Description: Impact investing is investments in “companies, organizations and funds with the intention to generate social impact alongside a financial return”.

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: Basic feature engineering uses input data to create dummy variables, log transforms, and other single-value transformations. This talk builds upon these univariate transformations and presents several strategies for creating complex multivariate features that can enhance your model's lift. Topics such as target encoding, dimension reduction/projection, row/column, and other feature engineering topics will be covered.

Description: This article discusses data mining and the statistics of coincidence, and provides “guidelines for backtesting integrity” to help ensure results have value beyond mere coincidence. Editor’s Note: The following article originally appeared in the Winter 1998 issue of the Horizon, a publication of BARRA, Inc., and is reprinted with permission.

Description: Comparison of healthcare costs for early retirees versus active workers in the same age band. When adjusted for age, there is not a significant difference in costs between each group.

Description: Neural networks have fallen only to rise again twice. The latest incarnation borrows much from the past but adds elements to support deep learning. This article demonstrates the state of the art in deep neural network programming.

Description: This dissertation by Tia Sawhney will help you understand this issue and start measuring it, or start promoting equitable public policy.

Description: A general introduction about predictive modeling in insurance applications. Some basic models are discussed, such as Generalized Linear Model(GLM), Calssification and Regression Tree Model. Other models are also briefly introduced, including data clustering, neural networks and support vector machine.

Description: How do you make model output media worthy? This article explores considerations that may contribute to the mass production of model results for public consumption.