Description: The presenters will share information about: -Insights into causes of death through the use of predictive models, based on a reinsured U.S. life portfolio, using logistic regression models to understand three main causes of death: cancer, heart and external causes; -Opioid abuse is a widespread phenomenon with drug-related mortality rates rising steeply in the U.S. over the past two decades. But what does the most recent data tell U.S. about the outlook for Opioid-related mortality?; -'Deaths of despair' have been publicized as a cause for the poor performance of U.S. mortality in recent years. The presenters will be looking at the different causes under this label, their evolution and explore the drivers behind them.

Description: The presenters will explore policyholder experience data for long-term products, risks of over-fitting data in developing behavioral models, and ways to mitigate these risks and develop a sustainable and coherent framework to translate complex policyholder behavior experience data to behavioral models using company- and industry-level data. At the conclusion of the session, attendees will be able to: - Identify key drivers of policyholder behavior for long-term product - Understand the risks of over-fitting data and a false sense of precision in developing behavioral mode - Understand techniques that can be used to mitigate these risk

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

Description: This session will review limited fluctuation credibility, and how to apply that approach to a GLM. Alternative credibility approaches through the lens of ASOP 25 will also be discussed.

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

Description: The Delphi method is a non-quantitative forecasting approach that is most useful when other forecasting techniques appear to have limited value. The Society of Actuaries (SOA) has had some impressive results from Delphi studies (even quoted in the Wall Street Journal for their uncanny accuracy on long-range predictions). Attend this session to learn about this effective, yet underutilized method of leveraging the wisdom of crowds.

Description: Actuarial tools now include both open and closed source software; both need a strong model governance framework to mitigate potential sources of model risk and external threats. This presentation will discuss how to develop, install and monitor a model governance framework to safeguard company modeling assets and intellectual capital.

Description: If you’re looking for a quick and easy way to begin exploring data analytics, machine learning, and AI, Microsoft has created a number of Data Science Virtual Machine images which include many of the most popular ML/AI tools pre-installed. In this presentation, we will start from scratch and demonstrate how to get onto the Azure cloud, fire up and connect to a Data Science VM, upload data, and train a machine learning model. While this presentation will use Microsoft’s Azure cloud, many of the concepts should be directly applicable to AWS or GCP.

Description: This is a case study session where the speakers will describe a project where a major health system converted its provider distinct reimbursement (i.e., separate physician IPA and hospital capitation) to an integrated reimbursement involving global capitation. The session will discuss the strategic issues considered by the parties and how they evaluated them in their decision process. This session will provide attendees an example of how to approach this type of decision.

Description: The advent of machine learning algorithms has taken predictive analytics and risk scoring to a new level. From gradient boosting machines to k-nearest neighbors regression, the use of these techniques has gained significant traction in healthcare - including health systems like the Cleveland Clinic. This session will discuss the use of predictive analytics to go beyond just assessing the risk of a patient, and instead focus on prescribing a specific intervention of care. In practice, the recommendation of a care plan goes beyond just attributing a score to a patient. It provides physicians and care coordinators the most probabilistic options - e.g. referral to social worker, depression screening, weight-loss program - for positively impacting a patient's future healthcare outcome.