Visa Inc.
FRAMEWORK FOR USING MACHINE-LEARNING MODELS TO IDENTIFY CARDHOLDERS TRAVELING ABROAD AND PREDICTING CARDHOLDER CROSS-BORDER CARD USAGE TO INCREASE PENETRATION OF CROSS-BORDER TRANSACTIONS

Abstract:

A method comprises identifying, by a first machine-learning (ML) model, cardholders who have purchased an international travel reservation, the first ML model using as input payment transaction records and travel itinerary records retrieved from one or more databases. For each of the identified cardholders, the first ML model identifies a payment card used to purchase the international travel reservation, and a corresponding destination country and a departure date. A second ML model identifies the payment cards of the identified cardholders having low probability of being used for a cross-border transaction based at least in part on historical payment transactions. For the cardholders associated with low probability cross-border cards, an action is initiated, including providing an offer to the identified cardholders of the low probability cross-border cards, wherein the offer incentivizes use the low probability cross-border cards in the destination country prior to, or during, the international travel.