CN109255718A - Insurance benefits method and apparatus, computer equipment and readable storage medium storing program for executing - Google Patents
Insurance benefits method and apparatus, computer equipment and readable storage medium storing program for executing Download PDFInfo
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- CN109255718A CN109255718A CN201810690847.5A CN201810690847A CN109255718A CN 109255718 A CN109255718 A CN 109255718A CN 201810690847 A CN201810690847 A CN 201810690847A CN 109255718 A CN109255718 A CN 109255718A
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- 238000000034 method Methods 0.000 title claims abstract description 44
- 230000008901 benefit Effects 0.000 title claims abstract description 42
- 230000000977 initiatory effect Effects 0.000 claims abstract description 64
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- 230000005540 biological transmission Effects 0.000 claims description 3
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- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 3
- 241000208340 Araliaceae Species 0.000 claims description 2
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- 235000003140 Panax quinquefolius Nutrition 0.000 claims description 2
- 235000008434 ginseng Nutrition 0.000 claims description 2
- 230000001419 dependent effect Effects 0.000 abstract description 6
- 241001269238 Data Species 0.000 description 6
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- 238000010168 coupling process Methods 0.000 description 3
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- 238000013528 artificial neural network Methods 0.000 description 2
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- 206010039203 Road traffic accident Diseases 0.000 description 1
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Classifications
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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
Abstract
The embodiment of the invention provides a kind of insurance benefits method and apparatus, computer equipment and readable storage medium storing program for executing.In the embodiment of the present invention, receive settlement of insurance claim application, obtain the Claims Resolution reference data of the initiation user of the settlement of insurance claim application, wherein the Claims Resolution reference data includes at least one of physical condition data, Assets data and accident related data, to, the Claims Resolution reference data for initiating user is handled using machine learning algorithm, obtains the Claims Resolution for initiating user with reference to the amount of money, in turn, the amount of money is referred to according to the Claims Resolution, insurance benefits are carried out to the initiation user.Therefore, technical solution provided in an embodiment of the present invention, which is able to solve in the prior art, determines the larger problem of consumption of the amount for which loss settled to cost of human resources dependent on human subjective.
Description
[technical field]
The present invention relates to field of computer technology more particularly to a kind of insurance benefits method and apparatus, computer equipment with
Readable storage medium storing program for executing.
[background technique]
With the promotion of people's awareness of safety, more and more people can buy insurance products, in order to which unexpected feelings are occurring
It can be protected when condition.Based on this, when the unexpected happens, when such as burst disease or generation accident traffic accident, use
Family can propose settlement of insurance claim application to insurance company.Corresponding, insurance company needs that a situation arises to contingency
On-site land survey is carried out, and based on the result of on-site land survey by manually realizing concluding for amount for which loss settled.In settlement of insurance claim service at least
There are the following problems:
Excessive depends on artificial subjective determination, this can not only consume a large amount of cost of human resources, moreover, subjective disconnected
Determining amount for which loss settled can also result in amount for which loss settled there are large error, be easy to happen accidentally compensation, wrong phenomena such as paying for.
[summary of the invention]
It is deposited in view of this, the embodiment of the invention provides a kind of insurance benefits method and apparatus, computer equipments with readable
Storage media determines that amount for which loss settled is biggish to the consumption of cost of human resources dependent on human subjective in the prior art to solve
Problem.
In a first aspect, the embodiment of the invention provides a kind of insurance benefits methods, comprising:
Receive settlement of insurance claim application；
Obtain the Claims Resolution reference data of the initiation user of the settlement of insurance claim application, wherein the Claims Resolution reference data packet
Include at least one of physical condition data, Assets data and accident related data；
The Claims Resolution reference data for initiating user is handled using machine learning algorithm, obtains the initiation
The Claims Resolution of user refers to the amount of money；
The amount of money is referred to according to the Claims Resolution, insurance benefits are carried out to the initiation user.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, the body feelings
Condition data include: that medical records, family's medical history, personal injury record and history body class are insured in purchase and Claims Resolution record extremely
Few one kind；
The Assets data include: in payment record, loan documentation, transaction in assets data and purchase transaction data
It is at least one；
The accident related data includes: accident responsibility determines that data and the scene of the accident illustrate at least one of data.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, the acquisition institute
State the Claims Resolution reference data of the initiation user of settlement of insurance claim application, comprising:
Whether the storage location for identifying the Claims Resolution reference data for initiating user is itself storage location；
When the storage location is itself storage location, the Claims Resolution reference number for initiating user is called
According to.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, the method is also
Include:
When the storage location is non-self storage location, the settlement of insurance claim is carried to storage location transmission
The data call of request is requested；
The storage location is received according to the Claims Resolution reference data of data call request feedback.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, it is described to utilize machine
Device learning algorithm handles the Claims Resolution reference data for initiating user, obtains the Claims Resolution reference for initiating user
Before the amount of money, the method also includes:
Settlement of insurance claim model is constructed, the input of the settlement of insurance claim model is the Claims Resolution reference number for initiating user
According to the output of the settlement of insurance claim model is that the Claims Resolution refers to the amount of money；
The Claims Resolution reference data for initiating user is inputted into the settlement of insurance claim model, obtains the initiation user
The Claims Resolution refer to the amount of money.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, the building are protected
Danger Claims Resolution model, comprising:
Initial settlement of insurance claim model is constructed, and obtains the history Claims Resolution record of multiple sample of users；
The initial settlement of insurance claim model is trained using history Claims Resolution record, obtains the settlement of insurance claim mould
Type.
The aspect and any possible implementation manners as described above, it is further provided a kind of implementation, it is described according to institute
Claims Resolution is stated with reference to the amount of money, insurance benefits are carried out to the initiation user, comprising:
The Claims Resolution is compensated as compensation pay-outs to the initiation user with reference to the amount of money.
A technical solution in above-mentioned technical proposal has the following beneficial effects:
In the embodiment of the present invention, when receiving any Client-initiated settlement of insurance claim application, then obtain initiation user's
Claims Resolution reference data, and based on these Claims Resolution reference datas, it is based on machine learning algorithm, Claims Resolution is immediately arrived at and refers to the amount of money, subtract
Small person works' amount saves human cost, and compared to Claims Resolution reference gold artificial, that the Claims Resolution reference data based on user obtains
The error of volume is smaller.Therefore, technical solution provided in an embodiment of the present invention is able to solve in the prior art dependent on human subjective
Determine the larger problem of consumption of the amount for which loss settled to cost of human resources.
Second aspect, the embodiment of the invention provides a kind of insurance benefits devices, comprising:
Receiving unit, for receiving settlement of insurance claim application；
Acquiring unit, the Claims Resolution reference data of the initiation user for obtaining the settlement of insurance claim application, wherein the reason
Paying for reference data includes at least one of physical condition data, Assets data and accident related data；
Processing unit, for using machine learning algorithm to it is described initiate user the Claims Resolution reference data at
Reason obtains the Claims Resolution for initiating user with reference to the amount of money；
Unit is compensated, for referring to the amount of money according to the Claims Resolution, insurance benefits are carried out to the initiation user.
The third aspect the embodiment of the invention provides a kind of computer equipment, including memory, processor and is stored in
In the memory and the computer program that can run on the processor, when the processor executes the computer program
Realize such as the described in any item insurance benefits methods of first aspect.
Fourth aspect, the embodiment of the invention provides a kind of computer readable storage mediums, including the executable finger of computer
It enables, when the computer executable instructions are run, to execute insurance benefits as claimed in any one of claims 1 to 8
Method.
A technical solution in above-mentioned technical proposal has the following beneficial effects:
In the embodiment of the present invention, when receiving any Client-initiated settlement of insurance claim application, then obtain initiation user's
Claims Resolution reference data, and based on these Claims Resolution reference datas, it is based on machine learning algorithm, Claims Resolution is immediately arrived at and refers to the amount of money, subtract
Small person works' amount saves human cost, and compared to Claims Resolution reference gold artificial, that the Claims Resolution reference data based on user obtains
The error of volume is smaller.Therefore, technical solution provided in an embodiment of the present invention is able to solve in the prior art dependent on human subjective
Determine the larger problem of consumption of the amount for which loss settled to cost of human resources.
[Detailed description of the invention]
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be to needed in the embodiment attached
Figure is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this field
For those of ordinary skill, without any creative labor, it can also be obtained according to these attached drawings other attached
Figure.
Fig. 1 is the flow diagram of the embodiment one of insurance benefits method provided by the embodiment of the present invention；
Fig. 2 is the flow diagram of the embodiment two of insurance benefits method provided by the embodiment of the present invention；
Fig. 3 is the flow diagram of the embodiment three of insurance benefits method provided by the embodiment of the present invention；
Fig. 4 is the functional block diagram of insurance benefits device provided by the embodiment of the present invention；
Fig. 5 is the functional block diagram of computer equipment provided by the embodiment of the present invention.
[specific embodiment]
For a better understanding of the technical solution of the present invention, being retouched in detail to the embodiment of the present invention with reference to the accompanying drawing
It states.
It will be appreciated that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.Base
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts it is all its
Its embodiment, shall fall within the protection scope of the present invention.
The term used in embodiments of the present invention is only to be not intended to be limiting merely for for the purpose of describing particular embodiments
The present invention.In the embodiment of the present invention and the "an" of singular used in the attached claims, " described " and "the"
It is also intended to including most forms, unless the context clearly indicates other meaning.
It should be appreciated that term "and/or" used herein is only a kind of incidence relation for describing affiliated partner, indicate
There may be three kinds of relationships, for example, A and/or B, can indicate: individualism A, exist simultaneously A and B, individualism B these three
Situation.In addition, character "/" herein, typicallys represent the relationship that forward-backward correlation object is a kind of "or".
Depending on context, word as used in this " if " can be construed to " ... when " or " when ...
When " or " in response to determination " or " in response to detection ".Similarly, depend on context, phrase " if it is determined that " or " if detection
(condition or event of statement) " can be construed to " when determining " or " in response to determination " or " when the detection (condition of statement
Or event) when " or " in response to detection (condition or event of statement) ".
Pass through and mistake larger there are human cost when human subjective's judgement amount for which loss settled in the presence of the prior art
The larger problem of difference, the embodiment of the invention provides following resolving ideas: when receiving any Client-initiated settlement of insurance claim Shen
Please, then the Claims Resolution reference data of initiation user is obtained, and based on these Claims Resolution reference datas, is based on machine learning algorithm, directly
It connects and show that Claims Resolution with reference to the amount of money, reduces person works' amount, save human cost, and compared to artificial, the Claims Resolution ginseng based on user
It is smaller with reference to the error of the amount of money to examine the Claims Resolution that data obtain.
Under the guidance of the thinking, this programme embodiment provides following feasible embodiment.
Embodiment one
The embodiment of the present invention provides a kind of insurance benefits method.Referring to FIG. 1, this method may include steps of:
S102 receives settlement of insurance claim application.
S104 obtains the Claims Resolution reference data of the initiation user of settlement of insurance claim application.
Wherein, Claims Resolution reference data include physical condition data, in Assets data and accident related data at least
It is a kind of.
Physical condition data according to the present invention are used to characterize the health situation of user.In concrete implementation scene
In, physical condition data can include but is not limited to: medical records, family's medical history, personal injury record and history body class are protected
At least one of danger purchase and Claims Resolution record.
Assets data according to the present invention are used to characterize the Assets of user, such as whether being in debt, if loan,
Whether transaction credit is good etc..In a concrete implementation scene, Assets data be can include but is not limited to: transaction letter
With at least one of data, payment record, loan documentation, transaction in assets data and purchase transaction data；
Accident related data involved in the embodiment of the present invention is for characterizing data relevant to accident and its scene.One
In a concrete implementation scene, accident related data be can include but is not limited to: accident responsibility determines that data and the scene of the accident are said
At least one of bright data.Wherein, the scene of the accident illustrates that data can be verbal description, is also possible to picture, alternatively, may be used also
To be multi-medium data etc., the embodiment of the present invention is not particularly limited this.
S106 handles the Claims Resolution reference data for initiating user using machine learning algorithm, obtains initiating user's
Claims Resolution refers to the amount of money.
S108 refers to the amount of money according to Claims Resolution, carries out insurance benefits to user is initiated.
Hereinafter, the implementation to above steps is illustrated respectively.
Storage location based on the Claims Resolution reference data to be obtained in S104 is different, and the implementation of the step is not yet
Together, it is based on this, the embodiment of the present invention provides following implementation, looks at and examines Fig. 2, and S104 step includes:
S1042, whether the storage location that the Claims Resolution reference data of user is initiated in identification is itself storage location.
When realizing the step in a realization scene, the storage position of the available Claims Resolution reference data for initiating user
It sets, then, is searched according to the path of the storage location in itself storage location, if can be according to the path searching to initiation
The Claims Resolution reference data of user, it is determined that the storage location is itself storage location；Conversely, if can not be found according to the path
Initiate the Claims Resolution reference data of user, it is determined that the storage location is non-self storage location.
S1044A calls the Claims Resolution reference data for initiating user when storage location is itself storage location.
Itself storage location involved in the embodiment of the present invention refers to that the storage location is located at itself memory space, alternatively,
The storage location belongs to other storage locations under current device control, for example, being set by the mobile hard disk that current device controls
It is standby etc..In this case, which can directly can call from itself storage location under the control of current device
These data, without to other equipment request data.
In another possible realization scene, this method can also be combined with block chain technology.Specifically, if will work as
The preceding equipment for executing the insurance benefits method is as the node on a block chain, then itself storage location on current device
These Claims Resolution reference datas are stored with, then, based on the security verification scheme that block chain has, then it can pass through block
Chain verifies the identity of current device, thus, when the authentication of current device passes through, directly downloads and reason can be obtained
Pay for reference data.
S1044B carries settlement of insurance claim request to storage location transmission when storage location is non-self storage location
Data call request；And storage location is received according to the Claims Resolution reference data of data call request feedback.
Non-self storage location involved in the embodiment of the present invention refer to the storage location not the control of current device it
Under, therefore, it is impossible to these data are called directly or read, it therefore, can be by sending what data call was requested to storage location
Mode obtains these data.
For example, the equipment for currently executing the insurance benefits method may not deposit when reference data of settling a claim is medical records
These data are contained, therefore, the data call request for carrying insurance benefits request can be sent to hospital server, so as to
In hospital server, according to the insurance benefits request confirmation, the equipment has data call permission, in this way, hospital server can be with
The medical record data that hospital stores is fed back into the equipment.
Alternatively, in another example, it, can be to the transaction credit for being stored with user when reference data of settling a claim is transaction credit data
Bank, lending institution and hospital of data etc. send the data call request for carrying insurance benefits request respectively, in this way, these
The server of mechanism is based on the transaction credit that after insurance benefits request confirmation data call permission, own institutions can be stored
Data feedback is returned, in this way, realizing the acquisition to transaction credit data.
Based on above-mentioned steps, the acquisition in S104 to Claims Resolution reference data may be implemented.
In this way, when executing S106 step, referring to FIG. 3, the step further includes specifically including following two small steps:
S1062 constructs settlement of insurance claim model.
Wherein, the input of the settlement of insurance claim model is to initiate the Claims Resolution reference data of user, the output of settlement of insurance claim model
The amount of money is referred to for Claims Resolution.
The Claims Resolution reference data for initiating user is inputted settlement of insurance claim model by S1064, obtains the Claims Resolution reference for initiating user
The amount of money.
Wherein, the process for settlement of insurance claim model being constructed in S1062 can be with are as follows: constructs initial settlement of insurance claim model, and obtains
The history of multiple sample of users, which is settled a claim, to be recorded；Then, initial settlement of insurance claim model is trained using history Claims Resolution record, is obtained
To settlement of insurance claim model.
Wherein, initial settlement of insurance claim model can be constructed according to machine learning algorithm, then, pass through sample of users
History Claims Resolution record is trained initial settlement of insurance claim model, so that it may obtain settlement of insurance claim model.Wherein, sample of users
History Claims Resolution record includes: that the history Claims Resolution reference data of sample of users and history Claims Resolution refer to the amount of money.In specific implementation,
Sample of users can according to need selection.
Machine learning algorithm involved in the embodiment of the present invention can include but is not limited to: decision Tree algorithms, neural network
Algorithm etc..
In order to make it easy to understand, the process of training machine learning model is briefly described by taking neural network algorithm as an example.
First, on the one hand, the framework relationship building input based on neural network model is Claims Resolution reference data, output is Claims Resolution with reference to gold
The initial settlement of insurance claim model of volume；On the other hand, the history Claims Resolution record of multiple sample of users is subjected to feature extraction, obtained each
The history Claims Resolution feature of sample of users；Then, the history Claims Resolution feature of multiple sample of users is imported into the initial settlement of insurance claim mould
Type is trained, to confirm the weight of each input parameter, thus, it obtains eventually passing through trained settlement of insurance claim model.
Based on this, the number of sample of users, and obtained settlement of insurance claim model is more accurate.
Based on the reason for initiating user accessed by settlement of insurance claim model constructed by above-mentioned S1062 step and S104 step
Reference data is paid for, then, when executing S108 step, it is only necessary to which the Claims Resolution reference data for initiating user is inputted settlement of insurance claim mould
The Claims Resolution for initiating user can be obtained with reference to the amount of money in type.
There can be following two when executing the Claims Resolution step of S108 with reference to the amount of money based on the Claims Resolution that above-mentioned steps are got
Implementation:
The first: Claims Resolution is compensated as compensation pay-outs to initiation user with reference to the amount of money.
This mode can be operated with prosthetic, realized complete automatic processing, greatly reduced cost of human resources, mention
High Claims Resolution efficiency.
Second: output carries the prompt information that Claims Resolution refers to the amount of money, in order to prompt user to initiation user's
Claims Resolution can be referred to the amount of money as reference during compensation.
In this fashion, it is contemplated that the Claims Resolution obtained by machine learning with reference to the amount of money may inaccuracy, can also be into
One step increases the step of manual synchronizing, so that the more accurate closing to reality situation of amount for which loss settled, reduces accidentally compensation or the wrong feelings paid for
Condition occurs.
Based on above-mentioned insurance benefits method, the embodiment of the invention also provides a kind of computer readable storage mediums, including
Computer executable instructions, when the computer executable instructions are run, to execute any realization side as described above
The insurance benefits method of formula.
The technical solution of the embodiment of the present invention has the advantages that
In the embodiment of the present invention, when receiving any Client-initiated settlement of insurance claim application, then obtain initiation user's
Claims Resolution reference data, and based on these Claims Resolution reference datas, it is based on machine learning algorithm, Claims Resolution is immediately arrived at and refers to the amount of money, subtract
Small person works' amount saves human cost, and compared to Claims Resolution reference gold artificial, that the Claims Resolution reference data based on user obtains
The error of volume is smaller.Therefore, technical solution provided in an embodiment of the present invention is able to solve in the prior art dependent on human subjective
Determine the larger problem of consumption of the amount for which loss settled to cost of human resources.
Embodiment two
Insurance benefits method provided by one based on the above embodiment, the embodiment of the present invention, which further provides, realizes above-mentioned side
The Installation practice of each step and method in method embodiment.
On the one hand, the embodiment of the invention provides a kind of insurance benefits devices, referring to FIG. 4, the insurance benefits device 400
Include:
Receiving unit 41, for receiving settlement of insurance claim application；
Acquiring unit 42, the Claims Resolution reference data of the initiation user for obtaining settlement of insurance claim application, wherein the Claims Resolution
Reference data includes at least one of physical condition data, Assets data and accident related data；
Processing unit 43 is obtained for being handled using machine learning algorithm the Claims Resolution reference data for initiating user
The Claims Resolution for initiating user refers to the amount of money；
Unit 44 is compensated, for referring to the amount of money according to Claims Resolution, carries out insurance benefits to user is initiated.
Wherein, physical condition data involved in the embodiment of the present invention can include but is not limited to: medical records, h disease
History, personal injury record and at least one of history body class insurance purchase and Claims Resolution record；
Assets data can include but is not limited to: payment record, loan documentation, transaction in assets data and purchase transaction
At least one of data；
Accident related data can include but is not limited to: accident responsibility determines that data and the scene of the accident illustrate in data extremely
Few one kind.
Specifically, acquiring unit 42 can be specifically used for:
Whether the storage location that the Claims Resolution reference data of user is initiated in identification is itself storage location；
When storage location is itself storage location, the Claims Resolution reference data for initiating user is called.
And when storage location is non-self storage location, is sent to storage location and carry what settlement of insurance claim was requested
Data call request；
Storage location is received according to the Claims Resolution reference data of data call request feedback.
In the embodiment of the present invention, processing unit 43 is specifically used for:
Settlement of insurance claim model is constructed, the input of the settlement of insurance claim model is the Claims Resolution reference number for initiating user
According to the output of the settlement of insurance claim model is that the Claims Resolution refers to the amount of money；
The Claims Resolution reference data for initiating user is inputted into the settlement of insurance claim model, obtains the initiation user
The Claims Resolution refer to the amount of money.
Wherein, processing mode of the processing unit 43 when being specifically used for building settlement of insurance claim model, may include such as lower section
Formula:
Initial settlement of insurance claim model is constructed, and obtains the history Claims Resolution record of multiple sample of users；
The initial settlement of insurance claim model is trained using history Claims Resolution record, obtains the settlement of insurance claim mould
Type.
In the embodiment of the present invention, compensates unit 44 and is specifically used for:
Claims Resolution is compensated as insurance benefits gold to initiation user with reference to the amount of money.
On the other hand, the embodiment of the invention also provides a kind of computer equipments, referring to FIG. 5, the computer equipment 500
Include: memory 51, processor 52 and be stored in the computer program that can be run in memory 51 and on the processor 52, locates
It manages when device 52 executes computer program and realizes such as the step of one described in any item insurance benefits methods of embodiment.c
Method shown in embodiment one is able to carry out as each unit in this present embodiment, what the present embodiment was not described in detail
Part can refer to the related description to embodiment one.
The technical solution of the embodiment of the present invention has the advantages that
In the embodiment of the present invention, when receiving any Client-initiated settlement of insurance claim application, then obtain initiation user's
Claims Resolution reference data, and based on these Claims Resolution reference datas, it is based on machine learning algorithm, Claims Resolution is immediately arrived at and refers to the amount of money, subtract
Small person works' amount saves human cost, and compared to Claims Resolution reference gold artificial, that the Claims Resolution reference data based on user obtains
The error of volume is smaller.Therefore, technical solution provided in an embodiment of the present invention is able to solve in the prior art dependent on human subjective
Determine the larger problem of consumption of the amount for which loss settled to cost of human resources.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,
The specific work process of device and unit, can refer to corresponding processes in the foregoing method embodiment, and details are not described herein.
In several embodiments provided by the present invention, it should be understood that disclosed system, device and method can be with
It realizes by another way.For example, the apparatus embodiments described above are merely exemplary, for example, the unit
It divides, only a kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or group
Part can be combined or can be integrated into another system, or some features can be ignored or not executed.Another point, it is shown
Or the mutual coupling, direct-coupling or communication connection discussed can be through some interfaces, device or unit it is indirect
Coupling or communication connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.
It, can also be in addition, the functional units in various embodiments of the present invention may be integrated into one processing unit
It is that each unit physically exists alone, can also be integrated in one unit with two or more units.Above-mentioned integrated list
Member both can take the form of hardware realization, can also realize in the form of hardware adds SFU software functional unit.
The above-mentioned integrated unit being realized in the form of SFU software functional unit can store and computer-readable deposit at one
In storage media.Above-mentioned SFU software functional unit is stored in a storage medium, including some instructions are used so that a computer
It is each that device (can be personal computer, server or network equipment etc.) or processor (Processor) execute the present invention
The part steps of embodiment the method.And storage medium above-mentioned includes: USB flash disk, mobile hard disk, read-only memory (Read-
Only Memory, ROM), random access memory (Random Access Memory, RAM), magnetic or disk etc. it is various
It can store the medium of program code.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent substitution, improvement and etc. done be should be included within the scope of the present invention.
Claims (10)
1. a kind of insurance benefits method, which is characterized in that the described method includes:
Receive settlement of insurance claim application；
Obtain the Claims Resolution reference data of the initiation user of the settlement of insurance claim application, wherein the Claims Resolution reference data includes body
At least one of body situation data, Assets data and accident related data；
The Claims Resolution reference data for initiating user is handled using machine learning algorithm, obtains the initiation user
Claims Resolution refer to the amount of money；
The amount of money is referred to according to the Claims Resolution, insurance benefits are carried out to the initiation user.
2. the method according to claim 1, wherein the physical condition data include: medical records, h disease
History, personal injury record and at least one of history body class insurance purchase and Claims Resolution record；
The Assets data include: payment record, loan documentation, in transaction in assets data and purchase transaction data at least
It is a kind of；
The accident related data includes: accident responsibility determines that data and the scene of the accident illustrate at least one of data.
3. method according to claim 1 or 2, which is characterized in that the initiation for obtaining the settlement of insurance claim application is used
The Claims Resolution reference data at family, comprising:
Whether the storage location for identifying the Claims Resolution reference data for initiating user is itself storage location；
When the storage location is itself storage location, the Claims Resolution reference data for initiating user is called.
4. according to the method described in claim 3, it is characterized in that, the method also includes:
When the storage location is non-self storage location, the settlement of insurance claim request is carried to storage location transmission
Data call request；
The storage location is received according to the Claims Resolution reference data of data call request feedback.
5. the method according to claim 1, wherein described initiate user's to described using machine learning algorithm
The Claims Resolution reference data is handled, and obtains the Claims Resolution for initiating user with reference to the amount of money, comprising:
Settlement of insurance claim model is constructed, the input of the settlement of insurance claim model is the Claims Resolution reference data for initiating user,
The output of the settlement of insurance claim model is that the Claims Resolution refers to the amount of money；
The Claims Resolution reference data for initiating user is inputted into the settlement of insurance claim model, obtains the institute for initiating user
Claims Resolution is stated with reference to the amount of money.
6. according to the method described in claim 5, it is characterized in that, the building settlement of insurance claim model, comprising:
Initial settlement of insurance claim model is constructed, and obtains the history Claims Resolution record of multiple sample of users；
The initial settlement of insurance claim model is trained using history Claims Resolution record, obtains the settlement of insurance claim model.
7. the method according to claim 1, wherein described refer to the amount of money according to the Claims Resolution, to the initiation
User carries out insurance benefits, comprising:
The Claims Resolution is compensated as compensation pay-outs to the initiation user with reference to the amount of money.
8. a kind of insurance benefits device characterized by comprising
Receiving unit, for receiving settlement of insurance claim application；
Acquiring unit, the Claims Resolution reference data of the initiation user for obtaining the settlement of insurance claim application, wherein the Claims Resolution ginseng
Examining data includes at least one of physical condition data, Assets data and accident related data；
Processing unit is obtained for being handled using machine learning algorithm the Claims Resolution reference data for initiating user
The amount of money is referred to the Claims Resolution for initiating user；
Unit is compensated, for referring to the amount of money according to the Claims Resolution, insurance benefits are carried out to the initiation user.
9. a kind of computer equipment, including memory, processor and storage are in the memory and can be in the processor
The computer program of upper operation, which is characterized in that the processor realized when executing the computer program as claim 1 to
7 described in any item insurance benefits methods.
10. a kind of computer readable storage medium, which is characterized in that including computer executable instructions, when the computer can
It executes instruction when being run, to execute insurance benefits method as described in any one of claim 1 to 7.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810690847.5A CN109255718A (en) | 2018-06-28 | 2018-06-28 | Insurance benefits method and apparatus, computer equipment and readable storage medium storing program for executing |
| PCT/CN2018/111379 WO2020000803A1 (en) | 2018-06-28 | 2018-10-23 | Insurance compensation settlement method and apparatus, computer device and readable storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810690847.5A CN109255718A (en) | 2018-06-28 | 2018-06-28 | Insurance benefits method and apparatus, computer equipment and readable storage medium storing program for executing |
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| CN109255718A true CN109255718A (en) | 2019-01-22 |
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| CN201810690847.5A Pending CN109255718A (en) | 2018-06-28 | 2018-06-28 | Insurance benefits method and apparatus, computer equipment and readable storage medium storing program for executing |
Country Status (2)
| Country | Link |
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| CN (1) | CN109255718A (en) |
| WO (1) | WO2020000803A1 (en) |
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| CN110443716A (en) * | 2019-06-17 | 2019-11-12 | 中国平安财产保险股份有限公司 | Claims Resolution method, apparatus, computer equipment and storage medium |
| CN110689191A (en) * | 2019-09-24 | 2020-01-14 | 深圳前海微众银行股份有限公司 | Agricultural insurance compensation amount prediction method, device, equipment and readable storage medium |
| CN111275523A (en) * | 2020-01-17 | 2020-06-12 | 青梧桐有限责任公司 | Method and system for calculating recommended amount based on irregular data |
| CN111292159A (en) * | 2020-01-17 | 2020-06-16 | 青梧桐有限责任公司 | Method and system for calculating claim payment amount based on multi-factor influence |
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| Publication number | Publication date |
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| WO2020000803A1 (en) | 2020-01-02 |
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Application publication date: 20190122 |