Measuring the Adequacy of Loss Distribution for the Ghanaian Auto Insurance Risk Exposure through Maximum Likelihood Estimation

Abstract

Loss distribution plays an influential role in evaluating risks from policyhold ers’ claims. Nevertheless, the auto insurance market in Ghana pays little at tention to policyholders’ claims distribution, resulting in the market’s ineffi ciency. This study investigates the type of loss distribution function that best approximates policyholders’ claims in Ghana. We applied the Kullback-Leibler divergence, Kolmogorov Smirnov, Anderson-Darling statistical tests and max imum likelihood estimation (MLE) to estimate policyholders’ claims. The re sults suggest that Ghana’s auto policyholder’s claims are better approximated using the lognormal probability distribution. Through the lognormal distribu tion, the industry can adequately evaluate policyholders’ claims to minimize potential loss. Additionally, this distribution could enable the market reach decisions on premiums and expected profits theoretically