Insurance underwriters and risk managers have long recognized the need for up-to-date, high-quality property data. Traditional methods of assessment often rely on outdated or incomplete information. But with AI-derived risk factors based on frequently updated aerial imagery, insurers can stay ahead of evolving property risks.
Nearmap AI models categorize insights into 10 key categories, including roof condition, yard objects, roof objects, vegetation, and property characteristics. These comprehensive insights provide a holistic understanding of a property’s risk profile, ensuring underwriters make accurate and timely decisions. As a result, insurers can streamline their underwriting process, minimize costs, and reduce exposure to unanticipated losses.