Section 9 – Portfolio management and disclosure

Module 22 – Climate stress testing

FIs are often required to conduct regular stress-testing exercises to meet national regulatory requirements. These typically aim to:

1. Evaluate resilience to economic downturns, market shocks or sector-specific crises.
2. Assess adequacy of capital and provisions under adverse conditions.
3. Inform risk appetite, limit setting and contingency planning.
4. Satisfy supervisory expectations and support stakeholder confidence.

Climate stress testing builds upon existing risk management practices by assessing how well a portfolio can withstand climate-related shocks. It uses the same core infrastructure as traditional stress testing, including scenario design, data collection, cross-functional collaboration and board-level oversight.

• The goals are to protect financial stability, anticipate emerging risks and meet evolving regulatory requirements.
• As with stress tests that inform capital and risk appetite, climate stress testing introduces an additional dimension – evaluating the impact of plausible but severe climate-related stresses on clients, assets and markets.

Climate stress testing differs from traditional stress testing in several ways:

Typical outputs from climate stress testing

Common metrics assessed in climate stress testing include:

1. Expected credit loss (ECL): A core credit risk measure to assess provisioning needs and capital adequacy.
2. CET1 ratio: A standard regulatory capital indicator.
3. Portfolio-at-risk by sector or geography: Measured through indicators such as non-performing loans (NPL), loss given default (LGD) or probability of default (PD) for key areas of portfolio concentration.

Insights from climate stress testing

• For risk management and appetite setting:

  • Identifies sectors, geographies and client types most vulnerable to climate-driven shocks.
  • Informs refinement of risk appetite statements, portfolio limits and early warning systems.
  • Guides pricing, collateral requirements and loan structuring for higher-risk exposures.

• For strategic planning and business model adaptation:

  • Assesses the resilience of existing lending strategies.
  • Highlights misalignments between long-term climate risk and short-term profitability.
  • Supports the development of new climate finance products and services.

• For data and capability development:

  • Reveals gaps in data collection, modelling and scenario analysis.
  • Helps facilitate client discussions about climate risks, transition plans and adaptation needs.

• For regulatory compliance and disclosure:

  • Produces robust, decision-useful insights for disclosure, risk management and resilience-building, especially in vulnerable sectors and geographies.
  • Demonstrates to stakeholders that the institution is proactively assessing and managing climate risks, building credibility and trust.

Tool 7: Climate stress testing approaches

Tool 7 provides step-by-step approaches, and example narratives, for conducting climate-related stress tests on portfolios. Focusing on both physical and transition risks. It outlines scenario design, data requirements, impact modelling, and reporting to assess credit risk impacts under climate stress events.

Guidance 21a: High-level approach for stress testing physical risks

Guidance 21 presents a high-level approach for conducting climate stress tests focused on physical risk shocks to the portfolio. By defining clear objectives, choosing suitable analytical approaches and translating climate hazards into financial outcomes, vulnerabilities can be identified, credit losses quantified, and portfolio resilience strengthened.

The table below shows how to model a physical risk event, such as a severe flood, within a stress testing framework to assess its financial impact on a mortgage portfolio. It highlights how property-level shocks can lead to higher loan-to-value (LTV) ratios, increased default probabilities and greater loss rates.

Scope: This analysis estimates the potential impact of a severe flood event on the performance of a mortgage portfolio, focusing on property values, borrower risk and expected credit losses.

Key scenario mechanisms

• A flood event reduces property values due to physical damage, repair costs and reduced market desirability in affected areas.
• Falling property values lead to higher LTV ratios across the portfolio.
• Higher LTVs are statistically linked a greater probability of default (PD).
• When defaults occur, the total financial loss (LGD) rises because the property value falls below the loan balance, especially where insurance coverage is low.

Calculation logic: The stress test estimates total losses by multiplying exposure at default (EAD) by the probability of default (PD) and the loss given default (LGD) for each loan, then aggregating the results across the entire loan portfolio.

Guidance 21b: High-level approach for stress testing transition risks

Guidance 21b presents a high-level approach for stress testing transition risk shocks to the portfolio. It can help institutions to assess how sudden shifts in climate policy, carbon pricing or market conditions could affect portfolio performance.

The table below shows how a transition risk stress test can evaluate the financial impact of an abrupt and severe climate policy intervention, in this case, the introduction of a $100/tCO2 carbon price. The scenario explores how such a shock could ripple through the power generation sector by increasing operating costs, eroding profit margins and elevating credit risk metrics such as PD, ECL and LGD.

Scope: This analysis estimates how a sudden, severe carbon price shock could affect the credit risk of power generation exposures, focusing on profit margins and associated PDs.

Key scenario mechanisms:

• A sudden carbon pricing policy raises operating costs for carbon-intensive generators, particularly coal and gas.
• If higher costs cannot be fully passed on to consumers, profit margins shrink substantially.
• Lower margins increase the probability of default (PD), while loss given default (LGD) rises as asset values fall, or assets become stranded.
• Renewable energy producers are largely unaffected, but fossil fuel assets could experience steep losses as carbon prices escalate.

Calculation logic: The stress test scenario forecasts total losses by multiplying exposure at default (EAD) by the probability of default (PD) and the loss given default (LGD) for each loan, then aggregating the results across all loan exposures in the portfolio.

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