CN110246047A - Accident vehicle Claims Resolution method and apparatus, electronic equipment - Google Patents
Accident vehicle Claims Resolution method and apparatus, electronic equipment Download PDFInfo
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- CN110246047A CN110246047A CN201910412658.6A CN201910412658A CN110246047A CN 110246047 A CN110246047 A CN 110246047A CN 201910412658 A CN201910412658 A CN 201910412658A CN 110246047 A CN110246047 A CN 110246047A
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- 238000000034 method Methods 0.000 title claims abstract description 29
- 238000012423 maintenance Methods 0.000 claims description 147
- 238000010801 machine learning Methods 0.000 claims description 15
- 230000004044 response Effects 0.000 claims description 14
- 238000012545 processing Methods 0.000 claims description 13
- 238000012549 training Methods 0.000 claims description 11
- 238000012790 confirmation Methods 0.000 claims description 8
- 238000000605 extraction Methods 0.000 claims description 6
- 230000005055 memory storage Effects 0.000 claims description 2
- 230000008439 repair process Effects 0.000 description 7
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- 206010039203 Road traffic accident Diseases 0.000 description 1
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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
- G06Q10/20—Administration of product repair or maintenance
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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
- G06Q40/08—Insurance
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Abstract
This specification one or more embodiment provides a kind of accident vehicle Claims Resolution method and apparatus, electronic equipment, which comprises obtains mantenance data corresponding with accident vehicle；The mantenance data is input to decision model, to be based on the mantenance data by the decision model, determines whether Claims Resolution case belonging to the accident vehicle is fraud case；Determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, carrying out Claims Resolution decision for the accident vehicle.
Description
Technical field
This specification one or more embodiment is related to computer application technology more particularly to a kind of accident vehicle reason
Pay for method and apparatus, electronic equipment.
Background technique
Nowadays, traffic accident accident is having occurred, after being put on record by insurance company for accident vehicle, it usually needs by
Setting loss person carries out setting loss for the accident vehicle, provides reference for the Claims Resolution for the accident vehicle.In this case, how
Discovery setting loss in time is unreasonable, avoids reducing loss to there are the accident vehicles of risk of fraud to carry out Claims Resolution processing, becoming urgently
It solves the problems, such as.
Summary of the invention
This specification proposes a kind of accident vehicle Claims Resolution method, which comprises
Obtain mantenance data corresponding with accident vehicle；
The mantenance data is input to decision model, to be based on the mantenance data by the decision model, determines institute
State whether Claims Resolution case belonging to accident vehicle is fraud case；
Determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being managed for the accident vehicle
Pay for decision.
Optionally, described to be determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being directed to the thing
Therefore vehicle carries out Claims Resolution decision, comprising:
If it is determined that Claims Resolution case belonging to the accident vehicle is fraud case, then by the Claims Resolution case to the reason
The responsible person concerned's output for paying for case, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case.
Optionally, described to be determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being directed to the thing
Therefore vehicle carries out Claims Resolution decision, comprising:
If it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case, then the Claims Resolution case is damaged to core
Member's output, to carry out core damage for the Claims Resolution case by the core damage person.
Optionally, the method also includes:
In response to the core damage person for the mantenance data confirmation operation of the Claims Resolution case, it is based on the mantenance data pair
The accident vehicle carries out Claims Resolution processing；
Operation is modified for the mantenance data of the Claims Resolution case in response to the core damage person, obtains modified maintenance number
According to；
The modified mantenance data is input to decision model, it is described modified to be based on by the decision model
Mantenance data determines whether Claims Resolution case belonging to the accident vehicle is fraud case.
Optionally, the decision model includes the first submodel and the second submodel；The mantenance data includes maintenance side
Case and whole maintenance price；
It is described that the mantenance data is input to decision model, to be based on the mantenance data by the decision model, sentence
Whether Claims Resolution case belonging to the fixed accident vehicle is fraud case, comprising:
Characteristic is extracted based on the maintenance program, and the characteristic is input to first submodel, with
The individual event maintenance price of the accident vehicle is predicted based on the characteristic by first submodel；
The whole maintenance price and the individual event maintenance price are input to second submodel, by described second
Submodel is based on the whole maintenance price and the individual event maintenance price, determines that Claims Resolution case belonging to the accident vehicle is
No is fraud case.
Optionally, the method also includes:
Obtain the maintenance program sample of preset quantity；Wherein, the maintenance program sample has been marked corresponding maintenance valence
Lattice；
Based on the maintenance program sample extraction characteristic sample, and based on preset machine learning algorithm for described
Characteristic sample is trained, to obtain first submodel；
Obtain the maintenance price sample of preset quantity；Wherein, the maintenance price sample includes whole maintenance price and list
Item maintenance price, the maintenance price sample have been marked corresponding fraud label；
It is trained based on preset machine learning algorithm for the maintenance price sample, to obtain second submodule
Type.
Optionally, first submodel is regression model, and affiliated second submodel is two disaggregated models.
This specification also proposes a kind of accident vehicle Claims Resolution device, and described device includes:
First obtains module, for obtaining mantenance data corresponding with accident vehicle；
Determination module, for the mantenance data to be input to decision model, to be based on the dimension by the decision model
Data are repaired, determine whether Claims Resolution case belonging to the accident vehicle is fraud case；
Decision-making module, for being determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, for described
Accident vehicle carries out Claims Resolution decision.
Optionally, the decision-making module is specifically used for:
If it is determined that Claims Resolution case belonging to the accident vehicle is fraud case, then by the Claims Resolution case to the reason
The responsible person concerned's output for paying for case, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case.
Optionally, the decision-making module is specifically used for:
If it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case, then the Claims Resolution case is damaged to core
Member's output, to carry out core damage for the Claims Resolution case by the core damage person.
Optionally, described device further include:
First respond module, for being directed to the mantenance data confirmation operation of the Claims Resolution case in response to the core damage person,
Claims Resolution processing is carried out to the accident vehicle based on the mantenance data；
Second respond module, for modifying operation for the mantenance data of the Claims Resolution case in response to the core damage person,
Obtain modified mantenance data；
The determination module is also used to the modified mantenance data being input to decision model, by the judgement mould
Type is based on the modified mantenance data, determines whether Claims Resolution case belonging to the accident vehicle is fraud case.
Optionally, the decision model includes the first submodel and the second submodel；The mantenance data includes maintenance side
Case and whole maintenance price；
The determination module is specifically used for:
Characteristic is extracted based on the maintenance program, and the characteristic is input to first submodel, with
The individual event maintenance price of the accident vehicle is predicted based on the characteristic by first submodel；
The whole maintenance price and the individual event maintenance price are input to second submodel, by described second
Submodel is based on the whole maintenance price and the individual event maintenance price, determines that Claims Resolution case belonging to the accident vehicle is
No is fraud case.
Optionally, described device further include:
Second obtains module, for obtaining the maintenance program sample of preset quantity；Wherein, the maintenance program sample is marked
Corresponding maintenance price is infused；
First training module for being based on the maintenance program sample extraction characteristic sample, and is based on preset machine
Device learning algorithm is trained for the characteristic sample, to obtain first submodel；
Third obtains module, for obtaining the maintenance price sample of preset quantity；Wherein, the maintenance price sample includes
Whole maintenance price and individual event maintenance price, the maintenance price sample have been marked corresponding fraud label；
Second training module, for being trained based on preset machine learning algorithm for the maintenance price sample,
To obtain second submodel.
Optionally, first submodel is regression model, and affiliated second submodel is two disaggregated models.
This specification also proposes a kind of electronic equipment, and the electronic equipment includes:
Processor；
For storing the memory of machine-executable instruction；
Wherein, the machine corresponding with the control logic of accident vehicle Claims Resolution stored by reading and executing the memory
Executable instruction, the processor are prompted to:
Obtain mantenance data corresponding with accident vehicle；
The mantenance data is input to decision model, to be based on the mantenance data by the decision model, determines institute
State whether Claims Resolution case belonging to accident vehicle is fraud case；
Determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being managed for the accident vehicle
Pay for decision.
In the above-mentioned technical solutions, it for accident vehicle, can be directed to and the accident vehicle pair based on decision model
The mantenance data answered is calculated, to determine whether Claims Resolution case belonging to the accident vehicle is fraud case, and based on judgement
As a result Claims Resolution decision is carried out for the accident vehicle.In this manner, with it is common artificial determine Claims Resolution case whether be
The mode of fraud case is compared, and due to that can determine fraud case automatically, the judgement efficiency of fraud case can be improved
And accuracy.
Detailed description of the invention
Fig. 1 is a kind of schematic diagram of accident vehicle Claims Resolution system shown in one exemplary embodiment of this specification；
Fig. 2 is a kind of flow chart of accident vehicle Claims Resolution method shown in one exemplary embodiment of this specification；
Fig. 3 is a kind of the hard of accident vehicle Claims Resolution device place electronic equipment shown in one exemplary embodiment of this specification
Part structure chart；
Fig. 4 is a kind of block diagram of accident vehicle Claims Resolution device shown in one exemplary embodiment of this specification.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all embodiments consistent with this specification one or more embodiment.Phase
Instead, they are only some aspects phases with the one or more embodiments of as detailed in the attached claim, this specification
The example of consistent device and method.
It is only to be not intended to be limiting this explanation merely for for the purpose of describing particular embodiments in the term that this specification uses
Book.The "an" of used singular, " described " and "the" are also intended to packet in this specification and in the appended claims
Most forms are included, unless the context clearly indicates other meaning.It is also understood that term "and/or" used herein is
Refer to and includes that one or more associated any or all of project listed may combine.
It will be appreciated that though various information may be described using term first, second, third, etc. in this specification, but
These information should not necessarily be limited by these terms.These terms are only used to for same type of information being distinguished from each other out.For example, not taking off
In the case where this specification range, the first information can also be referred to as the second information, and similarly, the second information can also be claimed
For the first information.Depending on context, word as used in this " if " can be construed to " ... when " or
" when ... " or " in response to determination ".
This specification is intended to provide one kind based on mantenance data corresponding with accident vehicle, determines belonging to the accident vehicle
Whether Claims Resolution case is fraud case, to carry out the technical solution of Claims Resolution decision for the accident vehicle based on judgement result.
In specific implementation, referring to FIG. 1, can by setting loss person for some accident vehicle carry out setting loss, that is, determine with
The corresponding mantenance data of the accident vehicle.
It is subsequent, the mantenance data can be obtained by electronic equipment, and the mantenance data is input to and trained is in advance sentenced
Cover half type determines whether Claims Resolution case belonging to the accident vehicle is case of victimization to be based on the mantenance data by the decision model
Part.
If the decision is that the Claims Resolution case is fraud case, then it can be by the Claims Resolution case to the phase of the Claims Resolution case
Person liable's output is closed, to be investigated and collected evidence by responsible person concerned for the Claims Resolution case.
If the decision is that the Claims Resolution case is not fraud case, then the Claims Resolution case can be exported to core damage person,
To carry out core damage for the Claims Resolution case by core damage person.
If fruit stone damage person confirms that Claims Resolution case core damage passes through, then can continue based on the mantenance data to the accident vehicle
Carry out Claims Resolution processing.
If fruit stone damage person confirms that Claims Resolution case core damage does not pass through, then the Claims Resolution case can be retracted into setting loss by core damage person
Member carries out setting loss to be directed to the accident vehicle again by setting loss person.It is subsequent, it can be obtained by electronic equipment again true by setting loss person
Fixed mantenance data corresponding with the accident vehicle, and the mantenance data redefined is input to above-mentioned decision model, with by
The decision model is based on the mantenance data, determines whether Claims Resolution case belonging to the accident vehicle is fraud case.
Alternatively, as fruit stone damage person confirm the Claims Resolution case core damage do not pass through, then core damage person can also to the accident vehicle
Corresponding mantenance data is modified (not shown in figure 1).It is subsequent, modified mantenance data can be obtained by electronic equipment,
And the modified mantenance data is input to above-mentioned decision model again, to be based on the mantenance data by the decision model, sentence
Whether Claims Resolution case belonging to the fixed accident vehicle is fraud case.
In the above-mentioned technical solutions, it for accident vehicle, can be directed to and the accident vehicle pair based on decision model
The mantenance data answered is calculated, to determine whether Claims Resolution case belonging to the accident vehicle is fraud case, and based on judgement
As a result Claims Resolution decision is carried out for the accident vehicle.In this manner, with it is common artificial determine Claims Resolution case whether be
The mode of fraud case is compared, and due to that can determine fraud case automatically, the judgement efficiency of fraud case can be improved
And accuracy.
This specification is described below by specific embodiment.
Referring to FIG. 2, Fig. 2 is a kind of process of accident vehicle Claims Resolution method shown in one exemplary embodiment of this explanation
Figure.This method can be applied to server, mobile phone, tablet device, laptop, palm PC (Personal Digital
Assistants, PDAs) etc. electronic equipments, include the following steps:
Step 202, mantenance data corresponding with accident vehicle is obtained；
Step 204, the mantenance data is input to decision model, to be based on the maintenance number by the decision model
According to, determine Claims Resolution case belonging to the accident vehicle whether be fraud case；
Step 206, determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being directed to the accident vehicle
Carry out Claims Resolution decision.
In the present embodiment, for the accident vehicle for needing to repair processing, it usually needs first determine the accident vehicle
Mantenance data, then Claims Resolution processing is carried out to the accident vehicle based on the mantenance data.It is available in order to avoid Claims Resolution fraud
Mantenance data corresponding with the accident vehicle, and fraud judgement is carried out based on the mantenance data.
It specifically, can be by being responsible for handling the accident vehicle institute after insurance company is put on record for the accident vehicle
The setting loss person of the Claims Resolution case of category carries out setting loss for the accident vehicle, that is, determines mantenance data corresponding with the accident vehicle.
In practical applications, electronic equipment can export accident vehicle setting loss interface to setting loss person, and setting loss person can be at this
Mantenance data corresponding with the accident vehicle is inputted in accident vehicle setting loss interface, i.e. electronic equipment can pass through the accident vehicle
Setting loss interface gets mantenance data corresponding with the accident vehicle.
For example, setting loss person can input to be directed to and be somebody's turn to do in accident vehicle setting loss interface corresponding with the accident vehicle
Work post (such as: metal plate, spray painting, machine work, dismounting etc.), the working hour quantity, component names, component grade, life that accident vehicle determines
Produce maintenance programs and the maintenance prices such as manufacturer, vehicle, car fare section, repair shop's type (such as: Zong Xiu factory, the shop 4S etc.).It is fixed
Damage person can click " confirmation " button in the accident vehicle setting loss interface after completing the setting loss for the accident vehicle.Electricity
Sub- equipment is when detecting setting loss person for the clicking operation for being somebody's turn to do " confirmation " button, it can obtains setting loss person in the accident vehicle
The mantenance data inputted in setting loss interface, and using the mantenance data as mantenance data corresponding with the accident vehicle.
After getting mantenance data corresponding with the accident vehicle, further the mantenance data can be input to pre-
First trained decision model determines Claims Resolution case belonging to the accident vehicle to be based on the mantenance data by the decision model
It whether is fraud case.
It may include maintenance program and entirety by the mantenance data that setting loss person determines in a kind of embodiment shown
Maintenance price, the decision model then may include the first submodel and the second submodel.Wherein the first submodel can be recurrence
Model, the second submodel can be two disaggregated models.
On the one hand, characteristic first can be extracted from above-mentioned maintenance program.Wherein, characteristic can be by technical staff
It presets, comprising: work post, working hour quantity, component names, component grade, production firm, vehicle, car fare section, repair shop's kind
Class etc..It is subsequent, the characteristic extracted can be input to above-mentioned first submodel and calculated.
It should be noted that the maintenance side of preset quantity can first be obtained from Claims Resolution case belonging to history accident vehicle
Case, such as: (non-fraud case can be registered as from Claims Resolution case belonging to the accident vehicle for having carried out Claims Resolution processing
Settle a claim case) in extract preset quantity maintenance program.
After getting these maintenance programs, corresponding individual event maintenance price can be marked for these maintenance programs.Wherein,
Individual event maintenance price, which can be, to be got from the Claims Resolution case.
It is subsequent, these can be marked to the maintenance program of corresponding maintenance price as training sample, based on default
Machine learning algorithm (such as: regression algorithm), be trained for maintenance program sample, to obtain for being based on and accident vehicle
Characteristic in corresponding maintenance program, predicts the first submodel of the individual event maintenance price of the accident vehicle.
Specifically, work post, working hour quantity, vehicle, car fare section, repair shop's type can be extracted from maintenance program sample
As characteristic sample.In this case, for each characteristic sample, for this feature data sample mark
Corresponding individual event maintenance price can be working hour maintenance price corresponding with the maintenance program sample.It is subsequent, it can be based on default
Machine learning algorithm, be trained for these characteristic samples for being marked corresponding working hour maintenance price, with
To for predicting the working hour maintenance price of the accident vehicle based on the characteristic in maintenance program corresponding with accident vehicle
First submodel.
Alternatively, can also from maintenance program extracting parts title, component grade, production firm, vehicle, car fare section,
Repair shop's type is as characteristic sample.It in this case, is this feature data for each characteristic sample
The corresponding individual event maintenance price of sample mark can be parts for maintenance price corresponding with the maintenance program sample.It is subsequent, it can
To be based on preset machine learning algorithm, carried out for these characteristic samples for being marked corresponding parts for maintenance price
Training, to obtain for predicting the component of the accident vehicle based on the characteristic in maintenance program corresponding with accident vehicle
First submodel of maintenance price.
In practical applications, work post, working hour quantity, component names, component grade, life can also be extracted from maintenance program
Manufacturer, vehicle, car fare section, repair shop's type are produced as characteristic sample.In this case, for each characteristic
For sample, it can be for the corresponding individual event maintenance price that this feature data sample marks corresponding with the maintenance program sample
Working hour maintenance price and parts for maintenance price.It is subsequent, it can be based on preset machine learning algorithm, be marked pair for these
The characteristic sample of the working hour maintenance price and parts for maintenance price answered is trained, to obtain for being based on and accident vehicle
Characteristic in corresponding maintenance program predicts the working hour maintenance price of the accident vehicle and the first son of parts for maintenance price
Model.
As an example it is assumed that the quantity of preset maintenance program sample is 100, then it can be belonging to the history accident vehicle
100 maintenance programs are obtained in case of settling a claim, and obtain this corresponding individual event maintenance price of 100 maintenance programs, thus
Its corresponding individual event maintenance price can be marked for each maintenance program.It is subsequent, corresponding list can be marked by this 100
The maintenance program of item maintenance price has been marked corresponding individual event dimension for this 100 as training sample, based on regression algorithm
The maintenance program sample for repairing price is trained, to obtain for based on the characteristic in maintenance program corresponding with accident vehicle
According to predicting the first submodel of the individual event maintenance price of the accident vehicle.
In this way, can be based on using trained first submodel from maintenance side corresponding with the accident vehicle
The characteristic extracted in case predicts the individual event maintenance price of the accident vehicle.Specifically, using this feature data as
The input parameter of one submodel, is input to after being calculated in the first submodel, the calculating knot that the first submodel can be exported
Fruit is determined as the individual event maintenance price of the accident vehicle, so as to realize the individual event maintenance price for predicting the accident vehicle.
On the other hand, valence further can be repaired into the individual event for the accident vehicle predicted by the first submodel
Lattice and above-mentioned whole maintenance price are input to above-mentioned second submodel and are calculated.
It should be noted that Claims Resolution case belonging to the history accident vehicle of available preset quantity, and obtain respectively
The whole maintenance price and individual event maintenance price of these history accident vehicles, such as: it can be obtained from these Claims Resolution cases respectively
Take the whole maintenance price and individual event maintenance price of corresponding history accident vehicle.
Further, it is also possible to be respectively that these Claims Resolution cases are noted for whether instruction Claims Resolution case is the fraud for cheating case
Label, such as: it can be to be registered as the Claims Resolution case mark fraud label 0 of non-fraud case, and to be registered as case of victimization
The Claims Resolution case mark fraud label 1 of part.
It is subsequent, can be using the whole maintenance price of history accident vehicle and individual event maintenance price as characteristic, and incite somebody to action
These have been marked the whole maintenance price of corresponding fraud label and individual event maintenance price as training sample (referred to as maintenance valence
Lattice sample), based on preset machine learning algorithm (such as: two sorting algorithms), it is trained for maintenance price sample, with
To for whole maintenance price and individual event maintenance price based on accident vehicle, determine that Claims Resolution case belonging to the accident vehicle is
No the second submodel for fraud case.
As an example it is assumed that the quantity of preset maintenance price sample is 100, then available 100 history accident vehicles
Claims Resolution case belonging to, and the whole maintenance valence of corresponding history accident vehicle is obtained from this 100 cases of settling a claim respectively
Lattice and individual event maintenance price.It is possible to further determine whether this 100 Claims Resolution cases are registered as fraud case respectively, from
And its corresponding fraud label can be marked for every group of entirety maintenance price and individual event maintenance price.It is subsequent, it can be 100 groups by this
The whole maintenance price and individual event maintenance price for being marked corresponding fraud label are based on two sorting algorithms as training sample
The maintenance price sample for being marked corresponding fraud label for this 100 is trained, to obtain for based on accident vehicle
Whole maintenance price and individual event maintenance price, determine whether Claims Resolution case belonging to the accident vehicle is cheat case the
Two submodels.
In this way, can be using trained second submodel, based on the thing predicted by the first submodel
Therefore the individual event maintenance price of vehicle, and the whole maintenance price of the accident vehicle determined by setting loss person, determine the accident vehicle
Whether the Claims Resolution case belonging to is fraud case.Specifically, using the individual event maintenance price and the entirety maintenance price as
The input parameter of second submodel, is input to after being calculated in the second submodel, can be based on the output of the second submodel
It calculates as a result, determining judgement result corresponding with Claims Resolution case belonging to the accident vehicle.
As an example it is assumed that be registered as the Claims Resolution case mark fraud label 0 of non-fraud case, and to be registered as
Cheat case Claims Resolution case mark fraud label 1, then the second submodel output calculated result be 0 when, can determine with
Claims Resolution case belonging to the accident vehicle is corresponding to be determined the result is that the Claims Resolution case is not fraud case；It is defeated in the second submodel
When calculated result out is 1, judgement corresponding with Claims Resolution case belonging to the accident vehicle can be determined the result is that the Claims Resolution case
Part is fraud case.
In the present embodiment, if it is decided that Claims Resolution case belonging to the accident vehicle is fraud case, then can should
Case of settling a claim is exported to the responsible person concerned of the Claims Resolution case, such as: it can be by modes such as mail, short messages by the Claims Resolution case
It notifies to give the responsible person concerned, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case, thus further really
Whether the fixed Claims Resolution case is fraud case, determines whether to need to carry out Claims Resolution processing for the accident vehicle.
It, then can be by the Claims Resolution case to core if it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case
Damage person's output, to carry out core damage for the Claims Resolution case by core damage person.
If fruit stone damage person is after carrying out core damage to the Claims Resolution case, it is believed that setting loss person determines corresponding with the accident vehicle
Mantenance data is reasonable, then core damage person can initiate the mantenance data confirmation operation for the Claims Resolution case.It is subsequent, in response to the dimension
Data validation operation is repaired, Claims Resolution processing can be carried out to the accident vehicle based on the mantenance data.
If fruit stone damage person is after carrying out core damage to the Claims Resolution case, it is believed that setting loss person determines corresponding with the accident vehicle
Mantenance data is unreasonable, then core damage person can initiate for the Claims Resolution case mantenance data modification operation, with to the accident
The corresponding mantenance data of vehicle is modified.It is subsequent, available modified mantenance data, and again by the modified dimension
It repairs data and is input to above-mentioned decision model, to be based on the mantenance data by the decision model, determine reason belonging to the accident vehicle
Pay for whether case is fraud case.
Alternatively, core damage person think setting loss person determine mantenance data corresponding with the accident vehicle it is unreasonable when, can also
The Claims Resolution case is retracted into setting loss person, setting loss is carried out to be directed to the accident vehicle again by setting loss person.It is subsequent, it is available
The mantenance data corresponding with the accident vehicle redefined by setting loss person, and the mantenance data redefined is input to above-mentioned
Decision model determines whether Claims Resolution case belonging to the accident vehicle is fraud to be based on the mantenance data by the decision model
Case.
In the above-mentioned technical solutions, it for accident vehicle, can be directed to and the accident vehicle pair based on decision model
The mantenance data answered is calculated, to determine whether Claims Resolution case belonging to the accident vehicle is fraud case, and based on judgement
As a result Claims Resolution decision is carried out for the accident vehicle.In this manner, with it is common artificial determine Claims Resolution case whether be
The mode of fraud case is compared, and due to that can determine fraud case automatically, the judgement efficiency of fraud case can be improved
And accuracy.
Corresponding with the aforementioned accident vehicle Claims Resolution embodiment of method, this specification additionally provides accident vehicle Claims Resolution device
Embodiment.
The embodiment of this specification accident vehicle Claims Resolution device can be using on an electronic device.Installation practice can lead to
Software realization is crossed, can also be realized by way of hardware or software and hardware combining.Taking software implementation as an example, as a logic
Device in meaning is to be referred to computer program corresponding in nonvolatile memory by the processor of electronic equipment where it
It enables and is read into memory what operation was formed.For hardware view, as shown in figure 3, for this specification accident vehicle Claims Resolution device
A kind of hardware structure diagram of place electronic equipment in addition to processor shown in Fig. 3, memory, network interface and non-volatile is deposited
Except reservoir, the actual functional capability that the electronic equipment in embodiment where device is settled a claim generally according to the accident vehicle can also be wrapped
Other hardware are included, this is repeated no more.
Referring to FIG. 4, Fig. 4 is a kind of frame of accident vehicle Claims Resolution device shown in one exemplary embodiment of this specification
Figure.The device 40 can be applied to electronic equipment shown in Fig. 3, comprising:
First obtains module 401, for obtaining mantenance data corresponding with accident vehicle；
Determination module 402, it is described to be based on by the decision model for the mantenance data to be input to decision model
Mantenance data determines whether Claims Resolution case belonging to the accident vehicle is fraud case；
Decision-making module 403, for being determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being directed to institute
It states accident vehicle and carries out Claims Resolution decision.
In the present embodiment, the decision-making module 403 specifically can be used for:
If it is determined that Claims Resolution case belonging to the accident vehicle is fraud case, then by the Claims Resolution case to the reason
The responsible person concerned's output for paying for case, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case.
In the present embodiment, the decision-making module 403 specifically can be used for:
If it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case, then the Claims Resolution case is damaged to core
Member's output, to carry out core damage for the Claims Resolution case by the core damage person.
In the present embodiment, described device 40 can also include:
First respond module 404, for confirming behaviour for the mantenance data of the Claims Resolution case in response to the core damage person
Make, Claims Resolution processing is carried out to the accident vehicle based on the mantenance data；
Second respond module 405, for modifying behaviour for the mantenance data of the Claims Resolution case in response to the core damage person
Make, obtains modified mantenance data；
The determination module 402 can be also used for the modified mantenance data being input to decision model, by institute
It states decision model and is based on the modified mantenance data, determine whether Claims Resolution case belonging to the accident vehicle is case of victimization
Part.
In the present embodiment, the decision model includes the first submodel and the second submodel；The mantenance data includes
Maintenance program and whole maintenance price；
The determination module 402 specifically can be used for:
Characteristic is extracted based on the maintenance program, and the characteristic is input to first submodel, with
The individual event maintenance price of the accident vehicle is predicted based on the characteristic by first submodel；
The whole maintenance price and the individual event maintenance price are input to second submodel, by described second
Submodel is based on the whole maintenance price and the individual event maintenance price, determines that Claims Resolution case belonging to the accident vehicle is
No is fraud case.
In the present embodiment, described device 40 can also include:
Second obtains module 406, for obtaining the maintenance program sample of preset quantity；Wherein, the maintenance program sample
It has been marked corresponding maintenance price；
First training module 407, for being based on the maintenance program sample extraction characteristic sample, and based on preset
Machine learning algorithm is trained for the characteristic sample, to obtain first submodel；
Third obtains module 408, for obtaining the maintenance price sample of preset quantity；Wherein, the maintenance price sample
Including whole maintenance price and individual event maintenance price, the maintenance price sample has been marked corresponding fraud label；
Second training module 409, for being instructed based on preset machine learning algorithm for the maintenance price sample
Practice, to obtain second submodel.
In the present embodiment, first submodel is regression model, and affiliated second submodel is two disaggregated models.
The function of modules and the realization process of effect are specifically detailed in the above method and correspond to step in above-mentioned apparatus
Realization process, details are not described herein.
For device embodiment, since it corresponds essentially to embodiment of the method, so related place is referring to method reality
Apply the part explanation of example.The apparatus embodiments described above are merely exemplary, wherein described be used as separation unit
The module of explanation may or may not be physically separated, and the component shown as module can be or can also be with
It is not physical module, it can it is in one place, or may be distributed on multiple network modules.It can be according to actual
The purpose for needing to select some or all of the modules therein to realize this specification scheme.Those of ordinary skill in the art are not
In the case where making the creative labor, it can understand and implement.
System, device, module or the module that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.A kind of typically to realize that equipment is computer, the concrete form of computer can
To be personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media play
In device, navigation equipment, E-mail receiver/send equipment, game console, tablet computer, wearable device or these equipment
The combination of any several equipment.
Corresponding with above-mentioned accident vehicle Claims Resolution embodiment of the method, this specification additionally provides the implementation of a kind of electronic equipment
Example.The electronic equipment includes: processor and the memory for storing machine-executable instruction；Wherein, processor and storage
Device is usually connected with each other by internal bus.In other possible implementations, the equipment is also possible that external interface,
Can be communicated with other equipment or component.
In the present embodiment, the control logic pair with accident vehicle Claims Resolution stored by reading and executing the memory
The machine-executable instruction answered, the processor are prompted to:
Obtain mantenance data corresponding with accident vehicle；
The mantenance data is input to decision model, to be based on the mantenance data by the decision model, determines institute
State whether Claims Resolution case belonging to accident vehicle is fraud case；
Determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being managed for the accident vehicle
Pay for decision.
In the present embodiment, the control logic pair with accident vehicle Claims Resolution stored by reading and executing the memory
The machine-executable instruction answered, the processor are prompted to:
If it is determined that Claims Resolution case belonging to the accident vehicle is fraud case, then by the Claims Resolution case to the reason
The responsible person concerned's output for paying for case, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case.
In the present embodiment, the control logic pair with accident vehicle Claims Resolution stored by reading and executing the memory
The machine-executable instruction answered, the processor are prompted to:
If it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case, then the Claims Resolution case is damaged to core
Member's output, to carry out core damage for the Claims Resolution case by the core damage person.
In the present embodiment, the control logic pair with accident vehicle Claims Resolution stored by reading and executing the memory
The machine-executable instruction answered, the processor are also prompted to:
In response to the core damage person for the mantenance data confirmation operation of the Claims Resolution case, it is based on the mantenance data pair
The accident vehicle carries out Claims Resolution processing；
Operation is modified for the mantenance data of the Claims Resolution case in response to the core damage person, obtains modified maintenance number
According to；
The modified mantenance data is input to decision model, it is described modified to be based on by the decision model
Mantenance data determines whether Claims Resolution case belonging to the accident vehicle is fraud case.
In the present embodiment, the decision model includes the first submodel and the second submodel；The mantenance data includes
Maintenance program and whole maintenance price；
Machine corresponding with the control logic of accident vehicle Claims Resolution by reading and executing the memory storage can be held
Row instruction, the processor are prompted to:
Characteristic is extracted based on the maintenance program, and the characteristic is input to first submodel, with
The individual event maintenance price of the accident vehicle is predicted based on the characteristic by first submodel；
The whole maintenance price and the individual event maintenance price are input to second submodel, by described second
Submodel is based on the whole maintenance price and the individual event maintenance price, determines that Claims Resolution case belonging to the accident vehicle is
No is fraud case.
In the present embodiment, the control logic pair with accident vehicle Claims Resolution stored by reading and executing the memory
The machine-executable instruction answered, the processor are also prompted to:
Obtain the maintenance program sample of preset quantity；Wherein, the maintenance program sample has been marked corresponding maintenance valence
Lattice；
Based on the maintenance program sample extraction characteristic sample, and based on preset machine learning algorithm for described
Characteristic sample is trained, to obtain first submodel；
Obtain the maintenance price sample of preset quantity；Wherein, the maintenance price sample includes whole maintenance price and list
Item maintenance price, the maintenance price sample have been marked corresponding fraud label；
It is trained based on preset machine learning algorithm for the maintenance price sample, to obtain second submodule
Type.
In the present embodiment, first submodel is regression model, and affiliated second submodel is two disaggregated models.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to this specification
Other embodiments.This specification is intended to cover any variations, uses, or adaptations of this specification, these modifications,
Purposes or adaptive change follow the general principle of this specification and undocumented in the art including this specification
Common knowledge or conventional techniques.The description and examples are only to be considered as illustrative, the true scope of this specification and
Spirit is indicated by the following claims.
It should be understood that this specification is not limited to the precise structure that has been described above and shown in the drawings,
And various modifications and changes may be made without departing from the scope thereof.The range of this specification is only limited by the attached claims
System.
The foregoing is merely the preferred embodiments of this specification one or more embodiment, not to limit this theory
Bright book one or more embodiment, all within the spirit and principle of this specification one or more embodiment, that is done is any
Modification, equivalent replacement, improvement etc. should be included within the scope of the protection of this specification one or more embodiment.
Claims (15)
- A kind of method 1. accident vehicle is settled a claim, which comprisesObtain mantenance data corresponding with accident vehicle；The mantenance data is input to decision model, to be based on the mantenance data by the decision model, determines the thing Therefore whether Claims Resolution case belonging to vehicle is fraud case；Determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being settled a claim certainly for the accident vehicle Plan.
- 2. according to the method described in claim 1, described based on judgement corresponding with Claims Resolution case belonging to the accident vehicle As a result, carrying out Claims Resolution decision for the accident vehicle, comprising:If it is determined that Claims Resolution case belonging to the accident vehicle is fraud case, then by the Claims Resolution case to the Claims Resolution case The responsible person concerned of part exports, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case.
- 3. according to the method described in claim 1, described based on judgement corresponding with Claims Resolution case belonging to the accident vehicle As a result, carrying out Claims Resolution decision for the accident vehicle, comprising:If it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case, then the Claims Resolution case is defeated to core damage person Out, to carry out core damage for the Claims Resolution case by the core damage person.
- 4. according to the method described in claim 3, the method also includes:In response to the core damage person for the mantenance data confirmation operation of the Claims Resolution case, based on the mantenance data to described Accident vehicle carries out Claims Resolution processing；Operation is modified for the mantenance data of the Claims Resolution case in response to the core damage person, obtains modified mantenance data；The modified mantenance data is input to decision model, to be based on the modified maintenance by the decision model Data determine whether Claims Resolution case belonging to the accident vehicle is fraud case.
- 5. according to the method described in claim 1, the decision model includes the first submodel and the second submodel；The maintenance Data include maintenance program and whole maintenance price；It is described that the mantenance data is input to decision model, to be based on the mantenance data by the decision model, determine institute State whether Claims Resolution case belonging to accident vehicle is fraud case, comprising:Characteristic is extracted based on the maintenance program, and the characteristic is input to first submodel, by institute State the individual event maintenance price that the first submodel predicts the accident vehicle based on the characteristic；The whole maintenance price and the individual event maintenance price are input to second submodel, by second submodule Type is based on the whole maintenance price and the individual event maintenance price, determine Claims Resolution case belonging to the accident vehicle whether be Cheat case.
- 6. according to the method described in claim 5, the method also includes:Obtain the maintenance program sample of preset quantity；Wherein, the maintenance program sample has been marked corresponding maintenance price；The feature is directed to based on the maintenance program sample extraction characteristic sample, and based on preset machine learning algorithm Data sample is trained, to obtain first submodel；Obtain the maintenance price sample of preset quantity；Wherein, the maintenance price sample includes whole maintenance price and individual event dimension Price is repaired, the maintenance price sample has been marked corresponding fraud label；It is trained based on preset machine learning algorithm for the maintenance price sample, to obtain second submodel.
- 7. affiliated second submodel is two classification according to the method described in claim 5, first submodel is regression model Model.
- The device 8. a kind of accident vehicle is settled a claim, described device include:First obtains module, for obtaining mantenance data corresponding with accident vehicle；Determination module, for the mantenance data to be input to decision model, to be based on the maintenance number by the decision model According to, determine Claims Resolution case belonging to the accident vehicle whether be fraud case；Decision-making module, for being determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being directed to the accident Vehicle carries out Claims Resolution decision.
- 9. device according to claim 8, the decision-making module is specifically used for:If it is determined that Claims Resolution case belonging to the accident vehicle is fraud case, then by the Claims Resolution case to the Claims Resolution case The responsible person concerned of part exports, to be investigated and collected evidence by the responsible person concerned for the Claims Resolution case.
- 10. device according to claim 8, the decision-making module is specifically used for:If it is determined that Claims Resolution case belonging to the accident vehicle is not fraud case, then the Claims Resolution case is defeated to core damage person Out, to carry out core damage for the Claims Resolution case by the core damage person.
- 11. device according to claim 10, described device further include:First respond module is based on for the mantenance data confirmation operation in response to the core damage person for the Claims Resolution case The mantenance data carries out Claims Resolution processing to the accident vehicle；Second respond module is obtained for modifying operation for the mantenance data of the Claims Resolution case in response to the core damage person Modified mantenance data；The determination module is also used to the modified mantenance data being input to decision model, by the decision model base In the modified mantenance data, determine whether Claims Resolution case belonging to the accident vehicle is fraud case.
- 12. device according to claim 8, the decision model includes the first submodel and the second submodel；The dimension Repairing data includes maintenance program and whole maintenance price；The determination module is specifically used for:Characteristic is extracted based on the maintenance program, and the characteristic is input to first submodel, by institute State the individual event maintenance price that the first submodel predicts the accident vehicle based on the characteristic；The whole maintenance price and the individual event maintenance price are input to second submodel, by second submodule Type is based on the whole maintenance price and the individual event maintenance price, determine Claims Resolution case belonging to the accident vehicle whether be Cheat case.
- 13. device according to claim 12, described device further include:Second obtains module, for obtaining the maintenance program sample of preset quantity；Wherein, the maintenance program sample is marked Corresponding maintenance price；First training module for being based on the maintenance program sample extraction characteristic sample, and is based on preset engineering It practises algorithm to be trained for the characteristic sample, to obtain first submodel；Third obtains module, for obtaining the maintenance price sample of preset quantity；Wherein, the maintenance price sample includes whole Maintenance price and individual event maintenance price, the maintenance price sample have been marked corresponding fraud label；Second training module, for being trained based on preset machine learning algorithm for the maintenance price sample, with To second submodel.
- 14. device according to claim 12, first submodel is regression model, and affiliated second submodel is two points Class model.
- 15. a kind of electronic equipment, the electronic equipment include:Processor；For storing the memory of machine-executable instruction；Wherein, it can be held by reading and executing the machine corresponding with the control logic of accident vehicle Claims Resolution of the memory storage Row instruction, the processor are prompted to:Obtain mantenance data corresponding with accident vehicle；The mantenance data is input to decision model, to be based on the mantenance data by the decision model, determines the thing Therefore whether Claims Resolution case belonging to vehicle is fraud case；Determined based on corresponding with Claims Resolution case belonging to the accident vehicle as a result, being settled a claim certainly for the accident vehicle Plan.
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| CN201910412658.6A CN110246047A (en) | 2019-05-17 | 2019-05-17 | Accident vehicle Claims Resolution method and apparatus, electronic equipment |
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