Insurance product proposal generation method and related device

Abstract

The embodiment of the invention provides an insurance product proposal generation method and a related device, and belongs to the technical field of artificial intelligence. The method comprises the steps of obtaining customer information of a target customer, determining a health condition evaluation value of the target customer based on health condition information in the customer information, and determining an economic condition evaluation value of the target customer based on economic condition information in the customer information, and inputting the customer information, the health condition evaluation value and the economic condition evaluation value into a prediction model, determining at least one insurance product by the prediction model, generating an insurance product proposal based on the at least one insurance product, and sending the insurance product proposal to the target customer. According to the embodiment of the invention, the insurance product better matched with the demand of the target customer can be output according to the health condition evaluation value and the economic condition evaluation value, so that a more effective insurance product proposal is generated subsequently.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method for generating an insurance product proposal and related devices. Background Art

[0002] In the modern insurance industry, customers seek personalized, efficient and accurate insurance product recommendation services. Existing insurance product recommendation services generally rely on a single artificial intelligence (AI) model to handle all tasks related to insurance product recommendation services, such as communicating with customers through customer communication assistants and then making insurance product recommendations based on the information communicated with customers.

[0003] The insurance products obtained based on a single artificial intelligence (AI) model have a low degree of match with customer needs, resulting in a decrease in the match between insurance product proposals and customer needs. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a method and device for generating an insurance product proposal, an electronic device, a storage medium, and a computer product, aiming to improve the effectiveness of the insurance product proposal.

[0005] To achieve the above-mentioned purpose, a first aspect of an embodiment of the present application proposes a method for generating an insurance product proposal, the method comprising:

[0006] Obtain customer information of target customers;

[0007] Determine the health status evaluation value of the target customer based on the health status information in the customer information, and determine the economic status evaluation value of the target customer based on the economic status information in the customer information;

[0008] Inputting the customer information, the health status assessment value and the economic status assessment value into a prediction model, and determining at least one insurance product by the prediction model;

[0009] generating the insurance product proposal based on the at least one insurance product;

[0010] The insurance product proposal is sent to the target customer.

[0011] In conjunction with the first aspect, in one implementation, generating the insurance product proposal based on the at least one insurance product includes:

[0012] Determining an insurance assessment coefficient of each insurance product among the at least one insurance product, wherein the insurance assessment coefficient is used to characterize the protection level of the corresponding insurance product;

[0013] sorting the insurance products according to the insurance assessment coefficients of the insurance products to obtain sorting information of the insurance products;

[0014] An insurance product proposal including the ranking information and the insurance assessment coefficients of the various insurance products is generated.

[0015] In conjunction with the first aspect, in one implementation, determining the insurance assessment coefficient of each insurance product in the at least one insurance product includes:

[0016] Obtaining a parameter value of at least one insurance parameter in the insurance product, where the insurance parameter is a parameter that affects the degree of protection of the insurance product;

[0017] An insurance assessment coefficient of the insurance product is determined based on a parameter value of at least one insurance parameter in the insurance product.

[0018] In combination with the first aspect, in one implementation, the at least one insurance parameter includes an insurance amount, an insurance period, an insurance premium rate, a compensation limit, and a deductible.

[0019] The step of determining the insurance assessment coefficient of the insurance product based on the parameter value of at least one insurance parameter in the insurance product comprises:

[0020] Obtain the weights set for the insured amount, insurance period, insurance premium rate, compensation limit, and deductible respectively;

[0021] The insurance assessment coefficient of the insurance product is calculated based on the parameter values ​​corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible, and the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible.

[0022] In combination with the first aspect, in one implementation, determining the health status assessment value of the target customer based on the health status information in the customer information includes:

[0023] Extracting at least one influencing factor related to the physical health of the target customer from the health status information in the customer information;

[0024] Obtaining a first target value corresponding to each influencing factor of the at least one influencing factor; wherein the first target value represents the risk degree of harm caused by the corresponding influencing factor to the physical health of the target customer;

[0025] The health status assessment value is calculated according to the first target value corresponding to each of the influencing factors.

[0026] In combination with the first aspect, in one implementation, determining the economic status evaluation value of the target customer based on the economic status information in the customer information includes:

[0027] Extracting at least one relevant factor related to the economic ability of the target customer from the economic status information in the customer information;

[0028] Obtaining a second target value corresponding to each of the at least one relevant factor; wherein the second target value represents the degree of influence of the corresponding relevant factor on the economic ability of the target customer;

[0029] The economic status assessment value is calculated according to the second target values ​​corresponding to the various relevant factors.

[0030] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application provides a device for generating an insurance product proposal, the device comprising:

[0031] Information acquisition module, used to obtain customer information of target customers;

[0032] An evaluation module is used to determine a health status evaluation value of the target customer based on the health status information in the customer information, and to determine an economic status evaluation value of the target customer based on the economic status information in the customer information.

[0033] The product output module is used to input the customer information, the health status assessment value and the economic status assessment value into a prediction model, and determine at least one insurance product by the prediction model.

[0034] A proposal generating module is used to generate the insurance product proposal based on the at least one insurance product.

[0035] A recommendation module is used to send the insurance product proposal to the target customer.

[0036] In one embodiment, the evaluation module is also used to: extract at least one influencing factor related to the physical health of the target customer from the health status information in the customer information; obtain the first target value corresponding to each influencing factor in the at least one influencing factor; wherein the first target value represents the risk degree of the corresponding influencing factor to the physical health of the target customer; and calculate the health status evaluation value based on the first target value corresponding to each influencing factor.

[0037] In one embodiment, the evaluation module is also used to: extract at least one relevant factor related to the economic ability of the target customer from the economic status information in the customer information; obtain a second target value corresponding to each relevant factor in the at least one relevant factor; wherein the second target value represents the degree of influence of the corresponding relevant factor on the economic ability of the target customer; and calculate the economic status evaluation value based on the second target value corresponding to each relevant factor.

[0038] In one embodiment, the proposal generation module is also used to: determine the insurance assessment coefficient of each insurance product among the at least one insurance product, wherein the insurance assessment coefficient is used to characterize the degree of protection of the corresponding insurance product; sort the insurance products according to the insurance assessment coefficients of the insurance products to obtain sorting information of the insurance products; and generate an insurance product proposal including the sorting information and the insurance assessment coefficients of the insurance products.

[0039] In one embodiment, the proposal generation module is also used to: obtain the parameter value of at least one insurance parameter in the insurance product, where the insurance parameter is a parameter that affects the degree of protection of the insurance product; and determine the insurance assessment coefficient of the insurance product based on the parameter value of at least one insurance parameter in the insurance product.

[0040] In one embodiment, the proposal generation module is also used to: obtain the weights set for the insured amount, insurance period, insurance premium rate, compensation limit, and deductible respectively; calculate the insurance assessment coefficient of the insurance product based on the parameter values ​​corresponding to the insured amount, insurance period, insurance premium rate, compensation limit, and deductible, and the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit, and deductible.

[0041] To achieve the above objectives, a third aspect of an embodiment of the present application proposes an electronic device, which includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the method described in the first aspect is implemented.

[0042] To achieve the above-mentioned purpose, the fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method described in the first aspect is implemented.

[0043] To achieve the above objective, a fifth aspect of an embodiment of the present application proposes a computer product, which includes the electronic device described in the third aspect.

[0044] The method and device for generating an insurance product proposal, electronic device, storage medium and computer product proposed in the present application obtain the customer information of the target customer, determine the health status assessment value of the target customer based on the health status information in the customer information, and determine the economic status assessment value of the target customer based on the economic status information in the customer information, input the customer information, the health status assessment value and the economic status assessment value into the prediction model, determine at least one insurance product by the prediction model, generate the insurance product proposal based on the at least one insurance product, and send the insurance product proposal to the target customer. In this way, the health status assessment value can more intuitively judge the health risk of the target customer, and can better serve as the output basis of the insurance product. The health status assessment value is input into the prediction model, and the prediction model can output an insurance product that better matches the needs of the target customer according to the health status assessment value, and the economic status assessment value is used as an input parameter to output an insurance product that better matches the economic ability of the target customer, so that a more effective insurance product proposal is generated later. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 It is a flowchart of a method for generating an insurance product proposal provided in an embodiment of the present application;

[0046] Figure 2 The embodiment of this application provides Figure 1 Flow chart of the first embodiment of step S102 in FIG.

[0047] Figure 3 The embodiment of this application provides Figure 1 Flow chart of the second embodiment of step S102 in FIG.

[0048] Figure 4 The embodiment of this application provides Figure 1 Flow chart of step S104 in FIG.

[0049] Figure 5 The embodiment of this application provides Figure 4 Flow chart of step S401 in FIG.

[0050] Figure 6 The embodiment of this application provides Figure 5 Flow chart of step S502 in FIG.

[0051] Figure 7 It is a structural schematic diagram of an insurance product proposal generating device provided in an embodiment of the present application;

[0052] Figure 8 It is a schematic diagram of the hardware structure of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0053] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0054] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0055] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0056] The embodiment of the present application provides a method for generating an insurance product proposal, aiming to improve the matching degree between the insurance product proposal and customer needs.

[0057] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0058] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0059] The method for generating an insurance product proposal provided in the embodiment of the present application relates to the field of artificial intelligence technology. The method for generating an insurance product proposal provided in the embodiment of the present application can be applied to a terminal, can be applied to a server side, or can be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or can be configured as a server cluster or a distributed system composed of multiple physical servers, or can be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the method for generating an insurance product proposal, etc., but is not limited to the above forms.

[0060] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0061] It should be noted that in each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to user identity or characteristics such as user information, user behavior data, user historical data, and user location information, the user's permission or consent will be obtained first, and the collection, use, and processing of these data will comply with relevant laws, regulations, and standards. In addition, when the embodiment of the present application needs to obtain the user's sensitive personal information, the user's separate permission or consent will be obtained through a pop-up window or by jumping to a confirmation page. After clearly obtaining the user's separate permission or consent, the necessary user-related data for the normal operation of the embodiment of the present application will be obtained.

[0062] Reference Figure 1 , Figure 1The flowchart of a method for generating a proposal for an insurance product provided in this embodiment includes, but is not limited to, the following steps S101 to S105:

[0063] Step S101, obtaining customer information of target customers.

[0064] The above-mentioned target customers are customers who currently need insurance product proposals. The above-mentioned customer information may include personal information of the target customers, such as some basic information: age, gender, occupation, marital status, family structure, etc.

[0065] In step S101 of some embodiments, communication with target customers can be conducted through a customer communication assistant module of an electronic device to collect customer information of the target customers. The main function of the customer communication assistant module is to be responsible for initial contact and continuous online communication with customers, to deeply understand customer needs and preferences, and to use advanced natural language processing technology to optimize the speech model to improve the naturalness and accuracy of communication.

[0066] In addition, the information summarization assistant module can also pre-process the collected customer information data to achieve information simplification, summarization, standardization and coding. For example, missing values ​​can be processed by filling in the mean, median or inferring based on other relevant information, standardizing numerical data and encoding categorical data, such as encoding gender as 0 (female) and 1 (male).

[0067] In one embodiment, the collected detailed customer information can be quickly summarized and simplified, and advanced text processing algorithms can be used to efficiently extract key information from the customer information, thereby reducing the burden for subsequent analysis.

[0068] Step S102, determining a health status evaluation value of the target customer based on the health status information in the customer information, and determining an economic status evaluation value of the target customer based on the economic status information in the customer information.

[0069] The above-mentioned customer information may also include health status information and economic status information. The above-mentioned health status information is used to evaluate the health status of the target customer, and the above-mentioned economic status information is used to evaluate the economic status of the target customer.

[0070] In step S102 of some embodiments, health status information may be age, occupational risk level, family medical history, past medical history, and living habits, etc. Age can be used to assess the risk of illness and accident. Generally speaking, the older you are, the higher the risk. Occupational risk level is used to assess accident risk, such as high-risk occupations face higher accident risk. Family medical history and past medical history can be used to determine the potential risk of genetic diseases and specific diseases. Living habits are used to assess health risks, such as smoking, drinking and other bad habits increase the risk of illness. It should be noted that whether it is illness or an accident, it will have an impact on health, so both can be included in the factors that affect health status.

[0071] Economic status information may include family structure, family responsibilities, income, and debt. Family structure is used to indicate the members of a family, such as whether there are children, parents, etc. Family responsibilities are used to indicate whether there are elderly people to support and children to raise.

[0072] The above health status assessment value is used to characterize the health risk level of the target customer, and the above economic status assessment value is used to characterize the economic ability of the target customer. In one embodiment, the larger the health status assessment value, the greater the health risk of the target customer, and the larger the economic status assessment value, the stronger the economic ability of the target customer.

[0073] Step S103, inputting the customer information, health status assessment value and economic status assessment value into a prediction model, and determining at least one insurance product by the prediction model.

[0074] The above prediction model can be a machine learning algorithm such as decision tree, random forest, support vector machine, etc.

[0075] The types of insurance products can be divided into insurance products related to financial management (financial management insurance), insurance products related to education funds, or insurance products related to accident insurance (personal accident insurance), etc.

[0076] In step S103 of some embodiments, customer information, health status assessment value and economic status assessment value are used as input parameters of the prediction model to obtain at least one insurance product output by the prediction model based on the customer information, health status assessment value and economic status assessment value.

[0077] The prediction model can obtain health information related to the target customer's accident risk and disease risk from the above customer information, and based on this health information, it can be determined whether it is necessary to recommend insurance products related to accident risk and disease risk, and the prediction model can obtain economic information related to the target customer's economic status from the above customer information, and based on this economic information, it can be determined whether it is necessary to recommend insurance products related to wealth inheritance, or whether to recommend insurance products related to education funds and pensions based on family structure and family responsibilities. In addition, the health status assessment value can more intuitively judge the health risk of the target customer, and can better serve as the output basis for insurance products. The health status assessment value is input into the prediction model, and the prediction model can output insurance products that better match the needs of the target customer based on the health status assessment value, and the economic status assessment value is used as an input parameter to output insurance products that better match the economic ability of the target customer.

[0078] Step S104: Generate an insurance product proposal based on at least one insurance product.

[0079] The above insurance product proposal is used as the basis for target customers to select the final insurance product.

[0080] In step S104 of some embodiments, the insurance product proposal may include information about each insurance product in the at least one insurance product, an information overview of the target customer, a risk analysis of each insurance product for the target customer, and an explanation and description of each insurance product.

[0081] Step S105: Sending an insurance product proposal to the target customer.

[0082] In step S105 of some embodiments, the insurance product proposal is sent to the target customer, and the target customer can select a satisfactory insurance product from the insurance products included in the insurance product proposal based on the insurance product proposal.

[0083] In this embodiment, the health status assessment value and the economic status assessment value are used as input parameters of the prediction model, which can improve the matching degree between the insurance products output by the prediction model and the needs of target customers.

[0084] See also Figure 2 In some embodiments, the above step S102 includes but is not limited to the following steps S201 to S203:

[0085] Step S201: extract at least one influencing factor related to the physical health of the target customer from the health status information in the customer information.

[0086] The above-mentioned influencing factors may include age, occupational risk level, family medical history, previous medical history, and lifestyle habits.

[0087] Step S202: Obtain a first target value corresponding to each influencing factor of at least one influencing factor.

[0088] The first target value represents the risk level of the corresponding influencing factor causing harm to the physical health of the target customer.

[0089] In one implementation, the first target value corresponding to each influencing factor can be obtained through a preset model, for example, each influencing factor is used as an input parameter of the preset model, and the preset model outputs the first target value of each influencing factor. The preset model can be a neural network model.

[0090] Step S203: Calculate the health status assessment value according to the first target value corresponding to each influencing factor.

[0091] In one implementation, the health status assessment value may be calculated by obtaining the weight corresponding to each influencing factor and according to the first target value and the weight corresponding to each influencing factor.

[0092] The calculation formula for the above health status assessment value can be as follows:

[0093]

[0094] Among them, P 1 is the health status assessment value, N is the number of influencing factors included in the above at least one influencing factor, i is the sequence number of the influencing factor, M i represents the first target value corresponding to the i-th influencing factor, k i is the weight corresponding to the i-th influencing factor.

[0095] Since the degree of influence of each influencing factor on the health status is inconsistent, in this embodiment, the health status assessment value is calculated by using each influencing factor and the corresponding weight, so that the health status assessment value can be obtained more effectively.

[0096] See also Figure 3 In some embodiments, the above step S102 includes but is not limited to the following steps S301 to S303:

[0097] Step S301: extract at least one relevant factor related to the economic ability of the target customer from the economic status information in the customer information.

[0098] The above-mentioned relevant factors may be family structure, family responsibilities, income, debt status, etc.

[0099] Step S302: Obtain a second target value corresponding to each relevant factor in at least one relevant factor.

[0100] The second target value represents the influence degree of the corresponding relevant factors on the economic ability of the target customers.

[0101] In one implementation, the second target value corresponding to each relevant factor may be acquired through a preset model, for example, each relevant factor is used as an input parameter of the preset model, and the preset model outputs the first target value of each relevant factor.

[0102] Step S303, calculating the economic status assessment value according to the second target value corresponding to each relevant factor.

[0103] In one implementation, the economic status assessment value may be calculated by obtaining the weights corresponding to the various relevant factors and according to the second target values ​​and weights corresponding to the various relevant factors.

[0104] If the relevant factors include family structure, family responsibilities, income and debt, the above economic assessment value can be calculated as follows:

[0105]

[0106] Among them, P 2 is the economic status assessment value, Z is 4, j is the serial number of the relevant factor, T 1 , T 2 , T 3 are the second target values ​​corresponding to family structure, family responsibilities and debt situation, T 4 is the second target value corresponding to income, m 1 、m 2 、m 3 、m 4 They are the weights corresponding to family structure, family responsibilities, debt situation, and income respectively.

[0107] In this embodiment, the economic status evaluation value is calculated by using various relevant factors and corresponding weights, so that the economic status evaluation value can be effectively obtained.

[0108] See also Figure 4 In one embodiment, the above step S104 includes but is not limited to the following steps S401 to S403:

[0109] Step S401, determining the insurance assessment coefficient of each insurance product in at least one insurance product.

[0110] The above insurance assessment coefficient is used to characterize the protection level of the corresponding insurance product. In one embodiment, the larger the insurance assessment coefficient is, the higher the protection level of the insurance product is.

[0111] Step S402, sorting each insurance product according to its insurance assessment coefficient to obtain sorting information of each insurance product.

[0112] In one implementation, insurance products are sorted from largest to smallest according to their insurance assessment coefficients.

[0113] For example, at least one insurance product output by the prediction model includes insurance product A, insurance product B, and insurance product C. The insurance assessment coefficients of insurance product A, insurance product B, and insurance product C are determined to be 0.4, 0.3, and 0.2, respectively. Since 0.4>0.3>0.2, the insurance products are ranked, and the ranking information of insurance product A, insurance product B, and insurance product C is obtained as serial number 1, serial number 2, and serial number 3, respectively.

[0114] Step S403: Generate an insurance product proposal including ranking information and insurance assessment coefficients of various insurance products.

[0115] For example, at least one insurance product output by the prediction model includes insurance product A, insurance product B, and insurance product C. It is determined that the insurance assessment coefficients of insurance product A, insurance product B, and insurance product C are 0.4, 0.3, and 0.2 respectively, and the ranking information of insurance product A, insurance product B, and insurance product C is sequence number 1, sequence number 2, and sequence number 3 respectively. The generated insurance product proposal may include the following information:

[0116] “1. Insurance product A, insurance assessment coefficient: 0.4;

[0117] 2. Insurance product B, insurance assessment coefficient: 0.3;

[0118] 3. Insurance product C, insurance assessment coefficient: 0.2".

[0119] In this embodiment, by indicating the insurance assessment coefficient and serial number of each insurance product in the insurance product proposal, the difference in the degree of protection of each insurance product can be more intuitively highlighted, and a better basis for selection can be provided for target customers.

[0120] See also Figure 5 In some embodiments, the above step S401 may include but is not limited to the following steps S501 to S502:

[0121] Step S501, obtaining a parameter value of at least one insurance parameter in an insurance product.

[0122] The above insurance parameters are parameters that affect the level of protection of insurance products, such as the insured amount, insurance period, insurance premium rate, compensation limit, deductible, etc.

[0123] Step S502: determining an insurance assessment coefficient of the insurance product based on a parameter value of at least one insurance parameter in the insurance product.

[0124] In one implementation, the insurance assessment coefficient of the insurance product may be obtained by comprehensively calculating the parameter values ​​of each insurance parameter in at least one insurance parameter according to a preset rule.

[0125] Since insurance parameters are parameters that affect the degree of protection of insurance products, in this embodiment, the insurance evaluation coefficient of the insurance product is determined by various insurance parameters, which can improve the effectiveness of the insurance evaluation coefficient of the insurance product.

[0126] See also Figure 6 In some embodiments, at least one insurance parameter in the insurance product may include an insurance amount, an insurance period, an insurance premium rate, a compensation limit, and a deductible. The above step S502 may include but is not limited to the following steps S601-S602:

[0127] Step S601, respectively obtain the weights set for the insured amount, insurance period, insurance premium rate, compensation limit, and deductible.

[0128] In one implementation, corresponding weights may be pre-set for the insured amount, insurance period, insurance premium rate, compensation limit, and deductible.

[0129] Step S602, calculates the insurance assessment coefficient of the insurance product based on the parameter values ​​corresponding to the insured amount, insurance period, insurance premium rate, compensation limit, and deductible, as well as the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit, and deductible.

[0130] In one embodiment, the insurance assessment coefficient of the insurance product is obtained by weighted calculation of the parameter values ​​corresponding to the insured amount, insurance period, insurance premium rate, compensation limit, and deductible, as well as the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit, and deductible. The calculation formula may be as follows:

[0131]

[0132] Among them, Q, W, R, I, and L are the insured amount, insurance period, insurance premium rate, compensation limit, and deductible, respectively. 1 、b 2 、b 3 、b 4 、b 5 are the weights corresponding to Q, W, R, I, and L, respectively, and b 1 >b 3 >b 4 >b 2 >b5 >0.

[0133] In this embodiment, the insurance assessment coefficient is calculated by using the parameter values ​​corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible, as well as the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible, which can improve the effectiveness of obtaining the insurance assessment coefficient.

[0134] In some embodiments, after an insurance product proposal is given to a target customer, in response to the target customer selecting an insurance product from the insurance product proposal, the insurance product selected by the target customer from the insurance product proposal is input into a prediction model, and the prediction model further adjusts and optimizes the insurance product based on the insurance product selected by the target customer to improve the accuracy and practicality of the insurance product.

[0135] In order to better understand the above method, an embodiment of the present invention provides a complete embodiment of a method for generating an insurance product proposal, and the complete embodiment is as follows:

[0136] Obtain customer information of target customers, including age, gender, occupation, marital status, profession, family medical history, previous medical history, lifestyle habits, family structure, family responsibilities, income and liabilities, etc.

[0137] Extract multiple influencing factors related to the physical health of the target customer from the health status information contained in the customer information, where the multiple influencing factors include age, occupational risk level, family medical history, previous medical history and living habits, obtain the weights corresponding to the multiple influencing factors, and calculate the health status assessment value by the following formula:

[0138]

[0139] Among them, P 1 is the health status assessment value, N is 5, M 1 、M 2 、M 3 、M 4 、M 5 They represent the first target values ​​corresponding to age, occupational risk level, family medical history, past medical history, and lifestyle habits, respectively. 1 , k 2 , k 3 , k 4 , k 5 They represent the weights corresponding to age, occupational risk level, family medical history, previous medical history, and lifestyle habits respectively.

[0140] Extract multiple relevant factors related to the target customer's economic ability from the economic status information in the customer information. The multiple relevant factors include family structure, family responsibilities, income and debt status. Obtain the weights corresponding to each relevant factor and calculate the economic status assessment value through the following formula:

[0141]

[0142] Among them, P 2 is the economic status assessment value, Z is 4, T 1 , T 2 , T 3 are the second target values ​​corresponding to family structure, family responsibilities and liabilities, respectively, T 4 is the second target value corresponding to income, m 1 、m 2 、m 3 、m 4 They are the weights corresponding to family structure, family responsibilities, debt situation, and income respectively.

[0143] Customer information, health status assessment values ​​and economic status assessment values ​​are input into a prediction model, and the prediction model determines multiple insurance products, including insurance product A, insurance product B, and insurance product C.

[0144] Obtain the parameter values ​​of the insured amount, insurance period, insurance premium rate, compensation limit and deductible corresponding to each insurance product, as well as the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible, and calculate the insurance assessment coefficient of each insurance product through the following formula:

[0145]

[0146] Among them, Q, W, R, I, and L are the insured amount, insurance period, insurance premium rate, compensation limit, and deductible, respectively. 1 、b 2 、b 3 、b 4 、b 5 are the weights corresponding to Q, W, R, I, and L respectively.

[0147] The insurance assessment coefficients of insurance product A, insurance product B, and insurance product C are 0.4, 0.3, and 0.2 respectively.

[0148] The insurance products are sorted, and the sorting information of insurance product A, insurance product B, and insurance product C is obtained as sequence number 1, sequence number 2, and sequence number 3 respectively. The generated insurance product proposal may include the following information:

[0149] “1. Insurance product A, insurance assessment coefficient: 0.4;

[0150] 2. Insurance product B, insurance assessment coefficient: 0.3;

[0151] 3. Insurance product C, insurance assessment coefficient: 0.2".

[0152] See also Figure 7 The embodiment of the present application further provides an insurance product proposal generation device, which can implement the above-mentioned insurance product proposal generation method. The device 700 includes:

[0153] The information acquisition module 701 is used to acquire the customer information of the target customer.

[0154] The above-mentioned target customers are persons who currently require insurance product proposals. The above-mentioned customer information may include the personal information of the target customers, such as some basic information: age, gender, occupation, marital status, and family structure.

[0155] The information acquisition module 701 can communicate with the target customers through the customer communication assistant module included in the information acquisition module 701 to collect customer information of the target customers. The main function of the customer communication assistant module is to be responsible for initial contact and continuous communication with customers, deeply understand customer needs and preferences, and use advanced natural language processing technology to optimize the speech model to improve the naturalness and accuracy of communication.

[0156] In addition, the information summarization assistant module included in the information acquisition module 701 can also pre-process the collected customer information data to achieve information simplification, summarization, standardization and encoding. For example, for processing missing values, mean filling, median filling or inference filling based on other relevant information can be used, numerical data can be standardized, and categorical data can be encoded, such as encoding gender as 0 (female) and 1 (male).

[0157] In one embodiment, the collected detailed customer information can be quickly summarized and simplified, and advanced text processing algorithms can be used to efficiently extract key information from the customer information, thereby reducing the burden for subsequent analysis.

[0158] The evaluation module 702 is used to determine the health status evaluation value of the target customer based on the health status information in the customer information, and to determine the economic status evaluation value of the target customer based on the economic status information in the customer information.

[0159] The above-mentioned customer information may also include health status information and economic status information. The above-mentioned health status information is used to evaluate the health status of the target customer, and the above-mentioned economic status information is used to evaluate the economic status of the target customer.

[0160] In some embodiments, the health status information may include age, occupational risk level, family medical history, past medical history, and living habits.

[0161] The economic status information may include family structure, family responsibilities, income and debt. Family structure is used to indicate the members of the family, such as whether there are children, parents, etc., and family responsibilities are used to indicate whether there are elderly people to support and children to raise.

[0162] In one embodiment, the greater the health status assessment value, the greater the health risk of the target customer, and the greater the economic status assessment value, the stronger the economic ability of the target customer.

[0163] The product output module 703 is used to input the customer information, health status assessment value and economic status assessment value into the prediction model, and determine at least one insurance product by the prediction model.

[0164] The above prediction model can be a machine learning algorithm such as decision tree, random forest, support vector machine, etc.

[0165] In some embodiments, the product output module 703 uses customer information, health status assessment values ​​and economic status assessment values ​​as input parameters of the prediction model to obtain at least one insurance product output by the prediction model based on the customer information, health status assessment values ​​and economic status assessment values.

[0166] The proposal generating module 704 is configured to generate an insurance product proposal based on at least one insurance product.

[0167] The above insurance product proposal is used as the basis for target customers to select the final insurance product.

[0168] In some embodiments, the insurance product proposal may include information about each insurance product in the at least one insurance product mentioned above, an information overview of the target customers, a risk analysis of each insurance product for the target customers, and explanations and descriptions of each insurance product.

[0169] The recommendation module 705 is used to send insurance product recommendations to target customers.

[0170] In some embodiments, the recommendation module 705 sends the insurance product proposal to the target customer, and the target customer can select a satisfactory insurance product from the insurance products included in the insurance product proposal based on the insurance product proposal.

[0171] In some embodiments, the above-mentioned evaluation module 702 is specifically used to: extract at least one influencing factor related to the physical health of the target customer from the health status information in the customer information; obtain the first target value corresponding to each influencing factor in at least one influencing factor; wherein the first target value represents the risk degree of the corresponding influencing factor causing harm to the physical health of the target customer; calculate the health status evaluation value according to the first target value corresponding to each influencing factor.

[0172] The above-mentioned influencing factors may include age, occupational risk level, family medical history, previous medical history, and lifestyle habits.

[0173] In one embodiment, the evaluation module 702 can obtain the first target value corresponding to each influencing factor through a preset model, and the evaluation module 702 can use each influencing factor as an input parameter of the preset model, and the preset model outputs the first target value of each influencing factor. The preset model can be a neural network model.

[0174] In one implementation, the health status assessment value may be calculated by obtaining the weight corresponding to each influencing factor and according to the first target value and the weight corresponding to each influencing factor.

[0175] In some embodiments, the above-mentioned evaluation module 702 is specifically used to: extract at least one relevant factor related to the economic ability of the target customer from the economic status information in the customer information; obtain the second target value corresponding to each relevant factor in the at least one relevant factor; wherein the second target value represents the degree of influence of the corresponding relevant factor on the economic ability of the target customer; and calculate the economic status evaluation value according to the second target value corresponding to each relevant factor.

[0176] The above-mentioned relevant factors may be family structure, family responsibilities, income, debt status, etc.

[0177] In one implementation, the evaluation module 702 may obtain the second target value corresponding to each relevant factor through a preset model. The evaluation module 702 may use each relevant factor as an input parameter of the preset model, and the preset model may output the first target value of each relevant factor.

[0178] In one implementation, the economic status assessment value may be calculated by obtaining the weights corresponding to the various relevant factors and according to the second target values ​​and weights corresponding to the various relevant factors.

[0179] In some embodiments, the proposal generation module 704 is specifically used to: determine the insurance assessment coefficient of each insurance product in at least one insurance product, wherein the insurance assessment coefficient is used to characterize the degree of protection of the corresponding insurance product; sort each insurance product according to the insurance assessment coefficient of each insurance product to obtain sorting information of each insurance product; generate an insurance product proposal including the sorting information and the insurance assessment coefficient of each insurance product.

[0180] In one embodiment, the larger the insurance assessment coefficient is, the higher the level of protection of the insurance product is.

[0181] In one implementation, insurance products are sorted according to their insurance assessment coefficients from large to small.

[0182] In some embodiments, the proposal generation module 704 is specifically used to: obtain the parameter value of at least one insurance parameter in the insurance product, where the insurance parameter is a parameter that affects the degree of protection of the insurance product; and determine the insurance assessment coefficient of the insurance product based on the parameter value of at least one insurance parameter in the insurance product.

[0183] The above insurance parameters may be the insured amount, insurance period, insurance premium rate, compensation limit, deductible, etc.

[0184] In one implementation, the proposal generation module 704 may obtain the insurance evaluation coefficient of the insurance product by comprehensively calculating the parameter values ​​of each insurance parameter in the at least one insurance parameter according to a preset rule.

[0185] In some embodiments, at least one insurance parameter in an insurance product may include an insured amount, an insurance period, an insurance premium rate, a compensation limit, and a deductible. The proposal generation module 704 is specifically used to: obtain weights set for the insured amount, the insurance period, the insurance premium rate, the compensation limit, and the deductible respectively; calculate the insurance assessment coefficient of the insurance product based on the parameter values ​​corresponding to the insured amount, the insurance period, the insurance premium rate, the compensation limit, and the deductible, and the weights corresponding to the insured amount, the insurance period, the insurance premium rate, the compensation limit, and the deductible.

[0186] In one implementation, corresponding weights may be pre-set for the insured amount, insurance period, insurance premium rate, compensation limit, and deductible.

[0187] The specific implementation of the insurance product proposal generating device is substantially the same as the specific implementation of the above-mentioned insurance product proposal generating method.

[0188] The embodiment of the present application also provides an electronic device, the electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the above-mentioned insurance product proposal generation method when executing the computer program. The electronic device can be any smart terminal including a tablet computer, a car computer, etc.

[0189] See also Figure 8 , Figure 8 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0190] The processor 801 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0191] The memory 802 may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 802 may store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 802, and the processor 801 calls and executes the insurance product proposal generation method of the embodiment of this application;

[0192] Input / output interface 803, used to implement information input and output;

[0193] The communication interface 804 is used to realize the communication interaction between the device and other devices. The communication can be realized through a wired manner (such as USB, network cable, etc.) or a wireless manner (such as mobile network, WIFI, Bluetooth, etc.);

[0194] A bus 805 that transmits information between the various components of the device (e.g., the processor 801, the memory 802, the input / output interface 803, and the communication interface 804);

[0195] The processor 801 , the memory 802 , the input / output interface 803 and the communication interface 804 are connected to each other in communication within the device via a bus 805 .

[0196] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned insurance product proposal generation method is implemented.

[0197] The memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Embodiments of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0198] The insurance product proposal generation method, insurance product proposal generation device, electronic device and storage medium provided in the embodiment of the present application obtain the customer information of the target customer, determine the health status assessment value of the target customer based on the health status information in the customer information, and determine the economic status assessment value of the target customer based on the economic status information in the customer information, input the customer information, the health status assessment value and the economic status assessment value into the prediction model, determine at least one insurance product by the prediction model, generate the insurance product proposal based on the at least one insurance product, and send the insurance product proposal to the target customer. In this way, the health status assessment value can more intuitively judge the health risk of the target customer, and can better serve as the output basis of the insurance product. The health status assessment value is input into the prediction model, and the prediction model can output an insurance product that better matches the needs of the target customer according to the health status assessment value, and the economic status assessment value is used as an input parameter to output an insurance product that better matches the economic ability of the target customer, so that a more effective insurance product proposal is generated later.

[0199] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0200] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0201] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0202] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0203] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0204] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0205] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0206] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0207] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0208] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including multiple instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0209] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A method for generating an insurance product proposal, characterized in that: The method comprises: Obtain customer information of target customers; Determine the health status evaluation value of the target customer based on the health status information in the customer information, and determine the economic status evaluation value of the target customer based on the economic status information in the customer information; Inputting the customer information, the health status assessment value and the economic status assessment value into a prediction model, and determining at least one insurance product by the prediction model; generating the insurance product proposal based on the at least one insurance product; The insurance product proposal is sent to the target customer.

2. The method according to claim 1, characterized in that The generating the insurance product proposal based on the at least one insurance product comprises: Determining an insurance assessment coefficient of each insurance product among the at least one insurance product, wherein the insurance assessment coefficient is used to characterize the protection level of the corresponding insurance product; sorting the insurance products according to the insurance assessment coefficients of the insurance products to obtain sorting information of the insurance products; An insurance product proposal including the ranking information and the insurance assessment coefficients of the various insurance products is generated.

3. The method according to claim 2, characterized in that The step of determining the insurance assessment coefficient of each insurance product in the at least one insurance product comprises: Obtaining a parameter value of at least one insurance parameter in the insurance product, where the insurance parameter is a parameter that affects the degree of protection of the insurance product; An insurance assessment coefficient of the insurance product is determined based on a parameter value of at least one insurance parameter in the insurance product.

4. The method according to claim 3, characterized in that The at least one insurance parameter includes the insured amount, insurance period, insurance premium rate, compensation limit and deductible, The step of determining the insurance assessment coefficient of the insurance product based on the parameter value of at least one insurance parameter in the insurance product comprises: Obtain the weights set for the insured amount, insurance period, insurance premium rate, compensation limit, and deductible respectively; The insurance assessment coefficient of the insurance product is calculated based on the parameter values ​​corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible, and the weights corresponding to the insured amount, insurance period, insurance premium rate, compensation limit and deductible.

5. The method according to claim 1, characterized in that The determining the health status evaluation value of the target customer based on the health status information in the customer information includes: Extracting at least one influencing factor related to the physical health of the target customer from the health status information in the customer information; Obtaining a first target value corresponding to each influencing factor of the at least one influencing factor; wherein the first target value represents the risk degree of harm caused by the corresponding influencing factor to the physical health of the target customer; The health status assessment value is calculated according to the first target value corresponding to each of the influencing factors.

6. The method according to claim 1, characterized in that The determining the economic status evaluation value of the target customer based on the economic status information in the customer information includes: Extracting at least one relevant factor related to the economic ability of the target customer from the economic status information in the customer information; Obtaining a second target value corresponding to each of the at least one relevant factor; wherein the second target value represents the degree of influence of the corresponding relevant factor on the economic ability of the target customer; The economic status assessment value is calculated according to the second target values ​​corresponding to the various relevant factors.

7. An insurance product proposal generating device, characterized in that: The device comprises: Information acquisition module, used to obtain customer information of target customers; An evaluation module, configured to determine a health status evaluation value of the target customer based on the health status information in the customer information, and to determine an economic status evaluation value of the target customer based on the economic status information in the customer information; A product output module, configured to input the customer information, the health status assessment value and the economic status assessment value into a prediction model, and determine at least one insurance product by the prediction model; A proposal generating module, configured to generate the insurance product proposal based on the at least one insurance product; A recommendation module is used to send the insurance product proposal to the target customer.

8. An electronic device, characterized in that: The electronic device comprises: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, the method for generating an insurance product proposal according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method for generating an insurance product proposal according to any one of claims 1 to 6 is implemented.

10. A computer product, characterized in that: Comprising the electronic device as claimed in claim 8.

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