Godfred Kwame Abledu, Elvis Dadey and Agbodah Kobina
Probability modeling has a wide range of applications in the field of insurance and finance. Over the years, its applications have been modified to include simulation techniques which in most cases are engaged to enhanced or validate the desired estimates. This study investigates the probability distributions that best fit a number of insurance claims. In particular, it compares the Poisson distribution and the negative binomial distribution models to determine which distribution best fits insurance claim data obtained from two Insurance Companies in Ghana. Data on number of claims of a funeral policy spanning from 2006 to 2010 were used for the study. Probability distribution models and the parametric bootstrap methods were employed in analyzing the data collected. The result of the study revealed that on the average, the number of claims tends to increase as the year go by. Also the Negative Binomial Distribution was found to be superior to the Poisson distribution in fitting the claims data. Finally, a comparison between the estimates obtained by the probability models and that of the parametric bootstrap estimates revealed no significant difference.