Interview With Dan Pinto – CEO and Co-founder of Fingerprint by Shauli Zacks
Shauli Zacks
Published on: May 6, 2025
SafetyDetectives recently sat down with Dan Pinto, the CEO and Co-founder of Fingerprint, to discuss how the company is redefining online fraud prevention. What began as an open-source project has become a cutting-edge device intelligence platform that empowers businesses to detect sophisticated threats—even when attackers use VPNs, virtual machines, or incognito mode. In this interview, Pinto shares how Fingerprint’s Smart Signals and real-time insights help security teams stay one step ahead of AI-driven fraud while preserving a seamless user experience.
Can you introduce yourself and explain what Fingerprint is, and what sets it apart from other fraud prevention platforms in the market today?
I’m Dan Pinto, CEO and Co-founder at Fingerprint. I started my career in software engineering, which led to an interest in creating bots and eventually entrepreneurship. After launching several small startups, I co-founded Fingerprint with Valentin Vasilyev. What started as his open-source project has evolved into what Fingerprint is today—the leading device intelligence platform for fraud prevention.
Fingerprint enables enterprises to identify users across web and native mobile applications with industry-leading accuracy, which sets us apart in the industry. Our platform detects sophisticated types of fraud by uniquely identifying devices and browsers, even when users try to hide behind VPNs or incognito mode. Most of our customers use the technology we provide to prevent fraud from impacting their services.
Fingerprint empowers teams with high-quality, real-time signals that help accurately identify malicious visitors while offering seamless experiences for trusted users. For example, our Smart Signals provide real-time, actionable signals about a user’s device—such as signs of tampering, VPN and incognito mode, and virtual enviornments—delivering valuable data and insights unmatched by other platforms.
What are some of the most common digital fraud tactics you’re seeing right now, and how is Fingerprint helping businesses stay ahead of them?
Today, the most common and damaging digital fraud tactics are phishing, online payment fraud, and account takeover attacks—now accelerated by AI. Bad actors are using AI-powered tools and increasingly sophisticated bots to automate and scale these familiar attack methods, causing greater harm faster. In the past, we have seen fraudsters leverage bots to carry out these attacks, and while we do expect to see more from AI agents in fraud schemes, they’re still too expensive and inefficient for widespread use today when compared to bots.
Fingerprint helps businesses stay secure by identifying devices with high accuracy, enabling businesses to detect and block sophisticated bot traffic without disrupting the user experience. Fingerprint’s Smart Signals, such as Virtual Machine Detection, Velocity Signals, and High-Activity Device Detection, surface suspicious behavior associated with AI-powered fraud attacks or bots, efficiently alerting teams of attempted fraud. As fraud techniques evolve, businesses can stay ahead by using device intelligence technology that enables their fraud and risk teams to correctly and quickly identify and prevent a multitude of attacks
reCAPTCHA used to be the go-to solution for bot detection, but it’s losing effectiveness. What’s changed, and why is device intelligence a better answer today?
Advances in AI, like image-recognition models, now allow bots to defeat visual reCAPTCHAs nearly 100% of the time. Meanwhile, the mean time for humans to solve them is about 10 seconds. Making reCAPTCHAs harder to solve is not a viable solution since it would just frustrate real users and impact conversion rates.
With device intelligence, organizations can continue efficiently moving forward, even with the increased use of AI-powered bots. Instead of interrupting users with a reCAPTCHA challenge or one-time password requirement, device intelligence works behind the scenes by analyzing hundreds of real-time device and browser signals to accurately distinguish humans from bots. Device intelligence provides organizations with actionable, real-time signals to accurately detect fraud, without slowing down genuine users. As bot technology gets smarter, the tools to stop them must evolve too, and device intelligence is leading the way.
Geolocation compliance is becoming a huge concern across sectors like finance, gaming, and healthcare. How does Fingerprint help companies meet these complex requirements without hurting usability?
As geolocation compliance becomes a priority across industries worldwide, businesses face the challenge of enforcing location-based restrictions without alienating legitimate users. Fingerprint achieves this by offering a layered approach to detection that goes beyond basic IP blocking.
Fingerprint’s Smart Signals—including IP Geolocation Detection, VPN Detection, and Geolocation Spoofing Detection—not only to identify fake locations, but pinpoint a visitor’s true location. This layered detection strategy reduces false positives and false negatives, ensuring that legitimate users aren’t blocked and restricted users are not allowed access.
Fingerprint also generates a stable, unique visitor ID for every browser or mobile device that accesses a site or app. This visitor ID remains consistent for weeks and months, even if users clear cookies, switch IPs, or use incognito mode. This allows companies to continuously monitor and verify user locations without requiring repeated logins or disruptive authentication steps.
By combining Smart Signals with the visitor ID, Fingerprint enables businesses to stay ahead of rapidly evolving regulations, without sacrificing user experience, customer trust, or account security.
A lot of security tools add friction to the user journey. How does Fingerprint strike that balance between fraud prevention and a seamless user experience?
Visitors don’t want to go through multi-factor authentication or complete a reCAPTCHA challenge every time they return to a site or relaunch an app—it creates unneeded friction and frustration. To help streamline the login process, many companies turn to cookies or IP addresses to identify returning users and personalize their experiences. However, cookies can be deleted, and IP addresses can be hidden via VPNs. This creates challenges for companies: Without the ability to accurately recognize returning users, even trusted customers are forced through friction-filled experiences like repeated verification steps, onboarding pop-ups, and re-entering preferred settings. Over time, these disruptions can lead to user frustration and abandonment, ultimately impacting revenue.
Fingerprint’s non-reliance on cookies or repetitive authentication methods enables companies to effectively prevent fraud and deliver optimal user experiences.
By gathering and analyzing 100+ signals from browser, device, and network environments, Fingerprint generates a stable, unique visitor ID that remains unchanged even through cookie clearing, private browsing, or network changes. This capability allows companies to confidently identify trusted users and tailor their experiences, speeding up logins, personalizing content, and eliminating the need for multi-factor authentication requirements. Meanwhile, Fingerprint’s advanced Smart Signals help detect and mitigate suspicious activity, alerting security teams only when real risk is detected.
As AI continues to evolve, how do you see the role of device intelligence changing in the future of online security and identity verification?
Device intelligence will play an ever-increasing critical role in distinguishing between human users, bots, and increasingly sophisticated AI agents. While today’s threats are still largely dominated by bots—which remain faster, cheaper, and, therefore, more damaging—that could shift as AI agents’ capabilities improve and become widespread.
Detecting AI agents today is challenging for organizations because many are designed to mimic human behavior. However, bot detection technology is already evolving to meet this complexity. For example, by collecting large amounts of browser data that bots leak, including errors, network overrides, browser attribute inconsistencies, API changes, and more, our Bot Detection Smart Signal enables organizations to reliably distinguish human users from automated visitors so companies can quickly take appropriate action to ask for additional human verification when needed to prevent fraud. Although systems can’t currently guarantee 100% detection yet, device intelligence will become essential for maintaining security and trust as AI-driven interactions grow.
In the future, as AI agents become more common, browsers and websites will be optimized to accommodate them. Businesses will need to differentiate human users from agents based on the very different ways they interact with the web. The development of AI agents will drive the next evolution of device intelligence, where user behavior itself becomes the key to detecting malicious actors and preserving trust online.
