Description: This paper introduces density estimation for functions of observations. The nonparametric density estimates are introduced and certain computational issues are discussed and a central limit theorem for the estimator is provided. From Actuarial Research Clearing House 1993, VOL. 1.

Description: In a product warranty, the renewal function is the expected number of failures in a specific warranty duration. To estimate the renewal function, cross-sectional regression data is assumed to be available and the data is assumed to be semiparametric. In this article, the observations are a11owed to be residuals from a complex regression model. It is observed that estimation can be accomplished using reasonable models for the contracts and data collection. From Actuarial Research Clearing House 1992, VOL. 2.

Description: This paper provides an overview of deductible ratemaking , and the pros and cons of various approaches under different parametric models are compared

Description: Presented at October 1986 Annual Meeting. This session discussion is about the use of simulation, or Monte Carlo, techniques to analyze complex insurance models such as estimating reserves, solvency considerations, and estimation of mortality and distribution of aggregate losses with the aid of a computer program

Description: Summary of the SOA's Annuity Valuation with Dependent Mortality research report which examines the standard industry practice of assuming independent lives for insurance products that cover multiple lives.

Description: This summary is intended to provide the pension actuary with guidance in interpreting and using the termination and retirement information in the 2003 SOA Pension Plan Termination and Retirement Study. The tables in the study were developed based on 1.7 million life years of data from 112 plans collected primarily from actuarial consulting firms for the period 1995 – 2000.

Description: This paper addresses the extension of the theory of life contingencies to a stochastic interest environment and its application to solvency valuation and surplus. A discussion of the paper follows. From Transactions of Society of Actuaries 1990, Vol. 42.

Description: This paper focuses on the fact that life and annuity reserves that are determined from discounted case flows mask the dynamic nature of interest rates. To study this effect in a stochastic interest environment, the authors look at a change in discounted reserves. By looking at the appropriate measure of change, the paper explores potential short-term consequences of changes in the interest environment.

Description: Automobile insurers classify the risks that they underwrite in order to subdivide the portfolio into classes of risks with similar profiles. While some insurers may have sufficient historical data, several others may not have significant volume of experience data in order to produce reliable claims predictions to help enhance their risk classification systems. A database containing a pooled experience of several insurers thereby helps to produce a more fair, reliable, and equitable premium structure for all risks concerned. This paper uses multilevel models to analyze the data on claim counts provided by the General Insurance Association of Singapore, an organization consisting of most of the general insurers in Singapore. The multilevel nature of the data is due to the following: a certain vehicle is observed over a period of years and is insured by a particular insurance company under a certain 'fleet' policy. The authors show how intercompany data lead to a priori premiums and a posteriori corrections to these initial premiums. Specific focus is made in understanding the intercompany effects using various count distribution models [Poisson, negative binomial, zero–inflated and hurdle Poisson]. The performance of these various models is compared the authors also investigate how to use the historical claims of a company, fleet and/or vehicle in order to correct for the premium initially set.

Description: This abstract describes a paper that introduces KDBINTMTM (Knowing, Doing, Being, Inspiring, and Networking), the framework in how it is being defined, and a plan to measure success for actuarial programs.