Description: Explores the open vs. closed systems debate with regards to actuarial modeling and exposes the over-simplification. Valuable for anyone who uses models.

Description: Mindful data visualizations show the end users the end way in how to analyze and interpret your data. More importantly, they can then use this data they see to drive decisions and modeling going forward.

Description: Using Healthcare Claims Data to Create Actuarial Models.

Description: Read the April 2017 issue of CompAct published by the Technology Section. Newsletters provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Possible usage of tools that can automate time consuming processes, and lead to a different team structure and organization for predictive analytics team.

Description: This article summarizes some of the operational considerations necessary to optimize the usefulness and impact of a predictive model, such as cross-functional support and involvement in model build, adequate training and reporting, and strategic model build.

Description: Letter fron the Chairman.

Description: Maintaining solid financial performance is a KPI for senior management. With the advancement of technology, the management can leverage new techniques to improve their decision making and focus on higher value activities in a timely manner. This presentation sets out the use of 1. correlation analysis to draw relationship between financial metrics and 2. smart analytics techniques, including text mining and analytics, to identify trends and drivers that impact the valuation of a company. We will also assess how the results of a comprehensive financial analysis could influence risk management considerations, including business steering and risk strategy.

Description: This article discussed the NEAT family of neural network algorithms. NEAT automatically determines the number of hidden neurons, as well as their structure. Additionally HyperNEAT can scale to very large problem domains.

Description: Review of a research project, co-sponsored by the SOA, which examined 83 organizations and over 150 programs that measure the quality and efficiency of hospitals and physicians.