Estimating Insurance Attrition Using Survival Analysis

Retention is an important factor that impacts both profit and growth of insurance companies. Conventional retention analysis, such as logistic regression, does not distinguish between two types of attrition: mid-term cancellation and end-term nonrenewal. In this paper, the authors propose to use survival analysis to estimate attrition and retention. Compared with conventional methods, this approach has three advantages: (1) it addresses not only whether the policy will leave but also when it will leave; (2) it analyzes mid-term cancellation and end-term nonrenewal sequentially, and therefore provides a dynamic insight of retention, which improves the static view derived from snapshot data; (3) it can take into account time-varying macroeconomic variables, and can help researchers to understand how insurance retention is impacted by the broader economic environment. A case study illustrates the technique, from creating the panel data required by survival analysis to interpreting the model results.