Research On Probability Of Auto Insurance Claims Under The Background Of Big Data

Since 2000,with the rapid development of China's economy and the increase of per capita disposable income,the per capita ownership of automobiles has grown rapidly.At the same time,due to the support of relevant national policies,the entire automobile insurance industry has developed comprehensively.With the rapid economic development and a series of policy support,the domestic auto insurance industry has developed rapidly,and auto insurance has become the largest insurance type of property insurance premium income,so it has also become an important part of daily life.Since the start of a new round of commercial fare reform in June 2015,as of March 8.201 8,the insurance regulatory department has implemented three commercial fare reforms,and has adopted a gradual approach to pilot commercial fare reforms in various provinces.Allowing insurance companies to determine the scope of the adjustment of the rate coefficient themselves when drafting commercial vehicle insurance rates.However,at the same time,the commercial car fee reform has also intensified competition among various insurance companies.Most insurance companies blindly rely on low premiums to obtain customers and high commissions to expand intermediary channels,and ignore the potential risks of customers and the company's own operations Risks,leading to the loss of annual profits of most small insurance companies.Therefore,insurance companies urgently need a set of auto insurance claim probability prediction models that can calculate more scientific and reasonable auto insurance premiums based on the risk levels of different customers.With the advent of the data age,big data has brought opportunities for change in the development of various industries.Therefore,how to use big data technology to develop a more accurate probability model of automobile claims has become the key to the development of various insurance companies.The content of this article involves theoretical knowledge in insurance.statistics,actuarial science,and computers.The qualitative analysis method,comparative analysis method,and literature research method are used to study the application of machine learning models to the prediction of automobile insurance claims.The dissertation first introduces the development status of the motor vehicle insurance market in detail.Nowadays,the development of big data insurance at home and abroad,these basic conditions can be verified by understanding the examples later.Secondly.this article takes an insurance company in Shandong as an example to empirically analyze the application of big data technology to insurance companies.The empirical results show that the random forest algorithm has a good performance in the auto insurance claim probability prediction model.The research results in this paper can be applied to the prediction of vehicle risk in the insurance industry,providing a basis for differentiated pricing for customers,reducing premiums for low-risk customers,and increasing premiums for high-risk customers,thereby attracting more high-quality customers.At the same time,the research method in this paper can provide a reference for other forecasting problems in the insurance field.Finally,this article summarizes the full text,and puts forward personal recommendations for the current status of domestic insurance.