Description: Python is the leading programming language for data science. Python programming is one skill that actuaries should acquire. It facilitates analytic work, and the available visualization tools help to communicate ideas. In this article, I use a traditional actuarial problem, mortality modeling, as an example.

Description: Techniques that have gained some traction in general (property/casualty) insurance will be highlighted with a particular focus on the linear mixed model. This model adds random effects to the more commonly seen fixed effects (for example, as used in GLMs).

Description: Health Watch, Issue 79, December 2015, Health Watch

Description: Research report that explores key factors associated with an insurer’s reputational risk and conditions that would generate incentives for insurers to behave in a way that causes loss of their positive reputation.

Description: Panelists discuss the methods HMOs employ to measure their providers' quality of care, outcomes, compliance with best practice guidelines, and cost control. From the Record of the Society of Actuaries, Vol. 25, No. 2.

Description: 1994 SOA Spring Meeting, Orlando. In this session the panel consider the question of uncertainty in loss reserves including discussion of sources and measurement. The panelists analyzed the same data set from different perspectives and discussed the strengths and weaknesses of the approaches.

Description: This paper outlines a method of parametric modeling that may be used to produce forecasts and forecast intervals that will convey a measure of the reliance that may be placed on the forecasts. Followed by 2 discussion papers submitted