"Terrorism Modeling & Risk Management" - Presented at the RAA's Cat Modeling Conference 2014

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RMS spoke at the RAA's catastrophe modeling conference in Orlando recently, discussing terrorism risk and how the corresponding modeling solutions have evolved since 9/11.

RMS spoke at the RAA's catastrophe modeling conference in Orlando recently, discussing terrorism risk and how the corresponding modeling solutions have evolved since 9/11.

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  • 1. TERRORISM MODELING AND RISK MANAGEMENT Chris Folkman Director, Model Product Management February 11, 2014
  • 2. OUTLINE •  Terrorism Modeling Overview •  Event frequency in probabilistic terrorism modeling •  Modeling Framework §  §  §  §  Exposure Hazard Vulnerability Probabilistic Framework •  TRIA implications in terrorism risk management
  • 3. TERRORISM MODEL BACKGROUND •  September 11th, 2001 attacks: $40 billion insured loss. WTC attack footprint: 16 acres. •  Models created in 2002-2003 in response to market demand for terrorism solutions. •  Terrorism modeling data has improved over the past decade. Ø  Ø  Ø  Ø  More data on plot frequency More data on attack suppression / success rates More insight into countersecurity Better calibration of hazard and vulnerability
  • 4. TERRORISM RISK MANAGEMENT – A “THREE PRONGED” APPROACH EXPOSURE MANAGEMENT SCENARIO LOSS MODELING PROBABILISTIC LOSS MODELING §  Monitor exposure concentrations around high risk targets. §  Quantify loss for one attack scenario. §  Identify most critical attack scenarios for a portfolio §  Manage losses of benchmark scenarios to acceptable levels. §  Determine relative likelihood of attack scenarios §  Submitted to rating agencies (i.e. Best SRQ). §  Calculate impact of multiple attacks as part of a single event (multiplicity). §  Identify building level accumulations. §  Identify exposure “Hot Spots” within given radius.
  • 5. PROBABILISTIC MODELING OF TERRORISM Probabilistic terrorism modeling delivers deep insight into key drivers of loss on a portfolio Ø  Analysis of comprehensive event catalog (90,000+ attacks). Ø  Key losses by account, location, target type, city, and line of business Ø  Assist underwriters in risk selection Ø  Design and implement underwriting guidelines Ø  Capacity allocation Ø  Evaluate reinsurance needs and options
  • 6. TERRORISM FREQUENCY: COMMON MISPERCEPTIONS “There’s not enough data to create meaningful rates” •  RMS rates are based on empirical data, not judgment. •  RMS frequency is calibrated against hundreds of plots from open source intelligence - known, intercepted, and/or resulting in court convictions – to set the baseline threat level for each country. •  Event rates are scaled with data based on: •  Attack mode •  Target category •  City •  As the threat landscape changes, so does frequency.
  • 7. TERRORISM FREQUENCY: COMMON MISPERCEPTIONS “You can’t model human behavior” •  RMS does not model human behavior. •  Terrorism modeled as a control process: terrorists’ actions are constrained by countersecurity measures. •  Terrorists are rational actors. Targeting strategy is based on maximizing “attack leverage”. •  Suppression and interdiction rates based on data from open source intelligence, court convictions, DHS disbursements. •  Range of outcomes from conventional terrorism is narrow: Ø  Multiple successive terrorist events: not plausible due to suppressive law enforcement action following the first event. Ø  Multiple hurricanes making landfall (i.e. 2004, Florida): plausible.
  • 8. PROBABILISTIC TERRORISM MODELING All carriers writing terrorism cover are making assumptions about frequency. •  These assumptions should be informed by data, not guesswork. •  RMS model incorporates dozens of data sources in frequency calibration: Terrorism Plots ü  Terrorism court convictions ü  Intercepted plots ü  Open source intelligence Strength of ü  DHS disbursements Countersecurity ü  Municipal anti-terror resources Environment ü  ü  Target Selection ü  ü  Gross municipal product of city City name recognition in middle east Symbolic value of target Building level security perimeters
  • 9. FRAMEWORK FOR TERRORISM MODELING EXPOSURE AT RISK QUANTIFY HAZARD ASSESS VULNERABILITY PROBABILISTIC ANALYSIS
  • 10. IMPORTANCE OF ADDRESS RESOLUTION ZIP Code Centroid 10017 Exposure at Risk Assess Vulnerability Probabilistic Analysis Concentrated nature of terrorism risk demands accurate and high resolution exposure data •  •  •  •  •  United Nations Quantify Hazard All addresses geocoded to lat-long before modeling Post code centroid is insufficient Large variations of risk exist within a single post code Hazard and vulnerability not averaged across a larger area Data quality is paramount
  • 11. ATTACK MODES MODELED Exposure at Risk Quantify Hazard Assess Vulnerability Probabilistic Analysis 600 lb Car Bomb 1 ton Minivan Bomb Sabotage Attacks 2 ton Box Van Bomb Chemical Agent Attack 5 ton Truck Bomb Biological Agent Attack 10 ton Trailer Bomb Radiological Attack Tanker Conflagration Attack Nuclear Weapon Aircraft Impact Attack Various wind speeds, isotopes, and indoor/outdoor options apply
  • 12. HAZARD BY ATTACK TYPE Exposure at Risk Quantify Hazard Assess Vulnerability ATTACK MODES HAZARD DESCRIPTION Conventional Bomb Attacks Blast pressure (PSI) Hazardous Transportation Sabotage, Industrial Sabotage - Toxic Release Particulate contamination Aircraft Impact Distance from target Biological / Chemical Attack (Outdoor) Dosage / deposition of contaminant Conflagration Fire ignitions Dirty Bomb, Nuclear Plant Sabotage Radiation level Probabilistic Analysis
  • 13. SIMPLE DAMAGE FOOTPRINT Exposure at Risk Quantify Hazard Assess Vulnerability Bomb blast in downtown Manhattan NY Accumulation Centroid Hazard rings represent blast pressure dissipating as it moves away from the centroid Exposure Highest 0 125 250 500 Meters Lowest Accum. Center Probabilistic Analysis
  • 14. HIGH RESOLUTION FOOTPRINT Exposure at Risk Quantify Hazard Assess Vulnerability Probabilistic Analysis Large Anthrax release in downtown Chicago Better reflects local environment and orientation of footprint Anthrax Contamination Downtown Chicago Highest Lowest 0 2.5 5 10 15 20 Miles
  • 15. VULNERABILITY OF TERRORIST ATTACKS Exposure at Risk Quantify Hazard Assess Vulnerability Probabilistic Analysis Represent the relationship between level of hazard and damage §  Effects on property, disruption of services, injury, and loss of life §  Expressed as mean damage ratio (MDR) or mean casualty rate (MCR) §  Vulnerability functions by building construction and height.
  • 16. MEAN DAMAGE RATIO BY DISTANCE TO TARGET Quantify Hazard Assess Vulnerability Probabilistic Analysis 2  Ton  Bomb  Scenario   Unknown  Construc3on  /  Height   Mean  Damage  Ra*o  (%)   Vulnerability varies by building characteristics. Exposure at Risk Reinforced  Masonry  -­‐  High  (8-­‐14)   Steel  Structure  -­‐  V  Tall   Unknown  Construc3on  -­‐  Tall   75   100   150   250   Distance  to  A4ack  Centroid  (meters)   400  
  • 17. FIRE LOSSES Exposure at Risk Quantify Hazard Assess Vulnerability Probabilistic Analysis Standard Fire Policy (SFP): In U.S., many states require that fire following terrorism be included in property coverage. Explicit quantification of fire-related damages is critical for selected attack modes: Mitsubishi Steel and Armament Works ~ 700 meters from hypocenter, Nagasaki From: www.hiroshima-remembered.com §  §  §  §  §  Bombs Aircraft Impact Conflagration Industrial Sabotage Nuclear
  • 18. TERRORIST TARGET DEVELOPMENT Exposure at Risk Quantify Hazard Assess Vulnerability Probabilistic Analysis Terrorist target selection based on maximizing attack leverage. Criteria for targets based on: §  §  §  Economic Impact Symbolic Value / Publicity Value Casualties §  §  §  §  Debriefings of Operatives Historical Attack Patterns Known Planned Attacks Intelligence Reports and Expert Opinions
  • 19. COMPONENTS OF TERRORISM RATES Exposure at Risk Quantify Hazard Assess Vulnerability Probabilistic Analysis •  Attack Frequency Ø  Country Specific Ø  Plots à Attacks Ø  Recalibrated frequently •  Conditional Probability. Given that an attack occurs, what is its likelihood by: Ø  Type of attack Ø  Type of target Ø  City •  Attack Multiplicity Ø  Multiple attacks = One Event
  • 20. From the Congressional Research Service, April 2013: TRIA STRUCTURE
  • 21. TRIA RENEWAL EFFORTS Political Challenges Key Support Non-renewal impacts •  House financial committee has 46% new membership since last TRIA renewal. •  Aversion to perceived “bail out” legislation persists. •  TRIA backstop provided without charge, premium collected without incident. •  Strong, united lobby from banking, insurance, and construction industries to promote TRIA renewal. •  Renewal proposed 3 times in congress in 2013, by members of both parties. •  Moody’s downgrades in 2002. •  Sunset clauses in 2005: delayed / halted lending and construction. •  Capacity shortage, large rate increases. •  RMS top five cities for terrorism risk: New York, Washington, Chicago, San Francisco, Los Angeles.
  • 22. TRIA CONSIDERATIONS Propor*on  of  Average  Annual  Terrorism  Loss     by  Metropolitan  area   Los  Angeles   San  Francisco   The terrorism threat gradient is steep: 75% of AAL is in five metro areas. Washington     DC   Rest  of  U.S.   Chicago   New  York  
  • 23. RMS U.S. Industry Loss Curves by Peril TRIA CONSIDERATIONS 600,000   500,000   400,000   $ Millions Terrorism risk is comparable with nat cat risk. 250 Year 1,000 Year 300,000   5,000 Year 200,000   100,000   0   Winterstorm Terrorism Earthquake + Fire Hurricane Convective Storm
  • 24. TRIA CONSIDERATIONS Event  Descrip*on   Nuclear  Detona*on,     5  kiloton  yield,  Chicago   Nuclear  Detona*on  ,   1  kiloton  yield,  Los  Angeles   Anthrax  a4ack,  75  kg  anthrax   slurry,  Philadephia   Nuclear  Power  Plant  Sabotage,   Illinois   Dirty  Bomb,  15,000  curies   cesium-­‐137,  New  York   Anthrax  a4ack,  1  kg  anthrax   slurry,  Philadephia   Sarin  Gas  A4ack,  1,000  kg   release,  New  York   NBCR severity makes it difficult to insure   Total  Loss   ($Billions)   Property  Damage   Loss  ($Billions)   Workers'  Comp   Loss  ($Billions)   Fatali*es   $530   $323   $207   300,000   $230   $163   $67   110,000   $216   $125   $91   60,000   $148   $146   $2   Few   $127   $127   $0.1   Few   $44   $26   $18   10,000   $17   $12   $5   2,000  
  • 25. TRIA RENEWAL: WHAT’S AT STAKE •  Market Capacity Ø  Evan Greenberg, CEO ACE Ltd: “I wouldn’t make [terrorism cover] available, nor would any other company that I know of.” •  Workers’ Compensation Ø  Terrorism cannot be excluded Ø  Residual markets can be >50% more expensive than private carriers •  Commercial Development Ø  Loan Covenants require terrorism cover Ø  Moody’s: $4.5 billion in mortgage securities downgraded (2002) due to lack of terrorism insurance.
  • 26. •  All terrorism writers make assumptions on event frequency. •  Assumptions should be based on data. •  Probabilistic terrorism modeling allows most comprehensive view of risk. •  Terrorists are rational actors whose targeting selections align with principals maximizing “attack leverage” •  Best practice: Use multiple approaches to best triangulate terrorism risk •  Exposure management •  Deterministic scenarios •  Probabilistic modeling •  Location-level data quality is important due to small event footprints •  Terrorism risk is comparable with nat cat risk. •  Terrorism risk can be successfully modeled. Insuring it remains difficult. TAKE AWAYS