Description: With freezing and termination of DB plans, there is a growing void in retirees' retirement planning that can best be solved by annuities. The presenters will discuss different ways that annuities can be used to provide retirement income in DC plans. They will also cover industry trends and the challenges of associated with adding annuities within DC plans

Description: This session will explain how, by applying his or her educational background and business experience, an actuary can quickly learn the basics of data science and perform the important modeling work of insurance.

Description: The speakers will discuss the replication of long-term options, including a discussion of issues such as liquidity, transaction costs, slippage, impact of policyholder behavior, and machine learning algorithms to improve hedge effectiveness.

Description: The speaker will discuss the training of neural networks to compute future Greeks of liabilities (or options) without the use of nested stochastics.

Description: Some new variable and index-linked annuities offer simplified guarantees with limited downside protection; the policyholder “pays” for this protection with a limited upside. These products effectively provide policyholders access to an equity index with an option pass-through. This new direction blurs the line between more traditional variable annuity and fixed indexed annuity products. This session will discuss these and other similar product innovations, including some interesting regulatory, accounting, and risk management considerations.

Description: Actuaries understand the technical benefits of converting their models to a modern actuarial system, such as new capabilities and upgraded technology. This article highlights additional, non-technical benefits that also come with model conversion. These benefits include advancements in attitudes and capacities among the team and across the company.

Description: Uncertainty of a predictive model is a fact of life that many insurers could be overlooking at their peril without a framework for assessing it. The article provides a framework to understand the prediction uncertainty, which can be critical for the insurance operations using predictive models. Coin toss example explains model uncertainty and randomness inherent in making predictions to the number of heads expected. A mortality analysis case study illustrates how the Bayesian methodology can be used to develop the prediction uncertainty. In particular, the article shows that the Bayesian framework is a way to combine historical data and actuarial judgment, and directly address the model uncertainty through its posterior distribution.

Description: The current coronavirus pandemic has caused a number of challenges for life insurers and this article summarizes the operational challenges, namely in two areas. First, the article will discuss the challenges companies are facing to collect traditional underwriting evidence and potential short-term solutions used to overcome these limitations. Second, the actions companies are taking to alleviate the financial difficulties customers may have paying premiums will be addressed.

Description: The February/March 2014 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.

Description: The June/July 2014 edition of The Actuary magazine—the Society of Actuaries’ flagship publication.