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

"Through cognitive analysis, BioCatch helps reduce instances of Account Opening fraud, which is particularly challenging to detect when the user is a new user and doesn’t have a historical digital footprint with the organization."

John Tolbert, Lead Analyst, KuppingerCole

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BioCatch Delivers Account Opening Protection to Help Your Organization:


How Can You Trust a New Customer You Have Never Seen Before?

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.

Cybercriminals input data differently from genuine users

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Cybercriminals
  • Dont’ have familiarity with data
  • Repeatedly delete and fix errors
  • Rely on copy and paste, or automated programs
  • Familiarity with new account opening process and online form
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Genuine Users
  • Different pace and navigation patterns
  • Display the use of long-term memory
  • Hesitate around fields criminals confidently fill
  • Use the AutoFill feature for personal details.

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:

Application Fluency:

How familiar is the user with the account application process?

Expert User Patterns:

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

Low Data Familiarity:

How familiar is the user with personal data?

Age Analysis

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

Additional Resources