Description: According to the Actuarial Standards Board’s Actuarial Standard of Practice No. 49 (ASOP 49), actuarially sound Medicaid managed care capitation rates will include a provision for underwriting gain in order to provide compensation for the risks assumed by an MCO. However, there is no generally accepted method for quantifying underwriting gain in managed Medicaid capitation rates. This article discusses a new model developed to address this void and calculate underwriting gain. The model was developed by researching existing financial literature and performing a statistical analysis of industry data to build out a framework that can be leveraged to estimate underwriting gain.

Description: This is the forecasting tool for the Modeling and Forecasting Cause of Death Mortality by Socioeconomic Factors.

Description: This study explores the use of geospatial imagery and high-resolution image technology in the property and casualty (P&C) insurance industry, focusing on improving risk determination through accurate building location data. It introduces new methods like structure footprints and high-resolution elevation information to enhance underwriting, rating, and claims settlement. The study includes two case studies: one on flood risk in Hillsborough County, Florida, and another on wildfire risk in three California communities, demonstrating the significant impact of precise location and elevation data on risk assessment and insurance premiums.

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.

Description: Constant maturity credit default swaps [CMCDS] are useful as hedging tools. In intensity model approach, the default time is defined as the first arrival time of the Poisson process. From the market quotes of CDS forward rates and bonds, we are able to numerically compute the default probabilities. Approximating CMCDS price depends largely on CDS forward rates’ volatilities and their correlations. This paper implements the price algorithm based on Brigo’s work [2006]. Starting with current market data such as CDS forward rates and nondefaultable bond prices, the paper describes steps involved to obtain the price CMCDS. The paper demonstrates the impact of convexity on the CMCDS price structure.

Description: We derive formulas for calculating the premiums that should be charged on policies in a discounted cash flow model with tax reserves and required assets that are determined by regulation. We also determine the unique division of required assets into “reserves” and “capital” that allows the product profitability to be correctly evaluated. That is, the profit after capital charges is zero if the product achieves the return assumed in pricing. We illustrate the concepts using whole life insurance and guaranteed minimum death benefit examples.

Description: This is an abstract for a research paper that compares the generalized linear array model [GLAM] and Lee-Carter models by fitting them to Swedish mortality data. GLAM is presented as an alternative to Lee-Carter for modeling mortality by age and calendar year.

Description: This presentation illustrates a calibration model against 60 years of historical data using a pragmatic mixture of filtering, maximum likelihood and method of moments techniques, and compare the resulting model with interest rates in contemporary economic scenario generators.

Description: This abstract describes a paper that considers the identification problem for age-period-cohort models for a class of non-trapezoidal index sets.

Description: This abstract describes a paper that investigates model uncertainty arising from different ways of treating the operational loss data collection threshold.