CN112580983A - Universal intelligent risk solution method and equipment - Google Patents
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Abstract
The application relates to a universal intelligent risk solution method and equipment, in the application, risk data are identified based on a third-party big data governance platform which is butted in advance in a discovery stage, the risk data are cleaned and converted, business data including risk data portrait labels and risk scores are generated, the business data are imported from the third-party big data governance platform, and the stage can be used for carrying out risk data merging collision on a plurality of third-party big data governance platforms, so that the generation of data islands is reduced. Then, analyzing and classifying the service data in the local platform according to the portrait label and the risk score; according to the type of the service data, based on the corresponding service strategy, the service data is sent to a third-party service processing system which is in butt joint in advance and is in customized configuration, and due to the fact that the third-party service processing system is in customized configuration, the third-party service processing system can identify the service data, the service data can be processed more effectively through a professional third-party service processing system, and finally, service data processing feedback sent by the third-party service processing system is received. According to the method and the system, a service closed loop of four links of feedback is found, analyzed and solved, and cooperative disposal is performed by different third-party functional departments, so that risks are processed more efficiently.
Description
Technical Field
The application relates to the technical field of risk solution platforms, in particular to a universal intelligent risk solution method and equipment.
Background
At present, various business scenes related to risk early warning exist in the field of electronic government affairs, including key character risk early warning, site risk early warning, public opinion risk early warning and the like, previous risk early warning platforms are all developed in a chimney mode, each risk early warning platform is designed independently, data are in an isolated island mode, and risk early warning and disposal can be carried out only in the platform. When the system is crossed and the platform is crossed, because the risk solution or the managed service standards are different, the specifications are different, the technical architectures are different, and the local single-line butt joint or the repeated butt joint of a star-shaped structure is adopted.
Disclosure of Invention
In order to overcome the problems in the related art at least to a certain extent, the application provides a general intelligent risk solution method and equipment.
The scheme of the application is as follows:
according to a first aspect of embodiments of the present application, there is provided a general intelligent risk solution method, including:
identifying risk data based on a third-party big data governance platform which is butted in advance, cleaning and converting the risk data to generate business data comprising risk data portrait labels and risk scores, and importing the business data from the third-party big data governance platform;
analyzing and classifying the business data according to the portrait label and the risk score;
according to the type of the service data, based on a corresponding service strategy, the service data is sent to a third-party service processing system which is in butt joint in advance and is configured in a customized manner;
and receiving service data processing feedback sent by the third-party service handling system.
Preferably, in an implementation manner of the present application, the method further includes:
the method comprises the steps of docking a third-party service handling system, and carrying out customized configuration on the third-party service handling system so that the third-party service handling system can identify service data;
classifying the third-party service handling system according to the service class which can be handled by the third-party service handling system; and associating the class of the third-party service handling system with the class of the service data to generate the service strategy.
Preferably, in an implementation manner of the present application, the customizing the configuration of the third-party service handling system specifically includes:
and performing field-level customized configuration on the third-party service handling system through form configuration.
Preferably, in an implementation manner of the present application, the analyzing and classifying the business data according to the portrait label and the risk score specifically includes:
and performing conditional label classification on the service data according to the portrait label, wherein the classification at least comprises the following steps: people, places, and public sentiments;
and performing risk grade classification on the business data according to the risk scores, wherein the classification at least comprises the following steps: low risk, medium risk and high risk.
Preferably, in an implementation manner of the present application, the customizing the configuration of the third-party service handling system specifically further includes:
enabling the third-party service processing system to generate an intelligent early warning module according to customized configuration information and based on risk grade classification of the service data; and based on the condition label classification of the service data, screening specific characteristic labels according to the super engine to obtain complete label data, and generating a special early warning module.
Preferably, in an implementation manner of the present application, the method further includes:
and auditing the service data through the third-party service processing system, and adding the service data which is approved into a risk list.
Preferably, in an implementation manner of the present application, the receiving the service data processing feedback sent by the third-party service handling system specifically includes:
and receiving service data processing result feedback and processing process feedback sent by the third-party service processing system.
Preferably, in an implementation manner of the present application, the method further includes: and according to the processing result feedback, updating the risk score of the business data in the risk list, classifying the updated business data according to the updated risk score of the business data, and sending the updated business data to a third-party business processing system which is in butt joint in advance and is in customized configuration based on a corresponding business strategy according to the category of the updated business data.
Preferably, in an implementation manner of the present application, the customizing the configuration of the third-party service handling system specifically further includes:
standardizing an event handling state of the third party transaction handling system.
According to a second aspect of the embodiments of the present application, there is provided a general intelligent risk solution device, including:
a processor and a memory;
the processor and the memory are connected through a communication bus:
the processor is used for calling and executing the program stored in the memory;
the memory for storing a program for at least performing a universal intelligent risk solution method as claimed in any one of the preceding claims
The technical scheme provided by the application can comprise the following beneficial effects: the application provides a general intelligent risk solution method, general risk early warning process can all be divided into four standard links of finding analysis solution feedback, in this application, in the discovery stage based on the third party big data governance platform discernment risk data of butt joint in advance, wash the conversion to risk data, the business datum including risk data portrait label and risk score is generated, and import the business datum from third party big data governance platform, this stage can carry out risk data merge the collision to a plurality of third party big data governance platforms, reduce the production of data isolated island. Then, analyzing and classifying the service data in the local platform according to the portrait label and the risk score; according to the type of the service data, based on the corresponding service strategy, the service data is sent to a third-party service processing system which is in butt joint in advance and is in customized configuration, and due to the fact that the third-party service processing system is in customized configuration, the third-party service processing system can identify the service data, the service data can be processed more effectively through a professional third-party service processing system, and finally, service data processing feedback sent by the third-party service processing system is received. According to the method and the system, a service closed loop of four links of feedback is found, analyzed and solved, and cooperative disposal is performed by different third-party functional departments, so that risks are processed more efficiently.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the application.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
FIG. 1 is a schematic flow chart diagram illustrating a generalized intelligent risk solution method provided in an embodiment of the present application;
fig. 2 is a schematic structural diagram of a general intelligent risk solution device according to an embodiment of the present application.
Reference numerals: a processor-21; a memory-22.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
A general intelligent risk solution method, referring to fig. 1, comprising:
s11: identifying risk data based on a third-party big data governance platform which is butted in advance, cleaning and converting the risk data, generating business data comprising risk data portrait labels and risk scores, and importing the business data from the third-party big data governance platform;
in the prior art, risk early warning processes of all platforms can be divided into four standard links of discovery, analysis, solution and feedback.
The big data governance platform and the data analysis platform that support the third party in this application dock and import. In a data discovery link, risk data can be screened in a first layer by each big data governance platform and each data analysis platform (such as the Ariiyun, Tencent cloud and the like, including a self-developed hadoop platform), screening actions include data cleaning and conversion, data tagging and the like, risk scoring is carried out on the risk data, service data including risk data portrait tags and risk scoring are generated, and finally, the service data are adapted through a unified interface or imported in an offline mode.
In the step, data collision conversion is carried out by means of third-party big data management platforms such as Ali cloud and Tencent cloud, and the problem of data isolated islands is solved. Moreover, due to the collision conversion of the data, a large amount of invalid or repeated risks can be filtered in a discovery link, and the working efficiency of basic-level workers can be effectively improved.
In the step, the technology supports simultaneous access to a plurality of third-party big data management platforms and coexistence, and in general implementation, each area is grounded only by butting one third-party big data management platform.
S12: analyzing and classifying the business data according to the portrait label and the risk score;
in this step, the service data is analyzed and classified according to the portrait label and the risk score, specifically, the service data is subjected to conditional label classification according to the portrait label, and the classification at least includes: people, places, and public sentiments; and classifying the risk level of the business data according to the risk score, wherein the classification at least comprises the following steps: low risk, medium risk and high risk.
S13: according to the type of the service data, based on a corresponding service strategy, the service data is sent to a third-party service processing system which is in butt joint in advance and is configured in a customized manner;
before the method in the embodiment is implemented, the method needs to be in butt joint with a third-party big data management platform and a third-party service disposal system in advance, wherein when the third-party service disposal system is in butt joint, the third-party service disposal system needs to be subjected to customized configuration, so that the third-party service disposal system can identify service data;
classifying the third-party service handling system according to the service class which can be handled by the third-party service handling system; and associating the class of the third-party service handling system with the class of the service data to generate a service strategy.
The method for customizing the third-party service handling system specifically comprises the following steps:
and performing field-level customized configuration on the third-party service handling system through form configuration.
The customized configuration is mainly field control of the business data, and the field requirements of each third-party business processing system on the business data are different, so that the customized configuration at the field level can be realized through form configuration.
The third-party service disposal system is subjected to customized configuration, and the method further comprises the following steps: the event handling state of the third party transaction handling system is standardized. Specifically, the processing flows and flow states of the respective service systems are different, in this embodiment, three states of adding, processing and handling are set for standardizing the flow state of the problem, and handling opinions of specific operations are set as a piece of text information and are pieced together by the respective third-party service handling system technologies according to the data field conditions of the respective third-party service handling systems. For example, the event handling of the primary treatment is newly increased, the states of acceptance, reporting, rollback, submission, handling and the like are connected in a butt joint mode according to the technical interface of risk solution, the acceptance, reporting, rollback and submission, all the intermediate states belong to the states in the treatment, the examination and approval opinions are uniformly formatted into a certain person or a certain department, a certain operation is performed at a certain time, the operation content is a text description, and the examination and approval or the handling opinions correspond to the operation content.
In the step, customized configuration information is generated and sent to each third-party service handling system, so that the third-party service handling systems generate intelligent early warning modules according to the customized configuration information and based on risk grade classification of service data; and (4) classifying condition labels based on the service data, screening specific characteristic labels according to the super engine to obtain complete label data, and generating a special early warning module.
In this embodiment, in the analysis link, the risk data may be freely combined according to different high, medium and low risks, so as to form different high, medium and low risk lists.
In this step, the third-party service processing system checks the service data, and adds the checked service data into the risk list.
The audit can be machine audit or manual audit, or a combination of machine audit and manual audit. The auditing process is to avoid direct issuing of dirty data.
And adding the checked business data into a corresponding high, medium and low risk list formed in the analysis link according to the risk grade of the risk data in the business data.
And after the business data is added into the risk list, automatically triggering the corresponding business strategy. The third-party service disposal system can comprise a snow bright platform, an emergency command platform, a basic treatment platform and the like. The service policy may specifically include: for example, the business data disposal strategy of the high-risk virus-absorbing crowd is sent to the snow bright platform and the emergency command platform for processing, and the business data disposal strategy of the low-risk low-insurance personnel is sent to the primary management for regular visiting and patrolling.
The business strategy is a rule engine formed by a 'customized label + risk level + butt joint configurable third party business handling system' triple. The customized tag is a customized tag in this embodiment, so that each third-party service handling system only obtains tag data in the customization authority.
In this step, a solution link is realized through a third-party service handling system.
S14: and receiving service data processing feedback sent by the third-party service handling system.
In this step, a standard interface for data feedback is provided, after each third-party service processing system processes service data, part of information is fed back to the platform, for example, the risk level of key personnel is reduced, some fields are updated, and the like, and the interfaces for related data feedback are uniformly registered and authority-assignment by the platform.
Specifically, service data processing result feedback and processing process feedback sent by the third-party service handling system are received.
And updating the risk score of the service data in the risk list according to the processing result feedback, classifying the updated service data according to the risk score of the updated service data, and sending the updated service data to a third-party service processing system which is in butt joint in advance and is in customized configuration based on a corresponding service strategy according to the category of the updated service data.
The universal intelligent risk solution method in the embodiment combs a universal risk solution business process standard, and can cooperate with different third-party functional departments to perform cooperative disposition. And the technical interface is standardized, the system docking is changed from the past star-shaped structure into a central structure, and the docking can be carried out once without repeated docking. The risk data belongs to a construction mode of a data center station, and the data islanding phenomenon is effectively avoided.
A generic intelligent risk solution device, with reference to fig. 2, comprising:
a processor 21 and a memory 22;
the processor 21 is connected to the memory 22 by a communication bus:
the processor 21 is configured to call and execute a program stored in the memory 22;
a memory 22 for storing a program for performing at least one of the above embodiments of a general intelligent risk solution method.
A universal intelligent risk solution platform, comprising: the system comprises an algorithm model module, a relational graph module, a holographic file module, a rule engine module, a tag center module, a metadata management module, a form configuration module, a user management module, a data management module and a butt joint management module;
and the system is used for analyzing the service data and is respectively connected with a third-party big data governance platform and a third-party service disposal system.
The third-party big data governance platform mainly comprises: the system comprises an offline calculation module, a data exchange module, a task management module, a data code table module, a space management module and the like.
The third-party business disposal system mainly comprises: a risk data resolving plate and a data feedback plate;
the risk data resolving plate is divided into a risk early warning plate, a risk control plate and a risk situation plate;
the risk early warning plate includes: the system comprises an intelligent early warning module, a super search module and a risk library module;
the risk management and control plate includes: the system comprises a risk studying and judging module, a task issuing module, an inspection feedback module, an association analysis module, a responsibility implementation module, a result evaluation module, a special investigation module, a disposal tracking module and a supervision and evaluation module;
the risk situation panel includes: the system comprises a macro analysis module, a trend study and judgment module and a situation control module;
wherein the data feedback plate includes: the system comprises a task receiving module, a task feedback module, a task transaction module, a data feedback module, an interface management module and a data statistics module.
It is understood that the same or similar parts in the above embodiments may be mutually referred to, and the same or similar parts in other embodiments may be referred to for the content which is not described in detail in some embodiments.
It should be noted that, in the description of the present application, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present application, the meaning of "a plurality" means at least two unless otherwise specified.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present application includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present application.
It should be understood that portions of the present application may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.
It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.
In addition, functional units in the embodiments of the present application may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.
The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.
In the description herein, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Although embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application, and that variations, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present application.
Claims (10)
1. A universal intelligent risk solution method is characterized by comprising the following steps:
identifying risk data based on a third-party big data governance platform which is butted in advance, cleaning and converting the risk data to generate business data comprising risk data portrait labels and risk scores, and importing the business data from the third-party big data governance platform;
analyzing and classifying the business data according to the portrait label and the risk score;
according to the type of the service data, based on a corresponding service strategy, the service data is sent to a third-party service processing system which is in butt joint in advance and is configured in a customized manner;
and receiving service data processing feedback sent by the third-party service handling system.
2. The method of claim 1, further comprising:
the method comprises the steps of docking a third-party service handling system, and carrying out customized configuration on the third-party service handling system so that the third-party service handling system can identify service data;
classifying the third-party service handling system according to the service class which can be handled by the third-party service handling system; and associating the class of the third-party service handling system with the class of the service data to generate the service strategy.
3. The method according to claim 2, wherein the customizing the configuration of the third-party transaction system specifically comprises:
and performing field-level customized configuration on the third-party service handling system through form configuration.
4. The method of claim 3, wherein analyzing and classifying the business data according to the portrait tags and risk scores comprises:
and performing conditional label classification on the service data according to the portrait label, wherein the classification at least comprises the following steps: people, places, and public sentiments;
and performing risk grade classification on the business data according to the risk scores, wherein the classification at least comprises the following steps: low risk, medium risk and high risk.
5. The method according to claim 4, wherein the customizing the third-party transaction system further comprises:
enabling the third-party service processing system to generate an intelligent early warning module according to customized configuration information and based on risk grade classification of the service data; and based on the condition label classification of the service data, screening specific characteristic labels according to the super engine to obtain complete label data, and generating a special early warning module.
6. The method of claim 5, further comprising:
and auditing the service data through the third-party service processing system, and adding the service data which is approved into a risk list.
7. The method according to claim 6, wherein the receiving the traffic data processing feedback sent by the third-party traffic handling system specifically comprises:
and receiving service data processing result feedback and processing process feedback sent by the third-party service processing system.
8. The method of claim 7, further comprising: and according to the processing result feedback, updating the risk score of the business data in the risk list, classifying the updated business data according to the updated risk score of the business data, and sending the updated business data to a third-party business processing system which is in butt joint in advance and is in customized configuration based on a corresponding business strategy according to the category of the updated business data.
9. The method according to claim 3, wherein the customizing the third-party transaction system further comprises:
standardizing an event handling state of the third party transaction handling system.
10. A universal intelligent risk solution device, comprising:
a processor and a memory;
the processor and the memory are connected through a communication bus:
the processor is used for calling and executing the program stored in the memory;
the memory for storing a program for performing at least one of the methods of generic intelligent risk solution of any of claims 1-9.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101714273A (en) * | 2009-05-26 | 2010-05-26 | 北京银丰新融科技开发有限公司 | Rule engine-based method and system for monitoring exceptional service of bank |
| EP2801942A1 (en) * | 2013-05-09 | 2014-11-12 | Rockwell Automation Technologies, Inc. | Risk assessment for industrial systems using big data |
| CN107491885A (en) * | 2017-08-25 | 2017-12-19 | 上海找钢网信息科技股份有限公司 | A kind of air control platform and risk control management method for steel trade financial business |
| CN110991883A (en) * | 2019-12-03 | 2020-04-10 | 中国民用航空总局第二研究所 | Operation control system and method based on flight risk preposition |
| CN111709603A (en) * | 2020-05-15 | 2020-09-25 | 北京健康之家科技有限公司 | Service request processing method, device and system based on wind control |
-
2020
- 2020-12-22 CN CN202011524629.8A patent/CN112580983B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101714273A (en) * | 2009-05-26 | 2010-05-26 | 北京银丰新融科技开发有限公司 | Rule engine-based method and system for monitoring exceptional service of bank |
| EP2801942A1 (en) * | 2013-05-09 | 2014-11-12 | Rockwell Automation Technologies, Inc. | Risk assessment for industrial systems using big data |
| CN107491885A (en) * | 2017-08-25 | 2017-12-19 | 上海找钢网信息科技股份有限公司 | A kind of air control platform and risk control management method for steel trade financial business |
| CN110991883A (en) * | 2019-12-03 | 2020-04-10 | 中国民用航空总局第二研究所 | Operation control system and method based on flight risk preposition |
| CN111709603A (en) * | 2020-05-15 | 2020-09-25 | 北京健康之家科技有限公司 | Service request processing method, device and system based on wind control |
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