Guest Post: How To Ensure Climate Intelligence Solutions Live up to Their Hype
BY: Mahesh Ramanujam
As was discussed at length during the COP26 climate summit in Glasgow last November, the private sector must step up the rate, scope and scale of its commitments to combating climate change if we’re to have any chance of achieving the emissions reductions targeted in the Paris Agreement.
Indeed, the growing number of issuers incorporating climate-related factors into their capital allocation decisions and capital raise strategies, as well as the concert of institutional investors who reward them for their efforts, are, together, a fundamental piece of the global decarbonization puzzle. And despite concerns over “greenwashing”, fortunately, there’s reason to believe these organizations appreciate this responsibility; they are preparing to deploy the resources that experts say is needed to finance roughly 80% of the hundreds of trillions of dollars needed to arrest and, ideally, reverse global climate change.
But when considering the urgent need to scale the decarbonization solutions for niche sectors and discrete energy applications that aren’t yet commercially available, perhaps most promising is the amount of money that investors are showering on the innovators behind tomorrow’s climate technologies, which experts say will yield upwards of 50% of the emissions reductions needed to achieve net-zero by 2050. Indeed, by the end of the third quarter last year, climate technology startups had raised a record $32 billion in VC funding alone, a nearly five-fold increase over the amount raised in the year following the Paris Agreement. And with inflows into ESG funds poised for rapid growth, especially into those with a climate focus, we can expect these trends to continue.
But how do we know whether organizations’ efforts, including their investments in and adoption of climate tech, are serving the climate, strengthening their positions and, as a result, reinforcing the incentive for more climate-aligned behavior?
This is what makes the rapid rise of enterprise climate intelligence platforms and services so important. Together, they are a class of climate tech that enables enterprise end-users to assess their present exposure to climate-related financial risks, track the impact of their climate-related investments and identify the assets and operations in need of additional attention.
The advantages these platforms offer their users, then, are clear. For financiers, a firm understanding of which managed assets are at risk not only helps with investment and divestment decision making, but also helps institutions avoid potential regulatory non-compliance. For credit rating agencies, overlaying a climate risk lens to their scoring methodologies and service offerings represents a sizable emerging revenue stream. And for corporates, knowing which existing and prospective business practices, procedures, initiatives and investments may undermine their sustainability credentials is as much a risk management imperative as it is a prudent investor relations and strategic growth tactic.
In short, climate (and emissions) intelligence is business intelligence, helping users to mitigate risk to their bottom lines while maximizing positive climate and environmental outcomes.
There’s just one problem. At the end of the day, these digital platforms are commercial products. The firms bringing them to market are competing for an enormous but nonetheless finite carbon abatement market. As a result, these platforms and services are divergent, each with their own bias. The insights they generate depend on the outputs of machine learning algorithms that may, among other things, be developed independently of one another and be constructed using irregular and incomplete guidance from climate-risk disclosure initiatives. As a result, these platforms and services may be fed with different data inputs, apply differing weights to whatever data is selected and impute unique substitutes for whatever data is relevant but unavailable.
This divergence is apparent across industries, including in the commercial real estate (CRE) sector where I’ve spent the majority of my career. A recent analysis by Morgan Stanley found low correlation among the climate-risk assessments that different platform providers made for a sample CRE portfolio. Providers were inconsistent in their incorporation of transition risks in their models, and largely failed to account for both asset- and community-level resilience measures, as well as the indirect impacts of their supply chains or local governments.
In a perfect world, though, diffusion of these solutions across sectors will mean companies no longer have to guess which capital goods to prioritize, which products to redesign and which markets to either pursue or leave behind. But without interoperability between these platforms, though, that potential will remain just that—potential.
For the CRE sector, often derided as slow to adopt transformative technologies, the uptake of these platforms and subsequent use of their data-driven insights to inform investment decisions is objectively necessary. But the lack of comparability and compatibility between a growing number of commercially available solutions stands in the way, leaving prospective end-users confused and discouraged.
The divergence of these platforms will act as a roadblock to more widespread adoption. We’ve seen this movie before. Universal disclosure of climate-related financial risks, and ESG performance in general, remains an ambition partly because organizations tasked with doing so are either ill-equipped or don’t know which of the seemingly innumerable voluntary (and competing) disclosure frameworks they should report to.
This is why the formation at COP26 of the International Sustainability Standards Board (ISSB), which will support the convergence of these frameworks, namely in their definitions of sustainable investments and emissions reductions, is a necessary step in the right direction.
Likewise, governments, as well as trade associations and industry certification organizations, have a unique opportunity to drive a similar convergence in the models and data used to inform climate intelligence and carbon accounting platforms and services.
Requirements for regulatory filings can be reformed to dictate a uniformity of data outputs that enables comparability, and guidelines for procurement of these solutions—produced either by the government itself or through public-private coalitions—can limit the discretion employed by prospective users. Trade associations and especially industry certification organizations can develop voluntary, performance-based incentives for adhering to strict standards for climate risk assessments, or at least establish a basic set of climate risk issues member organizations should evaluate and corresponding outputs their assessments should include.
In effect, what’s needed are standards. Whether they come from government regulators or industry membership organizations, climate risk and carbon accounting assessments must be comparable. Irregular results make for irregular impressions among end-users and their investors.
Fortunately, we’re seeing movement on this front already this year. A consortium of 19 global banks and the Risk Management Association, for instance, has recently announced it’s working to develop standards for measuring and managing climate risk in the financial sector, following earlier moves by regulatory bodies in the U.S. and U.K. to offer updated climate risk-related guidance for financial firms.
Come what may, though, it’s imperative these solutions offer reliably comparable assessments of risk exposure and emissions profiles so that subsequent assessments on the ROI of any implemented remedies may be comparable, too. Without it, we risk dispiriting otherwise well-meaning investors and misallocating capital we can’t afford to waste.
About the author:
Ramanujam is the former President and CEO of the U.S. Green Building Council