Artificial intelligence (AI) and deep-learning property analytics company, Arturo, has entered into a partnership with Urban Sky to incorporate the company’s stratospheric photos into its collection of property images.
The partnership is expected to enable Arturo to provide a more accurate analysis to its insurance customers in the U.S., focusing on both suburban and rural areas.
Arturo uses machine learning to translate satellite, stratospheric, aerial and ground imagery from multiple sources into data points.
The points are then used to identify a wide range of property characteristics relevant to global insurance carriers, such as roof condition, tree coverage, structural materials, fire risk and other exterior attributes.
For insurers, access to on-demand aerial imagery following catastrophic weather, and from multiple sources, enables them to better assess the damage caused by a specific event, issue disbursements faster and use human resources more strategically, says Arturo.
John-Isaac Clark, Chief Executive Officer (CEO) of Arturo, commented: “For insurance companies, precise and high-frequency property data is critical to making smart decisions that can effectively mitigate risk.
“Our machine learning technology excels at identifying property conditions and characteristics and predicting issues, but our ability to provide the greatest value is dependent on access to high-quality, on-demand imagery.
“By adding Urban Sky to our network of image providers, we are once again heightening the level of accuracy and insights for our clients.”
Andrew Antonio, CEO of Urban Sky, a provider of broad area, high-resolution aerial imagery, added: “Arturo is the leading player in property imaging analytics, and we’re excited to have them as our first commercial partner.
“The stratosphere provides a unique vantage point from which to collect high-resolution imaging at a low cost, made possible by our reusable Microballoon.
“As we look toward the future, we see stratospheric imagery as the gold standard for property insurance, and other sectors that rely on high-quality, frequent property images.”
