False positives, real revenue damage: The silent killer of online sales

As digital payments dominate retail transactions, false positive card declines pose an expensive, often overlooked problem. A false positive is when fraud detection systems incorrectly flag a genuine purchase as suspicious and fraudulent – and subsequently block the transaction from taking place. These errors cost businesses both revenue and reputation. Research even shows 42% of shoppers would boycott a brand that falsely declines their transaction. 

It‘s estimated that as many as 15% of all card-not-present (CNP) transactions are falsely declined. For e-commerce retailers, this translates to one in every seven legitimate customers turned away at checkout, often without explanation. 

The financial burden of false positives 

As businesses and banks look to defend against growing online threats, they often use a rules based approach or become too risk-averse, inadvertently blocking real customers’ payments. Research reveals 70% of falsely declined transactions are difficult to recover, making this a top priority for retailers. 

Typical triggers for false positives can include purchases made from unfamiliar locations, atypical transaction sizes or frequencies, and integration issues with digital wallets or buy now, pay later (BNPL) services. As mobile and cross-border shopping grows among consumer habits, such safeguards can unintentionally penalise legitimate shoppers. 

For retailers, each false decline is more than a lost sale. They frustrate customers, who may go on to abandon their purchase and buying from the brand altogether, eroding long-term value. Nearly half of consumers would switch retailers after just one poor payment experience. In today’s market, with competitors just a click away, this churn can be devastating. 

Meanwhile, real fraudsters continue to bypass security measures, posing ongoing risks. Banks face higher service costs and, in turn, diminished trust when cardholders experience unwarranted declines. This ripple effect impacts the entire payments ecosystem, from card issuers to merchants, pushing the urgent need for balance. 

What’s causing the rise in false positives? 

Cross-border transactions often trigger alerts based on geographic risk factors, even when legitimate. Regulatory requirements also push fraud systems toward caution, sometimes at the expense of customer experience. 

Mobile commerce and app-based payments add further complexity. Devices and IP addresses frequently change, making it harder for traditional fraud detection systems to verify user’s without causing false alarms. As more consumers use multiple devices and payment apps, fraud detection must adapt to fragmented data points. 

Smarter solutions to a growing issue 

Reducing false positives calls for smarter, adaptive systems that balance risk with customer experience. Two approaches prove most effective: 

• Advanced AI and behavioural analytics: Machine learning models, trained on extensive transaction data, can help distinguish between normal customer variations and actual fraud. This minimises unnecessary declines while maintaining strong protection. 

• Risk-based authentication: Rather than blocking transactions outright, businesses can apply additional verification steps only when necessary. Biometric authentication or one-time passcodes verify genuine shoppers. If doubt arises over a transaction, retailers need steps in place to counter-check authenticity. 

Beyond technology, collaboration is key. Sharing fraud intelligence among merchants, banks, and payment processors creates a more holistic view of emerging threats, reducing both false positives and real fraud. 

Minimising false declines, maximising trust and revenue 

Retailers need detailed customer insights – combining purchase history, device data, and behavioural patterns – to identify returning shoppers, even as habits shift. Investing in real-time tools for monitoring and decision-making helps flag highly suspicious transactions while giving loyal customers a seamless experience.