Canadian cities see reduction in large-scale event attack frequency: RMS terrorism model

RMS’s updated terrorism model reflects a reduction in large-scale event attack frequency for cities in Canada, Denmark, Ireland, Italy and the United Kingdom, the catastrophe modelling firm reports.

The updated Probabilistic Terrorism Model “shows a 15% to 35% reduction in the overall attack frequency of large-scale events for Copenhagen, Dublin, London, Milan, Montreal and Toronto, Rome and Vatican City,” Chris Folkman, director of model product management at RMS, notes in a statement issued Wednesday.

“Worldwide, the frequency of macro-terrorism attacks is 85% lower in 2014 than in 2006, with a marked decrease over the past six years due to reduced terrorist threat and increased counterterrorism capabilities,” Folkman points out.

The model includes only large-scale events that could threaten the solvency of an insurer or reinsurer, RMS reports, adding that such events have caused minimal insured losses in recent years.

The updated model – which offers a catalog of more than 90,000 high-resolution attack scenarios and almost 10,000 terrorism targets – follows RMS’s analysis of all major global terrorism events in the past decade, as well as changes in the risk landscape for each of the modelled countries.

The updated model reflects the following trends in terrorism:

• decline in the frequency of macro-terrorism attacks, attacks that result in significant property damage and more than 20 fatalities or more than 50 injuries;
• decline in the overall threat of large-scale terrorist attacks due to weakened al-Qaida operational capabilities and successful counter-terrorism measures; and
• continued violence and instability in Pakistan, Iraq and Syria, which provide a safe harbour for terrorist operations and recruitment.

RMS has also updated the three sets of rates – standard, reduced and increased – in its model, the statement notes.

The multiple views of risk reflect varying assumptions about the threat-level to enable model users to respond to rapid changes in the terrorism risk landscape, as well as perform sensitivity tests on prospective portfolios, RMS reports. The modeller’s view of attack probability is calibrated based on attack, plot and countersecurity data from open source intelligence.

“The model provides a granular probabilistic view of terrorism risk to equip underwriters and portfolio managers with an empirically driven method of evaluating terrorism risk, enabling them to manage their exposure, set corporate risk tolerances and assess the relative risk between prospective portfolios,” Folkman says.