Abstract: A system that investigates, identifies and cancels fraudulent transactions comprises a fraud detection server that receives a first dataset indicating a quantity of fraud-transactions. The first dataset is generated at least in part by a fraud-score model. The system receives a second dataset including a quantity of false positive fraud-transactions from the fraud transactions. The system calculates a fraud error rate using the quantity of fraud-transactions and the quantity of false positive fraud-transactions. The system generates a new fraud-score model when the fraud error rate exceeds a predefined error rate.

Abstract: A system that investigates, identifies and cancels fraudulent transactions comprises a fraud detection server that receives a first dataset indicating a quantity of fraud-transactions. The first dataset is generated at least in part by a fraud-score model. The system receives a second dataset including a quantity of false positive fraud-transactions from the fraud transactions. The system calculates a fraud error rate using the quantity of fraud-transactions and the quantity of false positive fraud-transactions. The system generates a new fraud-score model when the fraud error rate exceeds a predefined error rate.

Abstract: A system includes a transaction server configured to receive and process retail transactions. A fraud detection server is in communication with the transaction server and is configured to generate a plurality of fraud models from a first subset of the retail transactions. Each fraud model represents a potentially fraudulent transaction. The fraud detection server further predicts an effectiveness of each of the plurality of fraud models to identify potentially fraudulent transactions, selects the fraud model based at least in part on the predicted effectiveness based on the first subset of the retail transactions, and transmits the selected fraud model to the transaction server. The transaction server is configured to apply the selected fraud model to at least a second subset of the retail transactions to identify potentially fraudulent transactions.