Description: This paper develops credibility using a longitudinal data framework. In a longitudinal data framework, one might encounter data from a cross-section of risk classes towns with a history of insurance claims available for each risk class. For the marginal claims distributions, we use generalized linear models, an extension of linear regression that also encompasses Weibull and Gamma regressions. Copulas are used to model the dependencies over time specifically, this paper is the first to propose using a t-copula in the context of generalized linear models. The t-copula is the copula associated with the multivariate t-distribution like univariate t-distributions, it seems especially suitable for empirical work. Moreover, we show that the t-copula gives rise to easily computable predictive distributions that we use to generate credibility predictors. Like Bayesian methods, our copula credibility prediction methods allow us to provide an entire distribution of predicted claims, not just a point prediction.

Description: Data files for presentation.

Description: This is the first article in the new "Fireside Chat" series which intends to honor highly accomplised academic actuaries and allow them to share their insights into academic careers with young scholars. This article is mainly based on an interview with Dr. Edward Frees (Jed), one of the most accomplished actuarial professors.

Description: This article describes the 2009 actuarial research conference.t

Description: The University of Wisconsin–Madison used its Centers of Actuarial Excellence grant to develop technology enhanced learning (TEL) tools that would be distributed publicly to supplement the actuarial education classroom experience.