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報告題目：A comparative analysis of several multivariate zero-inflated and zero-modified models with applications in insurance

主講人：吳學淵教授（墨爾本大學）

時間：2024年11月18日（周一）9:30 a.m.

地點：北院卓遠樓305會議室

主辦單位：統計與數學學院

摘要：Claim frequency data in insurance records the number of claims on insurance policies during a finite period of time. Given that insurance companies operate with multiple lines of insurance business where the claim frequencies on different lines of business are often correlated, multivariate count modeling with dependence for claim frequency is therefore essential. Due in part to the operation of bonus-malus systems, claims data in automobile insurance are often characterized by an excess of common zeros. This feature is referred to as multivariate zero-inflation. In this paper, we establish two ways of dealing with this feature. The first is to use a multivariate zero-inflated model, where we artificially augment the probability of common zeros based on standard multivariate count distributions. The other is to apply a multivariate zero-modified model, which deals with the common zeros and the number of claims incurred in each line given that at least one claim occurs separately. A comprehensive comparative analysis of several models under these two frameworks is conducted using the data of an automobile insurance portfolio from a major insurance company in Spain. A less common situation in insurance is the absence of some common zeros resulting from incomplete records. This feature of these data is known as multivariate zero-deflation. In this case, our proposed multivariate zero-modified model still works, as shown by the second empirical study.

主講人簡介：

吳學淵，教授、博士生導師，現就職于澳大利亞墨爾本大學經濟及工商管理學院精算研究中心，同時擔任學院精算博士點項目主管。澳大利亞精算師協會準精算師，具有超過18年國際知名學府教學經驗。瑞士洛桑大學、香港大學和南開大學訪問學者。美國《數學評論》評論員及27個國際學術期刊審稿人。已發表精算相關學術論文近40篇。主要研究領域為風險理論、精算統計和機器學習等。