Description: A look at the near future and far future of various elements of Actuarial Models as defined through ASOP 51. What is driving the complexity for inputs, calculations, and outputs. Howe will actuaries handle these challenge?

Description: All things considered, caution needs to be applied to the use of so-called “standard” mortality tables. Sharpening up these blunt estimates by using individual assumptions reveals material differences in the structure of longevity, both between plans and within plans.

Description: Review of non public options to finance care including personal savings, revers mortgages, family care and private insurance.

Description: Provides an update, as of September 2022, on Financial Reporting Section sponsored research projects in process and those recently completed.

Description: Article describing content and key takeaways from experience completing the SOA PA Certificate

Description: An overview of bias and fairness in machine learning models, as they apply to use cases in life insurance.

Description: The Society of Actuaries announces the release of a new report that will provide a resource for the insurance industry to learn about image recognition technology. Authored by Kailan Shang, the report explores the current status of image recognition technology, models for image recognition, and various possible applications of image recognition to insurance.

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: The introduction and effective application of US GAAP LDTI have increased the scrutiny of those reviewing the updated financial results. That is because LDTI has resulted in significant changes in actuarial reserving and deferred acquisition cost (DAC) models for long-duration contracts, including significant changes to data, assumptions and required disclosures. In light of the changes, greater reliance has been put on companies’ model risk management (MRM) teams and model validations to assess the conceptual soundness and accuracy of their companies’ actuarial models and to assess that the underlying data and process utilized are suitable and appropriate. This article covers a brief background on model validation, walk through a sample LDTI-focused model validation framework/test plan, then provide insights on common LDTI-related validation observations based on the authors' prior validation experience.

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.