WO2021004121A1

WO2021004121A1 - Vehicle insurance recommendation method, apparatus and device, and computer-readable storage medium

Info

Publication number: WO2021004121A1
Application number: PCT/CN2020/086160
Authority: WO
Inventors: 谭莉
Original assignee: 深圳壹账通智能科技有限公司
Priority date: 2019-07-05
Filing date: 2020-04-22
Publication date: 2021-01-14
Also published as: CN110428279A

Abstract

Disclosed are a vehicle insurance recommendation method, apparatus and device, and a computer-readable storage medium, which relate to the field of big data processing. The method comprises: when a vehicle insurance recommendation request is received, extracting a target vehicle identifier in the vehicle insurance recommendation request, and querying a precreated data index according to the target vehicle identifier, so as to acquire a target data address (S10); acquiring vehicle information, historical vehicle insurance information and historical accident information of a corresponding vehicle according to the target data address, and determining, according to the historical vehicle insurance information and the vehicle information and on the basis of a first preset rule, a first vehicle insurance type to be recommended and an insurance company to be recommended (S20); determining, according to the historical vehicle insurance information, the historical accident information and the vehicle information, first estimated vehicle insurance expense of the first vehicle insurance type to be recommended (S30); acquiring first discount information, for the first vehicle insurance type to be recommended, provided by a preset insurance company, and calculating first actual vehicle insurance expense according to the first estimated vehicle insurance expense and the first discount information (S40); and generating corresponding first recommendation information according to the first actual vehicle insurance expense and the insurance company to be recommended, and pushing the first recommendation information to a corresponding user terminal (S50).

Description

Car insurance recommendation method, device, equipment and computer readable storage medium

This application claims the priority of a Chinese patent application filed with the Chinese Patent Office on July 5, 2019, the application number is 201910608902.6, and the invention title is "Auto Insurance Recommendation Methods, Devices, Equipment, and Computer-readable Storage Media". The reference is incorporated in this application.

Technical field

This application relates to the technical field of big data processing, and in particular to a method, device, device, and computer-readable storage medium for car insurance recommendation.

Background technique

In recent years, with the rapid development of our country's economy and the increasing improvement of people's living standards, cars have become an indispensable travel tool for many families. In order to reduce the economic risk of accidents, people usually buy auto insurance for their vehicles. However, many users do not know what kind of auto insurance to buy, and they usually buy under the promotion of business personnel, which makes users buy some unnecessary insurance types. Or, the recommendation is made through related software. However, the inventor realizes that the recommendation through software is usually only based on the user's historical insurance record, which has poor accuracy. Therefore, the current auto insurance recommendation method has the problem of poor accuracy.

Summary of the invention

According to various embodiments disclosed in the present application, a method, device, device, and computer-readable storage medium for car insurance recommendation are provided.

A method for recommending auto insurance, which includes:

When receiving the auto insurance recommendation request, extract the target vehicle identifier in the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

Obtain the vehicle information, historical auto insurance information, and historical risk information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended auto insurance type and the to-be-recommended insurance according to the first preset rule according to the historical auto insurance information and the vehicle information the company;

Determining the first estimated auto insurance premium of the first auto insurance type to be recommended according to the historical auto insurance information, the historical insurance information, and the vehicle information;

Acquiring the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculating the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information;

Generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.

This application also provides a car insurance recommendation device, which includes:

The address obtaining module is configured to extract the target vehicle identifier in the auto insurance recommendation request when receiving the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

The information determining module is used to obtain vehicle information, historical auto insurance information, and historical accident information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended according to the historical auto insurance information and the vehicle information according to the first preset rule Types of auto insurance and insurance companies to be recommended;

A first calculation module, configured to determine the first estimated auto insurance premium of the first auto insurance type to be recommended according to the historical auto insurance information, the historical insurance information, and the vehicle information;

The second calculation module is configured to obtain the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculate the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information ；

The first push module is configured to generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.

An auto insurance recommendation device, which includes a memory, a processor, and an auto insurance recommendation program stored on the memory and executable by the processor, wherein when the auto insurance recommendation program is executed by the processor, Implement the following steps:

A computer-readable storage medium having a car insurance recommendation program stored on the computer-readable storage medium, wherein when the car insurance recommendation program is executed by a processor, the steps of the following method are implemented:

The details of one or more embodiments of the application are set forth in the following drawings and description. Other features and advantages of this application will become apparent from the description, drawings and claims.

Description of the drawings

FIG. 1 is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the application;

FIG. 2 is a schematic flowchart of a first embodiment of a method for applying for car insurance recommendation;

Fig. 3 is a schematic diagram of functional modules of the first embodiment of the car insurance recommendation device of this application.

The realization, functional characteristics, and advantages of the purpose of this application will be further described in conjunction with the embodiments and with reference to the drawings.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the application, and are not used to limit the application.

Referring to FIG. 1, FIG. 1 is a schematic diagram of the device structure of the hardware operating environment involved in the solution of the embodiment of the application.

The car insurance recommendation device involved in the embodiment of the present application may be a terminal device such as a PC (personal computer, personal computer), a notebook computer, and a server.

As shown in FIG. 1, the vehicle insurance recommendation device may include a processor 1001, such as a CPU (Central Processing Unit, central processing unit), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components; the user interface 1003 may include a display (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. . The network interface 1004 can optionally include a standard wired interface and a wireless interface (such as Wireless-Fidelity, Wi-Fi interface); the memory 1005 can be a high-speed random access memory (random access memory, RAM), or it can be A stable memory (non-volatile memory), such as a disk memory, and the memory 1005 may optionally be a storage device independent of the aforementioned processor 1001. Those skilled in the art can understand that the structure of the car insurance recommendation device shown in FIG. 1 does not constitute a limitation on the car insurance recommendation device, and may include more or less components than shown in the figure, or a combination of certain components, or different components Layout.

Continuing to refer to FIG. 1, the memory 1005 as a computer storage medium in FIG. 1 may include an operating system, a network communication module, and a car insurance recommendation program. In FIG. 1, the network communication module can be used to connect to a server and perform data communication with the server; and the processor 1001 can be used to call the car insurance recommendation program stored in the memory 1005 and execute the car insurance recommendation method provided in the embodiment of the present application.

Based on the above hardware structure, various embodiments of the auto insurance recommendation method of this application are proposed.

This application provides a method for recommending auto insurance.

Please refer to FIG. 2, which is a schematic flowchart of a first embodiment of a method for recommending auto insurance in this application.

In this embodiment, the auto insurance recommendation method includes:

Step S10, when receiving the auto insurance recommendation request, extract the target vehicle identifier in the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

Before the above step S10, the vehicle recommendation method further includes:

When receiving the data access instruction, create a data index according to the data access instruction, and configure the attributes of the data index;

Obtain a data source address, establish a remote call connection with a target data source according to the data source address, and import data information corresponding to the data index from the target data source.

In this embodiment, the method for recommending car insurance is implemented by a car insurance recommending device. The car insurance recommending device may be a PC, a laptop, a server, etc. For the convenience of description, the car insurance recommending device is described by taking a server as an example.

In order to facilitate subsequent query of vehicle information, historical car insurance information, and historical risk information, a data index can be constructed to achieve rapid query. Specifically, the manager can log in to the corresponding software or application through a PC or other management terminal, and select the data access option on the relevant configuration interface to trigger the data access instruction. At this time, when the server receives the data access instruction, it creates a data index for the data source to be accessed according to the data access instruction.

Among them, the data index structure in this embodiment may be an index data table (index), the data index table may include content such as field names, field types, etc.; field names can be understood as the index of each row (or each column) of the index data table The meaning of data (value); the field type is the data type of the row (or column), including integer int, long integer, string, etc. In addition to the above content, the index data table may also include other content, such as storing original values, multi-value options, default values, and so on. In several rows (columns) of the data table, it is also necessary to determine a certain target row (column) as the primary key. This primary key row is the only basis for indexing each piece of data. For this embodiment, the row corresponding to the license plate number can be (Column) as the primary key. After the administrator enters the information of the data index, the server will create a corresponding data index based on the entered content, configure the relevant attributes of the data index according to the entered information, and open up corresponding storage space for the data index based on the attributes.

When the corresponding data index is created, the data source will be registered, that is, the corresponding data source will be imported for the data index. Specifically, the manager needs to enter the data source address in the configuration interface of the data index. The server obtains the data source address and finds the corresponding target data source based on the data source address; then obtains the data information from the target data source, and imports the original data into the corresponding storage space according to the data index. Wherein, the data source address may include the data source address of vehicle information, historical auto insurance information, and historical accident information.

When the server receives the auto insurance recommendation request, it extracts the target vehicle identifier in the auto insurance recommendation request, and then queries the pre-created data index based on the target vehicle identifier to obtain the target data address. Specifically, it is based on the target vehicle identifier in the pre-created data index. Find the matched field object in the data index, and obtain the target data address according to the value storage address of the matched field object. Among them, the triggering method of the auto insurance recommendation request may include but is not limited to: 1) The user logs in to the corresponding APP (Application) through the user terminal and selects the auto insurance recommendation option. At this time, the terminal will pop up a corresponding window for the user to fill in the corresponding The car insurance recommendation request can be triggered after the user fills in the confirmation; 2) The user has entered the corresponding license plate number in the corresponding APP, and the server can query the historical insurance information of the vehicle according to the license plate number, and then according to the history The insurance information obtains the remaining time of auto insurance expiration. When it is detected that the remaining time of auto insurance expiration of the vehicle is less than the preset time threshold, that is, when it is detected that the auto insurance of the vehicle is about to expire, the auto insurance recommendation request can be automatically triggered.

Step S20: Acquire vehicle information, historical auto insurance information, and historical insurance information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended auto insurance category and the first preset rule based on the historical auto insurance information and the vehicle information To be recommended insurance company;

After obtaining the target data address, obtain the vehicle information, historical auto insurance information, and historical risk information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended auto insurance type and to-be-recommended according to the historical auto insurance information and vehicle information according to the first preset rule Insurance company. Among them, the vehicle information includes the frame number, vehicle manufacturer, model, and purchase age. The frame number is also known as the Vehicle Identification Number (VIN), which is a set of seventeen alphanumerics and is used on cars. The first digit of the code represents the place where the vehicle was manufactured, and the tenth digit represents the year when the vehicle was manufactured. The historical auto insurance information includes historical insurance types and historical insurance companies. The historical auto insurance information may include historical insurance types, historical Insured amount and historical insurance company, etc., historical insurance information includes information such as the type and number of insurance incidents after an insured accident occurs. The step “determine the first to-be-recommended auto insurance according to the historical auto insurance information and the vehicle information according to the first preset rule Types of insurance and recommended insurance companies" include:

Step a1: Calculate the estimated value of the vehicle according to the frame number, the vehicle manufacturer and the model according to a preset calculation rule;

First calculate the estimated value of the vehicle according to the frame number, vehicle manufacturer and model according to the preset calculation rules. Specifically, step a1 includes:

Step a11: Determine the factory place and year of the vehicle according to the frame number and the first preset mapping relationship table;

Specifically, the factory location and year of the vehicle are first determined according to the frame number and the first preset mapping relationship table. Among them, the first digit code of the frame number represents the factory place of the vehicle, and the tenth digit code represents the year when the vehicle was manufactured. The first preset mapping relationship table includes the mapping relationship between different codes and the place of manufacture, and different codes and the vehicle factory For the mapping relationship between the years, the first and tenth digits of the frame number can be obtained first, and then combined with the first preset mapping relationship table to determine the factory location and year of the vehicle. Of course, in actual situations, the first preset mapping relationship table can be split into two mapping relationship tables, which are the mapping relationship table between the code and the factory place and the mapping relationship table between the code and the factory year.

Step a12: Obtain the factory price of the vehicle according to the factory location, the vehicle manufacturer, the vehicle model, and a second preset mapping relationship table;

Step a13, obtaining the current year, and calculating the delivery life of the vehicle according to the current year and the delivery year;

After determining the factory location and year of the vehicle, the factory price of the vehicle is obtained according to the factory location, vehicle manufacturer, model and the second preset mapping relationship table, and then the current year is obtained, and the vehicle is calculated according to the current year and factory year Factory life. Wherein, the second preset mapping relationship table includes the mapping relationships between different factory locations, vehicle manufacturers and models, and factory prices.

Step a14: Calculate the estimated value of the vehicle according to the ex-factory price, the ex-factory age and a preset calculation formula.

Calculate the estimated value of the vehicle based on the ex-factory price, ex-factory age and preset calculation formula. Among them, the preset calculation formula is:

Among them, y is the estimated value, x is the ex-factory price, and i is the ex-factory life.

Step a2: Determine the non-essential auto insurance types to be recommended according to the estimated value, the purchase period and the historical insurance types;

After the estimated value is calculated, the non-essential auto insurance types to be recommended are determined based on the estimated value, purchase period and historical insurance types. Among them, non-essential car insurance types include separate glass breakage insurance, vehicle theft rescue, vehicle parking loss insurance, spontaneous combustion loss insurance, no-fault liability insurance, and body scratch damage insurance. The rules for determining non-essential car insurance types can be: 1) For separate glass breakage insurance and vehicle theft rescue, it can be determined based on the estimated value and purchase period. Specifically, when the purchase period is less than 1 year, or the estimated value is ≥500,000 , It is determined that separate glass breakage insurance and vehicle theft rescue are non-essential car insurance types to be recommended, otherwise it will not be recommended; 2) For vehicle parking loss insurance, spontaneous combustion loss insurance, no-fault liability insurance, and body scratch loss insurance, It is determined based on the estimated value and historical insurance types. Specifically, when the estimated value is ≥500,000, and it is determined that one or more of the above types of insurance was purchased in the previous year based on the historical insurance type information, the The insurances purchased in the above types are non-essential car insurance types to be recommended, otherwise they are not recommended.

Step a3: Obtain the first recommended auto insurance type according to the non-essential auto insurance type to be recommended and the preset required auto insurance type, and determine the historical insurance company as the to-be-recommended insurance company.

According to the aforementioned determined non-essential car insurance types to be recommended and preset necessary car insurance types, the first type of car insurance to be recommended is obtained, and the historical insurance company is determined as the insurance company to be recommended. Among them, the pre-determined necessary auto insurance types can include compulsory traffic insurance, third party liability insurance, vehicle loss insurance, vehicle personnel liability insurance, and non-deductible special insurance. The to-be-recommended insurance company can be determined by all companies insured in history, or companies insured in the past year or in recent years among the insured companies in history. According to the historical insurance company to determine the insurance company to be recommended, it is more in line with the user's renewal habit, that is, more than 70% of users tend to renew the insurance when the final premium is not much different.

It should be noted that the above-mentioned delimitation of non-essential car insurance types and mandatory car insurance types, as well as the determination and recommendation rules for non-essential car insurance types, are not used to limit this application. Non-essential car insurance types and necessary car insurance types can be delineated according to actual conditions. , You can also set the recommended rules for determining non-essential car insurance types according to the actual situation.

Step S30: Determine the first estimated auto insurance premium of the first to-be-recommended auto insurance type according to the historical auto insurance information, the historical insurance information, and the vehicle information;

Then, the first estimated auto insurance premium of the first auto insurance type to be recommended is determined according to the historical auto insurance information, the historical accident information and the vehicle information. Specifically, first calculate the insurance premium of each first to-be-recommended auto insurance type according to the corresponding calculation rules according to the historical auto insurance information, historical out-of-risk information, and vehicle information. Sum and get the first estimated auto insurance cost of the first recommended auto insurance type. Among them, historical auto insurance information includes historical insurance types and historical insurance companies, as well as historical insurance amounts. Vehicle information includes not only the frame number, vehicle manufacturer, model, and purchase age, but also the number of seats. For each type of auto insurance The insurance premium calculation rules are different for different types of insurance. The specific classification descriptions are as follows: (1) Compulsory traffic insurance, that is, compulsory motor vehicle traffic accident liability insurance. The number of seats in the vehicle is first determined according to the vehicle manufacturer and model, and then according to the number of seats and factory age Determine the basic premium, and then determine the premium for compulsory insurance based on the basic premium and vehicle insurance information. (2) Third party liability insurance. The third party liability insurance premium is determined based on the third party liability insurance insured amount in the previous year. If third party liability insurance was purchased in the previous year, the insured amount will be the same as the previous year. The year remains the same. (3) Vehicle loss insurance is determined based on the basic premium and ex-factory price (determined according to vehicle information) determined above. Specifically, the insurance premium of vehicle loss insurance = basic premium + ex-factory price × 1.0880%. (4) On-board personnel liability insurance is calculated based on the number of seats in the vehicle and the preset single premium. The premium of the on-board personnel liability insurance = preset single premium (such as 50) * the number of seats in the vehicle. (5) Excluding special deductible insurance and spontaneous combustion loss insurance, the insurance premium = ex-factory price * 0.15%. (6) The independent glass breakage insurance is determined according to the factory location and ex-factory price of the vehicle (the factory location and the ex-factory price are determined according to the vehicle information), the insurance premium of the independent glass breakage insurance = the factory price of the imported new car * 0.25%, or, The insurance premium for the individual glass breakage insurance = the factory price of a new domestic car * 0.15%. (7) For vehicle theft rescue and vehicle parking loss insurance, the insurance premium = basic premium + ex-factory price × rate. (8) Engine water ingress insurance, the insurance premium of the engine water ingress insurance = basic insurance premium + ex-factory price x 1.0880%) * 5%. (9) No-fault liability insurance. The premium of no-fault liability insurance = the premium of third party liability insurance * 20%. (10) The car body scratch damage insurance is determined based on the estimated value (determined according to the vehicle information) and the insurance amount of the car body scratch damage insurance in the previous year. Of course, it should be noted that the above calculation rule settings can be updated and set according to actual conditions, and are not used to limit this application.

Step S40: Obtain the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculate the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information;

After the first estimated auto insurance fee is calculated, the first preferential information of the preset insurance company for the first recommended auto insurance type is obtained, and the first actual auto insurance cost is calculated according to the first estimated auto insurance cost and the first preferential information. Specifically, the first discount information may include discount point information and gift information. For the calculation of the first actual auto insurance fee, the discounted estimated auto insurance fee may be calculated according to the first estimated auto insurance fee and discount point information, and Give the gift information to get the gift amount, and then subtract the discounted estimated auto insurance premium and the gift amount to get the first actual auto insurance premium.

Step S50: Generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.

Finally, the corresponding first recommendation information is generated according to the first actual car insurance premium and the insurance company to be recommended, and the first recommendation information is pushed to the corresponding user terminal. The specific recommendation rules may include but are not limited to: 1) According to the first actual auto insurance premium, select the insurance company with the lowest preset number (for example, 3) of the first actual auto insurance premium, and the insurance company to be recommended, and then check the above insurance The company ranks and recommends according to the first actual auto insurance premium; 2) According to the first actual auto insurance premium, select the preset number (such as 3) insurance companies with the lowest first actual auto insurance premium, and check whether there are any insurance companies to be recommended , Synthesize the first actual auto insurance premium and whether to rank recommendation for the insurance company to be recommended.

In addition, in addition to the selected recommended company, the first recommended auto insurance type, and the first actual auto insurance premium, the first recommended information can also display the insurance premiums and discount information of each recommended company, and display the first actual auto insurance premium. The calculation process information makes the information transparent, so that users can understand the calculation rules of car insurance premiums intuitively and clearly, and enhance the user's sense of experience and security.

This application provides a method for car insurance recommendation. When a request for car insurance recommendation is received, the target vehicle identifier in the car insurance recommendation request is extracted, and the pre-created data index is searched according to the target vehicle identifier to obtain the target data address; according to the target data address Obtain the vehicle information, historical auto insurance information and historical risk information of the corresponding vehicle, and determine the first recommended auto insurance type and insurance company to be recommended according to the historical auto insurance information and vehicle information according to the first preset rule; according to the historical auto insurance information and historical risk information Determine the first estimated auto insurance cost of the first recommended auto insurance type with vehicle information; obtain the first discount information of the preset insurance company for the first recommended auto insurance type, and calculate it based on the first estimated auto insurance cost and the first discount information The first actual car insurance fee; according to the first actual car insurance fee and the insurance company to be recommended, corresponding first recommendation information is generated, and the first recommendation information is pushed to the corresponding user terminal. This application can intelligently recommend auto insurance based on multiple dimensions of information such as vehicle information, historical auto insurance information, historical insurance information, and preferential information of various companies, which can prevent users from being promoted to purchase unnecessary insurance types, and there is no need for users to compare and choose by themselves. This can improve the user experience and at the same time improve the accuracy of auto insurance recommendations.

Based on the foregoing implementation manners, a second embodiment of the auto insurance recommendation method of this application is proposed. Referring to Fig. 3, Fig. 3 is a schematic flowchart of a second embodiment of a method for recommending auto insurance according to this application.

Based on the first embodiment shown in Figure 2 above, in this embodiment, in step "determine the first to-be-recommended car insurance type and the to-be-recommended insurance company according to the first preset rule according to the historical car insurance information and the vehicle information" Previously, this auto insurance recommendation method could also include:

Step A, judging whether the vehicle is a new vehicle according to the purchase age;

Since the new car has no historical insurance information and historical auto insurance information, the corresponding recommendation rules will be different. Therefore, in this embodiment, after the server obtains the vehicle information, it can first determine whether the vehicle is purchased based on the purchase age in the vehicle information It is a new car, for example, to detect whether the purchase age is 0. Of course, it is also possible to directly detect whether historical insurance information and historical auto insurance information can be queried.

When it is determined that the vehicle is not a new car, perform the following steps: determine the first type of auto insurance to be recommended and the insurance company to be recommended in accordance with the first preset rule according to the historical auto insurance information and the vehicle information;

When it is determined that the vehicle is not a new car, query the historical car insurance information and historical risk information of the corresponding vehicle according to the vehicle information, and determine the first to-be-recommended car insurance type and the to-be-recommended insurance according to the historical car insurance information and vehicle information according to the first preset rule Company, and perform the subsequent steps, the process can refer to the above-mentioned first embodiment, which will not be repeated here.

When it is determined that the vehicle is a new car, perform step B: determine the second car insurance to be recommended according to the vehicle information according to the second preset rule, and determine the second car insurance to be recommended according to the vehicle information Estimated auto insurance costs;

When it is determined that the vehicle is a new car, at this time, the second car insurance type to be recommended is determined according to the vehicle information according to the second preset rule, and the second estimated car insurance premium of the second car insurance type to be recommended is determined according to the vehicle information. Specifically, the estimated value is first calculated according to the frame number, vehicle manufacturer and model in the vehicle information. The specific calculation method can refer to the first embodiment, and then the non-essential car insurance types to be recommended are determined based on the estimated value and historical insurance types. Since the vehicle is a new car, its non-essential car insurance types only include vehicle stoppage loss insurance, spontaneous combustion loss insurance, no-fault liability insurance, and body scratch damage insurance. The aforementioned non-essential car insurance types can be determined based on estimated value and historical insurance types. Specifically, when the estimated value is ≥500,000 and it is determined that one or more of the above types of insurance was purchased in the previous year based on the historical insurance type information, the insurance of the above types purchased in the previous year is determined to be recommended Non-essential car insurance types of insurance, otherwise it is not recommended.

Determine the non-essential car insurance types to be recommended for the new car, and then combine the necessary car insurance types of the new car (including compulsory traffic insurance, third party liability insurance, vehicle loss insurance, vehicle personnel liability insurance, special insurance without deductible, and separate glass breakage insurance And vehicle theft rescue) to get the second type of auto insurance to be recommended. Then, according to the vehicle information according to the corresponding calculation rules, the insurance premiums of the second car insurance types to be recommended are calculated, and after the insurance premiums of the second car insurance types to be recommended are obtained, they are added to obtain the second car insurance types to be recommended Second estimated auto insurance cost. Among them, the calculation rules for the insurance premium of each second to-be-recommended auto insurance category are the same as the calculation rules described in the first embodiment above except for the third party liability insurance. For the third party liability insurance of a new car, the insured amount is 1 million by default, and then the insurance premium corresponding to the insured amount is checked to obtain the insurance premium of the third party liability insurance.

Step C: Obtain the second preferential information of the preset insurance company for the second auto insurance type to be recommended, and calculate the second actual auto insurance cost according to the second estimated auto insurance cost and the second preferential information;

After the second estimated auto insurance premium is calculated, the second preferential information of the preset insurance company for the second to-be-recommended auto insurance type is obtained, and the second actual auto insurance premium is calculated based on the second estimated auto insurance cost and the second preferential information . Wherein, the specific calculation method of the second actual auto insurance premium is consistent with the calculation method of the first actual auto insurance premium in the foregoing embodiment, and reference may be made to the foregoing first embodiment, which will not be repeated here.

Step D: Generate corresponding second recommendation information according to the second actual car insurance premium, and push the second recommendation information to the corresponding user terminal.

Finally, the corresponding second recommendation information is generated according to the second actual car insurance premium and the insurance company to be recommended, and the second recommendation information is pushed to the corresponding user terminal. The specific recommendation rule can be: according to the second actual auto insurance cost, select the insurance company with the second preset number (such as 5) with the lowest actual auto insurance cost, and then select the insurance company according to the second actual auto insurance cost. The size is sorted and recommended.

Of course, when the vehicle is a new car, the service information of the preset insurance company can also be obtained, the service information can be scored, and the service score of each preset insurance company can be obtained, and then the second actual car insurance premium and service score can be combined for recommendation. Among them, the service information may include, but is not limited to, the order of payment and car repair, the time from report to compensation, and the number of free road rescues. Scores corresponding to various services can be set, and then the service scores of each preset insurance company can be calculated. At the time of recommendation, according to the second actual auto insurance cost and service score, the insurance company with the lowest preset number (such as 3) and the preset number (such as 3) with the highest service score can be selected. The insurance companies of the selected insurance companies are then sorted and recommended according to the second actual car premium insurance of each selected insurance company in ascending order. When the same second actual car premium insurance exists, the ranking is determined according to the service score.

This embodiment provides a method for recommending auto insurance for a new car, which can intelligently recommend auto insurance based on information such as vehicle information and preferential information of various companies, which can prevent users from being promoted to purchase unnecessary insurance types, and there is no need for users to compare and choose by themselves, thereby improving user experience.

Based on the foregoing embodiments, a third embodiment of the method for recommending auto insurance in this application is proposed.

In this embodiment, after step S50 in the first and second embodiments, the auto insurance recommendation method further includes:

Upon receiving the auto insurance application request triggered by the user based on the first recommendation information, the first target insurance company and the first target insurance type are determined according to the auto insurance application request, and the first target insurance company and the first target insurance type are determined Insured.

In this embodiment, after the user receives the first recommendation information through the user terminal, he can select the company he wants to insure based on the first recommendation information to apply for insurance. Of course, he can also make adjustments such as adding and deleting recommended auto insurance types. After selecting the insurance, the auto insurance application request can be triggered. At this time, when the server receives the auto insurance application request triggered by the user based on the first recommendation information, the first target insurance company and the first target insurance type are determined according to the auto insurance application request, and according to the first The target insurance company and the first target insurance type are insured. This embodiment can facilitate the user to directly apply for insurance based on the recommended information, which can improve user experience.

Of course, it is understandable that after step S90 based on the above second embodiment, the auto insurance recommendation method further includes:

Upon receiving the auto insurance application request triggered by the user based on the second recommendation information, the third target insurance company and the third target insurance type are determined according to the auto insurance application request, and the third target insurance company and the third target insurance type are determined Insured.

Correspondingly, when the vehicle is a new car, after the user receives the second recommendation information through the user terminal, the user can also apply for insurance based on the second recommendation information. At this time, the server receives the auto insurance application request triggered by the user based on the second recommendation information. , Determine the third target insurance company and the third target insurance type according to the auto insurance application request, and insure according to the third target insurance company and the third target insurance type.

In one of the embodiments, based on the foregoing embodiments, a fourth embodiment of the auto insurance recommendation method of this application is proposed.

In this embodiment, based on the first embodiment shown in FIG. 2, after step S50, the auto insurance recommendation method further includes:

Step E: Obtain the auto insurance expiration remaining time of the vehicle regularly, and detecting whether the auto insurance expiration remaining time is less than a preset time threshold;

In this embodiment, the server may periodically obtain the remaining time of the vehicle insurance expiration of the vehicle, and detect whether the remaining time of the vehicle insurance expiration is less than a preset time threshold. Specifically, the historical auto insurance information of the auto insurance can be obtained according to the frame number, the auto insurance expiration time is obtained therefrom, and then the current time is obtained, and the auto insurance expiration remaining time is calculated according to the auto insurance expiration time and the current time, and then it is detected whether the auto insurance expiration remaining time is less than Preset time threshold. Among them, the preset time threshold can be set according to actual conditions, and is not limited here.

Step F: When it is detected that the remaining time of auto insurance expiration is less than the preset time threshold, it is detected whether the automatic insurance application function has been turned on;

When it is detected that the remaining time of auto insurance expiration is less than the preset time threshold, it indicates that the auto insurance is about to expire. At this time, the automatic insurance function is detected whether it has been activated;

If the automatic insurance application function has been activated, perform step G: determine the second target insurance company and the second target insurance type according to the first recommendation information, and renew the insurance according to the second target insurance company and the second target insurance type;

If the automatic insurance application function is enabled, at this time, the second target insurance company and the second target insurance type are determined according to the first recommendation information, and the insurance is renewed according to the second target insurance company and the second target insurance type. Specifically, the insurance company ranked first in the first recommendation information and the recommended auto insurance type can be selected as the second target insurance company and the second target insurance type.

If the automatic insurance application function is not enabled, step H is executed: corresponding prompt information is generated and sent to the user terminal to prompt the user to renew the insurance.

If the automatic insurance application function is not enabled, a corresponding prompt message is generated and sent to the corresponding user terminal to prompt the user to renew the insurance.

In this embodiment, in order to prevent the user from forgetting to renew the insurance, an automatic insurance application function can also be set for the user to choose. When the server detects that the auto insurance expired remaining time is less than the preset time threshold and the automatic insurance application function is turned on, the server can 1. The recommendation information is automatically insured, so that the user does not need to pay attention to whether the auto insurance is expired or make a selection, which can realize the automatic insuring and improve the user experience. At the same time, it can prompt the user to renew the insurance when it is detected that the remaining time of the auto insurance expiration is less than the preset time threshold, but the automatic insurance function is not turned on, so as to prevent the user from forgetting to renew the insurance and improve the user experience.

This application also provides a car insurance recommendation device.

Referring to Fig. 3, Fig. 3 is a schematic diagram of the functional modules of the first embodiment of the car insurance recommendation device of this application.

In this embodiment, the car insurance recommendation device includes:

The address obtaining module 10 is configured to extract the target vehicle identifier in the auto insurance recommendation request when receiving the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

The information determining module 20 is configured to obtain vehicle information, historical auto insurance information, and historical accident information of the corresponding vehicle according to the target data address, and determine the first pending rule according to the historical auto insurance information and the vehicle information according to the first preset rule. Recommended types of auto insurance and insurance companies to be recommended;

The first calculation module 30 is configured to determine the first estimated auto insurance premium of the first to-be-recommended auto insurance type according to the historical auto insurance information, the historical insurance information, and the vehicle information;

The second calculation module 40 is configured to obtain first preferential information of a preset insurance company for the first to-be-recommended auto insurance type, and calculate the first actual car insurance according to the first estimated auto insurance cost and the first preferential information fee;

The first push module 50 is configured to generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.

Among them, each virtual function module of the above-mentioned car insurance recommendation device is stored in the memory 1005 of the car insurance recommendation device shown in FIG. 1, and is used to realize all the functions of the car insurance recommendation program; when each module is executed by the processor 1001, it can be realized according to vehicle information, The function of intelligently recommending auto insurance with information such as historical auto insurance information, historical insurance information and preferential information of various companies.

In one of the embodiments, the vehicle information includes frame number, vehicle manufacturer, model, and purchase age, the historical auto insurance information includes historical insurance types and historical insurance companies, and the information determining module 20 includes:

The first calculation unit is configured to calculate the estimated value of the vehicle according to the frame number, the vehicle manufacturer, and the model according to a preset calculation rule;

The first information determining unit is configured to determine the non-essential auto insurance types to be recommended according to the estimated value, the purchase period, and the historical insurance types;

The second information determining unit is configured to obtain the first recommended auto insurance type according to the non-essential auto insurance type to be recommended and the preset required auto insurance type, and determine the historical insurance company as the to-be-recommended insurance company.

Among them, the function realization of each module in the above-mentioned car insurance recommendation device corresponds to each step in the embodiment of the above-mentioned car insurance recommendation method, and the functions and realization processes thereof are not repeated here.

The present application also provides a car insurance recommendation device. The car insurance recommendation device includes a memory, a processor, and a car insurance recommendation program stored on the memory and running on the processor, and the car insurance recommendation program is used by the processor. The steps of the auto insurance recommendation method as described in any of the above embodiments are implemented during execution.

The specific embodiments of the car insurance recommendation device of this application are basically the same as the embodiments of the above-mentioned car insurance recommendation method, and will not be repeated here.

The present application also provides a computer-readable storage medium having a car insurance recommendation program stored on the computer-readable storage medium. When the car insurance recommendation program is executed by a processor, the method for car insurance recommendation as described in any of the above embodiments is implemented. step. The computer-readable storage medium may be a non-volatile storage medium or a volatile storage medium.

The specific embodiments of the computer-readable storage medium of the present application are basically the same as the embodiments of the above-mentioned auto insurance recommendation method, and will not be repeated here.

It should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements not only includes those elements, It also includes other elements that are not explicitly listed, or elements inherent to the process, method, article, or system. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, article or system that includes the element.

The serial numbers of the foregoing embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better.的实施方式。 Based on this understanding, the technical solution of this application essentially or the part that contributes to the existing technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM/RAM) as described above. , Magnetic disk, optical disk), including several instructions to make a device (can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) execute the method described in each embodiment of the present application.

The above are only preferred embodiments of this application, and do not limit the scope of this application. Any equivalent structure or equivalent process transformation made using the content of the description and drawings of this application, or directly or indirectly used in other related technical fields , The same reason is included in the scope of patent protection of this application.

Claims

A method for recommending car insurance, which includes the following steps:

When receiving the auto insurance recommendation request, extract the target vehicle identifier in the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

Obtain the vehicle information, historical auto insurance information, and historical risk information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended auto insurance type and the to-be-recommended insurance according to the first preset rule according to the historical auto insurance information and the vehicle information the company;

Determining the first estimated auto insurance premium of the first auto insurance type to be recommended according to the historical auto insurance information, the historical insurance information, and the vehicle information;

Acquiring the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculating the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information;

Generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.
The method for recommending auto insurance according to claim 1, wherein the vehicle information includes frame number, vehicle manufacturer, model, and purchase age, the historical auto insurance information includes historical insurance types and historical insurance companies, and the historical auto insurance information The steps of determining the first type of auto insurance to be recommended and the insurance company to be recommended according to the first preset rule and the vehicle information include:

Calculate the estimated value of the vehicle according to the frame number, the vehicle manufacturer and the model according to preset calculation rules;

Determine the non-essential auto insurance types to be recommended according to the estimated value, the purchase period and the historical insurance types;

According to the non-essential car insurance types to be recommended and the preset necessary car insurance types, the first to-be recommended car insurance types are obtained, and the historical insurance company is determined as the insurance company to be recommended.
The method for recommending car insurance according to claim 2, wherein the step of calculating the estimated value of the vehicle according to the frame number, the vehicle manufacturer and the model according to a preset calculation rule comprises:

Determining the factory place and year of the vehicle according to the frame number and the first preset mapping relationship table;

Obtaining the ex-factory price of the vehicle according to the factory location, the vehicle manufacturer, the vehicle model, and a second preset mapping relationship table;

Obtain the current year, and calculate the factory age of the vehicle according to the current year and the factory year;

Calculating the estimated value of the vehicle according to the ex-factory price, the ex-factory age and a preset calculation formula;

Wherein, the preset calculation formula is:

Among them, y is the estimated value, x is the ex-factory price, and i is the ex-factory life.
The auto insurance recommendation method according to claim 2, before the step of determining the first auto insurance type to be recommended and the insurance company to be recommended according to the historical auto insurance information and the vehicle information according to a first preset rule, the method further include:

Judging whether the vehicle is a new car according to the purchase period;

When it is determined that the vehicle is not a new car, perform the following steps: determine the first type of auto insurance to be recommended and the insurance company to be recommended in accordance with the first preset rule according to the historical auto insurance information and the vehicle information;

When it is determined that the vehicle is a new car, the second car insurance type to be recommended is determined according to the vehicle information according to the second preset rule, and the second estimated car insurance cost of the second car insurance type to be recommended is determined according to the vehicle information ；

Acquiring second preferential information of the preset insurance company for the second to-be-recommended auto insurance type, and calculating a second actual auto insurance premium according to the second estimated auto insurance premium and the second preferential information;

Generate corresponding second recommendation information according to the second actual car insurance premium, and push the second recommendation information to the corresponding user terminal.
8. The car insurance recommendation method according to claim 1, the car insurance recommendation method further comprising:

Upon receiving the auto insurance application request triggered by the user based on the first recommendation information, the first target insurance company and the first target insurance type are determined according to the auto insurance application request, and the first target insurance company and the first target insurance type are determined Insured.
8. The car insurance recommendation method according to claim 1, the car insurance recommendation method further comprising:

Regularly acquiring the remaining time of auto insurance expiration of the vehicle, and detecting whether the remaining time of auto insurance expiration is less than a preset time threshold;

When it is detected that the remaining time of auto insurance expiration is less than the preset time threshold, check whether the automatic insurance function has been turned on;

If the automatic insurance application function is activated, determine the second target insurance company and the second target insurance type according to the first recommendation information, and renew the insurance according to the second target insurance company and the second target insurance type;

If the automatic insurance application function is not enabled, a corresponding prompt message is generated and sent to the user terminal to prompt the user to renew the insurance.
8. The auto insurance recommendation method according to any one of claims 1 to 6, the auto insurance recommendation method further comprising:

When receiving the data access instruction, create a data index according to the data access instruction, and configure the attributes of the data index;

Obtain a data source address, establish a remote call connection with a target data source according to the data source address, and import data information corresponding to the data index from the target data source.
A car insurance recommendation device, which includes:

The address obtaining module is configured to extract the target vehicle identifier in the auto insurance recommendation request when receiving the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

The information determining module is used to obtain vehicle information, historical auto insurance information, and historical accident information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended according to the historical auto insurance information and the vehicle information according to the first preset rule Types of auto insurance and insurance companies to be recommended;

A first calculation module, configured to determine the first estimated auto insurance premium of the first auto insurance type to be recommended according to the historical auto insurance information, the historical insurance information, and the vehicle information;

The second calculation module is configured to obtain the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculate the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information ；

The first push module is configured to generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.
A car insurance recommendation device, which includes a memory, a processor, and a car insurance recommendation program stored in the memory and executable by the processor, wherein when the car insurance recommendation program is executed by the processor, Implement the steps of the following method.

When receiving the auto insurance recommendation request, extract the target vehicle identifier in the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

Obtain the vehicle information, historical auto insurance information, and historical risk information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended auto insurance type and the to-be-recommended insurance according to the first preset rule according to the historical auto insurance information and the vehicle information the company;

Determining the first estimated auto insurance premium of the first auto insurance type to be recommended according to the historical auto insurance information, the historical insurance information, and the vehicle information;

Acquiring the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculating the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information;

Generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.
The auto insurance recommendation device according to claim 9, wherein the vehicle information includes frame number, vehicle manufacturer, model, and purchase age, and the historical auto insurance information includes historical insurance types and historical insurance companies, and the historical auto insurance information and The step of determining the first vehicle insurance type to be recommended and the insurance company to be recommended according to the vehicle information according to the first preset rule includes:

Calculate the estimated value of the vehicle according to the frame number, the vehicle manufacturer and the model according to the preset calculation rules;

Determine the non-essential auto insurance types to be recommended according to the estimated value, the purchase period and the historical insurance types;

According to the non-essential car insurance types to be recommended and the preset necessary car insurance types, the first to-be recommended car insurance types are obtained, and the historical insurance company is determined as the insurance company to be recommended.
10. The vehicle insurance recommendation device according to claim 10, wherein the step of calculating the estimated value of the vehicle according to the frame number, the vehicle manufacturer and the model according to a preset calculation rule comprises:

Determining the factory place and year of the vehicle according to the frame number and the first preset mapping relationship table;

Obtaining the ex-factory price of the vehicle according to the factory location, the vehicle manufacturer, the vehicle model, and a second preset mapping relationship table;

Obtain the current year, and calculate the factory age of the vehicle according to the current year and the factory year;

Calculating the estimated value of the vehicle according to the ex-factory price, the ex-factory age and a preset calculation formula;

Wherein, the preset calculation formula is:

Among them, y is the estimated value, x is the ex-factory price, and i is the ex-factory life.
The auto insurance recommendation device according to claim 10, before the step of determining the first auto insurance type to be recommended and the insurance company to be recommended according to the historical auto insurance information and the vehicle information according to a first preset rule, the method further comprises :

Judging whether the vehicle is a new car according to the purchase period;

When it is determined that the vehicle is not a new car, perform the following steps: determine the first type of auto insurance to be recommended and the insurance company to be recommended in accordance with the first preset rule according to the historical auto insurance information and the vehicle information;

When it is determined that the vehicle is a new car, the second car insurance type to be recommended is determined according to the vehicle information according to the second preset rule, and the second estimated car insurance cost of the second car insurance type to be recommended is determined according to the vehicle information ；

Acquiring second preferential information of the preset insurance company for the second to-be-recommended auto insurance type, and calculating a second actual auto insurance premium according to the second estimated auto insurance premium and the second preferential information;

Generate corresponding second recommendation information according to the second actual car insurance premium, and push the second recommendation information to the corresponding user terminal.
The car insurance recommendation device according to claim 9, wherein the method for recommending car insurance further comprises:

Upon receiving the auto insurance application request triggered by the user based on the first recommendation information, the first target insurance company and the first target insurance type are determined according to the auto insurance application request, and the first target insurance company and the first target insurance type are determined Insured.
The car insurance recommendation device according to claim 9, wherein the method for recommending car insurance further comprises:

Regularly acquiring the remaining time of auto insurance expiration of the vehicle, and detecting whether the remaining time of auto insurance expiration is less than a preset time threshold;

When it is detected that the remaining time of auto insurance expiration is less than the preset time threshold, check whether the automatic insurance function has been turned on;

If the automatic insurance application function is activated, determine the second target insurance company and the second target insurance type according to the first recommendation information, and renew the insurance according to the second target insurance company and the second target insurance type;

If the automatic insurance application function is not enabled, a corresponding prompt message is generated and sent to the user terminal to prompt the user to renew the insurance.
The car insurance recommendation device according to any one of claims 9 to 14, the car insurance recommendation method further comprising:

When receiving the data access instruction, create a data index according to the data access instruction, and configure the attributes of the data index;

Obtain a data source address, establish a remote call connection with a target data source according to the data source address, and import data information corresponding to the data index from the target data source.
A computer storage medium storing a car insurance recommendation program, wherein when the car insurance recommendation program is executed by a processor, the steps of the following method are implemented:

When receiving the auto insurance recommendation request, extract the target vehicle identifier in the auto insurance recommendation request, and query the pre-created data index according to the target vehicle identifier to obtain the target data address;

Obtain the vehicle information, historical auto insurance information, and historical risk information of the corresponding vehicle according to the target data address, and determine the first to-be-recommended auto insurance type and the to-be-recommended insurance according to the first preset rule according to the historical auto insurance information and the vehicle information the company;

Determining the first estimated auto insurance premium of the first auto insurance type to be recommended according to the historical auto insurance information, the historical insurance information, and the vehicle information;

Acquiring the first preferential information of the preset insurance company for the first to-be-recommended auto insurance type, and calculating the first actual auto insurance cost according to the first estimated auto insurance cost and the first preferential information;

Generate corresponding first recommendation information according to the first actual car insurance premium and the insurance company to be recommended, and push the first recommendation information to the corresponding user terminal.
The storage medium according to claim 16, wherein the vehicle information includes frame number, vehicle manufacturer, model, and purchase age; the historical auto insurance information includes historical insurance types and historical insurance companies; and the historical auto insurance information includes historical insurance According to the vehicle information, the steps of determining the first type of auto insurance to be recommended and the insurance company to be recommended according to the first preset rule include:

Calculate the estimated value of the vehicle according to the frame number, the vehicle manufacturer and the model according to preset calculation rules;

Determine the non-essential auto insurance types to be recommended according to the estimated value, the purchase period and the historical insurance types;

According to the non-essential car insurance types to be recommended and the preset necessary car insurance types, the first to-be recommended car insurance types are obtained, and the historical insurance company is determined as the insurance company to be recommended.
The storage medium according to claim 17, wherein the step of calculating the estimated value of the vehicle according to a preset calculation rule according to the frame number, the vehicle manufacturer and the model comprises:

Determining the factory place and year of the vehicle according to the frame number and the first preset mapping relationship table;

Obtaining the ex-factory price of the vehicle according to the factory location, the vehicle manufacturer, the vehicle model, and a second preset mapping relationship table;

Obtain the current year, and calculate the factory age of the vehicle according to the current year and the factory year;

Calculating the estimated value of the vehicle according to the ex-factory price, the ex-factory age, and a preset calculation formula;

Wherein, the preset calculation formula is:

Among them, y is the estimated value, x is the ex-factory price, and i is the ex-factory life.
The storage medium according to claim 17, before the step of determining the first to-be-recommended auto insurance type and the to-be-recommended insurance company according to the first preset rule according to the historical auto insurance information and the vehicle information, the method further comprises:

Judging whether the vehicle is a new vehicle according to the purchase period;

When it is determined that the vehicle is not a new car, perform the following steps: determine the first type of auto insurance to be recommended and the insurance company to be recommended in accordance with the first preset rule according to the historical auto insurance information and the vehicle information;

When it is determined that the vehicle is a new car, the second car insurance type to be recommended is determined according to the vehicle information according to the second preset rule, and the second estimated car insurance cost of the second car insurance type to be recommended is determined according to the vehicle information ；

Acquiring second preferential information of the preset insurance company for the second auto insurance type to be recommended, and calculating a second actual auto insurance premium according to the second estimated auto insurance premium and the second preferential information;

Generate corresponding second recommendation information according to the second actual car insurance premium, and push the second recommendation information to the corresponding user terminal.
The storage medium of claim 16, further comprising:

Upon receiving the auto insurance application request triggered by the user based on the first recommendation information, the first target insurance company and the first target insurance type are determined according to the auto insurance application request, and the first target insurance company and the first target insurance type are determined Insured.