Description: Prepared for the Society of Actuaries by STATLAB at the University of Western Ontario, this report contains the results of a cash flow testing, ‘CFT,’ software survey performed in 2004. The results were based on the responses of 110 life insurance companies in the U.S. and Canada. The goal of the survey was to produce a report that will serve as a reference for comparing the available CFT packages and lead to better software and modeling techniques. CFT refers to analysis which is used to support both the Asset Adequacy Analysis for the Actuarial Opinion for U.S. companies, and the ALM Provision for Adverse Deviations in applying the Canadian Asset Liability Method to determine reserves for Canadian companies.

Description: This paper suggests that using the entire runoff triangle to keep a tail on the runoff curve was not necessary, and that doing so was actually a disadvantage if group medical and dental claim payment patterns changed over the period being used. An alternative was presented. From Actuarial Research Clearing House 1993, VOL. 3.

Description: The purpose of this paper is to explain several actuarial-demographic-statistical techniques and show their application in medical investigations. Actuarial Research Clearing House 1979, VOL. 1

Description: This paper reviews recursive formulas for aggregate claim distributions. Followed by a submitted discussion paper

Description: This people provides a derivation of continuous and curtate inequalities of life contingent functions and shows how the proofs of the continuous inequalities are of an entirely different nature from the usual proofs for the curtate inequalities Followed by discussion papers submitted by several authors

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: Shiu derives two formulas for calculating the probability of eventual ruin in a collective risk model. This paper implements one of the formulas by incorporating an algorithm to reduce round-off error due to convolution. It gives the results of the programs for some claim distributions.

Description: This paper discusses a mixed lognormal estimator of a risk distribution. Using the observed claim frequencies of a portfolio, the author presents a continuous nonparametric estimator of the risk distribution that reproduces some of the empirical moments and converges uniformly. The estimator that is investigated is a mixture of log-normal distributions whose parameters are calculated by considering the determinants of certain moment matrices. From Actuarial Research Clearing House 1993, VOL. 1.

Description: This paper compares percentile estimates of a large number of cash flow testing scenarios, where only a very small number fall in the ruin tail, by parametric and non-parametric methods.

Description: The purpose of this paper is to understand characteristics of a household that drive life insurance demand with more sophisticated analytical techniques. The analysis is based on the Survey of Consumer Finances data, a probability sample of the U.S. population. Household demand of two types of insurance, term life insurance and whole life insurance, is examined jointly. We model both the frequency and the severity of demand for insurance building on the work of Lin and Grace 2007 by using covariates that they developed.