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Bayesian prediction of disability insurance frequencies using economic indicators

Published online by Cambridge University Press:  30 April 2012

C. Donnelly  and
Mario V. Wüthrich
C. Donnelly*
Affiliation:
Heriot-Watt University, Edinburgh, UK
Mario V. Wüthrich
Affiliation:
ETH Zurich, RiskLab, Department of Mathematics, Switzerland
*
*Correspondence to: Catherine Donnelly, Department of Actuarial Mathematics and Statistics, and the Maxwell Institute for Mathematical Sciences, Heriot-Watt University, Edinburgh EH14 4AS, United Kingdom. Email: C.Donnelly@hw.ac.uk
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Abstract

We use economic indicators to improve the prediction of the number of incurred but not recorded disability insurance claims, assuming that there is a link between the number of claims and the chosen economic indicators. We propose a Bayesian model where we model the claims development in three directions: along incurred periods, recording lag periods and calendar periods. A stochastic model of the economic indicators is incorporated into the calendar period development direction. Thus we allow for the impact of the economic environment on the number of claims. Applying the proposed model to data, we illustrate how the inclusion of economic indicators affects the prediction of the number of incurred but not recorded disability claims.

Keywords

Bayesian modelCalendar periodClaims predictionCredit spreadsDisability insuranceEconomic indicatorsPrediction uncertaintyStochastic modelUnemployment

Information

Type
Papers
Information
Annals of Actuarial Science , Volume 6 , Issue 2 , 23 August 2012 , pp. 381 - 400
Copyright
Copyright © Institute and Faculty of Actuaries 2012

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