S&P Global Inc. (SPGI) Earnings Call Transcript & Summary

Hello, everyone, and welcome to today's webinar. My name is Steven Bullock, Global Head of Research and Methodology, S&P Global Sustainable1. It is my pleasure to moderate today's webinar entitled: Linking nature to Physical Risk: Climate Science and Adaptation Planning. Before I introduce my guests, a few housekeeping items to quickly run through. We recognize that the topic of today's webinar is of great interest to you all, and we want to do this in an interactive way. So at the bottom of your screen, you should see a row of widget icons. These icons will allow you to interact with us throughout the session. I would like to point out the Q&A widget, which can be used to submit questions to the panelists. I would also like to point out the survey widget. Please take the time to fill out our short survey after or during the webinar. We really, really do value your insights. Additionally, you can find more content surrounding the topic in the resource widget. The webinar is being recorded and a version will be available shortly afterwards. [Operator Instructions] So let's move on to our panelists, and I'm very pleased to introduce our 3 subject matter experts today. We're being joined first by Terence Thompson, who's the Chief Science Officer at S&P Global Sustainable1, part of our Climate Center of Excellence. We are also joined by Carter Ingram, who is the Managing Director at Pollination; and Nicola Ranger, a Director of Global Finance Group at the University of Oxford. So just before we get into the discussion, I wanted to set a little bit of context for the next hour. First of all, it's long established that climate change and nature and biodiversity loss are systemic risks that need to be tackled together. At the same time, climate science is playing a critical role in advancing our understanding of natural systems and the interaction between physical climate hazard nature and the economy, and most importantly, how these translate into risks and opportunities for market participants. Recognizing the importance of science at S&P Global, we recently launched a Climate Center of Excellence, which is a group of world-class climate scientists and strategists working to advance S&P Global's work on long-term climate environmental and nature research and methodology development. But the need for decision-useful metrics on climate and nature-related risks is bigger than ever before, propelled by regulatory reporting requirements around the world, and finding the right balance between scientific rigor and decision-useful applicability is an ongoing challenge for the industry. So in this webinar, we're going to be discussing a few areas. First, the critical role of science as a foundation for climate risk analysis, how we're bringing climate and nature-related risks together in scenario analysis, the importance of decision-useful metrics, and the role of regulation and future areas of innovation. So that's all for me. I'm going to now come to you, Terry, first of all, on this first piece around the critical role of science. And I wondered if you could talk a little bit about how S&P Global Sustainable1 is enabling these advancements -- in science-driven research and methodologies to provide actionable insights on climate-related risks and opportunities.

Yes. Hello, everyone. Thank you for joining today, and I hope you find this interesting and informative, and stimulating a cascade of questions and interests on this topic. So Steve has mentioned the Climate Center of Excellence at S&P Global Sustainable1. The Climate Center of Excellence, which I lead, is a catalytic effort across various teams at S&P Global. And our primary role is to be sure that the latest science influences all of our models, all of our quantifications, all of our methodologies. The role of science, particularly with regard to climate change and nature risk, is central. I think we should be all aware that we are operating at the boundaries of human knowledge with regard to climate at the boundaries of human knowledge with regard to the ecosystems that underlie natural capital, and at the boundaries of knowledge with regard to how the economics and finance associated with climate change and nature risk can influence and improve the situation. So that's what we mean by the role of science broadly put, not just physical science, but all of the sciences that can contribute to facing up to this challenge. I think I'll continue with a slide or two to give a flavor of what we are doing at S&P Global. There's too much on this slide to discuss in a few minutes. But I'd like you to take away essentially the idea that there are multiple efforts going on concurrently. Over on the left-hand side of the slide are reports recently published publicly available that have to do with the unpriced environmental costs, the externalities of human activities that deal with nature and biodiversity risk, the second report, in much more detail and are looking at dependencies -- are looking at impacts on nature and dependencies on nature in a qualitative and now beginning to be a quantitative way. In the middle, some thought leadership work on how sectors link, how sectors are affected by the interaction of physical and ecosystem risks. And on the right-hand side of this page, new work on how physical hazards impact specific ecosystems. In particular, on the right-hand side of the page, we are building upon an already very robust in-house, science-driven, data-driven climate risk analytic capability that happens to be known as Climanomics. But the point is that this platform is built upon the latest Earth system model data, the same data that drives the IPCC reports and literally hundreds of other scientific efforts. And this data is used to create very specific physical hazards to couple those physical hazards and the change in their levels through time across the planet to specific impact functions that measure the impact of those hazard changes due to climate on specific assets. There's a lot of technology in addition to the science behind this platform. But this platform and this methodology is now being extended. The lower right-hand corner gives you a couple of examples of how this technology is being extended into the nature risk and more specifically into the risk of climate change and its impacts on various types of ecosystem services. I'll move on to the next slide. I won't take time to go into depth but just to describe. Essentially this the first component, the measure of the unpriced externalities. In essence, this is a first order measure of how much current economic activities depend upon natural systems. The second component has to do with that nature and biodiversity impact assessment, which is now being assessed by sector. That's what these charts to the lower right mean assessed by sector. And additionally, the dependencies, the relative dependencies are being assessed by sector and by ecosystem service type. The next slide, again, is just blowing up or expanding the maps that I showed you earlier. These happen to be marine biomass projections, a current state in the center of the slide, a future state under one of the more threatening climate scenarios, so SSP 585 in the jargon. And this is looking at oceanic biomass. And though it's not immediately visible, perhaps there are changes here, particularly off the decreases in marine biomass, particularly off the Northeastern shores of the North American continent, also to the east of Norway and Sweden and so on. This is only an example of the connection between the Earth system model data that drives the platform that I described earlier. Oops, didn't mean to do that. Sorry about that. See, where are we? But other output variables include, as you can see in the gray box on the left, leaf area index, soil conditions, burnt area, groundwater, surface water. So this is to give you a flavor of how these connect to ecosystem services in more detail. Similarly, since the previous slide was showing you these types of metrics for oceanic areas, here are a couple of metrics for land areas. On the left, up here, current and future for soil temperature. On the right, up here for C3 grasses, a particular type of grass. Leaf area, current and future. So this is how we are coupling the already existent Earth system model data to essentially ecosystem services and coupling that back to the reports that I described for you earlier. We're bringing to bear the modeling capabilities, the quantification capabilities that lead us -- will lead us to be able to measure worldwide differentiation at the highest possible resolution, impacts on various types of ecosystem services. And that summed up, will be a way of quantifying nature risk. Back to you, Steve.

Thank you, Terry. Fascinating work. Just as a quick follow-up question, perhaps you could just outline from -- in your opinion, what are some of the challenges in bringing together insights on physical climate risk and nature risk, particularly over longer-term time horizons?

Well, I think the key challenge is related to the intellectual frontiers, the scientific frontiers at which we're operating. Nature risk has many, many layers. And the further one goes down into the details of ecosystem services. The greater the interaction between various components, possibly the greater the uncertainties. And so I think realizing that certain parts of nature risk are already currently included in Earth's models. For instance, because land cover, because leaf canopy health is important in interactions of the land surface with the atmosphere, we already have fairly sophisticated models for dealing -- for essentially measuring how is the interaction between land and atmosphere occurring, and what is that contributing to climate change. Similar things go on for interactions between land and ocean, between ocean and atmosphere and so on. That's what's built into our system model today. But the details of the underlying ecosystems, particularly as we go further down into the hierarchy of ecosystems, those are not included yet. So we have to build new models or rather we have to couple specialized models to Earth system models in order to measure -- quantify the impact on various types of ecosystem services and, therefore, on nature risk. And again, uncertainty in all of our modeling is a key challenge. Fundamentally, decision-making under uncertainty is not one of humanity's strengths. But we must quantify the uncertainty, we must become comfortable with expressing the uncertainties, differentiating the different types of uncertainty. And coupling that with practical decision-making techniques. I think those are the key challenges in this area.

Thank you, Terry. And we'll certainly come back to that last point you made around ensuring we have that balance between scientific rigor and decision-useful metrics. But before we do that, Nicola, I'd like to come to you next. While we're talking about sort of bringing climate and nature together from a forward-looking scenario perspective, I wondered if you could talk a little bit about how the work that you're doing at The University of Oxford is addressing this interaction between climate, nature, economics and finance?

Thank you very much, and thank you for the invitation to join you today. So from our work, we really find this absolutely critical to think about how nature and climate interact. And I would certainly argue that if you're not thinking about these nature feedbacks, actually, you're not fully assessing climate-related risk. So we worked with the NGFS over the last year as well as in the U.K. with the FCA and Treasury to calculate risks to the U.K. economy. And for that, we basically took a step-by-step approach. So we looked at what are all of the key types of nature-related risks that could impact on the U.K. economy, and we came up with almost 30 of them. Everything from sort of big food price shock, to pandemics, antimicrobial resistance, to sort of issues around water quality and air pollution that relate to environmental degradation. So we looked across the board. And then similar, as we just saw from Terry, looked at a sector-by-sector approach and looked at what are the key ecosystem services on which those sectors are depending, how are those being degraded and how does that transmit through to production of those sectors. And what you can see is that this very strong interaction with climate, so a lot of these risks have a big water component to them. So that is a real sort of driver of that interaction. And then we looked at a scenario-based approach and looked at what is the impact on the economy overall. And there, we looked at how, in particular, that sort of gradual degradation of nature can be aggravated by a big climate shock, like a big drought, for example. We also then put that with the NGFS scenarios. But overall, we found that what you can see is about nature is sort of doubling the risk of physical climate change. So this is a big, big feedback. It's not something that you can ignore. And it works both at the asset level, at the sector level, but also at that macroeconomic level being transmitted through supply chains, in particular, for example, in prices of key commodities. So that's sort of key conclusions that came out with. And then from an adaptation point of view, again, it means that if we think about how to manage these risks, we need to think both locally but also at the macro scale about how we can prepare ourselves for these types of shocks.

Maybe just as a follow-up for that, in your opinion, what is the holy grail for long-term scenario analysis that considers that interaction, the interaction between climate, nature, the macro, the micro? Is there something we're driving towards here from a long-term scenario analysis perspective?

Yes. So I think -- so the way that we reached it was really to think about those transmission channels. So trying to look at -- because I think our challenge in this space is you can come out of almost an infinite number of scenarios, which is just isn't practical. So to think about it from those key transmission channels that can impact either an asset level on economy. So the work that we did for the U.K., we boil that down to sort of 3 scenarios that we felt kind of represented the space of what could happen. One scenario was related to health. So it was an AMR, antimicrobial resistance related scenario. One was related to a big international supply chain shock. And the other one was related to domestic risk in the U.K., domestic soil erosion, for example, and water policy challenges. So in that way, we sort of sampled the space. But I would definitely say the holy grail in this area, I don't think there's one holy grail. But it's really to think, first and foremost, about the sort of narrative scenarios and then -- and sort of try to look at what is the space of what could happen. So don't focus on trying to be precise, but trying to be robust in your selection of scenarios, and then really sort of classically stress test what could happen and bringing in expert opinion as you need to as well as models.

Fantastic. So both you and Terry have kind of made the same point here, is that it's important, obviously, that we have that foundational scientific evidence, but we really need to focus on, on how we're focused on decision-useful metrics. And that's a really nice segue to you, Carter. And I wondered on this theme, whether you could talk a little bit about the sort of the main use cases that you're seeing for climate, nature, intelligence for the organizations that you're working with, at Pollination? And I guess what progress is being made in terms of integrating this into decision-making?

Yes. Thanks, Steven, and thanks for the opportunity to be a part of this conversation. It's really interesting so far and a really important discussion as well. So Pollination, for those of you who aren't familiar with us, we're an investment and advisory firm focused on nature and climate change mitigation and adaptation. And we help our clients who include a range of different types of corporations and financial institutions, as well as governments and NGOs. We help them make their transition to a net zero nature positive future. And I'm going to speak a little bit more from the perspective of the work we do with corporates and financial institutions, for the most part. And I would say the main use cases we're seeing for climate and nature intelligence include helping our clients develop transit climate and nature transition pathways, which could include setting goals and targets. It could include developing scenarios that are relevant for their business, including decarbonization pathways. And very importantly, what some of the cost and benefits of those different scenarios could be. And what the outcomes for nature or climate would be as well. And then where we try to focus a lot of our efforts is helping our clients identify and develop solutions that can help make that transition, whether they be nature-based solutions for climate change mitigation or new business models or products, or new investment opportunities. With respect to nature, where I spend most of my time, I would say the majority of the work we've been doing recently has been more specifically helping clients, especially in the food and fiber space, understand what their impacts and dependencies are on nature in alignment with the TNFD, understanding what their deforestation risk might be as well, and translating that into financial risks and opportunities. And we can come back to this, but I think that latter point is one of the more challenging areas where we need a lot more data and translation. And then helping our clients, as I mentioned earlier, kind of develop their strategies around protecting and restoring nature that are going to be aligned with business outcomes. So I would say that's the -- those are the primary use cases. One thing that we're starting to see a lot of, and I think it's relevant to this conversation, and some of the previous comments that Terry and Nicola mentioned, is we're seeing, because I think TNFD is emphasizing in particular, this location-specific analysis, the Leap process, we're seeing a lot more attention on the landscape scale, the landscapes in which operations and supply chains are located. And increasingly, companies want to take a landscape approach to understanding how the broader ecosystems in which they're embedded may impact their long-term business resiliency. And again, I think that's where a lot of data and climate intelligence is needed because a lot of companies don't have that information in-house. So I'll pause there and see if you want to have any follow-up questions to that.

No, it's great to hear that the experience of the organizations that you're working with in tackling the climate and nature, I guess, your transition planning and scenario planning. Has there been any difference in sort of adoption between the two thematic areas? Has the experience for nature been similar to the experience for climate? Or is there anything you can share with that in that regard?

Yes, I think that's a great question. I mean as probably most of us know, the adoption and use of climate data, especially by businesses and financial institutions, is a few years ahead of businesses and financial institutions using nature data and information to make decisions. And so I would say nature is lagging behind climate in that respect. I would say -- and this really applies to both, but I'll emphasize this more in the context of nature. I think when it comes to actually integrating nature data into decision-making, there's -- we've heard from a lot of our clients and a lot of the financial institutions and investors we speak to that there are some significant barriers from going -- from -- tremendous amount of nature data that's out there to translating it into metrics that are relevant for business decision-making at the scale at which decisions are made. And that includes translating nature data and different scenarios into outcomes with respect to profitability, returns, risks that are critical metrics that a business would use to make decisions. And I think we're lagging behind climate in that, although I wouldn't say that climate -- the climate data is perfect for supporting those kinds of decisions either, but I do think nature is lagging behind. Because most of the attention on nature from businesses and financial institutions has really increased, I would say, in a new way in the past few years, especially thanks to the TNFD and the Global Biodiversity Framework.

Fantastic. I'd love to come back to that point you made there as well around -- I guess, also the perceived complexity of nature data and the translation that's required into financial materiality or financial impacts information. But before that, I wanted to kind of talk a little bit about the role of regulation and also future areas of innovation. So coming back to you, again, Carter, for the use cases that you've just described, what are the current gaps that you see from a sort of data or technological perspective?

Yes. I mean, I think that some of the big gaps I touched on a little bit, I think one is going from -- and I'm a scientist by training as well. So I think there's -- I appreciate how the scientific advances we've made that, I think, Terry touched on -- touched upon with respect to our understanding of ecosystem services, a wide range of ecosystem services and the benefits and values that they provide to society. Where I think the gaps are going from understanding the value of ecosystem services and translating that into metrics that a business can use to make decisions about their business operations, supply chains, et cetera. So I don't think we -- what we're hearing is a lot of businesses and investment institutions don't yet have those decision-useful metrics. And some of that, I think, is related to the scale at which a lot of nature data is collected. Sometimes the spatial scale and the temporal scale, for different aspects of ecosystems and services just don't align to the scale at which business decisions are made, spatially or temporally. And I think that's one barrier. But I do think that a lot of focused effort to bring together scientists, analytics providers, translators and financial institutions, investment institutions and businesses to really understand what are some of -- why are some of those data gaps and bottlenecks still there and how do we get beyond that to really get to some of those decision-useful metrics like profitability, risk and return.

And do you think regulation, especially around reporting requirements and standards will help close some of those gaps?

Absolutely. I mean I think if you just look at the EU and the deforestation regulation, I think has catalyzed -- at least from what we've seen, there's a whole suite of data and tech providers now that are offering services around understanding your deforestation risk throughout your supply chain. And that's, I think, been catalyzed by the EU regulation. Even without regulation, we have seen just an explosion of providers that are helping companies understand their impacts and dependencies on nature, and supporting alignment and reporting with TNFD. And I think if there is regulation, that would only increase. And I think we probably -- we've seen this across the board, regulation is really needed to get to scale with respect to reporting around nature and climate.

Fantastic. Thank you, Carter. Terry and Nicola, I'm going to come back to you now with the same question. Perhaps, Terry, to you first. We've heard from Carter the use cases, some of the gaps and barriers. In your perspective, Terry, what are the advances in data or science or technology that you see as the most important in terms of serving those corporate and investor use cases in the future?

Well, echoing some of the themes that Carter just summarized, the way I see it, higher resolution data; observational data, as in remote sensing satellite data; and field observation data, at higher resolution, both temporal and spatial is a key -- advanced key gap. We need more of that. Particularly as she also mentioned, because we're being asked to provide information that's decision relevant, and that usually means that it needs to be as specific to location as possible. A big challenge on the science side. I've already mentioned quantifying uncertainty, which can be quite complex, different types of uncertainty. There's a bunch of jargon around that epistemic and aleatoric and so on and so forth. But nonetheless, being able to quantify the different sources of uncertainty as we move towards decisions. And beyond uncertainty, I think there is a challenge that I'll call the cross-disciplinary or the multidisciplinary challenge. Much of the academic world, much of the nonacademic world is stovepiped. People get rewarded for having very specialized knowledge about very specialized things, and not very many people get rewarded for crossing disciplinary boundaries. But as you can see, it's just so obvious that climate change, nature risk, the economics of both are so multidisciplinary that, I think, a science challenge is integrating across those disciplines. Finding the bridges, finding the collaborations, nurturing the collaborations, which are not going to provide immediate results, they're a barrier simply to having basic conversations about what's this metric mean, how do you use it, where does data come from and so on. I think also there's a challenge in realizing that there are, with a few exceptions, markets for ecosystem services don't exist. Therefore, we don't have prices. Therefore, we don't actually have values. So there's this value challenge, which there are various ways of addressing. But realizing that we don't have markets to help us decide on values makes the economics of ecosystem impacts, ecosystem risks, quite challenging. This is not an old problem. This problem has been around for a couple of centuries with regard to natural resource economics and environmental economics. There are ways to address it. But it is different from situations in which we have markets to set prices, asset values and so on. I'll leave it at that. Those are some of the gaps or challenges that I see.

And what about the role of regulation, Terry, in addressing some of those?

All right. I'll be a little bit flip. I think regulation is essential. It can help us a lot as long as it doesn't confuse us. I've seen examples of regulations that were written within, what I will call, from a scientific perspective, insufficient scientific specificity. And so there was -- their metrics are cast into enormous baskets. Some metrics don't even belong in the same basket. Metrics are insufficiently well defined. So I would be asserting that further earlier in the regulatory process, there'd be as much scientific information as possible to help keep the regulation clear so that there's more clarity and less confusion in how to interpret the regulation and apply it.

Thank you, Terry. So Nicola, the same question to you then. What are those advancements and the role of regulation. If you could comment on that.

Sure. So totally agree with the points from Carter and Terry. I would add on -- so from our work, we see that actually around half of these nature-related physical risks are actually coming through supply chains and through international supply chains. So I think actually there is one of the -- where we need most effort, both in terms of greater disclosure of that sort of supply chain and asset level information, but also a better understanding of those risks. And for example, the price impacts of that. Again, we often -- when we go to look at these physical risks, we often think about just the asset level risk, how is the property affected by a flood or something. Actually, from our work, that's not the thing that keeps me up at night. It's these big supply chain risks. So I would say that we need more focus there, and I think that regulation or more disclosures in that area, more availability of data in that area can help and there's lots of innovation and data in that area, which I think will help. I just want to touch on the other side of the picture, though, as well. So I know we've been talking a lot about the physical risk, but it's also the transition risk associated with nature, which will link obviously to physical climate risks as well. And there, I think for us, actually, that's where we see the biggest uncertainty, what does nature positive actually mean for an economy? Which we broadly know which sectors will be affected, but when and how? Where is there substitution potential? Where are there opportunities? We certainly hope to see as many opportunities as we will risks in a nature-positive transition. And I think that's where actually there's a lot more work needed to see which are the -- who are the winners and losers in this and how do we assess that. So we do a lot of work analyzing disclosures. I know S&P does a huge amount of work in that area as well. But trying to see, based on company's disclosures, who might we say are more winners and losers in this space. I think that's an area we need to focus. And again, more disclosure information can really help that.

Yes. I can't agree more with that. I think having that view of risks and opportunities, transition risk and opportunities for climate and nature is critical. And I think one of the challenges perhaps is that what does nature positive look like? We know what 1.5 or 2 degrees or 3 degrees looks like from a climate perspective, but what does that mean for nature? And I think perhaps that's one of those areas that needs a little bit more transparency from a scientific perspective.