N. Elshaiekh

Self-Supervised Knowledge Representation for Rare Fraud and Operational Failure Detection in Multi-Channel Payment Systems

It is shown that naive, generic, SSL-based anomaly detectors lead to reduced precision, and task-adapted representations of supervised models, stacked with task-adapted representations, can increase fraud recall by up to 4.9 with a small F1 increase, enhancing a knowledge based perspective of when self-supervised repre...