GenAI Fraud Detection

Defend against deepfake fraud attacks

Battle-tested AI technology to detect and prevent fake identities synthetically-generated by AI.

UNHCR logo Qatar logo KLM logo grupo salinas logo gopuff logo FAB logo
UNHCR logo Qatar logo KLM logo grupo salinas logo gopuff logo FAB logo
UNHCR logo Qatar logo KLM logo grupo salinas logo gopuff logo FAB logo

Evasive AI has turned fraud into a mainstream threat, making traditional defenses dangerously obsolete. 

Deepfakes are no longer niche; both organized networks and casual fraudsters use cheap tools to impersonate people, manipulate conversations, and erode digital trust. Costs are falling, quality is rising, and abuse is accelerating.

The real danger is blind spots. Most companies have little visibility into how exposed they already are, leaving them vulnerable to fraud, reputational damage, and regulatory scrutiny.

Benefits Microblink outpaces evolving GenAI attacks and deepfake fraud

Our proven, mature and innovative machine learning models detect synthetic ID documents and biometrics.

Proprietary Synthetic Data

Our in-house AI team creates over 100,000 synthetic IDs monthly, building an unmatched proprietary dataset for red hat anti-deepfake training and testing. This scale and diversity gives our machine-learning models a decisive edge against evolving fraud tactics.

Perfect Benchmark Results

Tested against the largest public, independent deepfake dataset backed by DHS, Microblink caught 100% of deepfakes with 0% false accepts. Performance held at a tolerance threshold aligned to an estimated FRR of 1.38–3.3%, setting a new standard for accuracy.

Adaptive Universal Defense

The Microblink universal intelligence platform delivers multi-layered protection, dynamically adapting to new attack vectors. Designed for resilience, it future-proofs enterprises against both today’s mainstream deepfake exploitation and tomorrow’s unknown fraud threats.

How To Measure Deepfake Detection

We pressure-tested Microblink against a US Department of Homeland Security-backed dataset.

Assess the result

Our Solution: Fluid Digital Certainty

Intelligence That Anticipates Threats – Our multi-layered Fraud Lab replicates attacks and builds countermeasures, preventing fraud patterns before they emerge and strengthening with every breach attempt.

Cross-Modal Learning Power – Dynamic liveness detection across documents, biometrics, and cards ensures smarter, adaptive defenses against stolen identities, account takeovers, and GenAI-driven fraud.

Proven Business Impact – 97% customer satisfaction, NPS of 74, 40% capture rate improvement, and 50% fraud reduction—protecting revenue, reputation, and long-term trust.

why microblink?

Our best-in-class universal identity intelligence platform is built for fluid digital certainty, leveraging our proprietary dynamic AI architecture to consistently surpass industry benchmarks in speed and accuracy.

97%

Customer satisfaction score

65 Million +

ID documents scanned every month

10+ years

of in-house R&D in AI for identity verification

Explore an interactive tour of the Microblink Platform, and download free SDK demo apps.

Go to demos
products Browse Microblink solutions
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Microblink Platform dashboard and card
Documento de identidad escaneado
Platform
All-in-one KYC/AML solution

No code workflow management, including ID card scanning and verification, biometrics, AML/CTF screening, PII data matching and risk signal.

Microblink Platform
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Example of ID
Documento de identidad verificado
BlinkID Verify
Document verification

A fully automated solution to quickly check and analyse if an ID is fake or real.

Learn more
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Example of credit card
Tarjeta de crédito escaneada
BlinkCard
Payment card scanning

Fast and accurate credit card scanning and checking that reduces card-not-present fraud and increases conversions.

Learn more

PREGUNTAS FRECUENTES

What is a deepfake in the context of fraud?

How can businesses prepare for evolving deepfake threats?

Why are deepfakes a growing threat to businesses?

How can deepfakes be detected in real time?

What types of algorithms are effective for deepfake detection?

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