CN110232484A - Risk policy optimization method, device, equipment and computer readable storage medium - Google Patents
Risk policy optimization method, device, equipment and computer readable storage medium Download PDFInfo
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- CN110232484A CN110232484A CN201910546294.0A CN201910546294A CN110232484A CN 110232484 A CN110232484 A CN 110232484A CN 201910546294 A CN201910546294 A CN 201910546294A CN 110232484 A CN110232484 A CN 110232484A
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Abstract
The invention discloses a kind of risk policy optimization method, device, equipment and computer storage mediums, the risk policy optimization method includes: that the corresponding first risk label of application information in partner's platform is obtained in risk label model, carries out the first examination & approval to the application information based on the first risk label；The second trial information that partner's platform is initiated based on first examination & approval is obtained, and the second risk label is determined in the risk label model according to the second trial information；Risk label interaction page is determined based on the first risk label and the second risk label, and the risk label interaction page is transferred to partner's platform；Approval results of the partner's platform in the risk label interaction page are obtained, and model iteration is carried out to the risk label model based on the approval results, to complete the optimization of risk label strategy.Solves the technical issues of can not risk label strategy being upgraded and be optimized in the prior art.
Description
Technical field
The present invention relates to techno-financial (Fintech) technical field more particularly to a kind of risk policy optimization methods, dress
It sets, equipment and computer readable storage medium.
Background technique
With financial technology (Fintech), the especially continuous development of internet techno-financial, more and more technologies are answered
Used in financial field.For example, risk of fraud administrative skill is exactly one such, and mainly by main strategies platform from
Thing is counter to cheat relevant work, i.e., provides a large amount of objective initial data by main strategies platform for co-operation platform, still
Objective initial data dimension is single, can not comprehensively cover the complexity of auto metal halide lamp and the risk of fraud object of various dimensions, and
Since the data providing formula of main strategies platform is the presentation mode of single dimension, i.e. main strategies platform can only provide original
Beginning data are to co-operation platform, and co-operation platform can not return data into main strategies platform, cause based on objective initial data
The risk label strategy of formation can not upgrade and optimize, so that co-operation platform be allowed to be difficult with.Therefore, how to risk label plan
Slightly upgraded and is optimized to for a technical problem to be solved urgently.
Summary of the invention
The main purpose of the present invention is to provide the storages of a kind of risk policy optimization method, device, equipment and computer to be situated between
Matter, it is intended to the technical issues of solution can not be upgraded and be optimized to risk label strategy in the prior art.
To achieve the above object, the present invention provides a kind of risk policy optimization method, device, equipment and computer-readable
Storage medium, the risk policy optimization method include:
The corresponding first risk label of application information in partner's platform is obtained in risk label model, based on described the
One risk label carries out the first examination & approval to the application information；
The second trial information that partner's platform is initiated based on first examination & approval is obtained, and is existed according to the second trial information
The second risk label is determined in the risk label model；
Risk label interaction page is determined based on the first risk label and the second risk label, and by the wind
Dangerous label interaction page is transferred to partner's platform；
Approval results of the partner's platform in the risk label interaction page are obtained, and are tied based on the examination & approval
Fruit carries out model iteration to the risk label model, to complete the optimization of risk label strategy.
Optionally, described the step of model iteration is carried out to the risk label model based on the approval results, comprising:
Obtain the corresponding refund data of the application information；
Model iteration is carried out to the risk label model based on the refund data and the approval results.
Optionally, described that the corresponding first risk label of application information in partner's platform is obtained in risk label model
The step of before, comprising:
The system platform where risk label model is obtained, and determines between the system platform and partner's platform and is
Whether system docking concept is open platform docking；
It is open to partner's platform to check that the system is flat if the system docking scheme is open platform docking
The permission of data in platform.
Optionally, if the system docking scheme is open platform docking, partner's platform opening is looked into
The step of seeing the permission of data in the system platform, comprising:
If the system docking scheme is open platform docking, the account information in partner's platform is obtained, and
Judge whether the account information matches with default account information；
It is open to partner's platform to check that the system is flat if the account information and the matching of default account information
The permission of data in platform.
Optionally, if the account information and the matching of default account information, only open partner's platform
The step of checking the permission of data in the system platform, comprising:
If the account information and the matching of default account information, obtain between the corresponding preset time of the account information
Every；
Based on the power for checking data in the system platform in the prefixed time interval to partner's platform opening
Limit.
Optionally, described that the corresponding first risk label of application information in partner's platform is obtained in risk label model
The step of, comprising:
Obtain the corresponding borrower's information of partner's platform application information；
Reference inquiry is carried out according to borrower's information in risk label model, to obtain the first risk label.
Optionally, the step for determining the second risk label in the risk label model according to the second trial information
Suddenly, comprising:
Obtain other corresponding main informations of second trial information；
Reference inquiry is carried out according to other described main informations in risk label model, to obtain the second risk label.
In addition, to achieve the above object, the present invention also provides a kind of risk policies to optimize device, the risk policy optimization
Device includes:
Module is obtained, for obtaining the corresponding first risk mark of application information in partner's platform in risk label model
Label carry out the first examination & approval to the application information based on the first risk label；
Determining module, the second trial information initiated for obtaining partner's platform based on first examination & approval, and according to
The second trial information determines the second risk label in the risk label model；
Transfer module, for determining risk label interaction page based on the first risk label and the second risk label
Face, and the risk label interaction page is transferred to partner's platform；
Iteration module, for obtaining approval results of the partner's platform in the risk label interaction page, and
Model iteration is carried out to the risk label model based on the approval results, to complete the optimization of risk label strategy.
In addition, to achieve the above object, the present invention also provides a kind of risk policies to optimize equipment；
Risk policy optimization equipment includes: memory, processor and is stored on the memory and can be described
The computer program run on processor, in which:
The computer program realizes the step of risk policy optimization method as described above when being executed by the processor.
In addition, to achieve the above object, the present invention also provides computer storage mediums；
Computer program, the realization when computer program is executed by processor are stored in the computer storage medium
Such as the step of above-mentioned risk policy optimization method.
The embodiment of the present invention propose a kind of risk policy optimization method, device, equipment and readable storage medium storing program for executing, by
The corresponding first risk label of application information in partner's platform is obtained in risk label model, is based on the first risk label
First examination & approval are carried out to the application information；The second trial information that partner's platform is initiated based on first examination & approval is obtained,
And the second risk label is determined in the risk label model according to the second trial information；Based on the first risk label and
The second risk label determines risk label interaction page, and the risk label interaction page is transferred to the partner
Platform；Approval results of the partner's platform in the risk label interaction page are obtained, and are based on the approval results
Model iteration is carried out to the risk label model, to complete risk policy optimization.By obtaining in risk label model
One risk label and the second risk label, and risk label interaction page is determined according to the first risk label and the second risk label
Face, then the risk label interaction page is transferred to partner's platform.By the way that risk label interaction page is transferred to partner
Platform, and approval results of partner's platform in risk label interaction page are obtained, further according to approval results to risk label
Model carries out model iteration and has ensured risk label to realize the interaction between risk label model and partner's platform
Model can be optimized based on the personalization of partner's platform, and solving in the prior art can not carry out risk label strategy
The technical issues of upgrading and optimization.
Detailed description of the invention
Fig. 1 be the hardware running environment that the embodiment of the present invention is related to terminal apparatus structure schematic diagram；
Fig. 2 is the flow diagram of risk policy optimization method first embodiment of the present invention；
Fig. 3 is the flow diagram of risk policy optimization method second embodiment of the present invention；
Fig. 4 is the system structure diagram that risk policy of the present invention optimizes one embodiment of equipment；
Fig. 5 is risk policy optimization method overall flow schematic diagram of the present invention；
Fig. 6 is the schematic diagram of a scenario of risk policy optimization method interface docking mode of the present invention；
Fig. 7 is the working principle diagram of interface docking mode in risk policy optimization method of the present invention.
The object of the invention is realized, the embodiments will be further described with reference to the accompanying drawings for functional characteristics and advantage.
Specific embodiment
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.
As shown in Figure 1, Fig. 1 is the terminal structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
The terminal of that embodiment of the invention is that risk policy optimizes equipment.
As shown in Figure 1, the terminal may include: processor 1001, such as CPU, network interface 1004, user interface
1003, memory 1005, communication bus 1002.Wherein, communication bus 1002 is for realizing the connection communication between these components.
User interface 1003 may include display screen (Display), input unit such as keyboard (Keyboard), optional user interface
1003 can also include standard wireline interface and wireless interface.Network interface 1004 optionally may include that the wired of standard connects
Mouth, wireless interface (such as WI-FI interface).Memory 1005 can be high speed RAM memory, be also possible to stable memory
(non-volatile memory), such as magnetic disk storage.Memory 1005 optionally can also be independently of aforementioned processor
1001 storage device.
Optionally, terminal can also include camera, RF (Radio Frequency, radio frequency) circuit, sensor, audio
Circuit, WiFi module etc..Wherein, sensor such as optical sensor, motion sensor and other sensors.Specifically, light
Sensor may include ambient light sensor and proximity sensor, wherein ambient light sensor can according to the light and shade of ambient light come
The brightness of display screen is adjusted, proximity sensor can close display screen and/or backlight when terminal device is moved in one's ear.Certainly,
Terminal device can also configure the other sensors such as gyroscope, barometer, hygrometer, thermometer, infrared sensor, herein no longer
It repeats.
It will be understood by those skilled in the art that the restriction of the not structure paired terminal of terminal structure shown in Fig. 1, can wrap
It includes than illustrating more or fewer components, perhaps combines certain components or different component layouts.
As shown in Figure 1, as may include that operating system, network are logical in a kind of memory 1005 of computer storage medium
Believe that module, Subscriber Interface Module SIM and risk policy optimize program.
In terminal shown in Fig. 1, network interface 1004 is mainly used for connecting background server, carries out with background server
Data communication；User interface 1003 is mainly used for connecting client (user terminal), carries out data communication with client；And processor
1001 can be used for that the risk policy stored in memory 1005 is called to optimize program, and execute following operation:
The corresponding first risk label of application information in partner's platform is obtained in risk label model, based on described the
One risk label carries out the first examination & approval to the application information；
The second trial information that partner's platform is initiated based on first examination & approval is obtained, and is existed according to the second trial information
The second risk label is determined in the risk label model；
Risk label interaction page is determined based on the first risk label and the second risk label, and by the wind
Dangerous label interaction page is transferred to partner's platform；
Approval results of the partner's platform in the risk label interaction page are obtained, and are tied based on the examination & approval
Fruit carries out model iteration to the risk label model, to complete the optimization of risk label strategy.
The present invention provides a kind of risk policy optimization method, in risk policy optimization method first embodiment, referring to figure
2, risk policy optimization method the following steps are included:
Step S10 obtains the corresponding first risk label of application information in partner's platform, base in risk label model
The first examination & approval are carried out to the application information in the first risk label；
Risk label can be to be described for the risk of special object and various dimensions.Risk label is important management and carries
Body is realized in examination & approval link and partner's docking and depth cooperation, participates in the air control management of wider scope.Risk label is by silver
The data that are there is provided by partner of row, in integration row and main strategies big data, and risky label model carries out special project
Risk assessment.Risk assessment is mainly made of object and degree of risk, for the risk measure of different partners, Ke Yiti
For the risk suggestion of differentiation.Main strategies platform, which can be, is engaged in reference class business, but is non-national approved, possesses sign
Believe the company of qualification.First risk label can be risk label engine 1, and bank carries out borrower by risk label model
The risk rating that reference inquiry generates.First examination & approval can be the examination & approval carried out for the first time in this loan.
Risk label model can be made up of reference and big data, and be updated by model iteration.And it levies
Letter and big data include reference class data, social category data, behavior class data, other class data.Social data can be user
The trace left on the internet using specific products, the user behavior data got by these traces.Reference is just
Being specialized, the independent third-party institution establishes credibility record for personal or enterprise, in accordance with the law acquisition, its credit of objective record letter
Breath, and a kind of activity of Credit Information Services is externally provided in accordance with the law, it provides credit information for specialized credit mechanism and is total to
The platform enjoyed.
When there is application client that loan is needed to buy some object in partner, then need by partner's platform
Application information determines borrower based on customer information to determine customer information, then carries out reference to borrower in bank
Inquiry, and determine by risk label model the first risk label of borrower, then bank clerk can be according to the
One risk label carries out the first examination & approval to application, to determine the need for borrowing money.
Step S20 obtains the second trial information that partner's platform is initiated based on first examination & approval, and according to described two
It examines information and determines the second risk label in the risk label model；
Second trial information can be second of application msu message initiated to bank of partner.Second risk label can be
Risk label engine 2, bank carry out the risk rating that reference inquiry generates to other main bodys by risk label model.Work as cooperation
After Fang Pingtai determines the first approval information to client, it is necessary to enter the second link, that is, when client determines order information
Afterwards, partner's platform actively can initiate second trial to bank.Bank can carry out reference inquiry to the main body of other except borrower, with
Risk label model be will pass through to determine the second risk label.Wherein, other main bodys are main bodys associated with borrower.
Step S30 determines risk label interaction page based on the first risk label and the second risk label, and
The risk label interaction page is transferred to partner's platform；
After having determined that the first risk label and the second risk label in bank, risk label integration engine pair can be crossed
First risk label and the second risk label are integrated, and to obtain the composite rating of this risk assessment, and will have first
The information of risk label, the second risk label and composite rating is shown in risk label interaction page, then again by this risk mark
Label interaction page transmitting is given to partner's platform, so that the approving person in partner's platform carries out in risk label interaction page
Examination & approval.
Step S40 obtains approval results of the partner's platform in the risk label interaction page, and is based on institute
It states approval results and model iteration is carried out to the risk label model, to complete the optimization of risk label strategy.
When partner's platform is after manually the examination & approval page sees the prompt of risk label, after completing risk verification, approver
Member can identify approval results in the manually examination & approval page.Wherein, manually the examination & approval page includes risk label interaction page.Work as inspection
Measure partner's platform by the approval results feedback in risk label interaction page to bank when, risk label model can root at this time
Model iteration is carried out according to approval results.Wherein, other than approval results can allow risk label model to carry out model iteration, may be used also
Model iteration is carried out to risk label model with the refund data by client, that is, approval results and refund data have
Model iteration system collects data, and periodically to carry out the optimization of new strategy according to the risk policy of the platform.Optimize new plan
It slightly will be updated into risk label model, and come into force and dispose automatically, is i.e. the optimization of completion risk label strategy.
Supplemented by assistant's solution risk label strategy is optimized, be exemplified below.
For example, as shown in figure 5, needing to apply client, cooperation during entire risk label strategy optimizes
Side, bank, reference and big data carry out simultaneously, that is, in link 1, and partner first obtains the customer information of application client,
And determine whether to be applied, when application documents are sent bank by partner, which is examined, that is, 1 is examined, and bank works
It needs first to carry out reference inquiry to borrower when personnel determine the need for examining, and is generated by risk label model
Risk label engine 1, and examined based on risk label engine, approval results are issued to partner and application client again, this
The task of Shi Huanjie 1 is completed, and into link 2, i.e. application client determines order information, and direction of cooperation bank initiates second trial again, this
Shi Yinhang will do it the inquiry of other main body references, and generate corresponding risk label engine 2 by risk label model, then lead to
It crosses risk label integration engine to integrate risk label engine 1 and risk label engine 2, obtains composite rating, i.e. risk
Label interaction page, and partner is sent by this risk labels page, at this time it is considered that having entered link 3, partner
Staff will do it artificial examination & approval, and feed back approval results to bank, at this time it is considered that into link 4, i.e. risk label
Model can carry out model iteration according to feedback approval results and refund data.Wherein, risk label model may include reference
And reference class data, social category data in big data, behavior class data and other class data.
In the present embodiment, by obtaining corresponding first wind of application information in partner's platform in risk label model
Dangerous label carries out the first examination & approval to the application information based on the first risk label；Partner's platform is obtained to be based on
The second trial information that first examination & approval are initiated, and the second risk is determined in the risk label model according to the second trial information
Label；Risk label interaction page is determined based on the first risk label and the second risk label, and by the risk
Label interaction page is transferred to partner's platform；Partner's platform is obtained in the risk label interaction page
Approval results, and model iteration is carried out to the risk label model based on the approval results, to complete risk policy optimization.
By obtaining the first risk label and the second risk label in risk label model, and according to the first risk label and the second wind
Dangerous label determines risk label interaction page, then the risk label interaction page is transferred to partner's platform.By by risk
Label interaction page is transferred to partner's platform, and obtains approval results of partner's platform in risk label interaction page,
Model iteration is carried out to risk label model further according to approval results, thus realize risk label model and partner's platform it
Between interaction, ensured that risk label model can be optimized based on the personalization of partner's platform, solved the prior art
In the technical issues of risk label strategy can not being upgraded and be optimized.
Further, on the basis of first embodiment of the invention, the of risk policy optimization method of the present invention is proposed
Two embodiments, the present embodiment are the step S40 of first embodiment of the invention, based on the approval results to the risk label mould
The step of type progress model iteration, refines, referring to Fig. 3, comprising:
Step S41 obtains the corresponding refund data of the application information；
Refund data can be the refund data that application information corresponds to borrower.Therefore it needs to obtain Shen in bank data
Please the corresponding refund data of information, so as in time to risk label model carry out model iteration, ensure pass through risk label model
Get the accuracy of risk policy.
Step S42 carries out model iteration to the risk label model based on the refund data and the approval results.
After getting refund data and approval results, so that it may according to refund data and approval results come to risk label
Model carry out model iteration, it should be noted that when in only refund data and approval results one of them when, can also be to wind
Dangerous label model carries out model iteration.Approval results ought be got, are gone back without getting refund data, or when getting
Amount of money evidence, and when approval results have not been obtained, model iteration can also be carried out to risk label model.
In the present embodiment, by obtaining refund data, and according to refund data and approval results to risk label model
Model iteration is carried out, to ensure the availability of the strategy generated based on risk label model.
Further, the present invention first to second embodiment any one on the basis of, propose risk plan of the present invention
The slightly 3rd embodiment of optimization method, the present embodiment is the step S10 in first embodiment of the invention, in risk label model
Before the step of obtaining the corresponding first risk label of application information in partner's platform, comprising:
Step S60 obtains the system platform where risk label model, and determines the system platform and partner's platform
Between system docking scheme whether be open platform docking；
System platform can be platform with risk label model and partner's platform is in same rank.Obtain wind
System platform where dangerous label model, and determine whether the system docking scheme between system platform and partner is open flat
Platform docking, it should be noted that system docking scheme is divided into interface docking and open platform docking.And open platform docking is to close
Work side can obtain the risk label of corresponding applicant after application obtains bill by the bill access operation page, that is,
Operator without partner's platform logs on and verifies identity, it can be achieved that easily using the docking with system data.
When by judging that discovery system docking scheme is open platform docking, then partner's platform can be accessed directly and be looked into
See system platform data.When by judging that discovery system docking scheme is not open platform docking, then the every access one of partner
Subsystem platform data is required to log in primary.
Step S70 checks institute to partner's platform opening if the system docking scheme is open platform docking
State the permission of data in system platform.
When by judging that discovery system docking scheme is open platform docking, then partner's platform development can be checked
The permission of data in system platform.For example, as shown in fig. 6, preparing to check in the Flash client of partner's browser
When the data at the end SERVER (server), Flash code can be obscured, crack cost to improve decompiling, and shield multiple
The functions such as system, selection.It wherein, is using long link data communication, and data transmission between Flash client and the end SERVER
Using the method for symmetric cryptography, data protocol uses proprietary protocol, to guarantee the safety of data.
In the present embodiment, by determining whether the docking concept between system platform and partner's platform is open platform
Docking, and when being open platform docking, permission only is checked to the opening of partner's platform, to ensure system platform data
Safety.
Specifically, if the system docking scheme is open platform docking, institute is checked to partner's platform opening
The step of stating the permission of data in system platform, comprising:
Step S71 obtains the account in partner's platform if the system docking scheme is open platform docking
Information, and judge whether the account information matches with default account information；
Default account information can be preset account information in system platform.When by judging that system docking scheme is out
Be laid flat platform docking when, it is also necessary to obtain the account information in partner's platform, and need to judge account information whether with default account
Number information matches.It, then can be directly to partner's platform when by judging that discovery account information and default account information match
The open permission for checking system data.When by judging that discovery account information and default account information mismatch, then need pair
Account information is verified, to ensure the safety of data.
Step S72 checks institute to partner's platform opening if the account information and the matching of default account information
State the permission of data in system platform.
When by judging that discovery account information and default account information match, then the opening of partner's platform can be checked
The permission of data in system platform, that is, partner's platform can only check the data in system platform, without can be carried out duplication,
The functions such as selection.
In the present embodiment, by being opened to partner's platform when determining that account information and default account information match
Permission is checked, so that the data information in system platform be avoided to be leaked to other personnel.
Specifically, if the account information and the matching of default account information, to partner's platform, only opening is checked
In the system platform the step of permission of data, comprising:
Step S721, if the account information and the matching of default account information, it is corresponding pre- to obtain the account information
If time interval；
Prefixed time interval can be the time interval of user's preset in advance.When by judging discovery account information and presetting
When account information matches, then need to obtain the corresponding prefixed time interval of account information.It should be noted that working as partner's platform
Login system platform and after exiting, within a preset period of time, can be directly entered system platform and check, without logging on and testing
Demonstrate,prove identity.
Step S722 is checked in the system platform based on open to partner's platform in the prefixed time interval
The permission of data.
After getting prefixed time interval, the open permission for checking data in system platform of partner's platform can be determined
Time, and after prefixed time interval, needing to reacquire.For example, as shown in fig. 7, partner's server and system
Communication between open platform uses two-way HTTPS, and the validity period of access token (access token) can be 3600 seconds,
The validity period of sign ticket (getting the ticket endorsed) can be 3600, the second, it should be noted that access token and ticket are global
Uniquely, reacquisition when and partner must fail in closing on expired and use.It and include partner's platform in figure
With open system platform ,/predefined function (api)/opening authorization (oauth2)/access token (access_token)/；Access enables
Board (access_token)；/ predefined function (api)/opening authorization (oauth2)/api bill (ticket), is verified (sign)；
It verifies bill (sign ticket)；/ predefined function (api)/business (business)/xxx? (sign)=ABCD is verified,
In, sign is verified.
In the present embodiment, the time of permission is checked by determining according to prefixed time interval, to further protect
The safety of system platform data is hindered.
Further, the present invention first to 3rd embodiment any one on the basis of, propose risk plan of the present invention
The slightly fourth embodiment of optimization method, the present embodiment is the step S10 in first embodiment of the invention, in risk label model
The refinement for the step of obtaining the corresponding first risk label of application information in partner's platform, comprising:
Step S11 obtains the corresponding borrower's information of partner's platform application information；
When detecting that partner's platform has the platform where initiating application information to risk label model, need to obtain conjunction
The corresponding borrower's information of work side's platform application information.To determine the user for needing to borrow money.
Step S12 carries out reference inquiry according to borrower's information in risk label model, to obtain the first risk
Label.
After getting borrower's information, it is also necessary to carry out reference according to borrower's information in risk label model and look into
It askes, and risk label engine is allowed to generate the first risk label according to reference query result, it should be noted that risk label draws
It holds up with risk label model in the same platform interior.
In the present embodiment, by first obtaining borrower's information, and reference inquiry is carried out to borrower's information, is obtained with this
First risk label, to ensure the accuracy of the first risk label got.
Further, the step of the second risk label is determined in the risk label model according to the second trial information,
Include:
Step S21 obtains other corresponding main informations of second trial information；
After having carried out the first examination & approval, platform initiates two where detecting partner's platform to risk label model again
When examining information, need to obtain other corresponding main informations of second trial information again.
Step S22 carries out reference inquiry according to other described main informations in risk label model, to obtain the second wind
Dangerous label.
And reference inquiry is carried out according to other main informations in risk label model, and new risk label is allowed to draw again
The reference query result according to other main informations is held up to generate the second risk label.
In the present embodiment, by first obtaining other main informations, and reference inquiry is carried out to other main informations, with this
The second risk label is obtained, to ensure the accuracy of the second risk label got.
In addition, the embodiment of the present invention also proposes a kind of risk policy optimization device, the risk policy optimization referring to Fig. 4
Device includes:
Module is obtained, for obtaining the corresponding first risk mark of application information in partner's platform in risk label model
Label carry out the first examination & approval to the application information based on the first risk label；
Determining module, the second trial information carried out for obtaining partner's platform based on first examination & approval, and according to
The second trial information determines the second risk label in the risk label model；
Transfer module, for determining risk label interaction page based on the first risk label and the second risk label
Face, and the risk label interaction page is transferred to partner's platform；
Iteration module, for obtaining approval results of the partner's platform in the risk label interaction page, and
Model iteration is carried out to the risk label model based on the approval results, to complete the optimization of risk label strategy.
Optionally, the iteration module, is also used to:
Obtain the corresponding refund data of the application information；
Model iteration is carried out to the risk label model based on the refund data and the approval results.
Optionally, the risk policy optimizes device, further includes:
The system platform where risk label model is obtained, and determines between the system platform and partner's platform and is
Whether system docking concept is open platform docking；
It is open to partner's platform to check that the system is flat if the system docking scheme is open platform docking
The permission of data in platform.
Optionally, the risk policy optimizes device, further includes:
If the system docking scheme is open platform docking, the account information in partner's platform is obtained, and
Judge whether the account information matches with default account information；
It is open to partner's platform to check that the system is flat if the account information and the matching of default account information
The permission of data in platform.
Optionally, the risk policy optimizes device, further includes:
If the account information and the matching of default account information, obtain between the corresponding preset time of the account information
Every；
Based on the power for checking data in the system platform in the prefixed time interval to partner's platform opening
Limit.
Optionally, the acquisition module, is also used to:
Obtain the corresponding borrower's information of partner's platform application information；
Reference inquiry is carried out according to borrower's information in risk label model, to obtain the first risk label.
Optionally, the determining module, is also used to:
Obtain other corresponding main informations of second trial information；
Reference inquiry is carried out according to other described main informations in risk label model, to obtain the second risk label.
Wherein, the step of each Implement of Function Module of risk policy optimization device can refer to risk policy optimization of the present invention
Each embodiment of method, details are not described herein again.
The present invention also provides a kind of terminal, the terminal includes: memory, processor, communication bus and is stored in institute
State the risk policy optimization program on memory:
The communication bus is for realizing the connection communication between processor and memory；
The processor is for executing the risk policy optimization program, to realize above-mentioned each reality of risk policy optimization method
The step of applying.
The present invention also provides a kind of computer readable storage medium, the computer-readable recording medium storage has one
Perhaps more than one program the one or more programs can also be executed by one or more than one processor with
The step of embodiment each for realizing above-mentioned risk policy optimization method.
Computer readable storage medium specific embodiment of the present invention and each embodiment base of above-mentioned risk policy optimization method
This is identical, and details are not described herein.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone,
Computer, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all 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, is included within the scope of the present invention.
Claims (10)
1. a kind of risk policy optimization method, which is characterized in that the risk policy optimization method the following steps are included:
The corresponding first risk label of application information in partner's platform is obtained in risk label model, is based on first wind
Dangerous label carries out the first examination & approval to the application information；
The second trial information that partner's platform is initiated based on first examination & approval is obtained, and according to the second trial information described
The second risk label is determined in risk label model；
Risk label interaction page is determined based on the first risk label and the second risk label, and by the risk mark
Label interaction page is transferred to partner's platform；
Approval results of the partner's platform in the risk label interaction page are obtained, and are based on the approval results pair
The risk label model carries out model iteration, to complete the optimization of risk label strategy.
2. risk policy optimization method as described in claim 1, which is characterized in that described to be based on the approval results to described
Risk label model carries out the step of model iteration, comprising:
Obtain the corresponding refund data of the application information；
Model iteration is carried out to the risk label model based on the refund data and the approval results.
3. risk policy optimization method as described in claim 1, which is characterized in that described obtain in risk label model is closed
In work side's platform the step of application information corresponding first risk label before, comprising:
The system platform where risk label model is obtained, and determines the system pair between the system platform and partner's platform
Connect whether scheme is open platform docking；
If the system docking scheme is open platform docking, partner's platform opening is checked in the system platform
The permission of data.
4. risk policy optimization method as claimed in claim 3, which is characterized in that if the system docking scheme is out
It is laid flat platform docking, then to partner's platform open the step of checking the permission of data in the system platform, comprising:
If the system docking scheme is open platform docking, the account information in partner's platform is obtained, and judge
Whether the account information matches with default account information；
If the account information and the matching of default account information, check in the system platform partner's platform opening
The permission of data.
5. risk policy optimization method as claimed in claim 4, which is characterized in that if the account information and default account
Number information matches, then to partner's platform only open the step of checking the permission of data in the system platform, comprising:
If the account information and the matching of default account information, obtain the corresponding prefixed time interval of the account information；
Based on the permission for checking data in the system platform in the prefixed time interval to partner's platform opening.
6. risk policy optimization method as described in claim 1, which is characterized in that described obtain in risk label model is closed
In work side's platform the step of application information corresponding first risk label, comprising:
Obtain the corresponding borrower's information of partner's platform application information；
Reference inquiry is carried out according to borrower's information in risk label model, to obtain the first risk label.
7. risk policy optimization method as described in claim 1, which is characterized in that it is described according to the second trial information described
The step of the second risk label is determined in risk label model, comprising:
Obtain other corresponding main informations of second trial information；
Reference inquiry is carried out according to other described main informations in risk label model, to obtain the second risk label.
8. a kind of risk policy optimizes device, which is characterized in that the risk policy optimizes device and includes:
Module is obtained, for obtaining the corresponding first risk label of application information in partner's platform in risk label model,
The first examination & approval are carried out to the application information based on the first risk label；
Determining module, the second trial information initiated for obtaining partner's platform based on first examination & approval, and according to described
Second trial information determines the second risk label in the risk label model；
Transfer module, for determining risk label interaction page based on the first risk label and the second risk label,
And the risk label interaction page is transferred to partner's platform；
Iteration module for obtaining approval results of the partner's platform in the risk label interaction page, and is based on
The approval results carry out model iteration to the risk label model, to complete the optimization of risk label strategy.
9. a kind of risk policy optimizes equipment, which is characterized in that the risk policy optimization equipment includes: memory, processor
And it is stored in the risk policy optimization program that can be run on the memory and on the processor, the risk policy optimization
The step of risk policy optimization method as described in any one of claims 1 to 7 is realized when program is executed by the processor.
10. a kind of computer readable storage medium, which is characterized in that store risky plan on the computer readable storage medium
Slightly optimize program, the risk policy optimization program is realized as described in any one of claims 1 to 7 when being executed by processor
The step of risk policy optimization method.
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