Metromile Leverages Artificial Intelligence And Sensor Data From Low-Impact Car Crashes To Tackle Insurance Fraud Markets Insider

In 2015, there were more than 6.3 million car accidents reported that involved property damage1 with insurance fraud accounting for 10 percent of property/casualty claims processed2. While not every accident resulted in an insurance claim, those that did required extensive effort to be verified manually. To help automate the process and to fight against fraud which contributes to rising insurance rates, Metromile, the leader in pay-per-mile car insurance in the U.S., staged the world's slowest car crashes to generate data and used a machine learning technology to help spot fraud more quickly. "With machine learning technology, our team will be able to better prevent insurance fraud and assist customers with hard-to-prove but common claim types, like hit-and-run collisions, car theft, and rear-ends," said Paul Anzel, a Data Scientist at Metromile. Each test vehicle was equipped with a Pulse device, a small GPS-enabled device that plugs into the OBD-II port, to record sensory data, to generate the digital First Notice of Loss (FNOL) and capture accident details.