Description: This article gives a brief overview of ways to extend clustering analysis beyond basic methods such a k-means

Description: Overview of opportunities for actuaries in business analytics, as well as the applied statistics and programming skills necessary to succeed.

Description: Health care predictive analytics varies between payers and providers as well as being a powerful tool in business decision modeling.

Description: A three-minute neuroscience-based image exercise is able to accurately unlock the emotional state of individual employees, permitting prediction of a host of specific needs. Actuaries can use this quantitative information at scale to target resources, benefits, and supports to increase the objective wellness and subjective well-being of workforces.

Description: In this article, we will overview some popular tree-based models and understand how such models may be applied to the insurance industry.

Description: In An Introduction to Incremental Learning, by Qiang Wu and I describe how machine learning is a natural enhancement to predictive analytics through its many useful tools to derive meaning from a lot of otherwise unusable data such as handwriting. Again, there are formulas involved; but we have tried to keep them understandable to the actuary who isn’t already familiar with stochastic gradient descent, perceptrons, and principal component analysis. Incremental learning can help you refine the estimations you derive from more traditional actuarial methods.

Description: The article introduces the concept of overfitting in predictive modeling and illustrates how it hinders our ability to predict new data well.

Description: A discussion on machine learning and how it can be used for forecasting.

Description: This article discusses techniques used to create risk scores to help determine appropriate primary care panel sizes for a provider organization.