ESG: Does motivation matter when the outcome is positive?

By Diana Rose, Head of ESG Research, Insig AI

The recent high-profile acquisition by Philip Morris International (PMI) of Vectura, a health tech company that produces inhalers, has been dominating headlines. Heated debate has been spurred as to whether such an apparent conflict of interest should be allowed, or whether it’s a sign that ESG momentum is biting and business is being forced to pivot for the better.

On one side, there is a sense of moral outrage that a company should profit from solutions to problems it contributed towards. There are also serious concerns expressed by health academics who believe the acquisition will allow Big Tobacco to wield undue influence on UK health policy. This response seems to boil down to a question of whether businesses with damaging legacies deserve to thrive now our eyes are open to their impact – are they beyond becoming sustainable.

On the other side of the coin is the more pragmatic view that these influential companies have a role to play in the transition away from harmful practices. This side argues that reactive divestment in bad news assets is not the answer; washing your hands of poor ESG stocks merely allows them to be snapped up by the less discerning. Ultimately, this leads to our environment and society being no better off.

So while PMI seems to have pulled off a highly strategic move that’s probably key to its survival and the whole thing makes us deeply uncomfortable, it begs the question: Does the motivation really matter if the overall outcome is positive? Sustainability is fundamentally about the long term view – how will we look back at this moment in its evolution?

It’s impossible to say, but critically, the first part of answering this question is to ensure that the outcome is positive and to do that, companies need to be held to account in fulfilling their ESG promises. It is the same logic when it comes to greenwashing. If a company sets long-term targets for emissions, ethics and equality but nobody checks in on whether they’re delivered upon, the company enjoys all the benefits of sounding virtuous without ever having to deliver or face the consequences.

Part of the problem is that littering reports with generic wording, vague long-term targets and catch-all terms has become dangerously easy. So much so that the EU has introduced new anti-greenwash rules forcing the asset management industry to categorise and qualify their ESG claims. And the EU is not alone, with the UK Competition and Markets Authority (CMA) recently putting business “on notice”. In a release published just last month, the CMA warned businesses they have until the New Year to make their environmental claims comply with the law. Further, it stated it would be carrying out a full review of misleading green claims early next year and “stands ready to take action against offending firms”.

Some see the greenwashing trend as threatening the whole ESG movement; others see it as teething problems that won’t hold back the wave of change. Again, what’s key to getting it right is to enforce accountability and responsibility. Consumer pressure, regulation and convergence of standards clearly have a role to play, but it’s still a tricky space for discerning investors. Assessing credibility and tracking delivery to targets is made challenging by the sheer volume of reporting resources published, and genuine disclosures can get obscured in confusion.

This is where we are starting to see the role technology can play in holding companies to account to having the impact they intend. AI and machine learning are emerging as practical tools that investment professionals can use to identify if corporate promises are being acted upon. Thoughtfully trained algorithms can do a lot of the heavy lifting of organising and processing vast volumes of corporate disclosures so that a researcher can more effectively and efficiently home in on metrics, read between the lines where things aren’t what they seem, and determine from the evidence whether words and actions match where it matters.

We are still in the early days of ESG and, as the PMI dilemma highlights, there are conflicts, trade-offs and strong arguments for principles and pragmatism that can pull in different directions. However, as the complexity we need to grapple with increases, so to do the tools and solutions at our disposal. It is my belief that ESG will create positive change over the long term, and AI and machine learning will play a valuable role in supporting us on the journey.