ESG In Corporate Filings: An AI Perspective

TL;DR

This paper employs AI to analyze corporate filings, identifying key ESG dimensions and background factors, and measuring investor responses to improve ESG rating systems.

Contribution

It introduces AI methods to discern ESG dimensions and background activities in corporate filings, enhancing ESG rating accuracy.

Findings

Identified three main ESG dimensions: diversity, hazardous materials, and greenhouse gases.

Detected background ESG activities providing additional context.

Measured investor responses to different ESG factors.

Abstract

Our main contribution is that we are using AI to discern the key drivers of variation of ESG mentions in the corporate filings. With AI, we are able to separate "dimensions" along which the corporate management presents their ESG policies to the world. These dimensions are 1) diversity, 2) hazardous materials, and 3) greenhouse gasses. We are also able to identify separate "background" dimensions of unofficial ESG activity in the firms, which provide more color into the firms and their shareholders' thinking about their ESG processes. We then measure investors' response to the ESG activity "factors". The AI techniques presented can assist in building better, more reliable and useful ESG ratings systems.