operation chart of each macroscopic audit target;
the operation level determining unit is used for determining an operation level of an audit index required by each macroscopic audit target in a macroscopic audit rule (the numerical value of the operation level is the same as the calculation step number of the audit index in the macroscopic audit rule);
and the variable merging unit is used for merging the data required by the coincident audit and the operation intermediate quantity in the operation flow chart of the audit indexes of the same operation level in the audit indexes required by each macroscopic audit target, and the macroscopic audit chart under each macroscopic audit target.
In the embodiment, the construction of the macroscopic audit graph is completed by combining the data required by the coincident audit and the operation intermediate quantity in the operation flow diagrams of the audit indexes of the same operation level and the connection of the operation flow diagrams, and the subsequent abnormal root tracing is facilitated by combining the data required by the coincident audit and the operation intermediate quantity in the operation flow diagrams of the audit indexes of the same operation level.
Example 5
On the basis of embodiment 1, the abnormality determination module includes:
the deviation rate determination submodule is used for determining the deviation rate of the macroscopic audit result of all macroscopic audit targets in the corresponding macroscopic audit graph and the standard audit result (namely, the macroscopic audit result corresponding to the condition that the audit object is abnormal);
the splicing fitting sub-module is used for carrying out dimensionality-division splicing fitting on the deviation values of all macroscopic audit targets based on various preset dimensions (such as time dimension, space dimension, economic dimension, safety dimension, construction dimension and the like) to obtain a macroscopic deviation characterization graph of the audit object in each preset dimension (namely, a characterization graph of the distribution condition (change condition) of the deviation rate of the macroscopic audit result of the macroscopic deviation target containing the audit object and the standard audit result in a single preset dimension);
the abnormality determination sub-module is used for determining an abnormality root of the audit object based on the macroscopic deviation characterization graph of each preset dimension and the macroscopic audit graphs under all macroscopic audit targets.
The deviation rate of the macroscopic audit result and the standard audit result in the macroscopic audit diagram is analyzed in multiple dimensions, and the macroscopic deviation characterization diagram containing the distribution or change characteristics of the deviation rate of the macroscopic audit result and the standard audit result of the macroscopic deviation target of the audit object in the corresponding single dimension is spliced and fitted, so that the traced abnormal root of the audit object is more accurate and efficient.
Example 6
On the basis of embodiment 5, the splice fitting sub-module includes:
the target classification summarizing unit is used for determining and summarizing all macroscopic audit targets with time sequence change characteristics among all macroscopic audit targets, and taking the macroscopic audit targets as time-varying characteristic target groups (the macroscopic audit targets with time sequence change characteristics among each other are the only variables with time change, for example, the only variables between the two macroscopic audit targets, namely the current quarter planning budget and the planning budget of the last quarter, are time variables, in addition, the time sequence change characteristics are the time sequence change characteristics among two or more macroscopic audit targets, in addition, the time sequence change characteristic target groups are clusters of the macroscopic audit targets with the time sequence change characteristics among each other);
the deviation value fitting unit is used for determining time sequence change characteristics among all macroscopic audit targets in the time-varying characteristic target group (namely, characteristics representing how to change in time or time sequence among the macroscopic audit targets, such as time sequence change characteristics among two macroscopic audit targets of the planning budget of the quarter and the planning budget of the previous quarter, namely, change according to the quarter and the planning budget of the previous quarter before the planning budget of the quarter), and performing curve fitting on deviation values of all macroscopic audit targets in the corresponding time-varying characteristic target group (performing curve fitting according to a time sequence corresponding to the time sequence change characteristics from front to back) based on the time sequence change characteristics to obtain a deviation time sequence change diagram (namely, a curve graph containing time change of the deviation values of all macroscopic audit targets in the time-varying characteristic target group);
the time sequence change diagram alignment unit is used for performing time sequence alignment on all deviation time sequence change diagrams to obtain a macroscopic deviation characterization diagram of an audit object in a time dimension;
the deviation splicing fitting unit is used for splicing the deviation values of all macroscopic audit targets based on the space dimension to obtain a macroscopic deviation characterization diagram of the audit object in the space dimension;
the preset dimension comprises a time dimension and a space dimension.
According to the embodiment, curve fitting and image generation are carried out on the variation condition of the deviation rate of the macroscopic audit result and the standard audit result of all the macroscopic audit targets in the corresponding macroscopic audit graphs in a single dimension through two dimensions of the time dimension and the space dimension, so that the variation condition and the distribution condition of the deviation rate of the macroscopic audit result and the standard audit result of all the macroscopic audit targets in the corresponding macroscopic audit graphs in the time dimension and the space dimension are more visual and clear.
Example 7
On the basis of embodiment 6, the bias splice fitting unit includes:
the target classification summarizing subunit is configured to determine and summarize all macroscopic audit targets with spatial distribution change features between each other in all macroscopic audit targets, where the macroscopic audit targets with spatial distribution change features between each other are spatial distribution change only in displacement variable, such as engineering construction of a region a and engineering construction of a region B, and the spatial distribution change features are spatial distribution change features between two or more macroscopic audit targets, and the spatial distribution change feature target group is a cluster of macroscopic audit targets with spatial distribution change features between each other;
the deviation value splicing subunit is used for determining spatial distribution change characteristics among all macroscopic audit targets in the spatial distribution change characteristic target group (namely, characteristics representing how the macroscopic audit targets change in a spatial distribution area) and splicing deviation values of all macroscopic audit targets in the corresponding spatial distribution change characteristic target group based on the spatial distribution change characteristics (splicing of areas (two-dimensional or three-dimensional) according to the principle of spatial distribution corresponding to the spatial distribution change characteristics) to obtain a deviation spatial distribution map (namely, images containing different distribution conditions of the deviation values of all macroscopic audit targets in the spatial distribution change characteristic target group);
and the spatial distribution diagram alignment subunit is used for carrying out spatial alignment on all deviation spatial distribution diagrams to obtain a macroscopic deviation characterization diagram of the auditing object in the spatial dimension.
According to the embodiment, the change condition of the deviation rate of the macro audit results and the standard audit results in the corresponding macro audit graphs in the space dimension is subjected to region splicing based on the space dimension, so that the change condition and the distribution condition of the deviation rate of the macro audit results and the standard audit results in the corresponding macro audit graphs in the space dimension are more visual and clear.
Example 8
On the basis of embodiment 5, the abnormality determination submodule includes:
the weight determining unit is used for determining the dimension abnormal weight of each preset dimension based on the macro deviation characterization graph of each preset dimension (namely, in the subsequent process of tracing the source of the macro audit graph of all macro audit targets corresponding to the macro deviation characterization graph, calculating the effective occupation ratio of the deviation rate of the middle quantity or the time required by the audit, wherein the dimension abnormal weight is also the rule degree of the deviation rate contained in the macro deviation characterization graph along with the dimension (such as the space distribution change direction and the time sequence change), when the dimension abnormal weight is the space dimension, the calculation mode of the dimension abnormal weight is that the approximate direction of the deviation rate along with the space change in the macro deviation characterization graph (namely, the direction along with the space change of the deviation rate met by the maximum quantity in the macro deviation characterization graph) is determined, the ratio of the total number of the deviation rates meeting the approximate direction in the macro deviation characterization graph to the deviation rate in the macro deviation characterization graph is regarded as the child weight, and the average value of all the macro deviation characterization graph is regarded as the dimension abnormal weight, when the dimension abnormal weight is the time dimension (such that the dimension abnormal weight is the space distribution change direction and the time sequence change direction), and the value of the average value of the macro deviation graph is calculated in the time curve is regarded as the value of the average value of the error curve of the error value of the macro deviation graph is calculated once;
the root source tracing unit is used for tracing abnormal root sources of all macroscopic audit graphs of all macroscopic audit targets corresponding to the macroscopic deviation characterization graph based on the dimension abnormal weight, and determining the abnormal root source of the audit object.
In the process, the deviation rate of intermediate quantity or time required by audit is calculated in the process of carrying out abnormal root tracing on the macro audit graphs of all macro audit targets corresponding to the macro deviation characterization graph by calculating the deviation rate, and the dimension abnormal weight of the deviation rate contained in the macro deviation characterization graph along with the rule degree of the dimension (such as the space distribution change direction and the time sequence change) is characterized, so that the accurate positioning of the abnormal condition of the audit objects is realized.
Example 9
On the basis of embodiment 8, an anomaly traceback unit includes:
an anomaly determination value calculation subunit, configured to calculate anomaly determination values of all data required for audit (sequentially determining whether there is a change feature (i.e., an order change feature or a spatial distribution change feature) of a certain preset dimension in a relation between an input amount and an output amount in each operation step in the macroscopic audit graph in a sequential manner from the operation step of the macroscopic audit graph) based on all operation intermediate amounts and corresponding standard audit values (i.e., preset values of operation intermediate amounts under no anomaly condition) in the macroscopic audit graph of all macroscopic audit targets corresponding to the dimension anomaly weights and the macroscopic deviation characterization graph, if yes, regarding a deviation rate of the output amount as an anomaly determination value of the input amount, and regarding a product of the anomaly determination value of the output amount and the anomaly weight of (1+ dimension) as an anomaly determination value of the input amount, otherwise, analogizing the macroscopic audit graph until the operation step is traversed, and calculating an anomaly determination value of the input amount (i.e., required data) in the last operation step from the last step;
the abnormal root determining unit is used for determining the abnormal root of the auditing object based on the abnormal judging values of all the data required by the auditing (namely, taking the data required by the auditing corresponding to the maximum abnormal judging value or the items or departments corresponding to the data required by the auditing as the abnormal root).
In the embodiment, the process performs gradual tracing on the macroscopic audit graph based on the determined dimension abnormal weight, so that efficient and accurate tracing on abnormal conditions of the audit object and final positioning are realized.
Example 10:
the invention provides an intelligent audit supervision and early warning method, which comprises the following steps with reference to figures 2 and 3:
s1: generating an operation flow chart of each audit index based on the to-be-audited data of the audit object;
s2: generating a macroscopic audit map of each macroscopic audit target based on the operation flow diagrams of all audit indexes;
s3: determining an abnormal root of an audit object based on the macroscopic audit graphs under all macroscopic audit targets;
s4: and generating early warning information based on the abnormal root cause.
According to the embodiment, the abnormal root of the auditing object is traced back based on the macroscopic audit diagram representing the auditing operation process of a plurality of macroscopic auditing targets, so that the abnormal accurate positioning and high-efficiency accurate early warning in the auditing object management process are realized, and the follow-up maintenance and improvement of the abnormal situation obtained by the supervision early warning system are facilitated.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. An intelligent audit supervision and early warning system, comprising:
the image generation module is used for generating an operation flow chart of each audit index based on the to-be-audited data of the audit object;
the image association module is used for generating a macroscopic audit graph of each macroscopic audit target based on the operation flow diagrams of all audit indexes;
the abnormality determining module is used for determining an abnormality root of the auditing object based on the macroscopic audit graphs under all macroscopic audit targets;
the abnormality early warning module is used for generating early warning information based on an abnormality root cause;
wherein, the image association module includes:
the required index determination submodule is used for determining an audit index required by each macroscopic audit target in all audit indexes based on the macroscopic audit rule of each macroscopic audit target;
the flow chart connection sub-module is used for generating a macroscopic audit chart under each macroscopic audit target based on each macroscopic audit rule and an operation flow chart of the audit indexes required by the corresponding macroscopic audit target;
wherein the flow chart connects the submodule, include:
the macro audit operation unit is used for calculating the audit index value of the audit index determined by the operation flow chart of the audit index required by each macro audit target based on the macro audit rule to obtain the macro audit result of the macro audit target;
the primary connection unit is used for carrying out primary connection on a macroscopic audit result of the macroscopic audit target and an operation flow chart of an audit index required by the macroscopic audit target based on each macroscopic audit rule, so as to obtain a primary operation chart of each macroscopic audit target;
the operation level determining unit is used for determining the operation level of the audit indexes required by each macroscopic audit target in the macroscopic audit rule;
the variable merging unit is used for merging the data required by the coincident audit in the operation flow chart of the audit indexes of the same operation level in the audit indexes required by each macroscopic audit target and the operation intermediate quantity, and the macroscopic audit chart under each macroscopic audit target;
wherein, the anomaly determination module includes:
the deviation rate determination submodule is used for determining the deviation rate of the macroscopic audit result and the standard audit result of all the macroscopic audit targets in the corresponding macroscopic audit graphs;
the splicing fitting sub-module is used for carrying out dimensionality splicing fitting on the deviation values of all macroscopic audit targets based on a plurality of preset dimensionalities, and obtaining a macroscopic deviation characterization diagram of the audit objects in each preset dimensionalities;
the abnormality determination submodule is used for determining an abnormality root of an audit object based on the macroscopic deviation characterization graph of each preset dimension and the macroscopic audit graphs under all macroscopic audit targets;
wherein, sub-module is fitted in concatenation includes:
the target classification summarizing unit is used for determining and summarizing all macroscopic audit targets with time sequence change characteristics from all macroscopic audit targets to serve as time-varying characteristic target groups;
the deviation value fitting unit is used for determining time sequence change characteristics among all macroscopic audit targets in the time-varying characteristic target group, and performing curve fitting on deviation values of all macroscopic audit targets in the corresponding time-varying characteristic target group based on the time sequence change characteristics to obtain a deviation time sequence change diagram;
the time sequence change diagram alignment unit is used for performing time sequence alignment on all deviation time sequence change diagrams to obtain a macroscopic deviation characterization diagram of an auditing object in a time dimension;
the deviation splicing fitting unit is used for splicing the deviation values of all macroscopic audit targets based on the space dimension to obtain a macroscopic deviation characterization diagram of the audit object in the space dimension;
the preset dimension comprises a time dimension and a space dimension.
2. The intelligent audit administration early warning system of claim 1, wherein the image generation module comprises:
the index item determining submodule is used for determining index items required by all macroscopic audit targets as audit indexes based on macroscopic audit rules of all macroscopic audit targets;
the data extraction sub-module is used for extracting the data required by auditing of the auditing indexes from the data to be audited of the auditing objects based on the preset auditing rules of each auditing index;
the index operation sub-module is used for carrying out operation based on preset audit rules of each audit index and data required by audit to obtain all operation intermediate quantities and audit index values of the audit index;
and the flow drawing submodule is used for generating an operation flow chart of each audit index based on the data required by the audit of each audit index, the operation intermediate quantity and the audit index value.
3. The intelligent audit supervision and early warning system according to claim 1, wherein the deviation splice fitting unit includes:
the target classification summarizing subunit is used for determining and summarizing all macroscopic audit targets with spatial distribution change characteristics among all macroscopic audit targets to be used as a spatial distribution change characteristic target group;
the deviation value splicing subunit is used for determining the spatial distribution change characteristics among all macroscopic audit targets in the spatial distribution change characteristic target group, and splicing the deviation values of all macroscopic audit targets in the corresponding spatial distribution change characteristic target group based on the spatial distribution change characteristics to obtain a deviation spatial distribution map;
and the spatial distribution diagram alignment subunit is used for carrying out spatial alignment on all deviation spatial distribution diagrams to obtain a macroscopic deviation characterization diagram of the auditing object in the spatial dimension.
4. The intelligent audit supervision early warning system of claim 1, wherein the anomaly determination sub-module comprises:
the weight determining unit is used for determining the dimension abnormal weight of each preset dimension based on the macroscopic deviation characterization graph of each preset dimension;
the root source tracing unit is used for tracing abnormal root sources of all macroscopic audit graphs of all macroscopic audit targets corresponding to the macroscopic deviation characterization graph based on the dimension abnormal weight, and determining the abnormal root source of the audit object.
5. The intelligent audit supervision and early warning system according to claim 4, wherein the anomaly traceback unit includes:
the abnormal judgment value calculation subunit is used for calculating the abnormal judgment value of all data required by audit based on the dimension abnormal weight and the standard audit value corresponding to the sum of all operation intermediate quantities in the macroscopic audit graphs of all macroscopic audit targets corresponding to the macroscopic deviation characterization graph;
and the abnormal root cause determining unit is used for determining the abnormal root cause of the auditing object based on the abnormal judgment values of all the data required by the auditing.
6. An intelligent audit supervision and early warning method, which is characterized by being applied to the intelligent audit supervision and early warning system as claimed in any one of claims 1 to 5, and comprising:
s1: generating an operation flow chart of each audit index based on the to-be-audited data of the audit object;
s2: generating a macroscopic audit map of each macroscopic audit target based on the operation flow diagrams of all audit indexes;
s3: determining an abnormal root of an audit object based on the macroscopic audit graphs under all macroscopic audit targets;
s4: and generating early warning information based on the abnormal root cause.
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