Causality Link Building Next-Gen ESG Dashboard

Artificial intelligence (AI)-based research platform provider Causality Link will release a dedicated environmental, social, and governance (ESG) dashboard later this year that will allow financial analysts and firms to track and evaluate ESG metrics relative to competitors and peers. Causality Link is collaborating with a large consulting company on the initiative to bring the dashboard to scale.

The dashboard will differ from typical ESG indexes and ratings on the market not only by decoupling the environmental, social, and governance factors from one another but also by drilling down into the nuances of each factor. According to Causality Link CEO Pierre Haren, this will be important to the next evolution of the ESG space.

“As it matures, it’s going to be totally linked with the regular business. You don’t want to just rate somebody on ESG; you want to be able to understand the causal links between their decision [on] ESG and their profits, and conversely, how their better stock price and green bonds will enable them to do more in ESG,” Haren says. “So we believe that extending a global understanding of the financial forces acting on the markets through ESG makes more sense in the long term than just studying an ESG-focused type of index.”

Sustainability will be a very different topic from fighting climate change even though it will be interlinked. So I think it’s not going to just be  ‘E’— ‘E’ is going to split into sustainability and greenhouse gas effects.

Pierre Haren

For example, a reduction in CO2 emissions is a relatively easy factor to track. It involves measuring a company’s direct emissions and indirect emissions such as electricity or energy purchased from another company, as well as implied emissions, covering emissions relative to things like business travel, waste, and water.

Tracking something like a company’s sustainability is much more complicated, Haren says. Where one energy company may take the strategy of producing oil and gas as cleanly as possible, another may shift entirely to, say, renewables. On top of that, those companies may be in the US versus Europe. In this case, it might be more apt for similar companies to take different routes depending on regulation, social attitudes, or available resources.

“You cannot have the same index for everybody,” Haren says. “You need to customize, so that’s where we’re going.”

The dashboard will have an index that tracks companies’ efforts to fight climate change, versus a separate index that measures those increasing their sustainability. Drilling down further, fighting climate change has two components: reducing emissions or capturing them, Haren says.

He expects that most companies will not go into carbon capturing—which involves trapping emissions at their source so that they aren’t released into the atmosphere—but it will become a major part of the ESG conversation along with reducing emissions. On the other side, evaluating sustainability will become much more circular. It could mean accounting for external factors like whole ecosystems, population growth, resource scarcity, and broader recycling of resources.

“Sustainability will be a very different topic from fighting climate change even though it will be interlinked,” Haren says. “So I think it’s not going to just be  ‘E’— ‘E’ is going to split into sustainability and greenhouse gas effects.”

Similarly, Causality Link’s model for judging governance is broken down into three elements—board governance, business practices, and disclosure practices. Whether or not a company is well-managed is a very different topic from whether it discloses that information properly. As a result, there will be a day when indexes are only for disclosure, separate from business practices, Haren says. 

Senior Year

Causality Link has spent the last four years since its founding investing in emerging technologies like machine learning and natural language processing (NLP) to create its flagship research platform, the Causality Link Research Assistant. The platform is designed to extract insight and forecasts on companies, industries, and macroeconomic events from texts by highlighting specific cause-and-effect relationships between market indicators and company key performance metrics.

The platform processes more than 50,000 texts per day in 18 different languages from roughly 4,000 newspapers, magazines, other publications, as well as government sites. These fields are updated daily, and every week, the system also detects emerging topics that begin to gain traction in that timeframe.

After training its NLP models to learn the jargon and nuance of financial news, reports, and sentiment, a delve into ESG is a natural next step for the company, Haren says.

“It’s an extension, but it’s not a horrible extension. Where it’s bizarre is that it’s more fuzzy than the things we’ve done up to this point because it keeps moving,” Haren says.