Description: The article provides an overview of the federal tax treatment of long-term care insurance contracts, including a brief history of the tax treatment of long-term care insurance, the requirements that must be satisfied in order to be treated as qualified long-term care insurance under the Internal Revenue Code, and a brief discussion of qualified long-term care combination products and chronic and terminal illness accelerated death benefits offered under life insurance contracts.

Description: The University of International Business and Economics (UIBE) in Beijing has been named a new SOA Center of Actuarial Excellence (CAE).

Description: The SOA and Milliman announce the completion of the first certificate program focused on measuring and managing climate risk for actuaries. The Climate Change Risk Certificate Program pairs the risk management acumen of actuaries with the interdisciplinary expertise necessary to manage the complexity of climate risk.

Description: The summary and introduction of an SOA research paper that explores valuable insights and recommendations for insurance companies considering entering the market of commercial long-term care insurance (LTCI) in the Asia-Pacific, based on individual health status.

Description: A news release announcing the winners of the 2024 Student Research Case Study Challenge.

Description: Leveraging advanced technologies like Generative AI is essential for insurers looking to compete and drive business growth. In this high-level webcast, we discuss the transformative potential of Generative AI in actuarial work and how it empowers actuaries to become more efficient and effective.

Description: Actuaries historically modeled new launches in pharmaceuticals by anticipating the expected change to the market basket. This became more complicated with the recent launches of gene and cell therapies as they address rare diseases. Rare conditions have low total member volume to study and some do not currently have a diagnosis code to identify them within claims data. Addressing this modeling challenge has been growing more important in the recent years with the number of therapies launching. What has the health care industry, and more specifically health care, done to enhance modeling and how should this be altered for the future? Additionally, historic modeling has sometimes incorporated a level of direct medical treatment cost offsets where studies have shown lower treatment costs are achievable. Can gene and cell financial modeling include cost offsets as well? And if so, what are suggested precautions or limitations to this effort?

Description: Renal disease is a very heterogenous medical condition whose end state is dialysis, a recurring cost intensive medical condition. Dialysis cost is one of the major medical cost drivers in USA. Insufficient and improper care management in the early stages of CKD (chronic kidney disease) leads to early incidence of end stage renal disease (ESRD) among CKD patients which not only leads to high medical costs, but also reflects poor health quality.

Description: This is a paper from the session on the Asia at the January 15-18, 2023, 2023 Living to 100 Symposium in Orlando, Florida.

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.