US Patent 11288673 Online fraud detection using machine learning models

A method is disclosed. The method includes obtaining an access request associated with a user for a software application; obtaining a plurality of verification attributes associated with the user; generating a fraud score for the access request by feeding a supervised machine learning (ML) classifier with a feature vector for the user that is based on the plurality of verification attributes; selecting a first unsupervised ML anomaly detector of a plurality of unsupervised ML anomaly detectors based on the fraud score; generating an anomaly score for the access request by feeding the first unsupervised ML anomaly detector with an augmented feature vector for the user that is based on the plurality of verification attributes and the fraud score; and processing the access request based on the anomaly score.