Detect real and live users and deter bad actors using Amazon Rekognition Face Liveness

Financial services, the gig economy, telco, healthcare, social networking, and other customers use face verification during online onboarding, step-up authentication, age-based access restriction, and bot detection. These customers verify user identity by matching the user's face in a selfie captured by a device camera with a government-issued identity card photo or preestablished profile photo. They also estimate the user's age using facial analysis before allowing access to age-restricted content. However, bad actors increasingly deploy spoof attacks using the user's face images or videos posted publicly, captured secretly, or created synthetically to gain unauthorized access to the user's account. To deter this fraud, as well as reduce the costs associated with it, customers need to add liveness detection before face matching or age estimation is performed in their face verification workflow to confirm that the user in front of the camera is a real and live person.