Description: Actuaries provide special subject matter expertise to question (or validate) the results of data analytics models. Other quants often cannot do this.

Description: A good primer on how clinical studies should be conducted and how statistics are used and misused to influence us.

Description: Panelists discuss pricing issues, patent issues, safeguards, successes, failures, and other observations about the future of automated underwriting. From the 2002 Record of Society of Actuaries, Volume 28, No. 3. Session 134PD of the Boston Annual Meeting.

Description: 1. A simplified description of how a genetic algorithm works (requiring no knowledge of biology) and how to build your own. 2. A free Excel workbook that allows you to solve problems without doing any coding; or to let you extend the existing code for your own special needs.

Description: Provides a simplified explanation of the modeling and statistical terms currently in use by the profession, and provides a list of publications worth reading in regards to complexity science plus a list of free software.

Description: The first annual SOA Predictive Analytics Symposium was held in Chicago and exceeded all expectations in attendance, presentation quality, and relevant content.

Description: The author discusses the two-part presentation on complexity science tools at the SOA Annual Meeting October 2010. He explains that presentations went back to basics with explanations about the difference between modeling tools used to employ deterministic methods for classical actuarial models.

Description: This is the full version of CompAct newsletter, published May 2004, Issue No. 17.

Description: A first look, and actuarial review of an electronic book for actuaries who wish to learn Excel beyond the basics.

Description: The editor of the newsletter provides a running list of articles included in the issue highlighting such topics as the applicability genetic algorithms, the power of group dynamics, judgmental forecasting, improvement in mortality and complexity science.