CN104318477A - Vehicle insurance evaluation method based on big data - Google Patents
Vehicle insurance evaluation method based on big data Download PDFInfo
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- CN104318477A CN104318477A CN201410631996.6A CN201410631996A CN104318477A CN 104318477 A CN104318477 A CN 104318477A CN 201410631996 A CN201410631996 A CN 201410631996A CN 104318477 A CN104318477 A CN 104318477A
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Abstract
The invention belongs to the field of vehicle insurance evaluation, and provides a vehicle insurance evaluation method based on big data. The vehicle insurance evaluation method based on the big data comprises the steps that a vehicle insurance establishing request is received; vehicle insurance historical records of a user are obtained, and position information and time information of accident records in the vehicle insurance historical records are extracted; historical weather information corresponding to the time and the position are obtained from a data server according to the position information and the time information; a weather evaluation factor is obtained according to the weather information; the cost needed by current insurance buying is generated according to historical vehicle insurance information of the user. According to the vehicle insurance evaluation method based on the big data, the time information and the position information recoded through an existing method can be used and the weather information and/or the position information which can be obtained under the environment of the big data are used, so that a more accurate evaluation factor is worked out, and an accurate and personalized vehicle insurance evaluation scheme is provided for the user.
Description
Technical field
The present invention is applicable to car insurance evaluation areas, provides the method for a kind of car insurance based on large data assessment.
Background technology
The insurance assessment of vehicle is exactly in industry a complicated process.In existing assessment, generally based on the multinomial evaluation factor for fixing a price, such as vehicle class, driving frequency, operating range, berth etc., and the many index of client such as age, sex, occupation, driving age, Claims Resolution, driving license deduction of points etc. factor.To a certain extent, there is a correlativity in this multinomial Pricing Factor and contingency occurrence probability, and thus insurance company can roughly assess client.But, there is a problem in this existing method: the consideration of driving under various circumstances for user is still thorough not, and when insuring only with reference to the number of times be in danger former years, wherein, it is unilateral for calculating the evaluation factor that required insurance premium considers of insuring in prior art, and can not recall.
Summary of the invention
The development of large data technique, makes more accurate client risk evaluation become possibility.This large data analysis technique is not describe different clients with a kind of model.On the contrary, in conjunction with the relevant information provided during existing being in danger, fully can analyze the data in internet, thus the evaluation factor of car insurance expense calculating can be provided more comprehensively, more accurately.The object of the embodiment of the present invention is a kind of method providing car insurance based on large data to assess, to solve the problem of prior art.
The embodiment of the present invention is achieved in that on the one hand, the invention provides the method for a kind of car insurance based on large data assessment, said method comprising the steps of:
Receive the request of setting up car insurance; Obtain the car insurance historical record of user, and extract positional information and the temporal information of the record that is wherein in danger; The history weather information of corresponding time and position is obtained to data server according to described positional information and temporal information; According to described weather information, obtain meteorological evaluation factor; In conjunction with described user's history car insurance information, generate current required expense of insuring.
On the other hand, a kind of method that the present invention also provides car insurance based on large data to assess, said method comprising the steps of:
The reception request of being in danger, described in be in danger request comprise: user profile of being in danger, temporal information of being in danger, positional information of being in danger; The driving information being arranged on the Train-borne recorder on user's vehicle and recording is transferred according to user profile; According to the weather information of described be in danger temporal information and on this time relevant position of being in danger in positional information called data server; Generate according to described driving information, weather information and the menace level that is in danger rate evaluation factor of insuring, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user.
The beneficial effect of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention provides comprises: the embodiment of the present invention can in conjunction with the temporal information recorded in existing method and positional information, the weather information that can obtain under utilizing large data environment and/or positional information, thus calculate more accurate evaluation factor, for user provides more accurate and personalized car insurance evaluation scheme.
Accompanying drawing explanation
In order to be illustrated more clearly in the technical scheme in the embodiment of the present invention, be briefly described to the accompanying drawing used required in embodiment or description of the prior art below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is the system chart being applicable to the method for a kind of car insurance based on large data assessment that the embodiment of the present invention provides;
Fig. 2 is the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention provides;
Fig. 3 is the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention provides;
Fig. 4 is the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention provides;
Fig. 5 is the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention provides.
Embodiment
In order to make object of the present invention, technical scheme and advantage clearly understand, below in conjunction with drawings and Examples, the present invention is further elaborated.Should be appreciated that specific embodiment described herein only in order to explain the present invention, be not intended to limit the present invention.
Embodiment one
Be illustrated in figure 1 a kind of system chart being applicable to the method for the assessment of the car insurance based on large data that the present invention proposes provided by the invention, figure comprises: the PC terminal 104 of Train-borne recorder 102, insurance company, the server 106 of insurance company and data server 108, above-mentioned each equipment is according to more perfect system layout, during the method comprised in specific implementation the present invention, some equipment is optional, can specifically state in the particular embodiment.Below concrete being used as each terminal and server is clearly described.
Train-borne recorder 102, mainly based in user's vehicle install or extrapolation various sensors, such as: speed pickup, engine speed sensor etc., also comprise GPS locator, clock etc., the running time of real time record user vehicle, traveling-position, movement velocity, acceleration of motion and motion position angle.For the vehicle of some higher configurations, rain sensor, vehicle-mounted camera etc. can also be possessed, be configured with the vehicle of more multisensor or vehicle-mounted camera accordingly, road conditions before more real-time Weather information and car also just can be provided.For Train-borne recorder, it can set up data link by terrestrial communication networks 110 and the server 106 of insurance company, and described terrestrial communication networks comprises: 2G, 3G, 4G or future network.And by described data link passage, in real time, the mode in cycle or in the mode of request-reply, by each sensor of record in real time and/or historical data send to the server 106 of insurance company.
The server 106 of insurance company, is mainly used to the personal information storing different user, and the information of vehicles collected from Train-borne recorder 102, specifically comprises the temporal information that above-mentioned each sensor and GPS and clock generate.Except above-mentioned functions, the server 106 of insurance company also utilizes the network 110 of communication relay medium cable composition to be connected to data server 108 in internet, further, the history car insurance information, weather information, traffic road segment information etc. of user can be obtained from data server 108.
Data server 108, the storage medium that the finger that described data server 108 is general in the present embodiment utilizes Internet resources to link by insurance company server 106, such as described data server 108 can be: the data server of observatory, provide the server of user's history car insurance information query system, the routing information server of Department of Communications, or can also be to provide the enterprise-level server of relevant information of the present invention inquiry.In the present invention, be described in order to described data server does not distinguish by terseness one by one that describe, the content that those skilled in the art can describe in conjunction with known technology and the present invention goes to obtain corresponding data content in each data server 108 in internet, such as: history car insurance information of weather information, traffic road segment information, user etc.
The PC terminal 104 of insurance company, interactive function with the server 106 of insurance company is mainly provided, conveniently the history car insurance information of user can be presented to staff, and can based on the related data obtained in Train-borne recorder 102, such as: temporal information and positional information, server 106 to insurance company asks weather information and traffic road segment information (server 106 self being applicable to insurance company can store the associated vehicle had in data server 108 and insure relevant information), or ask weather information and traffic road segment information (being applicable to the situation of information relevant with car insurance in the server 106 not responsible storage data server 108 of insurance company) to data server 108.The PC terminal 104 of described insurance company is also for presenting the expense of car insurance of user for insuring, and this expense can be that the server 106 of insurance company calculates, and also can be that the PC terminal 104 of insurance company is calculated.In field of cloud calculation, traditional PC terminal all substitute by thin client, the computation process of described PC terminal has also been realized turning by the virtual machine in high in the clouds.
Embodiment two
After describing applicable system framework figure of the present invention, how to realize describing the present invention in conjunction with said system block diagram.Be illustrated in figure 2 the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention two provides, the method is mainly applicable to user and selects this insurance company to insure the situation of car insurance first, said method comprising the steps of:
In step 202., the request of setting up car insurance is received.
Concrete, this request can be that insurance company employee is inputted by the PC terminal 104 of insurance company.
Also can be that the portal website that user utilizes internet to log in insurance company by the user terminal of oneself realizes, namely received by the server 106 of insurance company and completed process.
In step 204, obtain the car insurance historical record of user, and extract positional information and the temporal information of the record that is wherein in danger.
Owing to come the user that insures as first time under normal circumstances, the server 106 of described insurance company do not have user data, therefore, the server 106 of insurance company will send the request message that carry the car insurance historical record of the acquisition user of user profile to data server 108, and the name and ID (identity number) card information etc. that usually carry in described request message can the contents of this user of unique identification.Data server 108 will return the history car insurance information of this user, comprise: the insure time limit, history of this user is insured the record violating the regulations etc. of the record that is in danger in period, user every year.Wherein, the record that is in danger also can comprise the positional information and temporal information of being in danger.Data server 108 is now servers of the history car insurance information for maintenance customer.
In step 206, the history weather information of corresponding time and position is obtained according to described positional information and temporal information to data server 108.
Now, data server 108 specifically refers to server in the Meteorological Unit relevant with Meteorological Services or enterprise servers of providing relevant weather to seek advice from etc.
In a step 208, according to described weather information, obtain meteorological evaluation factor.
Such as, better simply implementation is: described weather information, comprise: cloudy, cloudy, light rain, moderate rain, heavy rain, rain and snow mixed, shower, thunder shower etc. weather category, and corresponding weather category and evaluation factor can be safeguarded by table 1, described table 1 is specific as follows:
Table 1
| Weather category | Meteorological evaluation factor |
| Cloudy, cloudy | 0.99 |
| Light rain, moderate rain | 0.98 |
| Heavy rain | 0.97 |
| Rain and snow mixed | 0.96 |
| Shower, thunder shower | 0.95 |
In step 210, in conjunction with the history car insurance information of described user, generate current required expense of insuring.
The use-pattern of the meteorological evaluation factor described in table 1 is exactly as discount rate, carry out product calculation with the car insurance expense initial value calculated based on this user's history car insurance information, and do required for server 106 or PC terminal 104 from table 1, match corresponding meteorological evaluation factor according to weather information exactly.Wherein, based on the car insurance expense that this user's history car insurance information calculates, based on vehicle class, driving frequency, operating range, berth etc. in reference prior art, and the car insurance expense that the many index of client such as age, sex, occupation, driving age, Claims Resolution, driving license deduction of points etc. factor calculates.
The use-pattern described in the particular content of meteorological evaluation factor described in above-mentioned steps 208 and step 210, is only the one in all multimodes, not does particular determination to it at this.
The embodiment of the present invention can in conjunction with the positional information of the record that is in danger recorded in existing method and temporal information, the weather information that can obtain under utilizing large data environment, thus calculate more accurate evaluation factor, for user provides more accurate and personalized car insurance evaluation scheme.Owing to not considering weather conditions when being in danger in prior art, and user also can not carry this parameter when insuring, therefore, embodiment two provided by the invention is just by the record that is in danger of insuring in information that user provides, under the overall situation of large data network, find the weather information of being in danger of history, thus, can be extra the reference factor of a reference factor as generating car insurance expense is provided, make to assess the scheme of insurance premium more accurately, rationally.
Embodiment three
The method of a kind of assessment of the car insurance based on large data provided by the invention is being described by embodiment two, can more accurate Calculation car insurance expense, relate to the information of existing history car insurance being omitted, utilize the platform of large data network, it is excavated again and is used as car insurance calculated factor.The present embodiment three is based in content basis disclosed in embodiment two, excavates large data network further, thus more fully can consider that history is in danger situation.Be illustrated in figure 3 the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention three provides, wherein step 202,204,206, the description of 208 and explaining as described in embodiment two, therefore, repeat no more in the present embodiment three, said method comprising the steps of:
In step 202., the request of setting up car insurance is received.
In step 204, obtain the car insurance historical record of user, and extract positional information and the temporal information of the record that is wherein in danger.
In step 206, the history weather information of corresponding time and position is obtained according to described positional information and temporal information to data server.
In step 207, the operating habit of user is calculated according to the Velicle motion velocity in the traveling record data of user, vehicle movement acceleration and direction of vehicle movement angle.
Described Velicle motion velocity, vehicle movement acceleration and direction of vehicle movement angle can calculate average overall travel speed, the frequency of overtaking other vehicles of user, speed etc. of overtaking other vehicles of user of user, and be used for the operating habit assessed in user driving habits be outstanding, good, in, poor.
Preferably, the driving habits of described user can also comprise and travels according to user the run routing information recorded in record data, obtain the custom of user's running section, thus be the section often got congestion according to the section that user travels usually, or traffic hazard section occurred frequently etc. obtains the evaluation factor of user habit.This preferred scheme can realize as the supplemental content of step 207, also can as an alternative 207 technology contents realize.
In a step 208, according to described weather information, obtain meteorological evaluation factor.
In step 209, the driving habits evaluation factor of user is obtained according to described driving habits.
Such as, to be accustomed to reference to operating habit in user's driving habits and driving path simultaneously, form 2 is referred to:
Table 2
The computing formula of described driving habits evaluation factor, is specially: select the evaluation factor under relative users operating habit and driving path custom to do product, thus obtain the evaluation factor of the driving habits of this user.
In the step 212, in conjunction with described user's history car insurance information, described meteorological evaluation factor and user side driving habits evaluation factor, current required expense of insuring is generated.
Table 1 and the meteorology described in table 2 are assessed because commenting son, the use-pattern of driving habits evaluation factor is exactly as discount rate, and carries out product calculation based on the car insurance expense initial value that this user's history car insurance information calculates.The use-pattern described in the particular content of meteorological evaluation factor described in above-mentioned steps 209 and step 212, is only the one in all multimodes, not does particular determination to it at this.
In the present embodiment, step 206 and step 207 can be adopt parallel mode to carry out simultaneously, also can be adopt serial mode to complete successively, and do special restriction not based on the sequence number of described step.
The embodiment of the present invention can in conjunction with the positional information of the record that is in danger recorded in existing method and temporal information, the weather information that can obtain under utilizing large data environment, thus calculate more accurate evaluation factor, for user provides more accurate and personalized car insurance evaluation scheme.The driving habits of user considers into by the present embodiment, further perfect car insurance evaluation scheme.
Embodiment four
Above-described embodiment two and embodiment three mainly insurance company how for the user having history car insurance record, the additional information that large data network can be utilized to excavate it be in danger when its first time insures, thus provide the method that more can accurately calculate car insurance expense.Under large data network environment, inventor has found further, and this technological means can also be applied to the vehicle user of having insured, and is specially when it is in danger, and calculates the rate evaluation factor of insuring in this user coming year.So by embodiment four, specifically introduce the realization under this scene.Be illustrated in figure 4 the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention four provides, this example comprises:
In step 402, receive being in danger request, described in be in danger ask comprise: user profile of being in danger, temporal information of being in danger, positional information of being in danger.
Concrete, this request can be that insurance company employee is inputted by the PC terminal 104 of insurance company.
Also can be that the portal website that user utilizes internet to log in insurance company by the user terminal of oneself realizes, namely received by the server 106 of insurance company and completed process.
In step 404, the driving information being arranged on the Train-borne recorder on user's vehicle and recording is transferred according to user profile.
The driving information that described Train-borne recorder records comprise in following parameter one or more: the moment that when being in danger, vehicle travels, vehicle travel the mileage number of duration, vehicle traveling-position, Velicle motion velocity, vehicle movement acceleration, vehicle movement position angle and vehicle.
In a step 406, obtain with positional information of being in danger the weather information that this time goes up relevant position according to described temporal information of being in danger.
Due to the server 106 of described insurance company under normal circumstances not having weather information, therefore, the server 106 of insurance company will send the request message that carry be in danger temporal information and positional information of being in danger to data server 108.Data server 108 will return the weather information of this time upper relevant position.
In a step 408, generate according to described driving information, weather information and the menace level that is in danger rate evaluation factor of insuring, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user.
Optionally, the simplest mode is exactly adopt such as embodiment two and the product mode described by embodiment three kinds; Optionally, the mode usually adopted in prior art can also be utilized, at this, repeat no more.
The embodiment of the present invention can in conjunction with user profile of being in danger, temporal information of being in danger, the positional information of being in danger comprised in the request of being in danger in existing method, the weather information that can obtain under utilizing large data environment, thus calculate more accurate evaluation factor, for user provides more accurate and personalized car insurance evaluation scheme.The present embodiment scheme comparatively prior art, can to provide more accurately when Second Year renews car insurance, more personalized car insurance expense.
Embodiment five
Except as described in embodiment four, utilize large data network calculate user insure rate evaluation factor time, using the weather information of being in danger as with reference to outside factor, can also as described in embodiment three, using traffic road segment information as with reference to factor, the calculating of rate evaluation factor of insuring can be joined, specifically, be illustrated in figure 5 the process flow diagram of the method for a kind of assessment of the car insurance based on large data that the embodiment of the present invention five provides, this example comprises:
In step 402, receive being in danger request, described in be in danger ask comprise: user profile of being in danger, temporal information of being in danger, positional information of being in danger.
In step 404, the driving information being arranged on the Train-borne recorder on user's vehicle and recording is transferred according to user profile.
In a step 406, according to the weather information of described be in danger temporal information and on this time relevant position of being in danger in positional information called data server.
In step 407, according to the road section information A of described be in danger temporal information and on this time relevant position of being in danger in positional information called data server.
In step 409, generate according to described driving information, weather information, road section information A and the menace level that is in danger and to insure rate evaluation factor, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user.
The embodiment of the present invention can in conjunction with user profile of being in danger, temporal information of being in danger, the positional information of being in danger comprised in the request of being in danger in existing method, the weather information that can obtain under utilizing large data environment, thus calculate more accurate evaluation factor, for user provides more accurate and personalized car insurance evaluation scheme.
Those of ordinary skill in the art it is also understood that, the all or part of step realized in above-described embodiment method is that the hardware that can carry out instruction relevant by program has come, described program can be stored in a computer read/write memory medium, described storage medium, comprises ROM/RAM, disk, CD etc.
The foregoing is only preferred embodiment of the present invention, not in order to limit the present invention, all any amendments done within the spirit and principles in the present invention, equivalent replacement and improvement etc., all should be included within protection scope of the present invention.
Claims (8)
1., based on the method that the car insurance of large data is assessed, it is characterized in that, described method comprises:
Receive the request of setting up car insurance;
Obtain the car insurance historical record of user, and extract positional information and the temporal information of the record that is wherein in danger;
The history weather information of corresponding time and position is obtained to data server according to described positional information and temporal information;
According to described history weather information, obtain meteorological evaluation factor;
In conjunction with described user's history car insurance information, generate current required expense of insuring.
2. the method for claim 1, it is characterized in that, can provide the traveling record data of its Tachographs or server can from related Data Services device when the traveling record data of calling and obtaining user when described user, user's history car insurance information described in described combination, generate current required expense of insuring, specifically comprise:
The operating habit of user is determined according to the movement velocity in the traveling record data of user, acceleration of motion and direction of motion angle;
The driving habits evaluation factor of user is obtained according to described operating habit;
In conjunction with described user's history car insurance information, described meteorological evaluation factor and described driving habits evaluation factor, generate current required expense of insuring.
3. the method for claim 1, it is characterized in that, can provide the traveling record data of its Tachographs or server can from related Data Services device when the traveling record data of calling and obtaining user when described user, the run routing information of user is recorded in described traveling record data, user's history car insurance information described in described combination, generate current required expense of insuring, specifically comprise:
Determine that user travels high-frequency section according to the run routing information of user;
Blocking up and/or characteristic of being in danger according to described high-frequency section, obtains the driving habits evaluation factor of user;
In conjunction with described user's history car insurance information, described meteorological evaluation factor and described driving habits evaluation factor, generate current required expense of insuring.
4. the method as described in as arbitrary in claim 1-3, it is characterized in that, user's history car insurance information described in described combination, generates current required expense of insuring, specifically comprises:
Generate the evaluation factor of current expense institute foundation of insuring required, except described meteorological evaluation factor, also comprise: the mileage number evaluation factor of user's vehicle and the history of user record violating the regulations evaluation factor.
5., based on the method that the car insurance of large data is assessed, it is characterized in that, described method comprises:
The reception request of being in danger, described in be in danger request comprise: user profile of being in danger, temporal information of being in danger, positional information of being in danger;
The driving information being arranged on the Train-borne recorder on user's vehicle and recording is transferred according to user profile;
According to the weather information of described be in danger temporal information and on this time relevant position of being in danger in positional information called data server;
Generate according to described driving information, weather information and the menace level that is in danger rate evaluation factor of insuring, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user.
6. method as claimed in claim 5, is characterized in that, the driving information that described Train-borne recorder records comprise in following parameter one or more:
The moment that when being in danger, vehicle travels, vehicle travel the mileage number of duration, vehicle traveling-position, Velicle motion velocity, vehicle movement acceleration, vehicle movement position angle and vehicle.
7. the method as described in claim 5 or 6, is characterized in that, after the described reception request of being in danger, also comprises:
According to the road section information A of described be in danger temporal information and on this time relevant position of being in danger in positional information called data server;
Then, describedly generate according to described driving information, weather information and the menace level that is in danger rate evaluation factor of insuring, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user, specifically comprise:
Generate according to described driving information, weather information, road section information A and the menace level that is in danger and to insure rate evaluation factor, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user.
8. the method as described in as arbitrary in claim 5 or 6, is characterized in that, after transferring and be arranged on driving information that the Train-borne recorder on user's vehicle records, also comprises according to user profile:
Road section information B when acceleration derivation vehicle is in danger is travelled according to the Vehicle Speed recorded in Train-borne recorder and vehicle;
Then, describedly generate according to described driving information, weather information and the menace level that is in danger rate evaluation factor of insuring, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user, specifically comprise:
Generate according to described driving information, weather information, road section information B and the menace level that is in danger and to insure rate evaluation factor, described in insure the calculated factor of expense that rate evaluation factor will insure as follow-up described user.
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