基于卡尔曼滤波的人寿保险原保费收入预测分析

Prediction Analysis of Original Premium Income of Life Insurance Based on Kalman Filter

近年来,我国保险业发展迅速,尤其是保费收入增速明显。保费收入不仅会对保险公司未来决策产生影响,也会影响政府对保险业的政策导向,因此使用科学的方法预测原保费收入,可以为其提供有效的理论支撑。本文利用卡尔曼滤波算法与指数平滑法,对我国人寿保险原保费收入进行预测分析,发现卡尔曼滤波算法的平均误差比指数平滑法减少了约1003%,提高了预测的精度。

In recent yeais,insurance industiy has developed rapidly,especially the growth rate of insurance premiums.The collection of premiums will not only affect the future decision-making of insurance companies,but also affect the govemment's policy orientation towards the insurance industry.Therefore,a scientific approach of predicting the original premium input can provide an effective theoretical support for the insurance industry.This paper predicted and analyzed the original premium income of life insurance by using the Kalman filtering algorithm,and the forecast accuracy was improved based on the exponential smoothing method.Compared with the exponential smoothing method,the average error of the model is reduced by 18.43%,which provides more possibilities for future prediction.