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GRAInsurance NexusEstablished
Financial-system transmission

Financial-system transmission

Physical hazards, health crises, technology failures and economic shocks reach the insurance sector as claims and asset losses, and the sector transmits them onwards to reinsurers, capital markets, lenders, households and governments. This page, part of Insurance Nexus at The Global Risks Alliance (GRA), shows how real-system and financial vulnerabilities propagate through insurance, using sector-level analysis that assesses no individual firm.

Publisher
The Global Risks Alliance
Field
Insurance and catastrophe, Climate and hazards, Health and biosecurity
Status
Established
Service level
R0: information and enquiries

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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

STEM methods
5
Canonical methods this field applies
Topics
9
Subject pages in the field
Counterparts
13
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 Insurance 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 gross written premium by line and market and insurance penetration; 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: Insurance 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 Insurance.Placeholder names and illustrative values; a design, not a record or a live system.
04Inbound channels

How shocks reach insurers.

Liabilities

Claims

Damage, illness, death, interruption and liability become claims, often clustered in time and place.

Assets

Investment losses

The same shock can depress the value of insurers' investment portfolios at the moment claims rise.

Operations

Operational disruption

Events that damage communities can also disrupt insurers' own staff, systems and claims handling.

When liabilities and assets are hit by the same shock, the effect on capital is compounded. Stress testing examines this double hit.

05Renewal transmission

How a reinsurance renewal reaches a household.

Property catastrophe reinsurance renews on a few dates each year. When reinsurers raise attachment points or rates after heavy losses, primary insurers retain more or pay more, and pass part of that to policyholders through premiums, higher deductibles or non-renewal in high-hazard areas. The effect shows up first where catastrophe exposure is concentrated. Lenders then see it as uninsured or underinsured collateral. The chain is set out at retrocession and capital.

06Spatial finance

Where transmission concentrates.

Mapping insured exposure against hazard and against mortgage collateral shows where repricing would move risk to banks and households. A parametric trigger on the same map shows which part of a loss a public cover would pay quickly. Design values only. Credit effects continue at Banking Nexus housing and property finance; governance at GRF recovery governance.

07Outbound channels

How insurers pass stress onwards.

  1. 01

    Reinsurance and capital markets

    Large losses flow to reinsurers and investors in insurance-linked securities, which then reprice cover. See Reinsurance and Catastrophe.

  2. 02

    Repricing and withdrawal

    After losses or when risk rises, premiums increase or cover is withdrawn, widening insurance protection gaps.

  3. 03

    Credit and property markets

    Where insurance becomes unavailable, lenders may restrict mortgages and loans, and property values can fall.

  4. 04

    Public budgets

    Uninsured losses fall on governments through disaster relief and contingent liabilities, examined at Public Finance and Sovereign Debt.

  5. 05

    Investment behaviour

    Insurers' asset sales or reallocations under stress can affect the markets in which they invest.

09Analysis and limits

Sector-level, aggregated, with limits stated.

Transmission analysis uses scenario and stress-testing methods, extreme value theory and tail risk for tail events and probability and statistics for dependence between risks. It uses aggregated sector data, assesses no individual firm and makes no recommendation. Models simplify how markets and policymakers respond, and correlations observed in normal times can change in crises.

Because members compete, GRA's programmes are designed around competition-law safeguards that keep cooperation precompetitive, set out in a written competition policy that counsel reviews before membership opens.

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.

Is competitor data shared in transmission analysis?
No. Any firm data is aggregated before use, under the safeguards in GRA's written competition policy, which counsel reviews before membership opens.
Does this analysis assess my company?
No. It is sector-level research. Firm-level assessments are for firms, their supervisors and their advisers.
Why do insurance withdrawals matter beyond insurance?
Because mortgages, business loans and property values often depend on insurance being available. Withdrawal transmits risk to lenders, owners and governments.
Insurance Nexus

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