时 间：2023年10月27日13:00-14:00
地 点：普陀校区理科大楼A1514
报告人：Phillip Yam 香港中文大学教授
主持人：危佳钦华东师范大学教授
摘 要：
Classifying severity of risks has long been of vital importance in insurance and finance, this is a major concern in InsurTech and FinTech. Among widely adopted classifiers in practical use, the application of Support Vector Machine, Neural Network and Logistic Regression to insurance and finance datasets would lead to a potential substantial loss of information as these datasets usually involve a lot of categorical variables, yet none of these classifiers handle them comprehensively; on the other hand, Classification and Regression Tree handles categorical and discrete feature variables well enough by its design, yet it lacks the mechanism to deal with continuous feature variables. Moreover, the relatively strong dependence structures among feature variables, especially among categorical feature variables, in insurance and finance practices have not been explicitly accounted for in the aforementioned existing classifiers. We here propose to effectively model such an implicit strong enough dependence by comonotonicity. Altogether will be dealt with through our newly proposed Comonotone-Independence Bayes Classifier (CIBer), this leads to a far better clustering of the predictive feature variables that can facilitate an effective classification. We shall also demonstrate the effectiveness of CIBer as a tool in data analytics against those common classifiers through the empirical studies upon several representative datasets in finance and insurance.
报告人简介：
Phillip Yam received his BSc in Actuarial Science with first class honours and MPhil from the University of Hong Kong. Supported by the two scholarships awarded by the Croucher Foundation (Hong Kong), he obtained an MASt (Master of Advanced Study) degree, Part III of the Mathematical Tripos, with Distinction in Mathematics from University of Cambridge and a DPhil in Mathematics from University of Oxford. During his postgraduate studies, he was awarded with the E. M. Burnett Prize in Mathematics from University of Cambridge, and the junior research fellowship from The Erwin Schrödinger International Institute for Mathematics and Physics of University of Vienna.
Phillip is currently the Co-Director of the Interdisciplinary Major Program in Quantitative Finance and Risk Management Science, and a full Professor at the Department of Statistics of CUHK. He is also Assistant Dean (Education) of CUHK Faculty of Science, and Fellow of the Centre for Promoting Science Education in the Faculty. He got appointed as a research fellow in the Hausdorff Research Institute for Mathematics of University of Bonn and a Visiting Professor in the Department of Statistics of Columbia University in the City of New York. He has about a hundred journal articles in actuarial science and financial mathematics, applied mathematics, engineering, and statistics, and has also been serving in editorial boards of several journals in these fields. Together with Alain Bensoussan and Jens Frehse, he wrote up the first monograph on mean field games and mean field type control theory. His research project with the title Comonotone-independence Bayes Classifier (CIBer) was awarded a Silver Medal in the 48th International Exhibition of Inventions Geneva in 2023.