EcoLens: An AI-Powered ESG and Carbon Footprint Analyzer

Abstract

ESG metrics are now widely regarded as key measures of a company’s long-term viability, its risk, and its corporate governance. Traditionally, ESG metrics were primarily derived from disclosures that are sufficiently static in nature (i.e., self-reported and operating on a retrospective basis), but also lack cooperation, consistency, and conviction. Similarly, the inability to utilize carbon emissions data in the context of broader corporate sustainability metrics often leads to an inaccurate assessment of emissions levels.

In this paper, we will outline the creation of EcoLens, an AI-powered analytics platform which can provide companies with actionable insights into their carbon emissions and ESG scores. The EcoLens system combines both structured data (e.g., corporate financials) and unstructured data (e.g., sustainability reports, regulatory filings, news alerts) to generate real-time reports on ESG ratings, critical carbon emissions information, and interpretable indicators of corporate risk using advanced an-alytical techniques such as Natural Language Processing (NLP), machine learning, and Explainable AI. The implementation of EcoLens will provide a level of transparency, timeliness, and informed decision-making that will ultimately improve the quality of reporting for all stakeholders involved with a company, including investors, regulators, and the companies themselves.