Future insurance losses for pluvial flooding in Canada and the United States

Bourget, Mathilde; Boudreault, Mathieu; Carozza, David A.; Boudreault, Jérémie et Raymond, Sébastien (2023). Future insurance losses for pluvial flooding in Canada and the United States. Université du Québec à Montréal, Montréal, 30 p.

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Résumé

There is mounting pressure on the financial services industry to factor in climate extremes and climate change. As a result, new reporting and regulatory requirements are gradually being enforced on (re)insurers globally. One key requirement is physical risk assessment, that is, quantifying the financial impacts of climate change on the frequency and severity of claims due to weather events such as flooding. This is however a very challenging task for (re)insurers as it requires modelling at the scale of a portfolio and at a high enough spatial resolution to incorporate local climate change effects. In this paper, we introduce a data science approach to physical risk assessment of pluvial flooding for insurance portfolios over Canada and the United States. The underlying flood model is focused on quantifying the financial impacts of short-term (12-48 hours) precipitation dynamics over the present (2010-2030) and future climate (2040-2060) using a methodological approach that leverages statistical/machine learning and regional climate models. The flood model is designed for applications that do not require street-level precision as is often the case for scenario and trend analyses. It is performed at the full scale of Canada and the U.S. at 10 to 25 km resolution. Our models show that climate change and urbanization will typically increase losses over Canada and the U.S., while impacts are strongly heterogeneous from one state or province to another, or even within a territory. Portfolio applications highlight the importance for a (re)insurer to differentiate between future changes in hazard and exposure, as the latter may magnify or attenuate the impacts of climate change on losses. While the overall methodology can be applied to physical risk assessment of various risks, we also provide detailed maps and tables of the impacts of climate change on pluvial flooding for use by researchers and practitioners.

Type: Rapport de recherche
Mots-clés ou Sujets: flood insurance, pluvial flooding, climate change, physical risk assessment, machine/statistical learning, climate models
Unité d'appartenance: Centres institutionnels > Centre pour l'étude et la simulation du climat à l'échelle régionale (ESCER)
Déposé par: Mathieu Boudreault
Date de dépôt: 03 oct. 2023 08:04
Dernière modification: 03 oct. 2023 08:04
Adresse URL : http://archipel.uqam.ca/id/eprint/17031

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