Case Study: a Fortune 500 insurance company improves weather risk prediction with Kopius cloud-based machine learning and IoT

a major insurance company detects 12 weather events with 85% accuracy using Kopius

The customer, a Fortune 500 insurance company, faced the challenge of improving its risk models amid escalating climate change risks. It approached Kopius for a solution to better predict weather disasters in real-time to allow for more accurate policyholder premiums.

Kopius developed a pilot solution using cloud-based machine learning and IoT devices. The solution involved training machines with 10,000 audio files to recognize 12 unique weather event types. Kopius deployed 500 devices that achieved 85% accuracy in the initial pilot, which informed the client's future technology strategy.