December 4, 2019 – 427 REPORT. Scenario analysis is an essential yet challenging component of understanding and preparing for the impacts of climate change on assets, markets and economies. When focusing on the short term, the warming and related impacts we have already committed to calls for scenarios that are decoupled from economic and policy activities and instead focus on the impacts that are already locked in. This report explores which impacts are already locked in, identifies how Representative Concentration Pathway (RCP) scenarios fit into the conversation, and describes an approach to setting up scenario analysis for near-term physical climate risks.
As the effects of climate change increasingly threaten financial stability, investors and regulators are seeking to understand what impacts lie ahead, and calling for an increase in physical climate risk assessment and disclosure in line with the Task Force on Climate-related Financial Disclosures (TCFD). To assess the scale of financial risk posed by physical climate change it is important to quantify risks under different climate scenarios. How will changes in extreme weather patterns, longer droughts and rising seas differ under various scenarios? Answering these questions through scenario analysis helps uncover the range of risks, allowing investors to identify assets and markets that are more likely to become stranded over time and to begin developing forward-looking resilience strategies. However, science-driven, decision-useful scenario analysis poses many challenges for businesses and financial stakeholders today, due to complex feedback loops, varying timescales, and multiple interacting factors that ultimately determine how global climate change manifests.
Figure 2. Distribution of daily extreme temperature changes in 2030-2040, expressed as a percent change, relative to a baseline of 1975-2005 under RCP 8.5. This map shows statistically downscaled global climate models averaged together, for this time frame and scenario. NASA Earth Exchange Global Daily Downscaled Projections statistically downscales climate model outputs to a ~25 kilometer resolution (see full details here) White areas are excluded because they lack potential for significant economic activity.
This new report, Demystifying Climate Scenario Analysis for Financial Stakeholders, explores which physical impacts are already locked in, identifies how Representative Concentration Pathway (RCP) scenarios apply, and describes an approach to setting up scenario analysis for near-term physical climate risks. Scenario analysis is often approached from the perspective of transition risk, where policy developments and greenhouse gas (GHG) emission targets are the key drivers of risk pathways over the near-term, in the next 10 to 30 years. Physical risk, however, requires a different approach. Impacts over the coming decades are largely locked in, making the emissions scenarios less relevant. Unlike transition risk, GHG emission pathways play a minimal role in the behavior of the near-term climate and GHG emission pathways only begin to meaningfully influence global temperatures near mid-century. The uncertainty in physical climate risks in the near-term is driven by uncertainty in physical processes, rather than in policy decisions.
For organizations looking to construct physical climate risk scenarios for risk management and strategy purposes, it is critical to understand the scientific phenomena driving our plausible climate futures. This report outlines an approach called percentile-based analysis, which allows users to explore the range of potential outcomes based on climate model outputs within a single RCP. This offers a flexible, data-driven approach, suitable for portfolio-level screenings, reporting, and in some cases, direct engagement with asset managers.
July 29, 2019 – 427 FACTSHEET. In 2015 France laid the groundwork for legislating climate risk disclosure with Article 173 of its Energy Transition Law, mandating that publicly traded companies and asset managers report on their physical and transition risks from climate change. Building on its track record as an early mover, France’s financial regulators are now actively involved in national and international endeavors to frame climate risk as a financial risk and determine the most effective response. Staying up-to-date on these developments will provide early indications of regulatory action to come. This factsheet on regulatory developments in France provides background on France’s sustainable finance agenda, outlines key actions and highlights upcoming dates to remember.
France’s Art. 173 helped build support for the Taskforce on Climate-related Financial Disclosures recommendations, prompted firms to begin disclosing climate-related risks early and set an example for other nations considering regulation on climate risk disclosure. Since this landmark legislation, French financial regulators have become engaged on addressing financial risks from climate change and the Banque de France was a co-founder and provides the Secretariat for the Network of Central Banks and Supervisors for Greening the Financial System (NGFS), which is focused on propelling the transition to a low-carbon and sustainable economy. By providing the Secretariat for the NGSF, the Banque de France identifies itself as a key player in international efforts to address climate risk. This factsheet, Financial Climate Risk Regulation in France, summarizes France’s stance on the financial risk of climate change, notes key regulatory players and highlights recent and upcoming regulatory action applicable to financial markets.
JULY 8, 2019 – LONDON, UK – Four Twenty Seven receives Wealth & Finance Magazine’s Alternative Investment Award for Best in Climate-Related Economic Risk Reporting 2019.
Wealth & Finance Magazine recognized Four Twenty Seven among the winners of their 2019 Alternative Investment Awards. For six years these awards have acknowledged firms and individuals that positively shape the industry’s growth. “Historically considered an undervalued industry, the alternative investment has grown over the past few years. Behind this prominent growth and success, are the leading lights whose innovation, dedication and inventive ways has delivered some award-worthy results,” Wealth & Finance writes.
The Best in Climate-Related Economic Risk Reporting award highlights Four Twenty Seven’s climate risk scores for listed instruments and on-demand scoring of real assets, that assess financial firm’s exposure to physical climate risk and inform risk reporting. Our analysis leverages best-in-class climate data at the most granular level and scores assets on their exposure to physical climate impacts based on their precise geographic location. Investors use this data to drive investment strategies, forward-looking risk management and TCFD/risk disclosures.
In this second installment of our blog series of scenario analysis, we focus on how investors can start exploring impacts on portfolios of listed equities/fixed income with existing climate risk analytics. The series provides our current reflections on how corporations and financial institutions can integrate physical climate risk into scenario analysis. The first installment, on foundations, focuses on important characteristics of climate science that affect how climate data can be used to inform scenario analysis for economic and financial risk. A forthcoming post will discuss scenario analysis at the asset level for real asset investments and corporate facilities.
Scenario Analysis Serves Different Purposes
Scenario analysis serves different purposes for real asset investors and for equity or fixed income investors. When looking at a single real asset, scenario analysis can be used to inform very concrete decisions regarding the asset, working directly with the asset operator: whether and what flood protections to put in place, insurance requirements, anticipated impacts on operational costs from water and energy consumption, etc.
In contrast, for an equity or fixed income portfolio, investors’ influence on the resilience of the underlying asset (e.g. a corporation or a sovereign entity) is much more limited. In a previous publication we discussed the importance of shareholder engagement with corporations as a key channel for investors to help raise awareness of rising risks from climate change, and encourage companies to invest in responsible corporate adaptation measures. Investors, however, would be hard pressed to run scenario analysis on individual portfolio companies themselves, and disclosures from corporations on scenario analysis remain weak and fragmented.
Meanwhile, prudential authorities in Europe have been signalling expectations that insurers and banks perform scenario analysis on their portfolio to examine potential impacts of climate change, to understand how different climate-driven outcomes might prevent the insurers and lenders from meeting their financial obligations. Most recently, in April, the Bank of England Prudential Regulatory Authority (PRA) released a proposed set of specifications for scenario analysis that includes some simplified assumptions on climate impacts on financial portfolios.
In this piece we examine how available climate risk analytics can be leveraged to inform early attempts at developing stress test assumptions and simulate potential outcomes on investment portfolios aligned with the relative exposure of corporations by sectors and by regions.
Climate Risk Analytics for Equities/Fixed Income
We leverage our data on corporate physical risk exposure to determine what assumptions can be made in this type of early stress test. In this piece, we analyze the climate risk scores for 1730 of the largest companies in MSCI All Country World Index (ACWI). This physical risk assessment is based on the exposure of the underlying database of about a million facilities globally.
We score each company on three components of physical climate risk: Operations Risk, Supply Chain Risk and Market Risk.
Scores are normalized, with 0 being the least exposed and 100 being the most exposed. (For more details, please refer to our previous report Physical Climate Risk in Equity Portfolios as well as our Solutions page)
In line with considerations of relevant time horizons and of impacts being locked in over the climatic short term (detailed in Part 1), our standard equity risk score data considers projected climate impacts in the 2030-2040 time period under a single RCP scenario, RCP 8.5 (the worst case scenario, also known as business as usual), but leverages several climate models.
From Climate Hazard Exposure to Financial Impacts
Studies of how physical climate hazards translate into financial impacts at the company level are scarce. While a growing body of research explores the complex relationships between climate hazards and economic impacts, which vary by sector and by region, academic research on the relationship between climate events and corporate/stock performance, at scale, is still limited. Our approach focuses on leveraging what can be estimated in a robust, data-driven way: relative exposure of companies to climate hazards.
Our analysis of global corporations shows the relative exposure of industries to climate related risks across all three dimensions: operations risk, market risk and supply chain risk (Table 1). This table shows the sectors with the highest exposure, including manufacturing, infrastructure (utility, energy, transportation), and industries with high dependency on natural resources (food, apparel).
Table 1. Industries most exposed to physical climate risks . Source: Four Twenty Seven.
Services, not shown in the table, are not only less exposed, they’re also far less sensitive to changes in climatic conditions, with the exception of the financial sector, which holds the risk of all the other sectors in its investment, lending or insurance portfolios. Note that real estate is not included in this analysis, but data on regional exposure in that sector can be found in our white paper on climate risk in real estate.
These differentiated impacts by sectors can lay the foundations for a stress test, as industry risk levels can be used to set initial assumptions on sector-wide impacts. Following the example set out by the Bank of England’s PRA, for example, investors could assume that sectors with high exposure might see a 10% or 20% drop in value, whereas sectors with medium exposure would see half of that impact. These assumptions are not intended to substitute for financial impact modeling, but provide a shortcut to test how a portfolio might perform under climate-driven duress.
Drivers of Exposure to Physical Climate Risk
While some sectors overlap with those examined in scenario analysis exercises for transition risk, such as utilities and energy, other sectors with high exposure are not typically included in scenario analysis, like tech manufacturing or pharmaceuticals. Understanding the nuances of the risk pathways in each sector and their relative exposure to different hazards is critical to refining assumptions and developing models that can quantify value-at-risk by sector with some accuracy.
Manufacturing companies in the tech sector rely on complex value chains that can be interrupted by extreme weather events, particularly in Asia, which is a region highly exposed to typhoons and extreme precipitation. They also often produce expensive and water sensitive products using costly machinery and can incur costs and damages from extreme events on site. Pharmaceuticals are particularly exposed because of the prevalence of their manufacturing in water-stressed regions (India, California) and regions highly exposed to hurricanes & typhoons. For example, damaged manufacturing sites in Puerto Rico had rippling impacts on pharmaceutical operations globally during Hurricane Maria in 2017. Pharmaceuticals is also one of the groups with the most weight in the MSCI ACWI, making this exposure particularly significant (Fig 2).
Figure 2. The average company risk score by GICS Industry Group, with Operations Risk on the y-axis and Market & Supply Chain Risk on the x-axis. Red represents those industries with the highest exposure, green represents those with the lowest exposure and the size of the bubble signifies an industry’s weight in the MSCI ACWI. Source: Four Twenty Seven.
In the utility sector, the nature of the exposure is very different from that observed in transition risk analysis: carbon neutral power generation can be as exposed as thermal generation – for example due to water stress or floods for hydro facilities. In addition, utilities rely on expensive equipment, such as cables, poles, fuel storage and pipes that are often exposed to severe weather and sensitive to extreme conditions. Their operations are also resource-intensive, relying heavily on energy and water for cooling. They can experience operations disruptions during peak energy demands or due to equipment damage during storms.
The exposure of the automobiles & components sector has been illustrated by recent flooding in Japan. Automobile companies rely on manufacturing processes and machinery that can be interrupted due to flooding or hurricane damage, but their reliance on employee labor also makes these companies vulnerable to the wider regional impacts of extreme events. For example, during Japan’s extreme flooding in July 2018, Mazda was forced to halt operations at some of its facilities that were not physically damaged themselves, because its employees could not travel safely to work.
Climate change calls for a better understanding of impacts of physical hazards on financial markets, which remains a topic largely unexplored. Yet as regulators push insurers and banks towards the integration of climate scenarios into stress testing, robust, data-driven views on the relative exposure of sectors or regions provide a helpful foundation from which to explore the potential impacts on equity and fixed income portfolios.
Over time, better data will become available as academic and industry providers develop models that capture the nuances of climate impacts on different industries and geographies, but also as companies make a concerted effort to disclose better data on their past and anticipated financial exposure to extreme weather and climate-related events.
Four Twenty Seven’s data products and portfolio analytics support risk reporting and enable investors and businesses to understand their exposure to physical climate risks across asset classes.
The TCFD Status Report published early June 2019 reiterates the need for corporations and financial institutions to perform scenario analysis in a context of uncertainty over climate risk. It notes that while about 56% of companies use scenario analysis, only 33% perform scenario analysis for physical risk. Even fewer firms (43% of those using scenario analysis) disclose their assumptions and findings. The report contains useful case studies, but most focus on transition risk.
Yet a growing number of corporations and financial institutions recognize the need to integrate physical risk into scenario analysis and to develop resilience strategies that address imminent challenges from climate impacts. For example, the most recent IPCC report illustrating the impact of 1.5˚C increase in global temperatures on mean temperatures, extreme temperatures, extreme precipitation and sea levels shows that there will be significant implications for economies even with a 1.5˚C increase in global temperatures. This is still a best case scenario compared to impacts of 2˚C or 2.5˚C warming.
Scenario analysis for physical risk is fundamentally different from transition risk in its challenges and assumptions. This blog series provides our current reflections on how corporations and financial institutions can integrate physical climate risk into scenario analysis. This first blog presents the Foundations, focusing on important characteristics of climate science that affect how climate data can be used to inform scenario analysis for economic and financial risk. The next blog focuses on Equity Markets, with concrete examples of how available data can inform financial stakeholders ready to start putting scenario analysis into action. A forthcoming post will discuss scenario analysis at the asset level for real asset investments and corporate facilities.
The physical impacts of climate change encompass a range of direct and indirect hazards caused or exacerbated by the concentration of greenhouse gases in the atmosphere. Previous publications such as Advancing TFCD Guidance for Physical Risks and Opportunities, for which Four Twenty Seven was a lead author, provide background on these hazards as they pertain to corporate value chains and economic activities. Further information is also available in Cicero’s excellent report, Shades of Climate Risk. Categorizing climate risk for investors.
Rapid developments in atmospheric and climate science over the past 30 years enable us to understand how these physical hazards will evolve over time due to climate change. Sophisticated global climate models project expected changes in key physical phenomena affected by greenhouse gas (GHG) concentration: heat, humidity, precipitation, ocean temperature, ocean acidification, etc. Like any other models, climate models have limitations in their accuracy and ability to correctly simulate complex and interrelated phenomena. However, it is worth noting that since 1973 models have been consistently successful in projecting within the range of warming that we have experienced in the past twenty years. More details on climate data and uncertainties from global climate models can be found in our report, Using Climate Data.
The Bad News: Impacts Are Locked In
Global climate models project different possible outcomes using scenarios called Representative Concentration Pathways (RCPs). RCP scenarios capture differing GHG emissions trajectories based on a representation of plausible global policy outcomes, without specifying the details of the underlying policies that could generate this outcome. These scenarios show that GHG emissions generated over the coming decades will influence the severity of impacts in the long-term, but also that we are already committed to some impacts through 2100 and beyond.
This is particularly noticeable over the “short term.” When looking at the next 10 to 20 years, projections for temperature and other physical hazards do not present significant differences under different emissions scenarios (Fig 1). This is due to the massive inertia of the Earth’s systems, and the life expectancy of the stock of greenhouse gases already in the atmosphere. To put it simply, significantly reducing GHG emissions is akin to applying the brakes on a rapidly moving truck. It won’t stop instantaneously. Even if we were to stop emitting GHG altogether, climate change would persist. In the words of the Intergovernmental Panel On Climate Change (IPCC), climate change “represents a substantial multi-century commitment created by the past, present, and future emissions of CO2.”
This is by no mean an invitation to give up on reducing GHG emissions. Quite the opposite. Emission reductions are critical to curbing long term impacts and avoiding irreversible effects to our environment (Fig. 2). But for organizations looking at climate data and scenario analysis for risk management and strategy, with a focus on the coming decade(s), this is a critical fact to understand.
Aside from RCP-driven scenarios, there is, of course, a broad range of possible increases in temperature (and other climate hazards) even when looking at the 2030-2040 time frame. These plausible differences are not so much policy-driven as science-driven, demonstrating the different possible responses from the Earth’s systems to the existing stock of GHG.
These differences have significant implications for businesses and investors. For example, a model of sea level rise developed in 2018 incorporates accelerated rates of melting and recent advancements in modelling ice-cliff dynamics to capture extreme risk of coastal flooding. The model shows the Atlantic rising by 1.2m (3.9ft) by 2060 on the Florida coastline, which would equate to widespread flooding of coastal properties with potential domino effects on real estate prices across the state (Fig 3). The ‘intermediate’ scenario, however, most often used for planning, predicts only a 55cm (1.8ft) rise in water levels. While reducing GHG emissions does reduce the risk of more extreme sea level rise millennia into the future, year after year, scientists find that the Antarctic is warming faster than anybody predicted, and there is increasing concern that the process of ice sheet melt may be too far advanced to be stopped.
Thus, performing scenario analysis where the key variable is GHG emission reduction targets may not be an accurate representation of the range of possible outcomes for the near future. Rather, looking at high and low warming projections across a large set of models to understand the range of potential outcomes (independent of the underlying RCP scenario) is a better way to understand potential risk. In other words, physical risks over the next 10-20 years are largely independent from policy decisions and emission pathways, and a rapid, orderly, effective transition to a low-carbon economy could still come with massive physical impacts as these processes are already under way, fueled by the past 150 years of GHG emissions.
The Worse News: Tipping Points
Another challenge is that climate scientists are not currently able to model certain possible impacts from climate change, commonly known as “tipping points.” Tipping points is a catch-all term for a wide range of phenomena that may accelerate feedbacks due to climate change, though the timing or probability of their manifestation is currently not well understood. The phenomena are known as tipping points because past a certain threshold, they may not be reversible, even with a dramatic reduction in GHG emissions. Tipping points of most concern to the scientific community are presented in this report from the Environmental Defense Fund.
Some tipping points catalyze “feedback loops” which can worsen and dramatically accelerate climate change beyond human control. Such is the case, for example, with melting ice sheets, which would not only lead to catastrophic sea level rise, but would also further heat up the planet as the poles’ albedo (reflectivity) is reduced after the ice disappears. Thawing permafrost could lead to massive amounts of methane, a particularly powerful GHG, to be released from the frozen tundra into the atmosphere (in addition to many direct impacts for local communities, infrastructure and ecosystems in the region).
Tipping points further reinforce uncertainty about severity and timing of these extreme impacts and the limitations of using RCP scenarios to understand the range of outcomes for physical risk.
Another source of uncertainty for physical climate impacts are knock-on effects, or ‘indirect hazards,’ from the primary expression of global warming (rising temperature and humidity), ranging from biodiversity losses and ecosystem collapses, human health impacts, impacts on crop yields, pests and soil, impacts on human society, increased violence, and rates of war and migration, etc. (Fig 4)
These indirect or second-order hazards are as relevant as first-order impacts to understand the implications of physical climate change on economic outcomes, but they’re not captured by RCP scenarios and many require stand-alone models that cannot easily be integrated into one clean set of scenarios.
Scenario analysis is often approached from the perspective of transition risk, where policy developments and GHG emission targets are the key drivers of risk pathways over the next 10 to 30 years. Physical risk, however, requires a different approach. Impacts over the coming decades are largely locked-in and are only marginally influenced by GHG emission pathways. In contrast, uncertainty looms large regarding how severe these physical hazards will be, and exploring a range of possible outcomes for physical risk, including looking at tail-risks, provides important insights for risk management and financial analysis. In summary, the current state of scientific knowledge and the nature of the Earth’s atmospheric systems call for the developments of scenarios that are decoupled from transition/policy scenarios and instead focused on key scientific drivers of uncertainty and risks that may be experienced regardless of policy decisions over the short to medium term (2020-2040).
While efforts to develop easy-to-use tools for physical risk analysis are nascent, organizations can still extract important insights from climate data and leverage estimates of risk exposure across portfolios. Our next blog in this series provides examples of how financial institutions can leverage data on physical risk exposure in equities to inform some early scenario analysis in equity markets.
Four Twenty Seven’s data products and portfolio analytics support risk reporting and enable investors and businesses to understand their exposure to physical climate risks across asset classes.