In rate making process the statistical information on claim experience are combined with observable variables describing the risks, in order to build a tariff. The observable variables considered in the tariff structure are called tariff variables and the premium for a new risk is estimated from the observed values of these variables. In this process, many statistical methods and mathematical algorithms are applied to select the variables and to build the tariff. Many tariff methods require the values of the tariff variables to be collected in classes. Even if it is not necessary, commercial reasons often suggest making use of a low number of tariff classes. For instance, if “age of the insured” is a motor vehicle insurance tariff variable, it may be better to classify the risks into age classes instead of considering the single ages. Obviously, a question arises: which values of the tariff variable should be grouped together and which not, and also how many classes should be formed. In this paper some methods that can be used to collect these values in classes are illustrated.
