Description: This article describes how to externalize code of Moody's Axis platform to Visual Studio, so that all the actuarial calculation code run through corporate DevOps pipeline. This article gives specific examples of the author has used in his job to accomplish automated model governance.

Description: This article will be focused on maximizing the reuse of code using features available within Moody’s Axis specifically targeted at using Formula Link.

Description: This article demonstrates how to implement DevOps for data using Moody's Axis. This was described as Model as Data (MAD). It described how extract turn-around documents from the model so they could be loaded back into the model. This feature allows continuous integration, continuous deployment and continuous testing of the model, which are important concepts in DevOps. This will allow the actuaries to speed up the model development cycle.

Description: Read the December 2017 issue of Predictive Analytics & Futurism published by the Predictive Analytics & Futurism Section.

Description: This article describes how to model variable annuities using a GPU along with some of the stumbling blocks.

Description: Insurance regulations are undergoing a paradigm shift in determining capital and reserves. With Solvency II in Europe and principle-based reserving in the United States, the old formula-based static approach is being replaced or supplemented by a principle-based dynamic method. This change requires enhanced modeling, stochastic simulation and sensitivity analysis, which pose challenges to insurers whose infrastructure has not been built for big computation. This paper introduces a method of building complicated models with small reusable modules and running them on a many-task computing platform to achieve high performance with simplicity. The paper presents an example of a term life insurance model built to take advantage of computer hardware for parallel computing at the task level.

Description: Insurance regulations are undergoing a paradigm shift in determining capital and reserves. With Solvency II in Europe and principle-based reserving in the United States, the old formula-based static approach is being replaced or supplemented by a principle-based dynamic method. This change requires enhanced modeling, stochastic simulation and sensitivity analysis, which pose challenges to insurers whose infrastructure has not been built for big computation. This paper introduces a method of building complicated models with small reusable modules and running them on a many-task computing platform to achieve high performance with simplicity. The paper presents an example of a term life insurance model built to take advantage of computer hardware for parallel computing at the task level.

Description: Health Watch, Issue 79, December 2015, Health Watch

Description: October 2015 issue of CompAct, the technology section's member benefit newsletter.

Description: The Modeling Platform

Description: This article discussed the NEAT family of neural network algorithms. NEAT automatically determines the number of hidden neurons, as well as their structure. Additionally HyperNEAT can scale to very large problem domains.