Account Opening Protection

When New Customers Are Not

BioCatch Account Opening Protection generates advanced behavioral insights to provide you with the real-time visibility you need to detect more fraud, introduce less friction, and acquire more customers.

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New Account Fraud In Numbers



Total losses attributed to new account fraud in 2021


Average loss per incident from credit card application fraud


Percent of financial institutions that experience fraud in the account opening process


Average loss per victim to identity fraud in 2021

Filter Out Criminals. Focus on Customers.

Through innovative research, a decade of data, and proven results, BioCatch risk models analyze a user’s physical and cognitive digital behavior to distinguish between genuine users and criminals in order to detect fraud and identity theft and to improve customer experience. By profiling user behaviors such as mouse movements, typing cadence, swipe patterns or device orientation, the BioCatch platform, powered by machine learning, identifies statistically observed norms for “good” and “bad” behavior.

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How One Bank Uses BioCatch to Reduce Fraud in Account Opening

“We really see that there is a clear difference between real customers and fraudsters. Since implementing BioCatch (Account Opening Protection), a lot of things have improved for the better. We can clearly identify certain fraud cases through BioCatch data. At the same time, we have fewer false rejections.”

Erik Scheil, Head of Fraud, TeamBank

HubSpot Video


Did You Know?

64% of confirmed account opening fraud cases detected by BioCatch showed behaviors indicating lack of familiarity with data.


Only BioCatch delivers insights on:

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    Application Fluency
    How familiar is the user with the account application process?

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    Expert User Patterns
    Does the user display advanced computer skills compared to the general population?

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    Low Data Familiarity
    How familiar is the user with personal data?

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    Bot Activity
    Are there behavioral anomalies present that indicate bot activity?

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    Age Analysis
    Do the human-device interactions align with the common behavior patterns associated with users of a certain age group?

Actionable Behavioral Insights Start Here

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