لخّصلي

The dependent variable explanation rate of the independent variables in the econometric model is around 55%. This result shows the strength of the independent variables selected for the model in explaining credit risk (R2 = 0.55). The model is statistically significant at a confidence level of %99 (Prob. = 0.00). When the findings in Table 5 are examined, it is seen that 5 of the 9 variables in the model are statistically significant. Among these variables, net profit share incomes, natural log of total assets, gross domestic product and fixed variable are significant at
%99 confidence level. The capital adequacy ratio variable was found to be significant at %95 confidence level. In Islamic banks, which are used as net interest margins in traditional banking, the net profit share variable is one of the important components affecting credit risk. The findings suggest that there is a positive significant relationship between net profit share and credit risk with 99% reliability. This result shows that a 1 unit change in the net profit shares of Islamic banks will increase the credit risk by 0.81. In addition, similar results have been reached in the studies conducted in the literature (Rahman and Shahimi, 2010; Ozkan and Isıl, 2016).
In Table 5, the result of the multiple linear connection test between the variables in the model is shown in the VIF (variance inflation factor) column. As the outputs are less than 5, H0 hypothesis that there is a multiple linear connection is rejected and it is concluded that there is no problem of multiple linear connection between variables. The coefficient of the constant variable in the model was found to be negative and statistically significant at 99% confidence level. This result means that 1 unit increase in the fixed term will decrease the credit risk by 0,36 while the selected arguments are zero.
In this study, it is seen that there is a positive relationship between the natural log variable of total assets used to represent bank size and credit risk. The results show that this relationship is meaningful with 99% reliability. These results mean that each unit increase in the size of Islamic banks will increase the credit risk by 1.89%. These results are similar to the studies in literatures (Abdullah, Khan and Nazir, 2012). An important factor in the credit risk management of banks is the capital adequacy ratio. In the study period, the effect of capital adequacy ratios on the credit risk of the banks included in the sample was found to be 95% positive. This result reveals that one unit increase in the capital adequacy ratios of Islamic banks will increase the credit risk by 0.36. These results are similar to the studies in the literature (Ahmad and Ariff, 2007). The coefficient of the constant variable in the model is negative and statistically significant at 99% confidence level. This means that one unit change in the fixed

term will reduce the credit risk by 0.36 while the bank-specific and macroeconomic variables are zero. It is seen that there is a negative relationship between the total loans variable which shows the share of loans in total assets and credit risk. This result shows that as the ratio of loans increases, credit risk will decrease. P value was statistically insignificant. The variables that show the share of special provisions (SP) and equity in total assets are negative with credit risk. But it is statistically insignificant. In addition, a positive but statistically insignificant relationship was found between total loans and income generating assets (IGS) variables and credit risk.
Among the macroeconomic variables in the research model, the coefficient of the gross domestic product quarterly growth rate variable was negative and 99% confidence level was statistically significant. This result shows that a one-unit increase in the gross domestic product ratio will reduce the credit risk by 0.0009. There was a negative and statistically insignificant relationship between inflation rate which is another macroeconomic variable and credit risk.