CN111651473B - Policy generation method, device, equipment and computer readable storage medium - Google Patents
Policy generation method, device, equipment and computer readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention provides a policy generation method, a device, equipment and a computer readable storage medium, wherein the method comprises the following steps: acquiring vehicle identification information input by a user through a policy generation interface; determining a user insurance type corresponding to the user according to the vehicle identification information; acquiring the insuring basic information corresponding to the vehicle identification information from a database corresponding to the user insuring type according to the user insuring type; acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information, and acquiring corresponding ticket data in the current period from the traffic management platform; and generating a current policy corresponding to the vehicle identification information according to the applied basic information, the driving characteristic data of the current period and the fine data of the current period. The method and the system can effectively reduce the information quantity manually input by the user, avoid input errors and improve user experience, and enable the generated policy to be matched with the user vehicle accurately, so that the generated policy is more suitable for the user.
Description
Technical Field
The present invention relates to the field of big data, and in particular, to a policy generation method, apparatus, device, and computer readable storage medium.
Background
In order to facilitate online management of a user policy, in the process of purchasing insurance by a user, the user is required to manually fill in personal information and insurance information, and an online policy is generated.
However, in the policy generation process, a user is often required to manually fill out a large amount of information including the insurance application region, the owner information, the vehicle information, the insured person information, the insurance policy information, and the like. The situation that the information is input incorrectly to cause re-quotation and order-making is very easy to occur, and the user experience is poor. In addition, when the policy is generated, risk information of the user vehicle is not considered, so that the generated policy cannot be accurately matched with the user vehicle, and the generated policy is not suitable for the user.
Disclosure of Invention
The invention provides a policy generation method, a device, equipment and a computer readable storage medium, which are used for solving the technical problems that the prior policy generation method has large data volume of information manually input by a user and is easy to cause information input errors, and solving the technical problems that the generated policy cannot be accurately matched with a user vehicle because risk information of the user vehicle is not considered when the policy is generated in the prior art, and the generated policy is not suitable for the user.
A first aspect of the present invention provides a policy generation method, including:
acquiring vehicle identification information input by a user through a policy generation interface;
determining a user application type corresponding to the user according to the vehicle identification information;
acquiring the insuring basic information corresponding to the vehicle identification information from a database corresponding to the user insuring type according to the user insuring type;
acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information, and acquiring corresponding fine data in the current period from the traffic management platform;
and generating a current policy corresponding to the vehicle identification information according to the applied basic information, the current period driving characteristic data and the current period ticket data.
In one possible design, the generating a policy corresponding to the vehicle identification information according to the application basic information, the current period driving feature data, and current period ticket data includes:
determining the current vehicle risk level of the user according to the current period driving characteristic data and the current period ticket data;
and generating a current policy corresponding to the vehicle identification information according to the insurance basic information and the current vehicle risk level.
In one possible design, the determining the current vehicle risk level of the user from the current period driving characteristic data and current period ticket data includes:
inputting the driving characteristic data of the current period and the fine data of the current period into a preset risk classification model trained to be converged;
classifying the vehicle risk levels through the risk assessment model trained to be converged, and outputting the current vehicle risk level of the user;
the risk classification model trained to be converged is a deep learning model trained to be converged.
In one possible design, the user insurance type includes a renewal type, and correspondingly, the acquiring, according to the user insurance type, the insurance base information corresponding to the vehicle identification information in a database corresponding to the user insurance type includes:
acquiring historical policy information of the user from a database corresponding to the renewal type according to the vehicle identification;
correspondingly, the generating the current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level includes:
determining a corresponding historical vehicle risk level according to the historical policy information;
If the current vehicle risk level is matched with the historical vehicle risk level, generating a current policy corresponding to the vehicle identification information according to the historical policy information;
and if the current vehicle risk level is not matched with the historical vehicle risk level, extracting user information and vehicle information in the historical policy information, and adjusting auxiliary insurance information related to the vehicle risk level to generate a current policy corresponding to the vehicle identification information.
In one possible design, the user insurance type includes a transfer insurance type, and correspondingly, the acquiring, according to the user insurance type, the insurance base information corresponding to the vehicle identification information in a database corresponding to the user insurance type includes:
acquiring user information and vehicle information of the user from a transfer type corresponding database according to the vehicle identification;
if the user confirms the user information and the vehicle information instruction is received, the user information and the vehicle information are used as the insuring basic information;
correspondingly, the generating the current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level includes:
Acquiring and displaying auxiliary insurance information of at least one transfer insurance policy matched with the current vehicle risk level from the transfer insurance type corresponding database;
and if the auxiliary insurance information of the target transfer insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the applied basic information and the auxiliary insurance information of the target transfer insurance policy.
In one possible design, the user insurance type includes a new insurance type, and correspondingly, the acquiring, according to the user insurance type, the insurance base information corresponding to the vehicle identification information in a database corresponding to the user insurance type includes:
acquiring vehicle information from a database corresponding to the new insurance type according to the vehicle identification, acquiring user information input by a user, and taking the vehicle information and the user information as the insurance basic information;
correspondingly, the generating the current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level includes:
acquiring and displaying auxiliary insurance information of at least one recommended policy matched with the current vehicle risk level from a database corresponding to the new policy type;
And if the auxiliary insurance information of the target recommended insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the insurance application basic information and the auxiliary insurance information of the target recommended insurance policy.
In one possible design, the method further comprises:
displaying the current policy to the user, wherein the basic information of the current policy is displayed in a first preset mode; and displaying the attached insurance information in the current policy in a second preset mode.
A second aspect of the present invention provides a policy generation apparatus including:
the acquisition module is used for acquiring the vehicle identification information input by the user through the policy generation interface;
the determining module is used for determining the user insurance type corresponding to the user according to the vehicle identification information;
the acquisition module is also used for acquiring the user insurance type of the user insurance type and acquiring the insurance basic information corresponding to the vehicle identification information from a database corresponding to the user type according to the user type;
the acquisition module is also used for acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information and acquiring corresponding ticket data in the current period from the traffic management platform;
And the generation module is used for generating a current policy corresponding to the vehicle identification information according to the application basic information, the current period driving characteristic data and the current period ticket data.
In one possible design, the generating module is specifically configured to determine a current vehicle risk level of the user according to the current period driving feature data and the current period ticket data; and generating a current policy corresponding to the vehicle identification information according to the insurance basic information and the current vehicle risk level.
In one possible design, the generation module is specifically configured to, when determining the current vehicle risk level of the user based on the current period driving characteristic data and current period ticket data
Inputting the driving characteristic data of the current period and the fine data of the current period into a preset risk classification model trained to be converged; classifying the vehicle risk levels through the risk assessment model trained to be converged, and outputting the current vehicle risk level of the user; the risk classification model trained to be converged is a deep learning model trained to be converged.
In one possible design, the user application type includes a renewal type, and correspondingly, the obtaining module is specifically configured to, when obtaining, according to the user application type, application basic information corresponding to the vehicle identification information in a database corresponding to the user application type:
Acquiring historical policy information of the user from a database corresponding to the renewal type according to the vehicle identification;
correspondingly, the generation module is specifically configured to, when generating the current policy corresponding to the vehicle identification information according to the application basic information and the current vehicle risk level:
determining a corresponding historical vehicle risk level according to the historical policy information; if the current vehicle risk level is matched with the historical vehicle risk level, generating a current policy corresponding to the vehicle identification information according to the historical policy information; and if the current vehicle risk level is not matched with the historical vehicle risk level, extracting user information and vehicle information in the historical policy information, and adjusting auxiliary insurance information related to the vehicle risk level to generate a current policy corresponding to the vehicle identification information.
In one possible design, the user application type includes a transfer type, and correspondingly, the obtaining module is specifically configured to, when obtaining, according to the user application type, application basic information corresponding to the vehicle identification information in a database corresponding to the user application type:
Acquiring user information and vehicle information of the user from a transfer type corresponding database according to the vehicle identification; if the user confirms the user information and the vehicle information instruction is received, the user information and the vehicle information are used as the insuring basic information;
correspondingly, the generation module is specifically configured to, when generating the current policy corresponding to the vehicle identification information according to the application basic information and the current vehicle risk level:
acquiring and displaying auxiliary insurance information of at least one transfer insurance policy matched with the current vehicle risk level from the transfer insurance type corresponding database; and if the auxiliary insurance information of the target transfer insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the applied basic information and the auxiliary insurance information of the target transfer insurance policy.
In one possible design, the user application type includes a new application type, and correspondingly, the obtaining module is specifically configured to, when obtaining, according to the user application type, application basic information corresponding to the vehicle identification information in a database corresponding to the user application type:
Acquiring vehicle information from a database corresponding to the new insurance type according to the vehicle identification, acquiring user information input by a user, and taking the vehicle information and the user information as the insurance basic information;
correspondingly, the generation module is specifically configured to, when generating the current policy corresponding to the vehicle identification information according to the application basic information and the current vehicle risk level:
acquiring and displaying auxiliary insurance information of at least one recommended policy matched with the current vehicle risk level from a database corresponding to the new policy type; and if the auxiliary insurance information of the target recommended insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the insurance application basic information and the auxiliary insurance information of the target recommended insurance policy.
In one possible design, the apparatus further comprises: a display module for:
displaying the current policy to the user, wherein the basic information of the current policy is displayed in a first preset mode; and displaying the attached insurance information in the current policy in a second preset mode.
A third aspect of the present invention provides a policy generation device including: a memory, a processor;
A memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the policy generation method of the first aspect by the processor.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein computer-executable instructions which, when executed by a processor, are adapted to carry out the policy generation method according to the first aspect.
The invention provides a policy generation method, a device, equipment and a computer readable storage medium, which are used for acquiring vehicle identification information input by a user through a policy generation interface; determining a user insurance type corresponding to the user according to the vehicle identification information; acquiring the insuring basic information corresponding to the vehicle identification information from a database corresponding to the user insuring type according to the user insuring type; acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information, and acquiring corresponding ticket data in the current period from the traffic management platform; the method comprises the steps of generating a current policy corresponding to vehicle identification information according to the application basic information, the current period driving characteristic data and the current period ticket data, acquiring the application basic data from a corresponding database according to the user application type, and automatically generating the policy according to the application basic data, the current period driving characteristic data and the current period ticket data, so that the information quantity manually input by a user can be effectively reduced, input errors are avoided, user experience is improved, the risk of the current vehicle can be determined according to the current period driving characteristic data and the current period ticket data of the vehicle, the generated policy is further matched with the user vehicle accurately, and the generated policy is more suitable for the user.
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 embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a schematic diagram of a system architecture on which the present invention is based;
fig. 2 is a flowchart of a policy generation method according to an embodiment of the present invention;
fig. 3 is a flow chart of a policy generation method according to a second embodiment of the present invention;
fig. 4 is a schematic structural diagram of a policy generation device according to a third embodiment of the present invention;
fig. 5 is a schematic structural diagram of a policy generating device according to a fourth embodiment of the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments obtained based on the embodiments in the present invention are within the scope of the protection of the present invention.
Aiming at the technical problems that the user manually inputs information in a large data volume and information input errors are easy to cause in the conventional policy generation method, the invention provides a policy generation method, a device, equipment and a computer readable storage medium.
It should be noted that the present application provides a policy generation method, apparatus, device, and computer readable storage medium, which can be applied in various scenes of policy generation.
Fig. 1 is a schematic diagram of a system architecture according to the present invention, as shown in fig. 1, where the system architecture according to the present invention at least includes: terminal equipment 1, policy generation device 2, database 3, vehicle-mounted terminal 4 and traffic management platform 5. Wherein, the policy generation device 2 is written by adopting languages such as C/C++, java, shell or Python; the terminal device 1 may be, for example, a desktop computer, a tablet computer, etc. The database 3 may be a cloud server or a server cluster, in which a large amount of data is stored. The in-vehicle terminal 4 may be a vehicle event data recorder or various vehicle sensors, etc. The driving characteristic data can be collected in the in-vehicle terminal. The traffic management platform 5 may be a server, a cluster of servers, a computer, or the like. The ticket data of the vehicle is stored in the traffic management platform, and various violation data of the vehicle can also be stored. The policy generating device 2 is in communication connection with the terminal device 1, the database 3, the vehicle-mounted terminal 4, and the traffic management platform 5, respectively, so as to be capable of performing information interaction with the terminal device 1, the database 3, the vehicle-mounted terminal 4, and the traffic management platform 5.
Fig. 2 is a flow chart of a policy generation method according to an embodiment of the present invention, as shown in fig. 2, the method includes:
step 101, acquiring vehicle identification information input by a user through a policy generation interface.
The execution subject of the present embodiment is a policy generation device. The policy generation means may be communicatively connected to a terminal device used by the user. When a user makes an insurance at an insurance company, a corresponding policy needs to be generated based on personal data of the user and vehicle data to be applied. Accordingly, in order to reduce the data manually input by the user, a database may be previously established in which a large amount of user information and/or vehicle information, history policy information, and the like may be stored. When the user inputs the vehicle identification information through the terminal device, the vehicle information, the user information, the policy information and the like corresponding to the vehicle identification information can be determined from the database according to the vehicle identification information. The user can input the vehicle identification information to be applied currently on the policy generation interface on the terminal device, and accordingly, the policy generation device can receive the vehicle identification information input by the user and sent by the terminal device. The vehicle identification information includes, but is not limited to, license plate number, vin code, etc.
Step 102, determining a user application type corresponding to the user according to the vehicle identification information.
In this embodiment, after receiving the vehicle identification information input by the user, the policy generation device may determine the user application type of the user according to the vehicle identification information, where the user application type specifically includes a renewal type, a conversion type, and a new protection type. If the insurance company which is currently applied by the user is the A company, the renewal type represents that the insurance company which is applied by the user in history is also the A company; the transfer type characterizes the insurance company non-A company of the user history application, and other companies transfer the insurance company non-A company to the A company; the new type of protection characterizes the user's previous lack of application operations.
It should be noted that, because the amount of information and the information items stored in the user databases of different types are different, the user can be better matched with the user data by classifying the user, and the user is prevented from manually inputting a large amount of data.
And 103, acquiring the insurance basic information corresponding to the vehicle identification information from a database corresponding to the user insurance type according to the user insurance type.
In this embodiment, the amount of information and the information items stored in the different types of user databases are different, for example, the database may store the vehicle information, the user information, and the history policy information of the renewing user, and the new type of protection does not have the history policy information. Accordingly, after the user's application type is determined from the vehicle identification information, the application basic information corresponding to the vehicle identification information can be acquired in the database corresponding to the user's type according to the different user's application type.
The insurance base information includes, but is not limited to, insurance regions, owner information, vehicle information, insured information, insurance policy information, and the like.
And 104, acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information, and acquiring corresponding fine data in the current period from the traffic management platform.
Specifically, in this embodiment, the policy generation device obtains the driving feature data of the current period stored in the vehicle-mounted terminal by communicating with the vehicle-mounted terminal of the vehicle identification information.
Wherein the driving characteristic data during the current period is driving characteristic data within a preset period of time nearest to the current time. Wherein the driving characteristic data may include: braking characteristic data, speed characteristic data, mileage characteristic data, sharp turning characteristic data and the like.
Specifically, in this embodiment, the policy generation device acquires the current period ticket data of the vehicle corresponding to the vehicle identification information through communication with the traffic management platform.
As an alternative implementation manner, in this embodiment, the policy generation device sends a ticket data acquisition request to the traffic management platform, where the ticket data acquisition request includes vehicle identification information and preset time period information nearest to the current time. The traffic management platform acquires the ticket data corresponding to the vehicle identification information according to the ticket data acquisition request, and extracts ticket information in a preset time period nearest to the current time to determine ticket data in the current period. The policy generation device receives the current period ticket data.
And 105, generating a current policy corresponding to the vehicle identification information according to the applied basic information, the driving characteristic data of the current period and the fine data of the current period.
In this embodiment, after the application basic information, the current period driving feature data and the current period ticket data corresponding to the user are obtained, the current period vehicle risk level of the user can be determined according to the current period driving feature data and the current period ticket data, and then the current policy corresponding to the vehicle identification information can be generated for the user according to the application basic information and the current vehicle risk level.
It can be understood that if the obtained basic information of the application is insufficient, the user can be prompted to manually input data according to the basic information of the application which is lack in the current policy. Since most of the data can be acquired automatically, the amount of data that needs to be manually input by the user is small.
According to the policy generation method provided by the embodiment, the vehicle identification information input by a user through the policy generation interface is obtained; determining a user insurance type corresponding to the user according to the vehicle identification information; acquiring the insuring basic information corresponding to the vehicle identification information from a database corresponding to the user insuring type according to the user insuring type; acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information, and acquiring corresponding ticket data in the current period from the traffic management platform; the method comprises the steps of generating a current policy corresponding to vehicle identification information according to the application basic information, the current period driving characteristic data and the current period ticket data, acquiring the application basic data from a corresponding database according to the user application type, and automatically generating the policy according to the application basic data, the current period driving characteristic data and the current period ticket data, so that the information quantity manually input by a user can be effectively reduced, input errors are avoided, user experience is improved, the risk of the current vehicle can be determined according to the current period driving characteristic data and the current period ticket data of the vehicle, the generated policy is further matched with the user vehicle accurately, and the generated policy is more suitable for the user.
Further, on the basis of any of the above embodiments, step 105 includes the steps of:
step 1051, determining the current vehicle risk level of the user based on the current period driving characteristics data and the current period ticket data.
As an alternative implementation, in this embodiment, step 1051 includes the following steps:
step 1051a, inputting the driving characteristic data of the current period and the fine data of the current period into a preset risk classification model trained to be converged.
In step 1051b, the risk level of the vehicle is classified by training to a converged risk assessment model, and the current risk level of the vehicle of the user is output.
The risk classification model trained to be converged is a deep learning model trained to be converged. The deep learning model trained until convergence can be a convolutional neural network model, a long-term and short-term memory neural network model and the like.
Specifically, in this embodiment, the risk classification model may be trained in advance according to the training samples. The training samples are historical driving characteristic data and historical ticket data which are marked with the risk level of the vehicle and are generated.
Specifically, when training the risk classification model, an initial risk classification model is obtained, then a plurality of training samples are input into the initial risk classification model, the initial risk classification model is trained, whether the model convergence condition is met or not is judged, and if the model convergence condition is met, the risk classification model meeting the model convergence condition is determined to be the risk classification model trained to be converged.
The model convergence condition may be that the loss function is minimized, or the iteration number reaches a preset iteration number, which is not limited in this embodiment.
In this embodiment, after determining the risk classification model trained to converge, the driving feature data of the current period and the fine data of the current period are input into a preset risk classification model trained to converge, and the preset risk classification model trained to converge classifies the risk level of the current vehicle of the user according to the driving feature data of the current period and the fine data of the current period, and outputs the risk level of the current vehicle of the user.
The current vehicle risk level output can be high risk, medium risk or low risk, and the like.
Step 1052, generating a current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level.
Specifically, in this embodiment, the generated current policy needs to include the affiliated insurance information in addition to the basic information of the application. The determination of the auxiliary insurance information is matched with the current vehicle risk level, so that the auxiliary insurance information can be determined according to the current vehicle risk level, and a current insurance policy corresponding to the vehicle identification information can be generated according to the applied basic information and the auxiliary insurance information.
Wherein the affiliated insurance information may include: premium information, insurance claim information, insurance range information, etc.
Further, on the basis of any of the above embodiments, the policy type includes a renewal type, and correspondingly, step 103 specifically includes:
acquiring historical policy information of a user from a database corresponding to the renewal type according to the vehicle identification;
in this embodiment, the policy type may specifically include a renewal type, where if the insurance company that is currently applied by the user is company a, the renewal type characterizes that the insurance company that is applied by the user in history is also company a. Accordingly, the database may store therein the user history policy information including therein the application basic information for generating the policy.
Accordingly, step 104 specifically includes:
step 104a, determining a corresponding historical vehicle risk level according to the historical policy information.
Specifically, in this embodiment, after the history policy information of each vehicle is determined, the history policy information and the history vehicle risk level may be stored in association according to the identification information of the vehicle. Therefore, after the history policy information is acquired, the history vehicle risk level with the association relation can be acquired as the corresponding history vehicle risk level according to the identification information of the vehicle.
Step 104b, if the current vehicle risk level matches the historical vehicle risk level, generating a current policy corresponding to the vehicle identification information according to the historical policy information.
In this embodiment, if the current vehicle risk level matches the historical vehicle risk level, it is explained that the historical policy is matched with the current vehicle of the user, so that the current policy corresponding to the vehicle identification information is generated according to the historical policy information.
Step 104c, if the current vehicle risk level does not match the historical vehicle risk level, extracting the user information and the vehicle information in the historical policy information, and adjusting the auxiliary insurance information related to the vehicle risk level to generate the current policy corresponding to the vehicle identification information.
In this embodiment, if the current vehicle risk level does not match the historical vehicle risk level, it is indicated that the current vehicle risk level is higher or lower than the historical vehicle risk level, only the user information and the vehicle information in the historical policy information can be extracted as the application basic information, and the auxiliary insurance information related to the vehicle risk level needs to be adjusted to the auxiliary insurance information matching the current vehicle risk level. And finally, generating a current policy corresponding to the vehicle identification information according to the insurance application basic information and the adjusted attached insurance information.
According to the policy generation method provided by the embodiment, the current policy is generated according to the history policy information of the renewing user and the current vehicle risk level, so that the current policy can be matched with the risk level of the renewing user, the current policy can be further accurately matched with the user vehicle, and the generated policy is more suitable for the user. And moreover, the manual information input of a user can be avoided, and the user experience is improved.
Fig. 3 is a flow chart of a policy generation method provided in the second embodiment of the present invention, where on the basis of any of the foregoing embodiments, a user application type may include a conversion type, and correspondingly, as shown in fig. 3, step 103 specifically includes:
step 1031, obtaining user information and vehicle information of a user from a transfer type corresponding database according to the vehicle identification;
step 1032, receiving the instruction for the user to confirm the user information and the vehicle information, the user information and the vehicle information are used as the basic information for application.
In this embodiment, the user insurance type may be specifically a transfer type, and if the insurance company that is currently being applied by the user is a company a, the transfer type characterizes that the insurance company that is historically being applied by the user is not a company a, and is transferred to the company a by other companies. The database can integrate open source data of a plurality of insurance companies, and further can acquire user information and vehicle information of the user according to the vehicle identification information input by the user.
Accordingly, step 104 includes the steps of:
step 1041, obtaining and displaying the auxiliary insurance information of at least one transfer insurance policy matching with the current vehicle risk level from the transfer insurance type corresponding database.
Optionally, in this embodiment, since the user is a representational user, the user may be provided with a plurality of selectable policies that match the current vehicle risk level. The transfer type corresponding database stores a plurality of transfer insurance policies of the transfer company in advance, and each transfer insurance policy is provided with attached insurance information. And the vehicle risk level matched with each transfer insurance policy is prestored in the transfer insurance type corresponding database. The auxiliary insurance information of at least one transfer insurance policy matched with the current vehicle risk level is acquired from the transfer insurance type corresponding database, and the auxiliary insurance information of each transfer insurance policy is displayed through the display interface, so that a user can select certain auxiliary insurance information through the display interface.
In step 1042, if the attached insurance information of the target transfer policy confirmed by the user is received, the current policy corresponding to the vehicle identification information is generated according to the applied basic information and the attached insurance information of the target transfer policy.
Optionally, in this embodiment, the user selects the auxiliary insurance information of the target transfer policy through the selection confirmation item on the display interface, and after receiving the auxiliary insurance information of the target transfer policy confirmed by the user, generates the current policy corresponding to the vehicle identification information according to the application basic information and the auxiliary insurance information of the target transfer policy.
According to the policy generation method provided by the embodiment, the current policy is generated according to the user information and the vehicle information of the reprovisioned user and the auxiliary insurance information of the matched target reprovisioned policy determined by the current vehicle risk level, so that the current policy is matched with the risk level of the vehicle of the reprovisioned user, and further the current policy is accurately matched with the vehicle of the user, and the generated policy is more suitable for the user. And moreover, the manual information input of a user can be avoided, and the user experience is improved.
Further, on the basis of any of the foregoing embodiments, the user's application type may specifically further include a new application type, and correspondingly, step 103 specifically includes:
and acquiring the vehicle information from the database corresponding to the new insurance type according to the vehicle identification, acquiring the user information input by the user, and taking the vehicle information and the user information as the insurance basic information.
In this embodiment, the user application type may specifically be a new application type. If the insurance company which is applied by the current user is company A, the new insurance type characterizes the user to conduct the application operation before. Therefore, the data amount in the database storage is small, and therefore, the vehicle information and the user information can be taken as the basic information of the application by acquiring the vehicle information from the database corresponding to the new insurance type according to the vehicle identification and acquiring the user information input by the user.
Accordingly, step 104 includes the steps of:
step 104A, obtaining and displaying the auxiliary insurance information of at least one recommended policy matched with the current vehicle risk level from the database corresponding to the new policy type.
In particular, in this embodiment, since the user is a new insurance user, the user may be provided with a variety of selectable insurance policies that match the current vehicle risk level. The policy is a recommended policy. A plurality of recommended insurance policies are stored in the corresponding database of the new insurance type in advance, and each recommended insurance policy is provided with attached insurance information. And the corresponding database of the new insurance type stores the vehicle risk level matched with each recommended insurance policy in advance. The auxiliary insurance information of at least one recommended insurance policy matched with the current vehicle risk level is acquired from the corresponding database of the new insurance type, and the auxiliary insurance information of each recommended insurance policy is displayed through the display interface, so that a user can select certain auxiliary insurance information through the display interface.
Step 104B, if the attached insurance information of the target recommended policy confirmed by the user is received, generating the current policy corresponding to the vehicle identification information according to the applied basic information and the attached insurance information of the target recommended policy.
Optionally, in this embodiment, the user selects the auxiliary insurance information of one of the plurality of recommended insurance policies as the auxiliary insurance information of the target recommended insurance policy through the selection confirmation item on the display interface, and after receiving the auxiliary insurance information of the target recommended insurance policy confirmed by the user, generates the current insurance policy corresponding to the vehicle identification information according to the insurance application basic information and the auxiliary insurance information of the target recommended insurance policy.
According to the policy generation method provided by the embodiment, the current policy is generated according to the user information and the vehicle information of the new insurance user and the auxiliary insurance information of the matched target recommended policy determined by the current vehicle risk level, so that the current policy is matched with the risk level of the vehicle of the new insurance user, further the current policy is accurately matched with the vehicle of the user, and the generated policy is more suitable for the user. And moreover, the manual information input of a user can be avoided, and the user experience is improved.
Further, on the basis of any one of the above embodiments, after generating the current policy corresponding to the vehicle identification information from the insurance base information, the current period driving characteristic data, and the current period ticket data, it may further include:
displaying a current policy to a user, wherein the basic information of the current policy is displayed in a first preset mode; and displaying the attached insurance information in the current policy in a second preset mode.
Specifically, in this embodiment, the generated current policy is displayed to the user through the display interface. In order to enable a user to clearly and accurately see the insurance application basic information and the auxiliary insurance information and distinguish the insurance application basic information from the auxiliary insurance information, the insurance application basic information in the current policy can be displayed in a first preset mode, and the auxiliary insurance information in the current policy can be displayed in a second preset mode.
Wherein the first preset mode is different from the second preset mode. If the first preset mode is a highlight mode, the second preset mode is a box frame mode. It is understood that the specific display modes of the first preset mode and the second preset mode are not limited.
According to the policy generation method provided by the embodiment, after the current policy information is generated, the current policy is displayed to the user, and the basic information of the current policy is applied and displayed in a first preset mode; the attached insurance information in the current policy is displayed in a second preset mode, so that a user can more clearly and accurately check key information in the current policy, and can timely adjust after finding unsuitable information.
Fig. 4 is a schematic structural diagram of a policy generation device according to a third embodiment of the present invention, where, as shown in fig. 4, the policy generation device includes: an acquisition module 31, a determination module 32 and a generation module 33.
The acquiring module 31 is configured to acquire vehicle identification information input by a user through a policy generation interface; a determining module 32, configured to determine a user application type corresponding to the user according to the vehicle identification information; the obtaining module 31 is further configured to obtain, according to the user type, the user application type of the user application type, application basic information corresponding to the vehicle identification information in a database corresponding to the user type; the obtaining module 31 is further configured to obtain corresponding driving feature data of a current period from the vehicle terminal according to the vehicle identification information, and obtain corresponding ticket data of the current period from the traffic management platform. And a generation module 33 for generating a current policy corresponding to the vehicle identification information based on the application basic information, the current period driving characteristic data, and the current period ticket data.
In one possible design, the generating module 33 is specifically configured to determine a current vehicle risk level of the user according to the current period driving feature data and the current period ticket data; and generating a current policy corresponding to the vehicle identification information according to the insurance basic information and the current vehicle risk level.
In one possible design, the generation module 33 is specifically configured to, when determining the current vehicle risk level of the user based on the current period driving characteristics data and the current period ticket data
Inputting driving characteristic data of the current period and fine data of the current period into a preset risk classification model trained to be converged; classifying the vehicle risk levels through the risk assessment model trained until convergence, and outputting the current vehicle risk level of the user; the risk classification model trained to converge is a deep learning model trained to converge.
In one possible design, the user application type includes a renewal type, and accordingly, the obtaining module 31 is specifically configured to, when obtaining, according to the user application type, the application basic information corresponding to the vehicle identification information in the database corresponding to the user application type:
acquiring historical policy information of a user from a database corresponding to the renewal type according to the vehicle identification;
accordingly, the generating module 33 is specifically configured to, when generating the current policy corresponding to the vehicle identification information according to the application basic information and the current vehicle risk level:
determining a corresponding historical vehicle risk level according to the historical policy information; if the current vehicle risk level is matched with the historical vehicle risk level, generating a current policy corresponding to the vehicle identification information according to the historical policy information; if the current vehicle risk level is not matched with the historical vehicle risk level, extracting user information and vehicle information in the historical policy information, and adjusting auxiliary insurance information related to the vehicle risk level to generate a current policy corresponding to the vehicle identification information.
In one possible design, the user's insurance type includes a transfer insurance type, and accordingly, the obtaining module 31 is specifically configured to, when obtaining, according to the user's insurance type, the insurance base information corresponding to the vehicle identification information in the database corresponding to the user's insurance type:
acquiring user information and vehicle information of a user from a corresponding database of the transfer type according to the vehicle identification; if a command of confirming the user information and the vehicle information is received, the user information and the vehicle information are used as the basic information for application;
accordingly, the generating module 33 is specifically configured to, when generating the current policy corresponding to the vehicle identification information according to the application basic information and the current vehicle risk level:
acquiring and displaying auxiliary insurance information of at least one transfer insurance policy matched with the current vehicle risk level from a transfer insurance type corresponding database; and if the auxiliary insurance information of the target transfer insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the insurance application basic information and the auxiliary insurance information of the target transfer insurance policy.
In one possible design, the user's insurance type includes a new insurance type, and accordingly, the obtaining module 31 is specifically configured to, when obtaining, according to the user's insurance type, the insurance base information corresponding to the vehicle identification information in the database corresponding to the user's insurance type:
Acquiring vehicle information from a database corresponding to the new insurance type according to the vehicle identification, acquiring user information input by a user, and taking the vehicle information and the user information as insurance basic information;
accordingly, the generating module 33 is specifically configured to, when generating the current policy corresponding to the vehicle identification information according to the application basic information and the current vehicle risk level:
acquiring and displaying auxiliary insurance information of at least one recommended policy matched with the current vehicle risk level from a database corresponding to the new policy type; and if the auxiliary insurance information of the target recommended insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the insurance application basic information and the auxiliary insurance information of the target recommended insurance policy.
In one possible design, the apparatus further comprises: a display module for:
displaying a current policy to a user, wherein the basic information of the current policy is displayed in a first preset mode; and displaying the attached insurance information in the current policy in a second preset mode.
Fig. 5 is a schematic structural diagram of a policy generation device according to a fourth embodiment of the present invention, where, as shown in fig. 5, the policy generation device includes: a memory 41, a processor 42;
A memory 41; a memory 41 for storing instructions executable by the processor 42;
wherein the processor 42 is configured to perform the policy generation method as in any of the embodiments above by the processor 42.
A memory 41 for storing a program. In particular, the program may include program code including computer-operating instructions. The memory 41 may comprise a high-speed RAM memory or may further comprise a non-volatile memory (non-volatile memory), such as at least one disk memory.
The processor 42 may be a central processing unit (Central Processing Unit, abbreviated as CPU), or an application specific integrated circuit (Application Specific Integrated Circuit, abbreviated as ASIC), or one or more integrated circuits configured to implement embodiments of the present invention.
Alternatively, in a specific implementation, if the memory 32 and the processor 33 are implemented independently, the memory 41 and the processor 42 may be connected to each other and perform communication with each other through a bus. The bus may be an industry standard architecture (Industry Standard Architecture, abbreviated ISA) bus, an external device interconnect (Peripheral Component, abbreviated PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, abbreviated EISA) bus, among others. The buses may be divided into address buses, data buses, control buses, etc. For ease of illustration, only one thick line is shown in fig. 5, but not only one bus or one type of bus.
Alternatively, in a specific implementation, if the memory 41 and the processor 42 are integrated on a chip, the memory 41 and the processor 42 may perform the same communication through an internal interface.
Still another embodiment of the present invention provides a computer-readable storage medium having stored therein computer-executable instructions which, when executed by a processor, are configured to implement the policy generation method of any of the above embodiments.
It will be clear to those skilled in the art that, for convenience and brevity of description, reference may be made to the corresponding process in the foregoing method embodiment for the specific working process of the apparatus described above, which is not described herein again.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the method embodiments described above may be performed by hardware associated with program instructions. The foregoing program may be stored in a computer readable storage medium. The program, when executed, performs steps including the method embodiments described above; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (8)
1. A policy generation method, comprising:
acquiring vehicle identification information input by a user through a policy generation interface;
determining a user application type corresponding to the user according to the vehicle identification information;
acquiring the insuring basic information corresponding to the vehicle identification information from a database corresponding to the user insuring type according to the user insuring type;
acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information, and acquiring corresponding fine data in the current period from the traffic management platform;
generating a current policy corresponding to the vehicle identification information according to the applied basic information, the current period driving characteristic data and the current period ticket data;
the generating a policy corresponding to the vehicle identification information according to the applied basic information, the current period driving characteristic data and the current period ticket data comprises the following steps:
determining a current vehicle risk level of the user according to the current period driving characteristic data and the current period ticket data, wherein the current vehicle risk level is obtained by inputting the current period driving characteristic data and the current period ticket data into a preset risk classification model trained to be converged; the preset risk classification model which is trained to be converged is obtained by training the risk classification model in advance according to training samples, wherein the training samples are historical driving characteristic data and historical ticket data which are marked with vehicle risk grades and are generated; the driving characteristic data includes: braking characteristic data, speed characteristic data, mileage characteristic data and sharp turning characteristic data;
Generating a current policy corresponding to the vehicle identification information according to the insuring basic information and the current vehicle risk level;
if the user insurance type is a renewal type, correspondingly, acquiring the insurance basic information corresponding to the vehicle identification information in a database corresponding to the user insurance type according to the user insurance type, including:
acquiring historical policy information of the user from a database corresponding to the renewal type according to the vehicle identification;
correspondingly, the generating the current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level includes:
determining a corresponding historical vehicle risk level according to the historical policy information;
if the current vehicle risk level is matched with the historical vehicle risk level, generating a current policy corresponding to the vehicle identification information according to the historical policy information;
and if the current vehicle risk level is not matched with the historical vehicle risk level, extracting user information and vehicle information in the historical policy information, and adjusting auxiliary insurance information related to the vehicle risk level to generate a current policy corresponding to the vehicle identification information.
2. The method of claim 1, wherein the determining the current vehicle risk level for the user based on the current period driving characteristics data and current period ticket data comprises:
inputting the driving characteristic data of the current period and the fine data of the current period into the preset risk classification model trained to be converged;
classifying the vehicle risk levels through the risk assessment model trained to be converged, and outputting the current vehicle risk level of the user;
the risk classification model trained to be converged is a deep learning model trained to be converged.
3. The method according to claim 1, wherein if the user's application type is a transfer type, the obtaining, according to the user's application type, the application basic information corresponding to the vehicle identification information in a database corresponding to the user's application type includes:
acquiring user information and vehicle information of the user from a transfer type corresponding database according to the vehicle identification;
if the user confirms the user information and the vehicle information instruction is received, the user information and the vehicle information are used as the insuring basic information;
Correspondingly, the generating the current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level includes:
acquiring and displaying auxiliary insurance information of at least one transfer insurance policy matched with the current vehicle risk level from the transfer insurance type corresponding database;
and if the auxiliary insurance information of the target transfer insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the applied basic information and the auxiliary insurance information of the target transfer insurance policy.
4. The method according to claim 1, wherein if the user's application type is a new application type, the obtaining, according to the user's application type, the application basic information corresponding to the vehicle identification information in a database corresponding to the user's application type includes:
acquiring vehicle information from a database corresponding to the new insurance type according to the vehicle identification, acquiring user information input by a user, and taking the vehicle information and the user information as the insurance basic information;
correspondingly, the generating the current policy corresponding to the vehicle identification information according to the applied basic information and the current vehicle risk level includes:
Acquiring and displaying auxiliary insurance information of at least one recommended policy matched with the current vehicle risk level from a database corresponding to the new policy type;
and if the auxiliary insurance information of the target recommended insurance policy confirmed by the user is received, generating a current insurance policy corresponding to the vehicle identification information according to the insurance application basic information and the auxiliary insurance information of the target recommended insurance policy.
5. The method of any one of claims 1-4, further comprising:
displaying the current policy to the user, wherein the basic information of the current policy is displayed in a first preset mode; and displaying the attached insurance information in the current policy in a second preset mode.
6. A policy generation apparatus, comprising:
the acquisition module is used for acquiring the vehicle identification information input by the user through the policy generation interface;
the determining module is used for determining the user insurance type corresponding to the user according to the vehicle identification information;
the acquisition module is also used for acquiring the user insurance type of the user insurance type and acquiring the insurance basic information corresponding to the vehicle identification information from a database corresponding to the user type according to the user type;
The acquisition module is also used for acquiring corresponding driving characteristic data in the current period from the vehicle-mounted terminal according to the vehicle identification information and acquiring corresponding ticket data in the current period from the traffic management platform;
the generation module is used for generating a current insurance policy corresponding to the vehicle identification information according to the insurance basic information, the current period driving characteristic data and the current period ticket data;
the generation module is further configured to determine a current vehicle risk level of the user according to the current period driving feature data and the current period ticket data, where the current vehicle risk level is obtained by inputting the current period driving feature data and the current period ticket data into a preset risk classification model trained to be converged; the preset risk classification model which is trained to be converged is obtained by training the risk classification model in advance according to training samples, wherein the training samples are historical driving characteristic data and historical ticket data which are marked with vehicle risk grades and are generated; the driving characteristic data includes: braking characteristic data, speed characteristic data, mileage characteristic data and sharp turning characteristic data;
Generating a current policy corresponding to the vehicle identification information according to the insuring basic information and the current vehicle risk level;
if the user application type is a renewal type, the acquiring module is specifically configured to acquire the historical policy information of the user from a database corresponding to the renewal type according to the vehicle identifier;
correspondingly, the generation module is specifically configured to determine a corresponding historical vehicle risk level according to the historical policy information; if the current vehicle risk level is matched with the historical vehicle risk level, generating a current policy corresponding to the vehicle identification information according to the historical policy information; and if the current vehicle risk level is not matched with the historical vehicle risk level, extracting user information and vehicle information in the historical policy information, and adjusting auxiliary insurance information related to the vehicle risk level to generate a current policy corresponding to the vehicle identification information.
7. A policy generation apparatus, characterized by comprising: a memory, a processor;
a memory; a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the policy generation method of any of claims 1-5 by the processor.
8. A computer readable storage medium having stored therein computer executable instructions which when executed by a processor are for implementing the policy generation method of any of claims 1-5.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108205784A (en) * | 2016-12-20 | 2018-06-26 | 邹红星 | Intelligent transportation management and control method of servicing and platform |
| CN109447824A (en) * | 2018-09-26 | 2019-03-08 | 平安健康保险股份有限公司 | Declaration form data processing method, device, computer equipment and storage medium |
| CN109658272A (en) * | 2018-12-26 | 2019-04-19 | 江苏数慧信息科技有限公司 | Driving behavior evaluation system and Insurance Pricing system based on driving behavior |
| CN110428279A (en) * | 2019-07-05 | 2019-11-08 | 深圳壹账通智能科技有限公司 | Vehicle insurance recommended method, device, equipment and computer readable storage medium |
-
2020
- 2020-05-29 CN CN202010479264.5A patent/CN111651473B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108205784A (en) * | 2016-12-20 | 2018-06-26 | 邹红星 | Intelligent transportation management and control method of servicing and platform |
| CN109447824A (en) * | 2018-09-26 | 2019-03-08 | 平安健康保险股份有限公司 | Declaration form data processing method, device, computer equipment and storage medium |
| CN109658272A (en) * | 2018-12-26 | 2019-04-19 | 江苏数慧信息科技有限公司 | Driving behavior evaluation system and Insurance Pricing system based on driving behavior |
| CN110428279A (en) * | 2019-07-05 | 2019-11-08 | 深圳壹账通智能科技有限公司 | Vehicle insurance recommended method, device, equipment and computer readable storage medium |
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