Description: Read the October 2017 issue of CompAct, published by the Technology Section.

Description: Describes different ways to display a distribution of numerical results.

Description: A study of claims cost variation by policy duration fo rindividual medical insurance. The report presents results for single vs. family contracts with long-form underwriting, based on approximately $1.3 billion in incurred claims data provided by seven carriers, for incurral years 2001 through 2003.

Description: This is the inventory part of the report from the research project that reviewed and inventoried the range of quality and efficiency measures currently available for healthcare. The goal was to outline key areas of quality and efficiency measurement and identify future opportunities for actuaries. The inventory lists the resources and provides brief descriptions of their services with links.

Description: This chapter introduces a few probability distributions that play an important role in understanding and analyzing healthcare data. While theoretical in nature, these distributions model real life if appropriately chosen. Probability distributions are mathematical representations of how statistical data behave.

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: SOA Product Development Section Contest Winning Article. Contest was to provide a creative article on future technology for the life insurance industry.

Description: Read the December 2018 issue of Small Talk published by Smaller Insurance Company Section. Practical information on trends that impact sections and activities.

Description: "Visual storytelling is frequently used to effectively convey complex actuarial concepts to our clients and other audiences. When talking about data visualization, we often focus on the explanatory aspect. But data visualization is also a crucial tool in developing insights from large and complex data sets at every stage of data analytics spectrum: • descriptive (what happened?), • diagnostic (why it happened?), • predictive (what will happen?), • and prescriptive (how do I influence what will happen?). In exploratory and modeling stages of data analytics’ project, we let the data tell the story or explore our intuition and hypothesis through data pictures. We demonstrate the power of visual display in healthcare data analytics through vivid examples from the healthcare case studies. These illustrations of data visualization exploratory power range from assessing the quality of data or examining outliers, to exploring variables’ relationships and trends, to hypothesis testing, to guiding in feature selection and models’ comparison and evaluation, to model validation. Throughout these illustrations, we will discuss principles of graphical effectiveness, excellence and integrity."