CN117151899A - User marking method, device, equipment and storage medium - Google Patents

User marking method, device, equipment and storage medium Download PDF

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CN117151899A
CN117151899A CN202311190463.4A CN202311190463A CN117151899A CN 117151899 A CN117151899 A CN 117151899A CN 202311190463 A CN202311190463 A CN 202311190463A CN 117151899 A CN117151899 A CN 117151899A
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information
user
determining
risk
target user
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陈晓青
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Ping An Property and Casualty Insurance Company of China Ltd
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Ping An Property and Casualty Insurance Company of China Ltd
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract

The application discloses a user marking method, which is applied to terminal equipment, wherein an application interface of the terminal equipment comprises a display area of each user, and the method comprises the following steps: when the fact that the current date is close to the user's underwriting expiration date is detected, determining the user corresponding to the underwriting expiration date as a target user; acquiring historical underwriting information, pay information and management information of a target user, wherein the historical underwriting information comprises deposit information and position information, and the management information comprises: service type information and credit information; based on a clustering algorithm, generating basic premium and first pay amount according to the premium information and the pay information; determining the risk level of the target user according to the position information, the service type information and the credit information; generating a second payable amount according to the risk level and the first payable amount; generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount; and implanting the renewal scheme into the display area of the target user, and marking the display area.

Description

User marking method, device, equipment and storage medium
Technical Field
The present application relates to the field of data display technologies, and in particular, to a user marking method, device, apparatus, and storage medium.
Background
Currently, when an insurance company provides a renewal scheme for a user, an agent evaluates the insurance requirement of the user and provides the renewal scheme for the user. In the above mode, the agent needs to collect user information by itself to complete the evaluation of the user insurance requirement, which has the following disadvantages: 1. a great deal of manpower resources and time are consumed, and if the seat fails to timely hold the customer, the bill is lost; 2. the user information automatically collected by the seat is incomplete, the personalized requirements and the risk characteristics of the user are ignored, the renewal scheme is not accurate and transparent enough, and the interests of the company and the interests of the user are easily damaged. For this purpose, an automated, dataized user labeling method is required.
Disclosure of Invention
The embodiment of the application provides a user marking method, device, equipment and storage medium, which are used for automatically collecting and analyzing data to push a renewal scheme, so that the loss of a user is avoided, and the standardization of a renewal process is improved.
In a first aspect, an embodiment of the present application provides a user indication method, which is applied to a terminal device, where the terminal device includes an application interface, and the application interface includes a display area of each user, and the method includes:
acquiring the underwriting ending periods of a plurality of users, and determining the user corresponding to the underwriting ending period as a target user when the current date is detected to be a preset time from the underwriting ending period;
acquiring historical underwriting information, pay information and management information of the target user, wherein the historical underwriting information comprises deposit information and position information, and the management information comprises: service type information and credit information;
based on a clustering algorithm, generating basic premium and first payoff amount corresponding to the service type information according to the premium information and the payoff information;
determining a risk level of the target user according to the position information, the service type information and the credit information;
generating a second payline according to the risk level and the first payline;
generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount;
generating a scheme link according to the renewal scheme, inserting the scheme link into a display area corresponding to the target user, and marking the display area corresponding to the target user.
In a second aspect, an embodiment of the present application provides a user indication apparatus, including: the system comprises a user determining module, an information obtaining module, a credit estimating module, a risk estimating module, a credit determining module, a scheme generating module and a result marking module;
the user determining module is used for acquiring the underwriting ending periods of a plurality of users, and determining the user corresponding to the underwriting ending period as a target user when detecting that the current date is a preset time from the underwriting ending period;
the information acquisition module is used for acquiring the historical underwriting information, the pay information and the management information of the target user, wherein the historical underwriting information comprises the insurance information and the position information, and the management information comprises: service type information and credit information;
the credit evaluation module is used for generating basic premium and first credit corresponding to the service type information according to the credit information and the credit information based on a clustering algorithm;
the risk estimation module is used for determining the risk level of the target user according to the position information, the service type information and the credit information;
the limit determining module is used for generating a second pay limit according to the risk level and the first pay limit;
the scheme generation module is used for generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount;
and the result marking module is used for generating a scheme link according to the renewal scheme, inserting the scheme link into the display area corresponding to the target user, and marking the display area corresponding to the target user.
In a third aspect, embodiments of the present application provide a computer device comprising a memory and a processor;
the memory is used for storing a computer program;
the processor is configured to execute the computer program and implement any one of the user indication methods provided in the embodiments of the present application when the computer program is executed.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement a user labeling method as provided in any one of the embodiments of the present application.
The user marking method provided by the embodiment of the application realizes the automatic determination of the target user according to the underwriting termination period of the user and the determination of the basic premium, risk level and second payable amount of the user according to the historical underwriting information, the payable information and the operation information, thereby obtaining the renewal scheme of the user, quickly drawing the attention of the seat after marking the display area of the target user and implanting the renewal scheme, and quickly acquiring the information in the renewal scheme by the seat to assist in user service, thereby avoiding the loss of the user and improving the normalization of the renewal process.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is an application scenario diagram of a user marking method provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart of a user indication method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a warranty arrangement provided by an embodiment of the present application;
FIG. 4 is a schematic block diagram of a user indication device according to an embodiment of the present application;
fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The flow diagrams depicted in the figures are merely illustrative and not necessarily all of the elements and operations/steps are included or performed in the order described. For example, some operations/steps may be further divided, combined, or partially combined, so that the order of actual execution may be changed according to actual situations.
It is to be understood that the terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should also be understood that the term "and/or" as used in the present specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
Some embodiments of the present application are described in detail below with reference to the accompanying drawings. The following embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 shows an application scenario diagram of a user marking method according to an embodiment of the present application. As shown in fig. 1, the method of the embodiment of the present application may be applied to a user indication platform, specifically, to a server of the user indication platform, where the server may run in a server or other computing devices, and is configured to obtain a determination of a target user according to an underwriting expiration date of the user, and finally output a renewal scheme to a terminal device of an agent according to historical underwriting information, pay information and business information of the target user, so that a normalized suggestion is given in the agent following the user service. The client is used for marking the target user and displaying the renewal scheme of the target user in the terminal equipment of the running seat. The client also runs in the terminal device of the user to be evaluated. The server and the client can be in communication connection through a wireless network.
When installing application programs of the user marking method in the terminal equipment and the server, the terminal equipment and the server are required to authorize corresponding authorities. For example, the basic attribute information of the terminal equipment and the server, album reading authority, the authority of information such as the number of the positioning information equipment and the network information and the like can be obtained.
The server may be an independent server, may be a server cluster, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms. The terminal device can be a mobile phone, a tablet computer, a notebook computer, a desktop computer, a personal digital assistant, a wearable device and other terminal devices.
It should also be noted that the embodiment of the present application may acquire and process related data based on artificial intelligence techniques, such as implementing XX through artificial intelligence. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
The user marking method provided by the embodiment of the application is applied to the terminal equipment, the terminal equipment comprises an application interface, the application interface comprises a display area of each user, and the agent can browse the information of the user through the application interface.
Referring to fig. 2, fig. 2 is a schematic flowchart of a user marking method according to an embodiment of the present application. . As shown in fig. 2, the specific steps of the user indication method include: S101-S107.
S101, acquiring the underwriting ending periods of a plurality of users, and determining the user corresponding to the underwriting ending period as a target user when the current date is detected to be a preset time from the underwriting ending period.
The agent inputs a request instruction through the terminal device, the terminal device responds to the request instruction, and requests to obtain lists and underwriting deadlines of a plurality of users from the server, wherein the users can be users for the agent to follow-up service, the terminal device displays the lists and underwriting deadlines of the users through an application interface, and determines the user corresponding to the underwriting deadline as a target user when detecting that the current date is a preset time, for example, the preset time is 30 days or 45 proposals.
Therefore, the user service can be automatically followed, the service user is prevented from being followed after the underwriting expiration date, the seat is convenient to contact the user in advance, and the user loss is reduced.
S102, acquiring historical underwriting information, pay information and management information of a target user, wherein the historical underwriting information comprises deposit information and position information, and the management information comprises: service type information and credit information.
Illustratively, in the process of information acquisition, an internal channel and an external channel are included. Wherein, inside channel is: the method comprises the steps of obtaining historical underwriting information of a target user according to historical underwriting records of the target user in an insurance company (own company and a company underwriting in the same industry), and obtaining pay information of the target user according to pay records of the target user in the insurance company. The history underwriting information includes the amount information and the position information. The premium information is the premium the target user invests and the degree of receipt of the premium. The pay information is the pay rate and pay amount. The location information is typically the business address where the underwriting business object is located. And the external channels are: and acquiring the business information of the target user according to the information channels disclosed by enterprise verification, license and the like. The business type information comprises business types of enterprises, and the credit information comprises: business status, risk status, and credit status.
The information collected by the information collection process is collected from public channels or the collection permission granted by the target user is obtained.
In some embodiments, after obtaining the historical underwriting information, the pay information, and the business information of the target user, the method further includes: and cleaning the data of the historical underwriting information, the reimbursement information and the management information.
Exemplary, the content of the data cleansing includes: removing invalid data, filling missing data, selecting characteristics, converting characteristics and the like. Thus, the enterprise name, customer industry, business address, main building structure, property and inventory type, limit, claim free, special contract, pay rate and pay amount information of the target user are obtained.
Through data cleaning, the quality of the data can be improved, erroneous, inaccurate and incomplete information in the data is removed, the data value is enhanced, redundancy and repeated data are reduced, the data processing efficiency and cost are improved, and a result with higher reliability is obtained.
And S103, generating basic premium and first pay amount corresponding to the service type information according to the premium information and the pay information based on a clustering algorithm.
Illustratively, a clustering algorithm is used to analyze the personalized demand and risk features of the target user. The data input into the clustering algorithm are all cleaned data, and the change trend of the premium input by the target user to each service type is obtained according to the premium information, so that the basic premium of each service type in the next period is estimated; and calculating the payment risk of the target user according to the payment rate and the payment amount in the payment information, so as to obtain a first payment amount corresponding to the basic insurance fee of each service type.
In some embodiments, when generating the basic premium and the first payable amount corresponding to the service type information according to the premium information and the payable information based on the clustering algorithm, the method includes: determining the premium acceptance of the target user according to the annual applied premium; determining a basic premium according to the applied premium and the premium acceptance of the previous year on the current date; the first payable amount is determined based on the payable amount and the base premium over the years.
Generally, the applied premium of the target user is incremented year by year, i.e., the premium acceptance of the target user is positive. Premium acceptance may also be understood as an incremental factor. In evaluating the underlying policy of the next cycle, the policy applied in the last cycle (the year preceding the current date) is an important reference value, and the product of the policy applied in the last cycle plus the policy applied in the last cycle Fei Chengyi by an increment factor is the underlying policy of the next cycle. And the amount paid over the years is used to estimate the payout coefficient of the next period, the first payout amount can be determined based on the payout coefficient and the base payout.
S104, determining the risk level of the target user according to the position information, the service type information and the credit information.
Illustratively, the location information and the business type information are used to evaluate the natural disaster that the business type of the target user may be affected by at the business address. The service type information is also used to evaluate that the service type of the target user is subject to regulatory influence. The information is used to evaluate the business impact of the business type of the target user.
In some embodiments, determining the risk level of the target user according to the location information, the service type information and the credit information includes: determining a first risk coefficient of the target user according to the position information and the service type information; determining a second risk coefficient of the target user according to the credit information; and determining the risk level according to the first risk coefficient and the second risk coefficient.
Illustratively, natural disaster effects and regulatory effects result in greater risk of payouts and greater amounts of payouts. Natural disaster effects include: floods, earthquakes, floods, typhoons, storms and snowstorms, the regulatory effects include: whether the business type belongs to the industry of forbidden or strictly controlled, such as fishery, processing of metal waste and scraps, hunting and animal catching, and the like. Therefore, when the operation address of the user is detected to belong to a high-risk area affected by natural disasters, the first risk coefficient with higher risk degree is marked for the user. The risk of payoff due to the business impact is small, and therefore the second risk factor is isolated from separate calculation.
In some embodiments, determining the first risk factor of the target user according to the location information and the service type information includes: acquiring a risk area corresponding to the service type information; determining a first risk coefficient according to the geographic relation between the position information and the risk area, wherein the geographic relation comprises: overlapping, adjacent and dispersed.
In some embodiments, implementing the determination of the risk level from the first risk coefficient and the second risk coefficient includes: when the first risk coefficient is detected to be larger than a first preset threshold value and the second coefficient is detected to be larger than a second preset threshold value, determining the risk level as a first risk level; when the first risk coefficient is detected to be smaller than a first preset threshold value and the second coefficient is detected to be larger than a second preset threshold value, determining the risk level as a second risk level; and when the first risk coefficient is detected to be smaller than a first preset threshold value and the second risk coefficient is detected to be smaller than a second preset threshold value, determining the risk level as a third risk level.
Illustratively, the first risk level target user is a high risk group, the second risk level target user is a medium risk group, and the third risk level target user is a low risk group.
High risk group:
(1) the target addresses are located at flood, earthquake, flood, typhoon, storm, and snowstorm sites.
(2) Industry types are in the industry of forbidden or strictly controlled industries, such as fishery, processing of metal scraps and scraps, hunting and capturing animals, etc.
(3) Severe loss: the rolling accumulated three-year policy cost rate and the rolling recent one-year policy cost rate are 80% -100%.
Stroke risk group:
(1) the risk probability of flood, earthquake, flood, typhoon, storm, snow disaster and the like of the target address is moderate.
(2) Industry types belong to the management and control industry, such as textile product manufacturing, stadiums and the like.
(3) Mild loss: the rolling accumulated three-year policy cost rate and the rolling recent annual policy cost rate are 30% -80%.
Low risk population:
(1) the target addresses have no risks such as floods, earthquakes, floods, typhoons, storm and snowdisasters in nearly 5 years.
(2) Industry types belong to the encouragement industry, such as building decoration industry, real estate development and management, and the like.
(3) No or mild deficit: the cost rate of the policy is 0-30% when the policy is rolled for three years.
S105, generating a second payable amount according to the risk level and the first payable amount.
For example, the first payable amount can only reflect the historical rule of the payable amount, if the rationality of the payable amount is to be improved, the payable amount needs to be corrected according to the real-time risk level of the target user, and the risk level can be used as the weight coefficient of the first payable amount to be multiplied to obtain the second payable amount.
S106, generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount.
Classifying based on the service types of the target users and the target users, and establishing corresponding insurance schemes and pricing models. Specifically, the location information, the operation information, the risk level, the basic premium and the second claim amount of the target user are input into a poisson regression algorithm and a nonlinear regression model, and different underwriting strategies are formulated for different risk groups. Personalized insurance schemes and prices are provided for carefully underwritten and underwritten customers, respectively. The insurance scheme recommends dangerous types, insurance amount, insurance period, additional insurance, claim free, limit and other contents according to the personalized requirements and the insurance characteristics of the clients and gives pricing.
Referring to fig. 3, fig. 3 is a schematic diagram illustrating a warranty scheme according to an embodiment of the present application. As shown in fig. 3, the renewal scheme includes at least a user name, a service type, an operation address, a loss condition, a risk level, an underwriting policy, a pay allowance, and a premium.
And S107, generating a scheme link according to the renewal scheme, inserting the scheme link into a display area corresponding to the target user, and marking the display area corresponding to the target user.
Illustratively, multiple users are presented through a table, so that the scheme links of the renewal scheme may be placed in the grid to which the users correspond, e.g., in the same row or column. In representing the target user, the target user may be ordered forward in the table and represented by a conspicuous color, e.g., yellow and red, which can quickly draw attention of the agent.
In some embodiments, after marking the display area corresponding to the target user, the method further includes: acquiring an agent input browsing instruction, and determining a target scheme link according to the browsing instruction, wherein the target scheme link is one of scheme links; acquiring a renewal scheme corresponding to the target scheme link; and generating a scheme browsing window on the application interface, and displaying a renewal scheme corresponding to the target scheme link through the scheme browsing window.
Referring to fig. 4, fig. 4 is a schematic block diagram of a user marking apparatus 300 according to an embodiment of the present application, where the user marking apparatus 300 is used to perform the user marking method described above. The user marking device can be configured in a server or terminal equipment.
The server may be an independent server, may be a server cluster, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms. The terminal device can be a mobile phone, a tablet computer, a notebook computer, a desktop computer, a user digital assistant, a wearable device and other terminal devices.
As shown in fig. 4, the user indication apparatus 300 includes: a user determination module 301, an information acquisition module 302, a credit estimation module 303, a risk estimation module 304, a credit determination module 305, a scheme generation module 306 and a result indication module 307;
the user determining module 301 is configured to obtain an underwriting expiration date of a plurality of users, and determine, when detecting that the current date is a preset time from the underwriting expiration date, a user corresponding to the underwriting expiration date as a target user.
The information obtaining module 302 is configured to obtain historical underwriting information, pay information, and management information of the target user, where the historical underwriting information includes insurance information and location information, and the management information includes: service type information and credit information.
In some embodiments, the information acquisition module 302, after being configured to obtain the historical underwriting information, the pay information, and the business information of the target user, is further specifically configured to: and cleaning the data of the historical underwriting information, the reimbursement information and the management information.
The credit evaluation module 303 is configured to generate a basic premium and a first credit corresponding to the service type information according to the premium information and the credit information based on the clustering algorithm.
In some embodiments, the credit evaluation module 303, when configured to implement a clustering algorithm, is specifically configured to implement: determining the premium acceptance of the target user according to the applied premium over the years; determining a basic premium according to the applied premium and the premium acceptance of the previous year on the current date; the first payable amount is determined based on the payable amount and the base premium over the years.
The risk estimation module 304 is configured to determine a risk level of the target user according to the location information, the service type information, and the credit information.
In some embodiments, risk estimation module 304, when configured to implement determining a risk level for a target user based on location information, business type information, and credit information, is specifically configured to implement: determining a first risk coefficient of the target user according to the position information and the service type information; determining a second risk coefficient of the target user according to the credit information; and determining the risk level according to the first risk coefficient and the second risk coefficient.
In some embodiments, the risk estimation module 304, when configured to determine the first risk factor of the target user according to the location information and the service type information, is specifically configured to implement: acquiring a risk area corresponding to the service type information; determining a first risk coefficient according to the geographic relation between the position information and the risk area, wherein the geographic relation comprises: overlapping, adjacent and dispersed.
In some embodiments, the risk estimation module 304, when configured to implement determining the risk level from the first risk coefficient and the second risk coefficient, is specifically configured to implement: when the first risk coefficient is detected to be larger than a first preset threshold value and the second coefficient is detected to be larger than a second preset threshold value, determining the risk level as a first risk level; when the first risk coefficient is detected to be smaller than a first preset threshold value and the second coefficient is detected to be larger than a second preset threshold value, determining the risk level as a second risk level; and when the first risk coefficient is detected to be smaller than a first preset threshold value and the second risk coefficient is detected to be smaller than a second preset threshold value, determining the risk level as a third risk level.
The credit determining module 305 is configured to generate a second credit according to the risk level and the first credit.
The scheme generating module 306 is configured to generate a renewal scheme according to the location information, the business information, the risk level, the basic premium, and the second claim amount.
The result marking module 307 is configured to generate a scheme link according to the renewal scheme, insert the scheme link into a display area corresponding to the target user, and mark the display area corresponding to the target user.
In some embodiments, the result marking module 307 is further specifically configured to, after being configured to mark the display area corresponding to the target user, implement: acquiring an agent input browsing instruction, and determining a target scheme link according to the browsing instruction, wherein the target scheme link is one of scheme links; acquiring a renewal scheme corresponding to the target scheme link; and generating a scheme browsing window on the application interface, and displaying a renewal scheme corresponding to the target scheme link through the scheme browsing window.
It should be noted that, for convenience and brevity of description, specific working processes of the user marking device and each module described above may refer to corresponding processes in the foregoing user marking method embodiment, and will not be described herein again.
The user marking means described above may be embodied in the form of a computer program which is executable on a computer device as shown in fig. 5.
Referring to fig. 5, fig. 5 is a schematic block diagram of a computer device according to an embodiment of the present application. The computer device may be a server or a terminal device.
With reference to FIG. 5, the computer device includes a processor, a memory, and a network interface connected by a system bus, where the memory may include storage media and internal memory.
The storage medium may store an operating system and a computer program. The computer program includes program instructions that, when executed, cause a processor to perform any of the user indication methods provided by the embodiments of the present application.
The processor is used to provide computing and control capabilities to support the operation of the entire computer device.
The internal memory provides an environment for the execution of a computer program in a storage medium that, when executed by a processor, causes the processor to perform any of a number of user identification methods. The storage medium may be nonvolatile or volatile.
The network interface is used for network communication such as transmitting assigned tasks and the like. It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
It should be appreciated that the processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field-programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. Wherein the general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In one embodiment, the processor is configured to execute a computer program stored in the memory to perform the steps of: acquiring the underwriting ending time limit of a plurality of users, and determining the user corresponding to the underwriting ending time limit as a target user when the current date is detected to be a preset time from the underwriting ending time limit; acquiring historical underwriting information, pay information and management information of a target user, wherein the historical underwriting information comprises deposit information and position information, and the management information comprises: service type information and credit information; based on a clustering algorithm, generating basic premium and first pay amount corresponding to service type information according to the premium information and the pay information; determining the risk level of the target user according to the position information, the service type information and the credit information; generating a second payable amount according to the risk level and the first payable amount; generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount; generating a scheme link according to the renewal scheme, inserting the scheme link into a display area corresponding to the target user, and marking the display area corresponding to the target user.
While the application has been described with reference to certain preferred embodiments, it will be understood by those skilled in the art that various changes and substitutions of equivalents may be made and equivalents will be apparent to those skilled in the art without departing from the scope of the application. Therefore, the protection scope of the application is subject to the protection scope of the claims.

Claims (10)

1. A user indication method, applied to a terminal device, the terminal device including an application interface, the application interface including a display area of each user, the method comprising:
acquiring the underwriting ending periods of a plurality of users, and determining the user corresponding to the underwriting ending period as a target user when the current date is detected to be a preset time from the underwriting ending period;
acquiring historical underwriting information, pay information and management information of the target user, wherein the historical underwriting information comprises deposit information and position information, and the management information comprises: service type information and credit information;
based on a clustering algorithm, generating basic premium and first payoff amount corresponding to the service type information according to the premium information and the payoff information;
determining a risk level of the target user according to the position information, the service type information and the credit information;
generating a second payline according to the risk level and the first payline;
generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount;
generating a scheme link according to the renewal scheme, inserting the scheme link into a display area corresponding to the target user, and marking the display area corresponding to the target user.
2. The user labeling method of claim 1, wherein the determining the risk level of the target user based on the location information, the service type information, and the credit information comprises:
determining a first risk coefficient of the target user according to the position information and the service type information;
determining a second risk coefficient of the target user according to the credit information;
and determining the risk level according to the first risk coefficient and the second risk coefficient.
3. The user labeling method of claim 2, wherein the determining the first risk factor of the target user based on the location information and the service type information comprises:
acquiring a risk area corresponding to the service type information;
determining the first risk coefficient according to the geographical relation between the position information and the risk area, wherein the geographical relation comprises the following steps: overlapping, adjacent and dispersed.
4. The user labeling method of claim 2, wherein the risk levels comprise a first risk level, a second risk level, and a third risk level, and wherein determining the risk level based on the first risk coefficient and the second risk coefficient comprises:
when the first risk coefficient is detected to be larger than a first preset threshold value and the second coefficient is detected to be larger than a second preset threshold value, determining the risk level as the first risk level;
when the first risk coefficient is detected to be smaller than the first preset threshold value and the second coefficient is detected to be larger than the second preset threshold value, determining the risk level to be the second risk level;
and when the first risk coefficient is detected to be smaller than the first preset threshold value and the second coefficient is detected to be smaller than the second preset threshold value, determining the risk level as the third risk level.
5. The user labeling method of claim 1, wherein the policy information comprises a policy applied fee over the years, the reimbursement information comprises a reimbursement amount over the years, the generating the base policy and the first reimbursement amount corresponding to the business type information based on the policy information and the reimbursement information based on a clustering algorithm comprises:
determining the premium acceptance of the target user according to the applied premium over the years;
determining the basic premium according to the applied premium and the premium acceptance of the year previous to the current date;
and determining a first payable amount according to the payable amount of the calendar year and the basic premium.
6. The user labeling method of claim 1, wherein after labeling the display area corresponding to the target user, the method further comprises:
acquiring an agent input browsing instruction, and determining the target scheme link according to the browsing instruction, wherein the target scheme link is one of the scheme links;
acquiring a renewal scheme corresponding to the target scheme link;
and generating a scheme browsing window on the application interface, and displaying a renewal scheme corresponding to the target scheme link through the scheme browsing window.
7. The user labeling method of claim 1, wherein after the obtaining of the historical underwriting information, the reimbursement information, and the administration information of the target user, the method further comprises:
and cleaning the data of the historical underwriting information, the pay information and the business information.
8. A user identification device, comprising:
the user determining module is used for acquiring the underwriting ending periods of a plurality of users, and determining the user corresponding to the underwriting ending period as a target user when detecting that the current date is a preset time from the underwriting ending period;
the information acquisition module is used for acquiring the historical underwriting information, the pay information and the management information of the target user, wherein the historical underwriting information comprises the insurance information and the position information, and the management information comprises: service type information and credit information;
the credit evaluation module is used for generating basic premium and first credit corresponding to the service type information according to the credit information and the credit information based on a clustering algorithm;
the risk estimation module is used for determining the risk level of the target user according to the position information, the service type information and the credit information;
the limit determining module is used for generating a second pay limit according to the risk level and the first pay limit;
the scheme generation module is used for generating a renewal scheme according to the position information, the operation information, the risk level, the basic premium and the second claim amount;
and the result marking module is used for generating a scheme link according to the renewal scheme, inserting the scheme link into the display area corresponding to the target user, and marking the display area corresponding to the target user.
9. A computer device, the computer device comprising a memory and a processor;
the memory is used for storing a computer program;
the processor being adapted to execute the computer program and to implement the user indication method according to any of claims 1 to 7 when the computer program is executed.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program, which when executed by a processor causes the processor to implement the user indication method according to any one of claims 1 to 7.
CN202311190463.4A 2023-09-14 2023-09-14 User marking method, device, equipment and storage medium Pending CN117151899A (en)

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CN202311190463.4A CN117151899A (en) 2023-09-14 2023-09-14 User marking method, device, equipment and storage medium

Applications Claiming Priority (1)

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Publications (1)

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