So before, we were having … not a huge, but we were having a fraud problem where people were placing orders, and they were getting fulfilled even though they were very obviously using a stolen credit card. So we started using Sift, which basically, we send Sift a collection of signals from users, so like they added this item to the cart. They tried to add a credit card, but it failed. They added this address and then they submitted. So we send them the collection of signals, and they run machine learning on those signals and send us back a classification of the user, and we use that as one of our elements to decide if we should fulfill that order or not.
So that's all happening in real-time. Without human intervention, you can tell. If they have a very high Sift score, you can say, “This person is clearly fraudulent. They’re using credit cards from six different places and ordering only Patrón.” Sift Science
