Description: As the Valuation Manual continues to evolve and PBR standards for additional products are drafted and incorporated, it will become increasingly important for companies to understand where the requirements are consistent across products, as well as how they differ. This session will scan the life (VM-20) and annuity (VM-21, VM-22) PBR standards across the Valuation Manual to compare and contrast key requirements. Attendees will understand where common methods and techniques can be used across products and platforms. Attendees will also be better positioned to consider assumption and margin setting, asset and derivative modeling, and model efficiency techniques for all types of principles-based valuations. Additionally, this session will profile specific challenges that can arise when actuaries use models to project PBR reserves at future dates for internal planning, pricing, and projections across life and annuity businesses.

Description: 2002 Valuation Actuary Symposium, Lake Buena Vista, FL. In this teaching session the instructor explained how to scrutinize model results and use models to make strategic decisions. Specific topics included validation of asset models, modeling considerations for derivatives and assets with embedded options, using models to assist with portfolio management, and using models to improve portfolio yields and realized product spreads.

Description: Asset cash flow modeling and asset assumptions are growing in importance with PBR especially considering the low interest rate environment. The Academy’s Life Practice Council and Life Valuation Committee have formed a Low Interest Rate Asset Adequacy Testing Task Force which has conducted an industry survey to raise awareness and summarize the actuarial best practices for financial reporting actuaries practicing in today’s very low interest rate environment. As the scrutiny on the asset side ratchets up, actuaries must consider how best to develop the asset assumptions as well as model the reinvestment and disinvestment strategies. Coherent assumptions and modeling practices across modeling exercises are expected while respecting the purpose of each calculation.