Hostname: page-component-84b7d79bbc-dwq4g Total loading time: 0 Render date: 2024-07-28T10:34:53.805Z Has data issue: false hasContentIssue false
  • English
  • Français

A credibility method for profitable cross-selling of insurance products

Published online by Cambridge University Press:  23 September 2011

Fredrik Thuring
Get access Rights & Permissions [Opens in a new window]

Abstract

A method is presented for identifying an expected profitable set of customers, to offer them an additional insurance product, by estimating a customer specific latent risk profile, for the additional product, by using the customer specific available data for an existing insurance product of the specific customer. For the purpose, a multivariate credibility estimator is considered and we investigate the effect of assuming that one (of two) insurance products is inactive (without available claims information) when estimating the latent risk profile. Instead, available customer specific claims information from the active existing insurance product is used to estimate the risk profile and thereafter assess whether or not to include a specific customer in an expected profitable set of customers. The method is tested using a large real data set from a Danish insurance company and it is shown that sets of customers, with up to 36% less claims than a priori expected, are produced as a result of the method. It is therefore argued that the proposed method could be considered, by an insurance company, when cross-selling insurance products to existing customers.

Keywords

InsuranceCross-sellingProfitabilityMultivariate credibility
Type
Papers
Information
Annals of Actuarial Science , Volume 6 , Issue 1 , 16 January 2012 , pp. 65 - 75
Copyright
Copyright © Institute and Faculty of Actuaries 2011

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

Bailey, A.L. (1950). Credibility Procedures, LaPlace's Generalization of Bayes’ Rule, and the Combination of Collateral Knowledge with Observed Data. Proceedings of the Casualty Actuarial Society, 37, 7–23.Google Scholar
Brockett, P.L., Golden, L.L., Guillén, M., Nielsen, J.P., Parner, J., Perez-Marin, A.M. (2008). Survival analysis of a household portfolio of insurance policies: how much time do you have to stop total customer defection? The Journal of Risk and Insurance, 75, 713–737.CrossRefGoogle Scholar
Bühlmann, H. (1967). Experience rating and credibility. Astin Bulletin, 4, 199–207.CrossRefGoogle Scholar
Bühlmann, H., Gisler, A. (2005). A Course in Credibility Theory and its Applications (Berlin, Germany: Springer Verlag).Google Scholar
Bühlmann, H., Straub, E. (1970). Glaubwürdigkeit für Schadensätze. Bulletin of Swiss Association of Actuaries, 70, 111–133.Google Scholar
Englund, M., Guillén, M., Gustafsson, J., Nielsen, L.H., Nielsen, J.P. (2008). Multivariate latent risk: A credibility approach. Astin Bulletin, 38, 137–146.CrossRefGoogle Scholar
Englund, M., Gustafsson, J., Nielsen, J.P., Thuring, F. (2009). Multidimensional Credibility with Time Effects – An Application to Commercial Business Lines. The Journal of Risk and Insurance, 76, 443–453.CrossRefGoogle Scholar
Frees, E.W. (2003). Multivariate credibility for aggregate loss models. North American Actuarial Journal, 1, 13–37.CrossRefGoogle Scholar
Gangopadhyay, A., Gau, W.-C. (2007). Bayesian nonparametric approach to credibility modelling. Annals of Actuarial Science, 2, 91–114.CrossRefGoogle Scholar
Jewell, W.S. (1974). Credibility means are exact Bayesian for exponential families. ASTIN Bulletin, 8, 77–90.Google Scholar
Jewel, W.S. (1989). A General Framework for Credibility Prediction of Multidimensional First and Second Moments. Insurance: Mathematics and Economics, 8, 127–136.Google Scholar
Kamakura, W.A., Ramaswami, S., Srivastava, R. (1991). Applying latent trait analysis in the evaluation of prospects for cross-selling of financial services. International Journal of Research in Marketing, 8, 329–349.CrossRefGoogle Scholar
Kamakura, W.A., Wedel, M., de Rosa, F., Mazzon, J.A. (2003). Cross-selling through database marketing: a mixed data factor analyzer for data augmentation and prediction. International Journal of Research in Marketing, 20, 45–65.Google Scholar
Knott, A., Hayes, A., Neslin, S.A. (2002). Next-product-to-buy models for cross-selling applications. Journal of Interactive Marketing, 16, 59–75.CrossRefGoogle Scholar
Li, S., Sun, B., Wilcox, R.T. (2005). Cross-selling sequentially ordered products: an application to consumer banking services. Journal of Marketing Research, 42, 233–239.Google Scholar
Mowbray, A.H. (1914). How extensive a payroll exposure is necessary to give a dependable pure premium? Proceedings of the Casualty Actuarial Society, 1, 24–30.Google Scholar
Venter, G. (1985). Structured Credibility in Applications – Hierarchical, Multidimensional, and Multivariate Models. Actuarial Research Clearing House, 2, 267–308.Google Scholar
Whitney, A.W. (1918). The theory of experience rating. Proceedings of the Casualty Actuarial Society, 4, 274–292.Google Scholar