MCFAM Seminar Series: “Dynamic Prediction of Outstanding Insurance Claims Using Joint Models for Longitudinal and Survival Outcomes"
Please join us for our last seminar of the semester! This seminar will feature Lu Yang from the University of Minnesota School of Statistics who will discuss dynamic prediction of outstanding insurance claims using joint models for longitudinal and survival outcomes.
About the lecture
To ensure the solvency and financial health of the insurance sector, it is vital to accurately predict the outstanding liabilities of insurance companies. Professor Yang and her colleagues aim to develop a dynamic statistical model that allows insurers to leverage granular transaction data on individual claims into the prediction of outstanding claim payments. However, the dynamic prediction of an insurer's outstanding liability is challenging due to the complex data structure. The liability cash flow from a claim is generated by multiple stochastic processes: a recurrent event process describing the timing of the cash flow, a payment process generating the sequence of payment amounts, and a settlement process terminating both the recurrence and payment processes.
About the speaker
Lu Yang is an assistant professor in the School of Statistics at the University of Minnesota Twin Cities. She received her Ph.D. in statistics from the University of Wisconsin-Madison in 2017. Prior to joining the U of M, she was an assistant professor in actuarial science and mathematical finance at the University of Amsterdam. Her current research focuses on multivariate analysis, nonparametric estimation of copulas, and regression model diagnostics, especially with discrete and semi-continuous outcomes.