Risk Index Model of Property and Cargo Insurance Claims Based on Precipitation in Hunan - Peng Weiying; Li Yueyong; Tan Shiqi; Li Hao; Guan Jianwen; Liao Chunhua; Zhou Wei; Xie Ruiheng (应用气象学报)
The relationship between insurance claims and precipitation levels is explored, especially in engineering insurance, home property insurance and enterprise property insurance within the realm of property and cargo insurance. It utilizes data from Hunan Branch of People's Insurance Company (Group) of China and Hunan Meteorological Station spanning from 2016 to 2020. By an advanced analysis method, a comprehensive risk index model is developed and tailored to different types of property and cargo insurance claims prevalent in Hunan Province. The primary objective is to assess how varying levels of precipitation affect the frequency and severity of insurance claims across these categories. Through the analysis of historical data, the key precipitation-related factors that significantly impact insurance claims are identified. These factors include 24-hour cumulative precipitation, 48-hour cumulative precipitation, 72-hour cumulative precipitation and the maximum hourly rainfall intensity preceding meteorological incidents.It is found that these factors exert varying degrees of influence on different types of property and cargo insurance. Notably, 48-hour accumulated precipitation emerges as the most critical factor affecting claims, followed closely by 72-hour accumulated precipitation. These insights are derived from a rigorous analysis that integrates meteorological data with insurance claims data, enabling the development of a robust risk index model. Validation of the model's efficacy involves approximately 202 insurance claim cases spanning from 2021 to 2022. Results show a commendable accuracy rate of 72.3%, particularly strong in predicting instances of mild claims risk levels. Importantly, the model proves effective even in scenarios where meteorological rainstorm standards are not met, showcasing its reliability in preemptively identifying potential insurance claim risks.Presently, the developed risk index model has been implemented in Hunan Insurance Meteorological Disaster Risk Control Service Platform Version 2.0. The platform uses advanced intelligent grid precipitation forecasting data to produce timely alerts for precipitation risk and impact forecasts. Such proactive measures are customized for different types of property and cargo insurance, thereby boosting the region's ability to reduce potential property and casualty insurance risks linked to precipitation events. In conclusion, the study emphasizes the significance of integrating meteorological insights with insurance analytics to enhance risk management strategies. By leveraging advanced modeling techniques and data-driven approaches, Hunan Province is better equipped to anticipate, assess and mitigate the impact of precipitation-related risks on property and cargo insurance, ultimately bolstering resilience and preparedness in the face of natural disasters.