Title: Where the Home Insurance Meets the Climate Change: Making Sense of Climate Risk, Data Uncertainty, and Projections
Abstract: Insurance industry is one of the most vulnerable sectors to climate change. Assessment of the future number of claims and incurred losses is critical for disaster preparedness and risk management. In this project, we study the effect of precipitation on joint dynamics of weather-induced home insurance claims and losses. We discuss new statistical and machine learning approaches to forecasting future climate-induced claim dynamics, while accounting for nonlinear multivariate dependence structure and quantifying for the associated modeling and data input uncertainties. We illustrate our methodology by application to attribution analysis and forecasting of weather-induced home insurance claims in Canada and Norway. This is a joint work with Slava Lyubchich, UMCES, Asim Dey, UT Dallas, and Hali Kilbourne, UMCES.
Biography
Yulia R. Gel is Professor in the Department of Mathematical Science at the University of Texas at Dallas. Her research interests include statistical foundation of data science, inference for random graphs and complex networks, time series analysis, and predictive analytics. She holds Ph.D in Mathematics, followed by a postdoctoral position in Statistics at the University of Washington. Prior to joining UT Dallas, she was a faculty member at the University of Waterloo, Canada. She also held visiting positions at Johns Hopkins University, University of California, Berkeley, and the Isaac Newton Institute for Mathematical Sciences, Cambridge University, UK. She is a Fellow of the American Statistical Association.
