Description: This paper is a sequel to Shapiro et. al. in that it discusses a similar role for CAI in topics specific to the text Actuarial Mathematics, by Bowers et. al 1986. The topics covered are the previous topics of actuarial notation, basic concepts, and what-if analysis, along with some new ideas for the presentation of stochastic models.

Description: The study of Employee Benefits has always been aided by using financial algorithms. During recent semesters, the Lotus 1-2-3 package Lotus has been introduced to students due to the explosion of its use in the business community. This paper will show how our students use Lotus to design a spreadsheet for computing minimum annual distributions from tax-sheltered plans.

Description: This paper presents an approach to analyzing continuing care retirement community [CCRC] data, and demonstrates the methods using data from a large CCRC. It is assumed that residents make transitions among a number of states that represent the levels of care required by residents. There is randomness associated with both the transition times and the states entered at these times. The model is conveniently characterized in terms of transition intensity functions, which represent the instantaneous rates of transition between pairs of states.

Description: In this paper, we introduce a family of leptokurtic symmetric distributions represented by the difference of two gamma variates. Properties of this family are discussed. The Laplace, sums of Laplace and normal distributions all arise as special cases of this family. We propose a two-step method for fitting data to this family. We develop a statistical test for goodness-of-fit and introduce a test of normality of the data. A simulation study is provided to illustrate the theory.

Description: It has been twenty years since DeWit 1982 first applied fuzzy logic FL to insurance. That article sought to quantify the fuzziness in underwriting. Since then, the universe of discourse has expanded considerably and now the FL methodologies include used fuzzy set theory, fuzzy numbers and fuzzy arithmetic, fuzzy inference systems, fuzzy clustering algorithms, fuzzy linear programming, fuzzy regression, and hybrids involving other soft computing technologies. This article presents an overview of these studies.

Description: This paper deals with how the credibility levels change based on this lack knowledge. Group insuraace models are used, bill some of tile techniques could apply to any insurance risk.

Description: This paper shows how discrete multivariate analysis or multidimensional contingency table methods may be applied to data arising in actuarial work. A brief introduction to the theory is followed by two detailed examples of its application. Finally, the concluding remarks indicate how the procedure could be incorporated into a complete rate-making procedure. This work was performed for the U.S. Department of Housing and Urban Development.

Description: As commodity markets evolve in tandem with advents in communications technology, the criticality of data management becomes a lynchpin of corporate success or failure. Advanced analysis on market movement can lead to substantive market gains, while an inability to assess risk in a timely fashion can hinder corporate responsiveness, stagnate growth or result in unmitigated risk. In essence, the old paradigm of data flow and management was severely limited by 1 the amount of readily available data, 2 the transmission capabilities for data, and 3 the costs of data storage and maintenance. Presented at 2010 Enterprise Risk Management Symposium, Society of Actuaries, April 12-15, 2010.

Description: Project portfolio risk management and risk analysis form one of the critical components of enterprise risk management. Organizations measure and analyze risks associated with projects, project portfolios, and programs. The important step of the process is quantitative risk analysis of project schedules using event chain methodology (ECM). ECM is a stochastic modeling technique for schedule risk analysis. All risks, including schedule and nonschedule-related risks, are assigned to a particular project and within this project to the particular activity or resource. Further, ECM allows one to model the relationship between project risks by defining risks that cause or trigger other risks. All risks and relationships between them will be presented on the project or portfolio Gantt charts using event chain diagrams. After risks are assigned to project and portfolio schedules, Monte Carlo simulation of the project schedule is performed. ECM simplifies complex risk analysis process.

Description: The purpose of this paper is to discuss computer application, the management of an insurance enterprise in an automobile insurance marketplace wherein a number of insurers compete for marketshare and profit. The paper begins with a description of the computer program next, a cursory description of the model is given then, the assumptions of the model are discussed next, potential future modifications are discussed and, finally, a prognosis is given.