Abstract

Survival analysis techniques are used to study the amount of time between entry into observation and a subsequent event in estimating insurance attrition. Retention has always been a worldwide concern. A study is carried out on the profile of the policyholder and policies that produces better persistency based on one of the Sri Lanka experience using the nonparametric analysis (e.g. Kaplan-Meier estimator and life table analysis) and Cox regression model available through SPSS Statistics 20. This paper uses the survival model to evaluate the impact of covariates on the survival curves over a period of time. Newly opened life policies were considered during the period of 1st of January 2013 and 30^th of June 2014 and our study period was end at 30^th of June 2016. Survival analysis techniques can take into account for dealing with time-dependent variables and can help researchers to understand how insurance attrition impacts to the economic environment. Instead, the survival model provides much more information to the management and the people who deal with policies than what the regression model can offer.

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