Abstract:

Cluster analysis is a multivariate method used in many fields in order to group a population of objects based on a set of computed variables into a number of different groups, so that similar objects be assigned to the same group. Discriminant analysis represents a technique of supervised recognition of forms used to determine which variables are the best predictors of the classification of objects belonging to a population into predetermined clusters. In this paper we will use discriminant analysis to classify the insurance companies that operated on the Romanian insurance market in 2012, taking in consideration a number of eight variables which are highly relevant for this industry. Before proceeding to discriminant analysis, we performed cluster analysis on the original data in order to identify classes that result from the data.