The Global Risks Alliance (GRA)
Stress tests ask how institutions and the system would fare under severe but plausible scenarios. Supervisors use them to set capital, central banks to study system dynamics, and boards to test their plans. Methods range from bank-run models to system-wide exercises that include nonbanks. This page sets out how stress tests are built and where they mislead, the records they produce, and who decides how they are used.
GRA · In development · service level R0
Stress testing methods are the ways supervisors, central banks and firms estimate how institutions would fare under severe but plausible scenarios. They range from bank-level tests with static balance sheets to system-wide exercises with second-round effects. Results are conditional, not forecasts. Supervisors and boards decide how they are used.
How physical and transition risk could reach a loan book under different scenarios. Illustrative design values.
Scenario, sensitivity and model limits. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
A stress test shows losses under the scenario chosen. Scenarios that are too mild, or that miss the next shock's shape, give false comfort.
Many tests hold balance sheets fixed. Real firms deleverage, sell assets and cut lending, which can amplify stress across the system.
Exercises that model banks, nonbanks and central counterparties together capture second-round effects that firm-level tests miss.
When results set capital buffers, firms have incentives to optimise models to the test. Varying scenarios and transparency limit gaming.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Adverse scenario | A hypothetical path of economic and financial variables designed to be severe but plausible. |
| Second-round effects | Losses caused by institutions' reactions to an initial shock, such as asset sales, rather than the shock itself. |
| Stress capital buffer | A capital requirement set from the results of a supervisory stress test. |
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 |
|---|---|---|---|---|
| Capital depletion under the adverse scenario | percentage points of CET1 ratio | annual | Supervisory stress test results | MODELLED |
| Stress capital buffer | percent of risk-weighted assets | annual | Supervisory determinations | OFFICIAL |
| Liquidity survival horizon under stress | days | periodic | Liquidity stress tests | MODELLED |
| Second-round losses in system-wide exercises | currency | per exercise | System-wide exercise reports | MODELLED |
| Scenario severity | peak-to-trough change in key variables | per exercise | Scenario documents | OFFICIAL |
| Climate scenario losses in exploratory exercises | currency or percent | per exercise | Climate exercise reports | MODELLED |
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 scenarios and results | Supervisory scenarios and bank results | Public domain |
| EBA EU-wide stress test results | Scenarios and bank-level results | Free, EU reuse terms |
| Bank of England system-wide exploratory scenario report | System-wide exercise covering banks and nonbanks | Free, Bank of England terms |
| NGFS climate scenarios | Reference climate scenarios for exploratory exercises | Free, NGFS terms |
| IMF FSAP stress test technical notes | Stress test methods and results by country | Free, IMF terms |
Financial Stability 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 |
|---|---|---|
| Prudential supervisors | How stress test results set capital buffers | Scenario design, model review and results |
| Central banks and macroprudential authorities | Whether system-wide dynamics need policy response | System-wide exercise findings |
| Bank and insurer boards | Whether capital and liquidity plans survive severe scenarios | Internal and supervisory test results |
| Scenario design teams | Which risks and severity to include | Historical episodes and emerging risk evidence |
How to design scenarios that challenge institutions without being arbitrary.
Which channels, such as credit losses, market moves and funding outflows, are modelled and which are left out.
Whether institutions' reactions and system-wide effects are represented.
What a stress test shows and what it cannot show.
Sensitivity analysis changes one factor at a time; scenario analysis changes many together in a coherent narrative. Reverse stress testing starts from failure and asks what would cause it.
Most traditional tests are static and firm-by-firm: they apply a shock and measure losses at each institution separately. They miss how institutions' responses, such as selling assets or cutting lending, affect each other and the economy.
System-wide and macroprudential tests add feedback, contagion and nonbank sectors. They are more realistic in structure but rely on more uncertain behavioural assumptions.
New risks challenge methods. Climate, cyber and pandemic scenarios involve long horizons, deep uncertainty and non-financial transmission paths that models were not built for.
Model risk is inherent. Results depend on data, assumptions and model choices; communicating uncertainty is as important as the headline results.
| Method or data | What it shows | Its limit |
|---|---|---|
| Sensitivity analysis | Exposure to single factors | Ignores interactions |
| Macro scenarios | Coherent multi-factor stress | Scenario design is judgemental |
| System-wide models | Feedback and contagion | Behavioural assumptions uncertain |
| Reverse stress tests | Paths to failure | Can identify implausible paths |
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.