Demonstrates a method to estimate tail factors in loss projections, suggesting improved accuracy in predictions.
This paper proposes a method to derive paid tail factors using incurred tail factors and historical payout patterns. Traditionally, a ratio of paid-to-incurred losses—and its reciprocal, the conversion factor—may be used to convert payments at a specific maturity to incurred losses, prior to attaching an incurred tail factor. The implied paid tail factor would be the product of the incurred tail factor and the selected conversion factor. However, relying on averages of historical ratios of paid-to-incurred losses for conversion may lead to unreasonable ultimate loss predictions. Shepard’s method of inverse-distance weighting provides a distribution-free prediction of the conversion factor, utilizing historical payout patterns that most closely resemble the year being projected to the point of tail attachment. This application should more reliably incorporate information from case reserves when deriving implied paid tail factors. In this paper, the application of Shepard’s method is compared to traditional conversion factor approaches (using various averaging techniques). In addition, the theoretical basis for the method and an example of the potential impact on ultimate loss projections are presented. Address for Correspondence: devanagriffith@gmail.com
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Devan Griffith (2020) studied this question.
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