Description: Describes the predictive analytics revolution taking place in the insurance industry

Description: We compare two predictive analytics methods - GLM and GBM in terms of predictiveness vs. interpretability.

Description: Read the February 2020 issue of Predictive Analytics and Futurism published by the Predictive Analytics and Futurism Section. Newsletter provide practical information for the working actuary, articles on trends that impact sections and news about section activities.

Description: Predictive models can improve the traditional actuarial assumption-setting process. Data science techniques can provide deeper insights into experience through their ability to identify key drivers, rank importance and account for interactions. The presenters will cover ways in which companies can utilize predictive analytics to set assumptions, including the various methods available and practical approaches for implementation. They will also discuss the advantages and challenges of using predictive models for setting assumptions for life, annuity and disability products.

Description: This article describes the history and in some respects, the future of Big Data, and the tools we can use to handle it for PM and for machine learning. One such tool is Vowpal Wabbit, which sounds like something from a Bugs Bunny and Elmer Fudd cartoon (“Dwat that wabbit”), but it really is a popular approach to process a dataset of any size, as there is no need to load all the data into memory. Big data is forcing us to enhance many of our tools. So is the increased actuarial usage of stochastic-in-stochastic analyses (nested stochastic processes), which can result in unacceptably long program run times. Many of our popular computer languages are not inherently well suited for parallel computations.

Description: The objective of this paper is to provide a practical guide with concrete case studies to help actuaries implement artificial intelligence and machine learning (AIML) to help accelerate the speed of analysis for life and annuity actuarial modeling. We do so by researching the existing literature regarding AIML and its applicability to stochastic modeling and exploring case studies.

Description: Read the August 2018 issue of Predictive Analytics and Futurism newsletter published by the Predictive Analytics and Futurism Section.

Description: The article recaps existing ideas for assessing credibility and describes questions remaining to be answered.

Description: Predictive models have disrupted the traditional underwriting process. In this session, we will review a decade in the life underwriting of a disruptor – the confluence of actuaries, underwriters and clinicians. In addition, perspectives of other stakeholders will be explored.

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