The Global Risks Alliance (GRA)
The methods Banking Nexus relies on, the assumptions they carry and the limits of what they can show.
GRA · Established · service level R0
The Banking Nexus methods page sets out the methods the platform relies on, among them financial economics and macro-finance, probability and statistics, and network science and contagion, with their assumptions, validation and limits. Each analysis lists its assumptions and data, reports ranges and confidence beside central estimates, is checked against observations or other models, and states what it cannot show.
Fig.How a finding is reviewed before it is published. Design, not a record.
For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on night lights, population density and true-colour imagery with built-up and settlement extent from NASA GIBS, framed on Western Europe; every other NASA layer, live feed and forecast waits in the layer list.
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For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on night lights, population density and true-colour imagery with built-up and settlement extent from NASA GIBS, framed on Western Europe; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.
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IFRS 9 expected credit loss requires forward-looking information, which is where climate and hazard evidence first enters bank accounts. Common approaches adjust probability of default through sector or regional overlays, adjust loss given default through collateral haircuts in hazard zones, or run a scenario-weighted expected loss. Each choice has a different auditability and a different sensitivity to hazard data quality.
| Approach | Strength | Weakness |
|---|---|---|
| Management overlay | Quick, transparent | Judgemental and hard to validate |
| Collateral haircut by hazard zone | Directly tied to geography | Depends on hazard map vintage and insurance assumptions |
| Scenario-weighted ECL | Consistent with IFRS 9 multiple scenarios | Scenario probabilities are not observable |
Climate and hazard overlays are models. In the United States they now fall under the April 2026 revised interagency guidance (SR 26-2), which superseded SR 11-7 and asks for risk-based, tailored validation; in the UK under PRA SS1/23. Model risk work continues at AI and Financial Model Risk.
Each analysis lists its assumptions and the data it depends on.
Ranges and confidence are reported alongside central estimates.
Models are checked against observations and, where possible, against other models.
What an analysis cannot show is stated beside what it can.
Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.
| Term | Definition |
|---|---|
| Uncertainty quantification | Characterising and propagating the uncertainties in a model to state confidence in its outputs. |
| Sensitivity analysis | Repeating an analysis under different assumptions to show how much the result depends on them. |
| Model validation | Independent testing that a model performs as intended and is fit for a stated use. |
| Financial economics and macro-finance | Financial economics and macro-finance study how asset prices, credit and financial institutions interact with the real economy. |
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
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.