数据挖掘技术在寿险客户购买行为分析中的应用

随着中国加入WTO,我国寿险市场的竞争日益白热化.我国寿险行业经过近二十年的发展,取得长足进步,积累了大量客户数据.本文的目的就是希望在这些公司所积累的寿险客户对产品的购买记录上,通过数据挖掘的方法,发现客户对险种类型选择的模式.在数据挖掘中,通过对客户的数据进行抽取、清洗和预处理,生成数据挖掘库,并使用SPSS Clementine数据挖掘工具,利用C5.0算法建立决策树模型,并对不同的模型进行了分析和对比,以发现客户在寿险产品选择上的一些模式.

Application of Data Mining Technology to Analyze Life Insurance Customers' Purchase Behavior

With China's entrance to WTO,the competition of domestic life insurance market is becoming red-hot day by day.With two decades' development,our life insurance has achieved rapid progress and accumulated a large amount of data of their customers.To find the rule that the customers selected their life insurance policy.the data mining technology is used based on their purchasing records.Data deriving,data cleaning and data pre-processing are necessary steps before data mining. After that,decision tree models were set up with C5.0 algorithm in SPSS Clementine tool and different models were compared and analyzed to find out some useful rules in the customers' decision about different life insurance product..