The Global Risks Alliance (GRA)
The methods Fintech Nexus relies on, the assumptions they carry and the limits of what they can show.
Fig.How a finding is reviewed before it is published. Design, not a record.
The Fintech Nexus methods page sets out the methods the platform relies on, among them payment and financial market technology, distributed ledgers and digital assets, and artificial intelligence and machine learning, 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.
For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on population density and night lights with night lights tonight from NASA GIBS, framed on East Africa; every other NASA layer, live feed and forecast waits in the layer list.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 2
Activity and exposure, for this page
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
Latest available
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth
Loading the latest NASA imagery.
Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.
For analysis and uncertainty, in GRA's spatial-finance reading, the map opens on population density and night lights with night lights tonight from NASA GIBS, framed on East Africa; 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
| Method | Use |
|---|---|
| Dependency mapping | Service-to-provider graphs for concentration analysis |
| Incident data analysis | Outage and cyber incident reports in common formats such as the FSB FIRE format |
| Model governance review | Documentation of credit and fraud models against SR 26-2, PRA SS1/23 and the EU AI Act |
| Inclusion measurement | Account ownership and digital payment use from public survey data such as the Global Findex |
Firm-level incident and dependency data are mostly confidential to supervisors. Sector research therefore works from public incident reports, published outsourcing registers where they exist and modelled networks, and states that limit. Inclusion work continues at financial inclusion.
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. |
| Payment and financial market technology | Payment and financial market technology covers the systems that clear and settle transactions and support trading. |
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.