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Banking Nexus · Financial-system transmission

Financial-system transmission

Risk reaches banks from the real economy and leaves them again into the economy and the financial system. A drought, a cyber incident or a housing downturn can move through borrowers, collateral, funding and operations into bank losses, and from there into tighter credit, lower spending and stress at other institutions. This page shows how real-system and financial vulnerabilities propagate, as studied on Banking Nexus by The Global Risks Alliance (GRA).

Publisher
The Global Risks Alliance
Field
Financial stability, Capital markets and investment, Climate and hazards
Status
Established
Service level
R0: information and enquiries

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Layers 2

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Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

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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 financial-system transmission, in GRA's spatial-finance reading, the map opens on night lights and population density with built-up and settlement extent from NASA GIBS, framed on World; 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.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · CIESIN/Columbia, NASA SEDAC HBASE · 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
  • GPM IMERG precipitation, NASA Precipitation Processing System; distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 cells where shown (modified). NASA open data
  • GHRSST Level 4 MUR analyses, NASA Jet Propulsion Laboratory; distributed by the NASA Physical Oceanography DAAC (PO.DAAC); 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.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Optional layers (35 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
  • Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026
  • Sea surface temperature anomaly: GHRSST MUR25, NASA JPL PO.DAAC · 12 Oct 2026

GeographyFor financial-system transmission, in GRA's spatial-finance reading, the map opens on night lights and population density with built-up and settlement extent from NASA GIBS, framed on World; every other NASA layer, live feed and forecast waits in the layer list.

STEM methods
5
Canonical methods this field applies
Topics
10
Subject pages in the field
Counterparts
11
Platforms in shared fields at GCRI, GRF and GRA
Report series
2
Nexus Reports series it contributes to
01In brief

The short answer.

Risk transmission in Banking Nexus is the path by which physical, transition, technology and systemic shocks reach the sector and travel onward through balance sheets, markets and the real economy. Analysis uses aggregated, sector-level indicators such as non-performing loan ratio and stage 2 and stage 3 loan share; it assesses no individual firm and is not investment advice.

02Canvas

One field, three institutions.

Canvas · one field, three institutionsDesign, not a record
One field, three institutions: Banking Nexus and its counterpartsGCRI studies the field as science, GRF governs and convenes it, GRA builds shared financial understanding; the Nexus Universe tests work across them and the competent authorities decide. Design of the arrangement, not a record.

Fig.How GCRI, GRF and GRA share one field while the authorities decide. Design, not a record.

03Console

Field overview, in outline.

The working screen behind this subject: its structure, terms and states. Names are placeholders and values illustrative.

Field overview: the screen's structure, terms and states for Banking.Placeholder names and illustrative values; a design, not a record or a live system.
04Inbound

How shocks reach banks.

ChannelMechanismExample
Borrower incomeShocks cut the cash flow that services loansCrop failure reduces farm loan repayments
Collateral valueHazards or price falls impair assets securing loansFlood damage lowers property values in a mortgage book
Sector concentrationExposures cluster in one region or industryA regional bank lending mainly to one exposed economy
FundingDepositors or markets withdraw on loss of confidenceRapid digital deposit outflows
OperationsOutages at the bank or a shared providerA cloud failure interrupts payments at several banks

Channels describe mechanisms, not measured strengths or probabilities.

05Feedback loop

The bank-sovereign-insurance loop after a disaster.

After a large disaster, three balance sheets interact. Uninsured collateral losses raise loan losses; insurers facing claims may sell assets or withdraw cover; the sovereign spends on reconstruction and may face higher borrowing costs, which lowers the value of the government bonds banks hold. The loop is strongest where banks hold much domestic sovereign debt and insurance penetration is low. Sovereign effects continue at Public Finance and Sovereign Debt; insurance effects at Insurance Nexus risk transmission.

06Liquidity

Deposits and payments in a regional shock.

Regional disasters also move liquidity: depositors draw cash, firms draw credit lines and payment systems may be disrupted. The BCBS liquidity standards assume stressed outflows but not regional physical disruption to branches, ATMs and power. Operational dependence continues at payment dependencies; infrastructure evidence at GCRI grid disruption and recovery.

07Amplification

Why losses grow inside the system.

Leverage magnifies losses relative to capital. When capital falls, banks cut lending to protect their ratios, which hurts borrowers and can create further losses, a feedback loop between banks and the real economy. Selling assets to raise liquidity can depress prices and impose losses on other holders.

Interconnection spreads stress. Interbank exposures, common holdings of similar assets and shared dependence on payment systems and technology providers mean that one institution's problem can become many institutions' problem. Uncertainty about who is exposed can freeze funding markets even for sound banks.

08Outbound

How bank stress reaches people.

Credit supply

Tighter lending

Households and small firms lose access to credit just when they need it to recover.

Payments

Interrupted services

Outages stop wages, purchases and supplier payments.

Public finances

Fiscal costs

Support for banks and lost tax revenue strain public budgets, which can feed back to banks holding government debt.

09How GRA studies it

Sector-level, aggregated, with limits.

Analysis uses network science and contagion, probability and statistics and scenario methods, with aggregated sector data. It does not assess individual firms, recommend transactions or constitute investment advice. Methods and uncertainty are set out on analysis and uncertainty. The system-wide view is developed on Financial Stability transmission, and the hazard evidence comes from The Global Centre for Risk and Innovation (GCRI), for example compound hazards.

10Key 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
Transmission channelThe route by which a shock reaches financial institutions' balance sheets.
ContagionTransmission of losses or stress from one institution or market to others.
Second-round effectsFeedback from bank losses to the economy, such as tighter credit deepening a downturn.
Common exposureHoldings of the same or similar assets by several institutions, which makes their losses move together.
11Sources

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.

12Questions

Questions and answers.

Does this page predict a banking crisis?
No. It describes mechanisms. Scenarios are published separately, labelled as such, with their assumptions.
Why include public finances?
Because banks and governments are linked: bank support costs the state, and banks often hold government debt, so stress can loop between them.
Can I use GRA analysis to assess a specific bank?
GRA analysis is aggregated and assesses no firm. Any use for a specific institution is the user's own responsibility.
Banking Nexus

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