The increase in NPLs that deteriorate banks’ asset quality is believed to have an adverse impact on the health and efficiency of the banking sector (Zhu, wang, mathrm Wu, 2014) . In addition, previous research indicates that loan defaults have harmful consequences on the overall economy (for example, Barseghyan, 2010; Zeng, 2012). Considering this substantial influence, it is important for banking supervisory authorities to understand the determinants affecting loan defaults in banks’ portfolio, especially in developing countries that still heavily rely on the banking sector. Empirically, loan defaults can be attributed to banks’ specific aspects and macroeconomic factors (Beaton, Myrvoda, Thompson, 2016; Dimistrios, Helen, Mike, 2016; Ekanayake Azeez, 2015; Vatansever Hepsen, 2013). However, by controlling for bank-specific factors, policy makers can comprehend micro-prudential contexts and identify the impact of the NPL ratio on the lending behavior of commercial banks.
The relationships between the bank-specific determinant factors are ambiguous, https://loan-on.com/payday-loans-mn/ and some scholars find positive while others suggest negative relations
Many researchers have examined the effects of macroeconomic and bank-specific factors on loan performance of banks in Indonesia (Alexandri Santoso, 2015; Diyanti Widyarti, 2012; Poetry Sanrego, 2011). This study aims to comprehend bankspecific determinants affecting non-performing loans (NPLs) in the Indonesian commercial banking sector. More specifically, this study seeks to address (1) what bankspecific factors significantly affect the NPL ratio, (2) the relationships of the determinant-factors with NPL ratio, and (3) the quantitative measure of that effect. The paper is organized as follows: Section II reviews the related literature and the overview of the recent development of the Indonesian banking sector. Section III explains the methodology, Section IV explores the empirical results on the determinant-factors affecting the NPL, focusing on bankspecific aspects and also discusses how data and information are gathered and analyzed. The last section concludes and suggests policy implications for the Indonesian commercial banking industry.
2.1. Literature on Non-performing Loan Determinants
Non-performing Loans (NPL) can be attributed to bankspecific and macroeconomic factors (Beaton et al., 2016; Dimistrios et al., 2016; Ekanayake Azeez, 2015; Vatansever Hepsen, 2013). Among the macroeconomic factors, business cycle, inflation rate, interest rate, and exchange rates are common determinants of NPLs in banks portfolios (for instance, Beck, Jakubik, Piloiu, 2015; Klein, 2013; Love Ariss, 2013; Skarica, 2013). Meanwhile, the financial aspects of internal banks including credit growth, capitalization, loan loss provision, portfolio composition, profitability, net interest margin, efficiency, and size are common determinants of NPLs (for instance, Ghosh, 2015; Klein, 2013; Love Ariss, 2013).
More specifically, analyzing the effects of macroeconomic variables on loan performance in the Indonesian banking sector has also been undertaken by many researchers (for example, Alexandri Santoso, 2015; Diyanti Widyarti, 2012; Poetry Sanrego, 2011). Moreover, Diyanti and Widyarti (2012) find that external and internal factors such as bank size, Capital Adequacy Ratio (CAR), Gross Domestic Product (GDP), and inflation are attributed to loan defaults of commercial banks in Indonesia. However, research that focuses only on analyzing internal commercial bank-specific factors to non-performing loans in Indonesian banks is currently considered very limited.
This study focuses on identifying the bank-specific factors that significantly affect the NPL ratio in the Indonesian commercial banking sector. Recognizing very different characteristics of commercial banks in Indonesia (e.g., asset size, ownership structure, main business, core-capital grouping); it is then valuable for policy makers to understand the determinant of the NPL ratio within the individual banklevel data for the micro-prudential context. Moreover, discovering bank-specific factors is important for policy makers to comprehend the effect of NPL on the lending behavior of individual banks.
Scholars have identified bank-specific factors significantly affecting the NPL ratio, including credit growth, profitability, operating efficiency, capitalization, and income diversification. Keeton (1999) argues that credit growth positively affects the NPL ratio, because when banks raise their credit supply, they might lower their loan interest rates and credit checks to attract debtors. Similarly, Ahmad and Bashir (2013) find a positive relationship between credit growth and NPLs. Furthermore, they suggest a procyclical credit policy hypothesis, stating that the growth of bank credit supply follows a business cycle; it goes up when the economy is booming because banks loosen their credit requirements, and vice versa. On the contrary, Boudriga et al. (2010) find that an increase in credit supply lowers loan defaults, implying an inverse relationship between credit growth and NPL. They argue that banks supplying more credit are most likely to have good credit risk scoring and management.