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GRAReinsurance and CatastropheIn development
Reinsurance and Catastrophe · Financial-system transmission

Financial-system transmission

A natural catastrophe starts as a physical event and becomes a financial one: damaged property, interrupted business, insurance claims, reinsurance recoveries, capital depletion and changes in prices and availability of cover. This page shows how real-system and financial vulnerabilities propagate through the insurance system and beyond, as part of the financial discipline overview.

Publisher
The Global Risks Alliance
Field
Insurance and catastrophe, Climate and hazards, Disaster and crisis
Status
In development
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 population density and night lights 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
  • 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 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
  • 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
  • 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 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
  • 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

  • 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, last day: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Precipitation rate, daily mean: GPM IMERG, NASA GES DISC · 12 Oct 2026

STEM methods
8
Canonical methods this field applies
Topics
8
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 Reinsurance and Catastrophe 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 reinsurance cession ratio and catastrophe excess-of-loss rate-on-line; 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: Reinsurance and Catastrophe 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 Reinsurance and catastrophe.Placeholder names and illustrative values; a design, not a record or a live system.
04From event to loss

How a catastrophe becomes an insured loss.

  1. 01

    Hazard

    Wind, ground shaking, flood water or fire affect a region, studied with GCRI's Climate and Hazards.

  2. 02

    Damage

    Buildings, infrastructure and contents are damaged according to their vulnerability, studied with structural and earthquake engineering.

  3. 03

    Interruption

    Businesses stop operating, including through damage to suppliers, power and transport.

  4. 04

    Claims

    Insured losses are claimed under policy terms; uninsured losses fall on owners and governments.

05Capital markets

How catastrophe risk reaches investors.

Catastrophe bonds and collateralised reinsurance move peak risk to pension funds, specialist funds and other investors. Collateral is held in trust, usually in high-quality money-market assets, so the investor's loss is the principal; the sponsor's counterparty risk falls. Retrocession passes reinsurers' risk on again. Topic depth at retrocession and capital.

06Protection gaps

When capacity retreats.

After heavy loss years, retrocession and reinsurance capacity can tighten, and primary carriers retain more or reduce cover. The uninsured share then moves to households, lenders and governments. Gap evidence at protection gaps; public-private schemes at GRF resilience finance governance.

07Through the insurance system

How losses move between layers.

LayerMechanismPossible stress
Primary insurersPay claims, recover from reinsuranceCapital depletion if reinsurance is insufficient
ReinsurersPay recoveries, recover from retrocessionCapital depletion after large or clustered events
Retrocession and capital marketsAbsorb peak layersCapital withdrawal after losses. See retrocession and capital
PolicyholdersFace higher premiums or reduced cover after lossesWider protection gaps
08Beyond insurance

Where the effects go next.

Banking

Mortgage and credit risk

Where insurance is withdrawn, property values and collateral may fall, affecting lenders.

Public finance

Government costs

Uninsured losses become public costs, studied by GRA's Disaster Risk Finance.

Households

Slower recovery

Uninsured households and firms recover more slowly. See protection gaps.

09Amplifiers

What makes transmission worse.

  • Accumulation: exposures concentrated in one region or peril, studied in aggregate accumulation.
  • Model error: underestimated tails or missing perils, studied in model validation.
  • Clustering: several large events in one season, depleting capital before it is replenished.
  • Changing hazards: models calibrated on a past climate, studied in climate and natural catastrophe.
  • Demand surge: reconstruction costs rising after large events because of shortages of labour and materials.

System-wide effects are studied with GRA's Financial Stability. This page is general research for professional understanding. It is not underwriting, pricing, investment or legal advice, and it does not recommend any model, product or counterparty.

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.

Can a catastrophe threaten financial stability?
Large catastrophes have generally been absorbed by the insurance system, but accumulated exposures, model error and insurance withdrawal can create wider stress. This is an active research question.
Why do premiums rise after big events?
Losses deplete capital and change perceptions of risk, which can tighten capacity. The platform studies the mechanism, not market conditions.
How does insurance withdrawal affect banks?
It can reduce collateral values and borrowers' ability to recover, raising credit risk. GRA's banking work examines this further.
What is demand surge?
The rise in repair and reconstruction costs after a large event, when labour and materials are scarce. It increases insured losses beyond what damage alone would suggest.
Reinsurance and Catastrophe

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