Document Type : Original Research Paper

Authors

• M. Bash Afshar ¹
• M. SaedPanah ²
• F. Tireh Eidouzehi ¹

¹ Department of Information Technology Management, Islamic Azad University, Qeshm International Branch, Hormozgan, Iran

² Department of Information Technology Management, Islamic Azad University, Central Tehran Branch, Tehran, Iran

Abstract

This research studies the information of life insurance customers in order to achieve a clustering model for providing services. From the community of life insurance companies, an insurance company with a sample size of 1000 people who purchased life insurance in 2013 was selected. Using data mining clustering models, the effective factors and relationships between them were investigated and finally, the results of different clustering models were compared with each other. Using the obtained results, insurance companies can classify life insurance customers into two main groups: "profitable customers" and "risky customers" and provide appropriate service packages to each group. In addition, demographic variables such as "gender" and "age" and insurance variables such as "annual insurance premium" and "accident death rate" are influential factors in identifying customer groups.

Keywords

• : Life Insurance Customers
• Data mining
• Clustering
• Life Insurance