Fingerprint Releases New Analysis on Neobanks, BNPL and Fraud

CHICAGO--(BUSINESS WIRE)--Fingerprint, a leader in device intelligence, today released its latest report, "Scaling Trust in Digital Finance." The research highlights an inflection point for neobanks: digital-first institutions have become primary targets for sophisticated fraud syndicates using AI-driven synthetic identities and advanced account takeover (ATO) techniques.

Digital-first financial institutions are transitioning from secondary tools to primary banking relationships. The number of neobanking customers worldwide has reached approximately 1.1 billion, up 30% in just 18 months. This rapid scale has fundamentally reshaped the fraud surface.

Fingerprint’s report highlights a shift from isolated fraud incidents to coordinated, AI-enabled schemes.

Key findings include:

• Synthetic Identity Crisis: Fraudsters are increasingly using a mix of real and fabricated data to bypass onboarding checks, with losses projected to exceed $23 billion by 2030.
• APP Fraud Surge: Authorized Push Payment (APP) fraud, in which users are manipulated into authorizing transactions, could reach $18.2 billion by 2028 if AI-driven scams continue to intensify.
• The BNPL Risk: Fraud rates in Buy Now, Pay Later (BNPL) transactions are now up to six times higher than traditional credit card fraud, driven by streamlined onboarding and high-speed approvals.

Scaling Trust in Digital Finance argues that traditional, point-in-time fraud checks (like those at login or signup) are no longer sufficient in 2026. With 51% of all web traffic now automated, legacy solutions generate excessive noise.

Click here to view the full report.

About Fingerprint

Fingerprint detects the intent of human and agentic visitors. Our device intelligence platform identifies over 1 billion unique devices every month and processes hundreds of signals to help fraud teams distinguish trusted visitors from bad actors at speed and scale. Over 6,000 companies, including innovators like Dropbox, checkout.com and NeuroID, use Fingerprint every day to recognize high-risk activity in real time, prevent fraud attacks and deliver frictionless user experiences. Learn more at https://fingerprint.com/.

FAQ

What is the biggest fraud threat identified in the report?

While many threats are growing, Fingerprint’s report highlights the industrialization of fraud. Attackers are using AI and automation to probe systems at scale, making synthetic identities and coordinated scams much harder to detect with traditional tools.

How does device intelligence differ from traditional fraud prevention?

Traditional tools often act as checkpoints that reset at every login. Device intelligence provides persistent insights by connecting signals across onboarding, access and payments. This lets financial institutions see whether the same device is being used for a hundred different "unique" accounts.

Does adding more fraud prevention always mean more friction for the user?

Not necessarily. Fingerprint’s report explains that conversion-safe prevention relies on signal quality over rule complexity. When signals are strong and persistent, institutions can intervene selectively for high-risk activity and devices while providing legitimate users with seamless experiences.