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The aim of this paper is to conduct market segmentation of Arab banks and suggest a model to classify them into cohesive segments on the basis of their financial ratios as a guideline for future consolidation. Twelve financial ratios taken from Bankscope Database have been retrieved for 92 Arab banks for the year 2015. In view of the sensitivity of multivariate analysis to the normality assumption, it was decided to use the common log transformation. Factor analysis is used as a data reduction technique to find twelve financial ratios. Cluster analysis is then used to separate the 92 Arab banks into five different performance groups (segments). Multi-discriminant statistical analysis is used to answer the question: can a combination of financial ratios be used to predict bank’s group membership? Findings of the study show that multidiscriminant analysis reveals that coverage ratio, profitability and efficiency separate the groups more widely than other financial ratios. The classification matrix shows that 98.9% of original banks are correctly classified. What’s more, to go after a more efficient risk policy, this paper recommends merging big banks with small Arab banks that are less profitable, less efficient, and in weaker condition than their non-acquired peers in addition to merging huge banks operating in different Arab countries. Results of this study should provide insight for future researchers. Also, this piece of research bridges the gap between financial ratio analysis and multivariate statistical analysis for Arab banks.

Market Segmentation of 92 Arab Banks