Description: This article discusses the risks of retirement and how those risks impact attaining a secure retirement in a defined contribution world.

Description: This paper presents an approach to analyzing continuing care retirement community CCRC data and demonstrates the methodology by using data from a CCRC. From The Old-Age Crisis - Actuarial Opportunities - The 1996 Bowles Symposium, M-RS99-1.

Description: The results obtained during the last one-third of the research project and the project at whole are presented. The report only contains brief descriptions of the results which are placed in addendums and which are in reality copies of papers and a chapter of a book submitted for publication. Some theoretical and applied problems induced by the research are discussed.

Description: In this paper, we propose measures of the risk that the value of the liabilities becomes larger than the value of the assets, and this especially for insurance companies. We study probabilities of mismatching and a degree of mismatching in unsegmented and multidimensional models of the balance, in which we stress the influence of interest rates on the active and passive side of the balance.

Description: Learn about key actuarial and analytic tools and methodologies used by commercial health insurance to identify and quantify drivers of healthcare cost and utilization (including wasteful and low-value ones) and risks. Use case scenarios in which these tools and methodologies apply, such as underwriting, reinsurance, medical management for population health and chronic diseases, managed care contracting, insurance market reform, provider payment reform, etc., will also be covered. Experience from the U.S., China and other parts of the world will be shared.

Description: The key tasks of credit risk capital project under CROSS II mainly focus onL(1 )Adjustment of measurement framework; (2) Calibration of risk factors, including both credit spread risk and credit default risk;3)Introduction of concentration risk measurement; (4) Higher requirement on look-through rule.

Description: After the bid process, desk review, rebate reallocation, an “enjoyable” audit, and open enrollment; the Medicare plan year starts. Throughout the year, organizations find it pertinent to get an accurate picture of their Part D liability as reinsurance, LICS (Low Income Cost-Sharing) subsidy, and risk corridors are accrued. Attendees will learn about the basics of Part D accruals, how future accrual amounts are estimated based on patterns in the data, and how bid assumptions versus actual results impact plan sponsor profitability. We will also discuss financial statement treatment of these items. Real-life examples from bids to outcomes will be provided to enhance the discussion. Ultimately, attendees will come away with a deeper understanding how their bid assumptions play out, and how they can use Part D accruals to plan for future bid development.

Description: The academy generator is widely applied in actuarial practice. Initially confined to regulatory reserving, companies are increasingly using the AAA/SOA generator over an ever widening range of applications testing the limits of the academy generator's intended function. The session will give a brief overview of the academy generator and the asset classes it can be used to model. It will also analyze the statistical properties of the academy scenarios and discuss the scenarios relative to standard validation criterion. Some of the challenges that actuaries face in using this framework will be reviewed and options for addressing these challenges will be offered.

Description: The management of the investments of an insurance enterprise has undergone a considerable evolution since the pioneering work of Redington in the mid 20th century. Best practices have evolved to incorporate ever more complex insurance liabilities, expanding investment asset classes and global market opportunities. Strategic asset allocation (SAA), liability driven investing, and other robust optimization approaches form the core of the professional management of insurance company investments.

Description: The cloud inspires awe and fear in equal parts these days. There is a need to learn more, but there’s much information to learn and it may be difficult to know what to learn next. In this session, we’ll carve off a small corner of the cloud and make it your own. Setting up a Data Science Virtual Machine on Digital Ocean will be demonstrated. It’s the fastest way to get a data science development environment setup for your own use. Many of the topics and ideas covered will apply to almost all other cloud offerings. What use cases Digital Ocean is good for, and what use cases you should look elsewhere for, will also be discussed.