How retail is using AI to prevent fraud


Jennifer: He says fraud management in places like this has changed quite a bit since he started this job. For example, they used to set up filters based on some simple questions.

David Cost: Was it a customer that we had ever seen before, right? We had certain flags that we would look for and somebody would manually go look at those orders and kind of have to just make a guess on whether they thought that order was good or not. We ship it out and if it turns out it’s not good, then we, the retailer, you know, take that loss. So it’s as if somebody stole those goods. It’s the same thing as shoplifting. You know, and it can, it can have a real impact on your business and you want to be careful. If you’re too cautious, you turn good business away. I mean, there’s nothing worse than taking a customer who’s got a good valid form of payment and telling them, nope. Sorry. Doesn’t look quite right, so we’re not gonna ship it.

Jennifer: One place Rainbow came up against this… was in doing business with buyers in other countries.

David Cost: So they’re placing the order from one of the islands in the Caribbean. So their billing address is a Caribbean address, they’re shipping the goods mainly to a Florida or a Texas re-shipper’s address where a bunch of orders are combined to go to the island, right? And then they’re taken into those islands. These are good customers but for traditional fraud, to be able to see that foreign credit card, foreign address, but a US delivery address would raise all kinds of alarm bells. So the sophistication of the AI ​​now to be able to help us accurately figure out what’s a good order and what’s a bad order, lets us raise our level of customer service… So that we’re taking care of customers at the same time, minimizing the potential loss to the business, with those orders that we would fulfill and ship and then not get paid for.

Jennifer: Rainbow is using a tool from fraud detection company, Signifyd… and he says these days they turn down less than 1% of their orders.

David Cost: In earlier times when we had to do this all manually… they would go to Google Maps and look up the address to see if the address looked legitimate. You know, now with the sophistication of the tech to know who you are, where else have we seen you order, digital IDs on your device, distance between your billing and shipping address. So many factors. So again, even five or six years ago, that process was manual and it could take a day or two, you know, now they’re being made in fractions of a second.

Will Douglas Heaven: I mean, this happened to me yesterday, actually, you know, I got a text message. I’d taken my car to the garage and, you know, put a larger than usual amount on it.

Jennifer: That’s Will Douglas Heaven, Tech Review’s senior AI editor.



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