Ventiv Technology

BRAVE NEW WORLD | 12 In the year 2020, extreme weather events caused an estimated $95 billion in property damage in the U.S. alone. One area that is becoming more susceptible to disaster losses is the U.S. coastline, due in large part to the huge increases in development. One catastrophe modeling company predicts that catastrophe losses will double every decade due to growing residential and commercial density and the installation of more expensive buildings. Travelers' CAT modelers pride themselves on their capabilities in leveraging the power of AI and sophisticated modeling techniques. The company is the second-largest writer of U.S. commercial property casualty insurance, and the sixth-largest writer of U.S. personal insurance through independent agents. It also happens to be a data-driven company powered by AI. More recently, the company utilized deep learning techniques in the company's Roof Shape Classification AI Model, which is currently available in some hurricane-prone Texas counties. The objective was to improve the speed and accuracy with which Travelers can quote customers' coverage needs as they related to their specific roof type. It is important to note that the shape of a homeowner's roof can make a big difference in how much damage a house sustains in high winds, and thus, impacts their insurance policy and the risk calculations involved in pricing. Using the Roof Shape Classification AI Model, Travelers' technology teams rely on algorithms and aerial imagery to identify a roof's shape – typically a time-consuming process for customers – with close to 90% accuracy. Mano Mannoochahr, Chief Data and Analytics Officer for Travelers', had this to say: "Ever since the damaging spate of California wildfires in late 2019, for example, our technology and data science teams have leveraged deep learning to analyze thousands of aerial images of property damage – immediately identifying which properties are total losses. As a result, we can advance payments on most wildfire total-loss claims prior to having an in-person inspection, allowing our customers to begin the recovery process faster than ever before while keeping our employees safe."

• Cover