Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

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: The next evolution of actuarial systems in the U.S. will likely be a move toward a single system solution. This article defines a single system solution and illustrates how models can be shared across actuarial functions, the potential benefits of a single system solution, and describes potential mitigation strategies to address typical actuarial concerns.

Description: The article describes the key components of actuarial model, leading practices in designing them, and characteristics of well-built models.

Description: The comments of DxCG about their participation in the SOA study A Comparative Analysis of Claims-Based Tools for Health Risk Assessment.

Description: The article provides a high-level, non-technical, introduction to artificial neural networks (ANNs) and deep learning with an application to risk management. The method relies on typical ANN components such as nodes, activation functions, and optimization through gradient descent.

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

Description: This panel discussion considers some of the approaches, techniques and problems in the development of corporate models and assumptions. The pros and cons of buying versus developing models was discussed and the use of deterministic versus stochastic models was addressed as well.