When it comes to digital commerce, payers and businesses are clear on one thing: they want checkout to be fast, safe and simple.
But while clicking “pay” and moving on sounds great, in practice it’s rarely that smooth. Checkout friction — the dreaded lags, glitches and payment hurdles — continues to frustrate eager shoppers who just want to finish their purchase and get on with their day.
One major culprit? Payment security protocols that aren’t exactly user-friendly. Sure, shoppers want protection, but they also want speed. Multi-step verifications, lengthy payment forms, and outdated CAPTCHAs can feel more like running an obstacle course than shopping.
Against that backdrop, soft-linked signals — dynamic, adaptable data points like device type, location and behavior, integrated within a network to verify transactions — are becoming recognized as critical to the future of secure, seamless payments.
Unlike traditional rigid forms of authentication, soft-linked signals provide a flexible yet powerful layer of security by drawing on real-time behavioral, environmental, and contextual data that help identify and thwart fraud before it occurs.
And they are increasingly doing it all through artificial intelligence (AI) models that can analyze end-user actions from initial login to checkout.
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Traditional security measures, like OTPs or hardware tokens, often disrupt the user experience. For instance, waiting for a text message or using a separate token device for each transaction adds friction.
“Around 27% of carts are abandoned because the process is too complex and slow,” Jennifer Marriner, executive vice president of global acceptance solutions at Mastercard, told PYMNTS, noting that for merchants, each abandoned cart represents a lost opportunity, underscoring the need for streamlined processes that improve conversion rates without compromising security.
Soft-linked signals, however, assess user intent by analyzing natural behavior, seamlessly integrating security into the payment flow by creating a background layer of verification that operates without the user’s explicit involvement.
This approach enables a real-time evaluation of potential fraud risk without demanding extra actions from the user, maintaining a frictionless experience by creating a security web that is both harder for fraudsters to manipulate and easier for legitimate users to navigate. For instance, if a transaction occurs outside a user’s typical geographic area, or the pattern of their input deviates from the norm, the system can flag it for further review without imposing friction on the user.
By linking these data points with prior behaviors and contextual factors, payment platforms can more accurately detect anomalies and reduce the reliance on static passwords or PINs, which are prone to compromise.
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AI plays a role in the effectiveness and adoption of soft-linked signals, making these dynamic security measures more intelligent and responsive to real-time threats. By leveraging advanced machine learning algorithms, AI can sift through large volumes of contextual data — such as device type, location, time of access, and behavioral patterns — to detect anomalies and validate transactions with precision.
“AI, machine learning, large language modeling will help us better combat fraud by making fraud detection more precise, while at the same time proving more adaptive to the new threats,” Max Spivakovsky, senior director of strategy and operations, global payments risk management and onboarding at Galileo, told PYMNTS.
One of the biggest challenges in payment security is balancing the need for speed with the need for security. AI-enabled soft-linked signals can assess risk in real time, without adding latency to the transaction process. By analyzing hundreds of data points instantly, AI can make split-second decisions on whether to approve, flag or block a transaction.
“We’ve needed to rethink, from the ground up, how we architect security,” Mastercard Chief Product Officer Jorn Lambert told PYMNTS TV.
AI excels at recognizing outliers in large datasets, which makes it ideal for detecting anomalies across multiple transactions and accounts. For payment providers processing thousands of transactions per minute, AI can flag potentially fraudulent activity based on subtle indicators that would be challenging to detect manually or with rule-based systems alone.
Ultimately, AI enables soft-linked signals to balance security with user convenience. For low-risk activities, AI can ensure a frictionless experience by reducing redundant security checks, while high-risk transactions can be flagged for extra scrutiny without unduly inconveniencing the user. This adaptability not only improves security but also enhances user satisfaction.
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