Research on Teaching Innovation of Property Insurance Course:Based on the Perspective of Big Data Development

The development of big data has brought unprecedented challenges and opportunities to the teaching reform of higher education.Property insurance course is the core course of economics and management,and it is the guarantee for the supply of talents in the health financial market.Big data technology and data economy put forward innovative requirements for its teaching objectives,teaching content,and teaching system.In China’s new round of double-first-class universities and disciplines,big data is an important foundation and driving force.The comprehensive integration of property insurance and big data is reflected in:Cultivate students’big data thinking;Cultivate students’practical application ability based on market employment needs;Build a new discipline system of applied economics,and achieve good coordination between property insurance courses and other disciplines;The government,enterprises and universities form a strategic partnership to jointly participate in the development and construction of courses;The formulation of government policies can have a better governance effect on the development of higher education and talent training.

Study on Torrential Rain Disaster Index and Threshold in Zhangjiajie City

Based on the precipitation data and torrential rain disaster data in Zhangjiajie City of Hunan Province from 2016 to 2020,taking the claim cases of the property and cargo insurance(hereinafter referred to as"property and cargo insurance")from Hunan Branch of the People’s Insurance Company of China as the research sample,the Dominance Analysis Method was used to determine the influence weights of disaster-causing factors to establish a comprehensive disaster-causing index(I)model of torrential rain.Second,an exponential function was used to fit the relationship between the number of town or street which filed claims of property and cargo insurance and I,then to determine the threshold of I corresponding to different accident levels.The claim cases caused by torrential rain disaster in Zhangjiajie in the flood season of 2021 were selected to verify the I and its threshold.The results showed that the number of property and cargo insurance accidents caused by torrential rain in Zhangjiajie was generally low in east and west but high in middle areas.Among the disaster-causing factors,the weight of the 96-h accumulated precipitation on the scope of accident was the largest,reaching 28.6%.The simulated grades of the scope of accident,the amount of claim and the number of accidents of property and cargo insurance had a high correlation with the grades of actual disasters,and all passed the test at the 0.01 significance level.The threshold test results showed that the consistency rate or accuracy between the predicted level and the actual level of torrential rain disaster-causing cases was 71.4%,in which the predicted values of accuracy for the mild,moderate and severe disaster levels were 70%,70%and 100%,respectively.Therefore,the threshold of I established in this study can be used for the industrial meteorological services related to the property and cargo insurance in Zhangjiajie.