Orchestrating data science workflows at scale
Accurate underwriting requires precise estimation and modeling of the insured’s risk. Traditionally, human experts achieve accuracy by analyzing data like vehicle reports and fleet stats. While most insurance companies use a handful of data points, Nirvana improves underwriting by leveraging IoT or intelligent sensor data. Specifically, we use telematics data like driver behavior, vehicle location, vehicle activity, and engine diagnostics, which we continuously receive and process from IoT devices attached to the insured vehicles. Analytics of this data gives us previously unexplored insights into the risk and behavior of our client’s fleets. One of our goals is to estimate risk as quickly as possible to minimize the turnaround time we take from the moment we receive an application to generating a quote.
