Description: This article provides a very high level overview of accelerated underwriting programs and their history in the US marketplace. It then discusses setting up an actuarial control cycle for such products and some items related to risk management that are helpful in this setting. Pros and cons of retrospective studies, random holdouts, targeted holdouts and post issue analysis are discussed. A mathematical example of how to estimate the mortality impact of such programs from early emerging experience is provided.

Description: A data format for mortality tables along with applications.

Description: This article details different methods for calculating mortality impact associated with new underwriting programs. A common simplified calculation is compared and contrasted with two first principles approaches. The strengths and weaknesses of both approaches are discussed.

Description: Milliman was engaged by the SOA to conduct two Accelerated Underwriting (AU) surveys, one of direct companies and another of reinsurers. The surveys explored actual results from 2019–2021 and expected results from 2022.

Description: Deep learning neural network applied to experience analysis for post-level term lapse and mortality.

Description: Future mortality improvement has been a common assumption in life insurance and annuity pricing and forecasting for many years. However, experience over the last decade suggests this might be an assumption that merits reconsideration in the United States. This article will take a closer look at factors that impact mortality improvement trends and discuss why insurers may want to reevaluate product designs to better manage the associated mortality risk. We then introduce a product idea with this in mind, where premiums are based on a life expectancy index and insurers share the risk (and opportunity) or mortality improvement with policyholders.