CN110210702A - Big data intelligent excavating analysis method, system, terminal device based on block chain - Google Patents
Big data intelligent excavating analysis method, system, terminal device based on block chain Download PDFInfo
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- CN110210702A CN110210702A CN201910333417.2A CN201910333417A CN110210702A CN 110210702 A CN110210702 A CN 110210702A CN 201910333417 A CN201910333417 A CN 201910333417A CN 110210702 A CN110210702 A CN 110210702A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
- G06Q40/03—Credit; Loans; Processing thereof
Abstract
The invention proposes a kind of big data intelligent excavating analysis method, system, terminal device and computer readable storage medium based on block chain, the credit applications request that the method is issued by reception Debit User；Request inquiry Debit User in the data of other each platforms according to the credit applications, other described each platforms are the platform being in same block chain pond with lending platforms；The preset condition whether Debit User triggers violation operation is analyzed according to the data of the Debit User inquired on other each platforms；When triggering the preset condition of violation operation, the corresponding operation of discipline rating is executed according to the discipline rating of violation operation.Credit risk is prevented to lending platforms by the analysis of the credit data to Debit User, improves risk prevention power.
Description
Technical field
The present invention relates to technical field of electronic equipment more particularly to a kind of big data intelligent excavating analyses based on block chain
Method, system, terminal device and computer readable storage medium.
Background technique
With the development of Internet era, network credit is gradually in fashion.Compared with traditional bank credit, network letter
Loan has many advantages, such as formality convenience, information transparency, allocation of risks, is suitable for the granting of petty load, for supporting small micro- finance
Group has positive effect.In addition, loan can absorb civil incative money by way of specification on the line of information relative transparent
Gold has certain facilitation to the civil financing behavior of specification.Currently, domestic some network lending platforms data to run well
It has been shown that, in the past few years network loan transaction rapid development, provides preferable financing services for little Wei enterprise, self-employed entrepreneur, has
Effect solves the problems, such as financing difficulties.But network credit, due to being in open internet, transaction transmission is being given in internet
While offering convenience, certain hidden danger also is left for credit safety.Since network credit is all directly to carry out on the internet,
Judge can not be made to the personal information of Debit User Face to face, this is just needed by internet big data, from internet
Debit User data are extracted, user data is analyzed, is provided safeguard for credit safety.
Summary of the invention
The big data intelligent excavating analysis method that the main purpose of the present invention is to provide a kind of based on block chain, system,
Terminal device and computer readable storage medium, it is intended to solve the problems, such as the credit safety in network credit process.
To achieve the above object, a kind of big data intelligent excavating analysis method based on block chain provided by the invention, institute
The method of stating includes the following steps:
Step S10 receives the credit applications request that Debit User issues；
Step S20, according to the credit applications request inquiry Debit User other each platforms data, it is described other
Each platform is the platform being in same block chain pond with lending platforms；
Step S30 analyzes whether Debit User touches according to the data of the Debit User inquired on other each platforms
Send out the preset condition of violation operation；
Step S40 executes discipline rating according to the discipline rating of violation operation when triggering the preset condition of violation operation
Corresponding operation.
Preferably, the step S20 includes:
Step S21 requests inquiry Debit User in the registration information of lending platforms according to the credit applications；
Step S21, according to Debit User lending platforms registration information inquiry Debit User personal information, and according to
Data of the personal information inquiry Debit User of Debit User in other each platforms.
Preferably, according to the seriousness of Debit User data violation, violation operation is divided into grade 1 violation operation and second level
Violation operation；
Described in the step S30 trigger violation operation preset condition the step of include:
Step S31 detects Debit User in other platforms and whether is marked as black list user；
Step S32, if it is, the preset condition of triggering grade 1 violation operation；
The step S40 includes:
Step S41 retracts the credit applications request of Debit User when triggering the preset condition of grade 1 violation operation.
Preferably, the step of preset condition of triggering violation operation described in the step S30 includes:
Step S33 detects Debit User in other platforms and whether data exception occurs；
Step S34, if it is, the preset condition of triggering grade 2 violation operation；
The step S40 includes:
Step S42, when triggering the preset condition of grade 2 violation operation, the prompt information for issuing supplement testimonial material is extremely believed
Borrow user
After the step S42 further include:
Veritify whether the testimonial material that Debit User is submitted meets the requirements；
When the testimonial material that Debit User is submitted is met the requirements, requested by the credit applications of Debit User.
Preferably, before the step S30 further include:
Step S01, according to the data of the Debit User inquired on other platforms according to the first default computation rule meter
Calculate the credit worthiness of Debit User；
Step S02 is calculated Debit User according to the second default computation rule according to the credit worthiness of Debit User and is believing
Borrow the line of credit of platform；
Step S03, the credit applications for inquiring Debit User request corresponding application amount, and compare credit applications request pair
The line of credit of the application amount answered and Debit User in lending platforms；
Step S04, if the corresponding application amount of credit applications enters step 30 within the scope of line of credit.
Preferably, the method also includes:
Step S50 monitors Debit User and credit provider in the behavioral data of lending platforms；
Step S60 is monitoring that it is abnormal that the behavioral data of Debit User or credit provider on lending platforms occurs
When, to third monitoring side signal an alert, interfered in time convenient for third monitoring side.
Preferably, the Debit User includes: registration of the Debit User in other platforms in the data of other each platforms
Information, Debit User are in the behavioral datas of other platforms, Debit User in the label datas of other platforms, Debit User at other
The transaction data of platform, Debit User other platforms debt-credit data.
In addition, to achieve the above object, the present invention also proposes a kind of big data intelligent excavating analysis system based on block chain
System, the system comprises:
Receiving module, the credit applications request issued for receiving Debit User；
Enquiry module, for requesting data of the inquiry Debit User in other each platforms, institute according to the credit applications
Stating other each platforms is the platform being in same block chain pond with lending platforms；
Judgment module, for being according to the data analysis Debit User of the Debit User inquired on other each platforms
The preset condition of no triggering violation operation；
Execution module, for executing and disobeying according to the discipline rating of violation operation when triggering the preset condition of violation operation
Advise the corresponding predetermined registration operation of grade.
In addition, to achieve the above object, the present invention also proposes a kind of terminal device, including memory, processor and deposits
The computer program that can be run in the memory and on the processor is stored up, the processor executes the computer journey
The step of as above any one the method is realized when sequence.
In addition, to achieve the above object, the present invention also proposes a kind of computer readable storage medium, described computer-readable
Storage medium is stored with computer program, and the method any one of as above is realized when the computer program is executed by processor
Step.
The credit issued based on the big data intelligent excavating analysis method of block chain by receiving Debit User of the invention
Application request；Request inquiry Debit User in the data of other each platforms according to the credit applications, described other are each flat
Platform is the platform being in same block chain pond with lending platforms；According to the Debit User inquired on other each platforms
Data analysis Debit User whether trigger the preset condition of violation operation；When triggering the preset condition of violation operation, according to
The discipline rating of violation operation executes the corresponding operation of discipline rating.By the analysis of the credit data to Debit User to credit
Platform prevents credit risk, improves risk prevention power.
Detailed description of the invention
Attached drawing is as a part of the invention, and for providing further understanding of the invention, of the invention is schematic
Examples and descriptions thereof are used to explain the present invention, but does not constitute an undue limitation on the present invention.Obviously, the accompanying drawings in the following description
Only some embodiments to those skilled in the art without creative efforts, can be with
Other accompanying drawings can also be obtained according to these attached drawings.In the accompanying drawings:
Fig. 1 is that the present invention is based on the flow diagrams of the big data intelligent excavating analysis method first embodiment of block chain；
Fig. 2 is that the present invention is based on the flow diagrams of the big data intelligent excavating analysis method second embodiment of block chain；
Fig. 3 is that the present invention is based on the flow diagrams of the big data intelligent excavating analysis method 3rd embodiment of block chain；
Fig. 4 is that the present invention is based on the module diagrams of the big data intelligent excavating analysis system of block chain.
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
The technical issues of with reference to the accompanying drawing and specific embodiment is solved to the embodiment of the present invention, used technical side
Case and the technical effect of realization carry out clear, complete description.Obviously, described embodiment is only one of the application
Divide embodiment, is not whole embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not paying creation
Property labour under the premise of, all other equivalent or obvious variant embodiment obtained all falls within protection scope of the present invention
It is interior.The embodiment of the present invention can be embodied according to the multitude of different ways being defined and covered by claim.
It should be noted that in the following description, understanding for convenience, giving many details.But it is very bright
Aobvious, realization of the invention can be without these details.
It should be noted that in the absence of clear limitations or conflicts, each embodiment in the present invention and its
In technical characteristic can be combined with each other and form technical solution.
The big data intelligent excavating analysis method based on block chain that the invention proposes a kind of, it is intended to solve network credit mistake
Credit safety problem in journey.
In the first embodiment of the invention, referring to Fig.1, the big data intelligent excavating analysis method packet based on block chain
Include following steps:
Step S10 receives the credit applications request that Debit User issues；
In the embodiment of the present invention, Debit User issues credit applications request in corresponding lending platforms, is issuing credit Shen
Debit User completes registration, typing personal information, including proof of identification information, passing debt-credit on lending platforms before please requesting
Information, phone information, e-mail messages, job information, work income information etc..
It should be noted that Debit User can request to check lending platforms before selecting to lending platforms registration information
Credit qualification and credit prestige.The credit prestige of lending platforms can comment lending platforms by collecting other Debit Users
Valence information provides.In order to improve lending platforms credit prestige authenticity, can to all evaluation informations carry out real name matter.Together
When in order to encourage the Debit User of lending platforms actively to evaluate lending platforms after having used lending platforms, can use
Certain energisation modes carry out, such as cash bonuses or red packet reward etc. mode are given after carrying out real name evaluation.
Step S20, according to the credit applications request inquiry Debit User other each platforms data, it is described other
Each platform is the platform being in same block chain pond with lending platforms；
Further, Debit User is inquired in the number of other each platforms according to the credit applications request that Debit User proposes
According to other described each platforms are the platform being in same block chain pond with lending platforms.It is in same with lending platforms
Other platforms in one block chain pond can realize data sharing, and lending platforms can obtain Debit User directly in block chain pond and exist
Data in other platforms, these data include: Debit User in the registration informations of other platforms, Debit User in other platforms
Behavioral data, Debit User other platforms transaction data or debt-credit data etc..It should be noted that same block
Be both needed between other platforms in chain pond abide by data sharing protocol, data sharing but be both needed to carry out data confidentiality.
Wherein, the step S20 includes:
Step S21 requests inquiry Debit User in the registration information of lending platforms according to the credit applications；
Step S21, according to Debit User lending platforms registration information inquiry Debit User personal information, and according to
Data of the personal information inquiry Debit User of Debit User in other each platforms.
Registration information of the inquiry Debit User on lending platforms is requested previously according to credit applications, is being believed from Debit User
The personal information that the registration information on platform gets Debit User is borrowed, according to the personal information of Debit User on other platforms
Information matches are carried out, data of the Debit User on other platforms are inquired.Specifically, believed by advantage distillation Debit User
Borrowing the personal identification registered on platform proves information, such as ID card No., to be matched；If do not had on other platforms
There is ID card information to match head image information etc. other information then to be matched.
Step S30 analyzes whether Debit User touches according to the data of the Debit User inquired on other each platforms
Send out the preset condition of violation operation；
Whether violation operation is triggered according to the Data Detection Debit User of the Debit User inquired on other platforms.This
Violation operation described in inventive embodiments includes grade 1 violation operation and grade 2 violation operation.Trigger the default of grade 1 violation operation
Condition may include: that Debit User in other platforms record of bad behavior occurred, and such as debt-credit is refunded not in time, occur in commodity transaction
Falseness purchase；The preset condition of grade 2 violation operation includes: situations such as identity information of Debit User is abnormal, the body of Debit User
Part loss of learning, Debit User are labeled abnormal etc. in the data of other platforms.
Step S40 executes discipline rating according to the discipline rating of violation operation when triggering the preset condition of violation operation
It is corresponding to set operation.
When Debit User triggers the preset condition of violation operation, then violation is executed according to the discipline rating of violation operation
The corresponding operation of grade.In the embodiment of the present invention, different violation operations corresponds to the different operational means to user, e.g., when
It is at this time the credit for retracting Debit User on lending platforms to the operational means of user when violation operation is that grade 1 violation operates
Application；Either Debit User in a period of time is forbidden to carry out credit applications etc. on lending platforms.
The embodiment of the present invention is issued based on the big data intelligent excavating analysis method of block chain by receiving Debit User
Credit applications request；According to the credit applications request inquiry Debit User other each platforms data, it is described other
Each platform is the platform being in same block chain pond with lending platforms；According to the letter inquired on other each platforms
Whether the data analysis Debit User for borrowing user triggers the preset condition of violation operation；In the preset condition of triggering violation operation
When, the corresponding operation of discipline rating is executed according to the discipline rating of violation operation.Pass through point of the credit data to Debit User
Analysis prevents credit risk to lending platforms, improves risk prevention power.
Based on the present invention is based on the first embodiment of the big data intelligent excavating analysis method of block chain, the present invention is based on areas
In the second embodiment of the big data intelligent excavating analysis method of block chain, according to the seriousness of Debit User data violation, it will disobey
Rule operation is divided into grade 1 violation operation and grade 2 violation operation；
Described in the step S30 trigger violation operation preset condition the step of include:
Step S31 detects Debit User in other platforms and whether is marked as black list user；
Step S32, if it is, the preset condition of triggering grade 1 violation operation；
The step S40 includes:
Step S41 retracts the credit applications request of Debit User when triggering the preset condition of grade 1 violation operation.
Further, in the present embodiment, whether detection Debit User was once marked as blacklist use in other platforms
It family will touching if detecting that Debit User once occurred being marked as the historical record of black list user on other platforms
Send out the grade 1 violation operation of lending platforms.In the present embodiment, if triggering grade 1 violation operation, retracts the letter of Debit User
Borrow application request.
Based on the present invention is based on the first embodiments of the big data intelligent excavating analysis method of block chain or second to implement
Example is touched described in the step S30 the present invention is based in the 3rd embodiment of the big data intelligent excavating analysis method of block chain
Send out violation operation preset condition the step of include:
Step S33 detects Debit User in other platforms and whether data exception occurs；
Step S34, if it is, the preset condition of triggering grade 2 violation operation；
The step S40 includes:
Step S42, when triggering the preset condition of grade 2 violation operation, the prompt information for issuing supplement testimonial material is extremely believed
Borrow user
After the step S42 further include:
Veritify whether the testimonial material that Debit User is submitted meets the requirements；
When the testimonial material that Debit User is submitted is met the requirements, requested by the credit applications of Debit User.
In the embodiment of the present invention, whether detection Debit User there are data exception, data herein on other platforms
It is abnormal include Debit User other platforms identity information it is expired do not update, there is debt-credit in other platforms and refunds in Debit User
There are situations such as abnormal etc. in the login time of other platforms and address in overdue situation, Debit User, not exhaustive one by one herein.
Debit User is being detected when the data of other platforms occur abnormal, then is triggering the grade 2 violation operation of lending platforms.It is touching
When sending out grade 2 violation operation, Debit User can release the data exception bring shadow of other platforms by supplement testimonial material
It rings.After supplementing testimonial material, lending platforms can audit updates Debit User, and the mode of audit can be letter
Loan system carries out, and can also be completed by the end of remotely attending a banquet of lending platforms.It is full in the testimonial material that audit to Debit User is submitted
The requirement of sufficient lending platforms and when can pass through audit, then requested by the credit applications of Debit User.
Based on the present invention is based on the first embodiments of the big data intelligent excavating analysis method of block chain to 3rd embodiment
Any embodiment, referring to Fig. 2, the present invention is based in the fourth embodiment of the big data intelligent excavating analysis method of block chain, institute
Before stating step S30 further include:
Step S01, according to the data of the Debit User inquired on other platforms according to the first default computation rule meter
Calculate the credit worthiness of Debit User；
Step S02 is calculated Debit User according to the second default computation rule according to the credit worthiness of Debit User and is believing
Borrow the line of credit of platform；
Step S03, the credit applications for inquiring Debit User request corresponding application amount, and compare credit applications request pair
The line of credit of the application amount answered and Debit User in lending platforms；
Step S04, if the corresponding application amount of credit applications enters step 30 within the scope of line of credit.
In the embodiment of the present invention, before through the request of the credit applications of Debit User, previously according to Debit User at it
Data on his platform calculate the credit worthiness of Debit User, for example, working as Debit User on other platforms without any bad note
When record, the credit worthiness of Debit User is set to excellent；When there is record of bad behavior together on other platforms in Debit User, Debit User
Credit worthiness positioning it is good, etc..
According to the credit worthiness of Debit User and combine the personal master data of Debit User according to the second preset rules meter
Calculation obtains Debit User in the line of credit of lending platforms, the personal master data of Debit User include the work of Debit User,
Wage level, the level of consumption etc. information.The line of credit of Debit User is calculated in conjunction with these informixes.
Inquire corresponding credit applications amount in the credit applications request of Debit User, detection credit applications amount and calculating
Debit User line of credit, if the credit applications amount of Debit User in the range of the line of credit being calculated,
The credit applications qualification for then continuing audit Debit User, that is, enter step S30.If the credit applications amount of Debit User does not exist
Within the line of credit of calculating, then prompt information is issued the user with, prompts user to modify credit applications amount, or abandon credit
Application.
Based on the present invention is based on the first embodiments of the big data intelligent excavating analysis method of block chain to fourth embodiment
Any embodiment, referring to Fig. 3, the present invention is based in the 5th embodiment of the big data intelligent excavating analysis method of block chain, institute
State method further include:
Step S50 monitors Debit User and credit provider in the behavioral data of lending platforms；
Step S60 is monitoring that it is abnormal that the behavioral data of Debit User or credit provider on lending platforms occurs
When, to third monitoring side signal an alert, interfered in time convenient for third monitoring side.
Behavioral data in the method for the present embodiment to Debit User and two side of credit provider on lending platforms carries out
Monitoring, if either party exception occurs, to third monitoring side signal an alert, does third monitoring side in time
It relates to, guarantees the interests of both sides.
In addition, to achieve the above object, referring to Fig. 4, the present invention also proposes that a kind of big data based on block chain is intelligently dug
Analysis system is dug, the system comprises:
Receiving module, the credit applications request issued for receiving Debit User；
Enquiry module, for requesting data of the inquiry Debit User in other each platforms, institute according to the credit applications
Stating other each platforms is the platform being in same block chain pond with lending platforms；
Judgment module, for being according to the data analysis Debit User of the Debit User inquired on other each platforms
The preset condition of no triggering violation operation；
Execution module, for executing and disobeying according to the discipline rating of violation operation when triggering the preset condition of violation operation
Advise the corresponding predetermined registration operation of grade.
In the embodiment of the present invention, Debit User issues credit applications request in corresponding lending platforms, is issuing credit Shen
Debit User completes registration, typing personal information, including proof of identification information, passing debt-credit on lending platforms before please requesting
Information, phone information, e-mail messages, job information, work income information etc..
It should be noted that Debit User can request to check lending platforms before selecting to lending platforms registration information
Credit qualification and credit prestige.The credit prestige of lending platforms can comment lending platforms by collecting other Debit Users
Valence information provides.In order to improve lending platforms credit prestige authenticity, can to all evaluation informations carry out real name matter.Together
When in order to encourage the Debit User of lending platforms actively to evaluate lending platforms after having used lending platforms, can use
Certain energisation modes carry out, such as cash bonuses or red packet reward etc. mode are given after carrying out real name evaluation.
Further, Debit User is inquired in the number of other each platforms according to the credit applications request that Debit User proposes
According to other described each platforms are the platform being in same block chain pond with lending platforms.It is in same with lending platforms
Other platforms in one block chain pond can realize data sharing, and lending platforms can obtain Debit User directly in block chain pond and exist
Data in other platforms, these data include: Debit User in the registration informations of other platforms, Debit User in other platforms
Behavioral data, Debit User other platforms transaction data or debt-credit data etc..It should be noted that same block
Be both needed between other platforms in chain pond abide by data sharing protocol, data sharing but be both needed to carry out data confidentiality.
Registration information of the inquiry Debit User on lending platforms is requested previously according to credit applications, is being believed from Debit User
The personal information that the registration information on platform gets Debit User is borrowed, according to the personal information of Debit User on other platforms
Information matches are carried out, data of the Debit User on other platforms are inquired.Specifically, believed by advantage distillation Debit User
Borrowing the personal identification registered on platform proves information, such as ID card No., to be matched；If do not had on other platforms
There is ID card information to match head image information etc. other information then to be matched.
Whether violation operation is triggered according to the Data Detection Debit User of the Debit User inquired on other platforms.This
Violation operation described in inventive embodiments includes grade 1 violation operation and grade 2 violation operation.Trigger the default of grade 1 violation operation
Condition may include: that Debit User in other platforms record of bad behavior occurred, and such as debt-credit is refunded not in time, occur in commodity transaction
Falseness purchase；The preset condition of grade 2 violation operation includes: situations such as identity information of Debit User is abnormal, the body of Debit User
Part loss of learning, Debit User are labeled abnormal etc. in the data of other platforms.
When Debit User triggers the preset condition of violation operation, then violation is executed according to the discipline rating of violation operation
The corresponding operation of grade.In the embodiment of the present invention, different violation operations corresponds to the different operational means to user, e.g., when
It is at this time the credit for retracting Debit User on lending platforms to the operational means of user when violation operation is that grade 1 violation operates
Application；Either Debit User in a period of time is forbidden to carry out credit applications etc. on lending platforms.
The embodiment of the present invention is issued based on the big data intelligent excavating analysis method of block chain by receiving Debit User
Credit applications request；According to the credit applications request inquiry Debit User other each platforms data, it is described other
Each platform is the platform being in same block chain pond with lending platforms；According to the letter inquired on other each platforms
Whether the data analysis Debit User for borrowing user triggers the preset condition of violation operation；In the preset condition of triggering violation operation
When, the corresponding operation of discipline rating is executed according to the discipline rating of violation operation.Pass through point of the credit data to Debit User
Analysis prevents credit risk to lending platforms, improves risk prevention power.
In addition, to achieve the above object, the present invention also proposes a kind of terminal device, including memory, processor and deposits
The computer program that can be run in the memory and on the processor is stored up, the processor executes the computer journey
The step of as above any one the method is realized when sequence.
In addition, to achieve the above object, the present invention also proposes a kind of computer readable storage medium, described computer-readable
Storage medium is stored with computer program, and the method any one of as above is realized when the computer program is executed by processor
Step.
Each step of the invention can be realized with general computing device, for example, they can concentrate on it is single
On computing device, such as: personal computer, server computer, handheld device or portable device, laptop device or more
Processor device can also be distributed over a network of multiple computing devices, they can be to be different from sequence herein
Shown or described step is executed, perhaps they are fabricated to each integrated circuit modules or will be more in them
A module or step are fabricated to single integrated circuit module to realize.Therefore, the present invention is not limited to any specific hardware and soft
Part or its combination.
Programmable logic device can be used to realize in method provided by the invention, and it is soft also to may be embodied as computer program
Part or program module (it include routines performing specific tasks or implementing specific abstract data types, programs, objects, component or
Data structure etc.), such as embodiment according to the present invention can be a kind of computer program product, run the computer program
Product executes computer for demonstrated method.The computer program product includes computer readable storage medium, should
It include computer program logic or code section on medium, for realizing the method.The computer readable storage medium can
To be the built-in medium being mounted in a computer or the removable medium (example that can be disassembled from basic computer
Such as: using the storage equipment of hot plug technology).The built-in medium includes but is not limited to rewritable nonvolatile memory,
Such as: RAM, ROM, flash memory and hard disk.The removable medium includes but is not limited to: and optical storage media (such as: CD-
ROM and DVD), magnetic-optical storage medium (such as: MO), magnetic storage medium (such as: tape or mobile hard disk), can with built-in
Rewrite the media (such as: storage card) of nonvolatile memory and the media (such as: ROM box) with built-in ROM.
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 big data intelligent excavating analysis method based on block chain, which is characterized in that described method includes following steps:
Step S10 receives the credit applications request that Debit User issues；
Step S20 requests inquiry Debit User in the data of other each platforms according to the credit applications, and described other are each
Platform is the platform being in same block chain pond with lending platforms；
Step S30, it is separated according to whether the data of the Debit User inquired on other each platforms analysis Debit User triggers
Advise the preset condition of operation；
It is corresponding to execute discipline rating according to the discipline rating of violation operation when triggering the preset condition of violation operation by step S40
Operation.
2. the big data intelligent excavating analysis method according to claim 1 based on block chain, which is characterized in that the step
Suddenly S20 includes:
Step S21 requests inquiry Debit User in the registration information of lending platforms according to the credit applications；
Step S21 inquires the personal information of Debit User according to Debit User in the registration information of lending platforms, and according to credit
Data of the personal information inquiry Debit User of user in other each platforms.
3. the big data intelligent excavating analysis method according to claim 1 based on block chain, which is characterized in that according to letter
Violation operation is divided into grade 1 violation operation and grade 2 violation operates by the seriousness for borrowing user data violation；
Described in the step S30 trigger violation operation preset condition the step of include:
Step S31 detects Debit User in other platforms and whether is marked as black list user；
Step S32, if it is, the preset condition of triggering grade 1 violation operation；
The step S40 includes:
Step S41 retracts the credit applications request of Debit User when triggering the preset condition of grade 1 violation operation.
4. the big data intelligent excavating analysis method according to claim 1 based on block chain, which is characterized in that the step
Suddenly the step of preset condition of triggering violation operation described in S30 includes:
Step S33 detects Debit User in other platforms and whether data exception occurs；
Step S34, if it is, the preset condition of triggering grade 2 violation operation；
The step S40 includes:
Step S42, when triggering the preset condition of grade 2 violation operation, prompt information to the credit for issuing supplement testimonial material is used
Family；
After the step S42 further include:
Veritify whether the testimonial material that Debit User is submitted meets the requirements；
When the testimonial material that Debit User is submitted is met the requirements, requested by the credit applications of Debit User.
5. the big data intelligent excavating analysis method according to claim 1 based on block chain, which is characterized in that the step
Before rapid S30 further include:
Step S01 is calculated according to the data of the Debit User inquired on other platforms according to the first default computation rule
The credit worthiness of Debit User；
Step S02 is calculated Debit User according to the second default computation rule according to the credit worthiness of Debit User and puts down in credit
The line of credit of platform；
Step S03, the credit applications for inquiring Debit User request corresponding application amount, and it is corresponding to compare credit applications request
Apply amount and Debit User in the line of credit of lending platforms；
Step S04, if the corresponding application amount of credit applications enters step 30 within the scope of line of credit.
6. the big data intelligent excavating analysis method according to claim 1 based on block chain, which is characterized in that the side
Method further include:
Step S50 monitors Debit User and credit provider in the behavioral data of lending platforms；
Step S60, monitor Debit User or credit provider when the behavioral data on lending platforms occurs abnormal, to
Third monitoring side signal an alert, is interfered in time convenient for third monitoring side.
7. the big data intelligent excavating analysis method according to claim 1 based on block chain, which is characterized in that the letter
It includes: that Debit User is flat at other in the registration information of other platforms, Debit User that user, which is borrowed, in the data of other each platforms
The behavioral data of platform, Debit User are used in the label datas of other platforms, Debit User in the transaction data of other platforms, credit
Debt-credit data of the family in other platforms.
8. a kind of big data intelligent excavating analysis system based on block chain, which is characterized in that the system comprises:
Receiving module, the credit applications request issued for receiving Debit User；
Enquiry module, for according to the credit applications request inquiry Debit User other each platforms data, it is described its
His each platform is the platform being in same block chain pond with lending platforms；
Judgment module, for whether being touched according to the data analysis Debit User of the Debit User inquired on other each platforms
Send out the preset condition of violation operation；
Execution module, for executing violation etc. according to the discipline rating of violation operation when triggering the preset condition of violation operation
The corresponding predetermined registration operation of grade.
9. a kind of terminal device, including memory, processor and storage are in the memory and can be on the processor
The computer program of operation, which is characterized in that the processor realizes such as claim 1 to 7 when executing the computer program
The step of any one the method.
10. a kind of computer readable storage medium, the computer-readable recording medium storage has computer program, and feature exists
In when the computer program is executed by processor the step of any one of such as claim 1 to 7 of realization the method.
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| CN110674222A (en) * | 2019-10-08 | 2020-01-10 | 腾讯科技（深圳）有限公司 | Data sharing method, device, equipment and medium |
| CN110807209A (en) * | 2019-11-01 | 2020-02-18 | 腾讯科技（深圳）有限公司 | Data processing method, device and storage medium |
| CN111737686A (en) * | 2020-07-31 | 2020-10-02 | 支付宝(杭州)信息技术有限公司 | Processing method, device and equipment of block chain data |
| CN116308736A (en) * | 2023-02-15 | 2023-06-23 | 广州市花都万穗小额贷款股份有限公司 | Loan money early warning management system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110674222A (en) * | 2019-10-08 | 2020-01-10 | 腾讯科技（深圳）有限公司 | Data sharing method, device, equipment and medium |
| CN110807209A (en) * | 2019-11-01 | 2020-02-18 | 腾讯科技（深圳）有限公司 | Data processing method, device and storage medium |
| CN110807209B (en) * | 2019-11-01 | 2021-04-30 | 腾讯科技（深圳）有限公司 | Data processing method, device and storage medium |
| CN111737686A (en) * | 2020-07-31 | 2020-10-02 | 支付宝(杭州)信息技术有限公司 | Processing method, device and equipment of block chain data |
| CN112560019A (en) * | 2020-07-31 | 2021-03-26 | 支付宝(杭州)信息技术有限公司 | Processing method, device and equipment of block chain data |
| US11265174B2 (en) | 2020-07-31 | 2022-03-01 | Alipay (Hangzhou) Information Technology Co., Ltd. | Method, apparatus, and device for processing blockchain data |
| CN116308736A (en) * | 2023-02-15 | 2023-06-23 | 广州市花都万穗小额贷款股份有限公司 | Loan money early warning management system |
| CN116308736B (en) * | 2023-02-15 | 2024-04-19 | 广州市花都万穗小额贷款股份有限公司 | Loan money early warning management system |
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Application publication date: 20190906 |