Description: While many know that machine learning is a big deal and even have a general idea of what it is, many do not know what machine learning can do for them. As an alternative to citing achievements or explaining algorithms, this article outlines the challenges that occur in statistics and the solutions that machine learning offers. Some of those challenges include correlated predictors, missing data, data interaction, and prediction intervals. Corresponding solutions include regularization technics, missing value imputation with KNN, tree based models, and cluster analysis for backtesting.

Description: Announcement of an upcoming 2003 Stochastic Modeling Symposium.

Description: Profitability of traditional life and health products has long been considered less sensitive to changes in interest rates than profitability of universal life, SPDAs, or other “interest-sensitive” products. Consequently, traditional products have often been priced with a single deterministic interest scenario.

Description: This article discusses how FHLB advances, i.e. low cost loans, can supply valuable risk management benefits. By carefully structuring an advance to mature coincident with the anticipated premium inflows generated by insurance products, a company can largely eliminate future net cash flows and consequently the need to invest them in uncertain capital markets.

Description: How to set asset assumption, at the cycle or through the cycle and other considerations