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DESCRIPTION:Title: Prediction of Bundled Insurance Risks with Dependence-aw
 are Prediction using Pair Copula Construction\n\n\n	Abstract:\n\n\nWe propo
 se a dependence-aware predictive modeling framework for multivariate risks
  stemmed from an insurance contract with bundling features – an important 
 type of policy increasingly offered by major insurance companies. The bund
 ling feature naturally leads to longitudinal measurements of multiple insu
 rance risks. We build a novel predictive model that actively exploits the 
 dependence among the evolution of multivariate repeated risk measurements.
  Specifically\, the longitudinal measurement of each individual risk is fi
 rst modeled using pair copula construction with a D-vine structure\, and t
 he multiple D-vines are then integrated by a flexible copula. While our an
 alysis mainly focuses on the claim count as the measurement of insurance r
 isk\, the proposed model indeed provides a unified modeling framework that
  can accommodate different scales of measurements\, including continuous\,
  discrete\, and mixed observations. A computationally efficient sequential
  method is proposed for model estimation and inference\, and its performan
 ce is investigated both theoretically and via simulation studies. In the a
 pplication\, we examine multivariate bundled risks in multi-peril property
  insurance using the proprietary data obtained from a commercial property 
 insurance provider. The proposed predictive model is found to provide impr
 oved decision making for several key insurance operations\, including risk
  segmentation and risk management. In the underwriting operation\, we show
  that the experience rate priced by the proposed model leads to a 9% lift 
 in the insurer’s profit. In the reinsurance operation\, we show that the i
 nsurer underestimates the risk of the retained insurance portfolio by 10% 
 when ignoring the dependence among bundled insurance risks.\n\n\n	Speaker\n
 \n\nPeng Shi is an associate professor in the Risk and Insurance Departmen
 t at the Wisconsin School of Business. He is also the Charles and Laura Al
 bright Professor in Business and Finance. His interests are problems at th
 e intersection of insurance and statistics. Current research focuses on lo
 ngitudinal data\, dependence models\, insurance analytics\, and actuarial 
 data science.\n\nProfessor Shi is an Associate of the Casualty Actuarial S
 ociety (ACAS) and a Fellow of the Society of Actuaries (FSA). He holds a P
 h.D. in business with a minor in economics from the University of Wisconsi
 n-Madison.\n\n\n	\n		\n			https://mcgill.zoom.us/j/83436686293?pwd=b0RmWmlXRXE3O
 WR6NlNIcWF5d0dJQT09\n\n			Meeting ID: 834 3668 6293\n\n			Passcode: 12345\n		\n	\n
 \n
DTSTART:20211119T203000Z
DTEND:20211119T213000Z
SUMMARY:Peng Shi (Risk and Insurance Department at the Wisconsin School of 
 Business)
URL:/mathstat/channels/event/peng-shi-risk-and-insuran
 ce-department-wisconsin-school-business-334820
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