CN110503564A - Save case processing method, system, equipment and storage medium from damage based on big data - Google Patents
Save case processing method, system, equipment and storage medium from damage based on big data Download PDFInfo
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Abstract
The embodiment of the present invention, which is provided, saves case processing method from damage based on big data, comprising: receives target user by what client was sent and saves application information from damage；Corresponding multiple associated datas are obtained according to application information is saved from damage；The input of multiple associated datas is saved from damage in risk evaluation model, obtains complaint risk coefficient by saving risk evaluation model from damage；The risk class for saving case from damage is determined according to complaint risk coefficient；Save audit policy from damage according to risk class execution is corresponding.The embodiment of the present invention, which is also provided, saves case processing system, equipment and readable storage medium storing program for executing from damage based on big data.The embodiment of the present invention saves case assessment from damage to target user by saving risk evaluation model from damage, and the method for carrying out risk management and control, the loss of computer equipment calculation resources is not allowed to easily cause, and avoid because the rule conflict between newly-increased rule may cause the generation of the crash event of computer equipment in data processing, the data-handling efficiency and accuracy rate of computer equipment are higher.
Description
Technical field
The present embodiments relate to big data field more particularly to it is a kind of based on big data save from damage case processing method,
System, computer equipment and computer readable storage medium.
Background technique
With the continuous development of cloud computing technology and big data technology, insurance data is also towards various dimensions, big data quantity side
To development, traditional insurance risk assessment means realized in a manual manner, because of low efficiency and due to need to put into a large amount of manpowers
It is not suitable for current insurance risk assessment.Therefore, it is used for data modeling by acquiring a large amount of insurance risk related datas, by big
The data model of data building carries out risk control and indicating risk, compared to traditional artificial experience risk control mode more section
It learns, it is more efficient.
By taking certain insurance company as an example, saving case load from damage every year is about 23,000,000, can there is a small amount of emit in these cases
Working part emits working part and refers to replace me to handle insurance business in the case where agreeing to without me.
Tradition saves anti-risk do from damage and mainly carries out risk management and control by the experience of expert and business rule, however this tradition is done
Method has some defects: 1, cost of labor is higher；2, magnanimity case is faced, traditional method needs constantly to add new business rule,
Following defect can be brought in this way: the business rule constantly increased can greatly consume Computing resource, and generate between rule
Rule conflict it is also possible that computer data processing composition in collapse time occurs, be also easy to cause the place of data processing
Reason efficiency and accuracy rate decline to a great extent.
Summary of the invention
Case processing method, system, calculating are saved from damage based on big data in view of this, the embodiment of the invention provides a kind of
Machine equipment and computer readable storage medium, for solve it is traditional save from damage business by the experience and business rule of expert come pair
Emit mode low efficiency and the higher problem of human cost that working part carries out risk management and control.
The embodiment of the present invention is to solve above-mentioned technical problem by following technical proposals:
It is a kind of that case processing method is saved from damage based on big data, it is applied in computer equipment, comprising:
It receives the target user and saves application information from damage by what client was sent；
Corresponding multiple associated datas are obtained according to the application information of saving from damage, the multiple associated data is and the mesh
Mark the related data of user or the associated multiple dimensions of target declaration form；
The multiple associated data is input to and is saved from damage in risk evaluation model, is obtained by the risk evaluation model of saving from damage
Take corresponding complaint risk coefficient；
The risk class for saving case from damage is determined according to the complaint risk coefficient；
Save audit policy from damage according to risk class execution is corresponding.
Further, receive the target user by client send the step of saving application information from damage, comprising:
Receive the JSON format that the target user is sent by the client saves applying for electronic list from damage；
Save applying for electronic list described in parsing from damage to obtain corresponding structural data, the structural data is stored in
In database；And
Multiple field informations of multiple fields are extracted from the structural data, the multiple field information includes user
Essential information and declaration form essential information.
Further, save the step of application information obtains corresponding multiple associated datas from damage according to described, comprising:
According to the number of policy or customer ID in the declaration form essential information, obtained from preset User Information Database with
The number of policy or the corresponding multiple associated datas of customer ID；
Wherein, the multiple associated data includes business personnel's data, customer data, declaration form data and business datum.
Further, the risk evaluation model of saving from damage is the Logic Regression Models after training；The method is also wrapped
Include the training step for saving risk evaluation model from damage:
Multiple sample datas of multiple users are obtained from customer database according to preset multiple risk labels；
The Logic Regression Models being pre-configured by multiple sample datas training of multiple users, to obtain by the multiple
Save risk evaluation model from damage after sample data sets training.
Further, the step of saving the risk class of case from damage, is determined according to the complaint risk coefficient, further includes:
Obtain the complaint risk coefficient for saving case from damage of the target user；
Save the risk class of case from damage according to complaint risk coefficient determination, the risk class includes the first wind
Dangerous grade, the second risk class, third risk class and the 4th risk class.
Further, corresponding the step of saving audit policy from damage, is executed according to the risk class, further includes:
If the case of saving from damage corresponds to first risk class, executes first and save audit policy from damage, to generate cabinet face
It handles suggestion prompt information and the suggestion prompt information is returned into the client；
If the case of saving from damage corresponds to second risk class, executes second and save audit policy from damage, by the guarantor
Whole case part is imported into the first electronic equipment, and video communication pass is established between first electronic equipment and the client
System carries out review operations by save case information of the video communication to the target user so as to attend a banquet；
If the case of saving from damage corresponds to the third risk class, executes third and save audit policy from damage, to pass through face
Identification technology identifies target user, so that target user is saved the self-service audit of case progress from damage to it and handles；
If the case of saving from damage corresponds to the 4th risk class, executes the 4th and save audit policy from damage, by corresponding
Short-message verification information target user is verified, make the target user it is saved from damage case carry out it is self-service audit handle.
To achieve the goals above, the embodiment of the present invention also provide it is a kind of case processing system is saved from damage based on big data,
Include:
First acquisition module saves application information from damage by what client was sent for receiving the target user；
Second acquisition module obtains corresponding multiple associated datas for saving application information from damage according to, the multiple
Associated data is the related data with the target user or the associated multiple dimensions of target declaration form；
Input module is saved from damage in risk evaluation model for the multiple associated data to be input to, and is saved from damage by described
Risk evaluation model obtains corresponding complaint risk coefficient；
Determining module, for determining the risk class for saving case from damage according to the complaint risk coefficient；
Execution module, for saving audit policy from damage according to risk class execution is corresponding.
Further, first acquisition module, is also used to:
Receive the JSON format that the target user is sent by the client saves applying for electronic list from damage；
Save applying for electronic list described in parsing from damage to obtain corresponding structural data, the structural data is stored in
In database；And
Multiple field informations of multiple fields are extracted from the structural data, the multiple field information includes user
Essential information and declaration form essential information.
To achieve the goals above, the embodiment of the present invention also provides a kind of computer equipment, and the computer equipment includes
Memory, processor and it is stored in the computer program that can be run on the memory and on a processor, the processor
When executing the computer program realize as described above based on big data the step of saving case processing method from damage.
To achieve the goals above, the embodiment of the present invention also provides a kind of computer readable storage medium, the computer
Computer program is stored in readable storage medium storing program for executing, the computer program can be performed by least one processor, so that institute
State at least one processor execute as described above based on big data the step of saving case processing method from damage.
It is provided in an embodiment of the present invention that case processing method, system, computer equipment and calculating are saved from damage based on big data
Machine readable storage medium storing program for executing is saved the anti-risk tradition done from damage and is done compared to by the way that expertise and the constantly business rule that increases are this
Method, the embodiment of the present invention pass through the associated data for excavating multiple dimensions relevant to case is saved from damage, and by saving risk assessment from damage
Model does risk class to assess the emitting for case of saving from damage of target user, further according to emit do risk class matching be pre-configured correspondence
Save audit policy from damage, it is this by saving risk evaluation model from damage from damage case assessment to be saved to target user, and carry out risk pipe
The method of control, it is not easy to cause the loss of computer equipment calculation resources, and avoid because between ever-increasing business rule
Rule conflict may cause the generation of the crash event of computer equipment in data processing, the data of computer equipment
Treatment effeciency and accuracy rate are higher.
Below in conjunction with the drawings and specific embodiments, the present invention will be described in detail, but not as a limitation of the invention.
Detailed description of the invention
Fig. 1 is the step flow chart for saving case processing method from damage based on big data of the embodiment of the present invention one；
Fig. 2 is the idiographic flow schematic diagram of step S100 in Fig. 1；
Fig. 3 is that the present invention is based on the program module schematic diagrames of the embodiment two for saving case processing system from damage of big data；
Fig. 4 is the hardware structural diagram of the embodiment three of computer equipment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that described herein, specific examples are only used to explain the present invention, not
For limiting the present invention.Based on the embodiments of the present invention, those of ordinary skill in the art are not before making creative work
Every other embodiment obtained is put, shall fall within the protection scope of the present invention.
Technical solution between each embodiment can be combined with each other, but must be with those of ordinary skill in the art's energy
It is enough realize based on, will be understood that the knot of this technical solution when conflicting or cannot achieve when occurs in the combination of technical solution
Conjunction is not present, also not the present invention claims protection scope within.
Embodiment one
Referring to Fig. 1, showing the step process for saving case processing method from damage based on big data of the embodiment of the present invention
Figure.The sequence for executing step is defined it is appreciated that the flow chart in this method embodiment is not used in.Below with computer
Equipment is that executing subject carries out exemplary description, specific as follows:
Step S100 receives the target user by what client was sent and saves application information from damage.
In the exemplary embodiment, referring to Fig. 2, step S100 can further include:
Step S100A, receive the JSON format that the target user is sent by the client saves applying for electronic from damage
List；
Step S100B saves applying for electronic list from damage to obtain corresponding structural data, the structuring number described in parsing
According to being stored in database；
Step S100C extracts multiple field informations of multiple fields, the multiple field letter from the structural data
Breath includes user basic information and declaration form essential information.
Specifically, the user basic information may include the ID card information of user, name, gender, the age, occupation,
Income range etc.；The declaration form essential information may include number of policy, customer ID etc..The number of policy refers to insurer to insurance
After company insures successfully, insurance company provides the number of insurance contract；The customer ID is that insurance company configures for each client
An identification number.
Step S102 obtains corresponding multiple associated datas, the multiple associated data according to the application information of saving from damage
For the related data with the target user or the associated multiple dimensions of target declaration form.
In the exemplary embodiment, according to the number of policy or customer ID in the declaration form essential information, from preset use
Multiple associated datas corresponding with the number of policy or customer ID are obtained in the information database of family；Wherein, the multiple incidence number
According to including business personnel's data, customer data, declaration form data and business datum.
Business personnel's data refer to the relevant information for handling the business personnel of target case, as business personnel's essential information,
Business personnel sells habits information etc.；Business personnel's essential information includes: gender, age, educational background, the entire period of actual operation, department's age, registration
Examination score, professional level, mechanism, enters trade-before occupation reference, marital status, held certificate type etc. at affiliated channel；The business
Member's sale habits information includes: customer quantity, effective customer quantity, customer insured's quantity, the situation of being in danger of client, customer satisfaction
Degree, commission deduction, product sales data, affiliated team etc..
The customer data may include: the identity information, credit information, funds flow information, internet information of user
Save information from damage with history.Wherein, the identity information of client may include: name, gender, age, occupation, income range, connection
Mode (telephone number information, mailbox message) etc.；The credit information may include: credit information, overdue loan information etc.；Institute
Stating funds flow information may include flowing into information, fund moon outflow information etc. the fund moon；The internet information includes purchase
Behavioural information etc.；The history, which saves information from damage, may include: declaration form modification information, saves classification information from damage, saves amount information from damage etc..
The declaration form data, refer to the relevant information of the corresponding declaration form of target case, as declaration form state, declaration form property,
Premium etc..
The business datum refers to the relevant information of the business of target case, and such as new contract accepts insurance, saves from damage, settling a claim
Deng.Wherein, save from damage migration, insurer that information may include declaration form or by the change of the information of insurer, the change of beneficiary,
Declaration form reports the loss benefit (changing) hair etc.；Further include the change of insured amount, postpones payment, is payment gold, declaration form loan, surrender value, red
All kinds of payment affairs such as benefit.
The multiple associated data is input to and saves from damage in risk evaluation model by step S104, saves risk from damage by described
Assessment models obtain corresponding complaint risk coefficient.
The risk evaluation model of saving from damage can be LR (Logistic Regression, logistic regression) model, GBDT
Built-up pattern, the GBDT+FM of (Gradient Boost Decision Tree, gradient promote decision tree)+LR
The built-up pattern or other models of (Factorization Machine, Factorization machine).
Step S106 determines the risk class for saving case from damage according to the complaint risk coefficient.
This step, further comprising the steps of:
Step S106A obtains the complaint risk coefficient for saving case from damage of the target user；
Step S106B judges the risk class for saving case described in the complaint risk coefficient determination from damage, the risk class
Including the first risk class, the second risk class, third risk class and the 4th risk class.
Wherein, the first risk class, definition Risk interval are the by stages 76-100, and possibility with higher is saved from damage
Case emits working part；
Second risk class, definition Risk interval are the by stages 51-75, and there is a possibility that medium to save case from damage and emit
Working part；
Third risk class, definition Risk interval are the by stages 26-50, and there is a possibility that medium relatively low to save case from damage
Part emits working part；
4th risk class, definition Risk interval are the by stages 0-25, and there is a possibility that lower to save case from damage and emit
Working part.
Step S108 saves audit policy from damage according to risk class execution is corresponding.
Specifically, judging that this is saved from damage according to the Risk interval where the complaint risk coefficient for saving case from damage of target user
The risk class of case, and review operations instruction feedback is saved from damage to the target user accordingly according to risk class acquisition.
Illustratively, if the complaint risk coefficient for saving case from damage is 86, the case of saving from damage corresponds to described the
One risk class then executes and first saves audit policy from damage, handles suggestion prompt information and by suggestions prompt to generate cabinet face
Information returns to the client.
It is described to save case from damage and correspond to described second risk etc. if the complaint risk coefficient for saving case from damage is 58
Grade then executes second and saves audit policy from damage, the case of saving from damage is imported into the first electronic equipment, and in first electricity
Video communication relationship is established between sub- equipment and the client, so that the guarantor to attend a banquet by video communication to the target user
Whole case part information carries out review operations.
It is described to save case from damage and correspond to described third risk etc. if the complaint risk coefficient for saving case from damage is 29
Grade, then execute third and save audit policy from damage, to identify by face recognition technology to target user, make target user to it
Save the self-service audit of case progress from damage to handle；
It is described to save case from damage and correspond to described 4th risk etc. if the complaint risk coefficient for saving case from damage is 14
Grade executes the 4th and saves audit policy from damage, to verify by corresponding short-message verification information to target user, makes the target
User saves the self-service audit of case progress from damage to it and handles.
In the exemplary embodiment, saving risk evaluation model from damage can be the Logic Regression Models after training.
Before step S100, the embodiment of the invention also includes the training steps for saving risk evaluation model from damage:
1.1, multiple sample datas of multiple users are obtained from customer database according to preset multiple risk labels；
1.2, the Logic Regression Models being pre-configured by multiple sample datas training of multiple users, to obtain by described
Save risk evaluation model from damage after multiple sample data training.
It is provided in an embodiment of the present invention that case processing method is saved from damage based on big data, compared to by expertise and not
The disconnected business rule increased is this to save the anti-risk traditional method done from damage, and the embodiment of the present invention is by saving risk evaluation model from damage to mesh
Mark user's saves case assessment, and the method for carrying out risk management and control from damage, it is not easy to the loss of computer equipment calculation resources is caused,
And it avoids because the rule conflict between ever-increasing business rule may cause computer equipment in data processing
Crash event generation, the data-handling efficiency and accuracy rate of computer equipment be higher.
Embodiment two
Please continue to refer to Fig. 3, the program module signal for saving case processing system from damage the present invention is based on big data is shown
Figure.In the present embodiment, the case processing system 20 of saving from damage based on big data may include or be divided into one or more journeys
Sequence module, one or more program module are stored in storage medium, and as performed by one or more processors, with complete
At the present invention, and it can realize and above-mentioned case processing method be saved from damage based on big data.The so-called program module of the embodiment of the present invention
It is the series of computation machine program instruction section for referring to complete specific function, is based on big data more suitable for description than program itself
Save implementation procedure of the case processing system 20 in storage medium from damage.Each program mould of the present embodiment will specifically be introduced by being described below
The function of block:
First acquisition module 200 saves application information from damage by what client was sent for receiving the target user.
Further, first acquisition module 200 is also used to:
Receive the JSON format that the target user is sent by the client saves applying for electronic list from damage；Parsing institute
It states and saves applying for electronic list from damage to obtain corresponding structural data, the structural data is stored in database；And from
Extract multiple field informations of multiple fields in the structural data, the multiple field information include user basic information and
Declaration form essential information.
Second acquisition module 202 obtains corresponding multiple associated datas for saving application information from damage according to, described more
A associated data is the related data with the target user or the associated multiple dimensions of target declaration form.
Input module 204 is saved from damage in risk evaluation model for the multiple associated data to be input to, and passes through the guarantor
Full risk evaluation model obtains corresponding complaint risk coefficient.
Determining module 206, for determining the risk class for saving case from damage according to the complaint risk coefficient.
Further, the determining module 206 is also used to:
Obtain the complaint risk coefficient for saving case from damage of the target user；
Judge the risk class for saving case described in the complaint risk coefficient determination from damage, the risk class includes the first wind
Dangerous grade, the second risk class, third risk class and the 4th risk class.
Execution module 208, for saving audit policy from damage according to risk class execution is corresponding.
Further, the execution module 208 is also used to:
If the case of saving from damage corresponds to first risk class, executes first and save audit policy from damage, to generate cabinet face
It handles suggestion prompt information and the suggestion prompt information is returned into the client；
If the case of saving from damage corresponds to second risk class, executes second and save audit policy from damage, by the guarantor
Whole case part is imported into the first electronic equipment, and video communication pass is established between first electronic equipment and the client
System carries out review operations by save case information of the video communication to the target user so as to attend a banquet；
If the case of saving from damage corresponds to the third risk class, executes third and save audit policy from damage, to pass through people
Face identification technology identifies target user, so that target user is saved the self-service audit of case progress from damage to it and handles；
If the case of saving from damage corresponds to the 4th risk class, executes the 4th and save audit policy from damage, by corresponding
Short-message verification information target user is verified, make the target user it is saved from damage case carry out it is self-service audit handle.
Embodiment three
It is the hardware structure schematic diagram of the computer equipment of the embodiment of the present invention three refering to Fig. 4.It is described in the present embodiment
Computer equipment 2 is that one kind can be automatic to carry out numerical value calculating and/or information processing according to the instruction for being previously set or storing
Equipment.The computer equipment 2 can be rack-mount server, blade server, tower server or Cabinet-type server
(including server cluster composed by independent server or multiple servers) etc..As shown in figure 4, the computer is set
Standby 2 include at least, but are not limited to, can be in communication with each other by system bus connection memory 21, processor 22, network interface 23,
And case processing system 20 is saved from damage based on big data.Wherein:
In the present embodiment, memory 21 includes at least a type of computer readable storage medium, the readable storage
Medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory etc.), random access storage device
(RAM), static random-access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory
(EEPROM), programmable read only memory (PROM), magnetic storage, disk, CD etc..In some embodiments, memory
21 can be the internal storage unit of computer equipment 2, such as the hard disk or memory of the computer equipment 2.In other implementations
In example, memory 21 is also possible to the grafting being equipped on the External memory equipment of computer equipment 2, such as the computer equipment 2
Formula hard disk, intelligent memory card (Smart Media Card, SMC), secure digital (Secure Digital, SD) card, flash card
(Flash Card) etc..Certainly, memory 21 can also both including computer equipment 2 internal storage unit and also including outside it
Store equipment.In the present embodiment, memory 21 is installed on the operating system and types of applications of computer equipment 2 commonly used in storage
Software, such as the program code etc. for saving case processing system 20 from damage based on big data of embodiment two.In addition, memory 21 is also
It can be used for temporarily storing the Various types of data that has exported or will export.
Processor 22 can be in some embodiments central processing unit (Central Processing Unit, CPU),
Controller, microcontroller, microprocessor or other data processing chips.The processor 22 is commonly used in control computer equipment 2
Overall operation.In the present embodiment, program code or processing data of the processor 22 for being stored in run memory 21, example
Case processing system 20 is saved from damage based on big data as run, to realize that the case of saving from damage based on big data of embodiment one is handled
Method.
The network interface 23 may include radio network interface or wired network interface, which is commonly used in
Communication connection is established between the computer equipment 2 and other electronic devices.For example, the network interface 23 is for passing through network
The computer equipment 2 is connected with exterior terminal, establishes data transmission between the computer equipment 2 and exterior terminal
Channel and communication connection etc..The network can be intranet (Intranet), internet (Internet), whole world movement
Communication system (Global System of Mobile communication, GSM), wideband code division multiple access (Wideband
Code Division Multiple Access, WCDMA), 4G network, 5G network, bluetooth (Bluetooth), the nothings such as Wi-Fi
Line or cable network.
It should be pointed out that Fig. 4 illustrates only the computer equipment 2 with component 20-23, it should be understood that simultaneously
All components shown realistic are not applied, the implementation that can be substituted is more or less component.
In the present embodiment, the case processing system 20 of saving from damage based on big data being stored in memory 21 may be used also
To be divided into one or more program module, one or more of program modules are stored in memory 21, and
It is performed by one or more processors (the present embodiment is processor 22), to complete the present invention.
For example, Fig. 3 shows the program mould of saving case processing system 20 embodiment two of the realization based on big data
Block schematic diagram, in the embodiment, the saving case processing system 20 from damage and can be divided into the first acquisition mould based on big data
Block 200, the second acquisition module 202, input module 204, determining module 206 and execution module 208.Wherein, alleged by the present invention
Program module be refer to complete specific function series of computation machine program instruction section, than program more suitable for description described in
Save implementation procedure of the case processing system 20 in the computer equipment 2 from damage based on big data.Described program module 200-
208 concrete function has had a detailed description in example 2, and details are not described herein.
Example IV
The present embodiment also provides a kind of computer readable storage medium, such as flash memory, hard disk, multimedia card, card-type memory
(for example, SD or DX memory etc.), random access storage device (RAM), static random-access memory (SRAM), read-only memory
(ROM), electrically erasable programmable read-only memory (EEPROM), programmable read only memory (PROM), magnetic storage, magnetic
Disk, CD, server, App are stored thereon with computer program, phase are realized when program is executed by processor using store etc.
Answer function.The computer readable storage medium of the present embodiment saves case processing system 20, quilt from damage based on big data for storing
That embodiment one is realized when processor executes saves case processing method from damage based on big data.
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.
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 save case processing method from damage based on big data, it is applied in computer equipment characterized by comprising
It receives the target user and saves application information from damage by what client was sent；
Corresponding multiple associated datas are obtained according to the application information of saving from damage, the multiple associated data is to use with the target
The related data of family or the associated multiple dimensions of target declaration form；
The multiple associated data is input to and is saved from damage in risk evaluation model, saves risk evaluation model acquisition pair from damage by described
The complaint risk coefficient answered；
The risk class for saving case from damage is determined according to the complaint risk coefficient；
Save audit policy from damage according to risk class execution is corresponding.
2. according to claim 1 save case processing method from damage based on big data, which is characterized in that receive the target
User by client send the step of saving application information from damage, comprising:
Receive the JSON format that the target user is sent by the client saves applying for electronic list from damage；
Save applying for electronic list described in parsing from damage to obtain corresponding structural data, the structural data is stored in data
In library；And
Multiple field informations of multiple fields are extracted from the structural data, the multiple field information includes that user is basic
Information and declaration form essential information.
3. according to claim 2 save case processing method from damage based on big data, which is characterized in that saved from damage according to described
Application information obtains the step of corresponding multiple associated datas, comprising:
According to the number of policy or customer ID in the declaration form essential information, obtained from preset User Information Database with it is described
Number of policy or the corresponding multiple associated datas of customer ID；
Wherein, the multiple associated data includes business personnel's data, customer data, declaration form data and business datum.
4. according to claim 1 save case processing method from damage based on big data, which is characterized in that described to save risk from damage
Assessment models are the Logic Regression Models after training；The method also includes saving the training step of risk evaluation model from damage:
Multiple sample datas of multiple users are obtained from customer database according to preset multiple risk labels；
The Logic Regression Models being pre-configured by multiple sample datas training of multiple users, to obtain through the multiple sample
Save risk evaluation model from damage after data acquisition system training.
5. according to claim 1 save case processing method from damage based on big data, which is characterized in that according to the complaint
Risk factor determines the step of saving the risk class of case from damage, further includes:
Obtain the complaint risk coefficient for saving case from damage of the target user；
Save the risk class of case from damage according to complaint risk coefficient determination, the risk class includes first risk etc.
Grade, the second risk class, third risk class and the 4th risk class.
6. according to claim 5 save case processing method from damage based on big data, which is characterized in that according to the risk
Grade executes corresponding the step of saving audit policy from damage, further includes:
If the case of saving from damage corresponds to first risk class, executes first and save audit policy from damage, handled with generating cabinet face
It is recommended that prompt information and the suggestion prompt information is returned to the client；
If the case of saving from damage corresponds to second risk class, executes second and save audit policy from damage, save case from damage for described
Part is imported into the first electronic equipment, and establishes video communication relationship between first electronic equipment and the client,
Review operations are carried out by save case information of the video communication to the target user so as to attend a banquet；
If the case of saving from damage corresponds to the third risk class, executes third and save audit policy from damage, to pass through recognition of face
Technology identifies target user, so that target user is saved the self-service audit of case progress from damage to it and handles；
If the case of saving from damage corresponds to the 4th risk class, execute the 4th and save audit policy from damage, by corresponding short
Letter verification information verifies target user, so that the target user is saved the self-service audit of case progress from damage to it and handles.
7. a kind of save case processing system from damage based on big data characterized by comprising
First acquisition module saves application information from damage by what client was sent for receiving the target user；
Second acquisition module obtains corresponding multiple associated datas, the multiple association for saving application information from damage according to
Data are the related data with the target user or the associated multiple dimensions of target declaration form；
Input module is saved from damage in risk evaluation model for the multiple associated data to be input to, and saves risk from damage by described
Assessment models obtain corresponding complaint risk coefficient；
Determining module, for determining the risk class for saving case from damage according to the complaint risk coefficient；
Execution module, for saving audit policy from damage according to risk class execution is corresponding.
8. according to claim 7 save case processing system from damage based on big data, which is characterized in that first acquisition
Module is also used to:
Receive the JSON format that the target user is sent by the client saves applying for electronic list from damage；
Save applying for electronic list described in parsing from damage to obtain corresponding structural data, the structural data is stored in data
In library；And
Multiple field informations of multiple fields are extracted from the structural data, the multiple field information includes that user is basic
Information and declaration form essential information.
9. a kind of computer equipment, the computer equipment includes memory, processor and is stored on the memory simultaneously
The computer program that can be run on the processor, feature is in the processor is realized when executing the computer program
As it is as claimed in any one of claims 1 to 6 based on big data the step of saving case processing method from damage.
10. a kind of computer readable storage medium, which is characterized in that be stored with computer in the computer readable storage medium
Program, the computer program can be performed by least one processors, so that at least one described processor executes such as right
It is required that described in any one of 1 to 6 based on big data the step of saving case processing method from damage.
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