Machine learning engine for fraud detection during cross-location online transaction processing

Abstract

A machine learning engine for fraud detection related to cross-location online transaction processing may be trained using artificial intelligence techniques and used according to techniques discussed herein. An account may be used to electronically process a transaction for an item in a foreign location, such as a new city or country. The transaction may be identified as potentially fraudulent based on the item and/or location of purchase. A service provider may identify a vertical, such as an item type, for the transaction, and may determine the account's propensity to purchase within that vertical in the new location and the merchant's propensity to sell within that vertical to the account's location or shipping address. Based on the propensities, the service provider may utilize one or more risk rules with a risk assessment engine to determine transaction processing risk and whether to proceed with transaction processing.