A-P07 · PROCESS · countriesGRA dossier · service level R0
GRAAI and Financial Model RiskIn development
Countries

Country readiness contexts

Country programmes of AI and Financial Model Risk, each listed with its status. A country appears only when a programme record exists for it.

Make an enquiry Back to Research and industry programmes
Publisher
The Global Risks Alliance
Field
Artificial intelligence, Financial stability
  1. 01QuestionNational, regional or institutional priority
  2. 02EvidenceSTEM foundation of the platform
  3. 03BuildNexus Foundry
  4. 04OrganizeNexus Ecosystem
  5. 05TestNexus Universe (independent site)
  6. 06PublishNexus Reports
  7. 07DecideCompetent authorities and institutions, through Nexus Rails
  8. 08RenewCorrections and the next annual agenda
01In brief

The short answer.

AI and Financial Model Risk country programmes are listed one by one, each country with a programme record showing its work on artificial intelligence and its status. A country appears only when such a record exists; national institutions lead under country ownership, and the platform supplies evidence and methods.

02Canvas

Scoping to review.

Canvas · scoping to reviewDesign, not a record
Country readiness contexts: a programme through its gatesA request with a named owner becomes a scoping note; inputs are qualified at a gate; delivery runs in workstreams; a controlled test and an independent review precede publication; the owner decides. Design of the process, not a record of a run.

Fig.A programme from scoping to the owner's decision. Design, not a record.

03Geography

Connected activity in California.

For country readiness contexts, in GRA's spatial-finance reading, the map opens on night lights and population density with place names and borders from NASA GIBS, framed on California; 3 further NASA layers wait in the list.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 2

Connected activity, for this page

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 country readiness contexts, in GRA's spatial-finance reading, the map opens on night lights and population density with place names and borders from NASA GIBS, framed on California; 3 further NASA layers wait in the list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · CIESIN/Columbia, NASA SEDAC HBASE · © OpenStreetMap contributors · GDACSSources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Context: CIESIN/Columbia, NASA SEDAC HBASE. Center for International Earth Science Information Network (CIESIN), Columbia University, and NASA Socioeconomic Data and Applications Center (SEDAC): Global Human Built-up And Settlement Extent (HBASE) 2010; Seto, Guneralp and Hutyra 2012, Global Grid of Probabilities of Urban Expansion to 2030; Global Urban Heat Island (UHI) Data Set, 2013.
  • Context: © OpenStreetMap contributors (ODbL), via NASA GIBS. © OpenStreetMap contributors (ODbL), rendered by NASA GIBS.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Optional layers (4 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026

04Scope

Countries in AI and Financial Model Risk.

  1. 01

    Model risk governance

    Inventory, ownership and validation.

  2. 02

    Credit and pricing models

    Finance-specific automated decisions.

  3. 03

    Generative AI in finance

    Use cases and failure controls.

  4. 04

    Explainability and fairness

    Interpretation, bias and accountability.

  5. 05

    Model monitoring and drift

    Changes over time and review thresholds.

  6. 06

    Human in the loop controls

    Authority and approvals.

05Country pages

What a AI and Financial Model Risk country page would contain.

A AI and Financial Model Risk country page would cover national guidance, drawing on public records only, and would appear once a programme record exists. It would never contain fairness opinions.

Country evidence for AI and Financial Model Risk would come from model records and monitoring data, labelled by source, and would be written for data scientists in finance and AI governance leads.

06Status

Work is shown as its record stands.

Programmes are listed as exploring, forming, constituted, active, paused or archived. Country and regional entries appear when a programme record supports them.

All programmes in AI and Financial Model Risk

07Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
Country ownershipThe principle that a country leads its own development policies and strategies and coordinates the actions that support them, set out in the Paris Declaration on Aid Effectiveness.
National Nexus ConsortiumIn the Consortium's national model, the body through which a country's institutions take part in Nexus work, formed under a national record with its own leadership and working groups.
Programme statusThe recorded state of a programme on Nexus pages: exploring, forming, constituted, active, paused or archived. A plan is never presented as an activity.
08Sources

Where this page's references lead.

The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.

09Questions

Questions and answers.

How do I propose work at this level?
Write to contact@therisk.global or a regional desk. A proposal receives a reference.
Related

Around AI and Financial Model Risk.

AI and Financial Model Risk

Bring your expertise to this field.

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.

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