Logistic Regression Model for Lapse Analysis of Life Insurance Policy
Abstract
The purpose of this research is to create the logistic regression model for forecasting life insurance lapse policy. The dependent variable is lapse class that is dichotomous qualitative variable. There are 18 independent variables which are qualitative or quantitative. The data set is divided into 2 parts; training set of 1,864 policies for building the predicting equation and testing set of 466 policies. The results show that the predicting equation consist of 6 independent variables which are age, face amount (between 50,001 – 100,000), duration of payment (more than 3 years), square root of duration of protection and occupation class (class 3 and class 4). The logistic regression equation predict that the lapse rate of insured is 31.76% and the accuracy performance of forecasting is 66.95%.
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