The present disclosure relates generally to a multi-layer fraud identification and risk analysis system. For example, the system may receive application data from a first borrower user, apply application data to one or more machine learning (ML) models, and receive a first score based at least in part upon output of the ML model that is associated with the first borrower user. The system may aggregate scores associated with multiple borrower users to a cumulative dealer user level. The aggregated first scores associated with the dealer user, as well as other corresponding application data, may be provided as input to a second ML model. Output from the second ML model may be associated with the dealer user as a second score.