About the company

ZBD is a fintech-meets-gaming platform that enables users to earn Bitcoin through gameplay and rewards. With a fast-growing user base, keeping fraud in check — especially multi-accounting — was critical to protecting both their bottom line and community trust.

Challenge: Stopping multi-accounting abuse at scale

As a rewards-based app, ZBD was a prime target for fraudsters attempting to create thousands of fake accounts to farm rewards. “We’d see a random spike — like 10,000% more accounts created in an hour — and have to manually investigate and suspend users,” said Ben Rice, product manager at ZBD. These attacks not only skewed growth metrics but created downstream operational pain and exposed the business to financial risk.

Why device fingerprinting was a no-brainer

From day one, the team knew they needed device fingerprinting as a foundational part of their fraud stack. “We always knew we’d need something like Fingerprint,” Rice said. “It was just a matter of time. When we were ready, it was a no-brainer.”

ZBD chose Fingerprint because the platform stood out for:

• Best-in-class visitor identification via persistent, highly accurate device fingerprinting
• Clean, developer-friendly documentation
• Additional signals that reveal potentially risky context — such as VPN usage, or jailbreaking and rooting detection 

“We wanted to find the best at fingerprinting — not an 'everything platform' that kind of does it,” Rice explained. “Plus, Fingerprint’s documentation was miles ahead of other vendors, which made implementation easier.”

How ZBD uses Fingerprint

ZBD integrated Fingerprint’s SDK into their mobile app, using the Visitor ID to validate account creation attempts. Fingerprint’s Visitor ID is a stable, device-linked identifier that allows ZBD to uniquely recognize a physical device, even across incognito sessions or IP changes.

This means a single fraudster can’t create dozens or hundreds of accounts from the same phone or emulator. Every account creation attempt must come from a unique device with a valid Fingerprint Visitor ID. If the same device attempts to register multiple accounts, ZBD’s system can detect and block it in real time.

Turning fraud incidents into intelligence with Smart Signals

In addition to Visitor ID, ZBD uses Smart Signals to enrich their internal fraud models. When a fraudulent event occurs — such as a confirmed case of multi-accounting — the team investigates the associated visitor and device profile. They analyze which Smart Signals were triggered and look for patterns across repeat offenders.

“We take that profile — looking at which Smart Signals fired for this fraudster — and feed it back into our model. That way, we’re not just stopping one fraudster. We’re training our system to spot others who look like them,” Rice explained.

Over time, this approach has helped ZBD go beyond reactive rule-setting and move toward a more adaptive, predictive fraud prevention strategy. Rather than writing static rules for each signal, they evaluate a broader picture, leveraging Fingerprint’s raw data to understand a user's environment and risk posture holistically.

“Some signals are clear red flags, like a jailbroken phone. But the real power comes from putting everything together and building a full profile so we can make smarter decisions without false positives,” Rice said.

The impact: 95% drop in multi-accounting

Since implementing Fingerprint, ZBD has seen a dramatic reduction in fraudulent activity. Fingerprint has also helped the team spend less time investigating spikes in account activity, enabling them to focus on scaling their platform instead of playing defense.