– Case Study –
Damage Assessment for Automotive Insurance Claims
AI based automotive damage assessment claims startup required highly accurate point/image classification
An AI based automotive damage assessment claims startup needed to provide more precise automated claim outcomes on their platform. The complexity of understanding diverse damages across a variety of car models is a tedious process. It is further complicated by models needing to also assess the severity of damages and connect its assessment to the underwriting process.
10k+ Images Classified Per Week
Innodata leveraged its AI-enabled platform and deployed a team of five specialists to provide point/image classification of over 10,000 images per week. Because of their extensive experience in auto claims adjustment, the specialists were able to provide labeled data at a very high granularity, in real time, and help refine client taxonomy.
By integrating Innodata’s combination of machine learning and humans-in-the-loop into their workflow, this startup was able to significantly reduce time and save money on resolving claims.
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