1. Conceptualizing Tail Risk: A Reinsurers Perspective Gabor
Jaimes - GAJA Consulting Aresty Instiute of Executive Education The
Wharton School of the University of Pennsylvania RMA/Wharton
Advanced Risk Management Program 2015 Philadelphia, 15 July
2015
2. Outline The reinsurance business model Assessing and
managing tail risk Group discussion
3. The Reinsurance Industry 300+ reinsurers worldwide Domiciles
concentrated in London, Zurich, Bermuda, Germany, Singapore Munich
Re, Swiss Re, Hannover Re, SCOR, Lloyds of London, Partner Re,
General Re/BH, XL- Catlin Re, China Re, Korean Re, GIC Re,
Reinsurance Group of America, Transatlantic Re, Everest Re,
Renaissance Re, Platinum Re, White Mountain Re, Aspen Re, Peak Re,
Top Layer Re, Samsung Re,
4. The reinsurance business model Absorb tail risk from
insurance companies Assess tail risk adequately Manage exposures
thoroughly Identify new/emerging risks early Diversify across
regions, products, risk types Minimize none-core business related
risks
5. The reinsurance business model Hurricane Katrina (2005)
6. Japan Earthquake (2011) Superstorm Sandy (2012) 9-11 (2001)
The reinsurance business model
7. Christchurch Earthquakes (2010-2011) Thailand Flood (2011)
Deep Water Horizon (2010) Indian Ocean Earthquake (2004) Northridge
Earthquake (1994) Hurricane Andrew (1992) Hurricane Ike (2008)
Alberta Floods (2013) The reinsurance business model
9. Event Year Insured Loss Victims Cyclone Bangladesh 1970 nil
300,000 Beijing Earthquake 1976 nil 255,000 Haiti Earthquake 2010
0.1 bn 225,600 Indonesia Earthquake 2004 2.5 bn 220,000 Cyclone
Nargis (Myanmar) 2008 nil 138,300 Cyclone Gorky (Bangladesh) 1991
nil 138,000 Sichuan Earthquake (China) 2008 0.4 bn 87,500 Pakistan
Earthquake 2005 nil 74,300 Peru Earthquake 1970 nil 66,000 Russia
Heat Wave 2010 nil 55,600 Iran Earthquake 1990 0.2 bn 40,000
Central Europe Heat Wave 2003 1.6 bn 35,000 Deadliest Cat Events
Source: Swiss Re Sigma 2015
10. Outline The reinsurance business model Assessing and
managing tail risk Group discussion
11. 1 From historical events to a probabilistic event set
Hurricane Katrinas historical track and the probabilistic events as
generated in the model Source Swiss Res Cat Perils (Dr Marc
Wueest)
12. 1 Northern Atlantic JunNov (~11 storms/year)Eastern Pacific
May Nov (~16 storms/year) Northwestern Pacific All year-round (~27
storms/year) North Indian Ocean Apr-May & Oct-Nov (~5
storms/year) South-West Indian Ocean Nov-Apr (~21 storms/year)
Australia South-West Pacific Nov-Apr (~9 storms/year) From
historical events to a probabilistic event set globally
13. Murphys Law Photo: Beverly Hills Cop => Murphys Law
14. Near Misses
15. Emerging Risks
16. 1 High Prolonged power blackout Run-away inflation and
surging bond yields Big data Endocrine disrupting chemicals
Unforeseen consequences of electromagnetic fields Unforeseen
consequences of nanotechnology Medium Cyber attacks Supply chain
vulnerability Underestimated nat cat exposure Changing
communication patterns Toxic substances and workplace safety
Changing lifestyle Emerging infectious diseases Unresolved
sovereign debt crisis Underinvestment in critical infrastructure
Legal actions drive changing claims patterns Personal damage
compensation in Europe Regulatory fragmentation and extra-
territoriality concerns Contingent reputational risks Drug
resistance The future of medicine Global talent crunch New forms of
mobility Low Social unrest Do-it-yourself galore A risky harvest
The robots among us 1-3 years 4-10 years > 10 years Potential
impact Time frame Insights are grouped by insurance business area
based on expected impact: Property Casualty Life & Health
Financial Markets Claims Operations Emerging Risks Source: Swiss
Re
17. Integrated view of the risk to allow for proper modeling of
(tail) dependences
18. Assessing (and managing) tail risk 1. Analyze &
understand historical events 2. Generate plausible future events 3.
Consider Murphys Law 4. Consider near misses 5. Anticipate emerging
risks 6. Anticipate tail dependences 7. Use a risk measure that
considers the tail (Exp. Shortfall) 8. Hedging: retrocession, cat
bonds, cat swaps 9. Fully integrated risk aggregation & capital
allocation 10. Risk-adjusted Return on Capital by transaction
19. Using a risk measure that gives sufficient weight to tail
events Source: Swiss Re Annual Report 2014
20. Integrated view of the risk to allow for proper modeling of
(tail) dependences
21. Consistent use of a risk measure across all modeled risk
categories Source: Swiss Re Annual Report 2014 also for
hedging
22. Assessing and managing tail risk 1. Analyze &
understand historical events 2. Generate plausible future events
from the historical set 3. Consider Murphys Law 4. Consider near
misses 5. Anticipate emerging risks 6. Anticipate tail dependences
7. Consistent use of a risk measure that considers the tail 8.
Fully integrated risk aggregation & capital allocation 9.
Risk-adjusted return on capital by transaction 10. Hedging:
retrocession, cat bonds, cat swaps
23. Outline The reinsurance business model Assessing and
managing tail risk Group discussion
24. Thank You!! Gabor Jaimes - GAJA Consulting
[email protected] Aresty Instiute of Executive Education
The Wharton School of the University of Pennsylvania RMA/Wharton
Advanced Risk Management Program 2015