Strategy customization method, device, electronic device and medium based on evaluation model

Abstract

The embodiment of the present application provides a policy customization method, device, electronic device and medium based on an evaluation model, which belongs to the field of financial technology. The method includes: obtaining insurance data to be evaluated, user demand information, and obtaining environmental factor information and historical policy data of the property to be insured; performing data analysis on the historical policy data to determine risk factors; inputting the risk factors into a preset evaluation model for quantitative evaluation and outputting the policy claim ratio; determining the insurance impact value based on the policy claim ratio and historical policy data; setting a risk level table based on the insurance impact value; inputting the insurance data to be evaluated and environmental factor information into the evaluation model for risk evaluation and outputting the risk evaluation result; determining the target risk range and target risk amount threshold; generating a target insurance policy based on the target risk amount threshold, insurance company information and user demand information. The embodiment of the present application can formulate different strategies according to the personalized needs of users.

Description

Technical Field

[0001] The present application relates to the field of financial technology, and in particular to a strategy customization method, device, electronic device and medium based on an evaluation model. Background Art

[0002] With economic development and social progress, property insurance plays an increasingly important role in protecting the property of individuals and businesses. In the current property insurance sector, despite the crucial role insurance products play in protecting personal and corporate property, traditional assessment and management methods face numerous challenges. These methods often rely on manual operations and outdated models, resulting in inefficient data processing and difficulty in quickly responding to market changes and customer needs. Furthermore, due to the lack of refined risk assessment tools, these traditional methods also lack accuracy and often fail to accurately predict and quantify risks. This can lead to insurance pricing or claims decisions deviating from actual risk levels, making it impossible to formulate tailored strategies to individual user needs, further reducing user satisfaction. Summary of the Invention

[0003] The main purpose of the embodiments of the present application is to propose a policy customization method, device, electronic device and medium based on an evaluation model, which can improve the accuracy of risk assessment and formulate different policies according to the personalized needs of users.

[0004] To achieve the above objectives, a first aspect of an embodiment of the present application proposes a policy customization method based on an evaluation model, the method comprising:

[0005] Obtaining insurance data to be evaluated and user demand information, and obtaining environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and historical policy data of the property to be insured, wherein the historical policy data includes policy information and insurance company information, and the environmental factor information is used to represent information on risk factors affecting the property to be insured;

[0006] Performing data analysis on the historical policy data to determine risk factors;

[0007] Input the risk factor into a preset evaluation model for quantitative evaluation, and output a policy loss ratio, wherein the policy loss ratio is used to represent the profit and loss situation of the policy corresponding to the policy information;

[0008] Determining an insurance impact value based on the policy claim ratio and the historical policy data, wherein the insurance impact value is used to represent the degree of influence of the policy information on the insurance company corresponding to the insurance company information;

[0009] Setting a risk level table according to the insurance impact value, wherein the risk level table includes a plurality of risk intervals, and each risk interval is set with a risk amount threshold;

[0010] Inputting the insurance data to be evaluated and the environmental factor information into the evaluation model to perform risk evaluation, and outputting the risk evaluation result;

[0011] Determining a target risk interval corresponding to the risk assessment result in the risk level table, and determining a target risk amount threshold corresponding to the target risk interval;

[0012] A target insurance policy is generated according to the target risk amount threshold, the insurance company information, and the user demand information.

[0013] In some embodiments, performing data analysis on the historical policy data to determine risk factors includes:

[0014] Standardizing the historical policy data to obtain multiple policy fields;

[0015] Performing data association operations on all the policy fields through a preset claims system to obtain target policy data;

[0016] Parameters of the target policy data are selected based on the preset single variable method to determine the risk factors.

[0017] In some embodiments, performing a data association operation on all the policy fields through a preset claims system to obtain target policy data includes:

[0018] Performing data association operations on all the policy fields through a preset claims system to obtain associated data and discrete data;

[0019] For each discrete data, creating a discrete variable corresponding to the discrete data, and setting an original variable value of the discrete variable;

[0020] Replacing the original variable value of the discrete variable based on a preset transformation rule to obtain a target discrete value;

[0021] updating the discrete data according to the target discrete value, and generating policy data according to the updated discrete data and the associated data;

[0022] The insurance policy data is cleaned to obtain target insurance policy data.

[0023] In some embodiments, the insurance company information includes operating cost information and the company's total insurance policy premiums; and determining the insurance impact value based on the insurance policy loss ratio and the historical insurance policy data includes:

[0024] Determining, based on the policy information, the policy premium of the policy corresponding to the policy information;

[0025] Determining the company loss ratio of the insurance company corresponding to the insurance company information based on the operating cost information;

[0026] Determining a policy impact value based on the policy loss ratio, the company loss ratio, and the policy premium;

[0027] Calculate the ratio of the policy impact value to the company's total policy premium to determine the insurance impact value.

[0028] In some embodiments, setting a risk level table according to the insurance impact value includes:

[0029] When the insurance impact value is greater than a first preset impact value, generating a first risk interval according to the first preset impact value, and determining the first amount as a risk amount threshold of the first risk interval;

[0030] When the insurance impact value is greater than the second preset impact value and less than or equal to the first preset impact value, generating a second risk interval according to the first preset impact value and the second preset impact value, and determining the second amount as the risk amount threshold of the second risk interval;

[0031] When the insurance impact value is less than or equal to a second preset impact value, generating a third risk interval according to the second preset impact value, and determining the third amount as a risk amount threshold of the third risk interval;

[0032] The first preset impact value is greater than the second preset impact value, and the first amount, the second amount and the third amount decrease in sequence.

[0033] In some embodiments, the insurance company information includes an insurance premium rate; generating a target insurance policy based on the target risk amount threshold, the insurance company information, and the user demand information includes:

[0034] Determining interval rules corresponding to the target risk interval based on the insurance company information, wherein the interval rules are rules that restrict application scenarios of the property to be insured;

[0035] Determining the intended insurance amount, insurance period, and compensation amount of the property to be insured based on the user demand information;

[0036] When the intended insurance amount is less than or equal to the target risk amount threshold, and the insurance period and the compensation amount meet the interval rule, a target insurance policy is generated based on the insurance premium rate, the intended insurance amount, the insurance period and the compensation amount.

[0037] In some embodiments, after determining the intended insurance amount, insurance period, and compensation amount of the property to be insured based on the user demand information, the method further includes:

[0038] When the intended insurance amount is greater than the target risk amount threshold, the insurance period does not comply with the interval rule, or the compensation amount does not comply with the interval rule, a target insurance policy is generated based on the target risk amount threshold, the insurance premium rate, and the interval rule.

[0039] To achieve the above-mentioned purpose, a second aspect of an embodiment of the present application proposes a policy customization device based on an evaluation model, the device comprising:

[0040] A data acquisition module, configured to acquire insurance data to be evaluated and user demand information, and to acquire environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and historical policy data of the property to be insured, wherein the historical policy data includes policy information and insurance company information;

[0041] A data analysis module, configured to analyze the historical policy data and determine risk factors;

[0042] A quantitative assessment module, configured to input the risk factors into a preset assessment model for quantitative assessment and output a policy loss ratio, wherein the policy loss ratio is used to represent the profit and loss situation of the policy corresponding to the policy information;

[0043] an impact value determination module, configured to determine an insurance impact value based on the policy claim ratio and the historical policy data, wherein the insurance impact value is used to represent the degree of influence of the policy information on the insurance company corresponding to the insurance company information;

[0044] A level table setting module is used to set a risk level table according to the insurance impact value, wherein the risk level table includes multiple risk intervals, and each risk interval is set with a risk amount threshold;

[0045] A risk assessment module, configured to input the insurance data to be assessed and the environmental factor information into the assessment model to perform risk assessment and output a risk assessment result;

[0046] a risk determination module, configured to determine a target risk interval corresponding to the risk assessment result in the risk level table, and determine a target risk amount threshold corresponding to the target risk interval;

[0047] A policy generation module is used to generate a target insurance policy based on the target risk amount threshold, the insurance company information and the user demand information.

[0048] To achieve the above-mentioned purpose, the third aspect of an embodiment of the present application proposes an electronic device, an electronic device, the electronic device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the policy customization method based on the evaluation model as described in the first aspect when executing the computer program.

[0049] To achieve the above-mentioned purpose, the fourth aspect of the embodiment of the present application proposes a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, it implements the policy customization method based on the evaluation model as described in the first aspect.

[0050] The present application proposes a strategy customization method, device, electronic device and storage medium based on an evaluation model. First, the insurance data to be evaluated and user demand information are obtained, and the environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and the historical policy data of the property to be insured are obtained, so as to facilitate the subsequent judgment of the physical environment in which the property to be insured is located and the factors that may cause risks to the property to be insured. Then, data analysis is performed on the historical policy data. The risk factors affecting the property to be insured are analyzed through the historical policy data to determine the risk factors, so as to facilitate the subsequent analysis of the compensation situation under different risk factors. The risk factors are input into the preset evaluation model for quantitative evaluation, and the various risks faced by the property to be insured are evaluated. The policy payout ratio is output, so as to obtain the profit and loss situation of the policy corresponding to the policy information under different risk factors, so as to facilitate the subsequent risk evaluation of the insurance product. Afterwards, the insurance impact value is determined according to the policy payout ratio and the historical insurance data, so as to determine the degree of influence of the policy information on the insurance company corresponding to the insurance company information, and conclusion can be made based on the policy payout ratio. By analyzing the impact of policy information in combination with other historical insurance data, it is possible to accurately analyze the impact of policy information on insurance companies, thereby improving the accuracy of policy analysis. A risk level table is then set up based on the insurance impact value, thereby dividing multiple risk intervals and achieving accurate division of risks of different levels. Finally, the insurance data to be evaluated and environmental factor information are input into the evaluation model for risk evaluation, and the risk evaluation results are output. This can accurately evaluate the risk level of a specific type of insurance, achieve accurate evaluation of the insurance data to be evaluated, and improve the accuracy and efficiency of property insurance evaluation. The target risk interval corresponding to the risk assessment result is determined in the risk level table, which can accurately determine the risk level of the property to be insured, and determine the target risk amount threshold corresponding to the target risk interval, so that the maximum amount threshold that the property to be insured can bear can be determined based on the risk assessment result, and then the target insurance strategy is generated based on the target risk amount threshold, insurance company information and user demand information, so that different insurance strategies can be personalized according to user needs to improve user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 This is a flow chart of a strategy customization method based on an evaluation model provided in an embodiment of the present application;

[0052] Figure 2 yes Figure 1 Flowchart of step S102 in FIG.

[0053] Figure 3 yes Figure 2 Flowchart of step S202 in FIG.

[0054] Figure 4 yes Figure 1 Flowchart of step S104 in FIG.

[0055] Figure 5 yes Figure 1 Flowchart of step S105 in FIG.

[0056] Figure 6 yes Figure 1 Flowchart of step S108 in FIG.

[0057] Figure 7 is a flow chart of a strategy customization method based on an evaluation model provided in another embodiment of the present application;

[0058] Figure 8 Schematic diagram of the structure of the strategy customization device based on the evaluation model provided in an embodiment of the present application;

[0059] Figure 9 This is a schematic diagram of the hardware structure of the electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0061] It should be noted that although the device schematics illustrate functional module divisions and the flowcharts illustrate logical sequences, in certain circumstances, the steps shown or described may be performed in a sequence that differs from the module divisions in the device or the sequence in the flowcharts. The terms "first," "second," and so on, in the specification, claims, and drawings, are used to distinguish similar items and are not necessarily used to describe a specific sequence or precedence.

[0062] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this application pertains. The terms used herein are for the purpose of describing the embodiments of this application only and are not intended to limit this application.

[0063] First, let’s analyze some of the terms used in this application:

[0064] Natural Language Processing (NLP): NLP uses computers to process, understand, and apply human languages ​​(such as Chinese and English). NLP is a branch of artificial intelligence and an interdisciplinary subject between computer science and linguistics. It is often referred to as computational linguistics. Natural language processing includes grammatical analysis, semantic analysis, and text understanding. Natural language processing is commonly used in technical fields such as machine translation, handwritten and printed character recognition, speech recognition and text-to-speech conversion, information intent recognition, information extraction and filtering, text classification and clustering, public opinion analysis, and opinion mining. It involves data mining related to language processing, machine learning, knowledge acquisition, knowledge engineering, artificial intelligence research, and linguistic research related to language computing.

[0065] One-Hot Encoding (OHE): One-Hot Encoding is a method for processing categorical variables that converts each category into a binary vector with one position being 1 to represent the current category and the rest being 0.

[0066] Label Encoding (LE): Label encoding maps each category of a categorical variable to a unique integer and is often used to convert text categories into numerical values ​​that can be processed by machine learning algorithms.

[0067] Structured Query Language (SQL): SQL is a programming language used to manage and manipulate relational databases. It allows users to perform various database operations such as querying, inserting, updating, and deleting data.

[0068] JOIN: In SQL, a JOIN is an operation used to combine rows from two or more tables into a single result set, typically based on related column values. There are several types of JOINs, such as INNER JOIN, LEFT JOIN, RIGHT JOIN, etc.

[0069] The evaluation model-based policy customization method and device, electronic device, and storage medium provided in the embodiments of the present application can improve the accuracy of risk assessment and formulate different policies based on the personalized needs of users.

[0070] The following examples are used to illustrate the specific implementation. First, the strategy customization method based on the evaluation model in the embodiment of the present application is described.

[0071] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. 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 achieve optimal results.

[0072] Fundamental AI technologies generally include sensors, specialized AI chips, cloud computing, distributed storage, big data processing, operating / interaction systems, and mechatronics. AI software technologies primarily encompass computer vision, robotics, biometrics, module management for online customer service systems, natural language processing, and machine learning / deep learning.

[0073] The policy customization method based on the evaluation model provided in the embodiment of the present application relates to the field of financial technology. The policy customization method based on the evaluation model provided in the embodiment of the present application can be applied to the terminal, can also be applied to the server side, and can also be software running in the terminal or the 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 as a server cluster or distributed system composed of multiple physical servers, or 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 policy customization method based on the evaluation model, etc., but is not limited to the above forms.

[0074] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld devices or portable devices, tablet devices, multi-processor systems, microprocessor-based systems, set-top boxes, programmable consumer electronic devices, 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 information 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.

[0075] It should be noted that in each specific embodiment of the present application, when it comes to the need to perform relevant processing based on data related to the user's 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 such data will comply with the relevant laws, regulations, and standards of the relevant countries and regions. 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.

[0076] With economic development and social progress, property insurance plays an increasingly important role in protecting the property of individuals and businesses. In the current property insurance sector, despite the crucial role insurance products play in protecting personal and corporate property, traditional assessment and management methods face numerous challenges. These methods often rely on manual operations and outdated models, resulting in inefficient data processing and difficulty in quickly responding to market changes and customer needs. Furthermore, due to the lack of refined risk assessment tools, these traditional methods also lack accuracy and often fail to accurately predict and quantify risks. This can lead to insurance pricing or claims decisions deviating from actual risk levels, making it impossible to formulate tailored strategies to individual user needs, further reducing user satisfaction.

[0077] In order to solve the above problems, this embodiment provides a strategy customization method, device, electronic device and storage medium based on an evaluation model. First, the insurance data to be evaluated and user demand information are obtained, and the environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and the historical policy data of the property to be insured are obtained, so as to facilitate the subsequent judgment of the physical environment in which the property to be insured is located and the factors that may cause risks to the property to be insured. Then, data analysis is performed on the historical policy data. The risk factors affecting the property to be insured are analyzed through the historical policy data to determine the risk factors, so as to facilitate the subsequent analysis of the compensation situation under different risk factors. The risk factors are input into a preset evaluation model for quantitative evaluation, and the various risks faced by the property to be insured are evaluated. The policy payout ratio is output, so as to obtain the profit and loss situation of the policy corresponding to the policy information under different risk factors, so as to facilitate the subsequent risk evaluation of the insurance product. Afterwards, the insurance impact value is determined according to the policy payout ratio and the historical insurance data, so as to determine the degree of influence of the policy information on the insurance company corresponding to the insurance company information, so as to be able to determine the degree of influence of the policy information on the insurance company corresponding to the insurance company information. Based on the analysis of the impact of policy information and other historical insurance data, the impact of policy information on the insurance company can be accurately analyzed, the accuracy of policy analysis can be improved, and then a risk level table is set according to the insurance impact value, thereby dividing multiple risk intervals and realizing accurate division of different levels of risks. Finally, the insurance data to be evaluated and the environmental factor information are input into the evaluation model for risk assessment, and the risk assessment results are output. It can accurately assess the risk level of a specific type of insurance, realize accurate assessment of the insurance data to be evaluated, and improve the accuracy and efficiency of property insurance assessment. The target risk interval corresponding to the risk assessment result is determined in the risk level table, which can accurately determine the risk level of the property to be insured and determine the target risk amount threshold corresponding to the target risk interval, so that the maximum amount threshold that the property to be insured can bear can be determined according to the risk assessment result, and then the target insurance strategy is generated according to the target risk amount threshold, insurance company information and user demand information, so that different insurance strategies can be personalized according to user needs to improve user satisfaction.

[0078] The following is a detailed description with reference to the accompanying drawings.

[0079] Figure 1 This is an optional flowchart of the strategy customization method based on the evaluation model provided in the embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S108.

[0080] Step S101 : obtaining insurance data to be evaluated and user demand information, and obtaining environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and historical insurance policy data of the property to be insured.

[0081] It should be noted that historical policy data includes policy information and insurance company information, and environmental factor information is used to characterize risk factors that affect the property to be insured.

[0082] In step S101 of some embodiments, the embodiments of the present application first obtain insurance data to be evaluated and user demand information, wherein the insurance data to be evaluated includes the property to be insured, and obtains environmental factor information and historical policy data of the property to be insured, so as to determine the environment in which the property to be insured is located, and further determine which factors in the environment in which the property to be insured is located that can cause risks to it, and can determine the previous insurance status of the property to be insured through historical policy data, so as to facilitate subsequent analysis of the compensation status under different risk situations.

[0083] It should be noted that the insurance data to be assessed in the embodiments of this application refers to data related to the insured property, such as property type, property value, property maintenance information, etc. Environmental factor information refers to external data related to the insured property, and represents risk factors that may affect the insured property, such as climate conditions, public security conditions, market price fluctuations, etc., facilitating subsequent accurate assessment of the risks of the insured property.

[0084] Understandably, a building located in a seismic zone may face a higher risk of earthquakes, or a property near a coastline may be more vulnerable to storms and flooding. Understanding these environmental factors can help insurers quantify potential losses, leading to more accurate risk assessments.

[0085] Step S102: Analyze historical policy data to determine risk factors.

[0086] In step S102 of some embodiments, data analysis is performed on historical policy data, and one or more variables that may affect the claims ratio are selected and determined as risk factors. The risk factors can be quickly identified, providing clear decision support information for the insurance company, facilitating the subsequent prediction of the claims ratio through risk factors.

[0087] Step S103: Input the risk factors into a preset evaluation model for quantitative evaluation and output the policy claim ratio.

[0088] It should be noted that the policy claim ratio is used to represent the profit and loss situation of the policy corresponding to the policy information.

[0089] It is worth noting that the evaluation model in the embodiment of the present application is a multiple linear regression model.

[0090] In step S103 of some embodiments, the risk factors are input into a preset evaluation model for quantitative evaluation. Specifically, the evaluation model in the embodiments of the present application uses risk factors as variables, trains the evaluation model through risk factors, adjusts model parameters, and then evaluates the impact of different features on model performance. The most influential feature is selected and the evaluation model is trained based on the feature. Thereafter, the risk factors are input into the trained evaluation model, the impact of each risk factor on the claims ratio is evaluated, and the policy claims ratio is output, thereby identifying and quantifying key risk factors, providing a basis for risk management, providing more personalized insurance services, and meeting the risk management needs of different users.

[0091] Step S104: determining the insurance impact value based on the policy claim ratio and historical policy data.

[0092] It should be noted that the insurance impact value is used to represent the degree of influence of the policy information on the insurance company corresponding to the insurance company information.

[0093] In step S104 of some embodiments, the insurance impact value is determined based on the policy claim ratio and historical policy data, so that the degree of impact of the policy on the insurance company corresponding to the insurance company information can be determined through the insurance impact value, and the benefits and risks of the policy can be evaluated through the insurance impact value.

[0094] Step S105 : setting a risk level table according to the insurance impact value, wherein the risk level table includes multiple risk intervals, and each risk interval is set with a risk amount threshold.

[0095] In step S105 of some embodiments, a risk level table is set according to the insurance impact value, which can divide the risk interval into different risk levels, facilitating the subsequent formulation of insurance policies.

[0096] Step S106: Input the insurance data to be evaluated and the environmental factor information into the evaluation model to perform risk evaluation and output the risk evaluation result.

[0097] In step S106 of some embodiments, the insurance data to be evaluated and the environmental factor information are input into the evaluation model for risk assessment, so that the evaluation model can consider multiple factors to perform risk assessment on the insurance data to be evaluated, for example, considering factors such as the value of the property, geographical location, nature of use, and past loss records. By comprehensively considering multiple factors such as property value, geographical location, nature of use, and past loss records, the evaluation model can provide more comprehensive evaluation results, which can better reflect the actual risk status of the insured object, thereby improving the accuracy of risk assessment and the reliability of prediction.

[0098] Step S107: determining a target risk interval corresponding to the risk assessment result in the risk level table, and determining a target risk amount threshold corresponding to the target risk interval.

[0099] In step S107 of some embodiments, after determining the risk assessment result, the embodiments of the present application need to determine the risk level of the risk assessment result. Specifically, the target risk interval corresponding to the risk assessment result is determined in the risk level table, and the target risk amount threshold corresponding to the target risk interval is determined. This can determine the risk level of the risk assessment result and the maximum tolerance amount in the target risk interval corresponding to the risk level, so as to facilitate the subsequent determination of the appropriate insurance amount, and further generate a reasonable insurance policy to avoid the situation where the insurance amount of the insured property is inconsistent with its corresponding risk interval.

[0100] Step S108: Generate a target insurance policy based on the target risk amount threshold, insurance company information, and user demand information.

[0101] In step S108 of some embodiments, a target insurance policy is generated based on the target risk amount threshold, insurance company information, and user demand information. The insurance policy can be adjusted and optimized based on customer needs and feedback, and the target insurance policy can be personalized to improve customer satisfaction and the competitiveness of the insurance business.

[0102] See also Figure 2 In some embodiments, step S102 may also include but is not limited to steps S201 to S203.

[0103] Step S201: Standardize historical policy data to obtain multiple policy fields.

[0104] In step S201 of some embodiments, during the data analysis of historical policy data, since policies for the same insurance product may come from different systems, for example, offline, online, or third-party, different data sources result in incomplete uniformity of the historical policy data. Therefore, the embodiment of the present application first standardizes the historical policy data. Specifically, the integrity of the historical policy data is first checked, and missing values ​​and outliers are processed. After checking the integrity of the historical policy data, all historical policy data are converted into a unified format so that data from different sources can be compared and analyzed under the same standards. The data after format conversion is then subjected to data recognition to identify and divide the fields and records that need to be corrected to obtain multiple policy fields. For each policy field, data correction is performed on the policy field to correct errors in the data, such as spelling errors, format errors, etc., to improve the accuracy of the data. Finally, the policy field after data correction is converted into a unified coding standard to obtain multiple standardized policy fields, thereby ensuring the consistency of the policy fields and improving the accuracy and reliability of the data.

[0105] Understandably, historical policy data is not completely standardized. For example, some address data is accurate to the city, while others only have specific street names without describing the specific city. In this case, it is necessary to standardize the fields with only specific street names. This can be done by querying the street name in the map database to obtain the detailed address. By inputting the detailed address, the standardized address can be obtained.

[0106] Step S202: Perform data association operations on all policy fields through a preset claim settlement system to obtain target policy data.

[0107] In step S202 of some embodiments, in order to obtain all data in the historical policy data, the embodiments of the present application perform data association operations on all policy fields through a preset claims system, thereby determining the associated data and discrete data in the policy fields, and performing corresponding processing on the discrete data to obtain the target policy data, which facilitates the subsequent enhancement of the model processing capabilities, improves the prediction accuracy, and enhances the flexibility of data analysis.

[0108] It should be noted that the claims system in the embodiment of the present application stores multiple claims information, and each claim information is provided with a corresponding field identifier.

[0109] Step S203: Select parameters of the target policy data based on a preset single variable method to determine risk factors.

[0110] In step S203 of some embodiments, the embodiments of the present application select parameters for the target policy data based on a preset single variable method. Specifically, the data type of the target policy data is determined, multiple data types are selected, one or more variables that may affect the claims ratio are selected, and the variables are determined as risk factors. The risk factors that can be quickly identified provide clear decision support information for the insurance company, which facilitates the subsequent prediction of the claims ratio through risk factors.

[0111] It is understandable that the risk factors of the embodiments of the present application include but are not limited to customer scenarios, work locations, additional conditions, rates, etc., and the embodiments of the present application do not impose specific restrictions.

[0112] See also Figure 3 In some embodiments, step S202 may also include but is not limited to steps S301 to S305.

[0113] Step S301: Perform data association operations on all policy fields through a preset claim settlement system to obtain associated data and discrete data.

[0114] In step S301 of some embodiments, in the process of performing data association operations on all policy fields, the embodiments of the present application perform data association operations on all policy fields through a preset claims system. Specifically, the claim fields in the claims system are matched with the policy fields, the common fields between the policy fields and the claims system are found, the associated fields between the two are determined, and then an SQL query statement is written, using the JOIN clause to specify how to associate the two tables. After that, the SQL query statement is run to retrieve and integrate the data, and the retrieved data is used as associated data, that is, the data corresponding to the policy fields exists in the claims system, and the unretrieved data is used as discrete data, that is, the data corresponding to the policy fields does not exist in the claims system, and associated data and discrete data are obtained, so that the relationship between the data can be clarified and the consistency and accuracy of the data can be ensured.

[0115] It is understandable that an insurance policy may have multiple claim data, and multiple claim data are stored in the claim system as an example. The claim data includes but is not limited to claim data, report information, etc. At this time, the preset claim system is used to perform data association operations on all insurance policy fields, and the details of the insurance policy's claim data can be queried.

[0116] Step S302: For each discrete data, create a discrete variable corresponding to the discrete data, and set the original variable value of the discrete variable.

[0117] Step S303: Replace the original variable value of the discrete variable based on a preset transformation rule to obtain a target discrete value.

[0118] Step S304: update the discrete data according to the target discrete value, and generate the insurance policy data according to the updated discrete data and the associated data.

[0119] In steps S303 to S304 of some embodiments, in the process of processing discrete data, for each discrete data, a discrete variable corresponding to the discrete data is created, and the original variable value of the discrete variable is set, so that the meaning represented by them can be reflected by setting the original variable value, such as "social security participation", "labor dispatch", "this city", and "this province". The original variable value of the discrete variable is then replaced based on the preset conversion rule to obtain the target discrete value. Specifically, the embodiment of the present application traverses each row of the discrete data, checks the original variable value of the discrete variable to be converted, and then replaces the original variable value with 1 and 0 according to the designed rules. After that, the discrete data is updated according to the target discrete value, and the converted target discrete value is integrated back into the original discrete data. The insurance policy data is generated based on the updated discrete data and the associated data, which facilitates the subsequent enhancement of the model processing capability, improves the prediction accuracy, and enhances the flexibility of data analysis.

[0120] It should be noted that the serialized data in the embodiment of the present application can express the original state more finely. For example, the location of work can be divided into "whether it is in this city" and "whether it is in this province", which can more accurately capture the differences between individuals.

[0121] It is understandable that the conversion rules in the embodiments of the present application can be set according to the needs of the user. For example, for binary categorical variables, such as "yes / no", "yes / no", etc., they can be directly converted into 1 and 0; for multi-category variables, one-hot encoding or label encoding, etc. can be used. The embodiments of the present application do not make specific restrictions.

[0122] Step S305: clean the policy data to obtain target policy data.

[0123] In step S305 of some embodiments, the policy data is cleaned up. Specifically, the policy data is checked for errors, duplications or inconsistencies, and duplicate records are deleted and erroneous values ​​are repaired, thereby cleaning up some invalid data, improving the accuracy and consistency of the data, and ensuring the reliability of the analysis results. In addition, the embodiments of the present application will also take appropriate methods to process blank or missing fields in the policy data, such as deletion, filling or interpolation, so as to reduce the incompleteness of the data, obtain the target policy data, and thus improve the quality of the target policy data.

[0124] See also Figure 4 In some embodiments, step S104 may also include but is not limited to steps S401 to S404.

[0125] It should be noted that insurance company information includes operating cost information and the company's total policy premiums. The operating cost information is used to represent the operating conditions of the insurance company, and the company's total policy premiums are the total premiums of all the company's policies.

[0126] Step S401: Determine the policy premium of the insurance policy corresponding to the insurance policy information based on the insurance policy information.

[0127] Step S402: determining the company loss ratio of the insurance company corresponding to the insurance company information based on the operating cost information.

[0128] Step S403: Determine the policy impact value based on the policy claim ratio, the company claim ratio, and the policy premium.

[0129] Step S404: Calculate the ratio of the policy impact value to the company's total policy premium to determine the insurance impact value.

[0130] In steps S401 to S404 of some embodiments, in the process of determining the insurance impact value based on the policy claims ratio and historical policy data, the embodiment of the present application first determines the policy premium of the policy corresponding to the policy information based on the policy information, that is, the policy premium of a single policy, and then determines the company claims ratio of the insurance company corresponding to the insurance company information based on the operating cost information, so as to obtain a simple claims ratio of the company's profit. Afterwards, the policy impact value is determined based on the policy claims ratio, the company claims ratio and the policy premium. Specifically, the difference between the policy claims ratio and the company claims ratio is first calculated, and then the difference is multiplied by the policy premium to obtain the policy impact value. Finally, the ratio of the policy impact value to the company's total policy premium is calculated to determine the insurance impact value, so that the degree of impact of the policy on the insurance company corresponding to the insurance company information can be determined through the insurance impact value, and the benefits and risks of the policy can be evaluated through the insurance impact value.

[0131] It should be noted that the company's claims ratio is used to represent the minimum claims ratio required for user liability insurance to make a profit under the current operating conditions of the insurance company. For example, the premium of a policy is 100 yuan, and the various costs required for the insurance company's operation (marketing expenses, employee wages, workplace rent, etc.) allocated to this policy are 48 yuan. It can be seen that the simple claims ratio of the institution's profit is 52%.

[0132] It is understandable that the larger the policy premium and the higher the compensation ratio, the greater the impact, which further reflects that the lower the quality of the policy, the greater the loss of the insurance company.

[0133] See also Figure 5 In some embodiments, step S105 may also include but is not limited to steps S501 to S503.

[0134] Step S501: When the insurance impact value is greater than a first preset impact value, a first risk interval is generated according to the first preset impact value, and a first amount is determined as a risk amount threshold of the first risk interval.

[0135] Step S502: When the insurance impact value is greater than the second preset impact value and less than or equal to the first preset impact value, a second risk interval is generated according to the first preset impact value and the second preset impact value, and the second amount is determined as the risk amount threshold of the second risk interval.

[0136] Step S503: When the insurance impact value is less than or equal to the second preset impact value, a third risk interval is generated according to the second preset impact value, and the third amount is determined as the risk amount threshold of the third risk interval.

[0137] It should be noted that the first preset impact value is greater than the second preset impact value, and the first amount, the second amount and the third amount decrease in sequence.

[0138] In steps S501 to S503 of some embodiments, in the process of setting the risk level table according to the insurance impact value, the embodiment of the present application will compare the insurance impact value with different preset impact values. When the insurance impact value is greater than the first preset impact value, a first risk interval is generated according to the first preset impact value, that is, the value greater than the first preset impact value is determined as the value of the first risk interval, and the first amount is determined as the risk amount threshold of the first risk interval, that is, the maximum insurance amount that the first risk interval can bear; when the insurance impact value is greater than the second preset impact value and is less than or equal to the first preset impact value, a second risk interval is generated according to the first preset impact value and the second preset impact value. , wherein the first preset impact value and the second preset impact value are respectively the two endpoints of the second risk interval, and the second amount is determined as the risk amount threshold of the second risk interval, that is, the maximum insurance amount that the second risk interval can bear; when the insurance impact value is less than or equal to the second preset impact value, a third risk interval is generated according to the second preset impact value, that is, the value less than the second preset impact value is determined as the data of the third risk interval, and the third amount is determined as the risk amount threshold of the third risk interval, that is, the maximum insurance amount that the third risk interval can bear, thereby realizing the division of different risk intervals, and being able to divide the risk intervals into different risk levels, which is convenient for the subsequent formulation of insurance strategies.

[0139] It is worth noting that in the embodiment of the present application, the first preset impact value is greater than the second preset impact value, and the first amount, the second amount and the third amount decrease in sequence. Specifically, the embodiment of the present application takes the first preset impact value of 0.1% and the second preset impact value of -0.1% as an example to illustrate, and the interval greater than 0.1% is determined as the first risk interval, the interval between -0.1% and 0.1% is determined as the second risk interval, and the interval less than -0.1% is determined as the third risk interval. The first risk interval is set to a high risk interval, the second risk interval is set to a medium risk interval, and the third risk interval is set to a low risk interval.

[0140] It is understandable that for insurance impact values ​​in the high-risk range, the embodiments of the present application will provide more comprehensive and high-value protection, such as adding supplementary insurance, increasing compensation amounts, etc. For insurance impact values ​​in the low-risk range, a relatively simple and economical insurance plan can be provided.

[0141] See also Figure 6 In some embodiments, step S108 may also include but is not limited to steps S601 to S603.

[0142] It should be noted that insurance company information includes insurance premium rates.

[0143] Step S601: Determine interval rules corresponding to the target risk interval based on insurance company information.

[0144] It should be noted that the interval rules are rules that limit the application scenarios of the property to be insured.

[0145] In step S601 of some embodiments, in the process of generating a target insurance policy based on the target risk amount threshold, insurance company information and user demand information, different risk intervals in the embodiments of the present application are configured with different interval rules, so the interval rules corresponding to the target risk interval are first determined based on the insurance company information, so as to facilitate the subsequent setting of different insurance policies according to the interval rules.

[0146] It is understandable that the embodiments of the present application will design corresponding interval rules for different risk levels, wherein the interval rules include core terms such as coverage items, deductibles, and compensation ratios.

[0147] Step S602: Determine the intended insurance amount, insurance period, and compensation amount of the property to be insured based on the user's demand information.

[0148] In step S602 of some embodiments, the intended insured amount, insurance period and compensation amount of the property to be insured are determined based on the user demand information, so that the amount of insurance the user wants to insure for the property to be insured can be determined through the intended insured amount, the number of years the user wants to insure the property to be insured can be determined through the insurance period, and the amount of compensation for the property to be insured can be determined through the compensation amount, so that the user needs can be clearly determined, which facilitates the subsequent formulation of different insurance strategies based on the user needs.

[0149] It is worth noting that user demand information also includes user's special demand information, such as emergency rescue, property repair assistance, legal advice, etc.

[0150] Step S603: When the intended insurance amount is less than or equal to the target risk amount threshold, and the insurance period and compensation amount meet the interval rule, a target insurance policy is generated based on the insurance premium rate, intended insurance amount, insurance period and compensation amount.

[0151] In step S603 of some embodiments, when the intended insurance amount is less than or equal to the target risk amount threshold, it means that the amount the user wants to insure is within the target risk amount threshold, meets the maximum amount that the risk level of the target risk interval can bear, and the insurance period and compensation amount meet the interval rules, which means that the insurance period and compensation amount meet the restriction requirements of the interval rules. At this time, the target insurance policy can be directly generated based on the insurance premium rate, intended insurance amount, insurance period and compensation amount, and the insurance policy can be adjusted and optimized according to customer needs and feedback, so that the target insurance policy can be personalized and generated while meeting user requirements, thereby improving customer satisfaction and the competitiveness of the insurance business.

[0152] It is worth noting that in the process of generating a target insurance policy based on insurance premiums, intended insured amounts, insurance periods, and compensation amounts, the embodiment of the present application can also obtain special demand information from user demand information, and then customize personalized terms based on the special demand information, such as special deductible agreements, value-added service terms, etc., to meet the specific requirements of customers.

[0153] See also Figure 7 , Figure 7 is a flowchart of a strategy customization method based on an evaluation model provided by another embodiment of the present application. Figure 7 The method may include but is not limited to step S701.

[0154] Step S701: When the intended insurance amount is greater than the target risk amount threshold, the insurance period does not meet the interval rules, or the compensation amount does not meet the interval rules, a target insurance policy is generated based on the target risk amount threshold, the insurance premium rate, and the interval rules.

[0155] In step S701 of some embodiments, when the intended insurance amount exceeds the target risk amount threshold, that is, the intended insurance amount exceeds the maximum amount that the risk level of the target risk interval can bear, the insurance period exceeds the preset insurance period in the interval rule, or the compensation amount exceeds the preset compensation amount in the interval rule, it means that the current user needs are difficult to meet or there is a risk, and it is necessary to generate a target insurance policy based on the target risk amount threshold, insurance premium rate and interval rules to ensure that the insurance amount can fully cover possible losses and will not be too high to cause excessive premium burden, thereby improving the flexibility of policy generation, further improving user satisfaction, and reducing claims costs and risks.

[0156] See also Figure 8 The embodiment of the present application further provides a policy customization device based on an evaluation model, the device comprising:

[0157] Data acquisition module 801 is used to acquire insurance data to be evaluated and user demand information, and acquire environmental factor information of the insured property corresponding to the insurance data to be evaluated and historical policy data of the insured property, wherein the historical policy data includes policy information and insurance company information;

[0158] Data analysis module 802, used to analyze historical policy data and determine risk factors;

[0159] The quantitative assessment module 803 is used to input the risk factors into a preset assessment model for quantitative assessment and output the policy loss ratio, wherein the policy loss ratio is used to represent the profit and loss situation of the policy corresponding to the policy information;

[0160] An impact value determination module 804 is configured to determine an insurance impact value based on the policy claim ratio and historical policy data, wherein the insurance impact value is used to represent the degree of impact of the policy information on the insurance company corresponding to the insurance company information;

[0161] The risk level table setting module 805 is used to set a risk level table according to the insurance impact value, wherein the risk level table includes multiple risk intervals, and each risk interval is set with a risk amount threshold;

[0162] The risk assessment module 806 is used to input the insurance data to be assessed and the environmental factor information into the assessment model to perform risk assessment and output the risk assessment results;

[0163] The risk determination module 807 is used to determine the target risk interval corresponding to the risk assessment result in the risk level table, and determine the target risk amount threshold corresponding to the target risk interval;

[0164] The policy generation module 808 is used to generate a target insurance policy based on the target risk amount threshold, insurance company information and user demand information.

[0165] The specific implementation of the policy customization device based on the evaluation model is basically the same as the specific embodiment of the policy customization method based on the evaluation model described above, and will not be repeated here.

[0166] An embodiment of the present application further provides an electronic device comprising: a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for enabling communication between the processor and the memory. When the program is executed by the processor, the aforementioned evaluation model-based policy customization method is implemented. The electronic device can be any intelligent terminal, including a tablet computer and an in-vehicle computer.

[0167] See also Figure 9 , Figure 9 The hardware structure of an electronic device according to another embodiment is shown. The electronic device includes:

[0168] The processor 901 may be implemented as a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is configured to execute relevant programs to implement the technical solutions provided in the embodiments of the present application.

[0169] The memory 902 can 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 902 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 902 and is called by the processor 901 to execute the policy customization method based on the evaluation model in the embodiments of this application.

[0170] Input / output interface 903, used to implement information input and output;

[0171] Communication interface 904, used to implement communication interaction between this device and other devices, which can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WiFi, Bluetooth, etc.);

[0172] Bus 905 , which transmits information between various components of the device (e.g., processor 901 , memory 902 , input / output interface 903 , and communication interface 904 );

[0173] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0174] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned policy customization method based on the evaluation model is implemented.

[0175] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely arranged relative to the processor, and these remote memories may be connected to the processor via a network. Examples 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.

[0176] The embodiment of the present application provides a policy customization method, device, electronic device and storage medium based on an evaluation model. First, the insurance data to be evaluated and user demand information are obtained, and the environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and the historical policy data of the property to be insured are obtained, so as to facilitate the subsequent judgment of the physical environment in which the property to be insured is located and the factors that may cause risks to the property to be insured. Then, data analysis is performed on the historical policy data. The risk factors affecting the property to be insured are analyzed through the historical policy data to determine the risk factors, so as to facilitate the subsequent analysis of the compensation situation under different risk factors. The risk factors are input into a preset evaluation model for quantitative evaluation, and the various risks faced by the property to be insured are evaluated. The policy payout ratio is output, so as to obtain the profit and loss situation of the policy corresponding to the policy information under different risk factors, so as to facilitate the subsequent risk evaluation of the insurance product. Afterwards, the insurance impact value is determined according to the policy payout ratio and the historical insurance data, so as to determine the degree of influence of the policy information on the insurance company corresponding to the insurance company information, so as to be able to By combining other historical insurance data to analyze the impact of policy information, it is possible to accurately analyze the impact of policy information on insurance companies, improve the accuracy of policy analysis, and then set a risk level table based on the insurance impact value, thereby dividing multiple risk intervals and achieving accurate division of risks of different levels. Finally, the insurance data to be evaluated and the environmental factor information are input into the evaluation model for risk assessment, and the risk assessment results are output. It is possible to accurately assess the risk level of a specific type of insurance, achieve accurate assessment of the insurance data to be evaluated, and improve the accuracy and efficiency of property insurance assessment. The target risk interval corresponding to the risk assessment result is determined in the risk level table, which can accurately determine the risk level of the property to be insured, and determine the target risk amount threshold corresponding to the target risk interval, so that the maximum amount threshold that the property to be insured can bear can be determined based on the risk assessment result, and then the target insurance strategy is generated based on the target risk amount threshold, insurance company information and user demand information, so that different insurance strategies can be personalized according to user needs to improve user satisfaction.

[0177] The embodiments described in the embodiments of this application are intended to more clearly illustrate the technical solutions of the embodiments of this application and do not constitute a limitation on the technical solutions provided by the embodiments of this 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 this application are also applicable to similar technical problems.

[0178] It will be understood by those skilled in the art that Figure 1-9 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 those shown in the figures, or a combination of certain steps, or different steps.

[0179] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, i.e., they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of this embodiment.

[0180] Those skilled in the art will appreciate that all or some of the steps in the methods, systems, and functional modules / units in the devices disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0181] 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 sequential order. 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 variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes 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.

[0182] It should be understood that in this 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 previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items 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.

[0183] In the several embodiments provided in this 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 merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, 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.

[0184] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0185] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0186] 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, 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, which is stored in a storage medium and includes multiple instructions for enabling a computer 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: various media that can store programs, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0187] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but are not intended to limit the scope of the present invention. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and essence of the present invention should be within the scope of the present invention.

Claims

1. A strategy customization method based on an evaluation model, characterized in that: The method comprises: Obtaining insurance data to be evaluated and user demand information, and obtaining environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and historical policy data of the property to be insured, wherein the historical policy data includes policy information and insurance company information, and the environmental factor information is used to represent information on risk factors affecting the property to be insured; Performing data analysis on the historical policy data to determine risk factors; Input the risk factor into a preset evaluation model for quantitative evaluation, and output a policy loss ratio, wherein the policy loss ratio is used to represent the profit and loss situation of the policy corresponding to the policy information; Determining an insurance impact value based on the policy claim ratio and the historical policy data, wherein the insurance impact value is used to represent the degree of impact of the policy information on the insurance company corresponding to the insurance company information, wherein the insurance company information includes operating cost information and the company's total policy premiums; Setting a risk level table according to the insurance impact value, wherein the risk level table includes a plurality of risk intervals, and each risk interval is set with a risk amount threshold; Inputting the insurance data to be evaluated and the environmental factor information into the evaluation model to perform risk evaluation, and outputting the risk evaluation result; Determining a target risk interval corresponding to the risk assessment result in the risk level table, and determining a target risk amount threshold corresponding to the target risk interval; Generate a target insurance policy based on the target risk amount threshold, the insurance company information, and the user demand information; The determining of the insurance impact value based on the policy claim ratio and the historical policy data includes: Determining, based on the policy information, the policy premium of the policy corresponding to the policy information; Determining the company loss ratio of the insurance company corresponding to the insurance company information based on the operating cost information; Determining a policy impact value based on the policy loss ratio, the company loss ratio, and the policy premium; Calculate the ratio of the policy impact value to the company's total policy premium to determine the insurance impact value; The step of setting a risk level table according to the insurance impact value includes: When the insurance impact value is greater than a first preset impact value, generating a first risk interval according to the first preset impact value, and determining the first amount as a risk amount threshold of the first risk interval; When the insurance impact value is greater than the second preset impact value and less than or equal to the first preset impact value, generating a second risk interval according to the first preset impact value and the second preset impact value, and determining the second amount as the risk amount threshold of the second risk interval; When the insurance impact value is less than or equal to a second preset impact value, generating a third risk interval according to the second preset impact value, and determining the third amount as a risk amount threshold of the third risk interval; The first preset impact value is greater than the second preset impact value, and the first amount, the second amount and the third amount decrease in sequence.

2. The strategy customization method based on the evaluation model according to claim 1, characterized in that: The performing of data analysis on the historical policy data to determine risk factors includes: Standardizing the historical policy data to obtain multiple policy fields; Performing data association operations on all the policy fields through a preset claims system to obtain target policy data; Parameters of the target policy data are selected based on the preset single variable method to determine the risk factors.

3. The strategy customization method based on the evaluation model according to claim 2, characterized in that: The preset claim system performs data association operations on all the policy fields to obtain target policy data, including: Performing data association operations on all the policy fields through a preset claims system to obtain associated data and discrete data; For each discrete data, creating a discrete variable corresponding to the discrete data, and setting an original variable value of the discrete variable; Replacing the original variable value of the discrete variable based on a preset transformation rule to obtain a target discrete value; updating the discrete data according to the target discrete value, and generating policy data according to the updated discrete data and the associated data; The insurance policy data is cleaned to obtain target insurance policy data.

4. The strategy customization method based on the evaluation model according to claim 1, characterized in that: The insurance company information includes insurance premium rates; generating a target insurance policy based on the target risk amount threshold, the insurance company information, and the user demand information includes: Determining interval rules corresponding to the target risk interval based on the insurance company information, wherein the interval rules are rules that restrict application scenarios of the property to be insured; Determining the intended insurance amount, insurance period, and compensation amount of the property to be insured based on the user demand information; When the intended insurance amount is less than or equal to the target risk amount threshold, and the insurance period and the compensation amount meet the interval rule, a target insurance policy is generated based on the insurance premium rate, the intended insurance amount, the insurance period and the compensation amount.

5. The strategy customization method based on the evaluation model according to claim 4, characterized in that: After determining the intended insurance amount, insurance period, and compensation amount of the property to be insured according to the user demand information, the method further includes: When the intended insurance amount is greater than the target risk amount threshold, the insurance period does not comply with the interval rule, or the compensation amount does not comply with the interval rule, a target insurance policy is generated based on the target risk amount threshold, the insurance premium rate, and the interval rule.

6. A strategy customization device based on an evaluation model, characterized in that: The device comprises: A data acquisition module, configured to acquire insurance data to be evaluated and user demand information, and to acquire environmental factor information of the property to be insured corresponding to the insurance data to be evaluated and historical policy data of the property to be insured, wherein the historical policy data includes policy information and insurance company information; A data analysis module, configured to analyze the historical policy data and determine risk factors; A quantitative assessment module, configured to input the risk factors into a preset assessment model for quantitative assessment and output a policy loss ratio, wherein the policy loss ratio is used to represent the profit and loss situation of the policy corresponding to the policy information; an impact value determination module, configured to determine an insurance impact value based on the policy claim ratio and the historical policy data, wherein the insurance impact value is used to represent the degree of impact of the policy information on the insurance company corresponding to the insurance company information, wherein the insurance company information includes operating cost information and the company's total policy premiums; A level table setting module is used to set a risk level table according to the insurance impact value, wherein the risk level table includes multiple risk intervals, and each risk interval is set with a risk amount threshold; A risk assessment module, configured to input the insurance data to be assessed and the environmental factor information into the assessment model to perform risk assessment and output a risk assessment result; a risk determination module, configured to determine a target risk interval corresponding to the risk assessment result in the risk level table, and determine a target risk amount threshold corresponding to the target risk interval; A policy generating module, configured to generate a target insurance policy based on the target risk amount threshold, the insurance company information, and the user demand information; The determining of the insurance impact value based on the policy claim ratio and the historical policy data includes: Determining, based on the policy information, the policy premium of the policy corresponding to the policy information; Determining the company loss ratio of the insurance company corresponding to the insurance company information based on the operating cost information; Determining a policy impact value based on the policy loss ratio, the company loss ratio, and the policy premium; Calculate the ratio of the policy impact value to the company's total policy premium to determine the insurance impact value; The step of setting a risk level table according to the insurance impact value includes: When the insurance impact value is greater than a first preset impact value, generating a first risk interval according to the first preset impact value, and determining the first amount as a risk amount threshold of the first risk interval; When the insurance impact value is greater than the second preset impact value and less than or equal to the first preset impact value, generating a second risk interval according to the first preset impact value and the second preset impact value, and determining the second amount as the risk amount threshold of the second risk interval; When the insurance impact value is less than or equal to a second preset impact value, generating a third risk interval according to the second preset impact value, and determining the third amount as a risk amount threshold of the third risk interval; The first preset impact value is greater than the second preset impact value, and the first amount, the second amount and the third amount decrease in sequence.

7. An electronic device, characterized in that: The electronic device includes a memory and a processor, the memory stores a computer program, and the processor implements the policy customization method based on the evaluation model according to any one of claims 1 to 5 when executing the computer program.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the policy customization method based on the evaluation model according to any one of claims 1 to 5 is implemented.

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