Description: 1993 SOA Annual Meeting, New York. Insurance regulators commissioned a task force to develop cash-flow variability measurement standards. This session presented the recommendations of that task force and the relationship to cash-flow testing. Topics included: 1. The regulatory need and how the process was approached. 2. The types of CMO variability that the standards attempt to address. 3. A description of the scenario selection process that's used in this model. 4. The prepayment assumptions and the method to be used to collect prepayment data. 5. The relationship to cash-flow testing. 6. The regulators' reactions.

Description: Gather with members and non-members in the China actuarial community to discuss recent topics and related issues in areas such as macroeconomic sharing, pension, investment, product strategy, and more.

Description: Article Permutations And Computations by Moordhead in The Actuary, February 1979, Volume 13, Number 2

Description: The National Association of Insurance Commissioners (NAIC) is in the middle of a project to change the real-world economic scenario generator (RW ESG) prescribed for principle-based reserve and capital calculations. Explore a brief summary of the NAIC's RW ESG project and gain a general overview of RW ESGs. Learn how RW ESGs impact principle-based reserve and capital levels, their potential impact on life insurance companies and consider differences between the currently prescribed RW ESG and the proposed RW ESG.

Description: As the use of predictive models and novel datasets becomes more prevalent, a focus on consumer protection is being highlighted by regulators, ethicists, and industry insiders. Over time, increased rigor should and will be applied in model development and implementation. These issues are not new. Hundreds of individuals have worked on these issues in the laboratory, the board room, and the court room. The Civil Rights Act of 1964, Uniform Guidelines of the US EEOC, the Principles for the Validation and Use of Personnel Selection and other sources are intended to protect the rights of citizens and consumers and provide guidance to professionals in the development and use of decision-making tools. Drawing heavily on examples and parallels from psychology and employment practices as well as other disciplines, concepts such as model bias, fairness, adverse impact, disparate treatment and the like will be presented. Suggestions to ensure model validity, demonstrate model and data relevancy and minimize the potential for adverse impact to protected classes will also be offered. Each of these considerations will be linked to recent dialogue and concerns in the Life Insurance sector.