Description: From a session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Teaching session covering the development of realistic liability models for use in asset adequacy analysis, asset/liability management, pricing/repricing, financial reporting or other corporate purposes. The primary focus is modeling issues for variable product features, such as minimum living or death benefit guarantees on both variable life and annuities, annuity death benefit enhancements, and variable immediate annuities. Topics include: • Analysis of the special risks posed by these products • Selecting realistic dynamic assumptions • Techniques used in modeling these products • Scenario testing and result presentation to best communicate risks

Description: The focus of the webcast on Modeling Long–Term Medical Trends for Valuation Purposes was a discussion of the underlying methodology of the model, a walk through of the actual model, and a review of the considerations for its practical usage by actuaries. The running time of this video is 1 hour and 3 minutes. It is a presentation of slides without audio.

Description: From a session at the 2000 Valuation Actuary Symposium held in Washington DC, September 14-15, 2000 Discussion of financial modeling considerations including: • Model platforms • Model structure • Static and dynamic model validation techniques • Data integrity

Description: From a teaching session at the 2000 Valuation Actuary Symposium held in Washington DC, September 14-15, 2000 Discussion of realistic liability models for use in asset adequacy analysis, asset/liability management, pricing/repricing, financial reporting, or other purposes.

Description: Presented at May 1996 Spring Meeting. This session offers a retrospective and prospective look at the development of actuarial pricing models and technology tools.

Description: From a session at the 2000 Valuation Actuary Symposium held in Washington DC, September 14-15, 2000 In this session the panelists discussed the issues related to the actuarial aspects associated with the demutualization process. The issues discussed included: • Developing historical and prospective assumptions • Aligning the models used in the company’s philosophy regarding dividend determination and pricing • Creating experience assumptions when less-than-perfect data exist • Determining who gets what • Complying with actuarial and accounting standards

Description: Panel discussion of alternative approaches to the design of reserve standards, to include those topics discussed in several recent papers and committee reports.

Description: Panelists of this teaching session discuss: [1] policyholder and company behavior and its impact on model and assumptions, [2] model purpose and structure, data collection, and behavior models, and [3] the modeling process, including objectives, considerations, constraints, and validation. Session 10 of the 1996 Valuation Actuary Symposium.

Description: An increasing need exists for the actuary to provide ranges and frequency distributions of possible values instead of providing only mean values. This discussion will cover: projections of asset experience under various economic scenarios, a practical application of profit analysis using scenarios and a deterministic model, exploring possible values by means of stochastic modeling, and a description of the new life contingencies textbook's stochastic approach and application to some practical population and census problems. From Record of the Society of Actuaries 1981, Volume 7, No. 4.

Description: From a session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Actuarial models must both accurately portray the assets and liabilities in question and produce relevant and meaningful projection results. The panel discusses important considerations in: • Proper organization of a model • Structuring of a model for an intended purpose i.e., pricing versus financial reporting, statutory versus GAAP accounting • Static and dynamic model validation techniques • Data integrity