Multivariate Modeling of Precipitation-Induced Home Insurance Risks Using Data Depth

While political debates on climate change become increasingly heated, our houses and city infrastructure continue to suffer from an increasing trend of damages due to adverse atmospheric events, from heavier-than-usual rainfalls to heat waves, droughts, and floods. Adapting our homes and critical in...

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Bibliographic Details
Published in:Journal of agricultural, biological, and environmental statistics biological, and environmental statistics, 2024-03, Vol.29 (1), p.36-55
Main Authors: Dey, Asim K., Lyubchich, Vyacheslav, Gel, Yulia R.
Format: Article
Language:English
Subjects:
Agriculture
Biostatistics
Climate change
Climate effects
Climate models
Critical infrastructure
Drought
Environmental risk
Health Sciences
Heat waves
Homeowners insurance
Infrastructure
Insurance
Machine learning
Mathematics and Statistics
Medicine
Monitoring/Environmental Analysis
Prairies
Rainfall
Risk analysis
Risk reduction
Statistics
Statistics for Life Sciences
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Summary:While political debates on climate change become increasingly heated, our houses and city infrastructure continue to suffer from an increasing trend of damages due to adverse atmospheric events, from heavier-than-usual rainfalls to heat waves, droughts, and floods. Adapting our homes and critical infrastructure to sustain the effects of climate dynamics requires novel data-driven interdisciplinary approaches for efficient risk mitigation. We develop a new systematic framework based on the machinery of statistical and machine learning tools to evaluate water-related home insurance risks and quantify uncertainty due to varying climate model projections. Furthermore, we introduce the concept of data depth to the analysis of weather and climate ensembles, which remains a novel territory for statistical depth methodology as well as the field of environmental risk and ensemble forecasting in general. We illustrate the new data-driven methodology for risk analysis in application to rainfall-related home insurance in the Canadian Prairies over 2002–2011. Supplementary materials accompanying this paper appear online.
ISSN:1085-7117
1537-2693
DOI:10.1007/s13253-023-00554-1