Climate and Nature Financial Risk
The Global Risks Alliance (GRA)
Climate scenario analysis asks how financial institutions would fare under different climate and policy pathways. Supervisors use it in exploratory exercises; firms use it to test strategy and meet disclosure rules. Scenarios translate emissions, temperatures and policy into macroeconomic and sector variables, then into losses. This page sets out how climate scenario analysis works, where it falls short, and who decides how it is used.
GRA · In development · service level R0
Climate scenario analysis is the assessment of how financial institutions would fare under alternative climate and policy pathways. Scenarios such as the NGFS set are translated into macroeconomic, sector and credit variables, adding uncertainty at each step. Supervisors, boards, disclosure preparers and the NGFS decide how it is used.
How physical and transition risk could reach a loan book under different scenarios. Illustrative design values.
The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.
Scenario analysis · Bank loan book · Exercise 2
basis points, illustrative
Horizon, assumptions and limitations. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Reference scenarios such as those from the NGFS describe orderly, disorderly and hot-house paths. Each implies different carbon prices, damages and growth.
Scenario variables must be translated into sector output, firm revenues, property values and default probabilities. Each step adds model uncertainty.
Climate effects unfold over decades; balance sheets turn over in years. Static balance sheet assumptions make long-horizon results illustrative.
Many scenario damage estimates omit tipping points, compound events and indirect effects, which can understate severe outcomes.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Orderly transition | A scenario in which climate policy is introduced early and becomes gradually more stringent. |
| Hot house world | A scenario in which limited policy action leads to severe physical risk. |
| Damage function | A relationship between climate change and economic loss used in scenario models. |
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Credit loss under climate scenarios | currency or basis points of exposure | per exercise | Supervisory and internal exercises | MODELLED |
| Change in probability of default by sector | percentage points | per exercise | Scenario models | MODELLED |
| Insurance losses under physical scenarios | currency | per exercise | Insurer scenario analysis | MODELLED |
| Portfolio value change under transition scenarios | percent | per exercise | Investor scenario analysis | MODELLED |
| Supervisory climate exercises completed | count by authority | annual | Supervisor publications | OFFICIAL |
| Scenario variables published | count of variables and regions | per vintage | NGFS scenario database | OFFICIAL |
The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.
Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| NGFS Scenarios Portal and database | Long-term and short-term climate scenarios with variables | Free, NGFS terms |
| ECB economy-wide climate stress test and supervisory exercise reports | Methods and results of euro area exercises | Free, ECB terms |
| Bank of England Climate Biennial Exploratory Scenario report | Exploratory scenario exercise for banks and insurers | Free, Bank of England terms |
| Federal Reserve pilot climate scenario analysis report | Exploratory exercise with large United States banks | Public domain |
| IPCC AR6 scenario database | Emissions and climate pathways | Free, terms per dataset |
Climate and Nature Financial Risk prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Supervisors and central banks | Which scenarios to use and how results inform supervision | Scenario design, exercise findings and limits |
| Bank, insurer and investor boards | How scenario results inform strategy and risk appetite | Internal and supervisory scenario results |
| Disclosure preparers | How to report scenario analysis under IFRS S2 | Standard requirements and peer practice |
| The NGFS | How scenarios are updated | User feedback and research |
Climate and nature risks unfold over decades under deep uncertainty about policy, technology and the climate system. History is a poor guide, and probabilities for different futures are not well defined. Scenarios address this by exploring a range of internally consistent futures, often based on reference sets such as those published by the Network for Greening the Financial System.
Scenario results depend heavily on their assumptions and on the models used to translate them into economic and financial terms. Many models have historically understated physical damages, omitted tipping points and assumed smooth adjustment, which may make severe outcomes look milder than they could be.
Using shared pathways for comparability, with scenario design and stress testing. Reference scenarios may not fit every institution's question.
Linking emissions, policy and the economy, with financial economics and macro-finance. Damage functions are a known weakness.
Mapping macro paths to sectors and assets. Each translation step adds uncertainty.
Testing which assumptions matter most and what would cause severe outcomes.
The current service level is R0: information and enquiries. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.