MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202611087419 A) filed by Krishna Institute Of Engineering & Technology Kiet on July 16, 2026, for "adaptive Ensemble Learning Model (aelm) For Esg-Based Mutual Fund Recommendation Using Dynamic Correlation-Driven Weight Optimization".
Inventors include Muskan Gupta; Mahi Gaur; Ishika Chaudhary; and Mr. Deep Kumar.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention provides a software-based artificial intelligence system, apparatus, and associated machine learning method for providing optimized ESG-based mutual fund recommendations. The full-stack FinTech architecture comprises an automated data ingestion layer, a data cleaning and normalization module, a Spearman correlation feature engineering engine, a dynamic ensemble core, a hybrid scoring engine, and an interactive environmental impact calculator dashboard. The feature engineering engine processes sustainability indicators-such as carbon footprint, fossil fuel exposure, and corporate gender diversity-using Spearman ranking to establish feature importance. The core Adaptive Ensemble Learning Model (AELM) integrates a plurality of machine learning models (Random Forest, XGBoost) and dynamically allocates predictive weights at runtime based on model accuracy and ESG sensitivity. A hybrid scoring function balances returns, sustainability scores, and expense fees using adjustable optimization weights to rank funds. The environmental impact calculator quantifies the real-world ecological benefits of an investment— such as $CO_2$ reduction and water saved-delivering an adaptive, reliable, and scalable roboadvisory solution. Figure 1 Dated this 23rd day of June, 2026
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