1 Weather covers Customized Contracts WMO meeting, Geneva, December 2007.

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Presentation transcript:

1 Weather covers Customized Contracts WMO meeting, Geneva, December 2007

2 Agriculture Hydro power Wind power Marketing Index Based Reinsurance TABLETABLE

3 Agriculture sector example: French vineyards exposure to frost and rainfall

4 Due to an excess rainfall and too cold temperature During the flowering Substantial part of production is lost Weather risk exposure : Solution : Double trigger : lack of heat & excess rainfall Payout is a linear function of both indices

5 Energy sector example: Hydropower’s weakness is drought Correlation between dam’s water level & electricity generation Dam’s water level depends on rainfall Weather risk : Solution : Put against insufficiency of cumulated rainfall Protection against decrease of index Index uses a basket of weighted weather stations when necessary

6 Energy sector example: Wind farm financing secured by wind guarantee Weather risk exposure : Solution : Wind Put : protection against insufficiency of wind Modelled production index which depends on wind speed: Wind Power Index Financial leverage to decrease the cost of capital Guaranteed minimum income is a security for creditors Sales are secured and prices are regulated (demand) Power generation depend on daily average wind speed Wind speed is THE key income factor

7 Insurance or energy example: Marketing Smoothing your Heating/Air conditioning bill Weather risk exposures : Solution : When summer is too hot (or the winter is too cold) end user electricity bill increases (Air conditioning/Heating demand) Monthly or seasonal digital protection against a high average daily max Temp. (ex €100 if Av. Temp > 30°C) Client pay off: credit on the next bill Guarantee paid by the client or free and provided by the distributor Development of customer loyalty and marketing differentiation

8 Reinsurance example: Wind trigger and intensity of damages (1/3) Weather risk exposure: Solution: Property and motor physical damages due to strong storms are strongly correlated to the wind speed Annual aggregate excess of loss property treaty 10 weather stations spread all over France Each station has a specific weight Each station has a specific wind speed threshold high enough to capture only strong storms (e.g. 120 Km/h) Each station has a specific wind speed limit high enough from the threshold (e.g. 160 km/h) as to capture storms severity

9 Reinsurance example: Wind trigger and intensity of damages (2/3) Daily index per station Wi1 = Min [(Max [(Wmax - Threshold) ; 0]) ; Lim] x weight Index Wi2 = sum of daily indices for all stations for the period Parameters of the cover are: Amount per index unit (tick) is EUR Deductible is EUR Limit is EUR i.e. 7.8 index units Applicable loss is the lesser of the index ; and the incurred losses

10 Reinsurance example: Wind trigger and intensity of damages (3/3)

11 Reinsurance example: Wind trigger and frequency of damages (1/3) Weather risk exposure: Solution: Property and motor physical damages due to strong storms are strongly correlated to the wind speed January-December SL treaty 45 weather stations spread over 5 European countries Each station has a specific weight Each station has a specific wind speed threshold high enough to capture storms (e.g. 110 Km/h) Each station has a specific wind speed limit close to the threshold (e.g. 115 km/h) as to capture storms frequency only

12 Reinsurance example: Wind trigger and frequency of damages (2/3) Daily index per station Wi1 = Min [(Max [(Wmax - Threshold) ; 0]) ; Lim] x weight Index Wi2 = sum of daily indices for all stations for the period in km/h Parameters of the cover are: Amount per index unit (tick) is EUR 24k Deductible is 300 km/h Limit is 300 km/h in excess of deductible i.e. EUR 7.4m

13 Reinsurance example: Wind trigger and frequency of damages (3/3)

14 Tel:+ (33) Fax:+ (33) Nicolas Chatelain Françoise Bollotte Salah Dhouib David Grégori Jean-Christophe Garaix A dedicated team at your entire disposal:

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