Description: This article discusses the goals set and progress-to-date for creating a standard file format for economic scenario generation.

Description: This column discusses the use and management of data withn the computer language R.

Description: Principal component analysis is an unsupervised linear transformation mainly used for dimension reduction. Determine key numerical variables with maximum variances in a dataset, identify the correlation and removal of redundant variables are the key aspects of this exploratory data analysis.

Description: Profile of an actuary in a non-traditional actuarial role: focusing on medical cost and analysis, both retrospective and prospective.

Description: Read the Sept. 2017 issue of Small Talk published by Smaller Insurance Company Section. Practical information on trends that impact sections and activities.

Description: This article gives an historical description of calculating and tabulating equipment used by, and is some cases developed by, actuaries in their work.

Description: This article looks at our use of technology- then and now. A reprinted article from the very first Pension Section News in June 1989, written by Barbara Choyke and titled '1,100 View SOA’s First Teleconference,' is juxtaposed against a view of today’s webcast communications.

Description: Technological innovations are disrupting traditional business models, improving products, and enhancing the user experience.

Description: Read the December 2017 issue of Predictive Analytics & Futurism published by the Predictive Analytics & Futurism Section.

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."