The Global Risks Alliance (GRA)
Stress and scenario models project how losses, capital and liquidity would change under adverse conditions. They are used for supervisory stress tests, internal capital assessment and climate scenarios. Because they model rare events with little data, they carry more uncertainty than everyday models. This page sets out how stress models fail, how they are validated, and who decides how their results are used.
GRA · In development · service level R0
Stress and scenario model risk is the risk that models projecting losses, capital and liquidity under adverse conditions are wrong, because extremes are rare, model chains compound error and behaviour is held fixed. Boards, validators, supervisors and capital planning teams decide how results are used.
How physical and transition risk could reach a loan book under different scenarios. Illustrative design values.
Verification and uncertainty. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Severe recessions and market crashes are rare, so the relationships linking scenarios to losses are estimated from few observations and may not hold in the next crisis.
Scenario variables pass through satellite models for each portfolio, then aggregation. Errors at each link compound, and the end result looks more precise than it is.
Where stress results set capital buffers, there are incentives to choose favourable assumptions. Supervisory models and challenge counter this.
Many stress models hold balance sheets and management actions static, missing the reactions that amplify or dampen losses.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Satellite model | A model translating scenario variables into a risk measure for a specific portfolio. |
| Management overlay | A judgement-based adjustment applied to model results to reflect risks the model does not capture. |
| Back-testing | Comparing a model's projections with what actually happened in past periods. |
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 |
|---|---|---|---|---|
| Stress loss projection against realised loss in past downturns | ratio | per back-test | Back-testing | ESTIMATED |
| Sensitivity of results to key assumptions | change in capital ratio | per exercise | Sensitivity analysis | MODELLED |
| Management overlays on stress results | currency | per exercise | Stress documentation | DECLARED |
| Supervisory model versus firm model differences | difference in projected losses | per exercise | Supervisory results | OFFICIAL |
| Stress models validated within cycle | share | annual | Validation records | DECLARED |
| Scenario variables used per model | count | per exercise | Model documentation | DECLARED |
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 |
|---|---|---|
| Federal Reserve stress test methodology documentation | Supervisory model descriptions | Public domain |
| EBA EU-wide stress test methodology | Constrained bottom-up approach and rules | Free, EU reuse terms |
| Bank of England stress testing documentation | Methods and model approach | Free, Bank of England terms |
| BCBS stress testing principles | International principles for stress testing | Free, BIS terms |
| NGFS scenarios technical documentation | Climate scenario models and limits | Free, NGFS terms |
AI and Financial Model 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 |
|---|---|---|
| Boards and risk committees | Whether stress results support capital and risk appetite | Results, sensitivities and validation |
| Model validators | Whether stress models are fit for purpose | Back-testing and benchmark evidence |
| Supervisors | How firm and supervisory models are compared and used | Exercise results and model reviews |
| Capital planning teams | Which overlays are justified | Overlay rationale and evidence |
The questions concern how far to trust a model of the unprecedented.
Stress tests link a scenario to outcomes through a series of models, for example from economic variables to default rates to losses to capital. Each link adds assumptions and uncertainty, and models calibrated on normal periods may not capture behaviour in extreme conditions. Climate scenarios extend horizons far beyond historical data, compounding uncertainty further.
Many stress tests consider institutions in isolation, missing interactions in which many firms' responses amplify stress. Machine learning components add new verification challenges. Presenting results as precise numbers can create false confidence; ranges and sensitivity analysis communicate limits more honestly.
| Method or data | What it shows | Limits |
|---|---|---|
| Scenario design | Plausible severe conditions | Choice of scenario shapes the answer |
| Satellite and loss models | Translation of scenarios into losses | Calibrated on limited stress data |
| Sensitivity and uncertainty analysis | Range of plausible outcomes | Cannot capture unknown unknowns |
| Reverse stress testing | Conditions that would cause failure | Identifies vulnerabilities, not probabilities |
| System-wide models | Interactions between institutions | Require behavioural assumptions |
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.