Description: This article explores the possibility of using machine learning to improve, or potentially rewrite, actuarial code within actuarial software.

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: Explores the open vs. closed systems debate with regards to actuarial modeling and exposes the over-simplification. Valuable for anyone who uses models.

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

Description: Presented at May 2005 Spring Meeting. Panelists discuss strategies for increased modeling speed as risk management, valuation and product development activities have been requiring increasingly complex financial models.

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

Description: Discussion of how to apply FinTech and IT processes and technologies to building an in house actuarial models.

Description: When setting reserves, multiple methods are often used in the creation of the reserve estimate. Judgment is warranted to combine these different estimates into a final recommendation. This paper describes two techniques that can be used to combine these estimates that may result in better accuracy and lower variance.

Description: This article explains why distributed computing systems have grown in popularity as well as the benefits and drawbacks of implementing them.