CN108364224A - Credit risk joint control method, apparatus, equipment and readable storage medium storing program for executing - Google Patents
Credit risk joint control method, apparatus, equipment and readable storage medium storing program for executing Download PDFInfo
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- CN108364224A CN108364224A CN201810033721.0A CN201810033721A CN108364224A CN 108364224 A CN108364224 A CN 108364224A CN 201810033721 A CN201810033721 A CN 201810033721A CN 108364224 A CN108364224 A CN 108364224A
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- 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
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Abstract
The invention discloses a kind of credit risk joint control method, apparatus, equipment and readable storage medium storing program for executing, the credit risk joint control method includes：When detecting credit examination ＆ approval instruction on the node device in all-in-one machine, obtains the credit examination ＆ approval and instruct corresponding application information；Identify whether the corresponding credit applications behavior of the application information is fraud；When the corresponding credit applications behavior of the application information is fraud, the first blacklist file is generated based on the application information；By the first blacklist file broadcast to the associated other node devices of all-in-one machine, so that other node devices update its local blacklist file.The present invention solves the technical issues of all types of credit equipment can be only in autonomous device state, be unable to real-time synchronization application risk information, that is, can not achieve strange land or across style credit risk joint control in the prior art.
Description
Technical field
The present invention relates to field of computer technology more particularly to a kind of credit risk joint control method, apparatus, equipment and readable
Storage medium.
Background technology
Currently, due to the development of financial circles, credit applications are also increasingly common, wherein how to evade the credits wind such as cheat loan
Become the problem for that need solve by inches, in the prior art, all types of credit equipment combination mobile device hardware informations carry out synthesis and comment
It surveys, to evade credit risk, however, all types of credit equipment of the above method can be only in autonomous device state, it cannot be same in real time
Step application risk information, that is, can not achieve strange land or across style credit risk joint control.
Invention content
The main purpose of the present invention is to provide a kind of credit risk joint control method, apparatus, equipment and readable storage medium storing program for executing,
It aims to solve the problem that all types of credit equipment can be only in autonomous device state in the prior art, is unable to real-time synchronization application risk letter
The technical issues of ceasing, that is, can not achieve strange land or across style credit risk joint control.
To achieve the above object, the present invention provides a kind of credit risk joint control method, the credit risk joint control method packet
It includes：
When detecting credit examination ＆ approval instruction on the node device in all-in-one machine, it is corresponding to obtain the credit examination ＆ approval instruction
Application information；
Identify whether the corresponding credit applications behavior of the application information is fraud；
When the corresponding credit applications behavior of the application information is fraud, first is generated based on the application information
Blacklist file；
By the first blacklist file broadcast to the associated other node devices of all-in-one machine, more for other node devices
Its new local blacklist file.
Optionally, whether the corresponding credit applications behavior of the identification application information is that fraud step includes：
Based on the application information, the credit number of corresponding credit applications people and the application time of each credit are inquired；
Application time based on the credit number and each credit, the credit applications for generating the credit applications people are special
Levy curve；
Based on the credit applications indicatrix, judge the credit applications people with the presence or absence of concentration credit applications behavior；
When the credit applications people, which exists, concentrates credit applications behavior, the corresponding credit applications of the application information are identified
Behavior is fraud.
Optionally, whether the corresponding credit applications behavior of the identification application information is that fraud step is also wrapped
It includes：
Based on the application information, the identity information of the credit applications people is obtained；
The reference information for calling credit applications people in credit investigation system compares the identity information and the base in reference information
Quasi- identity；
When the identity information and reference identity are inconsistent, identify that the corresponding credit applications behavior of the application information is
Fraud.
Optionally, described will be before the first blacklist file broadcast to the associated other node device steps of all-in-one machine
Including：
Each first blacklist file that each node device generates is obtained at interval of preset time period；
Each first blacklist file data described in cleaning treatment, to generate the second blacklist file；
The second blacklist file is sent to each node device, so that each node device loads.
Optionally, each first blacklist file data described in the cleaning treatment, to generate the second blacklist file step
Suddenly include：
The type that each node device of all-in-one machine corresponds to credit is obtained, obtains the corresponding air control power of the style credit respectively
Weight information；
The reputation score of each credit applications people in the first blacklist file is obtained, the air control weight information is based on, it is right
The reputation score of the credit applications people in first blacklist file carries out deduction processing, to obtain the second blacklist file.
Optionally, the corresponding air control weight information step of the style credit that obtains respectively includes：
Obtain audit stringency of the style credit corresponding node equipment to application information；
The corresponding air control weight information of the style credit is obtained respectively based on the audit stringency.
Optionally, described to obtain audit stringency step packet of the style credit corresponding node equipment to application information
It includes：
It obtains the style credit corresponding node equipment and number is audited to target audit data volume, the target of corresponding application information
According to number of types and target audit time；
Place is normalized to target audit data volume, target audit data type number and target audit time
Reason obtains each normalization data with correspondence；
Obtain the accounting information of audit data volume, audit data type number and audit time in auditing stringency, base
In the accounting information and each normalization data, audit of the style credit corresponding node equipment to application information is calculated
Stringency.
In addition, to achieve the above object, the present invention also provides a kind of credit risk joint control equipment, the credit risk joint control
Equipment includes：Memory, processor, communication bus and the credit risk joint control program being stored on the memory,
The communication bus is for realizing the communication connection between processor and memory；
The processor is for executing the credit risk joint control program, to realize following steps：
When detecting credit examination ＆ approval instruction on the node device in all-in-one machine, it is corresponding to obtain the credit examination ＆ approval instruction
Application information；
Identify whether the corresponding credit applications behavior of the application information is fraud；
When the corresponding credit applications behavior of the application information is fraud, first is generated based on the application information
Blacklist file；
By the first blacklist file broadcast to the associated other node devices of all-in-one machine, more for other node devices
Its new local blacklist file.
Optionally, whether the corresponding credit applications behavior of the identification application information is that fraud step includes：
Based on the application information, the credit number of corresponding credit applications people and the application time of each credit are inquired；
Application time based on the credit number and each credit, the credit applications for generating the credit applications people are special
Levy curve；
Based on the credit applications indicatrix, judge the credit applications people with the presence or absence of concentration credit applications behavior；
When the credit applications people, which exists, concentrates credit applications behavior, the corresponding credit applications of the application information are identified
Behavior is fraud.
Optionally, whether the corresponding credit applications behavior of the identification application information is that fraud step is also wrapped
It includes：
Based on the application information, the identity information of the credit applications people is obtained；
The reference information for calling credit applications people in credit investigation system compares the identity information and the base in reference information
Quasi- identity；
When the identity information and reference identity are inconsistent, identify that the corresponding credit applications behavior of the application information is
Fraud.
Optionally, described will be before the first blacklist file broadcast to the associated other node device steps of all-in-one machine
Including：
Each first blacklist file that each node device generates is obtained at interval of preset time period；
Each first blacklist file data described in cleaning treatment, to generate the second blacklist file；
The second blacklist file is sent to each node device, so that each node device loads.
Optionally, each first blacklist file data described in the cleaning treatment, to generate the second blacklist file step
Suddenly include：
The type that each node device of all-in-one machine corresponds to credit is obtained, obtains the corresponding air control power of the style credit respectively
Weight information；
The reputation score of each credit applications people in the first blacklist file is obtained, the air control weight information is based on, it is right
The reputation score of the credit applications people in first blacklist file carries out deduction processing, to obtain the second blacklist file.
Optionally, the corresponding air control weight information step of the style credit that obtains respectively includes：
Obtain audit stringency of the style credit corresponding node equipment to application information；
The corresponding air control weight information of the style credit is obtained respectively based on the audit stringency.
Optionally, described to obtain audit stringency step packet of the style credit corresponding node equipment to application information
It includes：
It obtains the style credit corresponding node equipment and number is audited to target audit data volume, the target of corresponding application information
According to number of types and target audit time；
Place is normalized to target audit data volume, target audit data type number and target audit time
Reason obtains each normalization data with correspondence；
Obtain the accounting information of audit data volume, audit data type number and audit time in auditing stringency, base
In the accounting information and each normalization data, audit of the style credit corresponding node equipment to application information is calculated
Stringency.
In addition, to achieve the above object, the present invention also provides a kind of readable storage medium storing program for executing, the readable storage medium storing program for executing storage
There are one either more than one program the one or more programs to be held by one or more than one processor
Row for：
When detecting credit examination ＆ approval instruction on the node device in all-in-one machine, it is corresponding to obtain the credit examination ＆ approval instruction
Application information；
Identify whether the corresponding credit applications behavior of the application information is fraud；
When the corresponding credit applications behavior of the application information is fraud, first is generated based on the application information
Blacklist file；
By the first blacklist file broadcast to the associated other node devices of all-in-one machine, more for other node devices
Its new local blacklist file.
The present invention is by when detecting credit examination ＆ approval instruction on the node device in all-in-one machine, obtaining the credit examination ＆ approval
Instruct corresponding application information；Identify whether the corresponding credit applications behavior of the application information is fraud；When the Shen
Please information corresponding credit applications behavior when being fraud, the first blacklist file is generated based on the application information；By institute
The first blacklist file broadcast is stated to the associated other node devices of all-in-one machine, so that other node devices update its Local Black name
Monofile.If first can be generated when a node device detects the credit applications people with fraud in the application
Simultaneously real-time broadcast is to other node devices of all-in-one machine for blacklist file, i.e., each node device of all-in-one machine cooperates in this application
The shared blacklist file of interaction, it is thus possible to realize the different node device real-time synchronization application risk information of all-in-one machine, effectively
It avoids the concentration in the short time from cheating loan, realizes strange land or across style credit risk joint control.
Description of the drawings
Fig. 1 is the flow diagram of credit risk joint control method first embodiment of the present invention；
Fig. 2 is the flow diagram of credit risk joint control method second embodiment of the present invention；
Fig. 3 is the device structure schematic diagram for the hardware running environment that present invention method is related to.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific implementation mode
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present invention provides a kind of credit risk joint control method, the credit risk joint control method is applied to all-in-one machine, at this
In the first embodiment of invention credit risk joint control method, referring to Fig.1, the credit risk joint control method includes：
When detecting credit examination ＆ approval instruction on the node device in all-in-one machine, it is corresponding to obtain the credit examination ＆ approval instruction
Application information；Identify whether the corresponding credit applications behavior of the application information is fraud；When the application information corresponds to
Credit applications behavior when being fraud, the first blacklist file is generated based on the application information；By the described first black name
Monofile is broadcasted to the associated other node devices of all-in-one machine, so that other node devices update its local blacklist file.Tool
Steps are as follows for body：
Step S10 obtains the credit examination ＆ approval and refers to when detecting credit examination ＆ approval instruction on the node device in all-in-one machine
Enable corresponding application information；
It should be noted that credit risk joint control method is applied to credit all-in-one machine, specifically, credit all-in-one machine includes each
A node device, each node device can be Agricultural Bank of China's credit ATM machine, Industrial and Commercial Bank of China's credit ATM machine, safety
Bank credit ATM machine etc..
It when credit applications people needs to carry out credit, can be operated on credit all-in-one machine node device, trigger credit
Request.Credit all-in-one machine node device is asked according to the credit received, will inquire background server, obtains credit product letter
Breath, and optional credit product is shown according to product information, so that target applicant selects.It is touched receiving applicant
When the product selection instruction of hair, credit all-in-one machine node device will determine the target of credit applications people according to the product selection instruction
Product.At this point, credit all-in-one machine node device will obtain the credit procedure information of the target product in the server, and according to
The credit procedure information shows corresponding credit flow interface；Applicant can input according to the prompt in credit flow interface
Or other operations, with the offer for completing data and other credit formalities.Wherein, ring is audited when credit flow enters credit information
It when section, needs to audit credit information, to avoid the event of cheating loan, to reduce the risk in credit process.
When credit flow, which enters credit information, audits link, it is based on credit applications people point on all-in-one machine node device
The credit approval process of triggering is hit or touched, credit examination ＆ approval instruction is generated, the credit examination ＆ approval are obtained based on credit examination ＆ approval
Corresponding application information is instructed, specifically, this application information further includes each in addition to the application materials uploaded including credit applications people
The application operation information of credit applications people in the application process of a node device acquisition, wherein application materials include credit applications
Application identity card, application driver's license, application property ownership certificate, bank's flowing water, reference information, the history application of applicant's demand for credit
Information and other personal information etc., time of application operation information when including credit applications people application between done different operation
Interval, and such as click of specific different operation, touch etc..
It should be noted that the history application information of applicant's demand for credit is not only including credit applications people in local node
The history application information of credit in equipment further includes credit histories Shen of the credit applications people on the other node devices of all-in-one machine
Please information, illustrate to specific embodiment, if this credit applications people carries out demand for credit on A node devices, need to obtain
The demand for credit history application information for taking credit applications people on local A node devices also needs to obtain on all-in-one machine A node devices
The demand for credit history application information of the credit applications people of other node devices, wherein other node devices can be to be saved with A
The different types of node device of point device, as A node devices can be Agricultural Bank of China's credit ATM machine and other nodes are set
But standby Industrial and Commercial Bank of China's credit ATM machine, safety bank credit ATM machine etc., other node device can be to be set with A nodes
The node device of standby diverse geographic location, if A node devices can be Agricultural Bank of China's credit ATM machine in Shenzhen, and its
Its node device can be Industrial and Commercial Bank of China's credit ATM machine in Shanghai etc..
Step S20 identifies whether the corresponding credit applications behavior of the application information is fraud；
After obtaining application information, identify whether corresponding credit applications behavior is fraud based on this application information,
Specifically, the blacklist file that all-in-one machine node device prestores is obtained first, and credit applications people is judged based on the application information
Whether in blacklist file, when being, identify that the corresponding credit applications behavior of the application information is fraud, when not being
When, execute following steps S21：
Step S21 is based on the application information, inquires the credit number of corresponding credit applications people and the Shen of each credit
It please the time；
Based on the application information, the identity information such as identification card number of credit applications people is obtained, based on credit applications people's
The credit time of server end of the identification card number in all-in-one machine or the server end inquiry credit applications people in local node equipment
The application time of number and each credit specifically can also be in the server end of all-in-one machine or in local node equipment
Server end inquires the credit amount of each credit of credit applications people.Have it should be noted that the server end of all-in-one machine summarizes
The credit information of each credit applications people, and local node equipment can load corresponding credit applications people from the server end of all-in-one machine
Credit information, thus, server end that can be in all-in-one machine or the server end in local node equipment inquire credit applications
The information such as the credit number of people and the application time of each credit.
Step S22, the application time based on the credit number and each credit generate the letter of the credit applications people
Borrow application indicatrix；
After obtaining the application time of credit number and each credit of credit applications people, the program segment to prestore is called,
To realize that the application time based on the credit number and each credit generates the credit applications feature of the credit applications people
Curve, particularly, the program segment to prestore can also be given birth to based on the application time of each credit amount and each credit
At corresponding credit amount-time graph.
Step S23 is based on the credit applications indicatrix, judges the credit applications people with the presence or absence of concentration credit Shen
It please behavior；
The credit applications indicatrix that application time based on the credit number and each credit is generated, judges institute
Credit applications people is stated with the presence or absence of credit applications behavior is concentrated, specifically, which can be：Judge the Shen of each credit
Please time interval whether all be shorter than preset time, when each credit application time interval all be shorter than preset time when, judge institute
It states credit applications people and there is concentration credit applications behavior, when the application time interval of each credit is not all shorter than preset time,
The identification model to prestore is called, identifies the credit applications people with the presence or absence of concentration credit applications behavior based on the identification model.
Step S24 identifies that the application information is corresponding when the credit applications people, which exists, concentrates credit applications behavior
Credit applications behavior is fraud.
When based on identification model, identify the credit applications people exist concentrate credit applications behavior when, identify the application
The corresponding credit applications behavior of information is fraud, when the credit applications people, which does not exist, concentrates credit applications behavior, is known
The corresponding credit applications behavior of not described application information is not fraud.
Step S30 is based on the application information when the corresponding credit applications behavior of the application information is fraud
Generate the first blacklist file；
When the corresponding credit applications behavior of the application information is fraud, the personal letter of credit applications people is obtained
Breath judges that credit applications people whether there is in the local blacklist file that local node equipment prestores, when it be not present, base
The first blacklist file is generated in the application information, and the body of corresponding credit applications people is specifically obtained from application information
Part card number and name generate the first blacklist file based on the identification card number and name.
Step S40, by the first blacklist file broadcast to the associated other node devices of all-in-one machine, for other sections
Point device updates its local blacklist file.
After generating the first blacklist file, pass through the shared association of existing blacklist between each node device of all-in-one machine
View, by the first blacklist file broadcast to the associated other node devices of all-in-one machine, so that other node devices update it
Local blacklist file is cheated loan behavior, wherein other node devices add after detecting first blacklist to avoid concentration
It carries in the first blacklist file to the local blacklist file of corresponding node equipment, so that other node devices identify row of cheating loan
For.
The present invention is by when detecting credit examination ＆ approval instruction on the node device in all-in-one machine, obtaining the credit examination ＆ approval
Instruct corresponding application information；Identify whether the corresponding credit applications behavior of the application information is fraud；When the Shen
Please information corresponding credit applications behavior when being fraud, the first blacklist file is generated based on the application information；By institute
The first blacklist file broadcast is stated to the associated other node devices of all-in-one machine, so that other node devices update its Local Black name
Monofile.If first can be generated when a node device detects the credit applications people with fraud in the application
Simultaneously real-time broadcast is to other node devices of all-in-one machine for blacklist file, i.e., each node device of all-in-one machine cooperates in this application
The shared blacklist file of interaction, it is thus possible to realize the different node device real-time synchronization application risk information of all-in-one machine, effectively
It avoids the concentration in the short time from cheating loan, realizes strange land or across style credit risk joint control.
Optionally, the present invention provides the second embodiment of credit risk joint control method, in a second embodiment, the identification
Whether the corresponding credit applications behavior of the application information is that fraud step further includes：
Step A1 is based on the application information, obtains the identity information of the credit applications people；
In the present embodiment, it is also necessary to obtain the identity information of credit applications people, credit Shen is judged based on the identity information
Asking someone, whether identity is faked, and when credit applications person part is faked, credit applications behavior is fraud.
Step A2 calls the reference information of credit applications people in credit investigation system, compares the identity information and believes with reference
Reference identity in breath；
Judge whether the detailed process that identity is faked can be credit applications people：In the identity information for obtaining credit applications people
Afterwards, the reference information of credit applications people in credit investigation system is called to compare the body to obtain the reference identity of credit applications people
Part information and the reference identity in reference information, to judge whether the two is consistent, wherein call the credit applications in credit investigation system
The reference information process of people can be：Name and identification card number of the node device of all-in-one machine based on credit applications people, to reference
The corresponding reference identity of system request, after the request for receiving the corresponding reference identity, credit investigation system is to credit applications
People asks to authorize, if after getting the mandate of credit applications people, credit investigation system is sent to corresponding reference identity at the section of all-in-one machine
Point device, so that the node device of all-in-one machine compares the identity information and the reference identity in reference information.
Step A3 identifies the corresponding credit Shen of the application information when the identity information and reference identity are inconsistent
Please behavior be fraud.
When the identity information and reference identity are inconsistent, identify that the corresponding credit applications behavior of the application information is
Fraud identifies the corresponding credit applications behavior of the application information not when the identity information is consistent with reference information
It is fraud, wherein the identity information individual for referring to the credit applications people described in reference record consistent with reference identity
Information such as job overall, name etc. are identical described in the identity information of credit applications people.
In the present embodiment, by being based on the application information, the identity information of the target credit applications people is obtained；It adjusts
With the reference information of target credit applications people in credit investigation system, the identity information and the benchmark body in reference information are compared
Part；When the identity information and inconsistent reference breath, identify that the corresponding credit applications behavior of the application information is fraud row
For.The present embodiment identifies the identity information of all-in-one machine credit applications people, accurately identifies blacklist, to realize and other node devices
Accurately shared blacklist.
Optionally, the present invention provides the 3rd embodiment of credit risk joint control method, in the third embodiment, described by institute
Include before stating the first blacklist file broadcast to the associated other node device steps of all-in-one machine：
Step B1 obtains each first blacklist file that each node device generates at interval of preset time period；
In the present embodiment, credit all-in-one machine obtains each of each node device generation of all-in-one machine at interval of preset time period
A first blacklist file, wherein the preset time period can be one day or two weeks etc..
Step B2, each first blacklist file data described in cleaning treatment, to generate the second blacklist file；
Each first blacklist file data described in cleaning treatment, wherein the cleaning treatment process includes credit applications people
Duplicate removal process, in addition, the cleaning treatment process further includes black to first of the different-format on each node device of all-in-one machine
List file data carries out format conversion processing, to generate the second blacklist file of unified format.
The second blacklist file is sent to each node device by step B3, so that each node device loads.
After generating the second blacklist file, each node is broadcasted or be sent to the second blacklist file consolidation
Equipment, so that each node device loads.
In the present embodiment, by obtaining each the first of each node device generation of all-in-one machine at interval of preset time period
Blacklist file；Each first blacklist file data described in cleaning treatment, to generate the second blacklist file；By described second
Blacklist file is sent to each node device, so that each node device loads.The present embodiment is not spaced preset time period system
The blacklist file of the one each node device of update, to realize credit risk joint control.
Optionally, the present invention provides the fourth embodiment of credit risk joint control method, in the fourth embodiment, the cleaning
Each first blacklist file data is handled, includes to generate the second blacklist Files step：
Step C1 obtains the type that each node device of all-in-one machine corresponds to credit, obtains the style credit respectively and corresponds to
Air control weight information；
Wherein, step C1 includes：
Step D1 obtains audit stringency of the style credit corresponding node equipment to application information；
The type that each node device of all-in-one machine corresponds to credit is obtained, obtains the style credit corresponding node equipment to Shen
Please information audit stringency, wherein data class can be audited based on credit product to the audit data volume of corresponding application information
Type, audit time etc. determine audit stringency of the node device to application information.
Step D2 obtains the corresponding air control weight information of the style credit respectively based on the audit stringency.
In the present embodiment, when credit product is stringenter to the audit stringency of application information, then the style credit pair
The air control weight information answered is heavier, when credit product is looser to the audit stringency of application information, then the style credit pair
The air control weight information answered is lighter, is illustrated to specific embodiment, and credit product includes x, y, z etc., x, y, z credit products
The Stringency of the audit stringency of application information is reduced successively, then x, y, the corresponding weight of z credit products may respectively be
50%, 30%, 20%.
Step C2 obtains the reputation score of credit applications people in the first blacklist file, is based on the air control weight information,
Deduction processing is carried out to the reputation score of the credit applications people in the first blacklist file, to generate the second blacklist text
Part.
The reputation score for obtaining credit applications people in the first blacklist file, the style credit based on acquisition are corresponding
Air control weight information calculates the reputation score of credit applications people in the first blacklist file, to the institute in the first blacklist file
The reputation score for stating credit applications people carries out deduction processing, to generate the second blacklist file.It is said to specific embodiment
It is bright, if the reputation score of A credit applications people is 85 points in the first blacklist file, and the first blacklist where credit applications people
The air control weight of corresponding types credit product is 50% in file, and often cheats loan or cheat primary, the type credit product pair
The reputation score of credit applications people subtracts 10*50%=5 points, if then corresponding in the first blacklist file where credit applications people
The air control weight of style credit product is 30%, and is often cheated loan or cheat once, and the type credit product is to credit applications people
Reputation score subtract 10*30%=3 point.
In the present embodiment, the type that credit is corresponded to by obtaining each node device of all-in-one machine, obtains the class respectively
The corresponding air control weight information of type credit；The reputation score of credit applications people in the first blacklist file is obtained, the wind is based on
Weight information is controlled, deduction processing is carried out to the reputation score of the credit applications people in the first blacklist file, to generate the
Two blacklist files, it is thus possible to accurately objectively obtain the reputation score of credit applications people in blacklist.
Optionally, the present invention provides the 5th embodiment of credit risk joint control method, in the 5th embodiment, the cleaning
Each first blacklist file data is handled, includes to generate the second blacklist Files step：
It is described to obtain the style credit corresponding node equipment and include to the audit stringency step of application information：
Step E1 obtains the style credit corresponding node equipment to the target audit data volume of corresponding application information, mesh
Mark audit data type number and target audit time；
It obtains the style credit corresponding node equipment and data volume is audited to the target of corresponding application information, target audits number
According to number of types, target audit time, wherein audit data volume is more, and audit data type number is more, and audit time gets over
Long, audit is stringenter.
Step E2 returns target audit data volume, target audit data type number and target audit time
One change is handled, and each normalization data is obtained with correspondence；
In acquisition target audit data volume, target audit data type number and after target audit time, normalized
Target audits data volume, target audit data type number and target audit, wherein normalized process is：Target is examined
Nuclear Data amount, target audit data type number and target audit all project between 0-1.Specifically normalized algorithm can be
Simultaneously divided by one digital greatly, big number=maximum value-minimum value.Maximum value refers to target audit data volume, target audit number
The maximum value of these three parameter values is audited according to number of types and target, minimum value refers to the minimum value of three parameter values.In order to
Negative is avoided the occurrence of, before being multiplied by big number, all parameter values are all subtracted into minimum value, then multiplied by with big number.It lifts
A example, the parameter value got is 1000,10,20 etc., then maximum value is 1000, minimum value 10, and in order to avoid going out
Existing negative, subtracts minimum and is worth to 990,0,10 first.Then again divided by 990, then corresponding parameter value has been converted to 1,
0,10/990.
Step E3 obtains the accounting of audit data volume, audit data type number and audit time in auditing stringency
Information calculates the style credit corresponding node equipment to letter of application based on the accounting information and each normalization data
The audit stringency of breath.
The accounting information of audit data volume, audit data type number and audit time in auditing stringency is obtained, such as
Audit data volume accounting can be 50%, and audit data type number accounting is 30%, and audit time accounting is 20%, is accounted for based on this
Than information and each normalization data, it is stringent to the audit of application information to calculate the style credit corresponding node equipment
Degree, specifically, audit data volume accounting can be 50%, and audit data type number accounting is 30%, and audit time accounting is
20%, it can be 1,0 that target audit data volume, target audit data type number and target audit time, which correspond to normalization data,
10/990, the style credit corresponding node equipment can be 1*50%+0*30%+20%* to the audit stringency of application information
10/990。
In the present embodiment, the target of corresponding application information is audited by obtaining the style credit corresponding node equipment
Data volume, target audit data type number and target audit time；Data class is audited to target audit data volume, target
Type number and target audit time are normalized, and each normalization data is obtained with correspondence；It obtains audit data volume, examine
The accounting information of Nuclear Data number of types and audit time in auditing stringency, based on the accounting information and each normalizing
Change data, calculates audit stringency of the style credit corresponding node equipment to application information.The present embodiment is accurately obtained and is examined
Core stringency, it is thus possible to accurately objectively obtain the reputation score of credit applications people in blacklist.
The present invention also provides a kind of credit risk combined control equipment, the credit risk combined control equipment includes：
First acquisition module, for when detecting credit examination ＆ approval instruction on the node device in all-in-one machine, described in acquisition
Credit examination ＆ approval instruct corresponding application information；
Identification module, whether the corresponding credit applications behavior of the application information for identification is fraud；
Generation module, for when the corresponding credit applications behavior of the application information is fraud, being based on the Shen
It please information the first blacklist file of generation；
Broadcast module, for by the first blacklist file broadcast to the associated other node devices of all-in-one machine, for
Other node devices update its local blacklist file.
Optionally, the identification module includes：
Query unit inquires the credit number of corresponding credit applications people and each letter for being based on the application information
The application time of loan；
Generation unit is used for the application time based on the credit number and each credit, generates the credit applications
The credit applications indicatrix of people；
Judging unit judges the credit applications people with the presence or absence of concentration for being based on the credit applications indicatrix
Credit applications behavior；
First recognition unit, for when the credit applications people exists and concentrates credit applications behavior, identifying the application
The corresponding credit applications behavior of information is fraud.
Optionally, identification module further includes：
First acquisition unit obtains the identity information of the credit applications people for being based on the application information；
Call unit, the reference information for calling credit applications people in credit investigation system, compare the identity information with
Reference identity in reference information；
Second recognition unit, for when the identity information and reference identity are inconsistent, identifying the application information pair
The credit applications behavior answered is fraud.
Optionally, the credit risk combined control equipment further includes：
Second acquisition module, each first for obtaining that each node device generates at interval of preset time period are black
Name monofile；
Cleaning module, for each first blacklist file data described in cleaning treatment, to generate the second blacklist file；
Sending module, for the second blacklist file to be sent to each node device, for each node device
Load.
Optionally, the cleaning module includes：
Second acquisition unit corresponds to the type of credit for obtaining each node device of all-in-one machine, obtains the class respectively
The corresponding air control weight information of type credit；
Third acquiring unit, the reputation score for obtaining each credit applications people in the first blacklist file are based on institute
Air control weight information is stated, deduction processing is carried out to the reputation score of the credit applications people in the first blacklist file, with
To the second blacklist file.
Optionally, the second acquisition unit includes：
First obtains subelement, stringent to the audit of application information for obtaining the style credit corresponding node equipment
Degree；
Second obtains subelement, and the corresponding air control power of the style credit is obtained respectively for being based on the audit stringency
Weight information.
Optionally, the first acquisition subelement is additionally operable to：
It obtains the style credit corresponding node equipment and number is audited to target audit data volume, the target of corresponding application information
According to number of types and target audit time；
Place is normalized to target audit data volume, target audit data type number and target audit time
Reason obtains each normalization data with correspondence；
Obtain the accounting information of audit data volume, audit data type number and audit time in auditing stringency, base
In the accounting information and each normalization data, audit of the style credit corresponding node equipment to application information is calculated
Stringency.
With reference to Fig. 3, Fig. 3 is the device structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
Credit risk joint control equipment of the embodiment of the present invention can be PC, can also be smart mobile phone, tablet computer, e-book
Reader, MP3 (Moving Picture Experts Group Audio Layer III, dynamic image expert's compression standard
Audio level 3) player, MP4 (Moving Picture Experts Group Audio Layer IV, dynamic image expert
Compression standard audio level 3) terminal devices such as player, pocket computer.
As shown in figure 3, the credit risk joint control equipment may include：Processor 1001, such as CPU, memory 1005 lead to
Believe bus 1002.Wherein, communication bus 1002 is for realizing the connection communication between processor 1001 and memory 1005.Storage
Device 1005 can be high-speed RAM memory, can also be stable memory (non-volatile memory), such as disk
Memory.Memory 1005 optionally can also be the storage device independently of aforementioned processor 1001.
Further, which can also include user interface, network interface, camera, RF
(Radio Frequency, radio frequency) circuit, sensor, voicefrequency circuit, WiFi module etc..User interface may include display
Shield (Display), input unit such as keyboard (Keyboard), optional user interface can also include standard wireline interface,
Wireless interface.Network interface may include optionally standard wireline interface and wireless interface (such as WI-FI interface).
It will be understood by those skilled in the art that credit risk joint control device structure shown in Fig. 3 is not constituted to credit
The restriction of risk joint control equipment may include either combining certain components or different than illustrating more or fewer components
Component is arranged.
As shown in figure 3, as may include that operating system, network are logical in a kind of memory 1005 of computer storage media
Believe module and credit risk joint control program.Operating system is management and control credit risk joint control device hardware and software resource
Program, support the operation of credit risk joint control program and other softwares and/or program.Network communication module is for realizing depositing
Communication between each component in the inside of reservoir 1005, and with communicated between other hardware and softwares in credit risk joint control equipment.
In credit risk joint control equipment shown in Fig. 3, processor 1001 is for executing the letter stored in memory 1005
Risk joint control program is borrowed, realizes the step in above-mentioned each embodiment of credit risk joint control method.
In addition, to achieve the above object, the embodiment of the present invention also provides a kind of credit risk joint control equipment, the credit wind
Dangerous joint control equipment includes：Memory, processor, communication bus and the credit risk joint control journey being stored on the memory
Sequence,
The communication bus is for realizing the communication connection between processor and memory；
The processor is for executing the credit risk joint control program, to realize above-mentioned each reality of credit risk joint control method
Apply the step in example
An embodiment of the present invention provides a kind of readable storage medium storing program for executing, readable storage medium storing program for executing storage there are one or one
Procedure above, the one or more programs can also be executed for realizing by one or more than one processor
The step of credit risk joint control method described in any one of the above embodiments.
Readable storage medium storing program for executing specific implementation mode of the present invention and above-mentioned each embodiment of credit risk joint control method are essentially identical,
Details are not described herein.
It these are only the preferred embodiment of the present invention, be not intended to limit the scope of the invention, it is every to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field includes similarly in the patent process range of the present invention.
Claims (10)
1. a kind of credit risk joint control method, which is characterized in that the credit risk joint control method is applied to all-in-one machine, the letter
Borrowing risk joint control method includes：
When detecting credit examination ＆ approval instruction on the node device in all-in-one machine, obtains the credit examination ＆ approval and instruct corresponding application
Information；
Identify whether the corresponding credit applications behavior of the application information is fraud；
When the corresponding credit applications behavior of the application information is fraud, the first black name is generated based on the application information
Monofile；
By the first blacklist file broadcast to the associated other node devices of all-in-one machine, so that other node devices update it
Local blacklist file.
2. credit risk joint control method as described in claim 1, which is characterized in that the identification application information is corresponding
Whether credit applications behavior is that fraud step includes：
Based on the application information, the credit number of corresponding credit applications people and the application time of each credit are inquired；
Application time based on the credit number and each credit, the credit applications feature for generating the credit applications people are bent
Line；
Based on the credit applications indicatrix, judge the credit applications people with the presence or absence of concentration credit applications behavior；
When the credit applications people, which exists, concentrates credit applications behavior, the corresponding credit applications behavior of the application information is identified
It is fraud.
3. credit risk joint control method as described in claim 1, which is characterized in that the identification application information is corresponding
Whether credit applications behavior is that fraud step further includes：
Based on the application information, the identity information of the credit applications people is obtained；
The reference information for calling credit applications people in credit investigation system compares the identity information and the benchmark body in reference information
Part；
When the identity information and reference identity are inconsistent, identify that the corresponding credit applications behavior of the application information is fraud
Behavior.
4. credit risk joint control method as described in claim 1, which is characterized in that described that the first blacklist file is wide
Include before casting to the associated other node device steps of all-in-one machine：
Each first blacklist file that each node device generates is obtained at interval of preset time period；
Each first blacklist file data described in cleaning treatment, to generate the second blacklist file；
The second blacklist file is sent to each node device, so that each node device loads.
5. credit risk joint control method as claimed in claim 4, which is characterized in that each first is black described in the cleaning treatment
List file data, with generate the second blacklist Files step include：
The type that each node device of all-in-one machine corresponds to credit is obtained, obtains the corresponding air control weight letter of the style credit respectively
Breath；
The reputation score of each credit applications people in the first blacklist file is obtained, the air control weight information is based on, to first
The reputation score of the credit applications people in blacklist file carries out deduction processing, to obtain the second blacklist file.
6. credit risk joint control method as claimed in claim 5, which is characterized in that described to obtain the style credit pair respectively
The air control weight information step answered includes：
Obtain audit stringency of the style credit corresponding node equipment to application information；
The corresponding air control weight information of the style credit is obtained respectively based on the audit stringency.
7. credit risk joint control method as claimed in claim 6, which is characterized in that described to obtain the style credit correspondence section
Point device includes to the audit stringency step of application information：
It obtains the style credit corresponding node equipment and data class is audited to target audit data volume, the target of corresponding application information
Type number and target audit time；
Target audit data volume, target audit data type number and target audit time are normalized, with
Correspondence obtains each normalization data；
The accounting information of audit data volume, audit data type number and audit time in auditing stringency is obtained, being based on should
Accounting information and each normalization data, it is stringent to the audit of application information to calculate the style credit corresponding node equipment
Degree.
8. a kind of credit risk combined control equipment, which is characterized in that the credit risk combined control equipment includes：
First acquisition module, for when detecting credit examination ＆ approval instruction on the node device in all-in-one machine, obtaining the credit
Examination ＆ approval instruct corresponding application information；
Identification module, whether the corresponding credit applications behavior of the application information for identification is fraud；
Generation module, for when the corresponding credit applications behavior of the application information is fraud, being based on the letter of application
Breath generates the first blacklist file；
Broadcast module is used for the first blacklist file broadcast to the associated other node devices of all-in-one machine, for other
Node device updates its local blacklist file.
9. a kind of credit risk joint control equipment, which is characterized in that the credit risk joint control equipment includes：Memory, processor,
Communication bus and the credit risk joint control program being stored on the memory,
The communication bus is for realizing the communication connection between processor and memory；
The processor is for executing the credit risk joint control program, to realize as described in any one of claim 1 to 7
The step of credit risk joint control method.
10. a kind of readable storage medium storing program for executing, which is characterized in that credit risk joint control program is stored on the readable storage medium storing program for executing,
The credit risk joint control as described in any one of claim 1-7 is realized when the credit risk joint control program is executed by processor
The step of method.
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|---|---|---|---|
| CN201810033721.0A CN108364224A (en) | 2018-01-12 | 2018-01-12 | Credit risk joint control method, apparatus, equipment and readable storage medium storing program for executing |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109523371A (en) * | 2018-10-12 | 2019-03-26 | 深圳壹账通智能科技有限公司 | Online make loans checking method, device, computer equipment and storage medium |
| CN109636574A (en) * | 2018-10-25 | 2019-04-16 | 平安科技（深圳）有限公司 | Risk checking method, device, equipment and the storage medium of credit information |
| CN109636578A (en) * | 2018-10-25 | 2019-04-16 | 平安科技（深圳）有限公司 | Risk checking method, device, equipment and the readable storage medium storing program for executing of credit information |
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| CN111212073A (en) * | 2020-01-02 | 2020-05-29 | 中国银行股份有限公司 | Public cloud-based blacklist account sharing method and device |
| CN111861733A (en) * | 2020-07-31 | 2020-10-30 | 重庆富民银行股份有限公司 | Fraud prevention and control system and method based on address fuzzy matching |
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130024364A1 (en) * | 2011-02-22 | 2013-01-24 | Abhinav Shrivastava | Consumer transaction leash control apparatuses, methods and systems |
| CN104850526A (en) * | 2015-06-10 | 2015-08-19 | 首都师范大学 | Method for time synchronization in dynamically reconfigurable high-speed serial bus |
| CN205451316U (en) * | 2016-03-15 | 2016-08-10 | 天津泰林科技发展有限公司 | Loan done by oneself machine |
| CN105871700A (en) * | 2016-05-31 | 2016-08-17 | 腾讯科技（深圳）有限公司 | Message propagation method and server |
| CN107392755A (en) * | 2017-07-07 | 2017-11-24 | 南京甄视智能科技有限公司 | Credit risk merges appraisal procedure and system |
| CN107392451A (en) * | 2017-07-11 | 2017-11-24 | 重庆卡西匚匚科技有限公司 | A kind of risk control system |
| CN206696966U (en) * | 2017-05-25 | 2017-12-01 | 山东智翔电子技术有限公司 | A kind of intelligent self-service all-in-one applied to bank |
| CN107426265A (en) * | 2016-03-11 | 2017-12-01 | 阿里巴巴集团控股有限公司 | The synchronous method and apparatus of data consistency |
-
2018
- 2018-01-12 CN CN201810033721.0A patent/CN108364224A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130024364A1 (en) * | 2011-02-22 | 2013-01-24 | Abhinav Shrivastava | Consumer transaction leash control apparatuses, methods and systems |
| CN104850526A (en) * | 2015-06-10 | 2015-08-19 | 首都师范大学 | Method for time synchronization in dynamically reconfigurable high-speed serial bus |
| CN107426265A (en) * | 2016-03-11 | 2017-12-01 | 阿里巴巴集团控股有限公司 | The synchronous method and apparatus of data consistency |
| CN205451316U (en) * | 2016-03-15 | 2016-08-10 | 天津泰林科技发展有限公司 | Loan done by oneself machine |
| CN105871700A (en) * | 2016-05-31 | 2016-08-17 | 腾讯科技（深圳）有限公司 | Message propagation method and server |
| CN206696966U (en) * | 2017-05-25 | 2017-12-01 | 山东智翔电子技术有限公司 | A kind of intelligent self-service all-in-one applied to bank |
| CN107392755A (en) * | 2017-07-07 | 2017-11-24 | 南京甄视智能科技有限公司 | Credit risk merges appraisal procedure and system |
| CN107392451A (en) * | 2017-07-11 | 2017-11-24 | 重庆卡西匚匚科技有限公司 | A kind of risk control system |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2020062641A1 (en) * | 2018-09-26 | 2020-04-02 | 深圳壹账通智能科技有限公司 | Method for identifying user role, and user equipment, storage medium, and apparatus for identifying user role |
| CN109523371B (en) * | 2018-10-12 | 2023-04-07 | 深圳壹账通智能科技有限公司 | Online payment auditing method and device, computer equipment and storage medium |
| CN109523371A (en) * | 2018-10-12 | 2019-03-26 | 深圳壹账通智能科技有限公司 | Online make loans checking method, device, computer equipment and storage medium |
| CN109636574A (en) * | 2018-10-25 | 2019-04-16 | 平安科技（深圳）有限公司 | Risk checking method, device, equipment and the storage medium of credit information |
| CN109636578A (en) * | 2018-10-25 | 2019-04-16 | 平安科技（深圳）有限公司 | Risk checking method, device, equipment and the readable storage medium storing program for executing of credit information |
| CN109636578B (en) * | 2018-10-25 | 2023-05-26 | 平安科技（深圳）有限公司 | Credit information risk detection method, apparatus, device and readable storage medium |
| CN109636574B (en) * | 2018-10-25 | 2023-05-23 | 平安科技（深圳）有限公司 | Credit information risk detection method, apparatus, device and storage medium |
| CN109711973A (en) * | 2018-11-09 | 2019-05-03 | 深圳壹账通智能科技有限公司 | Methods of risk assessment and device, storage medium, computer equipment |
| CN109859029A (en) * | 2019-01-04 | 2019-06-07 | 深圳壹账通智能科技有限公司 | Abnormal application detection method, device, computer equipment and storage medium |
| CN111212073A (en) * | 2020-01-02 | 2020-05-29 | 中国银行股份有限公司 | Public cloud-based blacklist account sharing method and device |
| CN111212073B (en) * | 2020-01-02 | 2022-07-05 | 中国银行股份有限公司 | Public cloud-based blacklist account sharing method and device |
| CN111861733A (en) * | 2020-07-31 | 2020-10-30 | 重庆富民银行股份有限公司 | Fraud prevention and control system and method based on address fuzzy matching |
| CN111861733B (en) * | 2020-07-31 | 2023-09-15 | 重庆富民银行股份有限公司 | Fraud prevention and control system and method based on address fuzzy matching |
| CN112668886A (en) * | 2020-12-29 | 2021-04-16 | 深圳前海微众银行股份有限公司 | Method, device and equipment for monitoring risks of rental business and readable storage medium |
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