We develop a joint default probability index to signal potential systemic risks in the highly concentrated Indonesian banking industry. To build the index, we estimate bank-level tail risks using monthly bank financial reports. We use the copula approach to derive the joint multivariate dependencies at the bank level, as reflected in the monthly financial reports. Our results, which are based on a sample of 104 banks fromDecember 2003 to April 2020, show joint multivariate dependencies at the bank level suggesting that the standard univariate normal distribution is unsuitable for capturing tail risks of individual banks. Our index accurately captures the global financial crisis of 2007-2008 indicating that it is a valid joint default probability index. Further, our index also signaled a higher degree of joint default before the COVID-19 outbreak in2020, suggesting that it is a good indicator of potential systemic risk in the economy.

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We investigate the default probability of Indonesian banks using the copula approach and analyze the macro-financial factors that drive them. We use quarterly data comprised of 80 banks from 2005 to 2019. We find empirical evidence that Common Equity Tier 1 (CET 1) ratio, inefficiency ratio, and deposit ratio have negativelyimpacted the bank’s default probability. We also find that macroeconomic variables such as policy rate, real exchange, economic growth, and unemployment reduce the default probability. Our study suggests that regulators should focus on capital and deposit management policies to reduce bank risk-taking behaviour. Additionally, the policy rate effectively anticipated the banks’ default risk.