The technique is applied to check the goodness of fit of a number of distributions using operational loss data and catastrophe insurance claims data sets.From the empirical analysis we conclude that heavier-tailed distributions better fit the data than Lognormal or thinner-tailed distributions in many instances.
In particular, the conclusion is strongly supported by the “upper tail” Anderson-Darling tests.