Managing Flood Risk in a changing Climate Dr. Jens Mehlhorn Head of Flood

2 Agenda Introduction Thailand Flood 2011 Pakistan Flood 2010 Flood Insurance Solutions Swiss Re Global Flood Zones TM Summary

Introduction 3

4 Think tank "Cat Perils" In-house models as key source for accurate Uwing at reasonable cost Taylor-made, state-of-the-art models to allow efficient Uwing process, incl. hot line No black box approach, benchmark RMS RiskLink Option to react swiftly on new findings e.g. EQ Chile & BI Team of experts to develop custom made solutions and train Uwers Value proposition and client centric approach as key drivers Structure and rate complex cases due to available R&D data set e.g. ILS Educated Uwers to go beyond simple tool usage, strong link to Universities Valuable client services, value proposition and branding Own R&D and natcat risk awareness brings added value to clients and builds SR reputation Client tools at minor additional cost e.g. CatNet TopTopic NatCat activities due to sound expertise Integrated & transparent risk management All relevant lines of business included, automatic process Successful portfolio steering thanks to transparent figures and sound hazard assessment No big surprises as long as "mother nature behaves"

River Flood affected regions source: Dartmouth Flood Observatory

6 Flood losses are on the rise! insured loss in m USD at 2011 price Source: Swiss Re Sigma Database

Increasing values Growing population and economic activity lead to increasing values Increasing vulnerability of insured values Exposed Areas Settlement s in high risk areas such as flood plains and coastal areas Increasing value concentration in flood prone areas Increased Insurance Penetration Increasing wealth of population leads to more people buying insurance Climate Change Hazard cycles and trends natural & man-made climate change 7 Reasons for increasing flood losses

Thailand Flood

61 out of 77 provinces affected 30,000 km 2 had been inundated Millions of people were affected and more than 800 people have died Insured loss of 12 billion USD Economic loss of 30 billion USD Largest insured fresh water flood loss in global history 9 Facts & Figures

DateCountry Insured loss, USD m, at 2011 prices Insured loss, as a % of country’s property premiums Insured loss, as a % of country’s non-life premiums Insured loss, as % of GDP Total Loss, as % of GDP July–Nov 2011Thailand %203.5%3.40%8.60% Aug 2002 Germany & Czech Republic %3.00%0.10%0.50% Jun 2007United Kingdom %2.20%0.10% Aug 2005Switzerland %11.70%0.60%0.90% Jan 2011Australia %5.90%0.20%0.40% Jul–Aug 1997 Poland & Czech Republic %42.3%0.80%2.30% Jul 2007United Kingdom2 1589%1.70%0.10% Dec 2010Australia %5.90%0.20%0.40% Apr 1973United States1 8735%0.60%0.03%0.10% Jun–Aug 1973United States1 6003%0.30%0.02%0.20% 10 Facts & Figures continued Sources: Swiss Re Economic Research databases, Oxford economics