Dynamics of Credit Risk Management in India

Abstract

Introduction: Indian banking system is subject to similar global risk categories of credit, market, liquidity, and operational risk though credit risk requires substantial managerial commitment since it can impact other risk characteristics. This study investigates the credit risk in the banking sector which is represented in three forms viz. loan loss reserve, NPAs and capital provisions.

Literature review/research gap: Earlier studies have not considered a wide variety of factors to examine the banks’ credit risk.

Research method: Quantile regression estimates supported by a position distribution framework model identifies the impact of prior NPA provisions on loan loss.

Findings: Operational risk, abnormal loan growth and business risk impact the loan provision. Bank competition, NPAs and abnormal loan growth negatively impact the return on asset and Liquidity risk and NPAs impact negatively the return on equity of banks.

Theoretical and practitioner implications: The non-linear impact of intermediation cost suggests a strategic credit risk management process in Indian banks and hence their ability to offset reduction in bank performance.

Limitations: Quantile regressions can identify the impact of variables without subjecting the data set to specific distribution assumptions and has the tendency to disregard the influence of outliers.

Australian Academy of Business Research, volume 1, issue 1, September 2023, pp 32-43