Description: This session from the 1995 SOA Vancouver Meeting discusses systems management, how users have become involved in the development of systems and the formal systems development process. From the Record of the Society of Actuaries, Vol. 21, No. 3b.

Description: Discusses the evolving role of technology within the actuarial profession and the current use of electronic bulletin boards on the internet.

Description: The author offers tips for e-mail etiquete.

Description: The Potential Impact of Pandemic Influenza on the U.S. Life Insurance Industry pandemic model tool. This tool is used to project a Life Insurance companies potential losses from an influenza pandemic. Please see the SOA website for complete instructions on how to use this excel spreadsheet tool. Also see the website for the complete research report: www.soa.org/research/research-projects/life-insurance/research-impact-pan-influ-life-ins.aspx. The core of the paper is quantifying the potential impact of selected pandemic scenarios on the Life Insurance industry.

Description: This is the first of two articles discussing technologies used to control data. this article covers data management strategies.

Description: In this article, Microsoft describes how it is meeting the insurance industry's need for increasingly powerful software tools.

Description: This article is about how to start a career in the technology field.

Description: Discusses an SOA study entitled Blue Ocean Strategies. The objective was to deliver insight into how the use of technology may impact the design, marketing, sales, underwriting and/or processing of insurance.

Description: LDTI’s introduction has forced many insurers to examine their existing operations and technologies. They must determine how to optimize compliance efforts while balancing data, analytics and system modernization considerations to achieve maximum value. This article will examine the four key facets—the data, technology, processes, and people—essential to any successful LDTI exercise. It will also touch on the various approaches for tackling LDTI and how a modernization mindset can help insurers realize much greater transformation for the business.

Description: Machine learning models are not black-boxes; these models can easily be interpreted using tools like SHAP, LIME and Anchor. These tools can facilitate the understanding of the model and the business problem. We can used these tools to build better models and communicate how predictions are generated. This article demonstrates their use in a mortality model.