An Integrated AI Blockchain Framework for Real-Time Greenwashing Risk Detection in ESG Asset

Environmental, Social, and Governance (ESG) investing has become one of the foundations of sustainable finance by considering environmental and social factors in making an investment decision. Nevertheless, the fast growth in the number of ESG-labeled financial products has also fueled the fears about greenwashing, in which companies oversell or falsify their sustainability efforts. Current methods of ESG assessment are mostly based on periodical reporting and ratings by third parties and are not capable of detecting greenwashing as it happens. The current paper suggests the hybrid Artificial Intelligence (AI) and Blockchain solution to real-time greenwashing risk detection in ESG assets. The suggested conceptual model is an amalgamation of machine learning, natural language processing, blockchain-provided transparency, IoT-based sustainability monitoring, and sentiment analytics to constantly re-assess ESG disclosures and produce dynamic Greenwashing Risk Scores (GRS). The framework increases the level of transparency, accountability and explainability in ESG investment decision-making and promotes regulatory compliance. The suggested architecture helps to make the finance sustainable as it will help to monitor risks automatically, ensure better investor confidence, and enhance the ESG governance.