Actuarial Mathematics and Data Analytics

Dear Colleagues,

The advances in actuarial data analytics have been witnessed in the past decade. The rapid developing artificial intelligence and machine learning technologies provide innovative insights on building actuarial descriptive/predictive models and addressing a variety of actuarial decision-making problems.  Emerging machine-learning methodologies can be found in the fields of both life and non-life insurance, such as mortality rate forecasting, health care claims modelling, loss reserving, insurance fraud detection, and index insurance design. These methodologies and skills also enable actuarial researchers to investigate more the interdisciplinary areas, such as pandemic risk, cyber risk, climate risk and agriculture insurance, and help them to develop related risk hedging tools.

The main aim of this Special Issue is to provide a platform for the discussion of quite recent achievements in actuarial data analytics and the related challenges. We welcome original research articles that explore either theoretical or applied aspects of data analytics in actuarial science, which include but not limited to the above-mentioned topics.

Dr. Wenjun Jiang
Dr. Yiying Zhang
Guest Editors

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