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: This paper develops a parametric model for health care insurance claims using currently available software to fit parametric models to the data. Model selection is based on the Chi-squared goodness-of-fit test and a comparison of the empirical limited expected value function to parametric limited expected value functions. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This paper develops a parametric model for health care insurance claims to fit parametric models to the data. Model selection is based on the ChJ-squared goodness-of-fit test and a comparison of the empirical limited expected value function to parametric limited expected value functions. A copula function was used to model the bivariate portion of the data. From Actuarial Research Clearing House 1993, VOL. 3.

Description: This article discusses the reliance the banking industry placed on sophisticated mathematical models.

Description: In this paper several probability models for the random amounts of needed long-term care are explained, and one model is used to provide an alternate premium calculation method for certain long-term care coverages. From Actuarial Research Clearing House 1990, VOL. 2.

Description: The primary objective of the paper was to develop a straightforward method for constructing an interpolation formula of finite range with desired properties stipulated in advance. This paper had in view mainly the application to polynomial interpolation as used in actuarial work. Followed by 2 discussion papers submitted

Description: Risk adjustment in government regulated health plans has been around for over two decades. Yet the strategies for promoting risk score accuracy haven't varied much during that time. Most health plans, physician groups, and vendors promote chart reviews and/or in-home assessments as the primary vehicle for collecting data not perceived to be present in the routine claims submission and adjudication stream. We know that most organizations trying to coalesce encounter data from multiple sources often fail to ensure that all relevant data is ultimately submitted to CMS or a state Medicaid agency. Crucial data, often with significant financial value, frequently gets lost in the data pipeline, somewhere between the provider's billing system and the health plan and/or its vendors. Because 837-formatted data is difficult to read, it complicates payers and vendor’s abilities to track encounter data so that every service delivered to patients is credited to the applicable risk adjustment formula. It is incumbent upon successful risk-adjusted entities to be able to track encounter data, identify processes and/or vendors which may be mangling or losing data, in order to ensure that risk scores are sufficiently accurate to be compliant with plan sponsor requirements and to ensure appropriate revenue to the health plan or provider group.

Description: This paper analyzes the U. S. Treasury monthly interest rates from 1953 to 1992, and the daily rates from 1981 to 1992 for various forms of chaotic behavior. The primary analysis was in determining the Burst Exponent by the use of Rescaled Range Analysis. This paper also discusses other possible uses of Fractional Brownian Motion in Finance Theory, Macroeconomics, and Actuarial Science. From Actuarial Research Clearing House 1994 VOL. 1.

Description: This paper presents an introduction to collective risk theory. In collective risk theory one seeks to investigate directly the risk enterprise as a whole. Primary interest is focused not upon the gains, losses, or claims from individual policies but upon the amount of total claims or the total gain arising from all the policies in the portfolio considered. Followed by several discussion papers submitted.

Description: From a session at the 2001 Valuation Actuary Symposium, held in Lake Buena Vista, Florida, November 29-30, 2001 Teaching session covering the development of realistic liability models for use in asset adequacy analysis, asset/liability management, pricing/repricing, financial reporting or other corporate purposes. The primary focus is modeling issues for variable product features, such as minimum living or death benefit guarantees on both variable life and annuities, annuity death benefit enhancements, and variable immediate annuities. Topics include: • Analysis of the special risks posed by these products • Selecting realistic dynamic assumptions • Techniques used in modeling these products • Scenario testing and result presentation to best communicate risks