Abstract: The disclosure includes a system and method for fraud detection in the context of a user submitting, via a client device, a photo of a photo ID and a selfie taken during a step of the verification process. The fraud detection aggregates a variety of different sources of information indicative of potential fraud, such as a liveness signal, a repeated fraudster signal, client device attributes, temporal attributes, country information, and other optional forms of information such as telephone information, IP address etc. A machine learning model may be trained to generate an aggregate fraud score and classify the aggregate fraud score into different risk categories.