Master'sOpen Access

Evaluation of financial performances of life insurance and personal pension companies with clustering analysis

2022
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Advisor: Prof. Dr. Nilüfer Dalkılıç

Abstract (EN)

Life insurance and private pension systems are recommended as a solution to the problems encountered in financing social security and alongside existing social security systems. Through the private pension system, individuals have the opportunity to give up their current expenses and earn additional income during their retirement. Besides, financing of social security system is facilitated by the savings obtained from the participants. In this study 17 pension and life insurance companies operating in Turkey with domestic and foreign capital in the 2019, 2020 and 2021 periods will be classified according to their various characteristics by making use of various financial indicators (written premiums, net profit/loss for the period, total assets, total equity, premium productions, sector market share, premiums/equity received, equity/total assets). Thus, it will be determined which of the domestic and foreign insurance companies have a homogeneous structure. Three different cluster analysis methods were used to classify different insurance companies based on their similar characteristics; non-hierarchical (k-means) clustering method, hierarchical clustering method and two-step clustering method. According to the findings, it has been observed that the financial indicators of domestic pension and life insurance companies, especially the market share ratios of the sector, are higher than those of foreign capital insurance companies. In addition, it has been observed that the insurance companies within the scope of the study are gathered in 3 different clusters as companies with foreign capital, companies with domestic capital and companies with domestic and public capital.

Author

Şevval Sultan Cendek

How to Cite

Şevval Sultan Cendek (Master Thesis). Evaluation of financial performances of life insurance and personal pension companies with clustering analysis, 2022, Kütahya Dumlupınar University.

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