Description: Most actuaries deal with model development at some point in their career. However, very few of us have proper training in programming, software engineering or software shop operations. Explore topics, techniques, and practices from the FinTech and IT industries that can be applied to building robust, high-quality actuarial models. This session will be of particular interest to actuaries engaged in 'in-house' model development, managers of modeling teams, and actuaries interested in software development.

Description: Read the October 2020 issue of Actuarial Technology Today 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: How the speed of change is accelerating and how we could react to this as a profession.

Description: To remain relevant, insurers need to understand and adapt to changing consumer behaviors. There is no doubt about it, millennials have different expectations around searching, buying and servicing, and insurance is no exception! Come hear from four different insurance startups who are designing solutions for this future generation of insurance buyers, followed by a panel discussion with the opportunity to ask questions. You'll learn and perhaps even be inspired to propose solutions in your own company. You may even start calling yourself a Millenial Maven too!

Description: Machine learning models have many practical applications in the world of insurance. These applications are well documented and most actuaries, at least at a high level, are familiar with these concepts. The presenters will take this one step further and provide an introduction to the theoretical formulas and real-world considerations that make machine learning models possible.

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.

Description: Predictive modeling continues to gain traction in the life insurance industry with the rapid growth of available data and maturity of open source tools. New methods and technology in predictive analytics have enabled the evaluation of extremely large data more quickly and allow us to incorporate features previously not considered. The presenters will provide background on predictive modeling tools and algorithms utilized by actuaries and data scientists for life insurance, highlighting applications from marketing to underwriting.

Description: There is enormous interest by investors and business leaders in the potential for artificial intelligence technologies, often powered by predictive modeling and machine learning, to transform the way that companies do business.

Description: A basic introduction to the emerging field - insurance technology

Description: Our firm has developed the first publicly available insured lives mortality table for Cambodia using data science methods. This essay provides a brief background, our approach and the impact of our work.