An Empirical Study on the Key Determinants of Credit Risk in the Banking Sector
Harun ÇetinkayaThe purpose of this study, the banking sector in Turkey is to identify the factors that influence their lending rates followed. The purpose of this study is to detect the factors that influence the rate of NPLs in the banking sector in Turkey. Quarterly financial data of banks operating in Turkey was used for this purpose. Quarterly financial data of banks operating in Turkey was used for this purpose. The first three banks with the largest volume operating between 2014-2017 were included in the analysis. The analysis was performed by method of panel data regression. The analysis was performed by method of panel data regression. The results of the study show that the variables such as asset profitability, bank size, net interest margin, finance deficit and return on equity among bank specific variables were statistically significant to a 99% confidence level. The results of the study show that the variables such as asset profitability, bank size, net interest margin, finance deficit and return on equity among bank specific variables were statistically significant to a 99% confidence level. There was a statistically significant relationship between the gross domestic product ratio which is macroeconomic variable and capital adequacy ratio variable and the credit risk at the 90% confidence level. These results are important and specific in terms of showing which variables should be taken into the foreground in managing non-performing loans in the banking sector, namely credit risk.
Bankacılık Sektöründe Kredi Riskinin Temel Belirleyicilerine Yönelik Ampirik Bir Çalışma
Harun ÇetinkayaBu çalışmanın amacı, Türkiye’deki bankacılık sektörünün takipteki kredi oranlarında etkili olan faktörleri tespit etmektir. Bu amaçla çalışmada Türkiye’de faaliyet gösteren bankaların üç aylık finansal verileri kullanılmıştır. Analiz kapsamına 2014-2017 yılları arasında faaliyet gösteren en büyük hacme sahip ilk üç banka dâhil edilmiştir. Analiz panel veri regresyon yöntemi ile yapılmıştır. Çalışmanın sonuçları, bankaya özgü değişkenler arasında yer alan aktif karlılığı, banka büyüklüğü, net faiz marjı, finansman açığı ve özsermaye karlılığı değişkenlerinin %99 güven düzeyinde ve istatistiksel olarak anlamlı olduğunu ortaya koymaktadır. Makroekonomik değişkenler arasında yer alan gayri safi yurtiçi hâsıla oranı değişkeni ve sermaye yeterlilik oranı değişkeni ile kredi riski arasında %90 güven düzeyinde istatistiksel olarak anlamlı bir ilişki çıkmıştır. Bu sonuçlar bankacılık sektöründe takipteki kredileri dolayısıyla kredi riskini yönetmede hangi değişkenlerin ön plana alınması gerektiğini göstermesi bakımından önemli ve özgündür.
The volume of loans or funds plays an important role in the growth and expansion of the impact areas of countries. The economic growth of a country is influenced by the institutions and organizations operating in the country. Banks fulfill the funding needs of firms and individual customers by providing loans. Banks may have problems in the collection of loans due to a number of negativity. These negativities that occur in the form of not paying the loans on time and in full cause the risk in the collection of the receivables. The failure of the borrower or counterparty to fully fulfill its obligations is defined as the credit risk faced by banks. The financial crises have shown that the increase in the non-performing loan ratios of the banks has indicated some problems in the real economy. For all these reasons, it is generally accepted that non-performing loans are a leading indicator that should be monitored and managed very carefully
While non-performing loans shed light on the current situation of the banking sector, it also holds an important projection to understand the course of the general economy. The share of non-performing loans in total loans depicts the asset quality of banks, while the debt solvency of the household and the real sector is shown. In this respect, non-performing loans are a leading indicator in determining the banking performance as a micro indicator and as a macro indicator in the performance of the general economy. It is important to make accurate forecasts in order for economic policy recommendations to be made accurately and for banks to continue their operations healthily . It is important to make accurate forecasts in order for economic policy recommendations to be made accurately and for banks to continue their operations healthily. Therefore, in our study, non-performing loans were used as dependent variables in order to represent credit risk. Factors affecting NPLs in the banking sector in Turkey is aimed to identify what is going on. Thus, this study has investigated what happened the factors affecting the NPLs in the banking sector in Turkey. From this point of view, it is aimed to contribute to the literature. Working in conventional banks operating in the banking sector in Turkey using quarterly data in credit risk between the years 2014-2017 aimed to identify factors that are effective. For this purpose, the first three largest banks were included in the sample. Thus, the study was estimated by panel data regression method. The econometric model for the banking sector was found to be significant at 99% confidence level. The results of the study revealed that the selected variables were 67% effective in explaining the credit risk in the banking sector. While all the bank-specific variables selected in the research model were significant, only gross domestic product was significant among the macroeconomic variables.
The results show that a unit increase in the return on assets of the first three banks operating in the banking sector will result in an increase of 5.84 in credit risk. This result reveals that the increase in asset profitability will adversely affect credit risk. In addition, the results of the study show that a one-unit increase in the size of the bank will increase the non-performing loans, namely the credit risk by 1.30%. The net interest margin variable in the model was positive and statistically significant at 99% confidence level. This result shows that a one-unit increase in the net interest margin will increase the credit risk by 0.03. A one-unit increase in the share of liquid assets in total assets reduces the credit risk by 0.09. A one-unit increase in the return on equity reduces the credit risk by 0.57. This result supports the idea that the increase in shareholders’ equity will decrease the credit risk. This result supports the idea that the increase in banks shareholders’ equity reduces credit risk. The findings suggest that a one-unit increase in banks’ capital adequacy ratios will reduce credit risk by 0.06 percent. Thus, the higher the capital adequacy ratio of the banks, the lower the exposure to credit risk. The results of the research show that there is a positive and statistically significant relationship between the gross domestic product variable and credit risk at 90% confidence level. In addition, the results showed that the inflation rate variable was meaningless in explaining the credit risk in banking.
The fact that banks have a solid liquidity structure is not only important in terms of the performance of the banks and the stability of the financial system, but also in terms of avoiding crises due to the increase in non-performing loans in the economy. Both the local banking crisis of 2000-2001 and the global financial crisis of 2007-2008 showed that nonperforming loans, ie, not managing credit risk effectively, could result in bankruptcy of banks. The study credits the banks operating in Turkey reveals factors that need attention in order to prevent exposure to risk. In this regard, considering the factors mentioned above, it is thought that banks that follow an appropriate policy will not have credit problems and keep their performance in good condition.
