Corporate reporting on sustainability — including environmental, social and governance (ESG) performance and achievements — has grown more than fivefold in the past 10 years. Roughly 20 percent of S&P 500 companies published a sustainability report in 2011. In 2018, that number rose to 86 percent. During that time, sustainability professionals have fretted about whether anybody reads their reports.
What we’re beginning to see is that it may not be "who" but "what."
Automation and artificial intelligence (AI) are being leveraged to both generate and evaluate ESG data.
The bots and AI are largely in response to the confusing world of ESG reporting. There are more than 600 ESG ratings agencies globally, according to the Global Initiative for Sustainability Ratings, as ESG data becomes a greater factor in a company’s valuation and access to capital. The challenge is that current corporate ESG disclosures lack consistency and standardization.
Further complicating things, financial markets don’t produce enough data to get the most out of AI and machine learning, according to industry watchdog MarketWatch. AI functions best on billions of data points rather than millions, but three decades of daily share-price data for the benchmark S&P 500 Index would yield only about 4 million data points, a mere drop in the big-data bucket.
For many investors, the technology doesn’t have to be exotic. For example, bot searches of companies’ 10-Q and 10-K filings with the U.S. Securities and Exchange Commission can track and redline what has changed when it comes to sustainability and ESG topics. Investors take notice when a phrase in what normally may be seen as boilerplate shifts from "probable" to "likely" from one report to the next. A machine is more likely to spot such subtleties.
The takeaway is that bots and AI work best when humans develop an investment thesis and machines test that theory. Go deeper here. LINK