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  From the report
Executive Summary
The Global Risks Landscape 2010
Fiscal Crises and Unemployment
Underinvestment in Infrastructure
Chronic Diseases
Risks to Keep on the Radar
Managing Global Risks
Processes and Definitions
Global Risks Barometer 2010
Contributors and Acknowledgements
  Global Risks 2010
    In collaboration with Citi, Marsh & McLennan Companies (MMC)
    Swiss Re, Wharton School Risk Center, Zurich Financial Services
Global Risks 2010 Home

Appendix 1: Processes and Definitions Printer friendly version  Send to a friend

How global risks are defined
The criteria for global risks have been set as follows:

Global Scope: To be considered global, a risk should have the potential to affect no less than three world regions on at least two different continents. While these risks may have regional or even local origin, their impact can potentially be felt globally.
Cross-Industry Relevance: The risk has to affect three or more industries.
Uncertainty: There is uncertainty about how the risk manifests itself within 10 years combined with uncertainty about the magnitude of its impact (assessed in terms of likelihood and severity).
Economic Impact: The risk has the potential to cause economic damage of US$ 10 billion or more.
Multistakeholder Approach: The complexity of the risk both in terms of its effects and its drivers, as well as its interlinkages with other risks, requires a multistakeholder approach for its mitigation. The risks are classified in five domains: economic, geopolitical, environmental, societal and technological risks.

The Risks Interconnection Map (RIM) and Global Risks Experts Perception Survey
One of the highlights of the Global Risks report is the analysis of the interconnectedness between global risks (see Figure 14). By detailing these links, the report aims to increase awareness and understanding of the interlinkages among risk issues and what this implies for decisions on risk management and mitigation.

The data used to build the Risk Interconnections Map (RIM, see Figure 14) is drawn from two sources:

1. The connections and strengths are developed using data from the Global Risks Experts Perception Survey 2010. This Web-based survey was completed over the third quarter of 2009 by over 200 experts, business leaders and policymakers from the Forum's and the Report partners' networks, as well as members of the Forum's Global Agenda Councils. The survey assesses how respondents perceive a selection of global risks tracked by the Global Risk Network (see above section "How global risks are defined"). For each risk respondents are asked to select 3 other risks from the taxonomy of global risks that they consider are the most connected to the risk in question. The aim is not to determine causal relationships among the risks or to identify drivers and consequences, but rather to determine the number and strength of interconnections between different risks.

2. The nodes on the RIM represent the same assessment data for severity and likelihood as in the Global Risks Landscape and the Global Risks Barometer, which are drawn from qualitative assessment that represents the aggregate views of experts from the partners involved in this Report. A greater node size indicates a higher likelihood (%), while a thicker node circumference shows a higher severity (US$). Each line represents a connection to another risk, while their thickness indicates the strength of the relationship between them.

The Global Risks Landscape
The visualisation of risk on the landscape places risks by severity of impact (measured in US$) on the vertical axis and the likelihood of occurrence on the horizontal axis over a 10-year time horizon. The numerical assessment of these categories of risks is created through qualitative assessment by the partners of the report. The risks which appear in the upper right-hand corner are those with the highest impact and highest likelihood and are the focus of the narrative of this report.

A note on the regional map of risk exposure produced by Zurich Financial Services (Figure 4)

The analysis is based on a methodology and data set developed by Zurich Financial Services. The methodology is broadly comparable to statistical cluster analysis that partitions a data set into subsets (or clusters) with the data in each subset (cluster) sharing common characteristics - in this case the characteristics are risks. Countries with similar risks are close neighbours on the risk map; they form clusters. In contrast, countries that are dissimilar with respect to their risk characteristics are displayed comparatively far apart from each other.

The data set covers 158 countries and more than 30 global risks. The risks are grouped in five risk classes: economic, environmental, health, geopolitical and technological risks. Data are drawn from established and reliable public sources and incorporated into the model using metrics developed by Zurich Financial Services for a spectrum of risk ranging from low to high.