MUMBAI, India, Sept. 28 -- Intellectual Property India has published a patent application (202611092967 A) filed by Manipal University Jaipur on July 31, 2026, for A Machine Learning-Based System For Integrated Reporting Quality Assessment And Corporate Governance.
Inventors include Dr. Parthvi Rastogi; and Ca. Dr. Jyoti Jain.
The application for the patent was published on September 25, 2026, under issue no. 39/2026.
Abstract: The present invention relates to a system for predictive assessment of the impact of corporate governance mechanisms on Integrated Reporting quality by employing machine learning approach such as random forest regression model on corporate governance data. The system comprises a data input module to collect structured panel data of NSE-listed companies, including corporate governance variables such as board size, board independence, gender diversity, CEO duality, and institutional shareholding, along with profitability based variables such as age, size, growth, return on assets, and Tobin’s Q; a data preparation module to organizes and formats this data for analysis and separates it into training and testing datasets; a machine learning prediction engine uses a Random Forest Regression model with multiple decision trees to predict Integrated Reporting (IR) quality; an evaluation module assesses model performance using metrics such as MAE, RMSE, and R²; and an interpretation/output component provides predicted IR quality scores, identifies the relative importance of input variables, and supports ranking, governance analysis, and decision-making. The system uses Random Forest Model to predictive assessment of IR quality. It has better predictive, adaptive and interpretative capability than traditional models.
Disclaimer: Curated by HT Syndication.
