Description: Statistics were invented to describe heterogeneity and are now applied to tackle alea. It may not be appropriate. Let's clarify their field of relevance.

Description: The different broad purposes served by the material change concept under federal tax law are outlined. More specific material change and similar issues that are pertinent to particular Code provisions and guidance from the IRS that has addressed those issues are also addressed. In the final part of this article, authors comment on whether any overarching principles can be gleaned that can assist insurers and policy owners in making decisions about whether particular changes can safely be made, and thoughts are offered with respect to future potential IRS guidance that would be helpful as taxpayers navigate these often uncertain waters.

Description: This article provides a detailed description of the unbalanced subsidy provisions in the Affordable Care Act with easy to follow numerical illustrations. An understanding of the illustrative calculations is necessary to understand the subsidy implications. The article highlights some surprising and likely unintended results that will be interest to issuers, employers, consumers, regulators and policymakers. Actuaries can add expertise to their clients and to the public discussion with a proper understanding of the subsidy calculations and the resulting implications.

Description: Introduction and table of contents of essay collection.

Description: A collection of essays that discuss the principles and ideas underpinning the ORSA initiative and the risk metrics used for decision making.

Description: This article delves into a new line of statistical thinking of the author, that may be useful for product development actuaries. The key concept is how product design can produce products that diversify quickly, meaning that the company can be confident of a profitable product line, based on fewer sales than might be true for other designs.

Description: Diverse Risks 2016 Call for Essays

Description: We highlight a new approach leveraging predictive analytics to identify high risk and rising risk opioid users for more effective screening and follow-up care.