The Global Risks Alliance (GRA)
The methods Reinsurance and Catastrophe relies on, the assumptions they carry and the limits of what they can show.
The Reinsurance and Catastrophe methods page sets out the methods the platform relies on, among them extreme value theory and tail risk, actuarial mathematics, and climate and atmospheric science, 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 population density, night lights and flood water with built-up and settlement extent from NASA GIBS, framed on the Gulf of Mexico coast; 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 population density, night lights and flood water with built-up and settlement extent from NASA GIBS, framed on the Gulf of Mexico coast; 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.
Layers and dates
| Measure | Definition | Use |
|---|---|---|
| Occurrence exceedance probability | Probability that the largest single event loss in a year exceeds a level | Per-occurrence reinsurance |
| Aggregate exceedance probability | Probability that total annual loss exceeds a level | Aggregate covers and capital |
| Average annual loss | Mean of the annual loss distribution | Technical premium component |
| Tail value at risk | Average loss beyond a return period | Capital and risk appetite |
Primary uncertainty is whether and where an event occurs; secondary uncertainty is the damage given the event. Models that report only mean damage per event understate tails. Methods at extreme value methods.
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. |
| Extreme value theory and tail risk | Extreme value theory and tail risk study the behaviour of rare, high-impact events. |
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.