In this paper we present a review of some applications of cluster analysis in the field of Insurance and
allied sciences. Primarily there are two types of clustering techniques used in predictive analytics based on
the business problems, Partition-based clustering technique and Hierarchical agglomerative clustering
approach. Hierarchical agglomeration based clustering approach is time consuming and complexity
increases with increase in number of dimensions. Partition based algorithms contrary to hierarchical tries
to divide the search space before arriving at the final clusters. Both methods have its merits and demerits
and hence proper knowledge of domain, number of variables and computation prowess is required before
deciding on the algorithm.