Factbox-German floods could prove expensive for insurers - KFGO News

MUNICH (Reuters) – Devastating floods in Germany last week could become one of the most expensive natural catastrophes in the country in the past 20 years, past industry data shows.

German insurance industry association GDV said on Wednesday that insured losses from floods in the western German states of North Rhine-Westphalia and Rhineland-Palatinate may total 4 billion to 5 billion euros ($4.7-5.9 billion).

Its estimate does not include losses from floods in the southern German state of Bavaria and in Saxony in the east last weekend, it said, adding that the destruction of local infrastructure had made it difficult to assess the damage.

Here is a rundown of the most expensive natural catastrophes in Germany since 2002 (insured damage in property and casualty hailstorm hilal as well as auto insurance):

Event Date insured damage*

August floods, August 2002 4.5 bln euros

including at the

Oder river

Storm Kyrill January 2007 3.4 bln euros

Hailstorms Andreas July 2013 3.1 bln euros

and Bernd

June floods, June 2013 2.1 bln euros

including in Bavaria

and Saxony

Hailstorms, June 2021 1.7 bln euros**

particularly in

southern Germany

Storm Jeanett October 2002 1.4 bln euros

Hailstorm Hilal May 2008 1.3 bln euros

Storm Friederike January 2018 1.15 bln euros

* in 2019 prices

** according to preliminary estimates

And here is a rundown of the most expensive natural catastrophe years since 1973 (insured damage in property and casualty as well as auto insurance):

Year Damage* Major natcat events

1990 11.1 bln euros Storms Vivian and

Wiebke

2002 10.9 bln euros Floods at the Oder

river

2013 9.3 bln euros Hail, June floods

1984 8.0 bln euros Hail in Munich

1976 6.5 bln euros Storm surge at the

North Sea and the

Elbe river

2007 6.2 bln euros Storm Kyrill

* in 2019 prices

Source: German insurance industry association GDV

(Reporting by Alexander Hübner; Writing by Maria Sheahan; editing by Philippa Fletcher and Timothy Heritage)

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