Competition, concentration and default-risk in the Indian banking industry

Purpose - The study investigates the impact of bank market competition and concentration on the bank default-risk using the data for 36 Indian scheduled commercial banks from 1999 to 2017. Design/methodology/approach - The study adopts the dynamic panel generalised method of moments (GMM) and panel quantile models to obtain the results. Findings - Bank market competition and concentration foster financial fragility in terms of high default-risk. This implies that concentration does not mean a lack of competition in the Indian banking market. The findings from the quantile model reveal that the stated relationships become weaker under the tails of the conditional distribution of the risk measure. Research limitations/implications - The authors recommend that non-structural measures (Lerner index and H-statistic) should be preferred over the concentration measures (HHI and CR3) to characterise bank market competition in India. Based on the evidence of persistence in the bank risk variable, from the methodological perspective, dynamic panel data models are better choices for bank-level analyses compared to the conventional panel data models. Practical implications - To improve the health of banks, price competition should be reduced among them. This objective should be achieved by creating new avenues to increase the banks' non-interest income parallelly with the consolidation of the market. riginality/value - First, it tries to answer whether concentration implies a lack of competition for a banking system like India. Second, the quantile regression technique enables us to understand the varying nature of the impact of market competition on bank risk at different locations on the latter's conditional distribution. Earlier studies have not looked at these aspects in the Indian context.