Actuarial Analytics and Data I

to provide students with basic training on modern data analytics methods, which include linear regression, classification, resampling methods, spline-based methods, generalised additive models and support vector machines. This subject focuses on applying the above methods to modelling non-life insurance claims frequency and severity.

学习精算数据分析与处理的基础。

• 1Recognise major types of non-life insurance data and their main characteristics.
• 2Demonstrate a depth of knowledge in linear regression methods, regression splines and smoothing splines.
• 3Demonstrate basic understanding in various statistical learning models that include classification methods, re-sampling methods, generalised additive models and support vector machines.
• 4Use relevant computer software to apply various statistical learning models for insurance related applications.
• 5Apply basic linear model selection and regularisation techniques when conducting linear regression analyses.
• 6Interpret the results of data analytics conducted on real insurance data
• 7Compare benefits/drawbacks of competing models and methods, relevant to real problems.