AI-Related Operational Efficiency and Management Quality in Selected Indian  Banks: A CAMELS ‘M’ Proxy Analysis

Ankita; Udayan Samajpati

doi:10.21844/crr.v3i01.1140

Ankita Research Scholar, P.G. Department of Commerce, Jai Prakash University, Chapra, Bihar
Udayan Samajpati Assistant Professor, P.G. Department of Commerce, Jai Prakash University, Chapra, Bihar

DOI: https://doi.org/10.21844/crr.v3i01.1140

Keywords: Keywords: Artificial intelligence in banking; operational efficiency; management quality proxies; CAMELS model; Indian commercial banks; cost-to-income ratio

Abstract

Abstract
This paper examines AI-related operational efficiency and management quality in selected Indian banks through a proxy
based CAMELS ‘M’ perspective. The study focuses on State Bank of India, HDFC Bank, and ICICI Bank and uses recent
secondary data for FY2024 and FY2025 drawn from annual reports, investor presentations, official bank disclosures, and
Reserve Bank of India sources. Since management quality is not directly observable in a short secondary-data design, the
analysis employs cost-to-income ratio, business per employee, and profit per employee as practical proxy indicators of
managerial efficiency, cost discipline, and resource utilization. The study adopts a descriptive and comparative analytical
approach using ratio analysis, inter-bank comparison, and interpretive ranking. The findings suggest that ICICI Bank shows
the strongest overall position on the selected proxy indicators, while HDFC Bank also reflects a relatively efficient
operating profile, though merger-related comparability issues require caution. SBI shows visible improvement in the latest
year but remains relatively more cost intensive. The paper concludes that a cautious proxy-based CAMELS ‘M’ approach
can generate useful comparative insight in technology-shaped banking environments.