Climate Scenario Analysis in Finance: Key Takeaways from the Climate Financial Risk Forum's 2021 Guide

Introduction

Climate scenario analysis not only enhances our understanding of potential risks but also equips financial institutions to make resilient, forward-looking decisions in the face of climate uncertainty. This approach transforms climate risk from a distant possibility into an actionable component of strategic planning, helping institutions assess and address the impacts of climate-related risks.

Purpose and Scope of Climate Scenario Analysis

• Definition: Climate scenario analysis is designed to help financial institutions assess the financial impacts of climate-related risks. This foundational tool aids in identifying exposures, testing portfolio alignment with climate goals (e.g., Paris Agreement), and guiding strategy.
• Key Drivers: Scenario analysis is driven by the need to align with global climate goals, manage risks from regulatory developments, and improve disclosures. For example, it can help institutions prepare for regulatory requirements and demonstrate resilience in the face of climate risks.

The End-to-End Climate Scenario Analysis Process

The "End-to-End Climate Scenario Analysis Process" provides a structured approach for banks and other financial institutions to evaluate and manage climate risks. It begins by identifying climate-related risks and examining how they might impact financial stability through various transmission channels. The process involves developing climate scenarios based on socio-economic factors, technological advancements, policy changes, and temperature pathways.

Banks and financial institutions use these scenarios to define risk metrics, select assessment tools, and quantify financial impacts. Finally, the analysis guides strategic actions to mitigate identified risks, ensuring resilience in a rapidly evolving climate landscape. Details of each step with example is available in the Appendix

Figure 1: End to end Climate Scenario Analysis Process

Key Considerations in Scenario Selection

In climate scenario analysis, selecting the right scenarios is essential to accurately assess potential impacts and inform strategic decisions. Financial institutions can tailor their scenario analysis by choosing a range of scenarios to model both baseline and more extreme climate risks.

A. Baseline Scenario (or Relevant Counterfactual)

The baseline scenario serves as the foundational scenario against which the impacts of other scenarios are measured. Firms have flexibility in selecting a baseline depending on their analysis objectives:

• Hypothetical Pathway: This pathway assumes no additional climate-related risks beyond what is already observed, modeling a "climate agnostic" world without further transition policies or physical risks. For instance, the NGFS scenarios apply this kind of baseline, which excludes incremental risks.
• Probability-weighted Central Scenario: Here, firms use a scenario that represents their most likely forecast. This may align with market expectations ("priced-in" factors) or internal assessments of climate risk.
• Current or Pledged Policies: This scenario reflects global temperature rises under existing or pledged climate policies (such as Nationally Determined Contributions under the Paris Agreement). Firms may apply either a static or dynamic balance sheet assumption here to account for potential future shifts or changes to the balance sheet.

B. Strategic Scenario

This scenario aligns with a firm’s climate goals, such as portfolio alignment with a low-carbon future. For example, firms that aim to support a low-carbon economy might use a strategic scenario targeting Net Zero by 2050 (1.5°C warming) or by 2070 (2°C warming). For firms without a defined alignment strategy, using a non-hypothetical baseline as a default is an option until a strategy is in place.

C. Tail Scenarios

Tail scenarios introduce extreme but plausible outcomes that help firms prepare for more severe, less likely climate risks. Key tail scenarios include:

• Higher Transition Risk: This models disruptive or delayed policy action, which could lead to rapid economic shifts to achieve ambitious climate targets, such as 1.5°C or below 2°C warming.
• Higher Physical Risk: This scenario models high physical risks, such as those from unmitigated emissions, which could lead to significant warming (e.g., exceeding 4°C).

These scenarios act as “bookends,” with the real future expected to fall between these extremes. Advanced frameworks might include multiple scenarios along a spectrum of severity and likelihood.

D. Comparing the Scenarios

To test resilience, firms compare risk metrics under tail scenarios with those under a baseline scenario. However, firms need to be mindful of underlying assumptions, as high baseline physical risks may make transition risks appear more impactful. Ideally, firms include both transition and physical risks to cover all aspects comprehensively, even if analyzed separately. Given the inherent uncertainty in forward-looking analyses, transparency and careful disclosure are essential to avoid misinterpretation.

Overview of NGFS Scenarios:

The NGFS (Network for Greening the Financial System) provides a set of climate scenarios to evaluate transition and physical risks within financial portfolios. These scenarios are structured as follows:

In the NGFS climate scenario framework, scenarios are represented by bubbles that are positioned based on their levels of transition and physical risks. These scenarios are set within a “Middle-of-the-road” socioeconomic development pathway, known as SSP2. This pathway assumes that the world continues along a trajectory where social, economic, and technological trends align closely with historical patterns. SSP2 is one of five shared socioeconomic pathways developed by the academic community to serve as foundational contexts for climate scenario analysis.

The NGFS scenarios rely on three sophisticated and widely recognized Integrated Assessment Models (IAMs): these models capture the interactions between human activities (such as energy consumption and related emissions) and environmental responses (like temperature increases). Each IAM also incorporates the socioeconomic assumptions of SSP2, making them robust tools for simulating climate-related risks.

Together, the six NGFS scenarios and three IAMs create a matrix of 18 possible future pathways. These pathways produce baseline parameters that are then inputted into the National Institute Global Econometric Model (NiGEM), which calculates important macroeconomic variables such as GDP growth, consumption, investment levels, and interest rates across different regions and countries. This economic data, being more familiar and actionable for financial institutions, is essential for conducting climate-related risk scenario analyses tailored to specific internal needs.

Additionally, the NGFS framework includes a tool called the Climate Impact Explorer, which provides granular data on physical climate risks. This allows financial institutions to drill down into region-specific physical impacts, enhancing their ability to prepare for potential climate disruptions.

Figure 2: Climate scenario flow chart (developed by CFRF)

The following explanation follows the structure and insights from the Climate Scenario Flow Chart, developed by the Climate Financial Risk Forum (CFRF). This framework is a structured guide to help financial institutions like banks to conduct thorough scenario analysis to understand and mitigate climate-related risks.

1. SSP (Shared Socio-Economic Pathways)

• Definition: Shared Socio-Economic Pathways (SSPs) are scenarios that project different possible socio-economic developments up to 2100, focusing on variables like GDP, population growth, and urbanization. These pathways help model how various socio-economic settings impact climate change.
• Purpose: SSPs provide foundational socio-economic contexts for subsequent models, influencing assumptions about economic growth, policy development, and energy demands.
• Example for a Bank: A bank might select SSP2, labeled "Middle-of-the-road," which assumes moderate economic and policy developments. This SSP could serve as the baseline socio-economic scenario, helping the bank predict the economic environment its borrowers and sectors may operate in. For example, moderate growth in GDP and urbanization rates could guide the bank’s lending strategy for urban infrastructure projects.

2. IAMs (Integrated Assessment Models)

• Definition: Integrated Assessment Models (IAMs) combine data from SSPs with projections on emissions, energy use, and land use to simulate the interaction between human activities and the environment. IAMs are comprehensive models that examine how socio-economic changes affect climate outcomes.
• Purpose: IAMs help banks and financial institutions understand sector-specific climate impacts, providing a deeper analysis of carbon emissions pathways and energy investments under different socio-economic scenarios.
• Example for a Bank: A bank might use the GCAM model to analyze its exposure to the energy sector. By understanding CO2 emissions pathways and potential changes in the energy system, the bank can gauge the future risks for its fossil fuel clients and adjust its lending policies to align with sectors that are more resilient to climate policies.

3. NGFS Scenarios

• Definition: The NGFS (Network for Greening the Financial System) Scenarios offer a range of climate scenarios based on different policy and technology assumptions.
• Purpose: These scenarios allow banks to explore a range of future outcomes, evaluating both physical and transition risks under different levels of climate action.
• Example for a Bank: In an “Orderly” scenario, where climate policies are introduced early, a bank might evaluate how gradual carbon reduction policies affect its energy portfolio. Conversely, a “Hot-House World” scenario could show the bank’s exposure to increased physical risks, such as extreme weather events impacting agriculture loans.

4. NiGEM Pathways (Macroeconomic Simulations)

• Definition: NiGEM (National Institute Global Econometric Model) pathways simulate macroeconomic effects of climate-related transition risks, such as GDP growth, unemployment, and inflation, at a country level.
• Purpose: These simulations provide banks with a country-level analysis of how climate transition policies affect the broader economy, aiding in risk assessment and strategic planning.
• Example for a Bank: In a “Disorderly” scenario with a rapid increase in carbon prices, a bank might use NiGEM to model how inflation and unemployment in a specific country could affect its mortgage portfolio. This could lead the bank to tighten lending criteria in regions more susceptible to economic fluctuations from sudden policy changes.

5. Climate Impact Explorer (CIE)

• Definition: The Climate Impact Explorer provides country-level data on physical climate risks, including potential impacts from extreme weather events, sea-level rise, and temperature changes.
• Purpose: This tool helps banks assess the physical risks associated with climate change at a granular level, enabling them to model the impacts on assets in specific geographic areas.
• Example for a Bank: A bank with a large number of real estate-backed loans in coastal areas could use CIE to assess the risk of sea-level rise on these properties. This analysis could influence the bank’s loan-to-value ratios, lending policies, or insurance requirements for properties in high-risk areas.

6. Internal Scenario Analysis

• Definition: Internal Scenario Analysis involves applying all gathered data from SSPs, IAMs, NGFS scenarios, NiGEM, and CIE to conduct an in-depth assessment of a bank’s portfolio resilience under various climate scenarios.
• Purpose: This step allows banks to customize their scenario analysis based on specific exposures, activities, and counterparty risks, enabling a tailored approach to managing climate risks.
• Example for a Bank: After analyzing NGFS and NiGEM scenarios, a bank might conduct internal scenario analysis on its energy-intensive loan portfolio. For instance, if a “Hot-House World” scenario suggests significant physical risks, the bank can assess its resilience by estimating potential loan defaults in vulnerable sectors and setting aside capital reserves for anticipated losses.

Challenges in Climate Scenario Analysis

Climate scenario analysis is essential for understanding climate-related financial risks. However, its complexity brings notable challenges:

• Breadth and Magnitude of Transition and Physical Risks: Climate change impacts are broad, with tipping points potentially leading to non-linear, correlated risks that are more significant than other economic changes.
• Extended and Uncertain Time Horizons and Feedback Loops: Climate-related risks often unfold over extended timeframes, with social tipping points and unpredictable technological advances adding further uncertainty.
• Weakness of Many Climate-Economic Models: Many models assume market efficiency, failing to capture disruptive feedback loops or tail risks. They also often rely on high discount rates, which may undervalue long-term physical risks.
• Data Gaps and Comparability of Disclosures: Accurate, firm-level emissions data is crucial yet limited. Financial i
• nstitutions face challenges in accessing consistent, quality data for all aspects of emissions reporting.
• Cognitive Bias: Cognitive biases, such as the tendency to overestimate familiar risks, can affect scenario interpretation. This bias highlights the importance of structured, objective analysis.

Conclusion:

This guide from the Climate Financial Risk Forum underscores the value of climate scenario analysis as an essential tool for financial institutions navigating climate risks. By applying structured analysis, firms can make informed, resilient decisions in an uncertain climate future. With advancements in modeling and data availability, climate scenario analysis will continue to evolve, empowering financial institutions to prepare for both known and unknown climate-related risks.

Reference: Scenario Analysis – Implementation GuideOpens in a new window

Appendix

End-to-End Climate Scenario Analysis Process Step by Step Detailed Explanation

This process is a step-by-step method that helps banks and other financial institutions understand and manage the risks they face from climate change. It helps them see how their loans, investments, and overall strategy might be affected by different climate scenarios and lets them prepare for possible future challenges.

1. Examine Transmission Channels

Banks first identify how climate risks can affect their financial health. Transmission channels are the pathways through which climate change impacts the economy and specific industries. For example, if there’s an increase in extreme weather events (like floods or hurricanes), this could affect the value of real estate assets. Similarly, if new policies are introduced to reduce carbon emissions, certain industries (like coal and oil) may suffer, impacting loans banks have made to companies in those sectors.

2. Identify Climate-related Risks

Here, banks classify climate risks into two main types:

• Physical Risks: These are risks from physical impacts like storms, floods, and rising temperatures that could harm property or disrupt business operations.
• Transition Risks: These come from changes in laws, technology, or consumer behavior as the world moves toward a low-carbon economy. For instance, if governments raise taxes on carbon emissions, companies that rely on fossil fuels may struggle, which could affect banks that lend to these companies.

Example: If a bank has provided loans to a car manufacturer, it would consider the risk of new emissions regulations that might require the carmaker to shift to electric vehicles.

3. Conduct Exposure Analysis

The bank then assesses which parts of its business are most exposed to these climate risks. This means examining which loans, investments, or properties are most vulnerable. Exposure analysis helps the bank see where it has the greatest risk so it can focus its efforts accordingly.

Example: A bank might find that it has a lot of exposure in coastal real estate, which is at high risk of flooding. Knowing this, the bank can start thinking about how to manage this risk.

4. Identify Potential Exposure to Climate-related Risks

This step goes deeper, estimating the financial impact if climate risks were to materialize. For example, how much could the bank lose if a storm damages properties it has financed, or if new laws make coal plants unprofitable? This helps the bank understand the potential scale of its climate risk.

5. Scenario Analysis Process

The bank then creates different climate scenarios—essentially, "what if" situations that explore a range of possible futures. By testing how the bank’s loans and investments would perform under different conditions, it can better prepare for uncertainties.

Example: A bank might create one scenario where the government imposes strict carbon limits by 2030 and another where no new policies are introduced. Each scenario helps the bank see how its business could be impacted.

6. Socio-economic Context

The bank considers broader socio-economic factors, like population growth or economic development, that might influence climate risks. For instance, a growing city might increase demand for housing, but it could also make the area more vulnerable to heatwaves if climate change intensifies.

7. Technological Evolution

Banks look at how technology might evolve and impact their investments. For instance, if renewable energy technology advances, companies that rely on fossil fuels may face increased risks, while those investing in green technology could perform better.

Example: If a bank has invested heavily in oil, it might consider how advancements in solar or wind energy could reduce demand for oil, potentially affecting the value of its investments.

8. Climate Policy Landscape

The bank examines current and potential future climate policies. These policies—like carbon taxes or emissions limits—can significantly affect the profitability of companies in high-emission sectors. By understanding policy risks, the bank can adjust its strategy.

Example: If a bank expects stricter emissions laws, it might choose to reduce its lending to coal-fired power plants and instead support renewable energy projects.

9. Emission and Temperature Pathways

This involves analyzing different temperature scenarios and related emission pathways. Banks use these to see how global warming levels (e.g., keeping it under 2°C or allowing it to rise above 3°C) might affect physical risks like floods, fires, or droughts.

Example: A bank with significant investments in agriculture would look at scenarios where temperatures increase, impacting crop yields and potentially affecting the ability of farmers to repay loans.

10. Develop Suitable Climate-related Scenarios

Using information gathered on socio-economic, technological, policy, and temperature factors, the bank develops specific scenarios that suit its unique portfolio. These scenarios simulate potential future outcomes, providing a foundation for analyzing risks.

Example: The bank might create a scenario for an orderly transition to a low-carbon economy and another for a disorderly transition with sudden policy shifts. These help the bank see what could happen in different climate futures.

11. Define Risk Measure

The bank decides on metrics to measure climate risk. This could include metrics like Value at Risk (VaR) to estimate potential losses or carbon footprint metrics to track emissions exposure.

Example: The bank could set a target to reduce its exposure to high-emission industries by 30% by 2030.

12. Choose Impact Assessment Tools

The bank selects tools and models to assess climate risk accurately. This could include software for stress-testing or financial models that incorporate climate data.

Example: A bank might use a climate risk model that factors in data on sea level rise to evaluate the risk of coastal real estate loans.

13. Assess the Financial Impact

The bank uses its tools to calculate the potential financial losses under each climate scenario. This step provides a detailed picture of how climate risks could affect its profits, capital, and overall stability.

Example: A bank might find that under a scenario with a sharp increase in carbon taxes, its exposure to coal plants could lead to significant losses.

14. Assess Financial Impacts and Take Appropriate Action

Finally, the bank uses insights from its scenario analysis to make strategic adjustments. Based on the identified risks, it may choose to reallocate funds, diversify its assets, or support clients in transitioning to greener practices.

Example: If a bank finds that its investments in oil companies carry high risk under stricter climate regulations, it might shift those funds toward green bonds or loans for renewable energy projects.

Disclaimer:

This article incorporates information and insights from the Climate Financial Risk Forum’s 2021 Guide on Scenario Analysis, as well as the Scenario Analysis – Implementation Guide published by industry experts. While efforts have been made to interpret and present these insights accurately, readers are encouraged to consult the original guides for comprehensive details. This article is intended for informational purposes only and does not constitute financial or professional advice. The views expressed are the author’s own and do not necessarily reflect those of the Climate Financial Risk Forum or the authors of the referenced guides.