GCRI · Global challenges
Systemic and cascading risks
Systemic risk is the risk that a shock in one part of a connected system spreads, amplifies and disrupts the whole. A drought travels through water, energy, food prices, budgets and health. A financial failure halts payments that hospitals and utilities rely on. The Global Centre for Risk and Innovation (GCRI) traces where shocks cross systems, where they amplify and where they can be stopped. Part of global challenges.
01Register
Systemic and cascading risks on the record.
The Global Centre for Risk and Innovation
- 01InstitutionThe Global Centre for Risk and Innovation (GCRI)
- 02Key ideasFour features make a risk systemic
- 03Terms and measuresWhat systemic risk means in practice, and what can be measured
- 04Methods and their limitsThe models experts use for connected risk, and where each breaks down
- 05Data and its statusThe evidence on connected risk is thinner than the evidence on single hazards
- 06GCRI’s partWhat GCRI does here, how it reaches Reports, and how you can help
- 07How GCRI approaches itMethods for connected risk
02Key ideas
Four features make a risk systemic.
Systemic risk is not a separate hazard. It is a property of how systems are connected, which is why it is often invisible to assessments made one sector at a time.
Coupling
Tight connections
Systems linked by flows of power, water, goods, data and money pass stress along quickly.
Amplification
Feedback loops
Price spikes, hoarding, panic and forced sales can make a shock larger as it spreads.
Common mode
Shared points of failure
One asset, supplier or assumption underneath many services can fail them all at once.
Non-linearity
Thresholds and tipping points
Systems can absorb stress up to a point and then change state abruptly.
03Terms and measures
What systemic risk means in practice, and what can be measured.
Two definitions anchor the work. The International Risk Governance Center describes systemic risks as risks to the functioning of a system that arise from the interactions of its parts. Their effects reach well beyond the point of origin. The UNDRR Global Assessment Report of 2019 adds that such risk is often embedded in a system without being recognised as a risk, until a shock reveals it.
| Concept | What it describes | How it is measured |
|---|---|---|
| Interdependency | A two-way state relation between systems; Rinaldi and colleagues distinguish physical, cyber, geographic and logical links | Dependency matrix of services and assets; share of a service’s inputs that come from each other system |
| Cascade | A failure that triggers failures elsewhere, possibly in sequence over hours, weeks or seasons | Fraction of nodes or services failed after propagation; time from first failure to last; time to recover in days |
| Amplification | A feedback that makes the shock larger as it spreads: fire sales, hoarding, price spikes, loss of confidence | Ratio of total to initial loss in a model run, reported with its range |
| Concentration | Many functions resting on one asset, supplier, route or assumption | Supplier or route shares; Herfindahl-Hirschman concentration index; count of single points of failure |
| Critical transition | An abrupt shift between states once a threshold is crossed | Rising variance and lag-one autocorrelation in long series, read as a possible warning, not a forecast |
04Methods and their limits
The models experts use for connected risk, and where each breaks down.
| Method | What it answers | Where it breaks down |
|---|---|---|
| Network contagion models, including DebtRank (Battiston and others, 2012) | Which institutions or assets carry a shock furthest through a web of exposures | Exposure networks are rarely complete or public; missing links change who looks central |
| Interdependent network percolation (Buldyrev and others, 2010) | Why coupled networks can collapse abruptly where a single network would degrade gradually | Stylised: real operators reroute, shed load and repair, which the theory leaves out |
| Input-output and inoperability models | How lost output in one sector reduces output in sectors that buy from it | Fixed technical coefficients allow no substitution; results overstate losses over longer horizons |
| Agent-based models | How behaviour such as hoarding, panic or switching suppliers shapes spread | Many parameters and few validation data; results are explorations, published with their sensitivity |
| Storylines and compound stress scenarios | What a physically and economically coherent bad sequence looks like, step by step | Carry no probability; their value depends on whether experts in each system test each step |
Haldane and May showed in 2011 how homogeneity and tight coupling made a banking system fragile in ways no single bank’s risk model could see. The same lesson holds for water, power and food systems: the property that matters belongs to the network. Every model result here carries its assumptions, its range and the label Modelled or Scenario.
05Data and its status
The evidence on connected risk is thinner than the evidence on single hazards.
| Evidence | What it gives | Honest status |
|---|---|---|
| National supply and use tables, and inter-country input-output tables (OECD ICIO) | Flows between sectors and countries for propagation models | Published with a lag of several years; sector detail too coarse for many infrastructure questions |
| Disaster loss databases (EM-DAT, DesInventar Sendai) | Recorded direct losses by event and place | Indirect and cascading losses are rarely recorded; small events are under-reported |
| Infrastructure dependency data held by operators | Which assets serve which services | Mostly restricted for security reasons; public studies work with permitted or synthetic topology |
| Supervisory financial exposure data | Bilateral exposures between institutions | Held by supervisors; public work relies on aggregates and reconstructed networks |
Where the data cannot support a claim, the page says the claim cannot yet be made. A gap is shown as a gap, never filled with a plausible number.
06GCRI’s part
What GCRI does here, how it reaches Reports, and how you can help.
GCRI is a research, development and policy institution. On systemic risk it develops and tests methods, helps national teams map their own dependencies on their own data, and publishes what review supports. It does not regulate, supervise, fund or approve projects, and every decision on a system stays with the authority or operator that runs it. Work is organised through the Systemic Risk Management platform and the Systems Science and Modelling platform.
Findings are designed to reach the Global Systems Risk and Resilience series and the Scenario and Stress-Test series. Under the proposed Nexus Standards, each dependency record and indicator series would carry a record identifier (NS-3) and each model a model card (NS-12). A reader could then trace a result back to its inputs.
- A documented cascade with a source for each step, including the steps where attribution is uncertain.
- A critique of a propagation method, with the case where it failed.
- Permitted dependency data for a city or sector, offered under stated terms through the Secretariat.
07How GCRI approaches it
Methods for connected risk.
- 01
Map the system
Dependencies across sectors and borders with network science and contagion.
- 02
Simulate propagation
Complex systems and agent-based models that show how behaviour shapes spread, with assumptions stated.
- 03
Stress-test
Compound scenarios using scenario design and stress testing, labelled as scenario evidence.
- 04
Find points of control
Interventions that cut or buffer transmission, with their trade-offs and limits.
08Where to go next
Platforms, fields and counterparts.
Field work runs through the Systemic Risk Management platform and the Systems Science and Modelling platform, and the risk management and systemic risk field gateway. The Global Risks Forum (GRF) examines all-hazards governance. The Global Risks Alliance (GRA) examines systemic stability in finance. Worked illustrations: risk transmission examples.
A model of systemic risk is a tool for understanding, not a prediction. Every result states its assumptions and uncertainty.
09Sources
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.
- IRGC Guidelines for the Governance of Systemic Risks (EPFL International Risk Governance Center, 2018)
- Global Assessment Report on Disaster Risk Reduction 2019, the systemic risk edition (UNDRR, 2019)
- OECD Recommendation of the Council on the Governance of Critical Risks (OECD, 2014)
- Haldane and May, Systemic risk in banking ecosystems, Nature 469 (2011)
- Battiston and others, DebtRank: too central to fail?, Scientific Reports 2 (2012)
- Buldyrev and others, Catastrophic cascade of failures in interdependent networks, Nature 464 (2010)
- Rinaldi, Peerenboom and Kelly, Identifying, understanding and analysing critical infrastructure interdependencies, IEEE Control Systems Magazine 21 (2001)
- Scheffer and others, Early-warning signals for critical transitions, Nature 461 (2009)
- OECD Inter-Country Input-Output tables and Trade in Value Added database
- NS-3, NXS-GRX (canonical data, provenance and risk) record UNIs, a proposed standard
- NS-12, Software, model and AI/ML artefacts, a proposed standard
10Questions
Questions and answers.
How is systemic risk different from ordinary risk?
Ordinary risk analysis looks at one hazard and one system. Systemic risk analysis looks at how connections spread and amplify a shock, so the whole can fail even when each part looks sound.
Can systemic risk be measured with one number?
No single number captures it. GCRI uses NXS-GRX-native indicators with their sources and uncertainty, alongside maps of dependencies and scenario results.
Who uses this work?
Ministries, regulators, operators, researchers and financial institutions that need to see across sector boundaries. Decisions remain with them.
How do countries take part?
Through a national programme, which starts with an exploration led by an accountable national contact. The Secretariat and regional desks receive those enquiries.
Can systemic risk be eliminated?
No. Connection brings efficiency and reach as well as exposure. The aim is to understand where coupling creates fragility, to add buffers and alternatives where they matter most and to recover faster when shocks occur.
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