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: Python has become the fastest-growing major programming language in the world. It has surged in popularity over the last decade, following the development of its industry-leading capabilities in data science, machine learning and artificial intelligence, and it is now one of the most globally popular and widely used languages. In this article, I discuss some of the reasons for its popularity and explain why many actuaries and insurers have started using Python.

Description: Chairperson's Corner

Description: The purpose of the article is to highlight how a person or organization can excel in both a highly-competitive expert-driven environment and one where the environment is less so. One should focus on what can be done well and delegate the remaining tasks to those who are better at performing them. One should understand the environment they are operating in, how it impacts them, and how it may change through time. The principles have application to investment management, investment performance, organizational performance, business development, career progression and economics.

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: 1998 Valuation Actuary Symposium. The panelists discussed the benefits of data integration, data warehousing, what OLifE is now, and what it is projected to be in the future.

Description: The article discusses the use of R in prototyping automation procedures. It offers general pros and cons for R and walks through a specific use case, which involves scraping and summarizing data stored in Microsoft Excel.