Does governance affect non-performing loans? Empirical evidence of Indonesian banks

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This paper examines how good corporate governance (GCG) affects Indonesian banks’ non-performing loans (NPLs) and its relevance to the current banking sector situation in Indonesia. The research findings provide a comprehensive understanding of the effect of bank-specific factors on NPLs, offering timely and important insights for the banking industry. This quantitative study focuses on commercial banks listed on the Indonesian Stock Exchange in 2021. The observation period spans four years (2018–2021), utilizing 216-unit panel data from 54 banks for analysis. Documentation was used for data collection, and panel data multiple regression analysis was employed as the data analysis technique. The findings indicate that increased board of directors’ meetings are associated with higher NPLs, while having independent board commissioners correlates with lower NPLs. The p-value of the board of director meetings is 0.027, and the coefficient is 0.005037. The p-value of the board of independent board commissioners is 0.017, and the coefficient is –0.00109. Effective GCG implementation is crucial in maintaining credit quality and reducing NPL levels. The p-value of the GCG score is 0.043, and the coefficient is –0.42985. However, the frequency of Board of Commissioners’ meetings does not significantly affect NPLs. The study also shows that the Loan Deposit Ratio (LDR) and bank size negatively and significantly impact NPLs. In contrast, Return on Equity (ROE) and leverage do not significantly affect NPL levels in Indonesian banks. This study provides empirical evidence that underscores the importance of robust GCG, especially during the challenging business conditions triggered by the pandemic.

Acknowledgments
This study received funding from LPPM UNNES, contract number 12.12.4/UN37/PPK.10/2023.

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    • Figure 1. NPLs of Indonesian banks in 2018–2021
    • Figure 2. Corporate governance indicators of Indonesian banks in 2018–2021
    • Figure 3. Bank-specific determinant indicators of Indonesian banks in 2018–2021
    • Figure 4. Growth of assets of Indonesian banks in 2018–2021
    • Table 1. Research variable descriptive statistics
    • Table 2. Matrix correlation
    • Table 3. Correlation test results
    • Table 4. Model fit test result
    • Table 5. Results of regression analysis with fixed model effects
    • Table A1. List of the banks
    • Conceptualization
      Ahmad Nurkhin, Fachrurrozie, Anna Kania Widiatami, Christian Wiradendi Wolor
    • Formal Analysis
      Ahmad Nurkhin, Fachrurrozie, Anna Kania Widiatami, Christian Wiradendi Wolor
    • Funding acquisition
      Ahmad Nurkhin, Fachrurrozie
    • Investigation
      Ahmad Nurkhin, Anna Kania Widiatami, Satsya Yoga Baswara
    • Methodology
      Ahmad Nurkhin, Anna Kania Widiatami
    • Software
      Ahmad Nurkhin, Christian Wiradendi Wolor
    • Supervision
      Ahmad Nurkhin, Fachrurrozie
    • Visualization
      Ahmad Nurkhin, Satsya Yoga Baswara
    • Writing – original draft
      Ahmad Nurkhin, Fachrurrozie, Anna Kania Widiatami, Satsya Yoga Baswara, Christian Wiradendi Wolor
    • Writing – review & editing
      Ahmad Nurkhin, Fachrurrozie, Anna Kania Widiatami, Satsya Yoga Baswara, Christian Wiradendi Wolor
    • Validation
      Fachrurrozie, Anna Kania Widiatami
    • Data curation
      Anna Kania Widiatami, Satsya Yoga Baswara
    • Project administration
      Anna Kania Widiatami, Satsya Yoga Baswara
    • Resources
      Anna Kania Widiatami, Satsya Yoga Baswara