Description: This paper demonstrates the calculation of the moments of the distribution of aggregate life insurance claims from seriatim inforce data, assuming that each record represents an independent Bernoulli trial with its own known probability of a claim, q. Continuous distributions matching the first three or four moments are identified.

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: Discusses four areas of interest: Alternative Examination References, Validation by Educational Experience, Academic Program Accreditation, and an Alternate Route.

Description: This article comments on the editorial policies of the Actuarial Research Clearing House publication.

Description: Presentation on estimating rates of early-onset Alzheimer's Disease. This document contains incident rates, critical illnese insurance information, adverse selection, and more.

Description: Presentation from the 41st Actuarial Research Conference held on August 10-12, 2006 in Montreal, Canada. Fuzzy set theory is incorporated into times series analysis, giving fuzzy parameter estimates of models such as ARMA and GARCH. Examples are given, including returns on a stock and option valuation.

Description: This is the abstract of a paper that complements the existing research on optimal reinsurance by proposing another model for the determination of the optimal reinsurance design.

Description: In many countries, insurers and banks are separately regulated. In some countries, banks and insurers are not allowed to be part of the same conglomerate and share capital. This raises questions about the efficient use of capital and return on equity to shareholders. This is the abstract of an empirical study that views economic capital from a solvency perspective with the focus on downside risk. The key question addressed is 'What efficiencies, if any, are gained by allowing banks and insurers of different types to merge and thus share capital.' We examine to what degree bank and insurer performances have been correlated historically, especially in the downside tail. This case study is based on Canadian banks, life insurers and property-casualty insurers.

Description: When fitting a model to any data, there is some uncertainty about which model is best. Green [1995] quantifies this uncertainty through the Reversible Jump Markov Chain Monte Carlo [RJMCMC] method. When using the RJMCMC method in a regime-switching situation, the chain determines the optimal number of regimes by jumping between various possibilities. This method gives each model its posterior probability of being the best. After an overview of the methodology, the authors apply it to various datasets and discuss the applications in modern actuarial science.

Description: This abstract is for a paper that addresses the problem of optimal reinsurance design using the criterion of minimizing the Conditional Tail Expectation (CTE) risk measure of the insurer's total risk.