Credit exposures and systemic risk in Indian banks

Purpose The stability of a financial system depends not only on individual bank risks but also on the interconnectedness of banks with similar credit exposure patterns. If banks form clusters based on their liabilities and asset similarities, the financial system may become fragile and vulnerable to systemic risk and contagion effects. This study investigates the clustering of Indian banks based on their credit exposure patterns and examines the implications for financial stability in COVID-19 and post-merger restructuring of public sector banks (PSBs). Design/methodology/approach This study employs a similarity matrix, suggested by Brechler et al. (2014), to quantify the degree of resemblance between banks’ credit portfolios and applies hierarchical clustering algorithms to identify clusters of banks with similar exposure structures. The dataset includes financial information from 2018 to 2023, covering pre-pandemic, pandemic and post-pandemic periods to analyze systemic risk dynamics. Findings The results reveal significant clustering among Indian banks (public sector and large private sector banks). These institutions exhibit strong positive correlations in their credit exposure patterns, indicating potential systemic risks. The findings suggest that highly correlated credit exposures increase contagion risk, where distress in one institution could have spillover effects across the cluster, amplifying financial instability. Originality/value This research provides empirical evidence of systemic risk clustering in Indian banking, extending the literature on financial stability in emerging markets. Unlike prior studies focusing on developed economies, this study emphasizes the challenges faced by emerging market banking systems, particularly during financial crises such as COVID-19. The findings offer policy-relevant insights for regulatory bodies seeking to strengthen financial resilience in economies with similar banking structures.