AI IN FORECASTING GEOPOLITICAL RISK AND ITS IMPACT ON ESG AND CORPORATE FINANCIAL STRATEGY EVIDENCE FROM THE INDIAN ENERGY SECTOR
Deepashree P Kulkarni
Abstract – Geopolitical instability has become one of the determinants of business financial decisions; thus, businesses use artificial intelligence (AI) to forecast their risks. This paper aims to find out if the usage of greenwashing, being a proxy for the credibility gap between ESG positioning and actual risk exposure of the firm, has an effect on stock price volatility at 20 energy firms in India, listed on the exchange for the 2019-2023 period (100 firm-year observations). The research investigates the moderating role of board independence and the mediating role of the market-to-book ratio. The sample companies’ financial performance is predicted using Artificial Intelligence techniques, including Linear Regression, Random Forest, Gradient Boosting and XGBoost. Out-of-sample predictions are provided for 2024-2026. Panel data tests include panel diagnostics, correlation, variance inflation factor (VIF) test, fixed/random effects regression, Hausman test, Sobel/bootstrap mediation test and moderated regression. It can be seen from the above-mentioned results that the ratio of market to book is a significant predictor of volatility and significantly mediates the effect of greenwashing on volatility, and at the same time board independence is a positive predictor of volatility; the Random Forest model demonstrates the best out-of-sample predictive stability and market to book, as well as firm size, is found to be the most significant predictor of volatility.