📄 Abstract
Indian banks have been moving rapidly towards the use of artificial intelligence, but there is still no consensus on the best way to assess how well they govern it. In this paper, a disclosure-based AI-Readiness Index is developed and tested for Indian banks, employing sixteen indicators divided into four categories: governance and oversight, risk management, capability and adoption, and transparency and ethics. Each indicator is assigned a score from 0 to 2 according to the actual information that the bank provides in its FY2025–26 annual report. Fifteen listed banks were assessed in this manner—five being public-sector and ten private-sector—resulting in an overall score out of 100. HDFC Bank achieves the highest score at 90.6 and Yes Bank comes second at 84.4; in both cases these are the only two banks that explicitly link their AI policies to the RBI's Framework for Responsible and Ethical Enablement of AI (FREE-AI), which was issued in August 2025. SBI is next at 81.3. Canara Bank is at the lowest level with a score of 25.0. The index is statistically robust (with a Cronbach's alpha of 0.87) and the ranking remains almost unchanged when different weighting methods are applied—whether equal weights, entropy weights or TOPSIS all show very similar results. A k-means clustering method divides the banks into three broad groups that correspond to the categories of adopters as described by the Diffusion of Innovation theory: Leaders, Followers and Laggards. On average private banks score higher than public-sector banks (61.3 compared to 48.8), although with only five public-sector banks in the sample this difference does not reach statistical significance. The correlations between the index and financial-risk indicators—NPAs, ROA, CRAR—are weak and inconclusive, and the paper states this clearly rather than presenting the figures in a more favourable light. What the study provides is a practical, regulator-linked method of measuring AI governance readiness, directly aligned with the structure of FREE-AI, thus addressing a gap that is not covered by any of the studies reviewed here: an index of this kind, designed for Indian banks, tested against real risk outcomes after the FREE-AI framework had been introduced.
📚 How to Cite:
Snehitha Bommidi, Dr. Golli Mohan , AI GOVERNANCE AND FINANCIAL RISK : DISCLOSURE BASED AI READINESS INDEX FOR INDIAN BANKS , Volume 12 , Issue 10, October 2026, EPRA International Journal of Multidisciplinary Research (IJMR) , Pages: 226 - 234 , DOI: https://doi.org/10.36713/epra31842