CN110222962A - Data configuration method and device for financial business risk control - Google Patents
Data configuration method and device for financial business risk control Download PDFInfo
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- CN110222962A CN110222962A CN201910441592.3A CN201910441592A CN110222962A CN 110222962 A CN110222962 A CN 110222962A CN 201910441592 A CN201910441592 A CN 201910441592A CN 110222962 A CN110222962 A CN 110222962A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
Abstract
This application discloses a kind of data configuration methods and device for financial business risk control.This method includes being configured to the analysis rule collection of analysis the first user data of processing according to risk control matching result；It is used to assess the scorecard of the first user credit according to financial business type configuration；According to the analysis rule collection and the scorecard, generation custom-configures result.The technical issues of can not being custom-configured present application addresses the data in risk control.Analysis rule, scorecard are custom-configured by the application realization, and facilitate business personnel's realization autonomy-oriented online and version management.
Description
Technical field
This application involves financial fields, in particular to a kind of data configuration side for financial business risk control
Method and device.
Background technique
Risk control refers to and adopts various measures in financial business field and method that event of reducing risks occurs various
Possibility, or reduce risks event occur when caused by loss.For example, the lending and borrowing business in financial business field.
Inventors have found that business personnel can not custom-configure rule, strategy or the scorecard polarity in risk control.
Aiming at the problem that data in risk control in the related technology can not custom-configure, not yet propose at present effective
Solution.
Summary of the invention
The main purpose of the application is to provide a kind of data configuration method and device for financial business risk control,
It can not be custom-configured with the data solved the problems, such as in risk control.
To achieve the goals above, it according to the one aspect of the application, provides a kind of for financial business risk control
Data configuration method.
The data configuration method for financial business risk control according to the application includes: to be matched to tie according to risk control
Fruit is configured to the analysis rule collection of analysis the first user data of processing；According to financial business type configuration for assessing first
The scorecard of user credit；According to the analysis rule collection and the scorecard, generation custom-configures result.
Further, it is also wrapped after generation custom-configures result according to the analysis rule collection and the scorecard
It includes: receiving the first user-association data；According to the first user-association data, according to the analysis rule and the scorecard
Generate the anticipation of financial business risk.
Further, according to risk control matching result, it is configured to the analysis rule of analysis the first user data of processing
Collection includes: to carry out rule match according to the first user data, obtains risk control matching result and saves the shape in operating process
State；According to analysis process demand, configuration rule simultaneously generates analysis rule collection.
It further, include: according to gold for assessing the scorecard of the first user credit according to financial business type configuration
The cluster data and derivative data for melting type of service the first user data of configuration obtain data processed result；According to data processing knot
Fruit carries out scorecard configuration according to financial business type, generates scorecard.
Further, according to the analysis rule collection and the scorecard, it includes: according to institute that generation, which custom-configures result,
State analysis rule collection create-rule engine；Modeling engine is generated according to the scorecard；Through financial business demand, in engine
Generation custom-configures result.
To achieve the goals above, it according to the another aspect of the application, provides a kind of for financial business risk control
Data configuration device.
Include: the first configuration module according to the data configuration device for financial business risk control of the application, is used for
According to risk control matching result, it is configured to the analysis rule collection of analysis the first user data of processing；Second configuration module is used
In the scorecard for being used to assess the first user credit according to financial business type configuration；Generation module, for according to the analysis
Rule set and the scorecard, generation custom-configure result.
Further, device further include: Data Analysis Services module, the data analysis module include: receiving unit, are used
In the first user-association data of reception；Generation unit is used for according to the first user-association data, according to the analysis rule
The anticipation of financial business risk is generated with the scorecard.
Further, first configuration module includes: first processing units, for being advised according to the first user data
It then matches, obtain risk control matching result and saves the state in operating process；The second processing unit, at according to analysis
Reason demand, configuration rule simultaneously generate analysis rule collection.
Further, second configuration module includes: third processing unit, for according to financial business type configuration the
The cluster data and derivative data of one user data obtain data processed result；Fourth processing unit, for according to data processing
As a result scorecard configuration is carried out according to financial business type, generates scorecard.
Further, the generation module includes: the first engine unit, for according to the analysis rule collection create-rule
Engine；Second engine unit, for generating modeling engine according to the scorecard；Customized unit, for passing through financial business
Demand generates in engine and custom-configures result.
It is used for the data configuration method and device of financial business risk control in the embodiment of the present application, using according to risk
Matching result is controlled, the mode of the analysis rule collection of analysis the first user data of processing is configured to, by according to financial business
Type configuration is used to assess the scorecard of the first user credit, has reached according to the analysis rule collection and the scorecard, raw
At the purpose of result is custom-configured, to realize the technical effect of risk control, and then solves the number in risk control
The technical issues of according to that can not custom-configure.
Detailed description of the invention
The attached drawing constituted part of this application is used to provide further understanding of the present application, so that the application's is other
Feature, objects and advantages become more apparent upon.The illustrative examples attached drawing and its explanation of the application is for explaining the application, not
Constitute the improper restriction to the application.In the accompanying drawings:
Fig. 1 is illustrated according to the data configuration method process for financial business risk control of the application first embodiment
Figure；
Fig. 2 is illustrated according to the data configuration method process for financial business risk control of the application second embodiment
Figure；
Fig. 3 is illustrated according to the data configuration method process for financial business risk control of the application 3rd embodiment
Figure；
Fig. 4 is illustrated according to the data configuration method process for financial business risk control of the application fourth embodiment
Figure；
Fig. 5 is illustrated according to the data configuration method process for financial business risk control of the 5th embodiment of the application
Figure；
Fig. 6 is the data configuration device structural representation for financial business risk control according to the application first embodiment
Figure；
Fig. 7 is the data configuration device structural representation for financial business risk control according to the application second embodiment
Figure；
Fig. 8 is the data configuration device structural representation for financial business risk control according to the application 3rd embodiment
Figure；
Fig. 9 is the data configuration device structural representation for financial business risk control according to the application fourth embodiment
Figure；
Figure 10 is shown according to the data configuration device structure for financial business risk control of the 5th embodiment of the application
It is intended to.
Specific embodiment
In order to make those skilled in the art more fully understand application scheme, below in conjunction in the embodiment of the present application
Attached drawing, the technical scheme in the embodiment of the application is clearly and completely described, it is clear that described embodiment is only
The embodiment of the application a part, instead of all the embodiments.Based on the embodiment in the application, ordinary skill people
Member's every other embodiment obtained without making creative work, all should belong to the model of the application protection
It encloses.
It should be noted that the description and claims of this application and term " first " in above-mentioned attached drawing, "
Two " etc. be to be used to distinguish similar objects, without being used to describe a particular order or precedence order.It should be understood that using in this way
Data be interchangeable under appropriate circumstances, so as to embodiments herein described herein.In addition, term " includes " and " tool
Have " and their any deformation, it is intended that cover it is non-exclusive include, for example, containing a series of steps or units
Process, method, system, product or equipment those of are not necessarily limited to be clearly listed step or unit, but may include without clear
Other step or units listing to Chu or intrinsic for these process, methods, product or equipment.
In this application, term " on ", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outside",
" in ", "vertical", "horizontal", " transverse direction ", the orientation or positional relationship of the instructions such as " longitudinal direction " be orientation based on the figure or
Positional relationship.These terms are not intended to limit indicated dress primarily to better describe the application and embodiment
Set, element or component must have particular orientation, or constructed and operated with particular orientation.
Also, above-mentioned part term is other than it can be used to indicate that orientation or positional relationship, it is also possible to for indicating it
His meaning, such as term " on " also are likely used for indicating certain relations of dependence or connection relationship in some cases.For ability
For the those of ordinary skill of domain, the concrete meaning of these terms in this application can be understood as the case may be.
In addition, term " installation ", " setting ", " being equipped with ", " connection ", " connected ", " socket " shall be understood in a broad sense.For example,
It may be a fixed connection, be detachably connected or monolithic construction；It can be mechanical connection, or electrical connection；It can be direct phase
It even, or indirectly connected through an intermediary, or is two connections internal between device, element or component.
For those of ordinary skills, the concrete meaning of above-mentioned term in this application can be understood as the case may be.
It should be noted that in the absence of conflict, the features in the embodiments and the embodiments of the present application can phase
Mutually combination.The application is described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.
As shown in Figure 1, this method includes the following steps, namely S102 to step S106:
Step S102 is configured to the analysis rule of analysis the first user data of processing according to risk control matching result
Collection；
According to the available initial risk control rule etc. of the risk control matching result, but these rules are not
Be it is fixed, matching result can be adjusted according to the related performance of the first user or historical record.Acquiring use
After user data can Auto-matching risk control rule, obtain risk control matching result.The risk control matching result can be with
Then data collecting model is obtained drift by offline mode batch processing.For example, by using tools such as spark, sql, hive
After being pre-processed in database MongoDB, the service database mysql stored based on distributed document and select feature
Create-rule afterwards, and rule is acquired into rule base.
Allocation Analysis rule set, the analysis rule collection is for analyzing the first user data of processing.It can pass through and configure
Analysis rule collection analyzes user data.
It should be noted that analysis rule collection according to risk control matching result and user data update feedback result into
Row custom-configures.The mode of configuration is to provide the regular configuration approach of analysis rule collection.
Step S104 is used to assess the scorecard of the first user credit according to financial business type configuration；
Go out scorecard according to specific financial business type configuration, user credit can be assessed by the scorecard.
Specifically, learnt by learning databases such as scikit-learn machine learning library, spark-mllib machine learning libraries
To scorecard model, for configuring the scorecard of the first user credit of assessment.
It should be noted that those skilled in the art can carry out flexibly scorecard according to the concrete type of financial business
Configuration, in embodiments herein and without specifically limiting.
Step S106, according to the analysis rule collection and the scorecard, generation custom-configures result.
Customized configuration knot can be generated in the analysis rule collection and the scorecard according to obtained in above-mentioned steps
Fruit, i.e. configuration result can be adjusted according to financial business type or risk control matching result, every once to be adjusted
Or it updates and the configuration of front and back rule or scorecard can be compared.The effect of comparison Different Rule is convenient in the management of multi version
Analysis facilitates business personnel's realization autonomy-oriented online and version management to substitute traditional model publication software.
It can be seen from the above description that the application realizes following technical effect:
In the embodiment of the present application, using according to risk control matching result, it is configured to analysis the first number of users of processing
According to the mode of analysis rule collection reached by being used to assess the scorecard of the first user credit according to financial business type configuration
It has arrived according to the analysis rule collection and the scorecard, the purpose for custom-configuring result has been generated, to realize risk control
The technical effect of system, and then solve the technical issues of data in risk control can not custom-configure
According to the embodiment of the present application, as preferred in the present embodiment, as shown in Fig. 2, according to the analysis rule collection and
The scorecard, generation custom-configure after result, further includes:
Step S202 receives the first user-association data；
Step S204 generates gold according to the analysis rule and the scorecard according to the first user-association data
Melt business risk anticipation.
Specifically, first user's financial business order information and signing information are received, when the first user initiates loan application,
It obtains the essential information that user provides and parses extraction.In addition, by obtain signing information, for analyze user percent of pass,
The indexs such as the equal amount of money of part.Order information based on user crawls use according to the SDK interface of application program in insertion user hand generator terminal
The information such as family collage-credit data, carrier data call third party's data according to configuration is automatic, and carry out that feature is derivative, data are whole
It closes, the high dimensional data that will summarize, using high dimensional data as the first user-association data, and according to the analysis rule and institute's commentary
Point card generates the anticipation of financial business risk, the suggestion of different stages such as is given by, refuses, alarming.
Using order as trigger point, tripartite's data are called automatically according to configuration and carry out feature derivative and data encapsulation, in conjunction with
Rule packet, score value section, model carry out screening in all directions to user, prejudge risk and provide suggestion.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in figure 3, according to risk control matching result,
Be configured to analysis processing the first user data analysis rule collection include:
Step S302 carries out rule match according to the first user data, obtains risk control matching result and saves operation
State in the process；
Step S304, according to analysis process demand, configuration rule simultaneously generates analysis rule collection.
Specifically, preset rules matching algorithm is used in the progress rule match according to the first user data, passed through
The state in operating process is saved, avoids largely computing repeatedly, greatly improves the matching efficiency of rule.According to analysis
Process demand, configuration rule simultaneously generate analysis rule collection.
It should be noted that the analysis process demand can pass through acquiring in offline batch processing large database concept
Rule obtains.
Preferably, using the RETE algorithm based on multi-mode matching.The algorithm is calculated before one kind to regular Rapid matching
Method, algorithm avoid and largely compute repeatedly, greatly improve the matching effect of rule by saving the state in operating process
Rate.And the node sharing policy in algorithm, solve matching problem when having a large amount of model identicals between Different Rule, thus
Improve the matching efficiency of algorithm.RETE algorithm promotes the rule matching efficiency of platform to Millisecond.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in figure 4, according to financial business type configuration
Scorecard for assessing the first user credit includes:
Step S402 obtains data according to the cluster data of the first user data of financial business type configuration and derivative data
Processing result；
Step S404 carries out scorecard configuration according to financial business type according to data processed result, generates scorecard.
Specifically, relevant information is gone out according to the financial business type configuration.It may include: application message configuration, data
Source configuration, the derivative configuration of feature, rule set configuration, model configuration.
Through the above steps, it is arranged using user-friendly interface, consequently facilitating business personnel is reached by interface configurations
From data access, the data processed result of derivative, the multi-faceted analysis of feature.
Preferably, data processed result includes the inside after coming into force to the historical record of the first user data or financial business
The processing of data.It can also include: that whether blacklist, operator, the first user data are belonged to the first user data
Consumption data, the social security of the first user data, the bank authentication of the first user data, the first user data debt-credit etc. it is outer
The processing of portion's data.
It may include anti-fraud model score when it should be noted that carrying out scorecard configuration according to financial business type
The configuration of card, credit evaluation scorecard and amount credit scorecard etc., those skilled in the art can be according to actual use feelings
Condition is selected or is adjusted.In addition, learnt based on intelligent rules, performance and High Dimensional Data Set after coming into force in conjunction with financial business, from
It is dynamic to generate effective rule.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in figure 5, according to the analysis rule collection and
The scorecard, generation custom-configure result and include:
Step S502, according to the analysis rule collection create-rule engine；
Step S504 generates modeling engine according to the scorecard；
Step S506 is generated in engine by financial business demand and is custom-configured result.
Specifically, it the regulation engine and is shown at the modeling engine based on the rule of more relationship many conditions and efficient
Matching.By financial business demand, generates and custom-configured as a result, configurableization data access, automated data in engine
Pretreatment, makes business personnel jump out cumbersome data, focuses more on model and regular and builds.
It should be noted that step shown in the flowchart of the accompanying drawings can be in such as a group of computer-executable instructions
It is executed in computer system, although also, logical order is shown in flow charts, and it in some cases, can be with not
The sequence being same as herein executes shown or described step.
According to the embodiment of the present application, additionally provide it is a kind of for implement the above method for financial business risk control
Data configuration device, as shown in fig. 6, the device includes: the first configuration module 10, for matching according to risk control matching result
Set the analysis rule collection for analyzing the first user data of processing；Second configuration module 20, for being matched according to financial business type
Set the scorecard for assessing the first user credit；Generation module 30 is used for according to the analysis rule collection and the scorecard,
Generation custom-configures result.
It is available initial according to the risk control matching result in first configuration module 10 of the embodiment of the present application
Risk control rule etc., but these rules are not fixation, it can be according to the related performance of the first user or historical record
Matching result is adjusted.After acquiring user data can Auto-matching risk control rule, obtain risk control
With result.The risk control matching result can then data collecting model be obtained by offline mode batch processing with drift.Than
Such as, by using tools such as spark, sql, hive in database MongoDB, the service database stored based on distributed document
After being pre-processed in mysql and create-rule after feature is selected, and rule is acquired into rule base.
Allocation Analysis rule set, the analysis rule collection is for analyzing the first user data of processing.It can pass through and configure
Analysis rule collection analyzes user data.
It should be noted that analysis rule collection according to risk control matching result and user data update feedback result into
Row custom-configures.The mode of configuration is to provide the regular configuration approach of analysis rule collection.
Scorecard is gone out according to specific financial business type configuration in second configuration module 20 of the embodiment of the present application, is passed through
The scorecard can assess user credit.
Specifically, learnt by learning databases such as scikit-learn machine learning library, spark-mllib machine learning libraries
To scorecard model, for configuring the scorecard of the first user credit of assessment.
It should be noted that those skilled in the art can carry out flexibly scorecard according to the concrete type of financial business
Configuration, in embodiments herein and without specifically limiting.
The analysis rule collection and institute's commentary according to obtained in above-mentioned steps in the generation module 30 of the embodiment of the present application
Divide card, customized configuration result can be generated, is i.e. configuration result can be matched according to financial business type or risk control
As a result it is adjusted, it is every once to be adjusted or updated and the configuration of front and back rule or scorecard compared.Multi version
Management facilitate business personnel to realize to substitute traditional model publication software convenient for the effect analysis of comparison Different Rule
Autonomy-oriented is online and version management.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in fig. 7, device further include: at data analysis
Module 40 is managed, the data analysis module 40 includes: receiving unit 401, for receiving the first user-association data；Generation unit
402, for generating financial business risk according to the analysis rule and the scorecard according to the first user-association data
Anticipation.
In the Data Analysis Services module 40 of the embodiment of the present application specifically, first user's financial business order information is received
And signing information, when the first user initiates loan application, the essential information that acquisition user provides simultaneously parses extraction.In addition, passing through
Obtain signing information, the indexs such as equal amount of money of percent of pass, part for analyzing user.Order information based on user, according to insertion
The SDK interface of application program crawls the information such as user's collage-credit data, carrier data in user hand generator terminal, adjusts according to configuration is automatic
With third party's data, and carry out that feature is derivative, Data Integration, the high dimensional data that will summarize, using high dimensional data as the first user
Associated data, and the anticipation of financial business risk is generated according to the analysis rule and the scorecard, it is given by, refuses, reports
The suggestion of the different stages such as alert.
Using order as trigger point, tripartite's data are called automatically according to configuration and carry out feature derivative and data encapsulation, in conjunction with
Rule packet, score value section, model carry out screening in all directions to user, prejudge risk and provide suggestion.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in figure 8, first configuration module 10 is wrapped
It includes: first processing units 101, for carrying out rule match according to the first user data, obtaining risk control matching result and protecting
Deposit the state in operating process；The second processing unit 102, for according to analysis process demand, configuration rule simultaneously to generate analysis rule
Then collect.
In the embodiment of the present application specifically, preset rules are used in the progress rule match according to the first user data
Matching algorithm avoids largely computing repeatedly, greatly improves the matching effect of rule by saving the state in operating process
Rate.According to analysis process demand, configuration rule simultaneously generates analysis rule collection.
It should be noted that the analysis process demand can pass through acquiring in offline batch processing large database concept
Rule obtains.
Preferably, using the RETE algorithm based on multi-mode matching.The algorithm is calculated before one kind to regular Rapid matching
Method, algorithm avoid and largely compute repeatedly, greatly improve the matching effect of rule by saving the state in operating process
Rate.And the node sharing policy in algorithm, solve matching problem when having a large amount of model identicals between Different Rule, thus
Improve the matching efficiency of algorithm.RETE algorithm promotes the rule matching efficiency of platform to Millisecond.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in figure 9, second configuration module 20 is wrapped
It includes: third processing unit 201, for being obtained according to the cluster data and derivative data of the first user data of financial business type configuration
To data processed result；Fourth processing unit 202, for carrying out scorecard according to financial business type according to data processed result
Configuration generates scorecard.
In the embodiment of the present application specifically, specifically, relevant information is gone out according to the financial business type configuration.It can wrap
It includes: application message configuration, data source configuration, the derivative configuration of feature, rule set configuration, model configuration.
Through the above steps, it is arranged using user-friendly interface, consequently facilitating business personnel is reached by interface configurations
From data access, the data processed result of derivative, the multi-faceted analysis of feature.
Preferably, data processed result includes the inside after coming into force to the historical record of the first user data or financial business
The processing of data.It can also include: that whether blacklist, operator, the first user data are belonged to the first user data
Consumption data, the social security of the first user data, the bank authentication of the first user data, the first user data debt-credit etc. it is outer
The processing of portion's data.
It may include anti-fraud model score when it should be noted that carrying out scorecard configuration according to financial business type
The configuration of card, credit evaluation scorecard and amount credit scorecard etc., those skilled in the art can be according to actual use feelings
Condition is selected or is adjusted.In addition, learnt based on intelligent rules, performance and High Dimensional Data Set after coming into force in conjunction with financial business, from
It is dynamic to generate effective rule.
According to the embodiment of the present application, as preferred in the present embodiment, as shown in Figure 10, the generation module 30 includes:
First engine unit 301, for according to the analysis rule collection create-rule engine；Second engine unit 302, for according to institute
It states scorecard and generates modeling engine；Customized unit 303, for generating customized match in engine by financial business demand
Set result.
In the embodiment of the present application specifically, specifically, the regulation engine and at the modeling engine be based on more relationships it is more
The rule of condition is shown and efficient matching.By financial business demand, generates and custom-configured as a result, configurable in engine
Change data access, automated data pretreatment, business personnel is made to jump out cumbersome data, focuses more on model and regular and take
It builds.
Obviously, those skilled in the art should be understood that each module of above-mentioned the application or each step can be with general
Computing device realize that they can be concentrated on a single computing device, or be distributed in multiple computing devices and formed
Network on, optionally, they can be realized with the program code that computing device can perform, it is thus possible to which they are stored
Be performed by computing device in the storage device, perhaps they are fabricated to each integrated circuit modules or by they
In multiple modules or step be fabricated to single integrated circuit module to realize.In this way, the application be not limited to it is any specific
Hardware and software combines.
The foregoing is merely preferred embodiment of the present application, are not intended to limit this application, for the skill of this field
For art personnel, various changes and changes are possible in this application.Within the spirit and principles of this application, made any to repair
Change, equivalent replacement, improvement etc., should be included within the scope of protection of this application.
Claims (10)
1. a kind of data configuration method for financial business risk control characterized by comprising
According to risk control matching result, it is configured to the analysis rule collection of analysis the first user data of processing；
It is used to assess the scorecard of the first user credit according to financial business type configuration；
According to the analysis rule collection and the scorecard, generation custom-configures result.
2. data configuration method according to claim 1, which is characterized in that according to the analysis rule collection and the scoring
Card, generation custom-configure after result, further includes:
Receive the first user-association data；
According to the first user-association data, it is pre- that financial business risk is generated according to the analysis rule and the scorecard
Sentence.
3. data configuration method according to claim 1, which is characterized in that according to risk control matching result, configuration is used
Include: in the analysis rule collection of analysis the first user data of processing
Rule match is carried out according to the first user data, obtain risk control matching result and saves the state in operating process；
According to analysis process demand, configuration rule simultaneously generates analysis rule collection.
4. data configuration method according to claim 1, which is characterized in that according to financial business type configuration for assessing
The scorecard of first user credit includes:
Data processed result is obtained according to the cluster data of the first user data of financial business type configuration and derivative data；
Scorecard configuration is carried out according to financial business type according to data processed result, generates scorecard.
5. data configuration method according to claim 1, which is characterized in that according to the analysis rule collection and the scoring
Card, generation custom-configure result and include:
According to the analysis rule collection create-rule engine；
Modeling engine is generated according to the scorecard；
By financial business demand, is generated in engine and custom-configure result.
6. a kind of data configuration device for financial business risk control characterized by comprising
First configuration module, for being configured to the analysis of analysis the first user data of processing according to risk control matching result
Rule set；
Second configuration module, for being used to assess the scorecard of the first user credit according to financial business type configuration；
Generation module, for according to the analysis rule collection and the scorecard, generation to custom-configure result.
7. data configuration device according to claim 6, which is characterized in that further include: Data Analysis Services module, it is described
Data analysis module includes:
Receiving unit, for receiving the first user-association data；
Generation unit, for generating gold according to the analysis rule and the scorecard according to the first user-association data
Melt business risk anticipation.
8. data configuration device according to claim 6, which is characterized in that first configuration module includes:
First processing units, for carrying out rule match according to the first user data, obtaining risk control matching result and saving
State in operating process；
The second processing unit, for according to analysis process demand, configuration rule simultaneously to generate analysis rule collection.
9. data configuration device according to claim 6, which is characterized in that second configuration module includes:
Third processing unit, for being obtained according to the cluster data and derivative data of the first user data of financial business type configuration
Data processed result；
Fourth processing unit generates scoring for carrying out scorecard configuration according to financial business type according to data processed result
Card.
10. data configuration device according to claim 6, which is characterized in that the generation module includes:
First engine unit, for according to the analysis rule collection create-rule engine；
Second engine unit, for generating modeling engine according to the scorecard；
Customized unit, for being generated in engine and custom-configuring result by financial business demand.
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| CN201910441592.3A CN110222962A (en) | 2019-05-24 | 2019-05-24 | Data configuration method and device for financial business risk control |
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| CN201910441592.3A CN110222962A (en) | 2019-05-24 | 2019-05-24 | Data configuration method and device for financial business risk control |
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Application publication date: 20190910 |