METHOD AND SYSTEM FOR REAL-TIME AUTOMATED IDENTIFICATION OF FRAUDULENT INVOICES

Known fraudulent invoice data, including defined and known fraudulent invoice feature data, is used to train a machine learning-based fraudulent invoice detection model to generate a fraudulent invoice score for invoices indicating a determined probability that a given invoice is fraudulent. The machine learning-based fraudulent invoice detection model is then used to generate a fraudulent invoice score for subsequent invoices before those invoices are paid by, and in some cases before the invoices are provided to, the parties being asked to pay the invoices. The fraudulent invoice score for the subsequent invoice is then used to determine if the subsequent invoice should be passed on to the parties being asked to pay the invoices for payment, or if one or more protective actions should be taken.