GRA · Disaster Risk Finance
Spatial financeWhere capital meets hazard, exposure and transition
Financing evidence and diligence
Every disaster finance decision rests on evidence: risk models, loss data, exposure, forecast skill and evaluations of past instruments. Diligence asks whether that evidence is fit for the decision, who produced it and what it leaves out. This page sets out the evidence chain behind disaster risk finance, the questions diligence asks, the data sources with their licences, and who decides what counts.
Financing evidence and diligence in seven parts.
- 01The questionFinancing evidence and diligence: how the risk develops
- 02IndicatorsWhat is measured, and how well
- 03SourcesWhere the evidence comes from
- 04DecisionsWho decides, and what the evidence serves
- 05Core questionsThe questions experts ask
- 06MechanismsWhat diligence looks at
- 07Methods and dataMethods and their limits
Financing evidence and diligence: how the risk develops.
Independent reviewer information needs. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Models drive price and triggers
Parametric triggers, insurance prices and layer sizes depend on catastrophe and forecast models. Their assumptions are often proprietary and hard for buyers to check.
Data gaps bias results
Exposure and loss data are thin in low-income countries. Models calibrated elsewhere may misjudge local vulnerability.
Independent review is rare
Buyers often rely on the seller's or broker's analysis. Independent review of models and terms protects buyers but adds cost and time.
Evaluation closes the loop
Evaluations of payouts, timeliness and outcomes show whether instruments worked. Without them, the same designs repeat regardless of results.
A drought index against its attachment point.
How a dry season is read against the point where drought cover starts to pay. Synthetic season and design terms.
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 |
|---|---|---|---|---|
| Instruments with independent model review | share of transactions | periodic | Programme records | REPORTED |
| Open risk models available for a country | count | on change | Open model registries | OBSERVED |
| Exposure data completeness for public assets | share of assets with location and value | periodic | Asset registers | OBSERVED |
| Published evaluations of disaster risk finance instruments | count | annual | Evaluation libraries | REPORTED |
| Forecast skill for trigger variables | verification score | periodic | Forecast verification | ESTIMATED |
| Disclosure of model assumptions to buyers | categorical | per transaction | Transaction documents | DECLARED |
Parametric trigger monitor.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Parametric trigger monitor
Financing evidence and diligence · Sovereign C · Season 2
Index vs trigger
Payment structure
| Attachment | 68 | 0 | Close |
| Mid | 85 | 54 | Not met |
| Exhaustion | 93 | 100 | Not met |
Risk layers
local m, pre-arranged
Payment to people
- Triggeragent confirms
- Payment15 days
- Treasurytransfer
- Social protectionscale-up
- Householdscash
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 |
|---|---|---|
| Insurance Development Forum Risk Modelling Steering Group tools | Open risk modelling resources | Free to read, terms to check |
| Oasis Loss Modelling Framework | Open platform for catastrophe models | Open source, BSD licence |
| Centre for Disaster Protection evaluations and guidance | Evidence reviews and diligence guidance | Free to read, terms to check |
| Risk Data Library standard | Open data schema for hazard, exposure, vulnerability and loss | Open, terms to check |
| World Bank and partner evaluation reports | Evaluations of disaster risk finance programmes | Free, World Bank terms |
Trace a shock in financing evidence and diligence to the balance sheet.
Assembled from the Nexus Standards area profile Disaster and climate risk finance: the shocks it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Pick an initiating shock and step through the cascade to see which exposures it reaches and where losses could concentrate. The Map view places the run on an example geography with open data. Every weight is a stated assumption. An exercise, not a forecast, a valuation, a rating or investment advice. 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
Who decides, and what the evidence serves.
Disaster Risk Finance 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 buyers | Whether evidence supports a purchase and its terms | Model documentation, independent review and evaluations |
| Donors paying premiums | Whether to fund premiums and on what evidence | Diligence findings and outcome evaluations |
| Pool and insurer risk managers | Which models and data to use | Validation and comparison evidence |
| Evaluation offices | Which instruments to evaluate and how | Programme records and evaluation standards |
Outputs this topic produces
- Diligence checklist for disaster risk finance evidence
- Guide to open risk models and data standards
- Method note on reviewing trigger design
- Questions buyers should ask sellers and brokers
What financing evidence and diligence means for exposure, loss and capital.
The exposure, loss, scenario and capital views a risk officer, supervisor or ministry of finance would ask for, with the frameworks they report against. Structures follow supervisory and actuarial practice. Values are illustrative: never prices, ratings or advice.
Financing instruments by layer
How retention and transfer instruments could share losses from financing evidence and diligence, from frequent to extreme.
| Layer | Who holds the risk | Speed of funds | Main limit |
|---|---|---|---|
| Retention and reserves | Budget, contingency funds | Immediate | Size of the budget |
| Contingent credit | Development banks, ministries of finance | Days to weeks | Debt capacity |
| Parametric cover and risk pools | Regional pools, insurers | Days, on a trigger | Basis risk |
| Reinsurance and catastrophe bonds | Reinsurers, capital markets investors | Weeks to months | Cost of capital |
| Residual loss | Households, firms, humanitarian funding | Uncertain | Unfunded |
The questions experts ask.
- What do independent reviewers need to know to assess a disaster finance arrangement?
- Is the hazard and loss evidence credible, documented and reproducible?
- Are plans for using funds clear, and are delivery channels in place?
- Is the governance of decisions and funds transparent and accountable?
- What uncertainties remain, and are they stated honestly?
What diligence looks at.
Reviewers, whether credit committees at development institutions, underwriters, investors or public audit bodies, typically examine several areas. Risk evidence covers hazard data, exposure, vulnerability and modelled losses, with their sources and uncertainty. Operational evidence covers plans, delivery systems and institutional capacity. Governance evidence covers legal authority, decision rules, safeguards and accountability. Financial evidence covers fiscal position, existing arrangements and how a new arrangement would fit.
Evidence quality matters more than volume. Reviewers look for documented methods, traceable sources, independent validation and clear statements of what is not known. Overstated certainty undermines trust; honest uncertainty allows reviewers to price or plan for it.
A disaster finance dossier, as the Global Risks Alliance (GRA) designs it, assembles such evidence as research for independent reviewers. It does not recommend a transaction, assess creditworthiness or certify readiness. Readiness is not approval: the decision remains with the reviewer and the competent authority.
Methods and their limits.
Evidence classes
Distinguishing observed data, modelled estimates and expert judgement.
Independent review
Review of models and data by parties not involved in producing them.
Traceability
Recording sources, versions and transformations so evidence can be checked.
Limits: evidence can reduce uncertainty but not remove it, and some information reviewers want, such as future political responses, cannot be known.
How it is studied, and what the methods cannot say.
- 01Actuarial mathematicsSizing retention and transfer layers · Pricing parametric cover · Contingency fund sizingApplied here
- 02Forecasting and time-series analysisForecast verification for triggers · Seasonal outlooks for drought financeApplied here
- 03Decision analysis under uncertaintyChoosing an instrument mix · Trigger threshold choice · Release rules for contingency fundsApplied here
- 04Economics and development economicsCost of ex post versus ex ante finance · Household welfare effects · Fiscal impact of disastersApplied here
Questions and answers.
What should diligence check in a parametric product?
What is the Risk Data Library?
Why do open models matter?
Is a dossier a recommendation to finance?
Who prepares dossiers?
Can a dossier be corrected?
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