Patent ID: 11875353
Assignee: NCR VOYIX CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A method, comprising:
training a machine-learning model on transaction events of transactions and transaction features for the transaction events to predict labels for each transaction action as being a risky action or a non-risky action, compare predicted labels for the risky actions and non-risky predicted labels against actual labels that correspond to actual transaction actions, compute a probability for the actual transaction actions based on transaction features of each transaction as a whole, and output risk scores for the transaction actions of each transaction based on the corresponding probabilities calculated, wherein the transaction features at least include preceding transaction events occurring in the transaction before each transaction action for the corresponding transaction and post transaction events occurring after each transaction action in the corresponding transaction, any first items appearing in the corresponding transaction more than once, and any second items appearing in the corresponding transaction with a same transaction weight;
receiving a current transaction comprised of current transaction events for a current transaction;
providing the current transaction events in the current transaction to the machine-learning model as input data;
receiving a current risk score for a current transaction action that was processed in the current transaction as output data from the machine-learning model; and
providing the current risk score to a fraud detection system, using the risk score in combination with a fraud score made independently by the fraud system for the current transaction, and determining whether the current transaction is fraudulent or not based on the risk score and the fraud score of the fraud detection system.