Allen describes how her background in working in the fraud departments of Etsy, Airbnb, and 1stDibs has allowed her to offer a plethora of information about various forms of fraud to the financial industry. She suggests that there are countless ways to perpetrate fraud in the digital economy, ranging from e-commerce to luxury fraud. Allen goes so far as to say that while working in the luxury fraud industry, they were able to avoid falling for the well-known Netflix scammer Anna Delvey.
 

Allen notes that "refund" or "return" fraud is a prevalent trend in fraud at the moment. Additionally, she asserts that consumer education is crucial for financial institutions and e-commerce companies, particularly in light of the current wave of scammers. Customers are starting to show more affinity for fraud influencers, or scammers who share their abilities in an economy known as "fraud as a service" in order to make money.
 

"Under the previous paradigm, fraud was committed by going onto a dark web page, obtaining some credit cards that had been stolen, and using those to make purchases. However, they can now reach a larger audience by connecting to the deep web through secure messaging apps like Telegram. Perhaps they will add mentorships on how to do refund fraud to the sales of those credit cards, or they might offer Bibles or instructions explaining how to use a website to perpetrate fraud.
 

Additionally, there is an increase in fraud-related chatter on the surface web, which is how fraudsters lure users to Telegram. For instance, if you're an average individual with no knowledge of fraud, you can stumble into a channel where people are promoting refund fraud when searching for a knockoff replica of an item on social media sites like TikTok. The recruiter often includes a Telegram link that directs visitors to those channels. Then that also shows up more on your for you page of recommendations regarding actual fraud with stolen payment methods and stolen accounts.
 

According to Allen, the difficult part of this kind of fraud is how companies are able to identify it. Influencers on TikTok, for instance, may not be discussing illegal stuff, but they may nevertheless conceal it using text boxes on the screen, banners inside videos, and other methods that make it harder to find.

Regarding the use of AI and deepfake technology by scammers, Allen notes that these technologies are less likely to be utilized when impersonating a close friend or relative because it takes a lot more work to fool a small number of individuals. On the other hand, it poses a serious risk to impersonate celebrities or other well-known people in order to raise money, for example by requesting charitable donations.

She goes on to say, "We are all going to have to be extra vigilant this election cycle," illustrating how quickly false information can proliferate. This is the first significant US federal election where AI techniques are widely available. There will undoubtedly be deepfakes of party candidates acting and saying strange things. These may or may not be produced by a different administration, not the opposition. Election meddling in that manner by a third party is possible, but it will occur nonetheless. I'm sure that some people will see it and fail to recognize that it is generative AI, so perhaps detection capabilities will outpace spread.
 

People should be wary of trusting sources on social media, as evidenced by the widespread uproar around the altered photo of Princess Kate and her family that was posted this week. Allen emphasized the need of conducting research, stating that while at first many might have scrolled past the images, more examination from news outlets showed a different story.
 

Allen explains, "Merchants and financial institutions see robust sets of data, but very different data from each other." This is in reference to what financial institutions and merchants should be doing to prevent payments fraud. An online retailer can identify fraudulent activity since they have complete access to a specific customer's browsing history, including goods added to favorites, things added to and removed from carts, browsing trends, and more. Financial companies see all of your other spending patterns but are not privy to any of that. They are aware of your past whereabouts, your typical shopping times, how you use their app, and the kinds of promotions you would click on.
 

"To increase their ability to assess risk and the consumer's ability to access risk, they must, whenever possible, develop partnership in order to bridge that gap. To accomplish just that and share data, Sift is collaborating with a certain issuing bank, and that is really significant.

She continues by saying that authorities are still attempting to smooth out several issues around banks' obligations to stop payments to scammers and where banks have the authority to forbid payments.

Allen states that when it comes to the application of AI and machine learning for fraud detection and prevention, her main concern is ensuring that datasets are impartial and free from prejudice.

"A fraud-free future is being discussed, but I don't think that's feasible. It will still be a discussion of prevention because you will then be turning away good clients. You need to strike a balance between your risk tolerance and how much fraud you are willing to allow in order to avoid offending too many customers. I would really like to see the industry go toward something that is more clear, easily readable, and accessible for merchants so they can comprehend, for example, why a machine learning model or an AI-driven model made a particular conclusion. After that, merchants will be able to comprehend the reasoning behind the choice and what they can do to perhaps influence it for subsequent transactions.