Claim Reserving Using Tweedie Distribution
Abstract
Fitting mathematical regression models to insurance claims data has always been
challenging. The problem is predominantly grave for data from individual policies
where most of the losses are zero. In addition, those policies with an affirmative loss,
the losses are highly skewed. Most of the traditional regression models do not deal
with a mixture of discrete losses of zero and continuous positive losses. One way of
dealing with this problem is to fit separate models to the frequency and severity. We
address this problem using a new stochastic model called the Tweedie distribution
model to derive estimates of outstanding Claims liabilities which are close to the
chain ladder estimates. We take a broad view the gamma cell distributions model
which leads to Tweedie's compound Poisson model. Choosing a suitable
parameterization, we estimate the parameters of our model within the framework of
generalized linear model. We show that these methods lead to rational estimates of the
outstanding claims liabilities.
Citation
Mbauni Harun Ndegwa (2013). Claim Reserving Using Tweedie Distribution. Master of Science in Actuarial SciencePublisher
University of Nairobi School of Mathematics