Think Tank: Is AI the Future of E-commerce Fraud Prevention?

There’s a lot of debate about what Artificial Intelligence really means, and how we should feel about it. As Gartner says in “A Framework for Applying AI in the Enterprise,” “The artificial intelligence acronym ‘AI’ might more appropriately stand for ‘amazing innovations’ that do what we thought technology couldn’t do.” One way and another, we’re talking about “smart machines” — machines that are trained on existing, historical data, and use that to make accurate deductions or predictions about examples with which they’re presented. 2) Personalization: The experience can be tailored to each customer in ways that were not an option when companies had to configure/design the experience for everyone at once (or maybe have a few versions based on geographies). All of this makes me unpopular with e-commerce fraud prevention systems. I was a fraud prevention analyst myself, back in the time before AI was an option. I know exactly how hard these transactions are to get right, from the human perspective. I know how long it can take to review a transaction, and that as an analyst the tendency is always to play it safe — even if that means sending a good customer away. AI is the future of e-commerce fraud prevention. It brings scale, accuracy and adaptivity to improve customer experience, block fraud and increase sales. Better fraud prevention is about to become standard.
Online fraud continues to grow.
Online fraud continues to grow.

There’s a lot of debate about what Artificial Intelligence really means, and how we should feel about it. Will it transform our world for the better? Will the machines take over? Will it simply make processes we already perform faster and smoother? As Gartner says in “A Framework for Applying AI in the Enterprise,” “The artificial intelligence acronym ‘AI’ might more appropriately stand for ‘amazing innovations’ that do what we thought technology couldn’t do.”

One way and another, we’re talking about “smart machines” — machines that are trained on existing, historical data, and use that to make accurate deductions or predictions about examples with which they’re presented. The applications are wide-ranging, from medicine to retail to self-driving cars and beyond.

For e-commerce, AI means the ability to deliver capabilities that simply were not possible before. There are two main directions in which this expresses itself:

1) Uncovering trends and audiences: A well-trained e-commerce AI can identify trends of buyer behavior, or interests in new products or experiences and adapt quickly.

2) Personalization: The experience can be tailored to each customer in ways that were not an option when companies had to configure/design the experience for everyone at once (or maybe have a few versions based on geographies). Customers can be offered the information and products they want, when they want them, in the ways that are best suited to them.

Why I’ve Come to Love AI

As someone who travels a lot, I often have a fairly complex customer story when I shop online. I might be on a work trip to China, using a proxy to shop on a favorite U.S. store with my credit card, which has a New York billing address, sending something to an office in San Francisco to pick up on my next stop. There’s a good chance I’ll be on a mobile device, and since I like to explore new things, I’m often buying something of a kind I’ve never bought before.

All of this…

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