Both Rachel J. Huang and Kili C. Wang are research fellows in Risk and Insurance Research Center, College of Commerce, NCCU. Rachel J. Huang can be contacted via e-mail: firstname.lastname@example.org. The authors would like to express their deep gratitude to Larry Tzeng, Yi-Ting Chen, and the two referees who made stimulating comments on the paper.
Can Vehicle Maintenance Records Predict Automobile Accidents?
Article first published online: 13 SEP 2011
© The Journal of Risk and Insurance, 2011
Journal of Risk and Insurance
Volume 79, Issue 2, pages 567–584, June 2012
How to Cite
Bair, S.-T., Huang, R. J. and Wang, K. C. (2012), Can Vehicle Maintenance Records Predict Automobile Accidents?. Journal of Risk and Insurance, 79: 567–584. doi: 10.1111/j.1539-6975.2011.01433.x
- Issue published online: 23 MAY 2012
- Article first published online: 13 SEP 2011
This article proposes that vehicle maintenance records can provide useful information for predicting the probability that an owner will have an automobile accident. To test the hypothesis, we use a unique data set that is merged from an insurance company and a vehicle manufacturer in Taiwan. We find weak evidence to support our hypothesis. Among all the proxies for proper maintenance, we indicate that proper maintenance defined by the recommended kilometers is significantly negatively correlated with the loss probability in compulsory automobile liability insurance. The average loss probability decreases by 0.23 percent when the insured vehicle is properly maintained according to the recommended number of kilometers in the previous years, whereas the average loss probability for the overall sample is 0.49 percent. We further find that proper maintenance is insignificantly correlated with loss severity.