UK SRS S2 Scenario Analysis: A Proportionate Approach to Climate Resilience

Educational practitioner guidance. Not legal or assurance advice. Verify the current UK SRS text, applicable reporting rules and entity-specific facts before acting.

A climate-related scenario is a plausible description of how the future could develop under a coherent set of assumptions. Scenario analysis does not attempt to predict one outcome. It tests how the entity’s strategy and business model might perform under materially different combinations of climate policy, technology, markets, macroeconomic conditions and physical hazards.

Under UK SRS S2, scenario analysis supports the climate resilience assessment in paragraph 22. The result should help users understand the implications for strategy and business model, significant uncertainties and the entity’s capacity to adapt. A scenario pack that stops at external variables or a coloured risk heat map is incomplete unless the analysis reaches the entity’s exposures, vulnerabilities, options, financial capacity and decisions.

Figure 1. The commensurate approach scales analytical sophistication with climate exposure and the entity’s skills, capabilities and resources.

The application guidance describes circumstances through two main considerations: the entity’s exposure to climate-related risks and opportunities, and the skills, capabilities and resources available to carry out scenario analysis. These considerations are assessed together. Low capability does not erase high exposure; it can justify an initially simpler method while capability is built, but it also makes the improvement plan and transparent limitations important.

The entity considers information about past events, current conditions and forecasts of future conditions. Inputs can be qualitative or quantitative, internal or external. Publicly available scenarios from authoritative sources are generally available without undue cost or effort, but availability does not make every scenario relevant. The entity needs a reasonable and supportable basis for the particular scenarios, variables and assumptions it uses.

The disclosure identifies the scenarios used and their sources, whether the set was diverse, whether scenarios addressed physical or transition risk, whether a scenario aligned with the latest international agreement on climate change was used, why the scenarios were relevant, the time horizons and the operational scope. This is not a requirement to use one universal library or a mandatory number of scenarios. The selection should create meaningful contrast and test the entity’s identified exposures and strategic assumptions.

Physical and transition analysis may use different source architectures, but the overall assessment should avoid internally contradictory assumptions. For example, a transition pathway with rapid policy action may reduce long-term physical risk relative to a delayed-transition pathway, while increasing near-term carbon cost and technology change. The entity should document how physical and transition components relate and where they are intentionally analysed separately.

UK SRS S2 does not equate quantitative analysis with compliance or qualitative analysis with weakness. Quantitative information often supports a more robust assessment, while qualitative scenario narratives can provide a reasonable and supportable basis alone or with quantitative data. The method should focus on the decisions the entity needs to test and the exposures that could affect prospects.

Figure 2. A first-year method can be structured and proportionate while establishing a controlled path to greater analytical depth.

1. Establish governance, purpose, material climate risks and opportunities, reporting entity, relevant value-chain scope and the strategic decisions to be tested.

2. Assess circumstances: document exposure by asset, geography, product or portfolio and assess available skills, capabilities, resources and data.

3. Select a small but diverse and relevant scenario set covering the material transition and physical pathways; record sources, versions and rationale.

4. Align short, medium and long-term horizons with planning, asset lives, financing, targets and risk horizons.

5. Create a controlled assumption register covering policy, macroeconomics, regional variables, energy use/mix, technology and management response.

6. Run structured qualitative analysis across the full material scope and targeted quantitative sensitivities for the most decision-relevant concentrations.

7. Document results for exposure, vulnerability, strategic implications, options, financial capacity, decision triggers and significant uncertainty.

8. Connect scenario findings to risk management, financial effects, metrics, targets, transition/adaptation plans and capital allocation.

9. Challenge the analysis through risk, finance, strategy, operations and governance review; retain evidence and alternative views.

10. Disclose method, scenarios, sources, diversity, physical/transition coverage, horizons, scope, assumptions, reporting period, results and limitations, and approve a capability-improvement plan.

UK SRS S2 requires the resilience assessment to be updated at each reporting date. The underlying scenario analysis may be performed in line with the entity’s strategic planning cycle, potentially every three to five years, provided it is updated at least in line with that cycle. In intervening periods, the entity assesses whether new information, events, exposures, strategy or assumptions change the resilience conclusion and updates the annual results accordingly.

The approach is proportionate because analytical depth follows the exposure concentration and available capability. It does not present high-level screening as equivalent to the targeted asset analysis, and it retains a clear improvement path.

A real disclosure would also explain the resulting implications for strategy and business model, the entity’s capacity to adapt and the connection to financial effects. Scenario names alone do not satisfy the paragraph 22 objective.

Treating scenario analysis as a forecast or probability-weighted prediction of one future.

Calling proportionality a first-year exemption from the resilience assessment.

Selecting scenarios by reputation rather than relevance to the entity’s risks, opportunities, geographies and decisions.

Using transition pathways without physical analysis, or vice versa, despite material exposure to both.

Using temperature labels without documenting scenario source, edition, variables and pathway assumptions.

Failing to align time horizons with strategy, asset life, financing and target periods.

Analysing hazards without exposure and vulnerability, or analysing policy without product, asset and market consequences.

Using qualitative judgement without a structured methodology and evidence record.

Building a complex model before establishing the material risk universe and decision questions.

Ignoring management-response feasibility, funding, dependencies and timing.

Failing to distinguish the date of scenario analysis from the annual resilience assessment date.

Publishing optimistic results while hiding model limitations, data gaps or alternative interpretations.