Description: Presenters at session 9I of the Maui II Spring Meeting discuss credibility and why it should be important to the actuary. From the Record of the Society of Actuaries, Vol. 24, No. 2.

Description: This article provides an overview of the commonly used structural credit risk modeling approach that is less familiar to the actuarial community.

Description: Article from The Actuary, June 1983, volume no. 17, issue no. 6, that discusses eras in life contingencies theory. In the history of actuarial education on this continent, the subject of life contingencies has been successively presented to students in four major textbooks embracing almost exactly a century of instruction.

Description: The attached report presents the results of a survey conducted by the Society of Actuaries Mortality and Underwriting Survey Committee in July of 2008 under the following categories: 1. Modeling Mortality Risk. 2. Use of Reinsurance to Manage Mortality. 3. Retention / Large Case Management. 4. Catastrophe Reinsurance. 5. Mortality Concentration of Risk. 6. Catastrophic Bonds.

Description: This paper presents a proof using the general mean value theorem that under specified conditions, the insurance premium for complete protection against a specified loss will decrease with increasing wealth. From Actuarial Research Clearing House 1994, Vol. 1.

Description: This paper evaluates the current practice of operational risk management in the insurance sector. Operational risk is nothing new in insurance, but, because of regulatory requirements, companies have initiated computation of risk capital for their operational losses. The current effort to manage operational risk is not a naturally evolving phenomenon, and operational risk, in the Basel Committee on Banking Supervision’s Basel II definition, is unlikely to be a significant cause of insurers’ failure. In addition, the current Basel II definition of operational risk is not suitable for the insurance sector. Consequently, the invention of models and tools based on the definition is incomplete and illusionary. My findings are based on the analysis of dozens of interviews with insurance industry professionals. I demonstrate the way operational risk is quantified in practice, show that the result obtained from this computation is of littl e use in managerial decision making and propose a set of policy recommendations illustrating the characteristics of operational risk in insurance. This study can be used as a platform for launching dialogues to initiate fresh thinking about operational risk in insurance beyond the current artificial and narrow boundaries.

Description: This session at the 2003 Valuation Actuary Symposium discusses advanced modeling techniques. Focus is on advanced liability and asset modeling issues, model distinctions between types of variable annuity guarantees, stochastic mortality, stochastic-on-stochastic modeling, and alternatives to stochastic modeling.

Description: Actuarial models have always been an important tool for helping companies project future results and understand risks. As complex models have started to become critical components of the reporting and compliance processes, however, models have vaulted to new levels of importance—and of scrutiny. This has raised everyone’s interest in the management of models, and by implication, in their ability to control the inherent model risk. From Small Talk Newsletter, Issue 37, January 2012.

Description: Abstract for a paper that develops links between credibility theory in actuarial science and longitudinal data models in statistics. The paper demonstrates that many additive credibility models can be expressed as special cases of the longitudinal data model.

Description: 1993 SOA Annual Meeting, New York. This session was about what constitutes a good predictor for modeling. Topics included: 1. Size of model. 2. Lines of business. 3. Purpose. 4. Kinds of models. 5. Accuracy of model versus assumptions. 6. Presentation of results. 7. How to get credibility.