Flood exposure in Africa Source: Sigma SwissRe

Flood exposure in Africa From global to local challenges Caspar Honegger Head Flood, Swiss Re

Title : Black Gill Sans MT Font Subtitle Agenda Text Global loss trends and the impact of climate change Natural catastrophes - focus on eastern and southern Africa Flood insurance - challenges and solutions CatNet - global natural peril assessement tool

Loss trends and effects of climate change

Insured natural catastrophe losses have been increasing Insured losses 1970 - 2013 Dark blue: EQ / Tsunami (2011 Japan, NZ), light blue: Weather-related catastrophes (Windstorm, Hurricane, Flood) (e.g. 2005 Katrina / Rita / Wilma), yellow: man-made. red line: 10 year moving average. Several things: - man made claims relatively stable (exception of 2001) - NatCat losses fluctuate much more, highest losses come from large natural catastrophes - looking at the red line and the plot in general: natural catastrophe losses are increasing mostly property

Flood losses are on the rise Source: Sigma Database Insured flood losses increased by 12% per year (7% when adjusted for inflation) worldwide since 1970 Global GDP growth for that period was less than 4% per year

Reasons for increasing flood losses 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

Global mean temperatures will continue to rise by between 2°C and 4 Global mean temperatures will continue to rise by between 2°C and 4.5°C by 2100 "Warming of the climate system is unequivocal. Human influence on the climate system is clear. Since 1950 many of the observed changes are unprecedented over decades to millennia. - The atmosphere and ocean have warmed, - the amounts of snow and ice have diminished, - sea level has risen, - and the concentrations of greenhouse gases have increased strongly…"  A 2°C outcome would be desirable, but very unlikely to be achieved  Even if we stop all emissions today, climate is still going to alter Intergovernmental Panel on Climate Change (IPCC) THE international body for assessing the science related to climate change 259 authors, 800 experts and 195 governments join forces to assess the scientific basis of climate change. 8

What we know… We have a good idea of the energy budget of the Earth, i.e. incoming energy (mainly solar radiation), outgoing energy (radiation off the Earth’s surface and the atmosphere) and reservoirs (oceans, soil, atmosphere) Climate models can reproduce the average changes in the system that are induced by changes in the energy budget (global temperature, etc.) rather well. We know: If we turn up the heat, the water will start to boil. 9

…where the uncertainty lies… Climate models are less reliable when it comes to the distribution of energy within the climate system. we have more problems to project how regional climates will change and what will happen to extreme events. ? We do not know: Where exactly the bubbles will be at a certain time… ? ? ? ? 10

…specifically on extremes Extremes are very rare by definition. Therefore we need very long-term observations to detect significant changes in extremes. Thus, observed changes are only detected for more frequent “extremes” (like warm or cold days, heat waves, heavy precipitation) or when aggregated over the globe. In order to statistically detect changes in very extreme events, the change must be huge, and it will most probably be too late to react. e.g. Very likely increase in the length, frequency and/or intensity of warm spells or heat waves over most land areas; - Likely increase in the frequency of heavy precipitation events or an increase in proportion of total rainfall from heavy falls over many areas of the globe; Does not really help us to quantify impact of climate change on losses  Swiss Re is part of ECA working group. Source: Special Report on Extreme Events by the IPCC 11

Natural catastrophes: How does Eastern and Southern Africa compare?

Cities most at risk from river flood worldwide by number of people affected - RANKS: Pearl River 12 mn, Shanghai 11.7, Kolkata 10.5, Jakarta 10. Delhi 8.9, Tokyo 8.9, Bangkok 7.1, Mexico City 6.1, Cairo 5.5, Tianjin 5.5 - almost every city to some degree (historic)  built along waterways - Numbers per individual city are smaller, but - total number of people potentially affected: river flood is number one (379m) - focus Asia - Many cities are at risk from NatCat  another example for value concentration in exposed areas - Bangkok shows up (Nr. 7), Jakarta as well Source: Mind the Risk, Swiss Re publication 2013 Top 3: Pearl River Delta (12.0m), Shanghai (11.7m), Kolkata (10.5m) Top 3 Africa: Cairo (5.5m), Khartoum (2.5m), Kinshasa (1.8m) Top OEASI: Nairobi (0.6m)

Cities most at risk from cyclones worldwide by number of people affected Anatananarivo Madagscar Maputo, Mozambique - Storm: Pearl River Delta (17.2m), Tokyo-Yokohama (14.1m), Manila (12.6m) - Surge: Pearl River Delta (5.3m), Osaka-Kobe (3m), Mumbai (2.6m) - Most acute in East Asia, basin of the West Pacific. In Europe: Winter storms. lower windspeeds, but not only at the coast, but also further inlands. London is highest Non-Asian city (18th, 2.2m) Source: Mind the Risk, Swiss Re publication 2013 Top 3: Pearl River Delta (17.2m), Tokyo-Yokohama (14.1m), Manila (12.6m) Top 2 Africa: Antananarivo (0.1m), Maputo(0.1m) Top OEASI: Antananarivo, Maputo (0.1m)

Cities most at risk from earthquakes worldwide by number of people affected -EQ: Tokyo 29.4, Jakarta 17.7, Manila 16.8, Los Angeles 14.7, Osaka 14.6, Tehran 13.6, Nagoya 9.4, Lima 8.9, Taipei 8, Istanbul 6.4 -Tsunami: Tokyo 2.4, Nagoya 2.4, Osaka 1.8, Shantou 0.7, Kolkata 0.6, Dhaka 0.4 -"Ring of fire", north Anatolian fault, middle East (Kazakhstan etc) Source: Mind the Risk, Swiss Re publication 2013 Top 3: Tokyo (29.4m), Jakarta (17.7m) and Manila (16.8m) Top 3 Africa: Cairo (17.6m), Tunis (0.4m) and Algier (0.3m) Top OEASI: Kampala (0.05m)

Mind the risk A global ranking of cities under threat from natural disasters http://www.swissre.com/rethinking/climate_and_natural_disaster_risk/Mind_the_risk.html

Africa and OEASI: Economic losses and victims since 2000 Flood is the dominant natural hazard in the OEASI region More than a third of Africa's flood losses happened in the OEASI countries More than a half of Africa’s storm losses occurred in OEASI countries Africa OEASI Countries Source: Sigma SwissReg

Source: Dartmouth Flood Observatory, 2015 18

Flood Insurance: Challenges and solutions

Key flood insurance challenge

The majority of people live in low flood risk zones A small number lives in high risk zones

People most at risk are most likely to buy a flood product Which results in a adverse selected insurance portfolio

Solutions to adverse selection Optional flood products risk based pricing market penetration often limited Examples: Germany, China, Brazil Mandatory flood products mandatory element solves adverse selection needs government and/or industry support UK, Switzerland, France

Risk based pricing for flood Hazard levels, as shown by flood zones, are the key determinant for flood risk Additional risk factors are protection measures, vertical value distribution and occupancies

Flood - an underestimated risk Inspect, inform, insure http://media.swissre.com/documents/Flood.pdf

CatNet: Swiss Re tool for worldwide natural peril assessement

What is CatNet®? Swiss Re's online natural hazard information and mapping system Professional overview and assessment of natural hazard exposure worldwide Preparation of local, regional and cross-regional risk profiles seismic hazard update this weekend

CatNet datasets Swiss Re Global Flood Zones Official flood zones (e.g. USA, Germany) Global storm surge layer Seismic Risk (update in 2015) Earthquake Epicentres Tropical Cyclone Tracks Storm, Hail and Tornado risk Recent Events, Global alerts, weather and climate information Population sigma World Insurance & sigma loss information CRESTA and more…! seismic hazard update this weekend

Swiss Re Global Flood Zones Dar es Salaam, Tanzania

CatNet® benefits & functionality Import your location data to illustrate risk exposures combined with natural hazard data Risk profiles for your locations Footprints of major catastrophes Import of Excel and KML Editing and Export of data Risk look-ups Single Risk Assessment Dashboard

For more details go to our website or contact your Swiss Re underwriter www.swissre.com/catnet

Conclusions

Title : Black Gill Sans MT Font Subtitle Flood insurance is a hot topic! Text Flood is the dominant natural hazard in eastern and southern Africa Climate change will likely increase the frequency and severity of heavy precipitations events Flood is a growth opportunity for insurers and adds value to insureds, if necessary preconditions are met. The Swiss Re Global Flood Risk ZonesTM accessed via CatNet are widely used in the insurance industry and have helped to improve flood risk underwriting.

Questions? 34

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