Description: Provides a how-to session on modeling assets and liabilities in the Valuation Actuary's work to comply with the Standard Valuation Law. Comparisons of the methods discussed are occasionally made with the requirements of New York Regulation 126. Session 12 of the 1991 Valuation Actuary Symposium.

Description: 2011 SOA Enterprise Risk Management Symposium, Chicago. This paper suggests the use of a policy event-based loss estimation method using expert input and simulation for forecasting long duration expenditures: that is to say, there is an efficient time, which is random and observable to replace a physical asset.

Description: This paper studies the tail probability of discounted aggregate claims in a continuous-time renewal model. For the case that the common claim-size distribution is subexponential, the authors obtain an asymptotic formula, which holds uniformly for all time horizons within a finite interval. Then, with some additional mild assumptions on the distributions of the claim sizes and inter-arrival times, the authors further prove that this formula holds uniformly for all time horizons.

Description: Producing a crystal-clear balance roll-forward on time, obtaining a fresh model output the first time or providing model results for your business partners with a tight turnaround all depend on one thing: how fast the model engine runs. Authors explored various reasons behind significant computational power consumption, and discussed different ways to speed the computational process such as in-force population compression, model use case consolidation, code simplification and streamlining, and infrastructure automation, etc.

Description: The purpose of this paper is to present to the actuarial profession a stochastic investment model which can be used for simulations extending for many years ahead. Discussed in the paper are the general reasons for choosing the style of model, the general model and how to use it, the assumptions and the sensitivity of model to the assumptions made and the possible applications in the investment and actuarial fields.

Description: Commentary on practical observations resulting from constructing and running Economic Capital models. Possible standardization of assumptions and result interpretation are morphing even though use of E.C. models has now been around for years.

Description: This article is the first installment of a three-part series that aims to provide an overview of ESGs and will focus on the general motivation for stochastic modeling, its advantages and its limitations. Future articles will further break down the key factors of ESGs and the application of these factors to better understand the Academy Interest Rate Generator (AIRG).

Description: This paper proposes a model for the incurred but not reported - IBNR- claims of an insurance company. This model will be fit to third party automobile bodily injury claims for which the months and years of occurrence of the accident are available. From the Actuarial Research Clearing House 1990 VOL. 1

Description: This paper represents a brief progress report on research, being sponsored by the Casualty Actuarial Society and the Society of Actuaries, in the area of modeling of economic series. In particular, research is being undertaken to provide a foundation for the actuarial community’s modeling of a variety of economic variables, including interest rates, equity returns, inflation, unemployment rates, and real estate price levels. The specific objectives of this research are to provide a summary of the literature in the area of economic scenario modeling, identify data sources and methodologies in this area useful to the actuarial profession, and produce working software for economic modeling, including appropriate documentation, to be made available to the general actuarial community in order to allow actuaries to use and build upon this research. From Actuarial Research Clearing House 2004, Vol. 1.

Description: This panel discussion considers some of the approaches, techniques and problems in the development of corporate models and assumptions. The pros and cons of buying versus developing models was discussed and the use of deterministic versus stochastic models was addressed as well.