讲座题目:Emerging Risk Management and Data Techniques in Insurance
主讲嘉宾：Professor Zhuo Jin，Macquarie University
讲座时间：2024年7月3日（周三）14:00-16:00
讲座地点：太阳成集团tyc33455ccwww学院南路校区主教306
Abstract:For cyber risk management, a cluster-based method is developed to investigate the risk of cyber-attacks in the continental United States. The proposed analysis considers geographical information on cyber incidents for clustering. By clustering state-based observations, the frequency and severity of cyber losses demonstrate a simplified structure: independent structure between inter-arrival time and size of cyber breaches. The independence between frequency and severity is significant at the state level instead of the national level. It is shown that the cluster-based models have a better fitting and are more robust than the aggregate model, where all incidents are considered together. To detect fraud insurance claims, we propose a new variable importance methodology incorporated with two prominent unsupervised deep learning models, namely, the autoencoder and the variational autoencoder. Each model's dynamics are discussed to inform the reader on how models can be adapted for fraud detection and how results can be perceived appropriately with a greater emphasis placed on qualitative evaluation.
Bio：
Dr Zhuo Jin is a professor of actuarial studies in the Department of Actuarial Studies and Business Analytics at Macquarie Business School. He is an Associate in the Society of Actuaries (ASA). His research interests include optimal control in actuarial science, mathematical finance, numerical methods in stochastic systems, and machine learning. His research has been funded by Hong Kong RGC and other funding bodies. He has published more than 60 papers in international journals and book chapters, including top-tier journals：Insurance Mathematics and Economics, European Journal of Operational Research, ASTIN Bulletin, Journal of Risk and Insurance, SIAM Journal on Control and Optimization, and Automatica.
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