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Abstract

The resilience of the banking sector has faced unprecedented challenges over the last decade, particularly because of the disruption caused by the COVID-19 pandemic and the subsequent economic volatility. This study aims to reconstruct an early warning model for financial distress in the Indonesian banking sector by evaluating the efficacy of the Risk Profile, Good Corporate Governance (GCG), Earnings, and Capital (RGEC) framework. Unlike previous studies that relied on the Altman Z-score, this study defines financial distress using a profitability-based approach (negative ROA), which is more aligned with the operational realities of financial institutions. Using secondary data collected from audited annual reports published on the Indonesia Stock Exchange, a sample of 220 firm-year observations was analyzed via logistic regression. The findings reveal that credit risk (NPL) is the sole, dominant predictor of financial distress. Conversely, the GCG scores and Capital Adequacy Ratios (CAR) failed to demonstrate statistical significance, meaning these variables do not reliably predict the likelihood of a bank falling into financial distress. This indicates a clear disconnect between administrative compliance and actual financial resilience. These results challenge the efficacy of the "self-assessment" governance model and imply that high capital buffers alone are insufficient to prevent distress without rigorous asset-quality management. This study contributes to the literature by providing a specific early warning model for emerging markets and offers policy recommendations for the Indonesian Financial Services Authority regarding the supervision of asset quality.

Keywords

Financial Distress RGEC Non-Performing Loan (NPL) Corporate Governance Capital Adequacy

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Rahma, A. A., & Wulandari, S. (2026). Determinants of Financial Distress Based on the RGEC Framework: A Logistic Regression Analysis of Commercial Banks Listed on the Indonesia Stock Exchange (2014-2024). Golden Ratio of Finance Management, 6(2), 420–435. https://doi.org/10.52970/grfm.v6i2.2128
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References

  1. Ahir, H. (2023). Financial stress and economic activity: Evidence from a new worldwide index. IMF Working Papers, 2023(217), Article WP/23/217. https://doi.org/10.5089/9798400257636.001
  2. Atriyani, I., Mulatsih, Y., Lestari, S. S., & Muslikh, M. (2025). Analysis of bank soundness level using RGEC method (risk profile, good corporate governance, earnings, capital) at PT Bank Pembangunan Daerah Jawa Timur Tbk for the period of 2020–2024. International Journal of Economics, Business and Accounting Research, 9. https://jurnal.stie-aas.ac.id/index.php/IJEBAR
  3. Choiriyah, C., Fatimah, F., Agustina, S., & Ulfa, U. (2021). The effect of return on assets, return on equity, net profit margin, earning per share, and operating profit margin on stock prices of banking companies in Indonesia Stock Exchange. International Journal of Finance Research, 1(2), 103–123. https://doi.org/10.47747/ijfr.v1i2.280
  4. Daniswari, S., & Meiranto, W. (2023). Analisis mekanisme corporate governance dan kinerja keuangan terhadap financial distress. Diponegoro Journal of Accounting, 12(4), 1–14. http://ejournal-s1.undip.ac.id/index.php/accounting
  5. Dao, L. K. O., Nguyen, T. Y., Hussain, S., & Nguyen, V. C. (2020). Factors affecting non-performing loans of commercial banks: The role of bank performance and credit growth. Banks and Bank Systems, 15(3), 44–54. https://doi.org/10.21511/bbs.15(3).2020.05
  6. Dendawijaya, L. (2009). Manajemen perbankan (2nd ed.). Ghalia Indonesia.
  7. Dewi, P. A. N., & Rosyadi, I. (2024). Analisis pengaruh good corporate governance (GCG) terhadap financial distress dengan financial performance sebagai variabel moderasi: Studi empiris perusahaan manufaktur subsektor food and beverage yang terdaftar di Bursa Efek Indonesia tahun 2020–2022. Jurnal Ilmiah Edunomika, 8(3). https://doi.org/10.29040/jie.v8i3.14453
  8. El-Chaarani, H., Abraham, R., & Skaf, Y. (2022). The impact of corporate governance on the financial performance of the banking sector in the MENA (Middle Eastern and North African) region: An immunity test of banks for COVID-19. Journal of Risk and Financial Management, 15(2), Article 82. https://doi.org/10.3390/jrfm15020082
  9. Ermar, F. H., & Suhono, S. (2021). Pengaruh RGEC (risk profile, good corporate governance, earning, capital) terhadap financial distress. Owner: Riset & Jurnal Akuntansi, 5(1), 107–118. https://doi.org/10.33395/owner.v5i1.320
  10. Financial Services Authority. (2016). Financial Services Authority Regulation Number 25/POJK.04/2016. https://www.ojk.go.id
  11. Financial Services Authority. (2020). Financial Services Authority Regulation Number 11/POJK.03/2020.
  12. Freeman, R. E. (2010). Strategic management: A stakeholder approach. Cambridge University Press.
  13. Fungáčová, Z., Turk, R., & Weill, L. (2015). High liquidity creation and bank failures. IMF Working Papers, 15(103), Article WP/15/103. https://doi.org/10.5089/9781475581805.001
  14. Ghozali, I. (2018). Aplikasi analisis multivariate dengan program IBM SPSS 25 (9th ed.). Badan Penerbit Universitas Diponegoro.
  15. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2013). Multivariate data analysis (7th ed.). Pearson Education Limited.
  16. Hanun, N., Ramadhani, N., & Purwanto, A. (2025). Analisis tingkat kesehatan bank syariah dengan metode RGEC dan financial distress: Studi pada bank umum syariah di Indonesia periode 2019–2023. Diponegoro Journal of Accounting, 14(2), 1–14. http://ejournal-s1.undip.ac.id/index.php/accounting
  17. Haq, H. I., & Harto, P. (2020). Pengaruh tingkat kesehatan bank berbasis RGEC terhadap financial distress: Studi pada perusahaan perbankan yang terdaftar di BEI tahun 2015–2017. Diponegoro Journal of Accounting, 8(3), 1–12. https://ejournal3.undip.ac.id/index.php/accounting/article/view/25557
  18. Harkati, R., Alhabshi, S. M., & Kassim, S. (2020). Does capital adequacy ratio influence risk-taking behaviour of conventional and Islamic banks differently? Empirical evidence from the dual banking system of Malaysia. Journal of Islamic Accounting and Business Research, 11(10), 1989–2015. https://doi.org/10.1108/JIABR-11-2019-0212
  19. Harris, J. K. (2021). Primer on binary logistic regression. Family Medicine and Community Health, 9(Suppl. 1), Article e001290. https://doi.org/10.1136/fmch-2021-001290
  20. Ikatan Akuntan Indonesia. (2017). Pernyataan Standar Akuntansi Keuangan 71: Instrumen keuangan. https://www.iaiglobal.or.id
  21. Irwansyah, I. (2017). Bankruptcy prediction of the company using Altman Z-score method for the conventional banks registered in the Indonesia Stock Exchange (BEI). The Management Journal of Binaniaga, 2(2), 11–22. https://doi.org/10.33062/mjb.v2i02.132
  22. Jensen, M. C., & Meckling, W. H. (1998). Theory of the firm: Managerial behavior, agency costs and ownership structure. SSRN Electronic Journal, 305–360. https://doi.org/10.2139/ssrn.94043
  23. Karamoy, H., & Tulung, J. E. (2020). The impact of banking risk on regional development banks in Indonesia. Banks and Bank Systems, 15(2), 130–137. https://doi.org/10.21511/bbs.15(2).2020.12
  24. Kurowski, C., Evans, D. B., Tandon, A., Eozenou, P. H.-V., Schmidt, M., Irwin, A., & Salcedo, C. J. (2021). From double shock to double recovery: Implications and options for health financing in the time of COVID-19 (Policy Research Working Paper). World Bank. https://www.worldbank.org/hnppublications
  25. Loang, O. K., Ahmad, Z., & Naveenan, R. V. (2023). Non-performing loans, macroeconomic and bank-specific variables in Southeast Asia during the COVID-19 pandemic. The Singapore Economic Review, 68(3), 941–961. https://doi.org/10.1142/S0217590822500679
  26. Mahfud, A., & Puspitasari, D. (2025). The effect of return on asset, return on equity, and net profit margin on the stock prices of banking companies. Green Economics: International Journal of Islamic and Economic Education, 2(4), 32–42. https://doi.org/10.70062/greeneconomics.v2i4.359
  27. Martini, R., Aksara, R. R., Sari, K. R., Zulkifli, Z., & Hartati, S. (2023). Comparison of financial distress predictions with Altman, Springate, Zmijewski, and Grover models. Golden Ratio of Finance Management, 3(1), 11–21. https://doi.org/10.52970/grfm.v3i1.216
  28. Megasanti, L. C., & Riwayati, H. E. (2023). The effect of liquidity, profitability, and solvency on financial distress with good corporate governance as a moderation. International Journal of Economic Studies and Management. https://doi.org/10.5281/zenodo.7740329
  29. Mubaraq, A. Z., & Lubis, M. R. (2022). Analisis kebijakan restrukturisasi kredit terhadap pembiayaan usaha mikro, kecil, dan menengah pada masa pandemi COVID-19 di Indonesia berdasarkan Peraturan Otoritas Jasa Keuangan Nomor 48/POJK.03/2020: Studi pada Dusun X Desa Medan Estate. Iuris Studia: Jurnal Kajian Hukum, 3(2), 158–170. https://jurnal.bundamediagrup.co.id/index.php/iuris
  30. Mukhtaruddin, M., Ubaidillah, U., Dewi, K., Hakiki, A., & Nopriyanto, N. (2019). Good corporate governance, corporate social responsibility, firm value, and financial performance as moderating variable. Indonesian Journal of Sustainability Accounting and Management, 3(1). https://doi.org/10.28992/ijsam.v3i1.74
  31. Nasir, M. S., Oktaviani, Y., & Andriyani, N. (2022). Determinants of non-performing loans and non-performing financing level: Evidence in Indonesia, 2008–2021. Banks and Bank Systems, 17(4), 116–128. https://doi.org/10.21511/bbs.17(4).2022.10
  32. Ninda Febriyanti, F., & Khalifaturofi’ah, S. O. (2023). Good corporate governance dan financial distress pada perusahaan manufaktur di Indonesia. Jurnal Ekonomi, 28(2), 274–291. https://doi.org/10.24912/je.v28i2.1625
  33. Nurwulandari, A., Hasanudin, H., Subiyanto, B., & Pratiwi, Y. C. (2022). Risk-based bank rating and financial performance of Indonesian commercial banks with GCG as an intervening variable. Cogent Economics & Finance, 10(1), Article 2127486. https://doi.org/10.1080/23322039.2022.2127486
  34. Oko-Odion, C., & Omogbeme, A. (2025). Risk management frameworks for financial institutions in a rapidly changing economic landscape. International Journal of Science and Research Archive, 14(1), 1182–1204. https://doi.org/10.30574/ijsra.2025.14.1.0155
  35. Oktaviani, N., & Zulvia, Y. (2025). The effect of profitability, sales growth, and leverage on financial distress in Indonesian retail companies. Golden Ratio of Finance Management, 6(1), 56–70. https://doi.org/10.52970/grfm.v6i1.1587
  36. Otoritas Jasa Keuangan. (2020). Peraturan Otoritas Jasa Keuangan Republik Indonesia Nomor 11/POJK.03/2020 tentang stimulus perekonomian nasional sebagai kebijakan countercyclical dampak penyebaran coronavirus disease 2019.
  37. Patricia, C., Setijaningsih, H. T., & Verawati, V. (2024). Analysis of the influence of bank health level with RGEC method on financial distress using Altman Z-score method. International Journal of Application on Economics and Business, 2(2), 3328–3340. https://doi.org/10.24912/ijaeb.v2i2.3328-3340
  38. Permatasari, R. I., Hermawan, S., & Jaelani, A. K. (2022). Disabilities concessions in Indonesia: Fundamental problems and solutions. Legality: Jurnal Ilmiah Hukum, 30(2), 298–312. http://www.ejournal.umm.ac.id/index.php/legality
  39. Putri, N. A., & Amin, M. N. (2024). Rasio keuangan berpengaruh negatif dalam mendeteksi financial distress dengan financial statement: Perusahaan konsumsi primer di Bursa Efek Indonesia (BEI) tahun 2018–2021. Jurnal Ekonomi Trisakti, 4(1), 405–414. https://doi.org/10.25105/jet.v4i1.19354
  40. Rahman, M., Sa, C. L., & Masud, M. A. K. (2021). Predicting firms’ financial distress: An empirical analysis using the F-score model. Journal of Risk and Financial Management, 14(5), Article 199. https://doi.org/10.3390/jrfm14050199
  41. Richard, O., Michael, A. A., & Samuel, G. G. (2019). Impact of credit risk on corporate financial performance: Evidence from listed banks on the Ghana Stock Exchange. Journal of Economics and International Finance, 11(1), 1–14. https://doi.org/10.5897/JEIF2018.0940
  42. Saputra, S. R. D., Tarigan, T. M., Prasetyo, C. Y., & Setiabudi, A. W. (2024). Komparasi bank konvensional dan bank digital dengan metode RGEC. Jurnal Akuntansi, 18(1), 134–167. https://doi.org/10.25170/jara.v18i1.5160
  43. Sari, M., & Diana, H. (2020). Financial ratio analysis to predict the financial distress conditions of pulp and paper companies listed on the Indonesia Stock Exchange. Research in Accounting Journal, 1(1), 32–48. http://journal.yrpipku.com/index.php/raj
  44. Serengil, S. I., Imece, S., Tosun, U. G., Buyukbas, E. B., & Koroglu, B. (2021). A comparative study of machine learning approaches for non-performing loan prediction. In 2021 6th International Conference on Computer Science and Engineering (UBMK) (pp. 326–331). IEEE. https://doi.org/10.1109/UBMK52708.2021.9558894
  45. Silva, F. B. G. (2021). Fiscal deficits, bank credit risk, and loan-loss provisions. Journal of Financial and Quantitative Analysis, 56(5), 1537–1589. https://doi.org/10.1017/S0022109020000472
  46. Spence, M. (1973). Job market signaling. The Quarterly Journal of Economics, 87(3), 355–374. https://doi.org/10.2307/1882010
  47. Steigenberger, N. (2025). Deceptive signalling: Causes, consequences and remedies. International Journal of Management Reviews, 27(2), 283–305. https://doi.org/10.1111/ijmr.12392
  48. Sugiyono. (2013). Metode penelitian kuantitatif, kualitatif, dan R&D. Alfabeta.
  49. Sumiyana, S., Na’im, A., Kurniawan, F., & Nugroho, A. H. L. (2023). Earnings management and financial distress or soundness determining CEOs’ future over- and under-investment decisions. Humanities and Social Sciences Communications, 10(1), Article 164. https://doi.org/10.1057/s41599-023-01638-6
  50. Wahasusmiah, R., & Watie, K. R. (2021). Metode RGEC: Penilaian tingkat kesehatan bank pada perusahaan perbankan syariah. I-Finance, 4(2). http://jurnal.radenfatah.ac.id/index.php/i-finance
  51. Wiksuana, I. G. B., & Andari, N. M. M. (2017). RGEC sebagai determinasi dalam menanggulangi financial distress pada perusahaan perbankan di Bursa Efek Indonesia. E-Jurnal Manajemen Unud, 6(1), 116–145.
  52. Yahya, A., Hidayat, T., Cahyaning, N., & Pratiwi, M. (2023). Analysis of factors influencing non-performing loans. 1st Pelita International Conference, 1. https://jurnal.pelitabangsa.ac.id/index.php/pic
  53. Zizi, Y., Jamali-Alaoui, A., El Goumi, B., Oudgou, M., & El Moudden, A. (2021). An optimal model of financial distress prediction: A comparative study between neural networks and logistic regression. Risks, 9(11), Article 200. https://doi.org/10.3390/risks9110200