Description: Increasing technology is available to create and disseminate educational resources worldwide. In response, this article advocates creation of open educational resources (OERs) that will benefit the actuarial profession with both recruitment and retention of members. Specifically, we describe OER contributions made at the University of Wisconsin-Madison and more recently through the ASTIN Academy, a working group of ASTIN, the non-life section of the International Actuarial Association. We advocate pushing boundaries and creating new ways of teaching effectively for the future. The innovative use of technology and open-source materials is a way to foster diversity, equity, and inclusion in the actuarial profession.

Description: In a product warranty, the renewal function is the expected number of failures in a specific warranty duration. To estimate the renewal function, cross-sectional regression data is assumed to be available and the data is assumed to be semiparametric. In this article, the observations are a11owed to be residuals from a complex regression model. It is observed that estimation can be accomplished using reasonable models for the contracts and data collection. From Actuarial Research Clearing House 1992, VOL. 2.

Description: An article in the Expanding Horizons newsletter, Issue 26, published in April 2003 that discusses the Annual Prize to the author or authors writing the best paper to appear in the North American Actuarial Journal, the leading scientific publication of the Society. It announces the winners of the award, Mary R. Hardy for A Regime–Switching Model of Long-Term Stock Returns,and Phelim P. Boyle, Adam W. Kolkiewicz and Ken Seng Tan, for Valuation of the Reset Options Embedded in Some Equity–Linked Insurance Products.

Description: The projection methods used by the Social Security Administration's Office of the Chief Actuary are important. The resulting projections are cited regularly by policy-makers, academics and others interested in the long-term financial solvency of the OASDI system. However, a complete description of this projection methodology that is vital for serious policy discussions is not available to the general public. This summary was constructed in connection with the Social Security Advisory Board's 1999 Technical Panel on Methods and Assumptions. A goal of the Methods and Modeling working group of the Technical Panel was to 'work to ensure that the projection methods used by the Office of the Chief Actuary become more public.' From Actuarial Research Clearing House 2000, Vol. 1.

Description: Automobile insurers classify the risks that they underwrite in order to subdivide the portfolio into classes of risks with similar profiles. While some insurers may have sufficient historical data, several others may not have significant volume of experience data in order to produce reliable claims predictions to help enhance their risk classification systems. A database containing a pooled experience of several insurers thereby helps to produce a more fair, reliable, and equitable premium structure for all risks concerned. This paper uses multilevel models to analyze the data on claim counts provided by the General Insurance Association of Singapore, an organization consisting of most of the general insurers in Singapore. The multilevel nature of the data is due to the following: a certain vehicle is observed over a period of years and is insured by a particular insurance company under a certain 'fleet' policy. The authors show how intercompany data lead to a priori premiums and a posteriori corrections to these initial premiums. Specific focus is made in understanding the intercompany effects using various count distribution models [Poisson, negative binomial, zero–inflated and hurdle Poisson]. The performance of these various models is compared the authors also investigate how to use the historical claims of a company, fleet and/or vehicle in order to correct for the premium initially set.

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: Abstract to research paper which introduces estimators of stock price volatility.

Description: This article discusses Jed Frees’ book in progress, “Regression Modeling with Actuarial and Financial Applications” which offers a synthesized introduction to regression and time series.

Description: This paper provides an overview of deductible ratemaking , and the pros and cons of various approaches under different parametric models are compared

Description: This paper provides an overview of deductible ratemaking , and the pros and cons of various approaches under different parametric models are compared