Patent ID: 11907954
Assignee: PAYPAL, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G  H

Claim 15:
16. A system, comprising:
at least one processor; and
a memory having instructions stored thereon that are executable by the at least one processor to cause the system to:
determine, using a trained machine learning model, whether one or more unlabeled transactions are anomalous, wherein the machine learning model is trained by:
generating a transaction network graph from an initial set of transactions with transaction attributes, wherein transactions in the initial set of transactions include known labels;
generating, from a training set of transactions using a first graph embedding routine, a first transaction matrix, wherein the first graph embedding routine is based on anomalies in related transactions occurring at one or more nodes in the transaction network graph that are multiple hops away, and wherein the training set includes a first subset of transactions in the transaction network graph;
generating, from the training set of transactions using a second, different graph embedding routine, a second, different transaction matrix, wherein the second, different graph embedding routine is based on anomalies in neighborhoods of similar transactions, and wherein generating the second, different matrix includes aggregating, for a given node assigned an anomaly label, attributes of transactions occurring at nodes within a neighborhood of nodes of the anomaly labeled node and attributes of transactions occurring at the anomaly labeled node;
generating a final embedded matrix from the first transaction matrix and the second, different transaction matrix, wherein one or more attributes of transactions in the final embedded matrix differ from the attributes of corresponding transactions in the training set of transactions; and
inputting the final embedded matrix into the machine learning model and adjusting weights of the model based on output of the model for the final embedded matrix.