Description: The article discusses what actuaries mean by "acting in the public interest." While the article is focused on the U.S. environment, it includes materials describing how other actuarial organizations are addressing this critical issue. The article concludes with observations that explaining to the public what the actuarial profession means by "acting in the public interest" is important for both the public and the members of the U.S. actuarial profession.

Description: Letter from the editor for the January 2013 publication.

Description: Chairperson's Corner discussing actuarial principles and what we as actuaries value in our work.

Description: Actuaries and the Actuarial profession have an obligation to act in the public interest. It is not enough to pass exams, keep current and do "good actuarial work.” Both Science and public service must be reflected in all of our activities...The intent of this article is to clarify what "acting in the public service” means for actuaries, particularly U.S. actuaries. It emphasizes the importance (necessity) of examining the "public interest" in everything we do ... and to warn the public where we have concerns. ...Acting in the public interest (a requirement for any profession or professional, is critical to the profession's future reputation and relevance.

Description: Description of program parameters for next year.

Description: Summary of changes in Social Security program parameters effective in 2018

Description: Commentary from section chair

Description: A response to American Legislative Exchange Council's report "Unaccountable and Unaffordable" in light of applicable Actuarial Standards of Practice.

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.