Vehicle Damage Assessment: Digitally transformed by Computer Vision and Data Annotation

Description

Machine learning is already being employed across multiple industries to automate the processes that are slowed down by manual, repetitive steps. With advanced algorithms, techniques, and frameworks under the hood, AI tools can accelerate the process of recognizing damaged vehicle parts, assessing damage, making predictions about what kind of repair is needed, and estimating how much it may cost.
Computer vision, a technology that processes visual information and interprets data, can paint a fuller and more accurate picture of an auto accident, including the conditions, scene, and what repairs are needed.
By working with partners to access AI, data engineering, and other digital tools, insurers can take advantage of these new technologies as they come to market without waiting for them to become fully plug-and-play. They need to ensure that their claims processes augment new technologies and decide who is going to execute the outcomes.