Browse Research
Viewing 126 to 150 of 7690 results
2019
CAS E-Forum, Summer 2019 Featuring a CAS Research Working Parties Report
2019
The NAIC RBC Formula treatment of line of business (LOB) diversification (referred to in this paper as the CoMaxLine% Approach) is very different from the Solvency II Standard Formula treatment.
2019
Motivation Application of the Shane-Morelli method in practice for multiple reserve reviews revealed potential areas of refinement.
Method A theoretical examination of curves best used to develop workers’ compensation tail factors resulted in a proposed enhancement to this part of the original methodology.
2019
CAS E-Forum, Spring 2019 Featuring CAS Research Working Parties' Reports
2018
As the level of competition increases, pricing optimization is gaining a central role in most mature insurance markets, forcing insurers to optimize their rating and consider customer behavior; the modeling scene for the latter is one currently dominated by frameworks based on generalized linear models (GLMs).
2018
Composite distributions have well-known applications in the insurance industry. In this paper, a composite exponential-Pareto distribution is considered, and the Bayes estimator under the squared error loss function is derived for the parameter q, which is the boundary point for the supports of the two distributions.
2018
Misrepresentation is a type of insurance fraud that happens frequently in policy applications. Due to the unavailability of data, such frauds are usually expensive or difficult to detect. Based on the distributional structure of regular ratemaking data, we propose a generalized linear model (GLM) framework that allows for an embedded predictive analysis on the misrepresentation risk.
2018
When predictive performance testing, rather than testing model assumptions, is used for validation, the need for detailed model specification is greatly reduced. Minimum bias models trade some degree of statistical independence in data points in exchange for statistically much more tame distributions underlying individual data points.
2018
Predictive modeling is arguably one of the most important tasks actuaries face in their day-to-day work. In practice, actuaries may have a number of reasonable models to consider, all of which will provide different predictions. The most common strategy is first to use some kind of model selection tool to select a “best model” and then to use that model to make predictions.
2018
This paper advocates use of the generalized logarithmic mean as the midpoint of property catastrophe reinsurance layers when fitting rates on line with power curves. It demonstrates that the method is easy to implement and overcomes issues encountered when working with usual candidates for the midpoint, such as the arithmetic, geometric, or logarithmic mean.
2018
CAS E-Forum, Summer 2018
Featuring the report of the CAS Working Party on Sustainable ERM (SERM)
2018
Actuaries have devised numerous methods for interpolating annual evaluation loss development factors (LDF) to arrive at quarterly evaluation factors. Not all of these work as well as might be hoped. Some introduce oscillations not found in the original factors. Many lead to IBNR projections that move erratically or have blips that are hard to explain.
2018
CAS E-Forum, Spring 2018-Volume 2 Featuring Ratemaking Call Papers, Climate Change Call Papers and three Independent Research Papers
2018
CAS E-Forum, Spring 2018 Featuring a report of the CAS Automated Vehicles Task Force and one Independent Research Paper
2017
Purpose and Intended Result: This research paper is intended to fill the void in the currently available actuarial literature related to information required by the reinsurance underwriter but often lacking when pricing property per risk coverages worldwide.
2017
I present evidence for a model in which parameters fit to the severity distribution at each report age follow a smooth curve with random error. More formally, this is a stochastic process, and it allows us to estimate parameters of the ultimate severity distribution.
2017
Given a Bayesian Markov chain Monte Carlo (MCMC) stochastic loss reserve model for two separate lines of insurance, this paper describes how to fit a bivariate stochastic model that captures the dependencies between the two lines of insurance. A Bayesian MCMC model similar to the Changing Settlement Rate (CSR) model, as described in Meyers (2015), is initially fit to each line of insurance.
2017
Bootstrapping is often employed for quantifying the inherent variability of development triangle GLMs. While easy to implement, bootstrapping approaches frequently break down when dealing with actual data sets. Often this happens because linear rescaling leads to negative values in the resampled incremental development data.
2017
In property-casualty insurance ratemaking, insurers often have access to external information which could be manual rates from a rating bureau or scores from a commercial predictive model. Such collateral information could be valuable because the insurer might either not have sufficient rating information nor the predictive modeling expertise to produce an effective score.
