GRA · Financial Stability
Spatial financeWhere capital meets hazard, exposure and transition
Financial discipline overview
Financial stability analysis studies the resilience of the financial system as a whole: whether it can keep providing credit, payments, insurance and market liquidity through shocks, or whether it amplifies them. It combines macroeconomics, finance, network science and the study of institutions. On Financial Stability, the Global Risks Alliance (GRA) treats the discipline as shared industry research, not as policy or execution.
- STEM methods
- 5
- Canonical methods this field applies
- Topics
- 8
- Subject pages in the field
- Counterparts
- 6
- Platforms in shared fields across the network
- Report series
- 2
- Reports series it contributes to
Two dimensions of systemic risk.
The cyclical dimension
How leverage, credit and asset prices build up in booms and unwind in busts, so that risk is created when it looks lowest.
The structural dimension
How exposures, common holdings and shared infrastructure connect institutions at any point in time.
Interaction
Booms deepen connections, and dense connections make busts spread faster.
Activity and exposure in Europe.
Population density, night lights and flood water over Europe, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
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.
Activity and exposure, framed on Europe.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.
Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · U.S. Geological Survey · CIESIN/Columbia, NASA SEDAC HBASESources 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 hexagonal 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 hexagonal 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 hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
- 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 hexagonal cells where shown (modified). NASA open data
- 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 hexagonal cells where shown (modified). NASA open data
- NASA Fire Information for Resource Management System (FIRMS), VIIRS 375 m active fire product, NASA LANCE; vector tiles via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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 hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. 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 hexagonal cells where shown (modified). ODbL
- Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal 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.
- Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
- Live: NASA EONET Events are indicative, not authority warnings.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- 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.
- NASA GIBS: 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).
- Optional layers (5 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
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
The sectors and links a stability view covers.
| Sector | Typical vulnerability | Link to others |
|---|---|---|
| Banks | Maturity transformation, concentration in property and sovereign debt | Lend to nonbanks; clearing members |
| Insurers and pension funds | Asset-liability mismatch, liquidity needs from hedging | Hold bank and corporate debt; use derivatives |
| Open-ended funds | Daily redemption against less liquid assets | Sell common assets under stress |
| Leveraged nonbanks and private credit | Leverage, margin calls, opaque valuations | Funded by banks and prime brokers |
| Market infrastructures | Concentration and operational dependence | Connect every sector |
Field overview.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Vulnerabilities, not predictions.
| Vulnerability | Why it matters | Typical indicators |
|---|---|---|
| Leverage | Magnifies losses relative to capital | Debt relative to income or equity across sectors |
| Maturity and liquidity mismatch | Creates exposure to funding runs | Short-term funding of long-term or illiquid assets |
| Asset valuations | Stretched prices can fall sharply | Valuations relative to fundamentals and history |
| Interconnectedness | Spreads distress between institutions | Bilateral exposures and common holdings |
| Concentration | Creates single points of failure | Dependence on few providers or counterparties |
Indicators describe conditions, not probabilities of crisis.
Stability is a public good that markets underprovide.
Each institution weighs its own risks, not the costs its distress would impose on others. Fire sales, funding runs and credit crunches impose losses on firms and households that had no part in the original decisions. Because these spillovers are not priced, the system as a whole tends to carry more leverage and liquidity risk than is socially optimal, which is why authorities pursue financial stability as a public policy objective.
For the industry, shared understanding of these spillovers is a common interest. It improves each firm's view of the conditions it operates in, and it gives the profession a common language with the authorities and researchers who study the system.
What the platform does.
Open analysis
Network, scenario and econometric methods that the industry can examine.
No firm identifiable
Evidence is aggregated so that no institution or position can be identified.
Shared evidence only
GRA publishes aggregated research. It assesses no firm, sets no policy and advises no one.
Related pages.
- How risk moves: financial-system transmission.
- Topics: systemic interconnectedness, liquidity and market stress and stress testing methods.
- Policy context: macroprudential policy on Financial Regulations Nexus.
- Systems science at GCRI: networks and cascades.
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.
Pages in Financial discipline overview.
Questions and answers.
Does GRA monitor the financial system for authorities?
Why distinguish the cyclical and structural dimensions?
Is a vulnerability a prediction?
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