Exploration of Property Insurance Benefits in Extreme Weather
DOI:
https://doi.org/10.54097/hmdpbk36Keywords:
Catastrophic Insurance, Risk Assessment Model, Rate-Adjusted Break-Even Analysis Model.Abstract
In recent years, the increasing frequency of extreme weather events has highlighted the insurance industry's dilemma - the profitability of insurance companies and the capacity of policyholders to bear the burden are in crisis. Therefore, seeking the development of property insurance in this environment is crucial. This paper establishes a Risk Assessment Model with a four-level index system, including four main indicators: natural, economic, social, and engineering defense, to assess the disaster risk and losses of a specific area. Subsequently, a Rate-Adjusted Break-Even Analysis Model is established and coupled with the Risk Assessment Model to facilitate practical insurance decision-making. By establishing this highly flexible and practical assessment system, precise indicators can be selected for evaluation based on the varying impacts of natural disasters in different regions. This will enable more accurate decision-making for local catastrophic insurance coverage. Consequently, it allows local residents to obtain better post-disaster relief protection against natural calamities, while businesses can also benefit from substantial reconstruction returns.
Downloads
References
[1] Fang Wenbin. How to Reinforce Catastrophe Insurance under the New Situation [J]. China Rural Finance, 2024 (7): 18-19.
[2] Wang He. Establishing a Catastrophe Insurance System in Line with China's Reality [J]. China Rural Finance, 2024 (7): 25.
[3] Ling Chaofan. Analysis and Exploration of the Current Situation and Development Strategies of Catastrophe Insurance in China [J]. Finance and Economics, 2019 (5): 77-82.
[4] Su Jianmin, Yang Lanxin, Jing Weipeng. High-Resolution Remote Sensing Image Semantic Segmentation Method Based on U-Net [J]. Computer Engineering and Applications, 2019, 55 (7): 207-213.
[5] Maki A, Dwyer P C, Blazek S, et al. Responding to natural disasters: Examining identity and prosociality in the context of a major earthquake [J]. Br J Soc Psychol, 2019, 58 (1): 66-87.
[6] Wang, ShiHao. Analysis of the Impact of Agricultural Natural Disasters on Agricultural Economy [J]. Agricultural Disaster Research, 2021, 11 (6): 170-171.
[7] Li, Hong. Regional Differences in the Economic Growth Effects of Natural Disasters: Based on Panel Data Analysis of Provinces from 1998 to 2018 [J]. Disaster Science, 2021, 36 (4): 1-6.
[8] Wang Guosheng. Analysis of Safety Production Management and Defensive Measures for Safety Accidents in Construction Engineering [J]. Development Orientation of Building Materials (Part I), 2019, 17 (12): 316-317.
[9] Zeng Taorui, Yin Kunlong, Gui Lei, Jin Bijing, Liu Xiepan, Liu Zhenyi, Guo Zizheng, Jiang Hongwei, Wu Liyang. Quantitative Assessment of Building Vulnerability Based on Landslide Hazard Intensity Prediction. Earth Science, 2023, 48 (5): 1807-1824.
[10] Liu Zhiyu, Liu Yuhuan, Kong Xiangyi. Problems, strategies and key technology research of flood forecasting and early warning for small and medium-sized rivers. Journal of Hohai University (Natural Sciences), 2021, 49 (1): 1-6.
[11] Dietz S, Niehörster F. Pricing ambiguity in catastrophe risk insurance [J]. The Geneva Risk and Insurance Review, 2021 (46): 112-132.
[12] Kramer B, Hellin J, Hansen J, et al. Building resilience through climate risk insurance: Insights from agricultural research for development [J]. CGIAR Research Program on Climate Change, Agriculture and Food Security, 2019: 287.
Downloads
Published
Issue
Section
License

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.






