Compound Poisson Model with Covariates A Case Study on Pet Insurance

• Published in: North American actuarial journal Vol. 10; no. 4; pp. 219 - 234
• Main Authors: Pai, Jeffrey S., Shand, Kevin J., Wang, Xikui
• Format: Journal Article
• Language: English
• Published: Schaumburg Taylor & Francis Group 01.10.2006; Taylor & Francis Ltd
• Subjects: Insurance; Insurance claims; Pets; Poisson distribution; Random variables; Studies; Canada
• ISSN: 1092-0277; 2325-0453
• DOI: 10.1080/10920277.2006.10597423

Pet insurance in North America continues to be a growing industry. Unlike in Europe, where some countries have as much as 50% of the pet population insured, very few pets in North America are insured. Pricing practices in the past have relied on market share objectives more so than on actual experience. Pricing still continues to be performed on this basis with little consideration for actuarial principles and techniques. Developments of mortality and morbidity models to be used in the pricing model and new product development are essential for pet insurance. This paper examines insurance claims as experienced in the Canadian market. The time-to-event data are investigated using the Cox's proportional hazards model. The claim number follows a nonhomogenous Poisson process with covariates. The claim size random variable is assumed to follow a lognormal distribution. These two models work well for aggregate claims with covariates. The first three central moments of the aggregate claims for one insured animal, as well as for a block of insured animals, are derived. We illustrate the models using data collected over an eight-year period.