Pay-how-you-drive (PHYD) or usage-based (UB) systems for automobile insurance provide actuaries with behavioural risk factors, such as the time of the day, average speeds and other driving habits. These data are collected while the contract is in force with the help of telematic devices installed in the vehicle. They thus fall in the category of a posteriori information that becomes available after contract initiation. For this reason, they must be included in the actuarial pricing by means of credibility updating mechanisms instead of being incorporated in the score as ordinary a priori observable features. This paper proposes the use of multivariate mixed models to describe the joint dynamics of telematics data and claim frequencies. Future premiums, incorporating past experience can then be determined using the predictive distribution of claim characteristics given past history. This approach allows the actuary to deal with the variety of situations encountered in insurance practice, ranging from new drivers without telematics record to contracts with different seniority and drivers using their vehicle to different extent, generating varied volumes of telematics data.

Most studies on seniors’ driving practices are based on self-reports; none have objectively examined winter driving patterns. We used electronic devices, together with trip logs, digital maps, and weather archives, to examine the driving patterns of seniors aged 65 to 91 over two consecutive weeks between November 2008 and March 2009. Night driving differed by month showing the importance of seasonal factors, particularly the amount of daylight. Although 69 per cent of the sample drove on days with adverse conditions, seniors were significantly more likely to make trips for social/entertainment purposes on days with good weather, and out-of-town trips on days with good road conditions. Driving comfort scores, particularly for night driving, were significantly related to multiple indicators of exposure and patterns, including radius from home. Compared to men, women had significantly lower driving comfort scores and were less likely to drive on days with adverse weather and road conditions.