An Analysis on Experiences of Life Insurance Polices Lapsation using Machin Learning Algorithms

Lapsation of life insurance policies is one of the major problems prevailing in the insurance industry, such that the insurance industry loses policyholders. This paper explores the effect of different variables on lapsation of life insurance policies. To this end, we use the decision trees technique, which is good at identifying data segments with significant differences in dependent variable. The aim of this paper is to highlight the structural factors related to the lapsation and presenting a decision making process. We focuses on three main variables: payment mood, premium, and the loading on life insurance data of Saman insurance company. The existence of correlation between interested variable and the lapsation possibility/ the type of lapsation will be evaluated. Then, the decision tree based on significant variables will provide using IBM-SPSS software.