Course Title:Non-life Insurance Actuarial Science
Prerequisites:Insurance, Probability Theory and Mathematical Statistics(EM), Risk Theory, Statistics
Corresponding Major:Actuarial Science
Course Introduction:
Non-life insurance actuarial science takes probability and statistics as the research tools and the uncertainties in non-life insurances as research objects. By establishing a stochastic model for quantitative description of the loss of insurance, it studies the law of future claims, and on this basis, and establishes the theoretical basis of rate determination and reserve withdrawal. Through the collection and analysis of all kinds of insurance compensation data, the future rate structure and the amount of reserve are determined, and a reasonable reinsurance method is arranged according to historical data.
The actuarial theory of non-life insurance plays a key role in the design of insurance types, the determination of premium rates, the withdrawal of reserves and reinsurance. Non-life actuarial science is the core content of the quasi actuary test and the quasi actuary test of China in the training system of the North American Actuary Council (NAAC). From the perspective of an actuary’s main responsibilities, it is the main business of non-life insurance actuary to assess risks, determine insurance rates, reserve, arrange reinsurances or carry out solvency tests. Therefore, non-life actuary is the core course in the whole actuary training system.
This course mainly focuses on the estimation of claim frequency and individual claim amount, the estimation of claim settlement model and the calculation of risk premium, complete and partial reliability, the most accurate reliability, the NCD system, rate determination, reserve evaluation,etc.The most accurate reliability, rate determination and reserve evaluation are the three most important and difficult learning points. Through this course, students can master the pricing model of non-life insurance products as well as the reasonable assessment method of reserves, which will lay a solid foundation for their future work and research.
