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For the auto insurance claims process, improvements in the First Notice of Loss and rapidity in the investigation and evaluation of claims could drive significant values by reducing loss adjustment expense. This paper proposes a novel application where advanced technologies in image analysis and pattern recognition are applied to automatically identify and characterize automobile damage. Success in this will allow some cases to proceed without human adjusters, while others to proceed more efficiently, thus ultimately shortening the time between the first Notice of Loss and the final payout. To investigate its feasibility, we built a prototype system which automatically identifies the damaged area(s) based on the comparison of before-and after-accident automobile images. Performance of the prototype system has been evaluated on images taken from forty scaled model cars under reasonably controlled environments, and encouraging results were obtained. It is our belief that, with the advancement of image analysis and pattern recognition technologies, the proposed idea could evolve into a very promising application area where the auto insurance industry could significantly benefit.