S&P 500 Banking Partner

Client Case Study

Streamlined onboarding and account recovery with enhanced fraud-prevention methods for an S&P 500 bank client


Improving customer experience and security for one of America’s largest credit card issuing banks

With a global customer base made up of tens of millions of active accounts, the company maintains an industry-leading stance in financial technology innovation. This enables them to reach their customers and end users with the best services possible, all while protecting the security of everyone involved. Trust Stamp worked alongside the bank to deploy a new approach to risk management and customer experience in an evolving world of digital finance.

The solution needed to optimize existing resources and provide a tangible impact in addressing the following problems with fraud, seen throughout the online banking space: 

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1. Keeping bad actors out

Banks are experiencing increasing rates and types of synthetic identity fraud and account takeover attacks due to greater numbers of consumers migrating to digital channels.

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2. Letting more good customers in

In an effort to reduce the incidence of fraud, banks may erroneously flag applications as high-risk, denying even legitimate transactions. Customers must prove their identities to clear these flags, but traditional tools can take over five business days to complete.


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Deter, detect and prevent identity fraud

Our AI identified three organized fraud rings in 2019 alone! In one sample of 7,915 applicants, we identified 63 unique fraudsters and referred 33 more for investigation

Recover previously lost customers

In a sample of existing customers whose accounts were closed for failing legacy authentication methods, 83% of the accounts were reopened

Onboard more genuine users with an improved pass rate

In a sample of new account applicants previously declined for failing legacy identity authentication methods, 81% of the applications were approved

How we helped

Our solution

Trust Stamp collaborated with the bank to implement biometric identity verification, document validation, and duplicate detection technologies throughout their identity architecture.

The bank implemented this framework into their onboarding and account recovery processes to enhance security with robust privacy and fraud-prevention measures in the touchpoints that present the most common and potentially disastrous opportunities for successful fraud attempts: when a financial institution and an individual first enter a business relationship, and when a user is unable to provide their existing access credentials.

Trust Stamp facial biometric capture with proof-of-liveness technology

Analyze biometrics

The customer uses their mobile phone to capture a selfie video; presentation-attack-detection including proof-of-liveness tests analyze authenticity

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Trust Stamp mobile ID document capture and verification

Validate the ID document

The customer captures a photo of their ID; multiple anti-spoofing tests check for print or device display attacks, along with other indicators of falsified documents

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Protect sensitive data

Trust Stamp's deep neural networks turn any sensitive data into secure tokens that are safe to use, store, and share as privacy-preserving identifiers

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Block fraudsters

New customer enrollments are compared to the entire user base to detect synthetic or stolen identities, for the next level of fraud prevention

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The program was deemed a success and has expanded to other customers and business lines within the bank. In a single year, the customer reported significant and substantial new sales revenue, hard fraud savings and fraud deterrence.


Deployment outcomes

For the bank

  • Reduced losses to fraud

  • Improved sales with faster onboarding

  • Increased customer retention

  • Increased efficiency / reduced need for manual verification

  • Greater card spend

For their customers

  • A frictionless, user-friendly verification experience

  • Authentication completed in minutes

  • Improved account security and personal data privac­y

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