CN112348521A - Intelligent risk quality inspection method and system based on business audit and electronic equipment - Google Patents
Intelligent risk quality inspection method and system based on business audit and electronic equipment Download PDFInfo
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Abstract
The invention provides an intelligent risk quality inspection method and system based on business audit and electronic equipment. The method comprises the following steps: receiving configuration information input by a user to generate a plurality of quality inspection random check rules, wherein each quality inspection random check rule is a rule for performing quality inspection on cases extracted by different services; extracting cases to be inspected from a plurality of different services according to a plurality of quality inspection sampling rules; automatically performing quality inspection on the extracted cases to be subjected to quality inspection, and generating a risk evaluation result of the case; displaying the risk evaluation result to a user, receiving confirmation operation of the user on the risk of each case, and generating a quality inspection result of each case; summarizing the quality inspection results of all cases to generate a quality inspection data report; and monitoring the quality inspection data report at regular time, and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions. The method of the invention improves the quality inspection work efficiency, optimizes the business auditing process, reduces the repetitive workload and ensures the quality inspection accuracy.
Description
Technical Field
The invention relates to the field of computer information processing, in particular to an intelligent risk quality inspection method and system based on business audit and electronic equipment.
Background
Risk control (wind control for short) refers to the risk manager taking various measures and methods to eliminate or reduce the various possibilities of occurrence of a risk event, or the risk controller reducing the losses caused when a risk event occurs. The risk control is generally applied to the financial industry, such as risk control on company transactions, merchant transactions or personal transactions and the like.
At present, the quality inspection of the whole flow is a crucial link of financial wind control, on one hand, the comprehensive review condition of an auditor can be copied, on the other hand, the quality inspection can be used for reversely feeding a wind control strategy and reinforcing a wind control safety net through the personnel error analysis of different service scenes. The existing quality inspection mode is to periodically extract a certain proportion of cases to monitor the business so as to complete the risk quality inspection. However, from the statistical point of view, the results obtained by simple random sampling cannot completely reflect the problem and symptom, and are easily influenced by the main observation, the existing spot inspection mode is time-consuming and labor-consuming, the quality inspection timeliness and the spot inspection coverage rate are low, and the following problems exist in the practical process: the coverage rate is low: cases with different service scenes can be as many as ten thousand every day, the quality inspection cannot be completely covered, and omission situations exist; the timeliness is low: because the quality inspection is in a relatively lagged link, the quality inspection result can be obtained only by circulating a part of cases for multiple days, and the risk condition of false passing is correspondingly delayed and intercepted; the efficiency is low: the manual quality inspection of a case consumes less time, several minutes and more half a day, some quality inspection processes of a specific service scene are completely non-differentiated quality inspection results, and the quality inspection efficiency can be greatly reduced by a large amount of repeated quality inspection contents for a long time.
Therefore, it is necessary to provide an intelligent risk quality inspection method with higher quality inspection accuracy.
Disclosure of Invention
In order to solve the problems of scattered risk points, low manual efficiency and large accuracy fluctuation of manual quality inspection work, the invention provides an intelligent risk quality inspection method based on business audit. The intelligent risk quality inspection method comprises the following steps: receiving configuration information input by a user to generate a plurality of quality inspection random check rules, wherein each quality inspection random check rule is a rule for performing quality inspection on cases extracted by different services; extracting cases to be inspected from a plurality of different services according to a plurality of quality inspection sampling rules; for the extracted cases to be subjected to quality inspection, calling corresponding automatic quality inspection processes according to the business types of the cases to automatically perform quality inspection on the cases to be subjected to quality inspection, and generating risk evaluation results of the cases; displaying the risk evaluation result to a user, receiving confirmation operation of the user on the risk of each case, and generating a quality inspection result of each case; summarizing the quality inspection results of all cases to generate a quality inspection data report; and monitoring the quality inspection data report at regular time, and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions.
Preferably, the receiving configuration information input by a user to generate a plurality of quality inspection sampling rules comprises: and displaying a visual rule configuration interface, and providing different quality inspection sampling inspection rule configuration templates according to different service types and logics so that a user can input configuration information.
Preferably, the service includes an electric connection service, a transaction link service and a product line service; presetting a risk point and a high-frequency error point based on different services, and configuring a quality inspection sampling rule based on the risk point and the high-frequency error point; the quality inspection sampling check rule comprises an identification rule, an extraction rule, a service quality inspection rule and a judgment rule.
Preferably, the automatic quality inspection process comprises: the method comprises the steps of detecting a case falling into a warehouse, extracting a case to be subjected to quality inspection, identifying the case to be subjected to quality inspection so as to shunt the case to a corresponding automatic quality inspection module, performing automatic quality inspection processing, confirming risks, calculating automatic quality inspection results in a gathering mode, and feeding back the effect of automatic quality inspection to a control platform.
Preferably, the automatically performing quality inspection on the case to be inspected, and the generating a risk assessment result of the case includes: and according to a preset risk judgment strategy, automatically carrying out risk point positioning and risk size estimation on the case to be subjected to quality inspection.
Preferably, the step of summarizing the quality inspection results of the cases and generating a quality inspection data report includes: and performing statistical calculation on the quality inspection result, and storing the statistical result in a data report platform, wherein the data report platform can be called by a user to generate a visual report.
Preferably, the periodically monitoring the quality inspection data report, and the generating of the quality inspection abnormal information and the quality inspection sampling rule updating suggestion includes: calling a quality inspection data report at regular time, and detecting data in the called quality inspection data report according to a borne abnormal detection rule; and when the data in the quality inspection data report is detected to be abnormal, generating quality inspection abnormal information.
Preferably, the generating of the quality inspection sampling rule update suggestion further comprises: and generating quality inspection sampling rule updating suggestions according to the quality inspection abnormal information and preset suggestion generation rules, wherein the suggestion generation rules comprise suggestions of business process blocks, personnel, parts and sampling intensity of quality inspection.
In addition, the invention also provides an intelligent risk quality inspection system based on business audit, which comprises: the receiving module is used for receiving configuration information input by a user to generate a plurality of quality inspection random check rules, and each quality inspection random check rule is a rule for performing quality inspection on cases extracted by different services; the extraction module is used for extracting cases to be subjected to quality inspection from a plurality of different services according to a plurality of quality inspection sampling rules; the quality inspection module is used for calling a corresponding automatic quality inspection process to automatically perform quality inspection on the cases to be subjected to quality inspection according to the service types of the cases to generate risk evaluation results of the cases; the generating module is used for displaying the risk evaluation result to a user, receiving confirmation operation of the user on the risk of each case and generating a quality inspection result of each case; the collecting module is used for collecting the quality inspection results of all cases and generating a quality inspection data report; and the monitoring module is used for monitoring the quality inspection data report at regular time and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions.
Preferably, the system further comprises a display module, wherein the display module is used for displaying the visual rule configuration interface and providing different quality inspection sampling inspection rule configuration templates for the user to input configuration information according to different service types and logics.
Preferably, the service includes an electric connection service, a transaction link service and a product line service; presetting a risk point and a high-frequency error point based on different services, and configuring a quality inspection sampling rule based on the risk point and the high-frequency error point; the quality inspection sampling check rule comprises an identification rule, an extraction rule, a service quality inspection rule and a judgment rule.
Preferably, the automatic quality inspection process comprises: the method comprises the steps of detecting a case falling into a warehouse, extracting a case to be subjected to quality inspection, identifying the case to be subjected to quality inspection so as to shunt the case to a corresponding automatic quality inspection module, performing automatic quality inspection processing, confirming risks, calculating automatic quality inspection results in a gathering mode, and feeding back the effect of automatic quality inspection to a control platform.
Preferably, the system further comprises a calculation module, and the calculation module automatically carries out risk point positioning and risk size estimation on the case to be subjected to quality inspection according to a preset risk judgment strategy.
Preferably, the summarizing module further comprises: and performing statistical calculation on the quality inspection result, and storing the statistical result in a data report platform, wherein the data report platform can be called by a user to generate a visual report.
Preferably, the quality control data report is called regularly, and the data in the called quality control data report is detected according to the accepted abnormal detection rule; and when the data in the quality inspection data report is detected to be abnormal, generating quality inspection abnormal information.
Preferably, the generating of the quality inspection sampling rule update suggestion further comprises: and generating quality inspection sampling rule updating suggestions according to the quality inspection abnormal information and preset suggestion generation rules, wherein the suggestion generation rules comprise suggestions of business process blocks, personnel, parts and sampling intensity of quality inspection.
In addition, the present invention also provides an electronic device, wherein the electronic device includes: a processor; and a memory storing computer executable instructions that, when executed, cause the processor to perform the intelligent risk quality inspection method based on business audit of the present invention.
In addition, the present invention also provides a computer readable storage medium, wherein the computer readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the method for intelligent risk quality inspection based on business audit according to the present invention is implemented.
Advantageous effects
Compared with the prior art, the intelligent risk quality inspection method optimizes the traditional business rules into automatic quality inspection rules, provides a rule control platform for flexible configuration, intelligently identifies the risk characteristics of omission inspection according to the configured automatic quality inspection rules, accurately positions, automatically identifies and extracts cases to be inspected, shortens the quality inspection duration of each case to the second level by automatic quality inspection, and greatly improves the quality inspection working efficiency; the business auditing process is further optimized, the coverage rate is improved, the risk of case omission in the scattered business data is reduced, the repetitive workload of business personnel is reduced, and the quality inspection accuracy can be ensured.
Drawings
In order to make the technical problems solved by the present invention, the technical means adopted and the technical effects obtained more clear, the following will describe in detail the embodiments of the present invention with reference to the accompanying drawings. It should be noted, however, that the drawings described below are only illustrations of exemplary embodiments of the invention, from which other embodiments can be derived by those skilled in the art without inventive faculty.
Fig. 1 is a flowchart of an example of an intelligent risk quality inspection method based on business audit according to embodiment 1 of the present invention.
Fig. 2 is a flowchart of another example of the intelligent risk quality inspection method based on business audit according to embodiment 1 of the present invention.
Fig. 3 is a flowchart of another example of the intelligent risk quality inspection method based on business audit according to embodiment 1 of the present invention.
Fig. 4 is a schematic diagram of an example of an intelligent risk quality inspection system based on business audit according to embodiment 2 of the present invention.
Fig. 5 is a schematic diagram of another example of the intelligent risk quality inspection system based on business audit according to embodiment 2 of the present invention.
Fig. 6 is a schematic diagram of another example of the intelligent risk quality inspection system based on business audit according to embodiment 2 of the present invention.
Fig. 7 is a block diagram of an exemplary embodiment of an electronic device according to the present invention.
Fig. 8 is a block diagram of an exemplary embodiment of a computer-readable medium according to the present invention.
Detailed Description
Exemplary embodiments of the present invention will now be described more fully with reference to the accompanying drawings. The exemplary embodiments, however, may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. Rather, these exemplary embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the invention to those skilled in the art. The same reference numerals denote the same or similar elements, components, or parts in the drawings, and thus their repetitive description will be omitted.
Features, structures, characteristics or other details described in a particular embodiment do not preclude the fact that the features, structures, characteristics or other details may be combined in a suitable manner in one or more other embodiments in accordance with the technical idea of the invention.
In describing particular embodiments, the present invention has been described with reference to features, structures, characteristics or other details that are within the purview of one skilled in the art to provide a thorough understanding of the embodiments. One skilled in the relevant art will recognize, however, that the invention may be practiced without one or more of the specific features, structures, characteristics, or other details.
The flow charts shown in the drawings are merely illustrative and do not necessarily include all of the contents and operations/steps, nor do they necessarily have to be performed in the order described. For example, some operations/steps may be decomposed, and some operations/steps may be combined or partially combined, so that the actual execution sequence may be changed according to the actual situation.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. I.e. these functional entities may be implemented in the form of software, or in one or more hardware modules or integrated circuits, or in different networks and/or processor means and/or microcontroller means.
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, or sections, these terms should not be construed as limiting. These phrases are used to distinguish one from another. For example, a first device may also be referred to as a second device without departing from the spirit of the present invention.
The term "and/or" and/or "includes any and all combinations of one or more of the associated listed items.
In order to further optimize the business auditing process, reduce the risk of case omission in the scattered business data, reduce the repetitive workload and ensure the quality inspection accuracy. The invention provides an intelligent risk quality inspection method based on business audit, which optimizes traditional business rules into automatic quality inspection rules, provides a rule control platform for flexible configuration, intelligently identifies the risk characteristics of omission inspection according to the configured automatic quality inspection rules, accurately positions and automatically identifies and extracts cases to be inspected, shortens the quality inspection duration of each case to a second level through automatic quality inspection, and greatly improves the quality inspection working efficiency.
Example 1
In the following, an embodiment of the intelligent risk quality inspection method based on business audit according to the present invention will be described with reference to fig. 1 to 3.
Fig. 1 is a flowchart of an intelligent risk quality inspection method based on business audit according to the present invention. As shown in fig. 1, an intelligent risk quality inspection method includes the following steps.
Step S101, receiving configuration information input by a user to generate a plurality of quality inspection random check rules, wherein each quality inspection random check rule is a rule for performing quality inspection on cases extracted by different services.
And step S102, extracting cases to be inspected from a plurality of different businesses according to a plurality of quality inspection sampling rules.
Step S103, for the extracted cases to be quality-checked, according to the business types of the cases, calling corresponding automatic quality-checking processes to automatically perform quality checking on the cases to be quality-checked, and generating the risk evaluation results of the cases.
And step S104, displaying the risk evaluation result to a user, receiving confirmation operation of the user on the risk of each case, and generating a quality inspection result of each case.
And step S105, summarizing the quality inspection results of all cases and generating a quality inspection data report.
And step S106, monitoring the quality inspection data report regularly, and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions.
First, in step S101, configuration information input by a user is received to generate a plurality of quality inspection sampling rules, each of which is a rule for quality inspection of how cases are extracted for different services.
In this example, the method of the present invention is applied to an intelligent risk quality inspection system. The intelligent risk quality inspection system comprises a rule control platform and a data report platform, wherein the rule control platform is provided with a visual rule configuration interface, and the data report platform is used for carrying out statistical calculation on a monitored risk confirmation result and taking the form of a report.
It should be noted that, in this example, the rule console is a maintenance platform for various automatic quality inspection rules, and can be divided into customized rule sets of credit transfer to manual work, transaction links, and different product lines according to different service lines.
Specifically, a visual rule configuration interface is displayed to a business person, for example, the request input of the business person is received, and different quality inspection sampling inspection rule configuration templates are provided according to different business types and logics so that a user can input configuration information.
In the present example, the services include an electricity federation service, a transaction link service, a product line service and the like, wherein the electricity federation service refers to an approval link telephone service; the transaction link business refers to related business such as risk points (overdue, default and the like) in the financial transaction link after approval; the product line service refers to a related service for identifying a high-frequency error point in the conventional service of each product.
Furthermore, the visual rule configuration interface also comprises a plurality of quality inspection modules corresponding to different services, wherein each quality inspection module has own configuration logic and supports flexible setting and adjustment of corresponding rules of automatic quality inspection.
Specifically, the automatic quality inspection calculates the case to be inspected which hits the rule according to the configured rule, and provides a quality inspection result.
For example, a rule is configured with the name of 'limit wrongly written', the content of the rule is 'approver' suggested limit > system 'suggested limit', if a certain case is hit on the rule through calculation, the case is automatically extracted, a preliminary quality inspection result is given by default, and an automatic quality inspection is completed. Therefore, automatic quality inspection processing is achieved, manual checking and verification of each case are not needed, the whole process is automatically completed by the intelligent risk quality inspection system, and efficiency and precision are remarkably improved compared with the traditional process.
As shown in fig. 2, a step S201 of presetting a risk point and a high frequency error point based on different services is further included.
In step S201, a risk point and a high frequency error point are preset based on different services.
In this example, based on the risk point and the high frequency error point, configuration parameters are set to configure quality inspection sampling rules.
Specifically, the intelligent risk quality inspection system performs cluster analysis on a large number of repeated quality inspection contents in different service scenes according to feedback information of service personnel, deeply excavates scenes of the same type, labels data characteristics, selects different label arrangement combinations through a rule console after the characteristics are labeled, and determines a quality inspection scene with high occurrence frequency and no difference according to a cluster analysis result.
Further, based on the cluster analysis result, a risk point and a high-frequency error point are determined.
Furthermore, the automatic quality inspection random inspection rule is set through the rule control platform based on the determined or preset risk points and high-frequency error points so as to realize automatic identification of cases in the same or similar quality inspection scenes, therefore, more service scenes can be covered, all cases falling into the warehouse are marked and transmitted, the coverage of the whole scene is completed, the coverage rate is improved, the repetitive workload of service personnel is reduced, and the quality inspection accuracy can be ensured.
It should be noted that each quality inspection sampling rule is a rule for performing quality inspection on cases extracted by different businesses. Further, as an algorithm for the cluster analysis, for example, a K-means algorithm, a density-based algorithm, or the like is used. However, the present invention is not limited thereto, and the above description is only by way of example and is not to be construed as limiting the present invention.
Specifically, the quality inspection sampling rule comprises an identification rule, an extraction rule, a business quality inspection rule and a judgment rule, wherein the identification rule is used for identifying the case to be inspected and distributing the case to the corresponding quality inspection module, and the extraction rule is used for extracting the corresponding case according to the quality inspection content and the screening condition; the business quality inspection rule is used for performing quality inspection on the extracted cases to be inspected; and the judgment rule is used for judging whether the extracted case to be inspected has risk and risk condition.
Preferably, the extraction rule further comprises a sampling ratio and a quality inspection sampling time.
It should be noted that the above description is only given as a preferred example, and the present invention is not limited thereto.
Next, in step S102, a case to be quality checked is extracted from a plurality of different businesses according to a plurality of quality check sampling rules.
In this example, at the beginning of the automatic quality inspection process, the cases of the database dropping are periodically monitored, and a predetermined number of cases to be inspected are extracted from the cases of the database dropping in different businesses within a specific time period according to the extraction rules.
Preferably, the automatic quality inspection process comprises the steps of detecting a case falling into a library, extracting a case to be inspected, identifying the case to be inspected so as to be shunted to a corresponding automatic quality inspection module, automatically performing quality inspection processing, confirming risks, summarizing and calculating automatic quality inspection results, and feeding back an automatic quality inspection effect to the control platform.
For example, for an automatic quality inspection process, a quality inspection rule a of the electric company business is configured, a late-term automatic quality inspection rule b and a regular case automatic quality inspection rule c are defined. After the automatic quality inspection task flow starts, if the cases A, B and C hit the rules a, B and C respectively after the completion, the cases A, B and C are marked and extracted by a first automatic quality inspection module (power connection), a second automatic quality inspection module (overdue) and a third automatic quality inspection module (conventional) respectively.
It should be noted that the above description is only given as a preferred example, and the present invention is not limited thereto.
Next, in step S103, for the extracted case to be quality-tested, according to the service type of the case, a corresponding automatic quality-testing process is invoked to automatically perform quality testing on the case to be quality-tested, and a risk assessment result of the case is generated.
In the example, the extracted cases to be quality-checked are identified according to the identification rules, and the cases to be quality-checked are distributed to the corresponding automatic quality-checking modules according to the case service types. For example, the utility company service is distributed to a first automatic quality inspection module, the transaction link service is distributed to a second automatic quality inspection module, and the product line service is distributed to a third automatic quality inspection module.
Specifically, an automatic quality inspection processing flow is called, wherein each automatic quality inspection module performs quality inspection on the case to be inspected according to the business quality inspection rule so as to generate a risk evaluation result of the case.
Further, according to a preset risk judgment strategy, the risk point positioning and risk size estimation are automatically carried out on the case to be inspected.
In the present example, in the first automatic quality inspection module (corresponding to the service of the power federation) for the examination and approval loop, the call etiquette, the dialect forbidden words and the necessary dialect of the service personnel are detected in real time for quality inspection.
In another example, where a second automated quality inspection module (e.g., an overdue case) monitors for an overdue approval case after the user allocates resources, the approval risk confirmation is traced back to credit based on the user repayment performance data. In this example, the predetermined risk determination policy includes whether an overdue rate threshold is exceeded, or whether the number of overdues within a certain period of time exceeds a number threshold, and so on.
In yet another example, a third automated quality inspection module (conventional) implements initial filtering of the cases to be inspected by the rules console for high frequency error points and provides initial inspection conclusions that can be referenced when quality inspection is to be confirmed. In this example, the predetermined risk judgment policy includes a preset high frequency error point, whether the number of high frequency error points exceeds a number threshold, and the like.
Furthermore, each automatic quality inspection module automatically completes error positioning and quality inspection result acquiescence for the case according to the configured rule.
Next, in step S104, the risk assessment result is presented to the user, the confirmation operation of the user on the risk of each case is received, and the quality inspection result of each case is generated.
In this example, upon completion of the automated quality inspection process, the risk assessment results are presented to a user (e.g., a business person).
Specifically, based on the displayed risk assessment results, the automatic quality inspection results are subjected to secondary confirmation or manual review by a human (e.g., a business person) to generate quality inspection results of each case.
Next, in step S105, the quality inspection results of the cases are collected, and a quality inspection data report is generated.
Specifically, the quality inspection result of each case is transmitted to the data report platform, and the quality inspection data report is automatically generated on the data report platform according to the artificial risk confirmation result, wherein the report is an effect monitoring visual chart.
More specifically, after the risk of the quality inspection case is qualitative, the data report platform collects and counts the accuracy of the automatic quality inspection case in a report form.
Preferably, the quality inspection result is subjected to statistical calculation, and the statistical result is stored in a data report platform, wherein the data report platform can be called by a user to generate a visual report.
Next, in step S106, the quality inspection data report is monitored at regular time, and quality inspection abnormal information and quality inspection sampling rule update suggestions are generated.
In this example, the generated quality inspection data report, such as the hit number and hit accuracy of the monitoring rules, is monitored at regular time, and the monitoring effect is fed back to the rule control platform.
Specifically, the use effect of each automatic quality inspection rule can be evaluated according to the quality inspection data report, and abnormal information and quality inspection sampling rule updating suggestions are generated.
For example, a rule with poor effect is adjusted in time, specifically, a coincidence rate of a case hitting the rule and a quality inspection result given by a final person is observed, and the calculated coincidence rate is compared with a set threshold, wherein a quality inspection result with the coincidence rate being greater than or equal to the set threshold indicates that the quality inspection sampling rule is good, and a quality inspection result with the coincidence rate being less than the set threshold indicates that the quality inspection sampling rule needs to be adjusted. Generally, a higher calculated agreement rate indicates a more accurate quality inspection random access rule, and a lower calculated agreement rate indicates a deviation in the quality inspection random access rule that requires adjustment.
Furthermore, specific parameters in the configuration rules are adjusted manually to achieve targeted tuning, so that the hit accuracy of the automatic quality inspection rules is improved.
Preferably, the method further comprises the following steps: calling a quality inspection data report at regular time, and detecting data in the called quality inspection data report according to a borne abnormal detection rule; and when the data in the quality inspection data report is detected to be abnormal, generating quality inspection abnormal information.
Specifically, quality inspection sampling rule updating suggestions are generated according to quality inspection abnormal information and preset suggestion generation rules, and the suggestion generation rules comprise suggestions of business process blocks, personnel, parts and sampling intensity of quality inspection.
It should be noted that, in other examples, step S106 may be further split into step S106 and step S301, specifically referring to fig. 3. However, the present invention is not limited thereto, and the above description is only given as a preferred example, and is not to be construed as limiting the present invention.
It should be noted that the above-mentioned embodiments are only preferred embodiments, and should not be construed as limiting the present invention.
Those skilled in the art will appreciate that all or part of the steps to implement the above-described embodiments are implemented as programs (computer programs) executed by a computer data processing apparatus. When the computer program is executed, the method provided by the invention can be realized. Furthermore, the computer program may be stored in a computer readable storage medium, which may be a readable storage medium such as a magnetic disk, an optical disk, a ROM, a RAM, or a storage array composed of a plurality of storage media, such as a magnetic disk or a magnetic tape storage array. The storage medium is not limited to centralized storage, but may be distributed storage, such as cloud storage based on cloud computing.
Compared with the prior art, the intelligent risk quality inspection method optimizes the traditional business rules into automatic quality inspection rules, provides a rule control platform for flexible configuration, intelligently identifies the missed risk characteristics (corresponding to risk points and error points) according to the configured automatic quality inspection rules, accurately positions and automatically identifies and extracts cases to be inspected, shortens the quality inspection duration of each case to the second level by automatic quality inspection, and greatly improves the quality inspection working efficiency; the business auditing process is further optimized, the coverage rate is improved, the risk of case omission in the scattered business data is reduced, the repetitive workload of business personnel is reduced, and the quality inspection accuracy can be ensured.
Example 2
Embodiments of systems of the present invention are described below, which may be used to perform method embodiments of the present invention. Details described in the system embodiments of the invention should be considered supplementary to the above-described method embodiments; reference is made to the above-described method embodiments for details not disclosed in the system embodiments of the invention.
Referring to fig. 4, 5 and 6, the present invention further provides an intelligent risk quality inspection system 400 based on business audit, including: a receiving module 401, configured to receive configuration information input by a user to generate a plurality of quality inspection sampling rules, where each quality inspection sampling rule is a rule for performing quality inspection on cases extracted by different services; an extracting module 402, configured to extract a case to be quality inspected from multiple different services according to multiple quality inspection sampling rules; the quality inspection module 403 is used for calling a corresponding automatic quality inspection process to automatically perform quality inspection on the cases to be subjected to quality inspection according to the service types of the cases, and generating risk evaluation results of the cases; a generating module 404, configured to show the risk assessment result to a user, receive a confirmation operation of the user on the risk of each case, and generate a quality inspection result of each case; a collecting module 405, configured to collect the quality inspection results of the cases, and generate a quality inspection data report; and the monitoring module 406 is used for monitoring the quality inspection data report regularly and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions.
As shown in fig. 5, the system further includes a display module 501, where the display module is configured to display a visual rule configuration interface, and provide different quality inspection sampling inspection rule configuration templates according to different service types and logics, so that a user can input configuration information.
Preferably, the service includes an electric connection service, a transaction link service and a product line service; presetting a risk point and a high-frequency error point based on different services, and configuring a quality inspection sampling rule based on the risk point and the high-frequency error point; the quality inspection sampling check rule comprises an identification rule, an extraction rule, a service quality inspection rule and a judgment rule.
Preferably, the automatic quality inspection process comprises: the method comprises the steps of detecting a case falling into a warehouse, extracting a case to be subjected to quality inspection, identifying the case to be subjected to quality inspection so as to shunt the case to a corresponding automatic quality inspection module, performing automatic quality inspection processing, confirming risks, calculating automatic quality inspection results in a gathering mode, and feeding back the effect of automatic quality inspection to a control platform.
As shown in fig. 6, the system further includes a calculating module 601, where the calculating module 601 automatically performs risk point positioning and risk size estimation on a case to be inspected according to a predetermined risk judgment policy.
Preferably, the summarizing module further comprises: and performing statistical calculation on the quality inspection result, and storing the statistical result in a data report platform, wherein the data report platform can be called by a user to generate a visual report.
Preferably, the method further comprises the following steps: calling a quality inspection data report at regular time, and detecting data in the called quality inspection data report according to a borne abnormal detection rule; and when the data in the quality inspection data report is detected to be abnormal, generating quality inspection abnormal information.
Preferably, the generating of the quality inspection sampling rule update suggestion further comprises: and generating quality inspection sampling rule updating suggestions according to the quality inspection abnormal information and preset suggestion generation rules, wherein the suggestion generation rules comprise suggestions of business process blocks, personnel, parts and sampling intensity of quality inspection.
In embodiment 2, the same portions as those in embodiment 1 are not described.
Those skilled in the art will appreciate that the modules in the above-described system embodiments may be distributed in the system as described, and that corresponding variations may be made in one or more systems other than the above-described embodiments. The modules of the above embodiments may be combined into one module, or further split into multiple sub-modules.
Compared with the prior art, the intelligent risk quality inspection system optimizes the traditional business rules into automatic quality inspection rules, provides a rule control platform for flexible configuration, intelligently identifies the missed risk characteristics (corresponding to risk points and error points) according to the configured automatic quality inspection rules, accurately positions, automatically identifies and extracts cases to be inspected, shortens the quality inspection duration of each case to the second level by automatic quality inspection, and greatly improves the quality inspection working efficiency; the business auditing process is further optimized, the risk of case omission in the scattered business data is reduced, the coverage rate is improved, the repetitive workload of business personnel is reduced, and the quality inspection accuracy can be ensured.
Example 3
Embodiments of the electronic device of the present invention are described below, which may be considered as specific physical implementations of the above-described embodiments of the method and system of the present invention. Details described in the embodiments of the electronic device of the invention should be considered supplementary to the embodiments of the method or system described above; for details not disclosed in the embodiments of the electronic device of the invention, reference may be made to the above-described method or system embodiments.
Fig. 7 is a block diagram of an exemplary embodiment of an electronic device according to the present invention. An electronic apparatus 200 according to this embodiment of the present invention is described below with reference to fig. 7. The electronic device 200 shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, the electronic device 200 is embodied in the form of a general purpose computing device. The components of the electronic device 200 may include, but are not limited to: at least one processing unit 210, at least one memory unit 220, a bus 230 connecting different system components (including the memory unit 220 and the processing unit 210), a display unit 240, and the like.
Wherein the storage unit stores program code executable by the processing unit 210 to cause the processing unit 210 to perform steps according to various exemplary embodiments of the present invention described in the processing method section of the electronic device described above in this specification. For example, the processing unit 210 may perform the steps as shown in fig. 1.
The memory unit 220 may include readable media in the form of volatile memory units, such as a random access memory unit (RAM)2201 and/or a cache memory unit 2202, and may further include a read only memory unit (ROM) 2203.
The storage unit 220 may also include a program/utility 2204 having a set (at least one) of program modules 2205, such program modules 2205 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 200 may also communicate with one or more external devices 300 (e.g., keyboard, pointing device, bluetooth device, etc.), with one or more devices that enable a user to interact with the electronic device 200, and/or with any devices (e.g., router, modem, etc.) that enable the electronic device 200 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 250. Also, the electronic device 200 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the Internet) via the network adapter 260. The network adapter 260 may communicate with other modules of the electronic device 200 via the bus 230. It should be appreciated that although not shown in the figures, other hardware and/or software modules may be used in conjunction with the electronic device 200, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments of the present invention described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiment of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to make a computing device (which can be a personal computer, a server, or a network device, etc.) execute the above-mentioned method according to the present invention. The computer program, when executed by a data processing apparatus, enables the computer readable medium to carry out the above-described methods of the invention.
As shown in fig. 8, the computer program may be stored on one or more computer readable media. The computer readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable storage medium may include a propagated data signal with readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A readable storage medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
In summary, the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. Those skilled in the art will appreciate that some or all of the functionality of some or all of the components in embodiments in accordance with the invention may be implemented in practice using a general purpose data processing device such as a microprocessor or a Digital Signal Processor (DSP). The present invention may also be embodied as apparatus or system programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
While the foregoing detailed description of the embodiments has described the objects, solutions, and advantages of the present invention in further detail, it is to be understood that the present invention is not inherently related to any particular computer, virtual machine, or electronic device, but may be implemented in various general-purpose systems. The invention is not to be considered as limited to the specific embodiments thereof, but is to be understood as being modified in all respects, all changes and equivalents that come within the spirit and scope of the invention.
Claims (10)
1. An intelligent risk quality inspection method based on business audit is characterized by comprising the following steps:
receiving configuration information input by a user to generate a plurality of quality inspection random check rules, wherein each quality inspection random check rule is a rule for performing quality inspection on cases extracted by different services;
extracting cases to be inspected from a plurality of different services according to a plurality of quality inspection sampling rules;
for the extracted cases to be subjected to quality inspection, calling corresponding automatic quality inspection processes according to the business types of the cases to automatically perform quality inspection on the cases to be subjected to quality inspection, and generating risk evaluation results of the cases;
displaying the risk evaluation result to a user, receiving confirmation operation of the user on the risk of each case, and generating a quality inspection result of each case;
summarizing the quality inspection results of all cases to generate a quality inspection data report;
and monitoring the quality inspection data report at regular time, and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions.
2. The intelligent risk quality inspection method of claim 1, wherein the receiving configuration information input by a user to generate a plurality of quality inspection snapshot rules comprises:
and displaying a visual rule configuration interface, and providing different quality inspection sampling inspection rule configuration templates according to different service types and logics so that a user can input configuration information.
3. The intelligent risk quality inspection method according to any one of claims 1-2,
the business comprises an electric connection business, a transaction link business and a product line business;
presetting a risk point and a high-frequency error point based on different services, and configuring a quality inspection sampling rule based on the risk point and the high-frequency error point;
the quality inspection sampling check rule comprises an identification rule, an extraction rule, a service quality inspection rule and a judgment rule.
4. The intelligent risk quality inspection method according to any one of claims 1-3, wherein the automatic quality inspection process comprises: the method comprises the steps of detecting a case falling into a warehouse, extracting a case to be subjected to quality inspection, identifying the case to be subjected to quality inspection so as to shunt the case to a corresponding automatic quality inspection module, performing automatic quality inspection processing, confirming risks, calculating automatic quality inspection results in a gathering mode, and feeding back the effect of automatic quality inspection to a control platform.
5. The intelligent risk quality inspection method according to any one of claims 1-4, wherein the automatically performing quality inspection on the case to be inspected and generating the risk assessment result of the case comprises:
and according to a preset risk judgment strategy, automatically carrying out risk point positioning and risk size estimation on the case to be subjected to quality inspection.
6. The intelligent risk quality inspection method according to any one of claims 1-5, wherein the summarizing the quality inspection results of each case and the generating a quality inspection data report comprises:
and performing statistical calculation on the quality inspection result, and storing the statistical result in a data report platform, wherein the data report platform can be called by a user to generate a visual report.
7. The intelligent risk quality inspection method according to any one of claims 1-6,
the regularly monitoring quality inspection data report forms and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions comprise:
calling a quality inspection data report at regular time, and detecting data in the called quality inspection data report according to a borne abnormal detection rule;
and when the data in the quality inspection data report is detected to be abnormal, generating quality inspection abnormal information.
8. An intelligent risk quality inspection system based on business audit is characterized by comprising:
the receiving module is used for receiving configuration information input by a user to generate a plurality of quality inspection random check rules, and each quality inspection random check rule is a rule for performing quality inspection on cases extracted by different services;
the extraction module is used for extracting cases to be subjected to quality inspection from a plurality of different services according to a plurality of quality inspection sampling rules;
the quality inspection module is used for calling a corresponding automatic quality inspection process to automatically perform quality inspection on the cases to be subjected to quality inspection according to the service types of the cases to generate risk evaluation results of the cases;
the generating module is used for displaying the risk evaluation result to a user, receiving confirmation operation of the user on the risk of each case and generating a quality inspection result of each case;
the collecting module is used for collecting the quality inspection results of all cases and generating a quality inspection data report;
and the monitoring module is used for monitoring the quality inspection data report at regular time and generating quality inspection abnormal information and quality inspection sampling rule updating suggestions.
9. An electronic device, wherein the electronic device comprises:
a processor; and the number of the first and second groups,
a memory storing computer-executable instructions that, when executed, cause the processor to perform the intelligent risk quality inspection method based on business auditing according to any one of claims 1-7.
10. A computer readable storage medium, wherein the computer readable storage medium stores one or more programs which, when executed by a processor, implement the intelligent risk quality inspection method based on business audit of any one of claims 1-7.
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| WO2023098623A1 (en) * | 2021-12-03 | 2023-06-08 | 北京字跳网络技术有限公司 | Information processing method and apparatus, and electronic device and storage medium |
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