1. Flood exposure in Africa
Source: Sigma SwissRe

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

3. 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

4. Loss trends and effects of climate change

5. Insured natural catastrophe losses have been increasing
Insured losses
Dark blue: EQ / Tsunami (2011 Japan, NZ), light blue: Weather-related catastrophes (Windstorm, Hurricane, Flood) (e.g 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

6. 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

7. 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

8. 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

9. 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

10. …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

11. …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

12. Natural catastrophes: How does Eastern and Southern Africa compare?

13. 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)

14. 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)

15. 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)

16. Mind the risk A global ranking of cities under threat from natural disasters

17. 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

18. Source: Dartmouth Flood Observatory, 201518

19. Flood Insurance: Challenges and solutions

20. Key flood insurance challenge

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

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

23. 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

24. 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

25. Flood - an underestimated risk Inspect, inform, insure

26. CatNet: Swiss Re tool for worldwide natural peril assessement

27. 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

28. 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

29. Swiss Re Global Flood Zones
Dar es Salaam, Tanzania

30. 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

31. For more details go to our website or contact
your Swiss Re underwriter

32. Conclusions

33. Title : Black Gill Sans MT Font Subtitle
Flood insurance is a hot topic!
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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.

34. Questions? 34

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