The Investigation of Impact of Extreme Weather Events on Property Insurance

DOI

10.2991/978-94-6463-540-9_26How to use a DOI?

Keywords

Extreme weather; Insurance; AHP-TOSIS; SARIMA; ArcGIS

Abstract

As the frequency of extreme weather in the world increases, so does the impact on the insurance industry, making the study of extreme weather on the sustainability of insurance properties particularly important. First, it collected some data on extreme weather occurrences from official databases in the United States and Africa. Subsequently, this study chose the SARIMA model to predict the losses and the number of insured people for the next seven years based on the characteristics of the data, and initially determined the baseline factors for the insurance program based on the break-even estimation model this study constructed. Second, this study analyzed the data to determine high-risk areas. Then evaluated the average damage to these high-risk areas from different weather extremes, identified that these extremes occurred most frequently in June. From the above conditions, this article used ArcGis to build a digital elevation model in Florida to select the recommended site areas. Third, in order to determine which buildings in the community should be protected in what way, this article constructed a key educational area scoring model (CGDAM-WRIR) based on the AHP-TOSIS evaluation model, which takes five metrics to derive a risk score and at the end calculates a building score in order to quantify the level of risk. Finally, this study went through a time trend analysis to examine when the different weather extremes occurred with the highest frequency and ranked the average damages of the different extremes to come up with a total event impact analysis.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yilin Lian
PY  - 2024
DA  - 2024/10/16
TI  - The Investigation of Impact of Extreme Weather Events on Property Insurance
BT  - Proceedings of the 2024 2nd International Conference on Image, Algorithms and Artificial Intelligence (ICIAAI 2024)
PB  - Atlantis Press
SP  - 237
EP  - 252
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-540-9_26
DO  - 10.2991/978-94-6463-540-9_26
ID  - Lian2024
ER  -