Port safety production responsibility insurance information verification method based on safety risk

Abstract

The invention discloses a port safety production responsibility insurance information verification method based on safety risks, and relates to the technical field of data verification. The method comprises the following steps: comprehensively evaluating the authenticity evaluation coefficient of the port safety production liability insurance information and the accuracy evaluation coefficient of the port safety production liability insurance information to obtain the verification evaluation coefficient of the port safety production liability insurance information; and according to difference matching between the authenticity evaluation coefficient of the port safety production liability insurance information and the authenticity evaluation threshold value of the port safety production liability insurance information, obtaining a preliminary optimization measure for the authenticity of the port safety production liability insurance information. According to the invention, the verification of the insurance policy information is deeply optimized according to the threshold comparison result, the effect of improving the supervision efficiency of the insurance market is achieved, and the problem of insufficient supervision efficiency of the insurance market in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of data verification, and in particular to a method for verifying information of port production safety liability insurance based on safety risks. Background Art

[0002] With the rapid advancement of information technology, there are many types of insurance. Due to the dangerous working environment of ports, insurance products targeting specific risks of ports have been established. The existing port production safety liability insurance information verification method relies on risk assessment models, data mining and analysis, identity authentication, electronic signatures and cloud services and other advanced technologies. It improves the accuracy and efficiency of insurance information verification through intelligent means, and ensures the authenticity and validity of port production safety liability insurance data.

[0003] For example, the property insurance information verification method, device, equipment and storage medium announced by the invention patent with announcement number: CN118037461B include: obtaining the insurance request uploaded by the service terminal, extracting the insurance information in the insurance request; determining the target insurance risk model and the target insurance risk association characteristics based on the insured property type and insurance risk association information in the insurance information; calling the insurance claim database, extracting the historical insurance risk association characteristics in the claim policy using the target insurance risk model, adjusting the risk redundancy of the target insurance risk model, and obtaining the final insurance risk model; inputting the target insurance risk association characteristics into the final insurance risk model, generating a verification result and sending it to the service terminal.

[0004] For example, the invention patent with publication number: CN119107188A discloses a method and system for verifying data submitted for regulatory reporting in the insurance industry, including: using records of a customer subject table, records of an underwriting subject table, and records of a payment and collection subject table in a relational database as nodes respectively, using the underwriting relationship between the customer subject table and the underwriting subject table in the relational database, and the payment and collection record relationship between the payment and collection subject table and the underwriting subject in the relational database as the first association relationship between the nodes respectively, to establish a graph database for regulatory reporting data in the insurance industry; verifying the graph database composed of the regulatory reporting data in the insurance industry according to preset verification rules and the core business database of the insurance company, marking risk nodes, and if a node is marked as a risk node, the insurance industry regulatory reporting data involved in the node will fail the verification.

[0005] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the prior art, when port production safety liability insurance is paid, due to the lack of an insurance information verification system, the verification of insurance beneficiaries, insured persons and policy information is not accurate enough, and there may be a problem of insufficient supervision efficiency in the insurance market. Summary of the invention

[0006] The embodiment of the present application solves the problem of insufficient supervision efficiency of the insurance market in the prior art by providing a port production safety liability insurance information verification method based on safety risks, thereby achieving the effect of improving the supervision efficiency of the insurance market.

[0007] The embodiment of the present application provides a method for verifying port production safety liability insurance information based on safety risk, comprising the following steps: collecting authenticity-related data of port production safety liability insurance information and accuracy-related data of port production safety liability insurance information, preprocessing the authenticity-related data of port production safety liability insurance information and accuracy-related data of port production safety liability insurance information to obtain authenticity-related data of preprocessed port production safety liability insurance information and accuracy-related data of preprocessed port production safety liability insurance information; analyzing the authenticity-related data of preprocessed port production safety liability insurance information to obtain an authenticity assessment coefficient of the port production safety liability insurance information, analyzing the accuracy-related data of preprocessed port production safety liability insurance information to obtain an accuracy assessment coefficient of the port production safety liability insurance information, and A comprehensive assessment is made on the authenticity assessment coefficient of the production liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information to obtain the verification assessment coefficient of the port production safety liability insurance information; the authenticity assessment threshold of the port production safety liability insurance information and the verification assessment threshold of the port production safety liability insurance information are obtained from the database, the authenticity assessment coefficient of the port production safety liability insurance information is subtracted from the authenticity assessment threshold of the port production safety liability insurance information, and preliminary optimization measures for the authenticity of the port production safety liability insurance information are obtained by matching the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information, the verification assessment coefficient of the port production safety liability insurance information is compared with the verification assessment threshold of the port production safety liability insurance information, and the verification of the policy information is deeply optimized according to the threshold comparison results.

[0008] Furthermore, the data related to the authenticity of the port production safety liability insurance information and the data related to the accuracy of the port production safety liability insurance information include: the data related to the authenticity of the port production safety liability insurance information include: the average data matching rate of multiple basic information of the insurance policy, the document consistency ratio and the historical claims frequency; the data related to the accuracy of the port production safety liability insurance information include: the data verification pass rate, the document consistency ratio, the historical error rate of information entry and the verification rate of the insured object.

[0009] Furthermore, the specific preprocessing process for preprocessing the authenticity-related data of port production safety liability insurance information and the accuracy-related data of port production safety liability insurance information is as follows: preprocessing includes data cleaning, data conversion and feature extraction; data cleaning includes filling missing values, deleting outliers and duplicate values; data conversion: normalizing the authenticity-related data of port production safety liability insurance information and the accuracy-related data of port production safety liability insurance information; feature extraction: using the principal component analysis method to perform feature processing on the authenticity-related data of port production safety liability insurance information and the accuracy-related data of port production safety liability insurance information.

[0010] Furthermore, the specific analysis process for analyzing the authenticity-related data of the pre-processed port production safety liability insurance information is as follows: a comprehensive analysis is conducted on the average data matching rate of multiple basic information of the policy, the document consistency rate and the historical claims frequency, and the average data matching rate of multiple basic information of the policy of the port production safety liability insurance information, the document consistency rate of the port production safety liability insurance information and the historical claims frequency of multiple basic information of the policy of the port production safety liability insurance information are multiplied by their corresponding weights and processed to obtain the authenticity assessment coefficient of the port production safety liability insurance information.

[0011] Furthermore, the specific analysis process for analyzing the accuracy-related data of the pre-processed port production safety liability insurance information is as follows: a comprehensive analysis is conducted on the data verification pass rate, the document consistency rate, the historical error rate of information entry and the insurance subject verification rate of the port production safety liability insurance information, and the data verification pass rate of the port production safety liability insurance information, the document consistency rate of the port production safety liability insurance information, the historical error rate of information entry of the port production safety liability insurance information and the insurance subject verification rate of the port production safety liability insurance information are multiplied by their corresponding weights and processed to obtain the accuracy assessment coefficient of the port production safety liability insurance information.

[0012] Furthermore, the specific process of subtracting the authenticity assessment coefficient of the port production safety liability insurance information from the authenticity assessment threshold of the port production safety liability insurance information is: obtaining the authenticity assessment threshold of the port production safety liability insurance information from the database, subtracting the authenticity assessment coefficient of the port production safety liability insurance information from the authenticity assessment threshold of the port production safety liability insurance information, and obtaining the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information.

[0013] Furthermore, according to the difference matching between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information, the specific matching process for obtaining preliminary optimization measures for the authenticity of the port production safety liability insurance information is as follows: comparing the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information with a preset tolerance range; if the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is within the tolerance range, marking the port production safety liability insurance information as having passed the authenticity test; if the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is outside the tolerance range, taking preliminary optimization measures for the port production safety liability insurance information; the preliminary optimization measures include data verification, risk assessment level correction and policy information correction.

[0014] Furthermore, the specific comparison process of comparing the verification and evaluation coefficient of the port production safety liability insurance information with the verification and evaluation threshold of the port production safety liability insurance information is: obtaining the verification and evaluation threshold of the port production safety liability insurance information from the database, comparing the verification and evaluation coefficient of the port production safety liability insurance information with the verification and evaluation threshold of the port production safety liability insurance information; if the verification and evaluation coefficient of the port production safety liability insurance information is greater than or equal to the verification and evaluation threshold of the port production safety liability insurance information, marking the port production safety liability insurance information as passed the verification; if the verification and evaluation coefficient of the port production safety liability insurance information is less than the verification and evaluation threshold of the port production safety liability insurance information, performing deep optimization on the port production safety liability insurance information; deep optimization includes establishing a prediction model and predicting insurance fraud.

[0015] Furthermore, the specific process of establishing the prediction model is as follows: obtaining the recurrent neural network model from the database, determining the number of layers of the recurrent neural network, the number of neurons in each layer and the activation function, dividing the authenticity-related data of the preprocessed port production safety liability insurance information and the accuracy-related data of the preprocessed port production safety liability insurance information into a training set and a test set according to a certain ratio, inputting the training set into the recurrent neural network for training to obtain a preliminary prediction model, using the test set to evaluate the performance of the preliminary prediction model, and obtaining the prediction model by adjusting the hyperparameters and the model structure.

[0016] Furthermore, the specific method for obtaining the verification and evaluation coefficient of port production safety liability insurance information is as follows: ; In the formula, It is expressed as the verification and evaluation coefficient of port production safety liability insurance information, It is expressed as the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the weight factor of the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the accuracy assessment coefficient of port production safety liability insurance information, It is expressed as the weight factor of the accuracy assessment coefficient of port production safety liability insurance information.

[0017] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By comparing the verification and evaluation coefficient of port production safety liability insurance information with the verification and evaluation threshold of port production safety liability insurance information, the verification of policy information is deeply optimized according to the threshold comparison result, thereby achieving the effect of improving the supervision efficiency of the insurance market and effectively solving the problem of insufficient supervision efficiency of the insurance market in the existing technology.

[0018] 2. By comprehensively evaluating the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information, the verification assessment coefficient of the port production safety liability insurance information is obtained, thereby achieving the effect of optimizing the allocation of insurance resources in the insurance market, and effectively solving the problem of insufficient allocation of insurance resources in the insurance market in the existing technology.

[0019] 3. By subtracting the authenticity assessment coefficient of the port production safety liability insurance information from the authenticity assessment threshold of the port production safety liability insurance information, preliminary optimization measures for the authenticity of the port production safety liability insurance information are obtained according to the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information, thereby achieving the effect of quantifying risk assessment, and effectively solving the problem in the existing technology that the risk assessment of the insurance market cannot be quantified. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flow chart of a method for verifying port production safety liability insurance information based on safety risks provided in an embodiment of the present application; Figure 2 An image of the authenticity assessment coefficient of port production safety liability insurance information in a port production safety liability insurance information verification method based on safety risk provided in an embodiment of the present application. DETAILED DESCRIPTION

[0021] The embodiment of the present application solves the problem of insufficient supervision efficiency of the insurance market in the prior art by providing a method for verifying port production safety liability insurance information based on safety risks. By comparing the verification evaluation coefficient of port production safety liability insurance information with the verification evaluation threshold of port production safety liability insurance information, the verification of policy information is deeply optimized according to the threshold comparison result, thereby achieving the effect of improving the supervision efficiency of the insurance market.

[0022] The technical solution in the embodiment of the present application is to solve the above-mentioned problem of insufficient supervision efficiency in the insurance market. The overall idea is as follows: By analyzing the authenticity-related data of the pre-processed port production safety liability insurance information, the authenticity assessment coefficient of the port production safety liability insurance information is obtained; by analyzing the accuracy-related data of the pre-processed port production safety liability insurance information, the accuracy assessment coefficient of the port production safety liability insurance information is obtained; a comprehensive assessment is made on the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information to obtain the verification assessment coefficient of the port production safety liability insurance information; the verification assessment coefficient of the port production safety liability insurance information is compared with the verification assessment threshold of the port production safety liability insurance information; and the verification of the policy information is deeply optimized according to the threshold comparison result, thereby achieving the effect of improving the regulatory efficiency of the insurance market.

[0023] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0024] like Figure 1As shown, it is a flow chart of a method for verifying port production safety liability insurance information based on safety risk provided in an embodiment of the present application, the method comprising the following steps: collecting authenticity-related data of port production safety liability insurance information and accuracy-related data of port production safety liability insurance information, preprocessing the authenticity-related data of port production safety liability insurance information and accuracy-related data of port production safety liability insurance information to obtain authenticity-related data of preprocessed port production safety liability insurance information and accuracy-related data of preprocessed port production safety liability insurance information; analyzing the authenticity-related data of preprocessed port production safety liability insurance information to obtain an authenticity assessment coefficient of port production safety liability insurance information, analyzing the accuracy-related data of preprocessed port production safety liability insurance information to obtain an accuracy assessment coefficient of port production safety liability insurance information, A comprehensive assessment is made on the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information to obtain the verification assessment coefficient of the port production safety liability insurance information; the authenticity assessment threshold of the port production safety liability insurance information and the verification assessment threshold of the port production safety liability insurance information are obtained from the database, the authenticity assessment coefficient of the port production safety liability insurance information is subtracted from the authenticity assessment threshold of the port production safety liability insurance information, and preliminary optimization measures for the authenticity of the port production safety liability insurance information are obtained by matching the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information, the verification assessment coefficient of the port production safety liability insurance information is compared with the verification assessment threshold of the port production safety liability insurance information, and the verification of the policy information is deeply optimized according to the threshold comparison results.

[0025] Furthermore, the data related to the authenticity of the port production safety liability insurance information and the data related to the accuracy of the port production safety liability insurance information include: the data related to the authenticity of the port production safety liability insurance information include: the average data matching rate of multiple basic information of the insurance policy, the document consistency ratio and the historical claims frequency; the data related to the accuracy of the port production safety liability insurance information include: the data verification pass rate, the document consistency ratio, the historical error rate of information entry and the verification rate of the insured object.

[0026] In this embodiment, the average data matching rate of multiple basic information of the insurance policy refers to the average matching degree of each basic information on the insurance policy (such as the name of the insured, the insurance period, the insurance amount, etc.) after comparing with the actual records or official data sources, which can be obtained by comparing with the official database and enterprise registration information and calculating.

[0027] The document consistency ratio refers to the degree of consistency between policy documents (such as electronic policy and paper policy) or between policy documents and related supporting documents, and is calculated by comparing the contents of different documents.

[0028] The historical claims frequency refers to the ratio of the number of insurance accidents to the number of insurance policies within a certain period of time, which can be obtained through the insurance company's claims records.

[0029] The data verification pass rate refers to the proportion of data items that pass the verification to the total data items during the data verification process, which can be calculated through data verification.

[0030] The historical error rate of information entry refers to the proportion of data items that have errors in the past entry process to the total data items, which can be obtained through historical record analysis.

[0031] The verification rate of the subject matter of insurance refers to the degree of consistency between the actual verification of the subject matter of insurance (such as ships, cargoes, etc.) and the insurance policy records, which can be obtained through on-site verification.

[0032] Furthermore, the specific preprocessing process for preprocessing the authenticity-related data of port production safety liability insurance information and the accuracy-related data of port production safety liability insurance information is as follows: preprocessing includes data cleaning, data conversion and feature extraction; data cleaning includes filling missing values, deleting outliers and duplicate values; data conversion: normalizing the authenticity-related data of port production safety liability insurance information and the accuracy-related data of port production safety liability insurance information; feature extraction: using the principal component analysis method to perform feature processing on the authenticity-related data of port production safety liability insurance information and the accuracy-related data of port production safety liability insurance information.

[0033] In this example, there are missing data on policy amounts in 5 samples, and it is decided to use the average value of the feature to fill these missing values. It is found that the policy amounts of 20 samples are much higher than those of other samples. These may be measurement errors, so they are deleted. It is found that the data of 10 samples are completely repeated, so these repeated samples are deleted. Data cleaning ensures the integrity and accuracy of the data set and reduces the impact of noise and errors on the model.

[0034] The specific process of principal component analysis is: standardize the data, calculate the covariance matrix of the data, calculate the eigenvalues ​​and eigenvectors of the covariance matrix, select the principal components, project the original data onto the principal components, and obtain new features.

[0035] Furthermore, the specific analysis process for analyzing the authenticity-related data of the pre-processed port production safety liability insurance information is as follows: a comprehensive analysis is conducted on the average data matching rate of multiple basic information of the policy, the document consistency rate and the historical claims frequency, and the average data matching rate of multiple basic information of the policy of the port production safety liability insurance information, the document consistency rate of the port production safety liability insurance information and the historical claims frequency of multiple basic information of the policy of the port production safety liability insurance information are multiplied by their corresponding weights and processed to obtain the authenticity assessment coefficient of the port production safety liability insurance information.

[0036] In this embodiment, the specific formula for obtaining the authenticity evaluation coefficient of port production safety liability insurance information is: ; ; In the formula, It is expressed as the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the average data matching rate of multiple basic information of insurance policies, Expressed as the document consistency ratio, is the historical claim frequency, It is expressed as the weight factor of the average data matching rate of multiple basic information of the insurance policy. Expressed as a weighting factor for the document consistency ratio, Expressed as the weight factor of historical claim frequency, Expressed as a natural constant.

[0037] In this embodiment, the weight factor of the average data matching rate of multiple basic information of the insurance policy, the weight factor of the document consistency ratio and the weight factor of the historical claims frequency respectively represent the numerical values ​​of the influence of the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information on the verification assessment coefficient of the port production safety liability insurance information.

[0038] When in use, the weight factor of the average data matching rate of multiple basic information of the policy, the weight factor of the document consistency ratio and the weight factor of the historical claims frequency are directly obtained according to the port production safety liability insurance information database, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of the average data matching rate of multiple basic information of the policy, the document consistency ratio and the historical claims frequency and their corresponding weight factors of the average data matching rate of multiple basic information of the policy, the weight factor of the document consistency ratio and the weight factor of the historical claims frequency is constructed through historical data, and the real-time values ​​of the average data matching rate of multiple basic information of the policy, the document consistency ratio and the historical claims frequency are input into the mapping set to obtain the weight factor of the average data matching rate of multiple basic information of the policy, the weight factor of the document consistency ratio and the weight factor of the historical claims frequency, and the mapping relationship can be one-to-one or many-to-one.

[0039] If the average data matching rate is high, it usually means that the information in the insurance policy is highly consistent with the actual business data, which will help improve the document consistency rate. A higher document consistency rate usually means that the insurance documents are more accurate and complete, which helps reduce claims disputes caused by incorrect or incomplete documents, thereby possibly reducing the historical claims frequency. A higher average data matching rate may reduce insurance fraud and erroneous insurance, thereby reducing the risk of claims and thus reducing the historical claims frequency.

[0040] In a specific embodiment, an example of authenticity assessment coefficient data of port production safety liability insurance information is shown in the following table.

[0041] Table 1 Example of data on authenticity assessment coefficients of port production safety liability insurance information

[0042] When the weight factors of the average data matching rate of multiple basic information of the insurance policy, the weight factors of the document consistency ratio, and the weight factors of the historical claims frequency are 0.1, 0.1, and 0.8 respectively, Figure 2 As shown, it is an image of the authenticity evaluation coefficient of the port production safety liability insurance information in the port production safety liability insurance information verification method based on safety risk provided by the embodiment of the present application, through Figure 2 It can be seen from the data in Table 1 that when the document consistency ratio and the historical claims frequency remain unchanged, the greater the average data matching rate of multiple basic information of the insurance policy, the greater the authenticity assessment coefficient of the port production safety liability insurance information.

[0043] Furthermore, the specific analysis process for analyzing the accuracy-related data of the pre-processed port production safety liability insurance information is as follows: a comprehensive analysis is conducted on the data verification pass rate, the document consistency rate, the historical error rate of information entry and the insurance subject verification rate of the port production safety liability insurance information, and the data verification pass rate of the port production safety liability insurance information, the document consistency rate of the port production safety liability insurance information, the historical error rate of information entry of the port production safety liability insurance information and the insurance subject verification rate of the port production safety liability insurance information are multiplied by their corresponding weights and processed to obtain the accuracy assessment coefficient of the port production safety liability insurance information.

[0044] In this embodiment, the specific formula for obtaining the accuracy evaluation coefficient of port production safety liability insurance information is: ; ; In the formula, It is expressed as the accuracy assessment coefficient of port production safety liability insurance information, Expressed as the data verification pass rate, Expressed as the document consistency ratio, Expressed as the historical error rate of information entry, It is expressed as the insurance subject matter verification rate, Expressed as the weight factor of the data verification pass rate, Expressed as a weighting factor for the document consistency ratio, Expressed as a weighting factor for the historical error rate of information entry, Expressed as the weighting factor of the insurance subject matter verification rate.

[0045] The weight factor of data verification pass rate, the weight factor of document consistency ratio, the weight factor of historical error rate of information entry and the weight factor of insurance subject matter verification rate respectively represent the numerical values ​​of the influence of data verification pass rate, document consistency ratio, historical error rate of information entry and insurance subject matter verification rate on the accuracy assessment coefficient of port production safety liability insurance information.

[0046] When in use, the weight factor of the data verification pass rate, the weight factor of the document consistency ratio, the weight factor of the historical error rate of information entry and the weight factor of the insurance subject verification rate are directly obtained according to the port production safety liability insurance information database, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of the data verification pass rate, the document consistency ratio, the historical error rate of information entry and the insurance subject verification rate and their corresponding weight factors of the data verification pass rate, the document consistency ratio, the historical error rate of information entry and the insurance subject verification rate is constructed through historical data, and the real-time data verification pass rate, document consistency ratio, historical error rate of information entry and insurance subject verification rate are input into the mapping set to obtain the weight factor of the data verification pass rate, the weight factor of the document consistency ratio, the historical error rate of information entry and the insurance subject verification rate. The mapping relationship can be one-to-one or many-to-one.

[0047] A high data verification pass rate means that the data in the insurance policy is correct and meets the requirements, which usually leads to an increase in the document consistency rate. A high data verification pass rate usually means that the accuracy of information entry is high, so the historical error rate will be low. A high insurance subject verification rate means that the insurance subject has been effectively verified, which helps to improve the data verification pass rate and document consistency rate.

[0048] Furthermore, the specific process of subtracting the authenticity assessment coefficient of the port production safety liability insurance information from the authenticity assessment threshold of the port production safety liability insurance information is: obtaining the authenticity assessment threshold of the port production safety liability insurance information from the database, subtracting the authenticity assessment coefficient of the port production safety liability insurance information from the authenticity assessment threshold of the port production safety liability insurance information, and obtaining the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information.

[0049] In this embodiment, for example, the authenticity assessment threshold of the port production safety liability insurance information obtained from the database is 0.7, and the calculated authenticity assessment coefficient of the port production safety liability insurance information is 0.8, then the authenticity assessment coefficient of the port production safety liability insurance information is subtracted from the authenticity assessment threshold of the port production safety liability insurance information, and the difference obtained is 0.8-0.7=0.1.

[0050] The authenticity assessment threshold of the port production safety liability insurance information obtained from the database is 0.7, and the calculated authenticity assessment coefficient of the port production safety liability insurance information is 0.5. Then, the authenticity assessment coefficient of the port production safety liability insurance information is subtracted from the authenticity assessment threshold of the port production safety liability insurance information, and the difference is 0.5-0.7=-0.2.

[0051] By calculating the difference, the authenticity assessment results of port production safety liability insurance information can be quantified, which is convenient for risk management and decision-making.

[0052] Furthermore, according to the difference matching between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information, the specific matching process for obtaining preliminary optimization measures for the authenticity of the port production safety liability insurance information is as follows: comparing the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information with a preset tolerance range; if the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is within the tolerance range, marking the port production safety liability insurance information as having passed the authenticity test; if the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is outside the tolerance range, taking preliminary optimization measures for the port production safety liability insurance information; the preliminary optimization measures include data verification, risk assessment level correction and policy information correction.

[0053] In this embodiment, assuming that the tolerance range is set to ±0.05, if the difference is -0.05, within the tolerance range of ±0.05, the insurance information is marked as having passed the authenticity test; if the difference is +0.1, preliminary optimization measures are performed; the preliminary optimization measures include data verification, risk assessment level correction and policy information correction.

[0054] By setting a tolerance range, risks can be effectively controlled to ensure that only insurance information that meets certain authenticity standards can pass the test.

[0055] Data verification refers to comparing the data in the insurance policy with industry standards or historical data. Specifically, through the EDI system, insurance companies and port enterprises can automatically exchange policy information, reducing the possibility of manual input errors. Risk assessment level correction refers to adjusting the risk assessment level according to the verification results. Specifically, through real-time data analysis technology, such as stream processing, immediate response to data changes and adjustment of risk assessment levels. Policy information correction refers to correcting erroneous information found during the verification process. Specifically, it applies data cleaning technology, such as deduplication, correction, completion, etc., to correct erroneous or incomplete data.

[0056] Furthermore, the specific comparison process of comparing the verification and evaluation coefficient of the port production safety liability insurance information with the verification and evaluation threshold of the port production safety liability insurance information is: obtaining the verification and evaluation threshold of the port production safety liability insurance information from the database, comparing the verification and evaluation coefficient of the port production safety liability insurance information with the verification and evaluation threshold of the port production safety liability insurance information; if the verification and evaluation coefficient of the port production safety liability insurance information is greater than or equal to the verification and evaluation threshold of the port production safety liability insurance information, marking the port production safety liability insurance information as passed the verification; if the verification and evaluation coefficient of the port production safety liability insurance information is less than the verification and evaluation threshold of the port production safety liability insurance information, performing deep optimization on the port production safety liability insurance information; deep optimization includes establishing a prediction model and predicting insurance fraud.

[0057] In this embodiment, for example, assuming that the verification evaluation threshold is 0.90, by analyzing the data of the insurance information, the verification evaluation coefficient of the port production safety liability insurance information is calculated to be 0.92, which is greater than the threshold value 0.90, and the insurance information is marked as passed the verification. If, by analyzing the data of the insurance information, the verification evaluation coefficient of the port production safety liability insurance information is calculated to be 0.85, which is less than the threshold value 0.90, deep optimization is performed including establishing a prediction model and predicting insurance fraud.

[0058] By comparing the verification assessment coefficient with the threshold, potential insurance fraud and risks can be quickly identified.

[0059] Furthermore, the specific process of establishing the prediction model is as follows: obtaining the recurrent neural network model from the database, determining the number of layers of the recurrent neural network, the number of neurons in each layer and the activation function, dividing the authenticity-related data of the preprocessed port production safety liability insurance information and the accuracy-related data of the preprocessed port production safety liability insurance information into a training set and a test set according to a certain ratio, inputting the training set into the recurrent neural network for training to obtain a preliminary prediction model, using the test set to evaluate the performance of the preliminary prediction model, and obtaining the prediction model by adjusting the hyperparameters and the model structure.

[0060] In this embodiment, a predefined recurrent neural network model structure is retrieved from a database or model library, a 2-layer long short-term memory network is set, each layer contains 128 neurons, the activation function is ReLU, 70% of the data is randomly extracted from the data set as a training set, and the remaining 30% is used as a test set. The RNN model is trained using the training set data, and the performance of the trained preliminary prediction model is evaluated using the test set to obtain test results. If the model accuracy is lower than 90%, the model structure can be adjusted by increasing the number of layers or the number of neurons to improve the model accuracy. If the model accuracy exceeds 90%, it means that the preliminary prediction model meets the requirements, and the prediction model is obtained. The basic information of the insurance is input to obtain the probability of insurance fraud in the insurance.

[0061] The ReLU function refers to Rectified Linear Unit, and the specific expression is: f(x)=max(0,x).

[0062] Recurrent neural networks can capture long-term dependencies in time series data and improve the accuracy of predictions.

[0063] Furthermore, the specific method for obtaining the verification and evaluation coefficient of port production safety liability insurance information is as follows: ; In the formula, It is expressed as the verification and evaluation coefficient of port production safety liability insurance information, It is expressed as the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the weight factor of the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the accuracy assessment coefficient of port production safety liability insurance information, It is expressed as the weight factor of the accuracy assessment coefficient of port production safety liability insurance information.

[0064] In this embodiment, the weight factor of the authenticity assessment coefficient of the port production safety liability insurance information and the weight factor of the accuracy assessment coefficient of the port production safety liability insurance information respectively represent the numerical values ​​of the influence of the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information on the verification assessment coefficient of the port production safety liability insurance information.

[0065] When in use, the weight factor of the authenticity assessment coefficient of the port production safety liability insurance information and the weight factor of the accuracy assessment coefficient of the port production safety liability insurance information are directly obtained according to the port production safety liability insurance information database, and the corresponding relationship can be a pre-set mapping relationship. For example, a mapping set of the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information and their corresponding weight factors of the authenticity assessment coefficient of the port production safety liability insurance information and the weight factors of the accuracy assessment coefficient of the port production safety liability insurance information are constructed through historical data, and the real-time values ​​of the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information are input into the mapping set to obtain the weight factor of the authenticity assessment coefficient of the port production safety liability insurance information and the weight factor of the accuracy assessment coefficient of the port production safety liability insurance information, and the mapping relationship can be a one-to-one correspondence or a many-to-one relationship.

[0066] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0070] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0071] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for verifying port production safety liability insurance information based on safety risk, characterized in that: The following steps are involved: Collecting data related to the authenticity of port production safety liability insurance information and data related to the accuracy of port production safety liability insurance information, preprocessing the data related to the authenticity of port production safety liability insurance information and data related to the accuracy of port production safety liability insurance information, and obtaining the preprocessed data related to the authenticity of port production safety liability insurance information and data related to the accuracy of port production safety liability insurance information; Analyze the authenticity-related data of the pre-processed port production safety liability insurance information to obtain the authenticity assessment coefficient of the port production safety liability insurance information; analyze the accuracy-related data of the pre-processed port production safety liability insurance information to obtain the accuracy assessment coefficient of the port production safety liability insurance information; conduct a comprehensive assessment on the authenticity assessment coefficient of the port production safety liability insurance information and the accuracy assessment coefficient of the port production safety liability insurance information to obtain the verification assessment coefficient of the port production safety liability insurance information; The authenticity assessment threshold and the verification assessment threshold of the port production safety liability insurance information are obtained from the database, the authenticity assessment coefficient of the port production safety liability insurance information is subtracted from the authenticity assessment threshold of the port production safety liability insurance information, and preliminary optimization measures for the authenticity of the port production safety liability insurance information are obtained by matching the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information. The verification assessment coefficient of the port production safety liability insurance information is compared with the verification assessment threshold of the port production safety liability insurance information, and the verification of the policy information is deeply optimized according to the threshold comparison results.

2. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1 is characterized in that: The data related to the authenticity of the port production safety liability insurance information and the data related to the accuracy of the port production safety liability insurance information include: Data related to the authenticity of port production safety liability insurance information include: average data matching rate of multiple basic information of the policy, document consistency ratio and historical claims frequency; Data related to the accuracy of port production safety liability insurance information include: data verification pass rate, document consistency rate, historical error rate of information entry and insurance subject matter verification rate.

3. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific preprocessing process of preprocessing the authenticity-related data of the port production safety liability insurance information and the accuracy-related data of the port production safety liability insurance information is as follows: Preprocessing includes data cleaning, data transformation, and feature extraction; Data cleaning includes filling missing values, removing outliers and duplicate values; Data conversion: normalize the data related to the authenticity of the port production safety liability insurance information and the data related to the accuracy of the port production safety liability insurance information; Feature extraction: The principal component analysis method is used to perform feature processing on the data related to the authenticity of the port production safety liability insurance information and the data related to the accuracy of the port production safety liability insurance information.

4. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific analysis process of analyzing the authenticity-related data of the pre-processed port production safety liability insurance information is as follows: A comprehensive analysis is conducted on the average data matching rate, document consistency ratio and historical claims frequency of multiple basic information of the insurance policy. The average data matching rate of multiple basic information of the port production safety liability insurance information, the document consistency ratio of the port production safety liability insurance information and the historical claims frequency of multiple basic information of the port production safety liability insurance information are multiplied by their corresponding weights and processed to obtain the authenticity assessment coefficient of the port production safety liability insurance information.

5. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific analysis process of analyzing the accuracy-related data of the pre-processed port production safety liability insurance information is as follows: A comprehensive analysis is conducted on the data verification pass rate, document consistency rate, historical error rate of information entry and insurance subject verification rate of port production safety liability insurance information, and the data verification pass rate of port production safety liability insurance information, the document consistency rate of port production safety liability insurance information, the historical error rate of information entry and the insurance subject verification rate of port production safety liability insurance information are multiplied by their corresponding weights and processed to obtain the accuracy assessment coefficient of port production safety liability insurance information.

6. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific process of subtracting the authenticity assessment coefficient of the port production safety liability insurance information from the authenticity assessment threshold of the port production safety liability insurance information is as follows: The authenticity assessment threshold of the port production safety liability insurance information is obtained from the database, and the authenticity assessment coefficient of the port production safety liability insurance information is subtracted from the authenticity assessment threshold of the port production safety liability insurance information to obtain the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information.

7. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific matching process of obtaining the preliminary optimization measures for the authenticity of the port production safety liability insurance information by matching the difference between the authenticity evaluation coefficient of the port production safety liability insurance information and the authenticity evaluation threshold of the port production safety liability insurance information is as follows: The difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is compared with a preset tolerance range. If the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is within the tolerance range, the port production safety liability insurance information is marked as having passed the authenticity test. If the difference between the authenticity assessment coefficient of the port production safety liability insurance information and the authenticity assessment threshold of the port production safety liability insurance information is outside the tolerance range, preliminary optimization measures are taken for the port production safety liability insurance information. Initial optimization measures include data verification, risk assessment level correction and policy information correction.

8. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific comparison process of comparing the verification and evaluation coefficient of the port production safety liability insurance information with the verification and evaluation threshold of the port production safety liability insurance information is as follows: Obtain the verification and evaluation threshold of the port production safety liability insurance information from the database, compare the verification and evaluation coefficient of the port production safety liability insurance information with the verification and evaluation threshold of the port production safety liability insurance information, if the verification and evaluation coefficient of the port production safety liability insurance information is greater than or equal to the verification and evaluation threshold of the port production safety liability insurance information, mark the port production safety liability insurance information as passed the verification, if the verification and evaluation coefficient of the port production safety liability insurance information is less than the verification and evaluation threshold of the port production safety liability insurance information, perform in-depth optimization on the port production safety liability insurance information; Deep optimization involves building predictive models and anticipating insurance fraud.

9. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 8, characterized in that: The specific process of establishing the prediction model is as follows: Obtain the recurrent neural network model from the database, determine the number of layers of the recurrent neural network, the number of neurons in each layer and the activation function, divide the preprocessed authenticity-related data of the port production safety liability insurance information and the preprocessed accuracy-related data of the port production safety liability insurance information into a training set and a test set according to a certain ratio, input the training set into the recurrent neural network for training to obtain a preliminary prediction model, use the test set to evaluate the performance of the preliminary prediction model, and obtain the prediction model by adjusting the hyperparameters and model structure.

10. The method for verifying port production safety liability insurance information based on safety risk as claimed in claim 1, characterized in that: The specific method for obtaining the verification and evaluation coefficient of the port production safety liability insurance information is as follows: ； In the formula, It is expressed as the verification and evaluation coefficient of port production safety liability insurance information, It is expressed as the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the weight factor of the authenticity evaluation coefficient of port production safety liability insurance information, It is expressed as the accuracy assessment coefficient of port production safety liability insurance information, It is expressed as the weight factor of the accuracy assessment coefficient of port production safety liability insurance information.

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