Title: Risk profiling of Indian commercial banks - a clustering approach

Authors: Shailja Vashisht; Mahesh Sarva

Addresses: Mittal School of Business, Lovely Professional University, Jalandhar, Punjab, India ' Mittal School of Business, Lovely Professional University, Jalandhar, Punjab, India

Abstract: It is important to understand the risk profile of banks to prevent systemic risk in the economy. The present study tracks the risk profile of Indian commercial banks using the k-means clustering approach based on selected financial variables indicative of prominent banking risks. Thirty Indian banks were studied from 2009-2020 and classified into high and low risk clusters. Analysis of variance was performed to identify variables crucial for their risk profiles. The findings indicate that profitability and credit risk variables are crucial for the risk profile of Indian banks. The overall performance of the Indian banking scenario has improved during the study period. The main contribution of the current study is to identify the characteristics of high and low risk banks based on the data mining clustering approach. This approach will be very useful for the government and regulators in achieving better results in banking consolidation.

Keywords: risk profiling; cluster analysis; banking; k-means clustering; banking risk.

DOI: 10.1504/AAJFA.2024.142112

Afro-Asian Journal of Finance and Accounting, 2024 Vol.14 No.6, pp.854 - 872

Received: 19 Aug 2021
Received in revised form: 08 Sep 2022
Accepted: 05 Oct 2022
Published online: 08 Oct 2024 *

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