Automating Vehicle Damage Estimation with Computer Vision
, Global Partner/Customer Partner Manager Financial Services, NVIDIA
, Senior Engagement Manager, Quantiphi
Auto insurers in the United States alone are losing almost $30 billion annually due to errors in damage estimation. The poor quality of vehicle images is a major contributing factor. Identifying grainy photo uploads in claims submission is a practical challenge. Failure to accurately identify noisy images may lead to delayed claims servicing, sub-optimal customer experience, or even rejection of claims. Join NVIDIA's Elite Service Delivery Partner, Quantiphi, as they showcase their solution powered by NVIDIA SDKs (TensorRT, TLT, Triton Inference Server) that accelerates image noise detection, assesses vehicle damage, optimizes claims processing workflows, and eliminates the need for manual intervention. Using NVIDIA's best-in-class AI platform, you'll learn how it can speed up damage identification, severity assessment, and cost estimation. Overall, the solution enhances the customer experience while also reducing erroneous payouts and operating costs.