Tag Archives: RMS Probabilistic Terrorism Model

Terrorism Modeling 101

Acts of terror can result in wide ranges of potential damage and the financial repercussions can threaten an insurer’s solvency.

Terrorism risk can be modeled probabilistically with an increasing degree of confidence. Its damages at long return periods are comparable to natural disasters such as hurricanes and earthquakes.

The events of September 11, 2001 resulted in insurable damages in excess of $44 billion, causing insurers to explicitly exclude terrorism from standard property policies. This resulted in the downgrade of billions in mortgage securities, and the costly delay of many important development, construction, and infrastructure projects.

The Terrorism Risk Insurance Act (TRIA)

To address the terrorism insurance shortage, the Terrorism Risk Insurance Act (TRIA) was signed into law by President George W. Bush in 2002, creating a $100 billion federal backstop for insurance claims related to acts of terrorism.

Originally set to expire December 31, 2005, it was extended for two years in December 2005, and again in 2007. The current extension, entitled the Terrorism Risk Insurance Program Reauthorization Act (TRIPRA), will expire on December 31, 2014 and its renewal is up for debate in Congress.

Insuring Against Terrorism

Just as with natural catastrophe risk, insurers rely on catastrophe models to underwrite and price terrorism risk.

Terrorism threat is a function of intent, capabilities, and counter-terrorism action; counter-terrorism factors have an impact on frequency, multiplicity, attack type, and targeting of terrorist actions, as well mitigation of loss. It’s not just what the terrorists can do that controls the outcome; it’s what governments can do to counteract their efforts.

RMS was first-to-market with a probabilistic terrorism model and has been providing solutions to model and manage terrorism risk since 2002. The RMS Probabilistic Terrorism Model takes a quantitative view of risk, meaning it uses mathematical methods from game theory, operational research, and social network analysis to inform its view of frequency. Its development involved the input of an extensive team of highly qualified advisors, all of which are authorities in their field of assessing terrorism threats.

The Probabilistic Terrorism Model is made up of four components:

  • The potential targets (comprised of landmark properties in major cities) and associated attack mode combinations (both conventional and CBRN – chemical biological, radiological, and nuclear), knowing that not every target is susceptible to all types of attack modes.
  • The relative likelihood of an attack, taking into account the target and type of attack. For example, attacks using conventional bombs are easier to plan for and execute than anthrax releases; locations having high symbolic or economic importance are much more likely to be targeted.
  • The relative likelihood of multiple attacks making up a single event. For example, a hallmark of many terrorist operations is to attack two or more targets simultaneously. Attack multiplicity modeling is derived based on terrorist groups’ ability to coordinate multiple attacks for a particular weapon type.
  • Event frequency, which is empirically-driven and determined by modeling three input parameters: the number of attempted events in a year, the distribution of success rate of attempted events, and a suppression factor that is based on government response to an event.

The RMS terrorism model’s damage module has been validated against historical terrorism events. All known terrorist plots or attacks that have occurred since the model’s launch have been consistent with our underlying modeling principles. There are blue ocean opportunities for those willing to understand terrorism risk and underwrite it accordingly.

To read more, click here to download “Terrorism Insurance & Risk Management in 2015: Five Critical Questions.”

Managing the Changing Landscape of Terrorism Risk

RMS has released an updated version of its Probabilistic Terrorism Model, which reflects the considerable changes in terrorism risk for Canada, Denmark, Ireland, Italy, and the U.K. as well as the decreased frequency of large-scale-terrorism events for each of the five countries.

To inform the new view of risk, our scientists carried out a comprehensive analysis of global attack and plot data from the past decade. We focused heavily on large-scale attacks – those with the potential to threaten the solvency of an insurer.

The analysis showed that incidents of large-scale attacks have steadily and significantly decreased, which corresponds with a rise in the funding and sophistication of major intelligence agencies in the west.

Our approach to terrorism modeling follows three principles, which have been validated by data on intercepted plots, past successful attacks, and recent intelligence leaks:

  • Effective terrorists seek to achieve optimal results relative to their effort
  • Their actions are highly rational
  • They are highly constrained by pervasive counter-terrorism measures

Of the estimated 200,000 documents taken or leaked by Edward Snowden, one of the most relevant validations of the RMS model is an N.S.A. presentation that explains the routing of international telecommunications traffic. A very significant proportion of international telecommunications traffic is routed through the U.S. and Europe which, coupled with advances in big data analytics and plummeting data storage costs, has made intelligence collection easier and more robust than it has ever been.

 an N.S.A. PRISM presentation explains the routing of international telecommunications traffic

According to available data on the frequency of plots and attacks, the risk of a large-scale attack has been in decline since 2007, but the risk of smaller-scale attacks perpetrated by lone-wolf operatives and homegrown militants remains high.

However, we have learned over the past decade that terrorism risk levels are fluid and can change quickly. With the rise of the Islamic State in Iraq and reports of its successful recruitment of foreigners, as well as ongoing instability in Afghanistan and Pakistan, the risk outlook can change at any moment.

The RMS Probabilistic Terrorism Model incorporates multiple risk outlooks to provide users with the agility to quickly respond to any changes in terrorism risk. RMS is committed to updating its terrorism model as frequently as necessary to provide the most up-to-date, granular, and accurate view of global terrorism risk.