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Interconnections among banks are an essential feature of the banking system as it helps in an effective payment system and liquidity management. However, it can be a nightmare during a crisis when these interconnections can act as contagion channels. Therefore, it becomes essentially important to identify good links (non-contagious channels) and bad links (contagious channels).

The article estimated systemic risk using quantile regression through the ΔCoVaR approach. The interconnected phenomenon among banks has been analyzed through Granger causality, and the systemic network properties are evaluated. The authors have developed a fixed effect panel regression model to predict interconnectedness. Profitability-adjusted systemic index is framed to identify good (non-contagious) or bad (contagious) channels. The authors further developed a logit model to find the probability of a link being non-contagious. The study sample includes 36 listed Indian banks for the period 2012 to 2018.

The study indicated interconnections increased drastically during the Indian non-performing asset crisis. The study highlighted that contagion channels are higher than non-contagious channels for the studied periods. Interbank bad distance dominates good distance, highlighting the systemic importance of banking network. It is also found that network characteristics can act as an indicator of a crisis.

The study is the first to differentiate the systemic contagious and non-contagious channels in the interbank network. The uniqueness also lies in developing the normalized systemic index, where systemic risk is adjusted to profitability.