CN109146670A - It provides a loan anti-rogue processes method, apparatus and readable storage medium storing program for executing - Google Patents
It provides a loan anti-rogue processes method, apparatus and readable storage medium storing program for executing Download PDFInfo
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- CN109146670A CN109146670A CN201810985867.5A CN201810985867A CN109146670A CN 109146670 A CN109146670 A CN 109146670A CN 201810985867 A CN201810985867 A CN 201810985867A CN 109146670 A CN109146670 A CN 109146670A
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- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
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- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/38—Payment protocols; Details thereof
- G06Q20/40—Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
- G06Q20/401—Transaction verification
- G06Q20/4016—Transaction verification involving fraud or risk level assessment in transaction processing
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Abstract
The invention discloses a kind of anti-rogue processes methods of loan, comprising the following steps: when there are loan requests, obtains various dimensions fraud relevant to the loan requests and determines data；The fraud is determined into data input rule engine, to carry out risk rating to the loan requests, exports risk class；Judge whether the risk class is within the scope of specified risk class；If so, carrying out fraud verification to creditor using one of group synkaryon skill section or a variety of core skill sections, output core body is as a result, and based on the core body as a result, determining decision of making loans；If it is not, being then based on the risk class, decision of making loans is determined.The invention also discloses a kind of anti-rogue processes device of loan and computer readable storage mediums.Present invention reduces credit risks, improve the treatment effeciency of loan transaction, the user experience is improved.
Description
Technical field
The present invention relates to financial risks technical field more particularly to a kind of anti-rogue processes method, apparatus of loan and calculating
Machine readable storage medium storing program for executing.
Background technique
With the continuous development of internet finance, for the ultimate attainment user for solving user's quick obtaining financial credit on grid line
Experience needs balancing user experience to manage with risk of fraud, and the loan experience of user can neither be aggravated to degrade rate of fraud
Process can not be taken precautions against for user experience using quick core skill section.
Financial credit usually requires to verify user, to carry out risk of fraud control.Existing loan business verifies mould
Formula be usually using single core skill section to user loan verifies, however each seed nucleus skill section be not it is omnipotent,
All have some limitations, and there is very big drawback in the loan transaction of Internet bank in this mode: first is that wireless
Lower resource does not accomplish to verify under line；Second is that verifying low efficiency, it is unable to satisfy the quick loan transaction demand of user；Third is that if
Using high risk, the mode of high price is avoided risk, then is unable to reach the target of general favour finance.
Summary of the invention
The main purpose of the present invention is to provide a kind of anti-rogue processes method, apparatus of loan and computer-readable storage mediums
Matter, it is intended to solve the technical issues of existing loan business carries out anti-risk of fraud control existing various drawbacks.
To achieve the above object, the present invention provides a kind of anti-rogue processes method of loan, the anti-rogue processes side of loan
Method the following steps are included:
When there are loan requests, obtains various dimensions fraud relevant to the loan requests and determine data；
The fraud is determined into data input rule engine, to carry out risk rating to the loan requests, exports risk
Grade；
Judge whether the risk class is within the scope of specified risk class；
If so, fraud verification is carried out to creditor using one of group synkaryon skill section or a variety of core skill sections, it is defeated
Core body is as a result, and based on the core body as a result, determining decision of making loans out；
If it is not, being then based on the risk class, decision of making loans is determined.
Optionally, described that fraud core is carried out to creditor using one of group synkaryon skill section or a variety of core skill sections
It looks into, output core body result includes:
Fraud verification is carried out to creditor using the corresponding core skill section of risk class described in group synkaryon skill Duan Zhongyu, it is defeated
Core body result out；Or
S1: fraud verification is carried out to creditor using one of group synkaryon skill section core skill section；
S2: judge whether this core body result meets the condition that fraud is verified that continues；
S3: fraud verification is continued to creditor and executes S2 if satisfied, then adjusting core skill section；
S4: if not satisfied, then based on core body each time as a result, output most end-nucleus body result.
Optionally, the anti-rogue processes method of loan further include:
Before the anti-rogue processes that provide a loan, third party's data of the data and acquisition that are provided according to creditor are raw
At for carrying out the problem of fraud is verified library to creditor, third party's data include: people's row data of creditor, public security number
According to, academic data, social data.
Optionally, the anti-rogue processes method of loan further include:
When carrying out fraud verification to creditor, select permeability carries out from described problem library for verifying people to creditor
It puts question to, and collects the answer of creditor；
When entering next round question and answer, according to the last round of answer of creditor, dynamic generation next round problem, and will be newborn
At the problem of be added described problem library in；
It is answered according to each round of creditor, Comprehensive Evaluation creditor whether there is fraud.
Optionally, the fraud determines that data include: the historical trading behavioral data of creditor, set used in creditor
Standby data, creditor's social data, history core body result data.
Optionally, described group of synkaryon skill section includes: phone core body, long-distance video core body, brush face core body.
Optionally, the risk class includes: devoid of risk grade, low risk level, risk grade, medium or high risk grade
And high-risk grade；The specified risk class range includes: low risk level, risk grade and medium or high risk grade.
Optionally, described to be based on the risk class, determine that decision of making loans includes:
When the risk class is devoid of risk grade, determines and make loans decision to agree to make loans；
When the risk class is for high-risk grade, determining decision of making loans is made loans for refusal.
Further, to achieve the above object, the present invention also provides a kind of anti-rogue processes device of loan, the loan is anti-
Rogue processes device includes memory, processor and is stored in the loan that can be run on the memory and on the processor
The anti-rogue processes program of money, the loan anti-rogue processes program are realized as described in any of the above-described when being executed by the processor
Loan anti-rogue processes method the step of.
Further, to achieve the above object, the present invention also provides a kind of computer readable storage medium, the computers
The anti-rogue processes program of loan is stored on readable storage medium storing program for executing, the loan anti-rogue processes program is real when being executed by processor
The step of existing loan as described in any one of the above embodiments anti-rogue processes method.
The present invention during provide a loan anti-rogue processes, first pass through various dimensions fraud determine data to loan requests into
Row risk rating, risk class is low directly to make loans, and risk class is high then can directly to be refused, to promote verification effect
Rate.And the loan requests placed in the middle for risk class, then it is verified using combined core skill section, and then realize and commented with risk
The combination prevention and control strategy of grade, while the disadvantage for preventing single means to be easy to be broken verify the risk class with specific reference to user
Difference and coped with using corresponding core skill section, so that devoid of risk user be made to be quickly obtained loan, and for medium to low-risk
User can realize the same day to account.The present invention improves loan transaction treatment effeciency, makes under the premise of guaranteeing that risk level is controllable
The loan experience of user is improved.
Detailed description of the invention
Fig. 1 is the flow diagram of anti-one embodiment of rogue processes method of present invention loan；
Fig. 2 is that the structure for the device hardware running environment that the anti-rogue processes Installation practice scheme of present invention loan is related to is shown
It is intended 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 embodiment
It should be appreciated that described herein, specific examples are only used to explain the present invention, is not intended to limit the present invention.
Referring to Fig.1, Fig. 1 is the flow diagram of anti-one embodiment of rogue processes method of present invention loan.In the present embodiment,
The anti-rogue processes method of the loan the following steps are included:
Step S10 obtains various dimensions fraud relevant to the loan requests and determines data when there are loan requests；
In the present embodiment, when the loan requests initiated on there are creditor's line, first obtain related to this loan requests
Various dimensions fraud determine data, for this loan requests carry out risk rating.
Fraud determines that data can specifically include data relevant to this loan, such as the amount of money and loan of this loan
Essential information of people, such as age, history loaning bill number etc., for example be the social data that can embody creditor's corelation behaviour,
Such as the trace that user is left using specific products on the internet, it can get user behavior data by these traces.
In addition, fraud determines that data can also include history core body data.Since history core body data can reflect to a certain extent
Therefore the risk level of creditor can improve the treatment effeciency of risk rating to a certain extent.
Optionally, fraud determines that data include following multiple data sources:
(1) the historical trading behavioral data of creditor, refers to the historical trading data that can embody creditor's trading activity；
(2) device data used in creditor, such as user equipment ID, equipment whether there is by the risk etc. of steal-number；
(3) creditor's social data, refers to the social data that can embody creditor's corelation behaviour, for example, user account whether
For on-hook account, black production, intermediary etc.；
(4) history core body result data carries out verifying generated data when referring to creditor's history loan.
In the present embodiment, fraud determine data be storable in local and carry out real-time update, can also by backstage from its
It is obtained on his database or server.It should be further noted that the source dimension of fraud judgement data includes but is not limited to
Above-mentioned dimension, for example can further include the dimensions such as the education degree of creditor, length of service.
The fraud is determined data input rule engine by step S20, to carry out risk rating to the loan requests,
Export risk class；
In the present embodiment, after obtaining fraud and determining data, fraud is determined that data input rule engine is calculated by classifying
Method carries out integrated decision-making, and then are carried out by risk rating, and exports the corresponding risk of this loan requests for this loan requests etc.
Grade.
During the integrated decision-making of regulation engine, history core body data occupy important influence to integrated decision-making.When logical
When crossing regulation engine to epicycle loan progress decision, if lacking fraud determines data (such as loan for the first time), can directly it comment
It is set to higher risk class, and then carries out creditor's identification check.After having verified, then this is verified into result and is updated to the loan
The corresponding fraud of money people determines in data, and then the debt-credit next time that can be used for creditor carries out risk of fraud judgement.
In the present embodiment, risk rating rule used in regulation engine can be carried out dynamic adjustment by administrative staff to answer
Rate of fraud, is finally reduced in a controllable range by the variation for fighting External Funtions behavior.
Step S30, judges whether the risk class is within the scope of specified risk class；
The present embodiment is unlimited for the setting of risk class, is preferably arranged to five class hierarchies:
(1) devoid of risk grade, the loan requests in the class hierarchy can directly make loans
(2) low risk level, the loan requests in the class hierarchy need further progress identification check, to reduce possibility
Existing loan fraud risk；
(3) risk grade, the loan requests in the class hierarchy need further progress identification check, to reduce possibility
Existing loan fraud risk；
(4) medium or high risk grade, the loan requests in the class hierarchy need further progress identification check, can with reduction
Loan fraud risk existing for energy；
(5) high-risk grade, the loan requests in the class hierarchy can directly be refused.
Step S40, if so, being cheated using one of group synkaryon skill section or a variety of core skill sections creditor
It verifies, output core body is as a result, and based on the core body as a result, determining decision of making loans；
In the present embodiment, if the risk class of regulation engine output is within the scope of the risk class specified, for example belong to
In low risk level as described above, risk grade and medium or high risk grade, then further progress identification check is needed, with drop
Low loan fraud risk that may be present.
The present embodiment specifically carries out fraud core to creditor using one of group synkaryon skill section or a variety of core skill sections
It looks into.
Optionally, group synkaryon skill section includes:
(1) phone core body, in such a way that auditor carries out telephone questions question and answer with creditor, verify whether my wish
Loan, whether there is or not frauds；
(2) long-distance video core body remotely hand in face of plane video by auditor and creditor using video call technology
Whether in person the case where flowing, by observation user behavior and answering a question provide a loan to verify wish, and whether there is or not frauds；
(3) brush face core body, creditor carry out recording facial video client is self-service, then upload service end, by with
Public security photo compares, to verify, whether my application is provided a loan.
Certainly, subsequent to increase newly with the continuous development and update of technological means in addition to above-mentioned core skill section
Core skill section or the existing core skill section of replacement.
It should be noted that auditor can provide manual examination and verification opinion, but finally be entirely during above-mentioned core body
Core body decision is carried out by machine, avoids risk problem brought by manual operation.
Output core body after having executed fraud and having verified as a result, and based on the core body as a result, determination is made loans decision, for example agree to
It makes loans or refuses to make loans.In addition, artificial adjustable decision of making loans, for example according to operation demand, can first make loans, it is subsequent electric again
It talks about the return visit of core body or long-distance video core body is paid a return visit.
Step S50 determines decision of making loans if it is not, being then based on the risk class.
In the present embodiment, if the risk class of regulation engine output is not within the scope of specified risk class, such as
Above-mentioned devoid of risk grade and high-risk grade are then in reason without carrying out creditor's core under such situation, and only need to be according to epicycle
The corresponding risk class of loan requests can determine decision of making loans, for example agree to make loans or refuse to make loans.
In the present invention, all verified if same debt-credit user is repeatedly provided a loan and provided a loan every time, and in creditor
It verifies and cheats by fraud and determine in the unchanged situation of data, then the risk fraud grading of creditor will gradually be dropped
Low, subsequent loan user continues that relatively simple verification strategy will be taken when borrowing money, even without being verified, to be promoted
User experience.And if the verification conclusion of creditor is that there are fraud, the subsequent verification hands for gradually aggravating loan user
Section, and after the fraud evaluation of subsequent risk is serious to a certain extent, it will directly refuse loan application, or even lock borrowing for creditor
Borrow account.
The present invention is graded using risk of fraud and manages strategy with the combination for organizing synkaryon skill section, and then user can not guess
When used specific core skill section, have core skill section when verifying out, so that the fraud cost of debtor is increased,
Even if debtor is soundd out by way of shock, but is also suitable only for single user, can not be attacked on a large scale,
By this combined control strategy, to reduce loan fraud rate.
It is further alternative, provide a loan in anti-one embodiment of rogue processes method in the present invention, using group synkaryon skill section into
The implementation that row fraud is verified specifically includes:
(1) one seed nucleus skill section
This fraud pattern verification specifically obtain regulation engine output risk class after, using a group synkaryon skill Duan Zhongyu
The corresponding core skill section of the risk class carries out fraud verification to creditor, then exports core body result.
For example, if the risk class of regulation engine output is low risk level, using phone core skill section to creditor
Carry out fraud verification；And if the risk class of regulation engine output is risk grade, uses brush face core skill section to loan
People carries out fraud verification；And if the risk class of regulation engine output is medium or high risk grade, uses long-distance video core skill
Section carries out fraud verification to creditor.
In the method, although core skill section is single, which is specifically the risk etc. exported with regulation engine
Grade is corresponding, since the specific judgment rule of regulation engine can not know, thus not can determine that the corresponding wind of this loan requests
Dangerous grade, and then can not know the specific core skill section that this core body uses.
(2) a variety of core skill sections
S1: fraud verification is carried out to creditor using one of group synkaryon skill section core skill section；
S2: judge whether this core body result meets the condition that fraud is verified that continues；
S3: fraud verification is continued to creditor and executes S2 if satisfied, then adjusting core skill section；
S4: if not satisfied, then based on core body each time as a result, output most end-nucleus body result.
This fraud pattern verification carries out first round core body first, can be the seed nucleus skill specified in group synkaryon skill section
Section, is also possible to group corresponding core skill section of synkaryon skill Duan Zhongyu risk class, or can also be in group synkaryon skill section
Any seed nucleus skill section.
It completes to judge whether this core body result meets the condition for continuing fraud and verifying behind first round core, such as
Fruit meets, then adjusts core skill section and continue fraud verification, and if conditions are not met, then based on core body each time as a result, defeated
Most end-nucleus body result out.
The method is unlimited for the setting for continuing the condition that fraud is verified.For example, it may be being set based on number is verified
The condition that fraud is verified that continues is set, if suites of measure core body must be verified twice, if not up to specified verification
Number then continues to verify next time.
The condition that fraud is verified is continued based on verification result setting in another example can be, for example, this brush face core body
The risk of borrower is still very high as the result is shown, then to avoid judging by accident, continues the core body of higher level next time, such as face
Core (long-distance video core body), if the risk of face core borrower as the result is shown can receive, the result based on brush face core body with
And face core core body as a result, output most end-nucleus body result.
For another example can be the condition for continuing fraud verification based on verification result and verification number setting.For example, this
The risk of secondary brush face core body borrower as the result is shown is still very high, then to avoid judging by accident, continues higher level next time
Core body, such as face core (long-distance video core body), if the risk of face core borrower as the result is shown is still very high and can not receive,
It needs to adjust core skill section again and continues next round fraud verification, when the number for time and again carrying out fraud verification reaches specified time
It when (such as twice) number, then exits, and based on core body each time as a result, output most end-nucleus body result.
Further, in anti-one embodiment of rogue processes method of present invention loan, question and answer core body is being carried out to creditor
When, for the fraud difficulty for increasing creditor, in the present embodiment, anti-rogue processes method of providing a loan further include:
Before the anti-rogue processes that provide a loan, third party's data of the data and acquisition that are provided according to creditor are raw
At for carrying out the problem of fraud is verified library to creditor.
In the present embodiment, the scene of generation problem can be expanded by introducing multiple data sources, increased the quantity of problem and mentioned
The covering surface of the problem of liter, and then the fraud difficulty of creditor can be increased.
In the present embodiment, the data that creditor provides can be personal essential information and other numbers relevant to core body
According to.Third party's data include:
(1) people's row data refer to that creditor remembers in the data of the People's Bank, such as in the loan documentation of other mechanisms, refund
Record, personal reference situation etc.；
(2) public security data refer to the data of creditor in public security system, such as personal head portrait, criminal information etc.；
(3) academic data, refer to the academic situation of creditor, can obtain from related academic issuer；
(4) social data, refer to embody creditor's corelation behaviour social data, such as user use on the internet it is specific
The trace that product leaves can get user behavior data by these traces.
It need to further illustrate, third party's data include but is not limited to above-mentioned dimension, such as can also include creditor
Interpersonal relationships data, social security data etc., such as relatives, the personal reference situation of friend or loan profile, the work of creditor
Industry and length of service etc..
Further, based on the above embodiment, in anti-one embodiment of rogue processes method of present invention loan, the loan
Anti- rogue processes method further include:
When carrying out fraud verification to creditor, select permeability carries out from described problem library for verifying people to creditor
It puts question to, and collects the answer of creditor；
When entering next round question and answer, according to the last round of answer of creditor, dynamic generation next round problem, and will be newborn
At the problem of be added described problem library in；
It is answered according to each round of creditor, Comprehensive Evaluation creditor whether there is fraud.
In the present embodiment, when carrying out fraud verification to creditor, such as phone core body or long-distance video core body, to realize
To verifying under the line of creditor's risk of fraud, therefore, third party's data source is introduced to generate problem base, and according to creditor's
Last round of answer, dynamic generation next round problem, to avoid problem from fixing and lead to existing potential risk, such as creditor
Fraud is ganged up with auditor.It verifies conclusion to need to answer progress Comprehensive Evaluation according to each round of creditor, therefore, it is determined that loan
People whether there is fraud.
The present invention also provides a kind of anti-rogue processes devices of loan.
Referring to Fig. 2, Fig. 2 is the device hardware running environment that the anti-rogue processes Installation practice scheme of present invention loan is related to
Structural schematic diagram.
As shown in Fig. 2, anti-rogue processes device of providing a loan may include: processor 1001, such as CPU, communication bus 1002,
User interface 1003, network interface 1004, memory 1005.Wherein, communication bus 1002 is for realizing between these components
Connection communication.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 standard
Wireline interface, 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
The storage equipment of processor 1001.It should be noted that processor 1001 is mounted on using embedded chip mode, loan is counter to be taken advantage of
It cheats in processing unit.
It will be understood by those skilled in the art that the hardware configuration of the anti-rogue processes device of loan shown in Figure 2 not structure
Provide a loan in pairs the restriction of anti-rogue processes device, may include than illustrating more or fewer components, or the certain components of combination,
Or different component layout.
As shown in Fig. 2, as may include operating system, net in a kind of memory 1005 of computer readable storage medium
Network communication module, Subscriber Interface Module SIM and the anti-rogue processes program of loan.Wherein, operating system is to manage and control loan instead
The program of rogue processes device and software resource supports network communication module, Subscriber Interface Module SIM, the anti-rogue processes program of loan
And the operation of other programs or software；Network communication module is for managing and controlling network interface 1004；Subscriber Interface Module SIM
For managing and controlling user interface 1003.
In the anti-rogue processes device hardware configuration of loan shown in Fig. 2, network interface 1004 is mainly used for connection system
From the background, data communication is carried out with system background；User interface 1003 be mainly used for connect client (user terminal), with client into
Row data communication；Anti- rogue processes device of providing a loan calls in memory 1005 loan that stores instead at fraud by processor 1001
Program is managed, and executes following operation:
When there are loan requests, obtains various dimensions fraud relevant to the loan requests and determine data；
The fraud is determined into data input rule engine, to carry out risk rating to the loan requests, exports risk
Grade；
Judge whether the risk class is within the scope of specified risk class；
If so, fraud verification is carried out to creditor using one of group synkaryon skill section or a variety of core skill sections, it is defeated
Core body is as a result, and based on the core body as a result, determining decision of making loans out；
If it is not, being then based on the risk class, decision of making loans is determined.
Further, anti-rogue processes device of providing a loan calls the loan stored in memory 1005 anti-by processor 1001
Rogue processes program also executes following operation:
Fraud verification is carried out to creditor using the corresponding core skill section of risk class described in group synkaryon skill Duan Zhongyu, it is defeated
Core body result out；Or
S1: fraud verification is carried out to creditor using one of group synkaryon skill section core skill section；
S2: judge whether this core body result meets the condition that fraud is verified that continues；
S3: fraud verification is continued to creditor and executes S2 if satisfied, then adjusting core skill section；
S4: if not satisfied, then based on core body each time as a result, output most end-nucleus body result.
Further, anti-rogue processes device of providing a loan calls the loan stored in memory 1005 anti-by processor 1001
Rogue processes program also executes following operation:
Before the anti-rogue processes that provide a loan, third party's data of the data and acquisition that are provided according to creditor are raw
At for carrying out the problem of fraud is verified library to creditor, third party's data include: people's row data of creditor, public security number
According to, academic data, social data.
Further, anti-rogue processes device of providing a loan calls the loan stored in memory 1005 anti-by processor 1001
Rogue processes program also executes following operation:
When carrying out fraud verification to creditor, select permeability carries out from described problem library for verifying people to creditor
It puts question to, and collects the answer of creditor；
When entering next round question and answer, according to the last round of answer of creditor, dynamic generation next round problem, and will be newborn
At the problem of be added described problem library in；
It is answered according to each round of creditor, Comprehensive Evaluation creditor whether there is fraud.
Further, anti-rogue processes device of providing a loan calls the loan stored in memory 1005 anti-by processor 1001
Rogue processes program also executes following operation:
When the risk class is devoid of risk grade, determines and make loans decision to agree to make loans；
When the risk class is for high-risk grade, determining decision of making loans is made loans for refusal.
The present invention also provides a kind of computer readable storage mediums.
The anti-rogue processes program of loan, the anti-rogue processes of loan are stored on computer readable storage medium of the present invention
It realizes when program is executed by processor such as the step of any of the above-described loan as described in the examples anti-rogue processes method.
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 a storage medium
In (such as ROM/RAM), including some instructions are used so that a terminal (can be mobile phone, computer, server or network are set
It is standby etc.) execute method described in each embodiment of the present invention.
The embodiment of the present invention is described with above attached drawing, but the invention is not limited to above-mentioned specific
Embodiment, the above mentioned embodiment is only schematical, rather than restrictive, those skilled in the art
Under the inspiration of the present invention, without breaking away from the scope protected by the purposes and claims of the present invention, it can also make very much
Form, it is all using equivalent structure or equivalent flow shift made by description of the invention and accompanying drawing content, directly or indirectly
Other related technical areas are used in, all of these belong to the protection of the present invention.
Claims (10)
1. a kind of anti-rogue processes method of loan, which is characterized in that the anti-rogue processes method of loan the following steps are included:
When there are loan requests, obtains various dimensions fraud relevant to the loan requests and determine data；
The fraud is determined into data input rule engine, to carry out risk rating to the loan requests, exports risk class；
Judge whether the risk class is within the scope of specified risk class；
If so, carrying out fraud verification to creditor using one of group synkaryon skill section or a variety of core skill sections, core is exported
Body is as a result, and based on the core body as a result, determining decision of making loans；
If it is not, being then based on the risk class, decision of making loans is determined.
2. anti-rogue processes method of providing a loan as described in claim 1, which is characterized in that described using in group synkaryon skill section
One or more core skill sections carry out fraud verification to creditor, and output core body result includes:
Fraud verification is carried out to creditor using the corresponding core skill section of risk class described in group synkaryon skill Duan Zhongyu, exports core
Body result；Or
S1: fraud verification is carried out to creditor using one of group synkaryon skill section core skill section；
S2: judge whether this core body result meets the condition that fraud is verified that continues；
S3: fraud verification is continued to creditor and executes S2 if satisfied, then adjusting core skill section；
S4: if not satisfied, then based on core body each time as a result, output most end-nucleus body result.
3. anti-rogue processes method of providing a loan as described in claim 1, which is characterized in that the anti-rogue processes method of loan is also
Include:
Before the anti-rogue processes that provide a loan, third party's data of the data and acquisition that are provided according to creditor are generated and are used
In carrying out the problem of fraud is verified library to creditor, third party's data include: people's row data of creditor, public security data,
Academic data, social data.
4. anti-rogue processes method of providing a loan as claimed in claim 3, which is characterized in that the anti-rogue processes method of loan is also
Include:
When carrying out fraud verification to creditor, select permeability mentions creditor for verifying people from described problem library
It asks, and collects the answer of creditor；
When entering next round question and answer, according to the last round of answer of creditor, dynamic generation next round problem, and will be newly-generated
Problem is added in described problem library；
It is answered according to each round of creditor, Comprehensive Evaluation creditor whether there is fraud.
5. anti-rogue processes method of providing a loan as described in claim 1, which is characterized in that the fraud determines that data include: to borrow
Device data, creditor's social data, history core body number of results used in the historical trading behavioral data of money people, creditor
According to.
6. anti-rogue processes method of providing a loan as described in claim 1, which is characterized in that described group of synkaryon skill section includes: electricity
Talk about core body, long-distance video core body, brush face core body.
7. such as the anti-rogue processes method of loan of any of claims 1-6, which is characterized in that the risk class packet
It includes: devoid of risk grade, low risk level, risk grade, medium or high risk grade and high-risk grade；The specified risk etc.
Grade range includes: low risk level, risk grade and medium or high risk grade.
8. anti-rogue processes method of providing a loan as claimed in claim 7, which is characterized in that it is described to be based on the risk class, really
Surely decision of making loans includes:
When the risk class is devoid of risk grade, determines and make loans decision to agree to make loans；
When the risk class is for high-risk grade, determining decision of making loans is made loans for refusal.
9. a kind of anti-rogue processes device of loan, which is characterized in that the anti-rogue processes device of loan includes memory, processing
Device and it is stored in the anti-rogue processes program of the loan that can be run on the memory and on the processor, the loan is anti-
It is realized when rogue processes program is executed by the processor such as the anti-rogue processes side of loan of any of claims 1-8
The step of method.
10. a kind of computer readable storage medium, which is characterized in that it is anti-to be stored with loan on the computer readable storage medium
Rogue processes program, the loan anti-rogue processes program are realized when being executed by processor such as any one of claim 1-8 institute
The step of loan stated anti-rogue processes method.
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| CN201810985867.5A CN109146670A (en) | 2018-08-27 | 2018-08-27 | It provides a loan anti-rogue processes method, apparatus and readable storage medium storing program for executing |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102035649A (en) * | 2009-09-29 | 2011-04-27 | 国际商业机器公司 | Authentication method and device |
| US20140012716A1 (en) * | 2012-07-03 | 2014-01-09 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for detecting tax refund fraud |
| CN105005901A (en) * | 2015-07-09 | 2015-10-28 | 厦门快商通信息技术有限公司 | Financial field oriented transaction fraud detection system and method |
| CN106447333A (en) * | 2016-11-29 | 2017-02-22 | 中国银联股份有限公司 | Fraudulent trading detection method and server |
| CN106575401A (en) * | 2014-07-31 | 2017-04-19 | 诺克诺克实验公司 | System and method for performing authentication using data analytics |
-
2018
- 2018-08-27 CN CN201810985867.5A patent/CN109146670A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102035649A (en) * | 2009-09-29 | 2011-04-27 | 国际商业机器公司 | Authentication method and device |
| US20140012716A1 (en) * | 2012-07-03 | 2014-01-09 | Lexisnexis Risk Solutions Fl Inc. | Systems and methods for detecting tax refund fraud |
| CN106575401A (en) * | 2014-07-31 | 2017-04-19 | 诺克诺克实验公司 | System and method for performing authentication using data analytics |
| CN105005901A (en) * | 2015-07-09 | 2015-10-28 | 厦门快商通信息技术有限公司 | Financial field oriented transaction fraud detection system and method |
| CN106447333A (en) * | 2016-11-29 | 2017-02-22 | 中国银联股份有限公司 | Fraudulent trading detection method and server |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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