Business Cycles and the Impact oF Natural Hazard Events

1. Business Cycles and the Impact oF Natural Hazard Events A Parochial Reinsurance Market View David Simmons: Managing Director Analytics, Willis Re Imperial College: 26th March 2013

2. Catastrophe Reinsurance PricingThe “Traditional” Model • Catastrophes are, by their nature, rare events • Before the “modelled age” pricing was based upon recent loss history and required return • Pricing at near return period dictated by recent history (burning cost) • Pricing at far return periods set by minimum return requirements (minimum rate on line) • Concept of “the bank” and “payback” prevailed • When loss occurred reinsured was in effect calling in their “bank” of premiums paid in clean years • If bank insufficient then rates in future years increased so that reinsurer was paid back over a fixed time period • But these arrangements were non-contractual, market practice only • Result was that catastrophe reinsurance pricing was very reactive • When losses occurred prices increased steeply • In period of no losses prices tended to drift down due to market pressure • Exacerbated by tendency for some reinsurers to exit post-loss and new entrants emerge when rates are high

3. Catastrophe Reinsurance Pricing1990s UK Catastrophe Example • Catastrophe Market in 1990 was already stressed • Large “1 in 100” windstorm loss in 1987 - 87J – USD 3.1m (original values per Munich Re) • Other market losses: Piper Alpha and Hurricane Gilbert (1988), Hurricane Hugo Exxon Valdez tanker (1989) tested catastrophe and specifically the Lloyd’s market • Storm 90A or Daria in January caused insurance losses event greater than 87J – USD 5.1m • Followed by a series of other smaller storms including Vivian in February costing USD 2.1m • In 1991 UK catastrophe prices reinsurance prices spiked in reaction to these losses • Prices more than tripling on average (source Willis Re) • Prices continued to increase in 1992 (impact of Hurricane Andrew) and 1993 as the LMX spiral, partially caused/revealed by this sequence of losses reduced ability of reinsurers to protect themselves so further reducing capacity • Prices peaked in 1994 with UK catastrophe reinsurance rates over 5 times 1990 levels

4. The New Modelled World • 1991/2 saw the first UK windstorm models • Concepts outlined by Don Friedman in 1984, put into practice by Karen Clark in the late 80s for US Hurricane • Prevailing view was that new modelling would damp reinsurance pricing movements • Pricing now technical rather than reactive • New market entrants in Bermuda aggressively predicated their offering on this new technical approach • Beginning of breakdown of old bank/payback model, Insureds were tempted by lower prices of new technical reinsurers, breaking gentlemen’s payback agreements • Threat of Capital Markets entry to market was widely believed to further constrain pricing • New Bermuda capital could leave as fast as it arrived, triggering price increases? • But capital market players, with “infinite capital” attracted to new zero beta class would stay/pile in post loss? • Prices declines steadily from 1994 to 2000 as confidence In the modelling increased and memory of 1990 weakened, helped by a benign period for European Storms and the catastrophe market

5. But shocks still have an impact • 9/11 in 2001 provided an unexpected shock to the system • Not a UK loss, not a natural catastrophe, but a major threat to the health of reinsurers • Market Loss circa USD 32m, over 50% higher than the highest natural catastrophe, Hurricane Andrew • P&C insurers suffered real losses to their capital (chart below source Insurance Information Institute) • Price impacts were felt throughout the market, UK prices jumped despite there being no underlying change to the assessed UK catastrophe risk and no actual UK catastrophe losses • The reactive kick-up in pricing was not limited to the UK – all markets showed a similar picture • Although not a model failure, the multi-class nature of loss caused reinsurers to question their base assumptions

6. Post 9/11A series of disappointments • The catastrophe market has proven to be very resilient in the current millennium despite a series of major events, each revealing a flaw in underlying modelling assumptions • Hurricane Katrina: Levee burst/flood not modelled • Hurricanes Katrina/Rita/Wilma: Hurricane clustering • Sichuan Earthquake: Missed fault • Japanese Earthquake: Tsunami not modelled, intensity of earthquake on fault • New Zealand Earthquake: Liquifaction impacts, intensity of earthquake on fault, aftershocks • Australian Flood: Unmodelled, scale/intensity, classification (riverine vs flash flood) • Thai Flood: Unmodelled, contingent business interruption claims, scale • But the re/insurance industry remained resilient to all of these despite modelling flaws • Why? Despite problems with catastrophe models, their introduction has lead to as greater appreciation of risk, portfolio development, aggregate control and data quality • Capital market involvement in reinsurance is growing BUT not reason for stability • Capital markets took fright after “model error” of Katrina, retreated from indemnity deals to parametric trigger • Now back, largely driven by seeking any asset with a return with low correlation to market risk • Ironically, it was market risk that caused the biggest impact on re/insurers, the 2008/2009 asset crash, but no significant long-term casualties (other than AIG)

7. Pricing trends from 4 major markets

8. Current ResearchImpact on Economy of Cat Events • What impact does a major catastrophe have on the economy of a country? • Recent losses have given us some evidence to chew on • Consider the Kobe (Great Hanshin) Earthquake of 17th January 1995 • Kobe Earthquake • 6,500 dead • Economic Loss circa USD 100bn (Insurance Losses though of order of only USD 3bn) • By end 1996 • manufacturing back to 98% of pre-earthquake trend • All department stores and 795 of city stores reopened • Import trade through port fully recovered • Export trade through port recovered to 85% below 1994 level • Both the Nikkei 225 and the USD/JPY rate broadly recovered to pre-earthquake levels after 9 months • Only significant broader financial impact was collapse of Baring’s Bank due to Nick Leason’s fraudulent dealings around movements in the Nikkea index • What impact does an extreme catastrophe have on the global economy? • Consider the San Francisco Earthquake of 1907 and potential of a Beijing Earthquake

9. San Francisco Eathquake 1906 impacts • Consider Paper by Odell and Weidenmeier “ Real Shock, Monetary Aftershock@ the 1906 San Francisco Earthquake and the Panic of 1907”, published in 2004 • Causal chain proposed as follows: • Earthquake strikes San Francisco. • Claims are paid in gold by English insurers. • Gold flows into the US, thus increasing liquidity in the country. • Bank of England reacts to gold outflow by raising interest rates (and also taking other monetary restriction measures, such as ban on discounting US bills). • Gold flows from New York back to London. • Liquidity squeeze results in New York, causing stock market crash and drop in industrial activity. • Short term interest rates rise in the US, thus offsetting Bank of England’s action. • The world today is very different: • Thankfully claimants don’t demand to be paid in gold • Arguably, financial instruments are more liquid (if not under stress) • But could a similar chain occur today? • My colleague at Willis Re, Giorgio Brida, has proposed a potential 21st Century equivalent, a Beijing Earthquake

10. Updated Odell-Weidenmeier modelBeijing Earthquake • Assume a major Beijing Earthquake at a point in the near future (one where insurance penetration rates in China begin to approach those of the West) • A very big earthquake strikes in Beijing • Foreign reinsurers are required to cover a significant amount of claims • Foreign reinsurers have to sell a significant amount of foreign assets, since they could not cover their Chinese risks with Chinese investments • Let us suppose that reinsurers sell T-bonds. Treasury yield spike in the US • The Fed cannot “sterilize” the sell-off because it does not have enough room for manoeuvre, due to the huge expansion in its balance sheet following the continuing financial crisis • Recession in the US, possibly aggravated by liquidity squeeze on shadow banking system. … could be offset by monetary inflows from other countries … but then US dollar appreciates, thus hampering US firms international competitiveness … • A related scenario have also been discussed for a large Tokyo earthquake • It envisages a large repatriation of Japanese funds from overseas investments in additional to a call on foreign reinsurers • The Kobe incident was large but well within the margins of Japan’s GDP (loss estimated at 2% to 2.5% of GDP) • But a repeat of the 1923 Great Kanto Earthquake in the Tokyo bay area could have a global impact

11. Lessons learnt • Reinsurers are pretty resilient • Very few recent failures • Catastrophe modelling has improved risk understanding but has not performed well when tested • Greater awareness now of unmodelled risks and perils • Focus on policy wordings (eg to avoid contigent BI issue for Thai Flood) and exposure control • Financial shocks can hurt as much as insurance ones • But insurers now largely de-risked • Implies lower investment returns to act as buffer to insurance cycles/catastrophe impacts? • Potential systemic risk from model use? • Regulators (eg Solvency II) are avoiding endorsing a model or models (like Florida) rather encouraging companies to take their own view of risk • BUT in practice difficult to be the one different from the others • “Don’t get sacked for buying IBM” = “Don’t get sacked for using RMS?” • Need contrarians to ensure robustness? • Be wary of surprises • Many Japanese insurers suffered more form the Thai Floods than the Japanese Earthquake/Tsunami • It’s the unknown unknowns that hurt every time

12. Business Cycles and the Impact oFNatural Hazard Events A Parochial Reinsurance Market View David Simmons: Managing Director Analytics, Willis Re david.c.simmons@willis.com