Description: Gross premium calculation methods may be arbitrarily separated into: a- Type 1 methods those which initially have commissions and other per cent of premium expenses in the denominator and b- Type 2 methods those which initially have commissions and other per cent of premium expenses in the numerator. The traditional Type 1 methods directly calculate the gross premium. The purpose of this paper is: 1. to present a Type 1 method of gross premium calculation which does the following: a Incorporates the cost of reinsurance into the gross premium calculation and may be shown as a level annual cost over the gross premium calculation period. b Calculates the effect on profit margins of a change in the retention limit without redoing the original calculation. c Calculates the premiums needed to break even e.g., amortize the initial investment in surplus at the end of each policy year as a by-product. d Calculates the profit or loss generated in each policy year or over any number of policy years for any gross premium without redoing the original calculation or first using a trial gross premium. e Directly solves for the gross premium that will produce any specified profit over any number of policy years without redoing the original calculation or first using a trial gross premium. f Directly solves for the premium that will produce a specified yield on surplus invested in new business by a flexible technique not first involving the use of the renewal net premium or any other preliminary gross premium. 2. to provide a mathematical definition of a financially meaningful average policy size which recognizes the cost of reinsurance. 3. to provide for mathematical definitions of common measures of profit, and the mathematical relationships between them. 4. To establish formulas expressing the effect of changes in various assumptions used in the gross premium calculation as a lev

Description: The purpose of this article is to revise the fuzzy regression portions of earlier studies and to discuss issues related to the Tanaka approach, including a consideration of fuzzy least-squares regression models. From Actuarial Research Clearing House, 2006.

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: Recent articles addressed the subject of fuzzy regression [FR] and the term structure of interest rates [TSIR]. Their approach relied on possibilistic regression. Although possibilistic regression has been used in many applications, it has a number of limitations, not the least of which is its nebulous relation to the least-squares concept. As an alternative to possibilistic regression, this paper uses fuzzy least square regression to investigate the TSIR.

Description: This paper investigates the implications of using the Basel II motivated Advanced Measurement Approaches as a method to assess operational risk capital charges for banks and insurance companies with regard to U.S. regulations. The AMA developed in the paper uses actuarial loss models complemented by the extreme value theory to determine the empirical probability distribution function of the aggregated capital charges in the context of various classes of copulas. From Actuarial Research Clearing House, 2006.

Description: This paper develops a formal framework to model the behavior of individual and small group health insurance policies in a competitive market. In this framework, anti-selective lapse is not assumed, but arises as a result of rational consumers seeking the best value in a competitive market where the premium rates are restricted by law. The authors obtain a model that addresses a number of fundamental questions which have not been fully answered previously, including the effect of price-induced anti-selective lapse on the mix of insureds in a block and the optimal renewal price to maximize the aggregate profit of a block.

Description: A statistical estimate is obtained for the total number of nodes in a three level tree. The number of nodes at each level is randomly distributed with certain pattern of distribution. Then the result is applied to the problem of estimating the LRA [logical record access] in data base design in a more refined way. It is more refined in the sense of using more information contained in the empirical distributions and being associated with a probability statement.

Description: This paper provides actuaries with background and scientific knowledge to understand global climate change and climate model projections for the 21st century.

Description: This paper presents a statistical and mathematical method to calculate Stop-Loss Premiums. It also includes a discussion of the paper. From Transactions of Society of Actuaries 1976, Vol. 28.

Description: This is a final report for a research project to create reference material that addresses the methods and techniques for quantifying margins for uncertainty in actuarial assumptions under a Principle-based statutory accounting framework.