CN113362137A - Insurance product recommendation method and device, terminal equipment and storage medium - Google Patents
Insurance product recommendation method and device, terminal equipment and storage mediumDownload PDFInfo
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Abstract
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to an insurance product recommendation method and device, terminal equipment and a storage medium.
Background
With the development of the mobile internet, the insurance industry gradually starts to recommend insurance schemes to users through the mobile terminal through the network. For example, in the prior art, after a user fills in basic information on an insurance application, the insurance application outputs a corresponding guarantee plan according to the basic information filled by the user. In the process of collecting user information, when reverse proxy software such as Apache, Nagix and the like is used, the real IP address of the user cannot be obtained, so that effective information of the user cannot be obtained, and further inaccuracy of a final recommendation guarantee scheme is caused. In addition, the guarantee scheme recommended by the conventional recommendation method is often obtained through a simple feature mapping relationship, so that the recommended scheme cannot meet the personalized requirements of the user, or cannot be matched with the actual conditions of the user, or cannot meet the current family conditions in budget, cannot be adapted according to the subjective requirements of the user, and the like.
Therefore, in the process of recommending internet insurance products, if the effective information of the user is collected and if the personalized guarantee scheme matched with the user is output according to the collected effective information, the method is a technical problem of popularization of the current internet insurance products.
Disclosure of Invention
In view of this, embodiments of the present invention provide an insurance product recommendation method, apparatus, terminal device and storage medium, so as to solve the problem that existing internet insurance product recommendation is inaccurate.
In a first aspect of the embodiments of the present invention, there is provided an insurance product recommendation method, including: acquiring user information, wherein the user information at least comprises user age, user gender and a real IP address of a user; determining the risks of the users and the responsibility incidence rate corresponding to each risk according to the ages and the sexes of the users; analyzing the risk exposure of the user at least according to the real IP address of the user; dividing the risk of the user into a protectable risk and an insurable risk according to whether an insurance product matched with the risk of the user exists in the insurance product database, and sequencing and displaying the protectable risk and the insurable risk, wherein the protectable risk is the risk of the corresponding insurance product, and the insurable risk is the risk of no corresponding insurance product; calculating expected loss of the insured risk of the user according to the risk exposure and the risk liability occurrence rate of the user; and sequencing the insured risk of the user according to the calculated expected loss, determining the minimum value of the numerical interval according to the risk exposure of the user and the highest premium of the insurance product corresponding to the insured risk, and determining the recommended guarantee scheme of the insured risk of the user.
In some alternatives, obtaining the user's true IP address includes: a mod _ remoteip module provided in a web server Apache is used For identifying a real IP address of an HTTP request end in an HTTP extended header X-Forwarded-For; and determining the IP address with the highest frequency as the real IP address of the user based on the number and time of the IP addresses acquired by the identification.
In some alternatives, the user age and the user gender are obtained according to at least one of: inviting the user to fill in the plan book, the user evaluation and the user account number initial registration on the terminal equipment.
In some alternatives, the determining the risks of the user and the liability occurrence rate corresponding to each of the risks according to the age and the gender of the user includes: acquiring a preset risk occurrence table, wherein the risk occurrence table comprises a plurality of risks mapped with different age distributions under different sexes and responsibility occurrence rate corresponding to each risk; and identifying the risk corresponding to the age and the gender of the user and the liability occurrence rate of the risk according to the risk occurrence table.
In some alternatives, the ranking the insured risk and the unsecured risk to display comprises: the insured risk is ranked ahead of the unsecured risk.
In some alternatives, further comprising: according to the liability occurrence rate of insurance, the insurable risk with high liability occurrence rate is ranked ahead.
In some alternatives, the calculation formula for the expected loss of securable risk is: incidence of liability of risk exposure.
In a second aspect of the embodiments of the present invention, there is provided an insurance product recommendation apparatus, including: the information acquisition module is configured to acquire user information, wherein the user information at least comprises user age, user gender and a real IP address of a user; the risk query module is configured to determine risks of the users and responsibility incidence rates corresponding to the risks according to ages and sexes of the users; a risk calculation module configured to resolve a risk exposure of the user based at least on the user's real IP address; the risk classification module is configured to classify the risks of the users into insured risks and non-insured risks according to whether insurance products matched with the risks of the users exist in the insurance product database or not, and sequence and display the insured risks and the non-insured risks, wherein the insured risks are risks of the corresponding insurance products, and the non-insured risks are risks of no corresponding insurance products; a period loss calculation module configured to calculate an expected loss of the insured risk of the user according to the risk exposure of the user and the liability occurrence rate of the risk; and the insurance recommending module is configured to sort the insurable risk of the user according to the calculated expected loss, determine the minimum value of the numerical interval according to the risk exposure of the user and the highest premium of the insurance product corresponding to the insurable risk, and determine the recommended guarantee scheme of the insurable risk of the user.
In a third aspect of the embodiments of the present invention, there is provided a terminal device, including: a terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method according to any one of the first aspect when executing the computer program.
In a fourth aspect of the embodiments of the present invention, a storage medium is provided, which stores a computer program, and the computer program realizes the steps of the method according to any one of the first aspect when being executed by a processor.
Compared with the prior art, the embodiment of the invention has the following beneficial effects: in the process of collecting the user information, the real IP address of the user is obtained to depict the risk exposure of the user, the risk responsibility probability of the user is calculated, then the risk of the user is sequenced based on expected loss calculation, and the risk exposure and the responsibility occurrence rate of the user are integrated to match and output a special guarantee scheme to the user, so that the recommendation accuracy of the internet insurance products is improved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a flow chart of an implementation of the insurance product recommendation method of the invention in one embodiment;
FIG. 2 is a schematic diagram of an embodiment of an insurance product recommendation device of the present invention;
fig. 3 is a schematic structural diagram of a terminal device to which the insurance product recommendation method or the insurance product recommendation apparatus can be applied.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In order to explain the technical means of the present invention, the following description will be given by way of specific examples.
Referring to fig. 1, an implementation flow of the insurance product recommendation method according to an embodiment of the present invention is shown, and as shown in fig. 1, the insurance product recommendation method at least includes the following steps S01-S06:
step S01, user information is obtained, wherein the user information at least comprises user age, user gender and user real IP address.
Here, the user age and the user gender may be obtained by inviting the user to fill in a planned book on the terminal device, user evaluation, contents required to be filled in for initial registration of a user account, and the like.
The real IP address of the user is acquired by a network technique means after the terminal device used by the user accesses the network. In the process of acquiring the used IP address, if technical means of reverse proxy software such as Apache (Apache network server) and Nagix are adopted, the acquired user IP address may not be the real address of the user.
Specifically, acquiring the real IP address of the user may specifically include: a mod _ remoteip module provided in a web server Apache is used For identifying a real IP address of an HTTP request end in an HTTP extended header X-Forwarded-For; and determining the IP address with the highest frequency as the real IP address of the user based on the number and time of the IP addresses acquired by the identification. Wherein the mod _ remoteip module is a functional module in the Apache For using X-Forwarded-For. The IP address of the access user is obtained according to the Web server, the IP address information of the user is analyzed by using the address library, the position and the retention time of the user are analyzed after the latitude and longitude information of the user is analyzed, and therefore the constant address information of the user can be determined, the city grade of the user can be determined, the high-grade degree of a residential district can be determined, and the income and budget information of the user and the like can be judged.
Step S02, according to the age and sex of the user, determining the risk of the user and the liability occurrence rate corresponding to each risk.
Specifically, the bank guardian may periodically release various risk liability occurrence tables for users of different genders at different age stages. Therefore, according to the age and the sex of the user, the risk of the user and the corresponding liability incidence rate can be obtained. For example, the step S02 may specifically include: acquiring a preset risk occurrence table, wherein the risk occurrence table comprises a plurality of risks mapped with different age distributions under different sexes and responsibility occurrence rate corresponding to each risk; and identifying the risk corresponding to the age and the gender of the user and the liability occurrence rate of the risk according to the risk occurrence table.
And step S03, analyzing the risk exposure of the user at least according to the real IP address of the user.
Specifically, the real IP address of the user can analyze the grade and average income of the city where the user is located and the high-grade degree of the cell where the address is located, so that income and budget information of the user are judged, which is equivalent to supplementing financial characteristics of the user, and the risk exposure of the user can be calculated more accurately.
It should be noted that, different risks are different in the method for calculating the risk exposure of the user at the different risks, and the specific calculation method is calculated by using a preset calculation model. The existing calculation models or mathematical formulas can be used for reference of the calculation models of the risk exposure, the models relate to parameters of various factors, whether the calculation of the risk exposure is accurate or not, and whether specific parameter values in the calculation models or the mathematical formulas exist or not. Therefore, the prior art may be referred to for the specific calculation process of risk exposure, which is not described in detail in this embodiment.
Step S04, according to whether insurance products matched with the user risks exist in the insurance product database, dividing the user risks into insurable risks and insurable risks, and displaying the insurable risks and the insurable risks in a sequencing mode, wherein the insurable risks are risks of corresponding insurance products, and the insurable risks are risks of no corresponding insurance products.
The insurance product database is used for collecting insurance data of all insurance products on the market at present, classifying risks of users into insureable risks and non-insureable risks through the insurance product database, and sequencing the insureable risks and the non-insureable risks. The user can then know which risks have solutions and where the risks have no solutions according to the displayed ranking structure.
For example, according to the gender and age of the user, it is determined that the user has a nursing risk, and the insurance product database does not have a corresponding nursing insurance product, so the nursing risk is an unsecured risk. Conversely, if the risk of the user has a corresponding insurance product in the insurance product database, the risk is an insured risk.
In addition, by ranking the insurable risk and the insurable risk, the insurable risk can be ranked ahead of the insurable risk. In addition, because each risk of the user has a corresponding liability occurrence rate, the insured risk and the non-insured risk can be ranked according to the liability occurrence rate of the insurance. For example, the insured risk of high incidence of liability is ranked ahead.
And step S05, calculating expected loss of the insured risk of the user according to the risk exposure and the risk liability incidence of the user.
Specifically, since the budget for users to purchase insurance is limited, all insurance products cannot be purchased at one time. Therefore, the expected loss of the risk is recalculated, so that the risk can be guaranteed and the risk can not be guaranteed, the risk can be sorted according to the expected loss, the guarantee scheme sequence specific to the user can be output, and the decision can be made by the user.
For example, if the liability occurrence rate of medical risk of a 30-year-old user a in the next year is 1%, and the risk exposure is 100 ten thousand, the expected loss of medical risk corresponding to the user is 100 × 1% — 1 ten thousand.
And step S06, sequencing the insurable risk of the user according to the calculated expected loss, determining the minimum value of the numerical interval according to the risk exposure of the user and the highest premium of the insurance product corresponding to the insurable risk, and determining the recommended guarantee scheme of the insurable risk of the user.
Specifically, the ranked order of the insured risks is a suggestion for representing the user's priority in handling their own risks, by which the user's order of purchasing various insurance products is ultimately decided. The size of the risk exposure is a suggestion for indicating that the risk occurrence is the expected risk level, and ultimately determines the amount of the insurance product the user purchases. According to the method and the system, the guarantee scheme of the user risks is output through the risk exposure and the risk guaranteeing sequence of the user, and the user can make a decision on purchasing insurance products.
For example, the user's critical risk exposure is 100 ten thousand, but the majority of the critical risk reserves on the market are 0-50 ten thousand, up to no more than 50 ten thousand. Therefore, the guarantee amount of the guarantee scheme is min (the highest guarantee amount of the serious risk is open) which is 50 ten thousand min (100, 50). Thus, the final guarantee plan's warranty would select an insurance product with a warranty of 50 ten thousand. It is to be understood that a user's insurable risk may correspond to one or more insurance products.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
Based on the embodiment of FIG. 1, the invention also provides an insurance product recommendation device based on the same inventive concept. Referring to fig. 2, which shows a schematic structural diagram of an insurance product recommendation device in an embodiment of the present invention, as shown in fig. 2, the insurance product recommendation device 200 includes: the system comprises an information acquisition module 201, a risk query module 202, a risk calculation module 203, a risk classification module 204, a period loss calculation module 205 and an insurance recommendation module 206, wherein the information acquisition module 201 is configured to acquire user information, and the user information at least comprises user age, user gender and a real IP address of a user; the risk query module 202 is configured to determine risks of the user and liability incidence corresponding to each of the risks according to the age and gender of the user; the risk calculation module 203 is configured to resolve the risk exposure of the user according to at least the real IP address of the user; the risk classification module 204 is configured to classify the risk of the user into an insured risk and an unsecured risk according to whether there is an insurance product matching the risk of the user in the insurance product database, and rank and display the insured risk and the unsecured risk, wherein the insured risk is a risk of having a corresponding insurance product, and the unsecured risk is a risk of not having a corresponding insurance product; the installment loss calculation module 205 is configured to calculate an expected loss of the user's insured risk according to the risk exposure of the user and the liability occurrence rate of the risk; the insurance recommending module 206 is configured to rank the insured risk of the user according to the calculated expected loss, determine the minimum value of the numerical interval according to the highest premium of the insurance product corresponding to the insured risk and the risk exposure of the user, and determine the recommended guarantee scheme of the insured risk of the user.
In some optional embodiments, theinformation obtaining module 201 includes: the IP address acquisition unit is configured to utilize a mod _ remoteip module provided in a web server Apache to identify a real IP address of an HTTP request end in an HTTP extended header X-Forwarded-For; and determining the IP address with the highest frequency as the real IP address of the user based on the number and time of the IP addresses acquired by the identification.
In some optional embodiments, theinformation obtaining module 201 is further configured to obtain the user age and the user gender according to at least one of the following manners: inviting the user to fill in the plan book, the user evaluation and the user account number initial registration on the terminal equipment.
In some optional embodiments, therisk query module 202 is further configured to obtain a preset risk occurrence table, where the risk occurrence table includes a plurality of risks mapped to different age distributions of different genders and a liability occurrence rate corresponding to each of the risks; and identifying the risk corresponding to the age and the gender of the user and the liability occurrence rate of the risk according to the risk occurrence table.
In some optional embodiments, therisk classification module 204 is further configured to rank insured risk ahead of non-insured risk.
In some optional embodiments, therisk classification module 204 is further configured to prioritize insured risks with high liability incidence according to liability incidence of insurance
In some optional embodiments, the termloss calculation module 205 is further configured to calculate the expected loss of the securable risk by the formula: incidence of liability of risk exposure.
Because the insurance product recommendation device and the insurance product recommendation method provided by the invention belong to the same inventive concept and have the same specific technical characteristics, on the basis of the clear and complete explanation of the insurance product recommendation method, the related technical content of the insurance product recommendation device can refer to the insurance product recommendation method, and the details are not repeated.
In summary, in practice, the insurance product recommendation apparatus and the insurance product recommendation method provided by the present invention may be applied to a system architecture composed of a server and a user terminal, that is, the user terminal is connected to the server through a network, and the server may be configured to execute the method shown in fig. 1, where the user terminal may be an insurance application installed on a computing device such as a mobile phone or a computer.
Specifically, referring to fig. 3, a schematic structural diagram of a terminal device to which the insurance product recommendation method or the insurance product recommendation apparatus can be applied is shown, where the terminal device may be a server, and as shown in fig. 3, theterminal device 300 at least includes: aprocessor 301, a memory 302 and acomputer program 303 stored in said memory 302 and executable on saidprocessor 301. Theprocessor 301, when executing thecomputer program 303, implements the steps of the various insurance product recommendation method embodiments described above, such as the steps S01-S06 shown in fig. 1. Alternatively, theprocessor 301, when executing thecomputer program 303, implements the functions of the modules/units in the embodiments of the insurance product recommendation device, such as themodules 201 to 206 shown in fig. 2.
Illustratively, thecomputer program 303 may be partitioned into one or more modules/units that are stored in the memory 302 and executed by theprocessor 301 to implement the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used to describe the execution process of thecomputer program 303 in theterminal device 300. For example, thecomputer program 303 may be divided into aninformation acquisition module 201, arisk query module 202, arisk calculation module 203, arisk classification module 204, anerosion calculation module 205, and aninsurance recommendation module 206.
Theterminal device 300 may be a desktop computer, a notebook, a palm computer, a cloud server, or other computing devices. The terminal device may include, but is not limited to, aprocessor 301, a memory 302. Those skilled in the art will appreciate that fig. 3 is merely an example of aterminal device 300 and does not constitute a limitation ofterminal device 300 and may include more or fewer components than shown, or some components may be combined, or different components, for example, the terminal device may also include input output devices, network access devices, buses, etc.
TheProcessor 301 may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 302 may be an internal storage unit of theterminal device 300, such as a hard disk or a memory of theterminal device 300. The memory 302 may also be an external storage device of theterminal device 300, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, which are provided on theterminal device 300. Further, the memory 302 may also include both an internal storage unit and an external storage device of theterminal device 300. The memory 302 is used for storing the computer programs and other programs and data required by the terminal device. The memory 302 may also be used to temporarily store data that has been output or is to be output.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions. Each functional unit and module in the embodiments may be integrated in one processing unit, or each unit may exist alone physically, or two or more units are integrated in one unit, and the integrated unit may be implemented in a form of hardware, or in a form of software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working processes of the units and modules in the system may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and reference may be made to the related descriptions of other embodiments for parts that are not described or illustrated in a certain embodiment.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal device and method may be implemented in other ways. For example, the above-described embodiments of the apparatus/terminal device are merely illustrative, and for example, the division of the modules or units is only one logical division, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated modules/units, if implemented in the form of software functional units and sold or used as separate products, may be stored in a computer readable storage medium. Based on such understanding, all or part of the processes in the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium and can implement the steps of the embodiments of the insurance product recommendation method described above when the computer program is executed by a processor. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, an executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, Read-Only Memory (ROM), Random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present 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 solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An insurance product recommendation method, comprising:
acquiring user information, wherein the user information at least comprises user age, user gender and a real IP address of a user;
determining the risks of the users and the responsibility incidence rate corresponding to each risk according to the ages and the sexes of the users;
analyzing the risk exposure of the user at least according to the real IP address of the user;
dividing the risk of the user into a protectable risk and an insurable risk according to whether an insurance product matched with the risk of the user exists in the insurance product database, and sequencing and displaying the protectable risk and the insurable risk, wherein the protectable risk is the risk of the corresponding insurance product, and the insurable risk is the risk of no corresponding insurance product;
calculating expected loss of the insured risk of the user according to the risk exposure and the risk liability occurrence rate of the user;
and sequencing the insured risk of the user according to the calculated expected loss, determining the minimum value of the numerical interval according to the risk exposure of the user and the highest premium of the insurance product corresponding to the insured risk, and determining the recommended guarantee scheme of the insured risk of the user.
2. The method of claim 1, wherein obtaining the user's real IP address comprises:
a mod _ remoteip module provided in a web server Apache is used For identifying a real IP address of an HTTP request end in an HTTP extended header X-Forwarded-For;
and determining the IP address with the highest frequency as the real IP address of the user based on the number and time of the IP addresses acquired by the identification.
3. The method of claim 1, wherein the user age and user gender are obtained according to at least one of: inviting the user to fill in the plan book, the user evaluation and the user account number initial registration on the terminal equipment.
4. The method of claim 1, wherein said determining the risk of the user and the incidence of liability associated with each of said risks based on the age and gender of the user comprises:
acquiring a preset risk occurrence table, wherein the risk occurrence table comprises a plurality of risks mapped with different age distributions under different sexes and responsibility occurrence rate corresponding to each risk;
and identifying the risk corresponding to the age and the gender of the user and the liability occurrence rate of the risk according to the risk occurrence table.
5. The method of claim 1, wherein said displaying the securable risk and the unsecured risk in an ordered manner comprises: the insured risk is ranked ahead of the unsecured risk.
6. The method of claim 5, further comprising: according to the liability occurrence rate of insurance, the insurable risk with high liability occurrence rate is ranked ahead.
7. The method of any one of claims 1-6, wherein the calculation of the expected loss of securable risk is: incidence of liability of risk exposure.
8. An insurance product recommendation device, comprising:
the information acquisition module is configured to acquire user information, wherein the user information at least comprises user age, user gender and a real IP address of a user;
the risk query module is configured to determine risks of the users and responsibility incidence rates corresponding to the risks according to ages and sexes of the users;
a risk calculation module configured to resolve a risk exposure of the user based at least on the user's real IP address;
the risk classification module is configured to classify the risks of the users into insured risks and non-insured risks according to whether insurance products matched with the risks of the users exist in the insurance product database or not, and sequence and display the insured risks and the non-insured risks, wherein the insured risks are risks of the corresponding insurance products, and the non-insured risks are risks of no corresponding insurance products;
a period loss calculation module configured to calculate an expected loss of the insured risk of the user according to the risk exposure of the user and the liability occurrence rate of the risk;
and the insurance recommending module is configured to sort the insurable risk of the user according to the calculated expected loss, determine the minimum value of the numerical interval according to the risk exposure of the user and the highest premium of the insurance product corresponding to the insurable risk, and determine the recommended guarantee scheme of the insurable risk of the user.
9. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 7 when executing the computer program.
10. A storage medium storing a computer program, characterized in that the computer program realizes the steps of the method according to any one of claims 1 to 7 when executed by a processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110651814.1ACN113362137B (en) | 2021-06-11 | 2021-06-11 | Insurance product recommendation method and device, terminal equipment and storage medium |
Applications Claiming Priority (1)
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