The paper explores the role of business models in the link between uncertainty and bank risk. From the perspective of banks, given that future outcomes tend to be less predictable if banking uncertainty rises, we highlight a framework that a larger dispersion of bank shocks to bank-specific variables might mirror such decreased predictability as a consequence of increasing uncertainty. To compensate for the persistence of bank risk and address the endogeneity issue, we applied the system generalized method of moments (GMM) estimator as the main regressions. Analyzing a panel of commercial banks from Vietnam between 2007 and 2019, we find that higher levels of banking uncertainty may increase bank risk, as gauged by banks' credit risk (loan loss reverses and non-performing loans) and default risk (Z-score index). This detrimental influence of uncertainty appears to be most pronounced with banks relying on pure lending, and it decreases with more non-interest income. A deeper investigation after estimating the marginal effects with plots reveals an asymmetric pattern that bank risk is immune to uncertainty in banks with the highest level of income diversification. Interestingly, we also provide evidence that uncertainty may lower the default risk level when income diversification exceeds a sufficiently high level. Our findings demonstrate that diversified business models are an efficient buffer against higher bank risk in times of increased uncertainty.
Copyright: © 2024 Huynh, Phan. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.