Abstract

AbstractOver the last few years, the Indian banking sector has been ceaselessly adding increasingly huge piles of non‐performing assets (NPAs), also known as bad loans, to its balance sheet. As of March 2018, gross NPAs for all scheduled commercial banks (SCBs) stood at over ₹10 trillion, compared to merely 4 years back, that is, March 2014, when they were almost one‐fourth of this. Aimed at tackling the NPA problem, the Insolvency and Bankruptcy Code (IBC) was enacted in 2016 by the Parliament of India, which provides for initiation and quick resolution of bankruptcy proceedings against defaulters. In 2017, the RBI identified 12 Mega‐defaulters which accounted for nearly INR 1.75 trillion of the total NPAs of Indian banks. Targeting the NPA problem at the policy level requires extensive research and analysis in order to come up with effective action plans. This study tries to analyse NPAs of Indian banks using panel data regression models and identify their key determinants. It also examines the relative severity of the NPA problem in case of public banks as compared to private banks.

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