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20210625:联合模型预测及其在个体准备金评估中的应用
时间:2021-06-24

报告时间:2021年6月25日 上午9:00-10:00

报告地点:腾讯会议(会议ID:463 350 220)

报告嘉宾:Peng Shi

报告主题:Joint model prediction and application to individual-level loss reserving 


报告摘要

In non-life insurance, the payment history can be predictive of the timing of a settlement for individual claims. Ignoring the association between the payment process and the settlement process could bias the prediction of outstanding payments. To address this issue, we introduce into the literature of micro-level loss reserving a joint modeling framework that incorporates longitudinal payments of a claim into the intensity process of claim settlement. We discuss statistical inference and focus on the prediction aspects of the model. We demonstrate applications of the proposed model in the reserving practice with a detailed empirical analysis using data from a property insurance provider. The prediction results from an out-of-sample validation show that the joint model framework outperforms existing reserving models that ignore the payment-settlement association.


个人简介

Peng Shi is an associate professor in the Risk and Insurance Department at the Wisconsin School of Business. He is also the Charles & Laura Albright Professor in Business and Finance. Professor Shi is an Associate of the Casualty Actuarial Society (ACAS) and a Fellow of the Society of Actuaries (FSA). His research interests are problems at the intersection of insurance and statistics. He has won several research awards, including the Charles A. Hachemeister Prize, the Ronald Bornhuetter Loss Reserve Prize, and the American Risk and Insurance Association Prize. He is the editor of Variance journal, and also serves on the editorial board of ASTIN Bulletin and Insurance Mathematics and Economics.