Insurance premium collection method and device, computer equipment and storage medium

Abstract

The invention relates to an insurance premium collection method and device, computer equipment and a storage medium, and the method comprises the steps of determining the credit data of an insurance applicant of a target insurance policy, the payment related data and the compensation risk of the target insurance policy based on the insurance policy information of the target insurance policy, and enabling the target insurance policy to be the insurance policy of which the insurance premium is to be paid; inputting the credit data into a credit evaluation model, and outputting an insurance applicant credit evaluation result by the credit evaluation model; inputting the payment related data into a payment prediction model, and outputting a payment probability prediction result of the insurance applicant on the target insurance policy by the payment prediction model; determining the user quality of the insurance applicant based on the credit evaluation result of the insurance applicant, the payment probability prediction result and the compensation risk of the target insurance policy; and determining a collection scheme corresponding to the insurance applicant based on a preset corresponding relationship between the user quality and the collection scheme. According to the method, customer maintenance and marketing strategies are accurately guided, the marketing conversion rate is improved, and the marketing cost is reduced.

Description

technical field [0001] The invention relates to the technical field of Internet applications, in particular to a premium collection method, device, computer equipment and storage medium. Background technique [0002] Insurance payment forecasting is one of the important tasks of insurance industry management departments. Accurate payment forecasting helps insurance companies better understand customer demands and behavioral characteristics, conduct cross-selling to old customers, accurately recommend products, and improve customer conversion efficiency , to solve the problem of corporate customer growth. For insurance customers, accurate payment forecasts represent more accurate demand matching, which can help customers choose more suitable insurance products, reduce unnecessary marketing interruptions, and achieve a win-win situation for insurance companies and insurance customers. [0003] Existing neural networks are widely used in the insurance forecasting industry, but...

AI Technical Summary

Problems solved by technology

[0003]Existing neural networks are widely used in the insurance forecasting industry, but in the process of forecasting complex insurance premiums and insured amounts, because the characteristics are not constant with each influencing factor but Dynamically changing, and each feature also has serious collinearity problems, which makes it relatively more difficult to predict insurance payment based on neural network learning and training samples, and the training results have not been able to achieve practical application results, resulting in low prediction accuracy

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