Machine Learning and Statistical Learning in Insurance and Actuarial Science

Dear Colleagues,

In the last decade, machine learning and statistical learning have seen vast applications in the insurance field, both in practice and in research. In the insurance industry, Artificial Intelligence has begun to play a key role in reshaping insurance claims, distribution, and underwriting and pricing. Advancements in machine learning and statistical learning enable actuarial researchers to develop better data-driven methods on studying real-life insurance-related problems.

Since early 2020, there have been dramatic changes in people’s lives all over the world due to the COVID-19 pandemic and climate change. Lengthy lockdowns, extreme weather conditions, and the COVID-19 pandemic continued to affect world, impacting every aspect of individuals’ life.

This Special Issue aims to showcase innovative applications of most recent machine learning and statistical learning developments in post-COVID-19 insurance practice and research, in particular, on insurance automation, InsurTech, extreme weather forecasting, and health and aging. We welcome contributions in areas including, but not limited to, the topics listed below (in alphabetical order):

Dr. Peng Shi
Dr. Xueyuan Wu
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.