Case Study: a global insurance company improves rooftop damage claims accuracy with WNS drone imagery analytics

Co-creation Helps in Claims Assessment of Rooftop Damages Using Cutting-edge Image Analytics Platform

The Global Insurance Company faced significant challenges in assessing rooftop damage claims. The process was traditionally manual and labor-intensive, requiring costly physical inspections that posed safety risks and were prone to inaccuracies. Existing drone imagery solutions were inadequate, often failing to correctly classify damage or handle high-resolution images. The company needed a comprehensive analytics solution to automate damage assessment and claims reporting, which led them to partner with vendor WNS.

WNS implemented an automated, AI and ML-based drone imagery analytics solution. This system used deep learning to process images, extract features, and analyze historical claims data to accurately identify and classify rooftop damages. The solution delivered a 95 percent accuracy rate in damage prediction, which eliminated manual effort and drastically reduced the claims cycle time. This co-created solution provided the client with potential benefits exceeding USD 30 million through automation and increased operational efficiency.