基于数据挖掘技术的寿险险种推荐模型研究

On the Types of Life Insurance Recommended Model Based on Data Mining Technology

本文利用数据挖掘技术对大量人寿保险数据进行处理和分析,首先从三方数据中抽取属性航班和险种做数据探索及初步处理,分析这两者之间的相关性,做出简单的预测购买险种判断;然后使用软件分析并自动从大量的预测变量中筛选出与险种相关的变量,采用多层感知器对三维属性构建神经网络模型,利用模型对搭乘航班的顾客做精准的险种推销。

This paper uses data mining techniques to process and analyze a large amount of life insurance data. At the first, it searches and deals with the data by extracting attributes and insurance types from third-party data to analyze the correlation between the two and make simple prediction judgments of buying insurance. Then, it uses software to analyze and automatically filter out the variables associated with insurance from a large number of predictor variables. The multi-layer perceptron is used to build neural network models for three dimensional properties, the models are used to sell the accurate coverage of the flight customers.