Description: 1998 Valuation Actuary Symposium. The speakers provided an overview of the GAAP accounting prior to SFAS 133, an example of that guidance and how the accounting works, the new GAAP guidance, the new SFAS 133, and deferred acquisition cost considerations for equity-indexed annuities.

Description: 1998 Valuation Actuary Symposium. The panelists addressed the practical implications of how to use value-at-risk in a real-life setting, risk-based surplus, and an update of the C-3 component of RBC. This session is a mix between the regulatory situation and quantitative analysis.

Description: 1998 Valuation Actuary Symposium. The speakers discussed dissecting and rearranging GAAP financials to provide more meaningful information and a comparison of the FAS 60 format of reporting earnings to a source-of-earnings format.

Description: 1999 Valuation Actuary Symposium, Los Angeles. This session provided a brief overview of a variety of financial reporting topics most of which were discussed in more detail at later sessions. Topics included: 1. NAIC Life and Health Actuarial Task Force developments and directions. 2. XXX Implementation Status. 3. New annuity valuation tables. 4. Statutory codification project. 5. AAA developments, including practice notes. 6. Unified Valuation Systems. 7. FASB and SEC developments. 8. Recent tax developments.

Description: This presentation is an open forum, session number 11OF, from the 2000 Valuation Actuary Symposium, held September 14-15 in Washington, DC. The panelists discuss recent Generally Accepted Accounting Principles [GAAP] developments and practical problems in implementing and maintaining GAAP systems. Topics include recent GAAP pronouncements and American Institute of Certified Public Accountants [AICPA] Insurance Companies Committee developments. Discussion from participants is included.

Description: From a session at the 2000 Valuation Actuary Symposium held in Washington DC, September 14-15, 2000 Technical discussion of asset modeling concepts and techniques

Description: Actuaries play pivotal roles in insurance companies, consulting firms and throughout the industry. With the ongoing accounting and regulatory changes, process and system modernization and the rapidly changing environment, actuaries frequently find themselves working in multidisciplinary projects with non-actuarial teams. In order to take on broader leadership roles, actuaries are often times expected to partner with and/or lead non-actuarial personnel. How can actuaries work most effectively with non-actuaries? A panel of industry leaders across different disciplines will share their perspectives on actuaries working with and building effective relationships with non-actuarial colleagues. The presenters will cover how actuaries add value in a non-actuarial world, what aspects actuaries can focus on to be more effective across disciplines and incorporate success stories as well as lessons learned. At the conclusion of the session, attendees will be able to: - Identify skills critical to working across disciplines with non-actuaries - Recognize characteristics that actuaries possess that enable them to build effective relationships, as well as the characteristics that detract from the ability to successfully partner with non-actuaries - Consider how existing skills can be further leveraged and new skills can be developed to enable productively and efficiencies across actuaries and non-actuaries

Description: The use of predictive models within life insurance has surged across underwriting, pricing, in-force management, and other areas. As the usage of these models have become the norm, carriers are beginning to face challenges around how to properly maintain and monitor these models. This session will cover how we evaluate, maintain, monitor and retrain models in production.

Description: In this presentation, the authors develop a stochastic generator for the generation of scenarios of the S & P 500 index, dividend yield, consumer price index, and U.S. Treasury yields. They first create a set of 'stylized facts' for these series. These in-sample statistical models are themselves not suitable for generation of scenarios for decision making, but instead are additional stylized facts that assist in model development. The 'best' statistical model according to standard statistical model selection criteria can easily lead to a model that is highly unsuitable for generation of scenarios for decision making. The authors develop a stochastic generator that is suitable for decision making under uncertainty. From Actuarial Research Clearing House 1997, Vol. 1.