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: The Society of Actuaries (SOA) is pleased to bring you information about the actuarial career path in life insurance and predictive analytics. We’ll continue to share more about actuaries who are tackling some of the industry's biggest challenges and top employers in life insurance.

Description: Using Healthcare Claims Data to Create Actuarial Models.

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: 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: 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.

Description: You really can have it all: readily available and relevant information derived from consistent and understood data. Getting at the Truth requires a good datawarehouse design and an appropriate business data model. Add a powerful and flexible Web–based analytical interface to get at the data and success in the pursuit of Truth will happen.