Fraud prevention spending among neobanks, digital-only banks and FinTechs jumped 357% in a year, from $1.8 million to $8 million per institution, according to the PYMNTS Intelligence report “Scams Get Personal: Why Banks Pay More to Fight Fraud”. Average fraud losses rose more than 250%, from $800,000 to $2.8 million.

One measure moved in the opposite direction: The fraud-loss rate for these neobanks, digital banks and FinTechs fell 20%, from 0.90 to 0.72 basis points.

For neobanks, the three numbers define the trend. A smaller share of transaction value is being lost, but achieving that result now comes with a much larger prevention bill while absolute losses continue to rise.

Digital banks were already showing elevated fraud exposure. PYMNTS’ previous reporting indicated that, as evidenced in an earlier fraud study, neobanks had a 1.1-basis-point fraud-loss rate in 2025, compared with 0.8 basis points across the full sample. PYMNTS reported at the time that the exposure accompanied the speed and scale of digital-first models.

Fraud Looks More Like Legitimate Activity

Our latest data indicates that the type of fraud neobanks are trying to stop is also changing.

Scams in which customers were manipulated into acting rose to 22.4% of fraud dollars in 2026 from 12% a year earlier. Account takeover through compromised credentials reached 28.2%. Overall, more than half of fraud dollars now involve a legitimate login or customer manipulation, up from 27.6% two years ago.

Neobanks have built their businesses around digital account access and fast transactions, but the models offer up tempting attack surfaces that bad actors probe for vulnerabilities.

A recent incident involving Revolut shows how the same problem can extend beyond the customer channel.

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As PYMNTS detailed last month, an unauthorized third party used a legitimate government email domain to make fraudulent requests for customer information. Revolut said its systems and customer funds weren’t affected, but information belonging to a limited number of customers was exposed.

Digital fraud defenses have to evaluate more than whether a login or transaction is genuine. They also have to determine whether apparently legitimate requests and interactions can be trusted.

Neobanks Push Fraud Detection Earlier

Neobanks are putting more technology behind their bids to bolster defenses.

Behavioral analytics and device fingerprinting are now used by every institution in the PYMNTS Intelligence survey, while 96% use machine learning. Among neobanks and FinTechs using machine learning, 91% said it enables a proactive fraud strategy, up from just 19% in 2025.

Revolut offers one example of the scale involved. PYMNTS reported in April that its PRAGMA model was trained on 207 billion data points covering 25 months of customer activity. A smaller version is designed to support real-time fraud checks by analyzing sequences of financial activity.

The latest PYMNTS Intelligence numbers put a price on the push to expand and improve defenses. Neobanks and their digital peers cut their fraud-loss rate to 0.72 basis points, but prevention spending reached $8.02 million per institution and average losses reached $2.84 million.

Fraud losses can also affect neobanks by changing how consumers use them. PYMNTS Intelligence, in collaboration with Block, found that 28% of consumers whose households had lost money to a scam stopped opening and using neobank accounts or did so less often. For digital-only providers, fraud can hit both sides of the business: the cost of preventing and absorbing losses and consumers’ willingness to use the accounts themselves.

At PYMNTS Intelligence, we work with businesses to uncover insights that fuel intelligent, data-driven discussions on changing customer expectations, a more connected economy and the strategic shifts necessary to achieve outcomes. With rigorous research methodologies and unwavering commitment to objective quality, we offer trusted data to grow your business. As our partner, you’ll have access to our diverse team of PhDs, researchers, data analysts, number crunchers, subject matter veterans and editorial experts.