AI will be an important tool for assessing transition plans against the growing range of frameworks

The most acute issue across ESG in recent years has been the relationship between relative outperformers and underperformers and the absolute outcomes that define issues such as success in addressing climate change. Many of the issues in greenwashing come down to promoting as ‘sustainable’ activities that improve on the norm, even if they fall short of what is required to bring about climate change mitigation, nature protection, or sustainable development.

There has continued to be a slew of frameworks and guidance around the elements of assessing the credibility of transition plans, with a guide from the Climate Bonds Initiative being among the most recent. A paper from the Department of Banking and Finance at Zurich University and the Oxford Sustainable Finance Group at Oxford University tries to simplify around a set of ‘red flag indicators’ that are common across many of the 28 transition plan disclosure and assessment frameworks they reviewed. They have design the framework as a tool that can be applicable at scale using AI.

For financial institutions, this perspective is highly relevant because there is a clear need for finance for both green and transition-related finance and very different thresholds for each type. Finance in support of transition plans is especially difficult because a financial institution may have a wide range of customers with transition plans and will be unable to review each one to assess its credibility. Instead it will fall back on the presence of a transition plan as a metric of its credibility.

The Transition Plan Red Flag paper outlines a set of simplified ‘yes/no’ items across a range of issues including emissions targets, governance, strategy, and tracking. Currently, the research has produced a concept note from analysis of the frameworks defined in a way that could be applied at scale across companies to understand how well the red flag indicators perform in separating credible plans from those with significant issues on either external consistency with science-based pathways or relating to internal consistency.

This is not the only resource being developed to use AI to assess the credibility of transition plans and deal with the scalability issue for financial institutions that have to navigate a tsunami of transition plans. There is unlikely to be a single tool that identifies greenwashing, and there will always be differences in expectations about what good transition plans include.

For financial institutions developing their own transition plans, and figuring out how to manage the impact of the credibility of their customers’ transition plans for pursuing opportunities and mitigating risk in financing the transition, this should be a wake-up call. The strength of the transition plan will be evaluated quantitatively.

The value of including qualitative statements in transition plans will become a primary for explaining discrepancies between what is drawn from the plan and compared against a framework by an AI bot. Most of the consumers of the transition plan will be doing so from the perspective of having it signposting red flags and won’t be satisfied by vague statements. Instead they will be looking for details about plans, target, execution and assurance. This will be a high bar for most financial institutions, even those that have been working for years on responsible finance.