Description: This article summarizes key points from the recently published research paper “Deep Learning for Liability-Driven Investment,” which applies reinforcement learning and deep learning techniques to liability-driven investment (LDI).

Description: Feature article discussing model monitoring

Description: Feature article discussing futurism and a study that contains in-depth descriptions of the Delphi and TIA methods; listings of the rationales and thought processes, the plausible future developments that could influence the values of these four economic variables and the resulting “fan of possibilities” for the values of these variables

Description: Python is the leading programming language for data science. Python programming is one skill that actuaries should acquire. It facilitates analytic work, and the available visualization tools help to communicate ideas. In this article, I use a traditional actuarial problem, mortality modeling, as an example.

Description: Feature article discussing the usefulness of Lorenz and Lift curves.

Description: There is a growing amount of “off-balance sheet” talent in the US and Global workforce. This spans from consultants and contractors, to gig workers and the crowd (both curated crowd and open crowd). One such example is Uber and Lyft workers. Insurance companies and the Actuarial profession have started to experiment with platforms such as Kaggle and this will continue to grow and evolve. This article explores these new sources of talent for companies, the implications to the actuarial function, benefits and challenges of the evolving workforce.

Description: Many life and health insurers are beginning to use Predictive Analytics (PA) for a variety of purposes. This article addresses the unique challenges and potential disruption PA brings to the risk manager, as well as the opportunities.

Description: The article explores the possibility of using the emerging technology for life insurers to build a monitor system for better risk and profitability management.

Description: An introduction to creating Shiny web applications, with sample code available to reproduce the interactive application displayed in screenshots in the article.

Description: It is about using actuarial judgement to validate the predictive model.

Description: In this article, we are going to discuss the AR model by making connections to time-dependent ordinary differential equations.

Description: This is the second article in a two-part series examining the potential value to companies of implementing a company profitability and risk dashboard.

Description: The SOA provides information about the actuarial career path in health care and predictive analytics. Throughout 2016, we will share more about actuaries who are tackling some of the industry's biggest challenges and hear from top employers in healthcare analytics.

Description: Looks at free and inexpensive resources for the novice in predictive analytics, covering the data analysis theory as well as the most commonly used languages/software used in the field.

Description: The article focuses on the use of predictive analytics in the development of experience studies, pros and cons of using predictive analytics versus traditional techniques, and the implications for setting assumptions and improving profitability.

Description: Important tools used in property & casualty P&C insurance—predictive modeling and data mining—can be applied to more effectively model policyholder behavior risks in variable annuity VA contracts. In this article, a case study is used to demonstrate how a predictive modeling approach can improve upon traditional methods used to model VA lapse behavior.