CN115393107A - Car insurance pricing method and device, electronic equipment and computer storage medium - Google Patents
Car insurance pricing method and device, electronic equipment and computer storage medium Download PDFInfo
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Abstract
The application discloses a car insurance pricing method, a car insurance pricing device, electronic equipment and a computer storage medium, which can be used in the distributed field, the big data field or the financial field. The method comprises the steps of obtaining an insurance pricing query instruction input by a user, and sending a vehicle identifier carried in the insurance query instruction to a second participant so that the second participant can obtain corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user. Therefore, the accuracy of car insurance pricing can be improved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a car insurance pricing method, a car insurance pricing device, electronic equipment and a computer storage medium.
Background
The traditional car insurance pricing method is that the car is priced, the premium is confirmed according to the quality of the car, and the using condition of the car in the actual process is not realized. Insurance pricing by means of a slave vehicle alone can result in inaccurate pricing.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for pricing a vehicle insurance, an electronic device, and a computer storage medium, so as to solve the problem in the prior art that pricing is not accurate.
In order to achieve the above object, the embodiments of the present invention provide the following technical solutions:
the first aspect of the embodiment of the invention shows a car insurance pricing method, which comprises the following steps: acquiring a vehicle insurance pricing query instruction input by a user, and sending a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier;
when first vehicle data and an authorization instruction sent by a second party are received, acquiring corresponding second vehicle data based on the vehicle identification;
waking up the car insurance pricing model based on the authorization instruction;
processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training;
and recommending the car insurance pricing of the vehicle to a user.
Optionally, the process of training to obtain the car insurance pricing model based on the sample data includes:
determining a participant for constructing a car insurance pricing model;
for each participant, acquiring sample data sent by all the participants, wherein the sample data is data held by each participant, and processing the held data to obtain intermediate result data;
and aiming at each participant, training sample data and a pricing label by using a federal learning algorithm to obtain a car insurance pricing model.
Optionally, receiving the vehicle data and the authorization instruction sent by the second party includes:
judging whether vehicle data and an authorization instruction sent by a second party are received;
and if the vehicle identification is received, executing the step of acquiring corresponding second vehicle data based on the vehicle identification.
Optionally, the obtaining corresponding second vehicle data based on the vehicle identifier includes:
and querying second vehicle data corresponding to the vehicle identification in a database based on the vehicle identification.
A second aspect of the embodiment of the present invention shows a car insurance pricing apparatus, applied to a first party, the apparatus including:
the system comprises an acquisition unit, a first vehicle data processing unit and a second vehicle data processing unit, wherein the acquisition unit is used for acquiring a vehicle insurance pricing query instruction input by a user and sending a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification;
a wake-up unit configured to wake up the car insurance pricing model based on the authorization instruction;
the processing unit is used for processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model and outputting vehicle insurance pricing of the vehicle, and the vehicle insurance pricing model is obtained based on training of the building unit;
and the recommending unit is used for recommending the car insurance pricing of the vehicle to the user.
Optionally, the building unit is configured to: determining a participant for constructing a car insurance pricing model;
for each participant, acquiring sample data sent by all the participants, wherein the sample data is data held by each participant, and processing the held data to obtain intermediate result data;
and aiming at each participant, training sample data and a pricing label by using a federal learning algorithm to obtain a car insurance pricing model.
Optionally, the obtaining unit that receives the vehicle data and the authorization instruction sent by the second party is specifically configured to: judging whether vehicle data and an authorization instruction sent by a second party are received;
and if the vehicle identification is received, acquiring corresponding second vehicle data based on the vehicle identification.
Optionally, the obtaining unit that obtains corresponding second vehicle data based on the vehicle identifier is specifically configured to: and querying second vehicle data corresponding to the vehicle identification in a database based on the vehicle identification.
A third aspect of the embodiments of the present invention shows an electronic device, where the electronic device is configured to run a program, where the program executes the method for pricing car insurance shown in the first aspect of the embodiments of the present invention.
A fourth aspect of the embodiments of the present invention shows a computer storage medium, where the storage medium includes a storage program, where the program, when executed, controls a device in which the storage medium is located to perform the insurance pricing method shown in the first aspect of the embodiments of the present invention.
Based on the vehicle insurance pricing method, the device, the electronic equipment and the computer storage medium provided by the embodiment of the invention, the method comprises the following steps: acquiring an insurance pricing query instruction input by a user, and sending a vehicle identifier carried in the insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user. In the application of the car insurance pricing model, any party, namely a first party initiates a car insurance pricing inquiry request, the unique identification of the car is generally transmitted to a second party, namely other parties in an encrypted manner, all parties cooperate in a joint manner, and the car insurance pricing of the car is output to a user of the initiator through the car insurance pricing model. Therefore, the accuracy of car insurance pricing can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic diagram illustrating interaction of parties according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating a method for pricing a car insurance according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a car insurance pricing system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In this application, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
It should be noted that the car insurance pricing method, the car insurance pricing device, the electronic equipment and the computer storage medium provided by the invention can be used in the distributed field, the big data field or the financial field. The above description is only an example, and does not limit the application field of the car insurance pricing method, apparatus, electronic device and computer storage medium provided by the present invention.
In the embodiment of the invention, an automobile insurance pricing query instruction input by a user is obtained, and an automobile identifier carried in the automobile insurance query instruction is sent to a second participant, so that the second participant can obtain corresponding first automobile data based on the automobile identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user. In the application of the car insurance pricing model, any party, namely a first party initiates a car insurance pricing inquiry request, the unique identification of the car is generally transmitted to a second party, namely other parties in an encrypted manner, all parties cooperate in a joint manner, and the car insurance pricing of the car is output to a user of the initiator through the car insurance pricing model. Therefore, the accuracy of car insurance pricing can be improved.
Referring to fig. 1, an interaction diagram of each participant is shown in the embodiment of the present invention;
the parties 10 are connected to each other by encrypted communication.
The participators can be data providers and/or data users such as insurance companies, personnel service centers, navigation APP servers, smart city traffic bureau systems, high-speed data acquisition centers and the like.
Any one of the parties 10 may be a first party and a second party. The first participant is a data provider and the second participant is a data consumer.
The process of pricing vehicle insurance based on implementation of the vehicle insurance based on the participants comprises the following steps:
a first participant acquires a vehicle insurance pricing query instruction input by a user based on the front end of the first participant, and sends a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that other participants can acquire corresponding first vehicle data based on the vehicle identifier;
when first vehicle data and an authorization instruction sent by a second party are received, second vehicle data corresponding to the second party are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing to the user.
In the embodiment of the invention, an insurance pricing query instruction input by a user is obtained, and a vehicle identifier carried in the insurance query instruction is sent to a second participant, so that the second participant can obtain corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user. In the application of the car insurance pricing model, any party, namely a first party initiates a car insurance pricing inquiry request, the unique identification of the car is generally transmitted to a second party, namely other parties in an encrypted manner, all parties cooperate in a joint manner, and the car insurance pricing of the car is output to a user of the initiator through the car insurance pricing model. Therefore, the accuracy of car insurance pricing can be improved.
Referring to fig. 2, a flow chart of the car insurance pricing method according to the embodiment of the present invention is shown, where the method includes:
step S201: the method comprises the steps of obtaining a vehicle insurance pricing inquiry instruction input by a user, and sending a vehicle identifier carried in the vehicle insurance inquiry instruction to a second participant so that the second participant can obtain corresponding first vehicle data based on the vehicle identifier.
Optionally, the user may input an insurance pricing query instruction carrying the vehicle identifier based on the front end of the first party.
It should be noted that the vehicle identification can uniquely identify the vehicle, such as an engine number.
In the process of implementing step S201 specifically, when receiving an insurance pricing query instruction input by a user, the first party transmits encrypted vehicle identifiers carried in the insurance query instruction to the second party.
Wherein the number of second parties is at least 1.
Optionally, each second participant obtains first vehicle data related to the vehicle stored by the second participant based on the vehicle identifier, and transmits the first vehicle data and the authorization instruction to the participant who sent the vehicle identifier.
The first vehicle data may be slave vehicle data, slave person data, and/or slave behavior data; the first vehicle data comprises data of the respective participant.
The first and second parties both belong to parties.
It should be noted that, the data distribution may be in the participant insurance company from the dimensions of the vehicle data including the brand of the vehicle, the age of the vehicle, the mileage, the price estimation, the number of times of coming out of insurance per year, etc.
From the people data: the data of the car owners specifically comprise dimensions such as age, gender, occupation, driving age, residence, self-driving frequency, driving routes and driving road conditions, and the data are distributed in a personnel service center of the participants or a navigation APP server of the participants.
The slave behavior data comprise dimensions of driving acceleration, deceleration and braking times, rapid acceleration, carelessness, dangerous driving, overspeed conditions and the like of the vehicle, and the data are distributed in participants such as a participant smart city traffic administration, a participant high-speed data acquisition center and the like.
Step S202: and judging whether the vehicle data and the authorization instruction sent by the second party are received or not, executing the step S203 when the first vehicle data and the authorization instruction sent by the second party are received, and if not, continuing to detect, namely executing the step S202.
In the process of implementing step S202 specifically, whether the vehicle data and the authorization instruction sent by each second party are received is detected in real time, when the first vehicle data and the authorization instruction sent by the second party are received, step S203 is executed, and if not, the detection is continued, that is, step S202 is executed.
It should be noted that the second vehicle data may also be slave vehicle data, slave person data and/or slave behavior data.
Step S203: and acquiring corresponding second vehicle data based on the vehicle identification.
In the process of implementing step S203 specifically, when first vehicle data and an authorization instruction sent by each second party are received, second vehicle data corresponding to the vehicle identifier in the database is queried based on the vehicle identifier.
Step S204: waking up the car insurance pricing model based on the authorization instruction.
In the process of implementing step S204 specifically, if receiving authorization instructions sent by all the second parties, it is determined that the first party can use the car insurance pricing model currently.
It should be noted that each participant stores its own data and does not interact with other participants.
The car insurance pricing model is respectively stored in each participant, and when any participant, namely a first participant is used, the authorization of other participants, namely a second participant needs to be obtained.
Step S205: and processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing.
In step S205, the car insurance pricing model is trained based on sample data.
It should be noted that the process of training the car insurance pricing model based on the sample data includes the following steps:
step S11: and determining the participants for constructing the car insurance pricing model.
In the process of implementing step S11, the provider that needs to provide the vehicle data is used as a participant for building the vehicle insurance pricing model.
Step S12: and acquiring sample data sent by all the participants aiming at each participant.
In step S12, the sample data is data held by each participant, and the held data is processed to obtain intermediate result data.
In the process of implementing step S12, a common sample is found for each participant on the premise of encryption because the sample ranges of each participant are different. And aiming at each participant, acquiring own held data, and processing the held data by data source combing, data cleaning, abnormal value processing, characteristic engineering and the like to obtain intermediate result data.
It should be noted that, the encryption technology such as differential privacy may be adopted to obtain the sample data in a manner of implementing encryption intersection without revealing privacy of other data.
The data source combing means that each participant combs local slave vehicle, slave person and slave behavior data dimensions related to vehicle insurance pricing because the data dimensions of each participant for mastering customers are different.
The data cleaning and abnormal value processing refers to null value filling, numerical value statistics, quantitative analysis and other processing.
Further, it should be noted that different parties may adopt different feature engineering modes due to different data conditions, and the module finally forms feature data with the unique vehicle identifier as the primary key.
Step S13: and aiming at each participant, training sample data and a pricing label by using a federal learning algorithm to obtain a car insurance pricing model.
In the specific step S13, a participant is usually required to provide a pricing label for modeling, and the present invention uses the car insurance pricing quota as a modeling target, so that the insurance company provides the pricing label. A decentralized network architecture is employed in which each participant uses only local data to cooperatively train the same machine learning model, and each participant uses secure links to transmit model parameters and intermediate result information between each other.
In order to secure communication between any two parties, an encryption mechanism, such as encryption based on a public key, is required to perform encryption.
In the invention, each participant grasps a part of model parameters, and when carrying out encryption model training, each participant cooperates to carry out the transmission of model gradient and intermediate result. After training is completed, all the participants respectively have pricing models which are all used for car insurance, but the pricing models can be used only by authorization of all the participants.
It should be noted that, each participant cooperates to perform machine learning model training, and the machine learning algorithm may adopt algorithms such as random forest, xgboost, GBDT, lightGBM, and the like.
For example: suppose there are two parties a and b, party a determines the held data relating to the vehicle and intermediate results, i.e. sample data, based on the local data; party b also determines held data relating to the vehicle and intermediate results, i.e. sample data, based on the local data; the two parties transmit the encrypted information to the other party, and b is assumed to be the party with the label, such as an insurance company; and the participators a and b respectively train based on the sample data until the calculated loss of the participators converges or the set training time or turn is reached, and the train insurance pricing model which is trained is determined.
In the process of implementing step S205 specifically, the first vehicle data and the second vehicle data are input into the trained vehicle insurance pricing model, so that the trained vehicle insurance pricing model is used to process the first vehicle data and the second vehicle data, and vehicle insurance pricing corresponding to the vehicle is output.
Step S206: and recommending the car insurance pricing to the user.
In the process of implementing step S206, the user is informed of the vehicle insurance pricing corresponding to the vehicle in an informational manner.
In the embodiment of the invention, an insurance pricing query instruction input by a user is obtained, and a vehicle identifier carried in the insurance query instruction is sent to a second participant, so that the second participant can obtain corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user. In the application of the car insurance pricing model, any party, namely a first party initiates a car insurance pricing inquiry request, the unique identification of the car is generally transmitted to a second party, namely other parties in an encrypted manner, all parties cooperate in a joint manner, and the car insurance pricing of the car is output to a user of the initiator through the car insurance pricing model. Therefore, the accuracy of car insurance pricing can be improved.
Based on the above vehicle insurance pricing method shown in the embodiment of the present invention, correspondingly, the embodiment of the present invention further discloses a schematic structural diagram of a vehicle insurance pricing device, and as shown in fig. 3, the device includes:
the acquiring unit 301 is configured to acquire a vehicle insurance pricing query instruction input by a user, and send a vehicle identifier carried in the vehicle insurance query instruction to a second party, so that the second party acquires corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification;
a wake-up unit 302 configured to wake up the car insurance pricing model based on the authorization instruction;
the processing unit 303 is configured to process the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and output vehicle insurance pricing of the vehicle, where the vehicle insurance pricing model is trained based on the building unit 305;
and the recommending unit 304 is used for recommending the vehicle insurance pricing of the vehicle to the user.
It should be noted that, the specific principle and the implementation process of each unit in the car insurance pricing device disclosed in the embodiment of the present application are the same as those of the car insurance pricing method disclosed in the embodiment of the present application, and reference may be made to corresponding parts in the car insurance pricing method disclosed in the embodiment of the present application, which are not described herein again.
In the embodiment of the invention, an insurance pricing query instruction input by a user is obtained, and a vehicle identifier carried in the insurance query instruction is sent to a second participant, so that the second participant can obtain corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user. In the application of the car insurance pricing model, any party, namely a first party initiates a car insurance pricing inquiry request, the unique identification of the car is generally transmitted to a second party, namely other parties in an encrypted manner, all parties cooperate in a joint manner, and the car insurance pricing of the car is output to a user of the initiator through the car insurance pricing model. Therefore, the accuracy of car insurance pricing can be improved.
Optionally, based on the car insurance pricing apparatus disclosed in the foregoing embodiment of the present disclosure, the constructing unit 305 is configured to: determining a participant for constructing a car insurance pricing model;
for each participant, acquiring sample data sent by all the participants, wherein the sample data is data held by each participant, and processing the held data to obtain intermediate result data;
and aiming at each participant, training sample data and a pricing label by using a federal learning algorithm to obtain a car insurance pricing model.
Optionally, based on the car insurance pricing apparatus disclosed in the embodiment of the present disclosure, the obtaining unit 302 that receives the vehicle data and the authorization instruction sent by the second party is specifically configured to: judging whether vehicle data and an authorization instruction sent by a second party are received;
and if the vehicle identification is received, acquiring corresponding second vehicle data based on the vehicle identification.
Optionally, based on the car insurance pricing device disclosed in the embodiment of the present disclosure, the obtaining unit 301 for obtaining corresponding second vehicle data based on the vehicle identifier is specifically configured to: and querying second vehicle data corresponding to the vehicle identification in a database based on the vehicle identification.
Based on the car insurance pricing device disclosed by the embodiment of the disclosure, the modules can be realized by a hardware device consisting of a processor and a memory. Specifically, the modules are stored in a memory as program units, and a processor executes the program units stored in the memory to realize the pricing of vehicle insurance.
The processor comprises a kernel, and the kernel calls a corresponding program unit from the memory. The kernel can be set to be one or more, and the car insurance pricing is realized by adjusting the kernel parameters.
The disclosed embodiment provides a computer storage medium, which includes a stored text processing program, wherein the program realizes the car insurance pricing method described in fig. 2 when being executed by a processor.
The disclosed embodiment provides a processor for running a program, wherein the program executes the vehicle insurance pricing method described in fig. 2.
The disclosed embodiment provides an electronic device, and the electronic device in the disclosed embodiment can be a server, a PC, a PAD, a mobile phone and the like.
The electronic device includes at least one processor, and at least one memory connected with the processor, and a bus.
The processor and the memory complete mutual communication through the bus. A processor for executing the program stored in the memory.
A memory for storing a program for at least: acquiring a vehicle insurance pricing query instruction input by a user, and sending a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, corresponding second vehicle data are obtained based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user.
The present application further provides a computer program product adapted to perform a program for initializing the following method steps when executed on an electronic device: acquiring a vehicle insurance pricing query instruction input by a user, and sending a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second party are received, acquiring corresponding second vehicle data based on the vehicle identification; waking up the car insurance pricing model based on the authorization instruction; processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training; and recommending the car insurance pricing of the vehicle to a user.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a device includes one or more processors (CPUs), memory, and a bus. The device may also include input/output interfaces, network interfaces, and the like.
The memory may include volatile memory in a computer readable medium, random Access Memory (RAM) and/or nonvolatile memory such as Read Only Memory (ROM) or flash memory (flash RAM), and the memory includes at least one memory chip. The memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Disks (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, the system or system embodiments are substantially similar to the method embodiments and therefore are described in a relatively simple manner, and reference may be made to some of the descriptions of the method embodiments for related points. The above-described system and system embodiments are only illustrative, wherein the units described as separate parts may or may not be physically separate, and the parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Those of skill would further appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for pricing car insurance, applied to a first party, the method comprising:
acquiring a vehicle insurance pricing query instruction input by a user, and sending a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier, wherein the first participant and the second participant both belong to participants;
when first vehicle data and an authorization instruction sent by a second party are received, acquiring corresponding second vehicle data based on the vehicle identification;
waking up the car insurance pricing model based on the authorization instruction;
processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model, and outputting vehicle insurance pricing of the vehicle, wherein the vehicle insurance pricing model is obtained based on sample data training;
and recommending the car insurance pricing of the vehicle to a user.
2. The method of claim 1, wherein training the process of obtaining the car insurance pricing model based on the sample data comprises:
determining a participant for constructing a car insurance pricing model;
for each participant, acquiring sample data sent by all the participants, wherein the sample data is data held by each participant, and processing the held data to obtain intermediate result data;
and aiming at each participant, training sample data and a pricing label by using a federal learning algorithm to obtain a car insurance pricing model.
3. The method of claim 1, wherein receiving the vehicle data and the authorization instruction sent by the second party comprises:
judging whether vehicle data and an authorization instruction sent by a second party are received;
and if the vehicle identification is received, executing the step of acquiring corresponding second vehicle data based on the vehicle identification.
4. The method of claim 1, wherein the obtaining corresponding second vehicle data based on the vehicle identification comprises:
and querying second vehicle data corresponding to the vehicle identification in a database based on the vehicle identification.
5. An insurance pricing apparatus for use with a first party, the apparatus comprising:
the system comprises an acquisition unit, a first vehicle data processing unit and a second vehicle data processing unit, wherein the acquisition unit is used for acquiring a vehicle insurance pricing query instruction input by a user and sending a vehicle identifier carried in the vehicle insurance query instruction to a second participant so that the second participant can acquire corresponding first vehicle data based on the vehicle identifier; when first vehicle data and an authorization instruction sent by a second participant are received, acquiring corresponding second vehicle data based on the vehicle identification, wherein the first participant and the second participant both belong to participants;
a wake-up unit configured to wake up the car insurance pricing model based on the authorization instruction;
the processing unit is used for processing the first vehicle data and the second vehicle data based on the vehicle insurance pricing model and outputting vehicle insurance pricing of the vehicle, and the vehicle insurance pricing model is obtained based on training of the building unit;
and the recommending unit is used for recommending the vehicle insurance pricing of the vehicle to the user.
6. The apparatus of claim 5, wherein the construction unit is configured to: determining a participant for constructing a car insurance pricing model;
for each participant, acquiring sample data sent by all the participants, wherein the sample data is data held by each participant, and processing the held data to obtain intermediate result data;
and aiming at each participant, training sample data and a pricing label by using a federal learning algorithm to obtain a car insurance pricing model.
7. The apparatus according to claim 5, wherein the obtaining unit that receives the vehicle data and the authorization instruction sent by the second party is specifically configured to: judging whether vehicle data and an authorization instruction sent by a second party are received;
and if the vehicle identification is received, acquiring corresponding second vehicle data based on the vehicle identification.
8. The apparatus according to claim 5, wherein the obtaining unit that obtains the corresponding second vehicle data based on the vehicle identifier is specifically configured to: and querying second vehicle data corresponding to the vehicle identification in a database based on the vehicle identification.
9. An electronic device, wherein the electronic device is configured to run a program, wherein the program when running performs the method of pricing insurance vehicle insurance as claimed in any of claims 1 to 4.
10. A computer storage medium, characterized in that the storage medium comprises a stored program, wherein the program, when running, controls a device on which the storage medium is located to execute the vehicle insurance pricing method according to any one of claims 1-4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211054942.9A CN115393107A (en) | 2022-08-31 | 2022-08-31 | Car insurance pricing method and device, electronic equipment and computer storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211054942.9A CN115393107A (en) | 2022-08-31 | 2022-08-31 | Car insurance pricing method and device, electronic equipment and computer storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115393107A true CN115393107A (en) | 2022-11-25 |
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ID=84124044
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202211054942.9A Pending CN115393107A (en) | 2022-08-31 | 2022-08-31 | Car insurance pricing method and device, electronic equipment and computer storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115393107A (en) |
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2022
- 2022-08-31 CN CN202211054942.9A patent/CN115393107A/en active Pending
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