Description: Actuaries are leveraging predictive modeling and machine learning more and more as they strive to provide greater value to their stakeholders. Actuarial standards of practice provide guidance around modeling and data. The world has changed significantly over the last few years, so it is important these models be tested for fairness as well as any statistical biases. This article addresses some of the key issues actuaries need to be aware of as Corporations and society work through the responsible us of this technology and underlying data.

Description: Details on the Retirement Section Council and the direction we're moving for our members.

Description: Frequently Asked Questions about the SOA's University-Earned Credit (UEC) program.

Description: The paper demonstrates that the most popular rationalization for evolving glide paths is flawed and should be discarded. The paper also demonstrates that glide paths should generally evolve for investors that endeavor to optimize outcomes and reevaluate their portfolios regularly.

Description: The incoming E&R chair for the coming year reflects on past accomplishments of the E&R council, acknowledges with thanks contributors, and looks forward to continuation in the coming year.

Description: In this article, Aneesha Deshpande examines how Hagerty's complementary business models- specialty insurance and automotive lifestyle and membership services- are a result of a deep understanding of customer needs.

Description: President Roy Goldman speech at the SOA 2020 Virtual Annual Meeting & Exhibit.

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: This paper uses the ideal quasi-natural experiment of government-subsidized agricultural insurance program phased out in different regions of China since 2007 to study the effects and transmission mechanisms of the program on alleviating regional poverty using a multi-period Difference-in-Differences (DID) approach. Specifically, this paper identifies the causal effects on the incidence, depth and intensity of poverty among rural residents. The research has important policy implications. First, this paper uses the program as a case to provide a research paradigm to estimate effects of implementing policy instruments that combine markets and government mandates. Second, as common prosperity is now a government imperative, the research also provides insights into ways insurance can be used to hedge income risks, alleviate poverty and help achieve more equitable distribution. The paper has been published on WeChat account of Chinese Association of Actuaries on February 9, 2022. The full version has been published in CSSCI journal Insurance Research, issue 11, 2021.

Description: Subtitle: My real-life connection to (almost) every supplemental product Data is king, but maybe it should be dethroned once in a while so we can better understand the "why" behind the data.