Applying the Tweedie model for improved microinsurance pricing

Abstract

Microinsurance usually involves basic rate making due to the scarcity of data and the lack of actuarial skills, causing microinsurers to add significant charges to premiums to compensate for unexpected variations in risk assessment. The situation could be improved by applying predictive modelling techniques to enable better pricing in the microinsurance market. This paper proposes the application of a generalised linear model with the Tweedie compound Poisson–Gamma distribution for a bundled microinsurance in the Philippines. The risk factors considered are mainly derived from the available database and are related to the features of the insured. The results of the predictive analysis point out that there are three predictors that best fit the model: age of the insured, policy age, and population density. The application of the Tweedie model provides fair and accurate risk premiums that outperform the model currently applied by the company and enhance its risk control.