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\begin{document}

\title{A Data-intensive Approach to Allocating Owner vs. NFIP portion of
Average Annual Flood Losses}



\author[1]{Md Adilur Rahim}%
\author[1]{Carol Freidland}%
\author[1]{Robert Rohli}%
\author[1]{Nazla Bushra}%
\author[1]{Rubayet Bin Mostafiz}%
\affil[1]{Louisiana State University}%


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  \date{June 14, 2024}


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\begin{abstract}
Accurate loss assessment plays a vital role in understanding the
economic risk of natural hazards, for planning, mitigation, and
actuarial purposes. Because of its juggernaut status as the most
widespread and costly hazard, both nationally and around the world, loss
assessment due to flood is particularly important. One of the
shortcomings in existing flood loss models is to partition the structure
(or building) economic value of loss into that borne by the homeowner
and that covered by flood insurance. The goal of this research is to
model the loss incurred by the homeowner and that incurred by the
National Flood Insurance Program, considering flood damage, building
replacement value, flood insurance coverage amount, deductible, and
flood characteristics (slope and y-intercept of the loss vs. return
period curve). A Monte Carlo approach is used to calculate the annual
average loss due to flood at the individual homeowner scale. Multiple
linear regression (MLR) and Classification and Regression Tree (CART)
models are trained to provide the output of the owner's share of the
loss. The CART model outperformed the MLR model with lower RMSE and MSE
values and a higher R\selectlanguage{ngerman}² value (0.95) on the test data set. Because
out-of-pocket expenses due to flood can be devastating to financial
security, the results of this study support and inform the proactive
decision-making process that homeowners can use to self-assess their
degree of preparation and vulnerability to the flood hazard.%
\end{abstract}\selectlanguage{ngerman}%



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