Fortune 500 Company
Building Machine Learning Models
to improve insurance risk assessments
A prominent Fortune 500 insurance company required a way to better predict and plan for abrupt weather disasters. Doing so would help increase reliability of risk models and allow better premiums for policy holders. Knowing that a major weather event had occurred or was about to occur and the capacity to act quickly was important.
Utilizing AWS IoT and Machine Learning services, we created an AI/ML edge solution capable of locally identifying a specific weather event and notifying our client on occurrence. Based on comparable in-market solutions and weather ground stations, utilizing audio as the input signal is a unique approach that the team was tasked to validate for technical feasibility and accuracy. The initial model was built with 10,000 seed audio files spanning various weather conditions.
Edge Devices with Deployed ML Model
Detection Accuracy in Initial Pilot
Weather Event Types & Severities Detectable
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