GCRI · Systemic Risk Management
Identification and risk taxonomy
Risks that are not named are not managed. Identification finds the hazards, threats, vulnerabilities and consequences that matter, and a taxonomy gives them shared names and classes so that registers can be compared, aggregated and linked. This page sets out how identification works, where taxonomies help and where they hide interconnection, and the reference vocabularies that make one register readable beside another.
How the work runs.
Risk register
Identification and risk taxonomy · Enterprise A · Review cycle Q3
Residual risk
likelihood × impact, risks per cell
Counts of risks per cell. Shading follows the appetite bands.
Above appetite
| Supplier concentration | Procurement | High | ▲ 1 |
| Data centre flooding | Operations | High | ▲ 0 |
| Model error in pricing | Finance | Medium | ▲ 0 |
| Key staff loss | People | Medium | ▼ 0 |
Risk management process, after the international standard
- Scope, context, criteriaset
- Identifytaxonomy
- Analyselikelihood · impact
- Evaluatevs appetite
- Treatplans
- Monitor and reviewKRIs
- Record and reportboard
Treatment actions
- T-11Dual-source critical componentOwner: procurement · overdue4 d late
- T-14Move backup site above flood levelOwner: operationsdue 28 d
- T-17Independent model validationOwner: financedue 27 d
Fig.Risk register: example names and illustrative values, not a record or a live system.
Identification and risk taxonomy: how the risk develops.
Risk identification beyond registers. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Identification follows experience
Workshops and registers list the risks people have seen before. Novel, slow or cross-sector risks are under-identified unless horizon scanning, scenario work and external sources are used deliberately.
Categories set what is seen
A taxonomy that sorts risks into separate boxes, such as operational, financial and strategic, can hide the links between them. Risks that span categories are split or counted twice.
Names differ between registers
Two organisations describe the same hazard in different terms and at different levels of detail. Without a shared reference vocabulary, their registers cannot be combined into a picture of shared exposure.
Registers go stale
A register reviewed once a year misses emerging risks and keeps retired ones. Without triggers for review, the list drifts away from the organisation’s real exposure.
Hazards and exposure in Asia.
Population density, flood water and active fires over Asia, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Hazards and exposure, 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 (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
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- 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.
Hazards and exposure, framed on Asia.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 Survey · NASA JPL OPERA DIST-ALERTSources 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 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
- MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery 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.
- Live: U.S. Geological Survey Events are indicative, not authority warnings.
- Observed (EO): NASA JPL OPERA DIST-ALERT (contains modified Copernicus Sentinel data 2026). 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).
- 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).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (11 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
- 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 cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
- Land surface temperature, day, 8-day composite: VIIRS NOAA-20 Level 3, 8-day, NASA LANCE · 14 Sep 2026
A taxonomy decides which cross-domain risks are seen at all.
- WaterCouplingHazard taxonomies such as the UNDRR-ISC profiles separate drought types that a single label would merge.What to watchConsistent use of hazard definitions in registers
- HealthCouplingZoonotic spillover falls between environment and health registers unless the taxonomy names it.What to watchSpillover risk in national registers
- BiodiversityCouplingSlow-onset ecosystem decline is often missing from registers built around events.What to watchSlow-onset risks recorded
Taxonomy work is designed for the Methods and Technical series. A shared taxonomy would carry identifiers for each risk class under NS-3 of the proposed Nexus Standards, so registers in different ministries can be compared.
- National risk registers and the taxonomies behind them, where published.
- Crosswalks between sector taxonomies.
Stocks, flows, delays and a tipping threshold.
Two stocks, pressure and adaptive capacity, joined by a reinforcing growth loop, a delayed balancing response and damage when pressure outruns capacity; past the threshold the system can tip. Teaching model with stated illustrative values, not a prediction. The map on this page shows Asia; the model itself is not tied to a place.
Controls
- Growth of pressure
- 6.0% a year
- Efficacy of capacity in reducing pressure
- 4.0% a year
- Investment response to perceived pressure
- 20%
- Perception delay
- 4.0 years
- Tipping threshold of pressure
- 60 index
- Amplification past the threshold
- 2.0 times
- Years simulated
- 50 years
Readouts
- Peak pressure
- 113 index
- Capacity at the end
- 186 index
- Years over the threshold
- 15.8 years
Numbers, methods and sources
| Year | Pressure | Capacity | Perceived |
|---|---|---|---|
| 0 | 20.0 | 50.0 | 20.0 |
| 4 | 23.3 | 44.9 | 21.2 |
| 8 | 27.2 | 42.2 | 24.0 |
| 12 | 31.7 | 42.3 | 27.7 |
| 16 | 36.8 | 45.5 | 32.2 |
| 20 | 42.3 | 51.5 | 37.2 |
| 24 | 47.9 | 60.3 | 42.6 |
| 28 | 53.2 | 71.3 | 48.0 |
| 32 | 57.8 | 84.3 | 53.1 |
| 36 | 66.4 | 98.4 | 58.4 |
| 40 | 82.7 | 115.9 | 69.7 |
| 44 | 97.8 | 139.7 | 83.8 |
| 48 | 109.1 | 169.4 | 97.3 |
Methods
- System dynamics Forrester (1961), Industrial Dynamics, MIT Press; Sterman (2000), Business Dynamics
- Critical transitions and tipping points Scheffer and others (2009), Early-warning signals for critical transitions, Nature 461
- Causal loop diagram Sterman (2000), Business Dynamics, McGraw-Hill
- 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
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Systemic Risk Management in Foundry
- Tested at Systemic Risk Management in Universe
- Codified in Systemic Risks in Standards
- Published in Systemic Risk Management in Reports
- Taught in Faculty of Risk Science and Methods in Academy
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 |
|---|---|---|---|---|
| Register entries mapped to a reference taxonomy | percent of entries | per review | Risk register | REPORTED |
| Emerging risks added | count per review cycle | per review | Horizon scanning records | REPORTED |
| Risks spanning more than one category | count | per review | Risk register with linked categories | REPORTED |
| Time since last register review | months | continuous | Register metadata | OBSERVED |
| Hazards covered against a reference list | percent of applicable hazard profiles | annual | Comparison with UNDRR-ISC Hazard Information Profiles | ESTIMATED |
| External sources consulted in identification | count by type | per review | Identification method record | DECLARED |
Model identification and risk taxonomy as a system. Run the cascade.
Assembled from the Nexus Standards area profile Global and systemic risk: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.
Hazards
- Dam failure
- Financial contagion
- River flood (set off downstream)
- Flash flood (set off downstream)
- Mass displacement (set off downstream)
- Widespread power outage (set off downstream)
- Water supply shortfall (set off downstream)
- Sovereign debt crisis (set off downstream)
- Currency crisis (set off downstream)
Systems and couplings
- Global and systemic risk
- Compound and cascading hazard standards Mechanism
- Financial stability and prudential risk Mechanism
- Supply chain and trade risk Cascade
- Future generations and long-term risk Common driver
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-H120Hazard family: Structural fragility of interconnected systems (NHS-1 sys.fragility)NRS-C6Systemic and cascading riskNRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-H62Hazard family: Compound and multi-hazard events (NHS-1 sys.compound)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-H60Hazard family: Supply-chain and flow disruption (NHS-1 sys.supply-chain)
Observation
- INFORM Risk Index (listed for reference)
- World Bank Open Data and World Development Indicators API (listed for reference)
- IMF data services (WEO, IFS, FSI via SDMX) (listed for reference)
- Direct economic loss attributed to disasters in relation to global GDP
- Macroeconomic Dashboard
Example geography
- Bangladesh: 134 hexagonal cells
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface soil moisture (SMAP), NASA GIBS
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 |
|---|---|---|
| UNDRR-ISC Hazard Information Profiles | Standard definitions and descriptions of hazards across natural, technological, biological and societal clusters | Public, UNDRR and ISC terms of use |
| UNDRR terminology on disaster risk reduction | Agreed definitions of hazard, exposure, vulnerability, capacity and related terms | Public, UN terms of use |
| National risk registers and national risk assessments | Government-published lists of risks with their descriptions and assessment approach | Public records, licence per government (UK under Open Government Licence) |
| IEC 31010 Risk assessment techniques | Descriptions of identification techniques such as checklists, HAZOP and scenario analysis | Licensed standard, purchase required |
| IRDR Peril Classification and Hazard Glossary | A hierarchical classification of perils used in loss databases | Public, IRDR terms of use (to check) |
How identification and risk taxonomy is modelled, measured and tested.
The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.
Model, equations and assumptions
The model structure used for identification and risk taxonomy, the assumptions it makes and how each is tested.
Ri = f(Hi, Ei, Vi, Ci)hazard, exposure, vulnerability and coping capacityEAL = ∑k pk · Lkover events k with annual probability pkxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Assumption | Why it is made | How it is tested |
|---|---|---|
| Hazard and exposure are independent within an event | Keeps the loss integral tractable | Compare with a copula fit on joint records |
| Couplings are linear near the operating point | Lets shocks propagate through A | Perturb beyond the linear range and compare |
| Vulnerability curves transfer between places | Local curves are rarely available | Validate against observed losses where they exist |
- Inputs
- versioned datasets with provenance
- Outputs
- distributions, never single numbers
- Code
- released with the model card and tests
- Reproduction
- same data, code, environment and seed
Who decides, and what the evidence serves.
Systemic Risk Management 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 |
|---|---|---|
| Chief risk officers and risk teams | Which taxonomy the register should follow, and how emerging risks enter it | Crosswalks; register health checks; identification protocols |
| National risk assessment teams | Which hazards and threats belong in the national register | Coverage against reference hazard profiles; peer register comparison |
| Sector regulators | Which risk classes regulated entities must report in a common format | Taxonomy options with their mapping to existing reporting |
Outputs this topic produces
- Crosswalks between organisational registers and reference hazard profiles
- Identification protocols that combine workshops, horizon scanning and external data
- Linked taxonomies that record dependencies between risk classes
- Register health checks covering completeness, ownership and review dates
What identification experts ask.
- What risks do we face that do not fit neatly into any category of our taxonomy?
- Which risks share causes or pathways, even though they sit in different parts of the register?
- What has changed in our environment, technology or dependencies since the register was last rebuilt?
- Whose knowledge is missing: front-line staff, suppliers, affected communities?
Why risks are missed.
Identification fails less from lack of effort than from the way organisations are built. Registers mirror the organisation chart, so each unit reports the risks it owns and few report the risks that arise between units or outside the organisation altogether.
Categories hide links
A taxonomy that separates operational, financial and strategic risks can hide a single cause behind all three.
Registers age
Registers are updated incrementally and drift away from how the organisation and its environment actually work.
Familiarity and optimism
People overweight recent and vivid events and underweight unfamiliar ones.
How risks are found and organised.
- 01
Risk ontology
A formal structure of concepts and relationships, such as cause, event, consequence and control, that lets risks be linked rather than only listed. Building one takes sustained effort and agreement on terms.
- 02
Causal mapping
Bow-tie diagrams, fault trees and causal loop diagrams expose shared causes and pathways. They are only as complete as the knowledge of those who build them.
- 03
Horizon scanning
Structured search for weak signals of emerging risk. It produces many false alarms and needs disciplined follow-up.
- 04
Structured workshops
Pre-mortems, red teams and cross-functional reviews widen perspective. Group dynamics can still suppress dissent.
How it is studied, and what the methods cannot say.
- 01Decision analysis under uncertaintyMulti-criteria treatment choice · Decision trees for contingent plansApplied here
- 02Network science and contagionDependency network mapping · Centrality and concentration · Failure propagation simulationApplied here
- 03Uncertainty quantification and model validationPropagating input uncertainty · Separating kinds of uncertainty · Deep uncertainty framingApplied here
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.
Questions and answers.
What is a risk taxonomy?
Why use the UNDRR-ISC Hazard Information Profiles?
How often should a risk register be reviewed?
What is the difference between a taxonomy and an ontology?
How often should a register be rebuilt rather than updated?
Can the platform review my register?
Contribute evidence from this page.
Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
- ZenodoOpen depositDeposit it and submit to the communityPublish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.
- ReportsGCRISee every way to contributeThe contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.
Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.
Bring a method, a dataset or a question.
Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.
Legal documents.
Maps, data and figures on this site are shown for context and general information. They are not advice, forecasts or warnings; the limits of the information are set out in the Disclaimers and Data Notices.