Fingerprint: The Technology Behind One-click Checkouts

August 2026

Fintech & Payments

Lorien Carter

Senior Research Analyst

Marketplaces and retailers have been chasing after one-click checkouts for years. The ideal customer interaction is one that produces no friction between a customer’s decision to buy the product and their ability to carry it out. But how can websites deliver this while maintaining their responsibilities to prevent fraud? 

As a pioneer of the technology necessary to deliver this interaction, Fingerprint is behind the original open-source legacy code that identifies returning customers to websites and apps, and analyses users for fraud risk. We spoke with Valentin Vasilyev, Co-founder and CTO of Fingerprint, to explore the many applications of Fingerprint’s technology, and to learn about the wide variety of industries where Fingerprint underlies customer experience. 

The Technology Behind Customer Recognition

Arguably, the most valuable aspect of this technology is the ability to build customer profiles without relying solely on user logins. As the creator of the original open-source fingerprinting library, Fingerprint analyses hundreds of device signals to create a unique identifier; enabling websites to identify whether they have seen a visitor before. This helps localise the experience of the user without requiring them to sign in. For example, showing them their preferred payment method or personalised deals.

Cards used to be the default for online checkout, and remain one of the most universally accepted options. However, the time taken to fill out card details and billing address can harm checkout conversion rates, which has led merchants to turn to other options, such as integrating digital wallets at checkout. The simplicity provided by Google Pay and Apple Pay has sharply increased their market share in processing eCommerce transactions; causing card networks to lose out on data gained from direct transactions. 

This led to major credit card companies developing express checkout options that automatically fill in card information with one click; competing with the easy experience provided by digital wallets. While developing this technology, credit card companies struggled to recognise and authenticate the devices requesting payment without introducing additional friction. Fingerprint provides the technology needed to address this. 

Its capabilities extend beyond recognition and toward fraud controls. Fingerprint is able to identify Virtual Private Network (VPN) and proxy usage, geolocate devices, identify tampering, and match to IP blocklists. This helps businesses build a clearer picture of who is interacting with its services, and whether this activity is legitimate. 

In an environment where ordinary users are working to conceal their identity in response to increased tracking, the distinction between privacy-conscious users and fraudsters is becoming increasingly important. Whilst both sets use similar technologies, Fingerprint utilises multiple fine-tuned, real-time device signals to distinguish between ordinary users employing anti-detection measures and fraudulent actors attempting to evade detection. As regulators place greater responsibility on financial institutions and merchants to prevent fraudulent transactions, businesses face growing pressure to strengthen security, without adding friction to the customer journey. In this environment, the ability to block potential malicious actors without interrupting the shopping experience of regular customers is highly valuable.

Travel Agencies and Personalisation 

As discussed in our Fraud Detection and Prevention in Banking report, travel is a high-fraud environment. Fraudsters target this industry due to the high average value of transactions, and bookings made long in advance mean that fraud is often discovered too late to recover funds. 

One of Fingerprint’s customers is Booking.com, the largest global travel agency, which uses Fingerprint’s technology to block fraud and identify returning visitors. The rich customer data allows them to personalise customer experience by offering relevant deals and add-ons.

This is a key competitive differentiator for travel agencies, which operate on thin margins, and compete directly with airlines and hotels that are investing in encouraging direct customer bookings. 

Synthetic Identity Fraud

Another problem Fingerprint is working to solve is synthetic identity fraud; an escalating threat faced by banks when onboarding customers. This is a form of fraud where criminals combine genuine stolen information with fabricated details to create entirely new identities. These identities can be convincing enough to bypass basic onboarding checks and traditional verification methods, such as matching a selfie to a driver’s licence picture. 

Furthermore, the problem is ramping up, as technology improvements simplify the process of creating these false identities. For example, software allowing a person to overlay another face on the original to pass live verification methods. 

In recent years, there has been a spate of fines for neobanks and challenger banks that have failed to live up to their Know Your Customer requirements. For example, Monzo was fined £21 million in 2025 for systemic failings in crime control; failing to verify addresses and detect multiple account openings or synthetic identities. The detection of synthetic identities is made more difficult by those who use software to overlay their device to hide fraudulent software; masking signals and impersonating a different browser.

Fingerprint’s approach uplevels fraud protection by providing a passive identification overlayer that can detect browser tampering, cloned app usage, and geolocation spoofing. Device fingerprinting can help to confirm users’ identities without interrupting the customer experience or requiring extra steps for verification. As fraud becomes increasingly sophisticated, protections such as these become necessary to avoid further regulatory fines. 

Preparing for the Rise of AI Agents

One unique aspect of Fingerprint’s database is the ability to differentiate between bots and authorised AI agents. The traditional approach is to block all bots, which protects businesses from scrapers and malicious actors. However, this also blocks legitimate traffic that is automated through AI. While, at present, this may only result in a few false negatives, agentic AI traffic is forecast to drastically increase; with agentic commerce spend forecast to be $1.5 trillion globally by 2030. 

Fingerprint anticipates a future where people ask AI models to scour the Internet for clothes that match their style, or to plan holidays according to their tastes. For this future to be realised, enterprises must be able to distinguish between authorised AI agents and malicious bots. Fingerprint cryptographically verifies AI agents, including those from OpenAI and AWS’ AgentCore. This provides retailers with 100% certainty of the validity and intentions of the AI attempting to access their websites to conduct purchases on the behalf of legitimate customers. Vasilyev views this capability as a necessity for merchants; if retailers do not integrate these capabilities now, they may later end up capping their own growth.