Hostname: page-component-78c5997874-4rdpn Total loading time: 0 Render date: 2024-11-10T14:38:31.917Z Has data issue: false hasContentIssue false
  • English
  • Français

Bonus-malus Systems in a Deregulated Environment: Forecasting Market Shares Using Diffusion Models

Published online by Cambridge University Press:  17 April 2015

Krupa S. Viswanathan  and
Jean Lemaire
Krupa S. Viswanathan
Affiliation:
Fox School of Business and Management, Temple University, Department of Risk, Insurance, and Healthcare Management, 471 Ritter Annex (004-00), Tel: 1 (215) 204-6183, Fax: 1 (215) 204-4712, E-mail: ksubrama@temple.edu
Jean Lemaire
Affiliation:
Wharton School, University of Pennsylvania, Insurance and Risk Management Department, 3620 Locust Walk, SH-DH 3404, Philadelphia, PA 19104-6320, USA, Tel: 1 (215) 898-7765, Fax: 1 (215) 898-0310, E-mail: lemaire@wharton.upenn.edu
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

In a deregulated insurance market, insurance carriers have an incentive to be innovative in their pricing decisions by segmenting their portfolios and designing new bonus-malus systems (BMS). This paper examines the evolution of market shares and claim frequencies in a two-company market, when one insurer breaks off the existing stability by introducing a super-discount class in its BMS. Several assumptions concerning policyholders and insurers behavior are tested. Diffusion theory is used to model the spread of the information concerning the new BMS among prospective customers. A wide variety of market outcomes results: one company may take over the market or the two may survive with equal or unequal market shares, each specializing in a specific niche of the market. Before engaging in an aggressive competitive behavior, insurers should consequently be reasonably confident in their assumptions concerning the reactions of their policyholders to the new BMS.

Keywords

Bonus-malus systemsrating freedomcompetitiondiffusion processesexternal and internal communication coefficients
Type
Workshop
Information
ASTIN Bulletin: The Journal of the IAA , Volume 35 , Issue 1 , May 2005 , pp. 299 - 319
Copyright
Copyright © ASTIN Bulletin 2005

References

Bartholomew, D.J. (1982) “Stochastic Models for Social Processes.” John Wiley and Sons, New York.Google Scholar
Bass, F.M. (1969) “A New Product Growth Model for Consumer Durables.” Management Science, 15, 215–227.CrossRefGoogle Scholar
Brouhns, N., Guillén, M., Denuit, M. and Pinquet, J. (2003) “Bonus-Malus Scales in Segmented Tariffs with Stochastic Migration Between Segments.” Journal of Risk and Insurance, 70, 577–599.CrossRefGoogle Scholar
Cummins, J.D., McGill, D., Winklevoss, H. and Zelten, H. (1974) “Consumer Attitudes Toward Auto and Homeowners Insurance.” Department of Insurance, The Wharton School.Google Scholar
De Palma, A., Droesbeke, J.J. and Lefèvre, C. (1991) “Modèles de Diffusion en Marketing.” Presses Universitaires de France, Paris.Google Scholar
Fels, Wolfgang A. (1995) “A Helicopter Tour over Competing Bonus-Malus Systems.” Economics Department, Austrian Association of Insurance Companies.Google Scholar
Fourt, L.A. and Woodlock, J.W. (1960) “Early Prediction of Market Success for Grocery Products.” Journal of Marketing, 25, 31–38.CrossRefGoogle Scholar
Gisler, A. (1996) “Bonus-Malus and Tariff Segmentation.” XXVIIth ASTIN Colloquium, Copenhagen.Google Scholar
Joskow, P. (1973) “Cartels, Competition, and Regulation in the Property-Liability Insurance Industry.” Bell Journal of Economics, 4, 375–427.Google Scholar
Lemaire, J. (1995) “Bonus-Malus Systems in Automobile Insurance.” Kluwer, Boston.CrossRefGoogle Scholar
Mahajan, V. and Wind, Y. (eds.) (1986) “Innovation Diffusion Models of New Product Acceptance.” Ballinger Publishing Company, Cambridge.Google Scholar
Mansfield, E. (1961) “Technical Change and the Rate of Imitation.” Econometrica, 29, 741–766.CrossRefGoogle Scholar
Portugal, L. (2001) “Sistemas de Bónus-Malus e dinâmica do mercado.” Actuarial – Consul-tadoria, Série Estudos no 4.Google Scholar
Schlesinger, H. and Graf von der Schulenberg, J.M. (1993) “Consumer Information and Decisions to Switch Insurers.” Journal of Risk and Insurance, LV (4), 591–615.CrossRefGoogle Scholar
Subramanian, K. (1998) “Bonus-Malus Systems in a Competitive Environment. North American Actuarial Journal, 2, 38–44.CrossRefGoogle Scholar
Taylor, G. (1997) “Setting a Bonus-Malus Scale in the Presence of Other Rating Factors.” ASTIN Bulletin, 27, 319–328.CrossRefGoogle Scholar