GRF · Capital Nexus
Resilience finance governance
Resilience finance is the set of arrangements a state uses to pay for shocks: reserves, contingent credit, insurance, catastrophe bonds, debt clauses that pause payments after a disaster, and the budget rules that release them. Each instrument encodes a decision right: who declares the trigger, who pays, how fast and under what oversight. This page sets out how risk evidence connects to those rights and what the institutions that hold them need to see.
Resilience finance governance on the record.
Resilience finance governance: how the risk develops.
Risk evidence and decision rights. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Layering risk
Frequent small losses are retained in budgets and reserves, rarer larger ones transferred through contingent credit, insurance pools or bonds. The layers only work when their attachment points are set from evidence and written into law or contract.
Triggers decide speed
Parametric triggers pay on a measured hazard and are fast but carry basis risk; indemnity triggers pay on assessed loss and are slower. The choice is a trade between speed, accuracy and who bears the gap.
Shocks become fiscal stress
Disasters raise spending and cut revenue at once. Without pre-arranged finance, reallocation and emergency borrowing follow, and a physical shock can become a debt sustainability problem.
Decision rights must be clear
Release of contingent funds needs a named authority, a declared procedure and an audit trail. Ambiguity delays payouts and invites discretion that later reviews cannot reconstruct.
People and hazards in Latin America and the Caribbean.
Population density, night lights and flood water over Latin America and the Caribbean, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
People and hazards, for this page
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds and overpass timing leave gaps)
- Source
- VIIRS NOAA-20 375 m (FIRMS) (NASA LANCE FIRMS)
- Provider
- NASA LANCE FIRMS
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds and overpass timing leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 500 m grid
- Uncertainty
- Satellite hot-spot detections for the day shown, including gas flares and industrial heat; not a confirmed fire, an incident report or a warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (persistent cloud still leaves gaps)
- Source
- VIIRS NOAA-20 Level 3, 8-day (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- 8-day; Satellite 8-day composite; persistent cloud still leaves gaps
- Newest at build
- 2026-09-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground over the 8 days ending on the date shown, a heat exposure indicator; not air temperature, heat index or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
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.
People and hazards, framed on Latin America and the Caribbean.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 SurveySources 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.
- Context: © OpenStreetMap contributors (ODbL), via NASA GIBS. © OpenStreetMap contributors (ODbL), rendered by NASA GIBS.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- 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
- Active fires and thermal anomalies: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 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
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Pre-arranged disaster finance coverage | percent of modelled annual expected loss | annual | Disaster risk finance diagnostics | MODELLED |
| Contingency reserve balance | percent of general government expenditure | annual | Budget documents | Published statistics |
| Contingent credit lines in force | national currency or US dollars | annual | Treasury and multilateral records | Published statistics |
| Sovereign debt with climate resilient debt clauses | percent of eligible stock | annual | Debt office records, lender term sheets | REPORTED |
| Time from trigger to disbursement | days | per event | Treasury and risk pool records | REPORTED |
| Disaster-related contingent liabilities disclosed in the fiscal risk statement | categories disclosed (yes or no by category) | annual | Fiscal risk statement | DECLARED |
| Basis risk incidence of parametric covers | count of events with payout mismatch | per event | Risk pool reports and post-event reviews | ESTIMATED |
Compare instruments: rules, incentives and information.
Three families of instruments side by side against the baseline, each with its own lag and adoption speed, under the coverage and compliance you set; effect sizes are teaching values to replace with evidence. Scenario: named assumptions about the future, not a forecast. The map on this page shows Latin America and the Caribbean; the model itself is not tied to a place.
Controls
- Baseline trend of the outcome
- 2.0% a year
- Coverage of the instrument
- 70%
- Compliance
- 75%
- Effect size, against the teaching value
- 100%
- Years ahead
- 20 years
Readouts
- Largest reduction at the horizon
- Regulation
- Its reduction against the baseline
- 21%
Numbers, methods and sources
| Year | Baseline | Regulation | Economic incentive | Information and capacity |
|---|---|---|---|---|
| 0 | 100.0 | 99.5 | 98.8 | 99.1 |
| 1 | 102.0 | 101.2 | 100.1 | 99.8 |
| 2 | 104.0 | 102.5 | 101.1 | 99.9 |
| 3 | 106.1 | 103.5 | 101.6 | 100.0 |
| 4 | 108.2 | 103.7 | 101.8 | 100.7 |
| 5 | 110.4 | 103.2 | 101.7 | 102.1 |
| 6 | 112.6 | 102.0 | 101.6 | 103.9 |
| 7 | 114.9 | 100.4 | 101.6 | 105.9 |
| 8 | 117.2 | 99.2 | 102.1 | 108.0 |
| 9 | 119.5 | 98.6 | 102.9 | 110.1 |
| 10 | 121.9 | 98.9 | 104.2 | 112.3 |
| 11 | 124.3 | 99.7 | 105.7 | 114.5 |
| 12 | 126.8 | 101.1 | 107.4 | 116.8 |
| 13 | 129.4 | 102.7 | 109.4 | 119.2 |
| 14 | 131.9 | 104.5 | 111.4 | 121.6 |
| 15 | 134.6 | 106.5 | 113.5 | 124.0 |
| 16 | 137.3 | 108.5 | 115.7 | 126.5 |
| 17 | 140.0 | 110.7 | 118.0 | 129.0 |
| 18 | 142.8 | 112.9 | 120.4 | 131.6 |
| 19 | 145.7 | 115.1 | 122.8 | 134.2 |
| 20 | 148.6 | 117.4 | 125.2 | 136.9 |
Methods
- Tools of government Hood (1983), The Tools of Government, Macmillan
- Carrots, sticks and sermons Bemelmans-Videc, Rist and Vedung (1998), Transaction
- Diffusion of innovations Rogers (2003), Diffusion of Innovations, Free Press
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Borders Natural Earth
- Cities Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Capital Nexus in Foundry
- Tested at Capital Nexus in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Capital Nexus in Reports
- Taught in Faculty of Finance and Economics in Academy
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| IMF Fiscal Monitor and Fiscal Transparency Evaluations | Fiscal risk practice, contingent liability disclosure and fiscal responses to shocks | Free, IMF copyright and usage terms |
| World Bank disaster risk finance diagnostics and Cat DDO documents | Country reviews of risk layering and contingent credit design | CC BY 3.0 IGO |
| Sendai Framework Monitor (UNDRR) | Reported disaster losses and progress on national risk reduction targets | Public, UN terms of use |
| Regional risk pool reports (CCRIF SPC, African Risk Capacity, PCRIC) | Policy terms, trigger design and payout histories | Public reports, terms per pool |
| EM-DAT international disaster database (CRED) | Event-level records of disasters and reported impacts | Free for non-commercial use, registration |
| National budget laws and fiscal risk statements | Contingency rules, reserve mandates and release procedures | Public records, terms per government |
From mandate to evaluation, by pillar.
The steps an instrument takes from mandate to evaluation, each with the pillar that runs it, and the decisions that stay with the authority. Teaching model with stated illustrative values, not a prediction. The map on this page shows Latin America and the Caribbean; the model itself is not tied to a place.
- Mandate and problem framing Competent authority (outside the programme)
A competent authority frames the problem and the mandate under its own rules. Howlett, Ramesh and Perl (2009) - Evidence and system model Foundry
The system is modelled with its feedbacks, data and stated limits. OECD (2014), principle 2 - Options appraised with scenarios Foundry
Instruments are compared under scenarios, with uncertainty shown. Hood (1983) - Exercise with stakeholders Universe
The options are tested in an exercise with those who would implement and bear them. OECD (2014), principle 3 - Standard or guidance drafted Nexus Standards
What works is codified as a standard or guidance, open to comment. Nexus Standards process - Decision by the authority Competent authority (outside the programme)
The authority decides, outside the programme, with the evidence on record. Howlett, Ramesh and Perl (2009) - Capacity and training Risk Academy
Those who implement are trained on the decided instrument and its data. Sendai Framework (2015), priority 2 - Monitoring and public report Reports
Indicators are published with sources, limits and corrections. OECD (2014), principle 5 - Evaluation and revision Nexus Standards
Results return to the standard and the model: the cycle closes. Howlett, Ramesh and Perl (2009)
Methods
- Policy cycle Howlett, Ramesh and Perl (2009), Studying Public Policy, Oxford University Press
- Governance of critical risks OECD (2014), Recommendation of the Council on the Governance of Critical Risks
- Layered drawing of directed graphs Sugiyama, Tagawa and Toda (1981), IEEE SMC 11
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Capital Nexus in Foundry
- Tested at Capital Nexus in Universe
- Codified in Finance, Insurance and the Economy in Standards
- Published in Capital Nexus in Reports
- Taught in Faculty of Finance and Economics in Academy
Who decides, and what the evidence serves.
Capital Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Finance ministries and debt management offices | Which layers of disaster risk to retain, transfer or pre-finance, and at what cost | Risk layering evidence, instrument terms and fiscal risk disclosures kept separate by layer |
| Parliaments | Whether contingency rules and release authority are set in law and subject to scrutiny | Budget law provisions, release procedures and audit coverage |
| Boards of regional risk pools and multilateral lenders | How triggers, pricing and contingent credit terms should be designed | Payout histories, basis risk reviews and post-event assessments |
| Bilateral and private creditors | Whether to offer and accept payment pause clauses after defined shocks | Clause terms, trigger definitions and sovereign debt composition |
Outputs this topic produces
- Decision-rights maps for each pre-arranged instrument, from trigger to audit
- Dialogue briefs on risk layering and the fiscal rules that hold it
- Question sets for basis risk and post-event review
- Comparative notes on climate resilient debt clauses
Exercise a cascade in resilience finance governance with the people who decide.
Assembled from the Nexus Standards area profile Disaster and climate risk finance: the hazards it names, the systems and communities that carry the loss, the controls and institutions that dampen it and the data that observe it. Pick an initiating event and step through the cascade to see where mandates meet and which decisions fall to whom. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise for dialogue, not a forecast, an assessment or a position. To model a place of your own choosing, open the full System Builder.
Hazards
- Tropical cyclone
- Earthquake
- Ice-jam flood
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Flash flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Aftershock sequence (set off downstream)
- Fault surface rupture (set off downstream)
- Soil liquefaction (set off downstream)
- Slope slide (set off downstream)
- Rockfall (set off downstream)
- Tsunami (set off downstream)
- Building collapse (set off downstream)
Systems and couplings
Controls
NS-0Constitution and principlesNS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-9Contextual UNIs (deployments, instances, programme instances)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-F8Parametric and index-based risk transferNRS-F7Disaster risk finance and pre-arranged financeNRS-H113Hazard family: Financial-system fragility (NHS-1 soc.financial-system)NRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-D1Risk-informed development and project screeningNRS-H28Hazard family: Climate-state shifts (NHS-1 eco.climate-state)
Observation
- ERA5 reanalysis (Copernicus Climate Data Store) (listed for reference)
- CHIRPS quasi-global gridded precipitation (listed for reference)
- USGS earthquake GeoJSON summary feeds (listed for reference)
- Total public international support for national disaster risk reduction actions (Sendai indicator F-1)
- Direct economic loss attributed to disasters in relation to global GDP
Example geography
- Western Europe: 152 hexagonal cells
- Rain rate, last half hour (IMERG), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
What experts ask.
- 01
Who decides to finance risk reduction?
Which institutions hold authority over prevention, preparedness and recovery spending.
- 02
What evidence do they use?
How hazard, exposure and loss data inform financial decisions, and where they are missing.
- 03
How is financing layered?
How budgets, reserves, contingent credit and insurance combine for events of different size.
- 04
Who is accountable for use?
How pre-arranged funds are released, spent and reported.
How resilience finance governance is governed: instruments, mandates and commitments.
The instruments, mandates, actors and accountability arrangements a policymaker, diplomat or development agency works with, citing the agreements that set them. Structures follow the frameworks named. Any state or progress drawn is illustrative, not a record.
Development outcomes
The Sustainable Development Goals and targets that outcomes on resilience finance governance are reported against.
| Goal | Target | How this subject links |
|---|---|---|
| Goal 1, no poverty | Target 1.5, resilience of the poor and vulnerable | Outcomes reported through the agreed indicator of the target |
| Goal 17, partnerships for the goals | Target 17.4, long-term debt sustainability | Outcomes reported through the agreed indicator of the target |
| Goal 10, reduced inequalities | Target 10.5, regulation and monitoring of financial markets | Outcomes reported through the agreed indicator of the target |
| Goal 16, peace, justice and strong institutions | Target 16.6, effective, accountable and transparent institutions | Outcomes reported through the agreed indicator of the target |
What drives the issue.
Ex-post financing is slow and uncertain. After a disaster, governments reallocate budgets, borrow or appeal for aid, and delays raise human and economic costs. Pre-arranged financing, agreed before events with clear rules, can speed response but requires governance in advance.
Evidence and decision rights are often separated. Scientific agencies hold hazard data, finance ministries hold budgets, and line ministries hold implementation. Without agreed processes, evidence does not shape spending.
Layering matches instruments to risk. Frequent small events are better met from budgets and reserves; rare large events may warrant risk transfer. Choosing the mix is a governance decision with fiscal consequences.
Trust depends on transparency. Clear rules for when and how funds are released, and published reporting on their use, sustain support for pre-arranged mechanisms.
Why now: disaster risk finance instruments, from contingency funds to risk pools, are spreading, and their governance decides whether money arrives when needed. Capital Nexus convenes the public institutions that hold these decisions; product and readiness questions go to Global Risks Alliance (GRA).
How evidence is gathered, and where it stops.
| Method or data | What it shows | Its limit |
|---|---|---|
| Fiscal risk analysis | Budget exposure to disasters | Depends on loss data quality |
| Comparative institutional review | How countries organise decisions | Context-specific |
| Post-event reviews | Speed and use of financing | Hindsight bias |
| Scenario dialogue | How institutions would act | Stated behaviour may differ from actual |
How it is studied, and what the methods cannot say.
- 01Policy, institutional and decision scienceMandate and decision-rights mapping · Institutional assessment synthesisApplied here
- 02Financial economics and macro-financeDebt sustainability under stress · The sovereign and bank feedback loopApplied here
- 03Economics and development economicsAppraisal of public investment · Fiscal incidence of policy choices · Indirect costs of shocksApplied here
Where this page leads across the Consortium.
Questions and answers.
What is a climate resilient debt clause?
What is basis risk?
Why do decision rights matter as much as money?
Does Capital Nexus recommend insurance or bonds?
Does Capital Nexus design financing instruments?
Why does pre-arranged financing need governance in advance?
Who examines the financial industry side?
Contribute evidence from this page.
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