CN110706117A - Business processing method, device, computer device and storage medium - Google Patents

Abstract

A business processing method includes: acquiring account information of a target business object; acquiring historical insurance application data corresponding to the account information; calling a preset classification model; inputting the historical insurance application data into the preset classification model, so that all The preset classification model determines the account level corresponding to the target business object according to the historical insurance application data; judges whether the target business object meets the insurance application standards of the insurance business according to the account level, and determines whether the target business A prompt message is generated when the object meets the insurance criteria. Embodiments of the present invention also provide a business processing device, a computer device, and a storage medium, which can accurately identify and divide target business objects through machine learning and improve the accuracy of underwriting results.

Description

Business processing method, device, computer device and storage medium

technical field

The present invention relates to the field of computer technologies, and in particular, to a service processing method, a service processing device, a computer device, and a computer-readable storage medium.

Background technique

With the advent of the Internet era, Internet business has developed by leaps and bounds, and people can realize more and more business operations through the Internet, such as: buying and selling commodities, insurance, etc. In related technologies, when a user wants to apply for insurance through the Internet, the user is often required to submit relevant review materials online for the insurance company to review, and provide insurance-related services to the user after the review is passed. However, in such an implementation scheme, users often need to fill in a large number of audit information for projects and provide relevant certification materials, and the audit cycle is long, which is poor for the user experience.

SUMMARY OF THE INVENTION

In view of the above content, it is necessary to provide a business processing method and device, a computer device and a computer-readable storage medium, so as to solve the above problems.

A first aspect of the present application provides a service processing method, which is applied in a computer device, and the service processing method includes:

Obtain the account information of the target business object;

Obtain historical insurance data corresponding to the account information;

Calling a preset classification model, wherein, when the input variable of the predictive classification model is insurance data, the output variable is the account level;

Inputting the historical insurance application data into the preset classification model, so that the preset classification model determines the account level corresponding to the target business object according to the historical insurance application data;

Judging whether the target business object meets the insurance application standards of the insurance business according to the account level; and

When the target business object meets the insurance application standard, a prompt message is generated and sent to the target business object.

A second aspect of the present application provides a service processing apparatus, which is applied in a computer apparatus, and the service processing apparatus includes:

The first acquisition module is used to acquire the account information of the target business object;

a second obtaining module, configured to obtain historical insurance data corresponding to the account information;

a calling module for calling a preset classification model, wherein, when the input variable of the predictive classification model is insurance data, the output variable is the account level;

an input control module, configured to input the historical insurance application data into the preset classification model, so that the preset classification model determines the account level corresponding to the target business object according to the historical insurance application data; and

The judgment and prompting module is configured to judge whether the target business object meets the insurance application standard of the insurance business according to the account level, and when the target business object meets the insurance application standard, generate a prompt message and send it to the target business object.

A third aspect of the present application provides a computer device, the computer device includes a processor, and the processor is configured to implement the aforementioned business processing method when executing a computer program stored in a memory.

A fourth aspect of the present application provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, implements the aforementioned business processing method.

The present invention obtains the historical insurance data of multiple dimensions such as the risk situation, renewal situation and premium amount of the target business object, and invokes a unified preset classification model to determine the underwriting result, which is conducive to accurately identifying and dividing the target business object And improve the accuracy of underwriting results; moreover, it solves the problem of long review cycle, and at the same time, the whole process does not require users to submit and provide materials, which greatly improves the user experience.

Description of drawings

FIG. 1 is a flowchart of a service processing method provided by Embodiment 1 of the present invention.

FIG. 2 is a schematic diagram of the service processing method shown in FIG. 1 .

FIG. 3 is a schematic structural diagram of a service processing apparatus according to Embodiment 2 of the present invention.

FIG. 4 is a schematic diagram of a computer device according to Embodiment 3 of the present invention.

Description of main component symbols

computer device 1

Memory 20

processor 30

computer program 40

business processing device 10

first acquisition module 101

second acquisition module 102

call module 103

Input Control Module 104

Judgment and Prompt Module 105

Training Module 106

The following specific embodiments will further illustrate the present invention in conjunction with the above drawings.

Detailed ways

In order to more clearly understand the above objects, features and advantages of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments may be combined with each other in the case of no conflict.

In the following description, many specific details are set forth in order to facilitate a full understanding of the present invention, and the described embodiments are only some, but not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terms used herein in the description of the present invention are for the purpose of describing specific embodiments only, and are not intended to limit the present invention.

Example 1

Please refer to FIG. 1 , which is a flowchart of the service processing method provided by the first embodiment of the present invention. The business processing method is applied in a computer device. According to different requirements, the order of the steps in this flowchart can be changed, and some steps can be omitted.

Step S11, acquiring account information of the target business object.

In this embodiment, the computer device first obtains the account information of the target business object when judging whether the historical insurance target business object meets the insurance application standard of a certain insurance business (hereinafter referred to as underwriting), and the account information It may include: account name, ID number, e-mail, mobile phone number and other information that can identify the identity of the target business object. For example, when the target business object dials the telephone agent system through the mobile phone number to inquire about insurance application issues, the computer device may obtain the mobile phone number of the target business object and use the mobile phone number as the target business object's account information. The target business objects may include users who have not applied for insurance services, and users who have applied for insurance services.

Step S12: Obtain historical insurance application data corresponding to the account information.

The historical insurance application data is data required for underwriting, and the computer device acquires the historical insurance application data from a data source. The data source may be an insurance application (Appliation, APP) or an insurance database of an insurance company. For example, the electronic policy corresponding to the insurance product purchased by the target business object may be acquired through the insurance database of the insurance company, and the historical insurance application data recorded in the electronic policy may be acquired.

Wherein, the historical insurance application data is preset by the developer according to the specific category of the insurance business. In this implementation manner, the historical insurance application data includes the accident situation, the insurance renewal situation, the premium amount, and the like. In actual implementation, different historical insurance application data may also be set for different types of target business objects, which is not specifically limited in this application.

Step S13, calling a preset classification model, wherein when the input variable of the predictive classification model is insurance application data, the output variable is the account level.

In this embodiment, the computer device obtains sample data of a plurality of groups of sample objects in advance, and each group of sample data includes insurance application data of the sample objects and a corresponding account level. The insurance application data includes the insurance situation, the insurance renewal situation and the premium amount. The account level may be divided into a first account level, a second account level, a third account level and a fourth type of account level. This embodiment is described by taking the first account level, the second account level, the third account level and the fourth type of account level as diamond level, platinum level, gold level and common level as an example. The sample data can be referred to as shown in Table 1.

Table 1 Sample data

Then, the computer device trains the preset classification model according to the sample data and stores the preset classification model for subsequent recall. Wherein, when training the preset classification model, machine learning algorithms, such as logistic regression (Logistic Regression, LR) algorithm, Support Vector Machine (Support Vector Machine, SVM) algorithm, and iterative decision tree (Gradient Boosting Decision) can be used. Tree, GBDT for short) algorithm and other standard two-class training methods, or one-class support vector machine (One Class SVM) and other single-class training methods.

Please refer to FIG. 2 together. In this embodiment, a decision tree algorithm is used to train the prediction classification model, wherein the decision tree algorithm belongs to a supervised learning classification algorithm, and the obtained prediction classification model represents a relationship between an object attribute and an object value. Mapping relations. The prediction classification model has N layers (N is a natural number, N>2, and N=4 in this embodiment). As shown in Figure 2, the first layer of the predictive classification model is the root node, and the second layer of the predictive classification model represents multiple nodes obtained by dividing the root node with the first-level historical insurance data, so The third layer of the prediction classification model represents a plurality of nodes obtained by dividing the upper layer nodes with the second-level historical insurance data, and the fourth layer of the prediction classification model represents the third-level historical insurance data. A plurality of nodes obtained by dividing the node, the node of the fourth layer is the leaf node of the prediction classification model, and each leaf node represents one of the account levels.

Step S14: Input the historical insurance application data into the preset classification model, so that the preset classification model determines the account level corresponding to the target business object according to the historical insurance application data.

Step S15, according to the account level, it is judged whether the target business object meets the insurance application standard of the insurance business.

In this embodiment, the computer device prestores a plurality of correspondences between insurance services and preset account levels, each insurance business corresponds to at least one preset account level, and the correspondence is used to indicate that the At least one preset account level of the insurance application standard of the insurance business. Therefore, the computer device can judge whether the target business object meets the insurance application standard of any of the insurance services according to the corresponding relationship.

Wherein, the insurance business may be a business type that the target object actively consults. For example, when the target object inquires about the insurance business through a telephone agent system, a relevant person (eg, an agent) may input an inquiry command including the insurance business into the computer device. The query instruction is used to control the computer to query whether the target business object complies with the insurance application standard of the insurance business according to the account level and the corresponding relationship. Specifically, the computer device determines at least one preset account level corresponding to the insurance business according to the insurance business determination and the corresponding relationship included in the query instruction, and determines whether the account level belongs to the determined account level. one of the at least one preset account level, when the account level corresponding to the target business object belongs to one of the determined at least one preset account level, it is judged that the target business object complies with the insurance business Insurance standards.

Step S16, when the target business object meets the insurance application standard, generate a prompt message and send it to the target business object.

Further, the prompt information can be displayed on the computer device in a text format, for example, the text can be "this customer meets the insurance standards for loan-type co-sale products". Therefore, after the relevant personnel (eg, the agent) directly learns that the target business object meets the insurance application standard according to the prompt information, the insurance business and the like can be pushed to the target business object. Of course, the prompt information can also be output by the computer device in other ways such as voice broadcast.

In other embodiments, the insurance service may also be actively pushed to the target service object. That is, the computer device actively searches for all insurance services corresponding to the target business object (ie, all insurance services that meet insurance standards) according to the account level and the corresponding relationship, and generates the prompt information. In this case, the computer device is further configured to send the prompt information to the target business object according to the account information (eg, e-mail, mobile phone number).

1 describes the service processing method of the present invention in detail, and the functional modules of the software device implementing the service processing method and the hardware device architecture implementing the service processing method are introduced below with reference to FIG. 3 and FIG. 4 .

It should be understood that the embodiments are only used for illustration, and are not limited by this structure in the scope of the patent application.

Embodiment 2

FIG. 3 is a structural diagram of a preferred embodiment of a service processing apparatus according to the present invention.

In some embodiments, the business processing device 10 runs on a computer device. The service processing apparatus 10 may include a plurality of functional modules composed of program code segments. The program codes of each program segment in the service processing apparatus 10 may be stored in the memory of the computer apparatus and executed by the at least one processor to realize service processing functions.

In this embodiment, the service processing apparatus 10 may be divided into multiple functional modules according to the functions performed by the service processing apparatus 10 . Referring to FIG. 3 , the functional modules may include: a first acquisition module 101 , a second acquisition module 102 , a calling module 103 , an input control module 104 , and a judgment and prompt module 105 . The modules referred to in the present invention refer to a series of computer program segments that can be executed by at least one processor and can perform fixed functions, and are stored in a memory. In this embodiment, the functions of each module will be described in detail in subsequent embodiments.

The first obtaining module 101 is configured to obtain account information of the target business object.

In this embodiment, when judging whether a historically insured target business object conforms to the insurance application standard of a certain insurance business (hereinafter referred to as: underwriting), the first obtaining module 101 is configured to first obtain the account information of the target business object , the account information may include: account name, ID number, e-mail, mobile phone number and other information that can identify the identity of the target business object. For example, when the target business object dials the telephone agent system through the mobile phone number to inquire about insurance application issues, the first obtaining module 101 may obtain the mobile phone number of the target business object and use the mobile phone number as the target business object of the account information. The target business objects may include users who have not applied for insurance services, and users who have applied for insurance services.

The second obtaining module 102 is configured to obtain historical insurance application data corresponding to the account information.

The historical insurance application data is data required for underwriting, and the second acquisition module 102 is configured to acquire the historical insurance application data from a data source. The data source may be an insurance application (Appliation, APP) or an insurance database of an insurance company. For example, the electronic policy corresponding to the insurance product purchased by the target business object may be acquired through the insurance database of the insurance company, and the historical insurance application data recorded in the electronic policy may be acquired.

Wherein, the historical insurance application data is preset by the developer according to the specific category of the insurance business. In this implementation manner, the historical insurance application data includes the accident situation, the insurance renewal situation, the premium amount, and the like. In actual implementation, different historical insurance application data may also be set for different types of target business objects, which is not specifically limited in this application.

The calling module 103 is used for calling a preset classification model, wherein when the input variable of the predictive classification model is insurance data, the output variable is the account level.

In this embodiment, the functional module further includes a training module 106 . The training module 106 is configured to obtain sample data of multiple groups of sample objects in advance, and each group of sample data includes insurance application data of the sample objects and corresponding account levels. The insurance application data includes the insurance situation, the insurance renewal situation and the premium amount. The account level may be divided into a first account level, a second account level, a third account level and a fourth type of account level. This embodiment is described by taking the first account level, the second account level, the third account level and the fourth type of account level as diamond level, platinum level, gold level and common level as an example. The sample data can be referred to as shown in Table 1 above.

Then, the training module 106 trains the preset classification model according to the sample data and stores the preset classification model for subsequent calling. Wherein, when training the preset classification model, machine learning algorithms, such as logistic regression (Logistic Regression, LR) algorithm, Support Vector Machine (Support Vector Machine, SVM) algorithm, and iterative decision tree (Gradient Boosting Decision) can be used. Tree, GBDT for short) algorithm and other standard two-class training methods, or one-class support vector machine (One Class SVM) and other single-class training methods.

Please refer to FIG. 2 together. In this embodiment, a decision tree algorithm is used to train the prediction classification model, wherein the decision tree algorithm belongs to a supervised learning classification algorithm, and the obtained prediction classification model represents a relationship between an object attribute and an object value. Mapping relations. The prediction classification model has N layers (N is a natural number, N>2, and N=4 in this embodiment). As shown in Figure 2, the first layer of the predictive classification model is the root node, and the second layer of the predictive classification model represents multiple nodes obtained by dividing the root node with the first-level historical insurance data, so The third layer of the prediction classification model represents a plurality of nodes obtained by dividing the upper layer nodes with the second-level historical insurance data, and the fourth layer of the prediction classification model represents the third-level historical insurance data. A plurality of nodes obtained by dividing the node, the node of the fourth layer is the leaf node of the prediction classification model, and each leaf node represents one of the account levels.

The input control module 104 is configured to input the historical insurance application data into the preset classification model, so that the preset classification model determines the account level corresponding to the target business object according to the historical insurance application data.

The judging and prompting module 105 is configured to judge whether the target business object meets the insurance application standard of the insurance business according to the account level, and when the target business object meets the insurance application standard, generate a prompt message and send it to the target business object.

In this embodiment, the computer device prestores a plurality of correspondences between insurance services and preset account levels, each insurance business corresponds to at least one preset account level, and the correspondence is used to indicate that the At least one preset account level of the insurance application standard of the insurance business. Therefore, the judging and prompting module 105 can judge whether the target business object meets the insurance application standard of any of the insurance services according to the corresponding relationship.

Wherein, the insurance business may be a business type that the target object actively consults. For example, when the target object inquires about the insurance business through a telephone agent system, a relevant person (eg, an agent) may input an inquiry command including the insurance business into the computer device. The query instruction is used to control the judging and prompting module 105 to query whether the target business object meets the insurance application standard of the insurance business according to the account level and the corresponding relationship. Specifically, the computer device determines at least one preset account level corresponding to the insurance business according to the insurance business determination and the corresponding relationship included in the query instruction, and determines whether the account level belongs to the determined account level. one of the at least one preset account level, when the account level corresponding to the target business object belongs to one of the determined at least one preset account level, it is judged that the target business object complies with the insurance business Insurance standards.

Further, the prompt information can be displayed on the computer device in a text format, for example, the text can be "this customer meets the insurance standards for loan-type co-sale products". Therefore, after the relevant personnel (eg, the agent) directly learns that the target business object meets the insurance application standard according to the prompt information, the insurance business and the like can be pushed to the target business object. Of course, the prompt information can also be output by the computer device in other ways such as voice broadcast.

In other embodiments, the insurance service may also be actively pushed to the target service object. That is, the judging and prompting module 105 actively searches all insurance services corresponding to the target business object (ie, all insurance services that meet insurance standards) according to the account level and the corresponding relationship, and generates the prompt information. In this case, the computer device is further configured to send the prompt information to the target business object according to the account information (eg, e-mail, mobile phone number).

As mentioned above, the business processing apparatus in the embodiment of the present invention obtains the historical insurance data of multiple dimensions, such as the accident situation, insurance renewal situation, and premium amount of the target business object, and invokes a unified preset classification model to determine the core value. The guarantee result is conducive to the accurate identification and division of the target business objects and improves the accuracy of the underwriting results; moreover, it solves the problem of long review cycle, and at the same time, the whole process does not require users to submit and provide materials, which greatly improves the user experience.

Embodiment 3

FIG. 4 is a schematic diagram of a preferred embodiment of the computer apparatus of the present invention.

The computer device 1 comprises a memory 20, a processor 30 and a computer program 40, such as a business processing program, stored in the memory 20 and executable on the processor 30. When the processor 30 executes the computer program 40, the steps in the foregoing service processing method embodiments are implemented, for example, steps S11 to S16 shown in FIG. 1 . Alternatively, when the processor 30 executes the computer program 40, the functions of each module/unit in the above-mentioned embodiment of the service processing apparatus, such as units 101-106 in FIG. 3, are implemented.

Exemplarily, the computer program 40 may be divided into one or more modules/units, and the one or more modules/units are stored in the memory 20 and executed by the processor 30 to complete the this invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, and the instruction segments are used to describe the execution process of the computer program 40 in the computer device 1 . For example, the computer program 40 can be divided into a first acquisition module 101 , a second acquisition module 102 , a calling module 103 , an input control module 104 , a judgment and prompt module 105 and a training module 106 in FIG. 3 . For the specific functions of each module, refer to Embodiment 2.

The computer device 1 may be a computing device such as a desktop computer, a notebook computer, a palmtop computer, and a cloud server. Those skilled in the art can understand that the schematic diagram is only an example of the computer device 1, and does not constitute a limitation on the computer device 1, and may include more or less components than the one shown, or combine some components, or different Components such as the computer apparatus 1 may also include input and output devices, network access devices, buses, and the like.

The so-called processor 30 may be a central processing unit (Central Processing Unit, CPU), and may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), Off-the-shelf programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and the like. The general-purpose processor can be a microprocessor or the processor 30 can also be any conventional processor, etc. The processor 30 is the control center of the computer device 1, and uses various interfaces and lines to connect the entire computer device 1. various parts.

The memory 20 may be used to store the computer program 40 and/or modules/units, and the processor 30 may call the computer programs and/or modules/units stored in the memory 20 by running or executing the computer programs and/or modules/units stored in the memory 20. 20 to realize various functions of the computer device 1 . The memory 20 may mainly include a stored program area and a stored data area, wherein the stored program area may store an operating system, an application program required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the storage data area may Data such as audio data and the like created according to the use of the computer apparatus 1 are stored. In addition, the memory 20 may include non-volatile memory such as hard disk, internal memory, plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card (FlashCard), at least A magnetic disk storage device, flash memory device, or other non-volatile solid state storage device.

If the modules/units integrated in the computer device 1 are implemented in the form of software functional units and sold or used as independent products, they may be stored in a computer-readable storage medium. Based on this understanding, the present invention can implement all or part of the processes in the methods of the above embodiments, and can also be completed by instructing relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the program is executed by the processor, the steps of the foregoing method embodiments can be implemented. Wherein, the computer program includes computer program code, and the computer program code may be in the form of source code, object code, executable file or some intermediate form, and the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM, Read-Only Memory) .

In the several embodiments provided by the present invention, it should be understood that the disclosed computer apparatus and method may be implemented in other manners. For example, the computer apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division manners in actual implementation.

In addition, each functional unit in each embodiment of the present invention may be integrated in the same processing unit, or each unit may exist physically alone, or two or more units may be integrated in the same unit. The above-mentioned integrated units can be implemented in the form of hardware, or can be implemented in the form of hardware plus software function modules.

It will be apparent to those skilled in the art that the present invention is not limited to the details of the above-described exemplary embodiments, but that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics of the invention. Therefore, the embodiments are to be regarded in all respects as illustrative and not restrictive, and the scope of the invention is to be defined by the appended claims rather than the foregoing description, which are therefore intended to fall within the scope of the claims. All changes within the meaning and range of the equivalents of , are included in the present invention. Any reference signs in the claims shall not be construed as limiting the involved claim. Furthermore, it is clear that the word "comprising" does not exclude other units or steps and the singular does not exclude the plural. A plurality of units or computer devices recited in the computer device claims can also be realized by one and the same unit or computer device by means of software or hardware. The terms first, second, etc. are used to denote names and do not denote any particular order.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be Modifications or equivalent substitutions can be made without departing from the spirit and scope of the technical solutions of the present invention.

Claims (9)

1. A business processing method, applied in a computer device, wherein the business processing method comprises: Obtain the account information of the target business object; Obtain historical insurance data corresponding to the account information; Calling a preset classification model, wherein, when the input variable of the predictive classification model is insurance data, the output variable is the account level; Inputting the historical insurance application data into the preset classification model, so that the preset classification model determines the account level corresponding to the target business object according to the historical insurance application data; Judging whether the target business object meets the insurance application standards of the insurance business according to the account level; and When the target business object meets the insurance application standard, a prompt message is generated and sent to the target business object. 2. The business processing method according to claim 1, wherein before the invoking a preset classification model, the business processing method further comprises: Obtain sample data of multiple groups of sample objects, each group of sample data includes the insurance application data of the sample objects and the corresponding account level, and the insurance application data includes the accident situation, the renewal situation and the premium amount; Train the preset classification model according to the sample data; and The preset classification model is stored. 3 . The business processing method according to claim 2 , wherein the predictive classification model is obtained by training using a decision tree algorithm. 4 . 4. The business processing method according to claim 1, wherein the computer device prestores the correspondence between a plurality of insurance services and a preset account level, and each insurance business corresponds to at least one preset account level , the corresponding relationship is used to indicate at least one preset account level that meets the insurance application standard of the insurance business, and the computer device determines whether the target business object meets the insurance application standard of the insurance business according to the corresponding relationship. 5. The business processing method according to claim 4, wherein the determining whether the target business object conforms to the insurance application standard of the insurance business according to the account level comprises: receiving an inquiry instruction including the insurance business; Determine at least one preset account level corresponding to the insurance service according to the insurance service determination and the corresponding relationship included in the query instruction; determining whether the account level belongs to one of the determined at least one preset account level; When the account level corresponding to the target business object belongs to one of the determined at least one preset account level, it is determined that the target business object meets the insurance application standard of the insurance business. 6. The business processing method according to claim 1, wherein when the target business object communicates with the computer device through a mobile phone, the mobile phone number of the target business object is obtained and the mobile phone number is used as the the account information. 7. A service processing device, applied in a computer device, wherein the service processing device comprises: The first acquisition module is used to acquire the account information of the target business object; a second obtaining module, configured to obtain historical insurance data corresponding to the account information; a calling module for calling a preset classification model, wherein, when the input variable of the predictive classification model is insurance data, the output variable is the account level; an input control module, configured to input the historical insurance application data into the preset classification model, so that the preset classification model determines the account level corresponding to the target business object according to the historical insurance application data; and The judgment and prompting module is configured to judge whether the target business object meets the insurance application standard of the insurance business according to the account level, and when the target business object meets the insurance application standard, generate a prompt message and send it to the target business object. 8. A computer device, characterized in that: the computer device comprises a processor, and the processor is configured to implement the service processing method according to any one of claims 1-6 when executing the computer program stored in the memory. 9. A computer-readable storage medium on which a computer program is stored, characterized in that: when the computer program is executed by a processor, the service processing method according to any one of claims 1-6 is implemented.

Images