Description: Open source programming languages have become a common part of the actuarial toolkit over the years. Using tools like R and Python, highly technical actuaries can automate onerous processes, easily work with massive amounts of data, create models and generate reports. Although these tools excel at turbo-charging analysts, it can be difficult for benefits to inure to the rest of the organization given the learning curve (“Can’t you just put this in Excel?”), control risks (“So your entire process could break overnight if some random person in Nebraska changes something?”), and internal IT environments. Listen in on a panel discussion where presenters share their personal stories of working with open source in a production setting. Hear about real world business problems, how open source tools were used, what risks were present, how they were overcome and the final business result.

Description: This report outlines a framework for interpretable machine learning algorithms for detecting fraud in health insurance. It discusses the challenges of using black-box machine learning models in the insurance industry and proposes various interpretable methods to enhance transparency and understanding.

Description: The document explores how AI-supported underwriting influences mortality slippage in accelerated underwriting and evaluates real-world applications, risks, and industry impacts.

Description: Session 2– Going Deeper through examples InsurTech (1) identifies a pain point to the industry, (2) brings a technology solution to address the shortcoming with a (3) business model that makes sense for all. Expect an illustration of this three-point structure through a handful of start-ups from various backgrounds (health, life, general operation) dealing with various aspects of the insurance value chain (acquisition, risk management, back-office…).

Description: This paper reviews the applications of operations research methods in the insurance industry. From Transactions of Society of Actuaries 1995, Vol. 47.

Description: Big data, predictive analytics, machine learning and AI will likely transform the insurance market and the actuarial profession. The actuarial profession is seeing changes many markets, including health and property and casualty. This article describes these trends and provides an introduction into what companies and the Society of Actuaries (SOA) are doing to adapt and capitalize on these trends.

Description: A call for articles for the Technology Section’s newsletter CompAct.

Description: Brief summaries of two sessions at the 2010 SOA Annual Meeting: Joint Technology and Entrepreneurial Actuaries sections' reception and The Actuarial Technology Perfect Storm.

Description: Enumerates the observed preferences of attendees at the June 2011 Southeast Actuaries Conference, SEAC, for apps, phones, and other technological appliances and applications.

Description: This article shows how to deal with very large CSV files and the R programming language.