Hostname: page-component-78c5997874-xbtfd Total loading time: 0 Render date: 2024-11-17T15:14:42.773Z Has data issue: false hasContentIssue false
  • English
  • Français

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: [email protected]
Get access Rights & Permissions [Opens in a new window]

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
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

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

de Alba, E. (2002). Bayesian estimation of outstanding claims reserves. North American Actuarial Journal, 6(4), 1–20.CrossRefGoogle Scholar
de Alba, E. (2006). Claims reserving when there are negative values in the runoff triangle: Bayesian analysis using the three-parameter log-normal distribution. North American Actuarial Journal, 10(3), 45–59.CrossRefGoogle Scholar
de Alba, E., Nieto-Barajas, L. (2002). Claims reserving: A correlated Bayesian model. North American Actuarial Journal, 6(4), 1–20.CrossRefGoogle Scholar
Denuit, M., Marechal, X., Pitrebois, S., Walhin, J.-F. (2007 ). Actuarial Modelling of Claim Counts: Risk Classification, Credibility and Bonus-Malus Systems. John Wiley & Sons, England.CrossRefGoogle Scholar
England, P., Verrall, R. (2006). Predictive distributions of outstanding liabilities in general insurance. Annals of Actuarial Science, 1(2), 221–270.CrossRefGoogle Scholar
König, B., Weber, F., Wüthrich, M. (2011). Prediction of disability frequencies in life insurance. Zavarovalniski horizonti, 7(3), 5–23.Google Scholar
Ntzoufras, I., Dellaportas, P. (2002). Bayesian modeling of outstanding liabilities incorporating claim count uncertainty. North American Actuarial Journal, 6(1), 113–128.CrossRefGoogle Scholar
Peters, G., Shevchenko, P., Wüthrich, M. (2009). Model uncertainty in claims reserving within Tweedie's compound Poisson model. ASTIN Bulletin, 39(1), 1–34.CrossRefGoogle Scholar
Schriek, K., Lewis, P. 2010. The link between disability experience and economic conditions in South Africa. Presented at the International Congress of Actuaries 2010 Conference. Download from http://www.ica2010.com/docs/02_final_paper_Schriek,_Lewis.pdfGoogle Scholar
Scollnik, D. (2001). Actuarial modeling with MCMC and BUGS. North American Actuarial Journal, 5(2), 96–124.CrossRefGoogle Scholar
Spiegelhalter, D., Best, N., Carlin, B., van der Linde, A. (2002). Bayesian measures of complexity and fit. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 64(4), 583–639.CrossRefGoogle Scholar
Verrall, R. (2004). A Bayesian generalized linear model for the Bornhuetter-Ferguson method of claims reserving. North American Actuarial Journal, 8(3), 67–89.CrossRefGoogle Scholar