Anyone who’s tried to buy online tickets to a hot sports event or sure-to-sell-out concert knows how fraught the experience can be. You’re bombarded with options, and it can be hard to tell legit sources from shady ones. You want to buy from the venue, the team, or a reputable broker, but who’s who? And even savvy fans can succumb to scams that use social engineering tactics like irresistibly low advertised prices or pressure to act quickly. After all, nobody wants to miss out on a good deal or a great show.

Here’s the thing: Ticket sellers face very similar challenges. 

Differentiating legit purchases from fraud is a challenge in the fast-paced and highly liquid ticketing space, and balancing risk and revenue is not easy. Ticket prices and demand are seasonal, volatile, and often unpredictable. High-velocity digital transactions invite exploitation and fraud attacks. And as scammers themselves will assure you, “everything is possible with social engineering.”

Fraudsters game the system

Riskified research showed a 22% YoY increase in risk as of mid-2024. It also revealed how closely fraudsters monitor merchant tactics and adapt to avoid detection.

They know tickets can be purchased instantaneously, virtually anonymously, and often with little time for a thorough payment review by the merchant.

They also know that they can hide behind behaviors that merchants use to identify good customers. For example, Riskified data shows fraudsters target low-volume orders and mid-priced tickets to mimic good customer behavior and blend in. This makes it extremely difficult for merchants to block fraud without falsely declining legitimate payments, which can be almost as costly as fraud itself. 

The average cost of a false decline in online ticketing

With scammers continually learning and adapting, merchants must implement prevention strategies that are equally dynamic.

Machine learning is the ticket

Merchants using AI can accurately differentiate between fraudulent and legitimate ticket buyers at the point of purchase, slashing the financial, reputational, and operational costs of both false declines and fraud. For TickPick, this meant pocketing $3 million in incremental revenue that otherwise would have been declined due to fraud risk.

Bounce fraud at the door

Learn more about current fraud trends facing ticket sellers in the latest Riskified Risk Rundown, and discover how to use machine learning to efficiently bounce fraud and approve more good orders.