Study on Development of the Taiwan Life Insurance Market Using Data Mining Techniques

• Main Authors: Chieh-Chuan Liu, 劉介傳
• Other Authors: Dr. Syun-Sheng Jhan
• Format: Others
• Language: zh-TW
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/13294885205985765890

碩士 === 嶺東科技大學 === 資訊科技應用研究所 === 101 === With the accumulation of insurers’ experiences and the improvement of information technology, Taiwan insurers have applied customer relationship management (CRM) system to maintain the relationship between insurance companies and their customers by means of establishing personal information and purchase history of customers, after-sales service, product planning, premium collection, accident claims and so on. According to the statistics, 70 percent of new contracts were from "re-purchase" customers. The decision whether or not those old customers would re-purchase new insurance contracts has been critical when running insurance companies or for successful insurance sales. However, lower fertility in Taiwan is the major cause of an aging population, which leads to the problems of negative population growth, decrease of labor, increase of dependency load, change of family structure and care, and demand of long-term nursing and social insurance. In other words, senior caring will become great pressure to the young. Under this circumstance, the insurance industry should improve its service to gain better profit. In the present study, questionnaire sampling was used to build a simulation database. With the use of variance and regression analysis of SPSS Software, data were analyzed, compared, and verified by means of the association rules and decision tree technology. The results indicated that the simulation database was relatively reliable. By using the approach of association rule, the preference of product and purchase number of insurance was correlated. By using the approach of decision tree, it was found that the number of insurance purchase may influence the willingness of purchase to some extent. These two methods provided a useful prediction and are suggested to be used as a reference of management, marketing strategies, and product design in the insurance industry.