An Investigation of Financial Performance in Insurance Market Using Classical and Fuzzy Clustering Methods

Insurance is one of the financial indicators for both global and country economies. As an important tools associated with hedging against the losses caused by the risk cases, insurance needs to be effectively managed by the market. Companies in the insurance market should be strength in terms of their financial conditions. Therefore, companies need to assess their current financial conditions, the safety or risk of their investments. Internal and external analysts evaluate insurance companies systematically using the performance techniques. In this study, the financial performance assessments of 16-unit life insurance companies in the Turkish insurance market are investigated using an external analysis technique for the period 2010-2014. The insurance companies are classified by their return on equity, return on asset, and financial leverage ratios using the classical and fuzzy approaches. k-means and fuzzy c-means algorithms are used as the well-known classical and fuzzy clustering methods, respectively. The clusters structured through these algorithms are matched. As a result of logistic regression analysis, 100% of original grouped cases are correctly classified by using these clustering methods. Return on equity ratio is determined as the most important factor in affecting the classification.