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Özet


Financial Ratio Analysis of Insurance Companies By Means Of Data Envelopment Analysis and Analytic Hierarchy Process

1. Introduction

Financial ratios are important tools in order to measure the performances of businesses and summarize their financial status. Thus reliable comments about the profitability, efficiency, liquidity of the businesses may be made (Ceylan & Korkmaz, 2014, 41). Financial ratio analysis is a method that is frequently used for measuring the relative efficiencies of businesses. In this method, input/output ratios are discussed. The relative efficiency scores are calculated by dividing these ratios to the best one. However, focusing on a single factor for making an efficiency comparison is the disadvantage of financial ratio analysis. To overcome this drawback, the comparison of businesses by using numerous financial ratios and the examination of the current situations of business are required. In this manner Pakkar (2014a) proposed a method that utilizes Data Envelopment Analysis (DEA) and Analytic Hierarchy Process (AHP) in order to compare the businesses by using numerous financial ratios. Pakkar (2014a) stated that weights can reflect unrealistic results when ratios are used as inputs or outputs in the DEA models. So Pakkar (2014a) proposed a ratio based the DEA model by help of the DEA, AHP and ratio analysis. The aim of this study is ranking of eight non-life insurance companies in Turkey by help of the financial ratios of year 2014 by utilizing the approach of Pakkar.

2. Method

In this study, the AHP and DEA are used as tools for the proposed method by Pakkar (2014a). The output ratios must be converted in the ratio based DEA model to avoid inequality of scales and negative values of outputs. In addition, the input oriented DEA model, which is a linear programming model, is used without input variables. The following steps are applied for the method proposed by Pakkar (Pakkar, 2014a, 270-273):

1.     The efficiency score of each Decision Making Unit (DMU) is calculated by the ratio based DEA model. The best efficiency score of kth DMU is denoted by .

2.   The set of weights that hold the minimum efficiency loss ( ) for each DMU is determined.  At the same time, these weights are close to . If the value of  equals zero, the similar weights are found in the first step.

3.     The priority weights for output ratios are determined by help of expert opinions (these weights are used as the limitations of weights in the maximum efficiency loss model). The priority weights of criteria and sub-criteria are calculated by handling them separately.

4.   Maximum efficiency loss ( ) is  determined to obtain priority weights of output ratios for each DMU by help of weights derived from the AHP and the limited ratio based DEA model. In this maximum efficiency loss model, scale factor ( ) is used to avoid from extremely minimizing of relative efficiencies or infinite solution (Podinovski, 2004, 382).

5.     The parametric goal programming model is used to measure the efficiency scores of the DMUs in terms of the relative proximity to priority weights of output ratios. In this model, total of positive and negative deviations of priority weights are desired to minimize. For  interval, different sets of weights are calculated by this parametric goal programming. Consequently, a decision maker evaluates the DMUs by changing  values (Pakkar, 2014b, 178). In addition, as the value of  gets higher, deviations also increase whereas the efficiency scores decrease.

6.     The range of deviations computed by the objective function of parametric goal programming model is different for each DMU so they should be normalized by using relative deviations rather than exact values.  is a measurement of closeness which is in the interval of [0,1] and shows the relative closeness to the weights found by the ratio based DEA model. For   situation,    is regarded as 1.

The capital adequacy, asset quality and liquidity, operation and profitability ratios are considered to analyze the financial status of companies in insurance industry.  In this study, 14 accessible financial ratios are utilized because of the lack of data. These ratios are capital adequacy ratios (premiums earned/equity, equity/assets, equity/technical reserves), asset quality ratios (liquid assets/assets, current ratio, liquidity ratio), operation ratios (payment of reimbursement ratio, retention ratio) and profitability ratios (loss ratio (net), expense ratio, combined ratio, profit before tax/premium earned, financial profit/premium earned, technical profit/premium earned).

3. Results and Discussion

The DEA and AHP based ratio analysis proposed by Pakkar (2014a) are applied to measure the performance of eight non-life insurance companies in Turkey. The determined financial ratios are performed as outputs for the DEA model. Two different results based on expert opinion are compared to find out how the findings are affected by different expert opinions. Finally, Liberty and Ziraat Insurance are determined as the most efficient companies whereas Sompo Japan and Gunes Insurance are determined as the least efficient insurance companies.

4. Conclusion

In this study, two different expert opinions are used in order to compare the ranking of insurance companies in terms of financial ratios. The ranking of insurance companies is found out as Ziraat, Liberty, Halk, Ankara Anonim Turk, Anadolu, Mapfre, Gunes and Sompo Japan by the first expert whereas the ranking of insurance companies is found out as Liberty, Ziraat, Anadolu, Ankara Anonim Turk, Mapfre, Halk, Gunes and Sompo Japan by the second expert. Also various rankings of insurance companies are observed by considering the value of the parameter which is in the determined minimum efficiency loss intervals.

In the future studies, the same study may be repeated by considering different expert opinions or group decision making methods. Moreover, this method may be applied for the companies in different sectors to compare them regarding their financial ratios. Pakkar (2015) examined Turkish banks by a new approach that is the multiplicative DEA model. Insurance sector or another sector may be analyzed with the new approach of Pakkar (2015).



Anahtar Kelimeler
Financial Ratio Analysis of Insurance Companies By Means Of Data Envelopment Analysis and Analytic Hierarchy Process

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