G-P01 · TOPIC · identification-and-risk-taxoGCRI dossier · service level R0
GCRISystemic Risk ManagementIn development
Topic dossier · 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.

Systems · around this subjectDesign, not a record

Risk register

Identification and risk taxonomy · Enterprise A · Review cycle Q3

Three risks above appetiteGCRI · Systemic Risk Management

Residual risk

likelihood × impact, risks per cell

Counts of risks per cell. Shading follows the appetite bands.

Above appetite

Supplier concentrationProcurementHigh▲ 1
Data centre floodingOperationsHigh▲ 0
Model error in pricingFinanceMedium▲ 0
Key staff lossPeopleMedium▼ 0

Risk management process, after the international standard

  1. Scope, context, criteriaset
  2. Identifytaxonomy
  3. Analyselikelihood · impact
  4. Evaluatevs appetite
  5. Treatplans
  6. Monitor and reviewKRIs
  7. Record and reportboard

Treatment actions

  1. T-11Dual-source critical componentOwner: procurement · overdue4 d late
  2. T-14Move backup site above flood levelOwner: operationsdue 28 d
  3. T-17Independent model validationOwner: financedue 27 d
Risk register: the screen's structure, terms and states for Identification and risk taxonomy.Placeholder names and illustrative values; a design, not a record or a live system.

Fig.Risk register. Design wireframe with placeholder names and illustrative values, not a record or a live system.

01In brief

The short answer.

A risk taxonomy is a structured set of names and categories used to describe risks consistently, so registers can be compared and combined. Identification finds the hazards, threats and consequences that matter. Reference vocabularies such as the UNDRR-ISC Hazard Information Profiles let national and organizational registers describe the same hazard in the same terms.

02Geography

Hazards and exposure in Asia.

For identification and risk taxonomy, in GCRI's spatial-intelligence reading, the map opens on population density, true-colour imagery and flood water, framed on Asia; every other NASA layer, live feed and forecast waits in the layer list.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Hazards and exposure, for this page

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.

For identification and risk taxonomy, in GCRI's spatial-intelligence reading, the map opens on population density, true-colour imagery and flood water, framed on Asia; 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 · NASA EONET · GDACS · Copernicus Sentinel-2 L2ASources 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 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
  • 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 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
  • 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.
  • Live: NASA EONET Events are indicative, not official warnings.
  • Live: GDACS (EC JRC / UN OCHA) Events are indicative, not official warnings.
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • 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
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 2026
  • Active fires and thermal anomalies, last day: VIIRS NOAA-20 375 m (FIRMS), NASA LANCE FIRMS · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026

03The question

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.

Mechanism

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.

Mechanism

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.

Mechanism

Names differ between registers

Two organizations 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.

Mechanism

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 organization's real exposure.

04Key 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
Risk identificationThe process of finding, recognising and describing risks that could affect objectives.
Risk registerA record of identified risks with their owners, assessments, treatments and review dates.
HazardA process, phenomenon or human activity that may cause loss of life, injury, damage or disruption, in UNDRR usage.
Horizon scanningA systematic search for early signs of emerging risks and opportunities beyond current planning.
05Indicators

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.

IndicatorUnitCadenceSource typeLabel
Register entries mapped to a reference taxonomypercent of entriesper reviewRisk registerREPORTED
Emerging risks addedcount per review cycleper reviewHorizon scanning recordsREPORTED
Risks spanning more than one categorycountper reviewRisk register with linked categoriesREPORTED
Time since last register reviewmonthscontinuousRegister metadataOBSERVED
Hazards covered against a reference listpercent of applicable hazard profilesannualComparison with UNDRR-ISC Hazard Information ProfilesESTIMATED
External sources consulted in identificationcount by typeper reviewIdentification method recordDECLARED
06Canvas

From sources to decisions.

The topic as a computational graph: named sources feed the methods, an evidence review gates the outputs, and the decisions stay with the authorities that hold them.

Pipeline canvas · Identification and risk taxonomy as a run graphDesign, not a record
Identification and risk taxonomy: bank stress testA scenario is designed and the balance sheet projected; credit losses, net interest income and market losses are estimated; capital ratios are compared with the hurdle, management actions considered and the supervisor reviews. Design of the process, not a record of a run.

Fig. 02Nodes carry their type, two metric rows and a state; connectors show what feeds what; dashed frames name the owners; the timeline is the cadence. Design of the pipeline, not a record of a run.

07Sources

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.

SourceWhat it givesLicence class
UNDRR-ISC Hazard Information ProfilesStandard definitions and descriptions of hazards across natural, technological, biological and societal clustersPublic, UNDRR and ISC terms of use
UNDRR terminology on disaster risk reductionAgreed definitions of hazard, exposure, vulnerability, capacity and related termsPublic, UN terms of use
National risk registers and national risk assessmentsGovernment-published lists of risks with their descriptions and assessment approachPublic records, licence per government (UK under Open Government Licence)
IEC 31010 Risk assessment techniquesDescriptions of identification techniques such as checklists, HAZOP and scenario analysisLicensed standard, purchase required
IRDR Peril Classification and Hazard GlossaryA hierarchical classification of perils used in loss databasesPublic, IRDR terms of use (to check)
08Decisions

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 decidesThe questionEvidence this page serves
Chief risk officers and risk teamsWhich taxonomy the register should follow, and how emerging risks enter itCrosswalks; register health checks; identification protocols
National risk assessment teamsWhich hazards and threats belong in the national registerCoverage against reference hazard profiles; peer register comparison
Sector regulatorsWhich risk classes regulated entities must report in a common formatTaxonomy options with their mapping to existing reporting

Outputs this topic produces

  • Crosswalks between organizational 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
09Core questions

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?
10Mechanisms

Why risks are missed.

Identification fails less from lack of effort than from the way organizations are built. Registers mirror the organization chart, so each unit reports the risks it owns and few report the risks that arise between units or outside the organization altogether.

Silos

Categories hide links

A taxonomy that separates operational, financial and strategic risks can hide a single cause behind all three.

Inertia

Registers age

Registers are updated incrementally and drift away from how the organization and its environment actually work.

Bias

Familiarity and optimism

People overweight recent and vivid events and underweight unfamiliar ones.

11Methods and limits

How risks are found and organized.

  1. 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.

  2. 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.

  3. 03

    Horizon scanning

    Structured search for weak signals of emerging risk. It produces many false alarms and needs disciplined follow-up.

  4. 04

    Structured workshops

    Pre-mortems, red teams and cross-functional reviews widen perspective. Group dynamics can still suppress dissent.

12Methods

How it is studied, and what the methods cannot say.

  1. Decision analysis under uncertaintyMulti-criteria treatment choice · Decision trees for contingent plansApplied here
  2. Network science and contagionDependency network mapping · Centrality and concentration · Failure propagation simulationApplied here
  3. Uncertainty quantification and model validationPropagating input uncertainty · Separating kinds of uncertainty · Deep uncertainty framingApplied here
13Questions

Questions and answers.

What is a risk taxonomy?
A structured set of risk names and categories, often hierarchical, used so that risks are described consistently across an organization or between organizations.
Why use the UNDRR-ISC Hazard Information Profiles?
They give agreed definitions for hundreds of hazards, which lets national and organizational registers describe the same hazard in the same terms and supports comparison and data exchange.
How often should a risk register be reviewed?
On a fixed cycle set by the organization and also when triggers occur, such as a major incident, a new activity, a change in a dependency or new external evidence.
What is the difference between a taxonomy and an ontology?
A taxonomy sorts risks into categories. An ontology also records relationships, such as which events share a cause or which controls address several risks, so that links can be analysed.
How often should a register be rebuilt rather than updated?
There is no fixed rule. A rebuild is warranted when the organization, its dependencies or its environment change substantially.
Can the platform review my register?
No. It publishes methods that organizations can apply themselves.
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