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In this paper we show that the actual methodology for the integration of these two approaches can lead to inconsistencies. We develop a statistical model that adequately integrates risk classification and experience rating. For this purpose we present Poisson and negative binomial models with regression component in order to use all available information in the estimation of accident distribution. A <jats:italic>bonus\u2010malus<\/jats:italic> system which integrates <jats:italic>a priori<\/jats:italic> and <jats:italic>a posteriori<\/jats:italic> information <jats:italic>on an individual basis<\/jats:italic> is proposed, and insurance premium tables are derived as a function of time, past accidents and the significant variables in the regression. Statistical results were obtained from a sample of 19,013 drivers.<\/jats:p>","DOI":"10.1002\/jae.3950070204","type":"journal-article","created":{"date-parts":[[2007,7,12]],"date-time":"2007-07-12T16:49:50Z","timestamp":1184258990000},"page":"149-165","source":"Crossref","is-referenced-by-count":126,"title":["Automobile insurance ratemaking in the presence of asymmetrical information"],"prefix":"10.1002","volume":"7","author":[{"given":"G.","family":"Dionne","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"C.","family":"Vanasse","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2006,11,7]]},"reference":[{"key":"e_1_2_1_2_1","first-page":"215","article-title":"Contributions to the theory of accident proneness","volume":"1","author":"Bates G. 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