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Gartner® names Reality Defender a Market Shaper in deepfake detection, June 2026
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Insight
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Brian Levin
CRO
Published Nov 5, 2025 Updated Nov 9, 2026
In September 2025, the Monetary Authority of Singapore (MAS) released a comprehensive analysis of how deepfakes are being used against financial institutions. The information paper, Cyber Risks Associated with Deepfakes, groups the risk into three areas: deepfakes that defeat biometric authentication, social engineering and impersonation scams, and misinformation that damages market and brand confidence. For each one, MAS sets out the controls it expects institutions to consider.
Here’s what each threat looks like and the controls MAS recommends for each.
Facial recognition and selfie checks were built on the assumption that a face on camera belongs to a real person. Deepfakes break that assumption, and MAS documents several cases where biometric authentication systems were beaten.
Attackers are no longer only holding a fake face up to a camera. Injection attacks feed synthetic video straight into the verification flow and bypass the camera entirely, which is why liveness detection techniques alone are no longer enough.
MAS recommends that institutions:
Deepfake technology amplifies traditional social engineering. A request that would once have come by email now arrives as a video call with a familiar face and voice.
In January 2024, every colleague on one Hong Kong video call was a deepfake. Engineering firm Arup lost $25M when an employee joined a video call with deepfaked versions of the CFO and colleagues and made 15 transfers.
In March 2025, a finance director at a company in Singapore was contacted on WhatsApp and invited to a Zoom call with someone impersonating the company’s CEO. The director was told to transfer more than US$499,000, and did. The director became suspicious only when a further US$1.4 million transfer was requested and alerted the bank. Singapore and Hong Kong authorities recovered the funds.
The same techniques reach beyond payments. In July 2024, a US security company discovered it had hired a North Korean operative who used a stolen identity and an AI-altered photo to pass four video interviews. Evidence shows deepfakes are infiltrating recruitment processes, giving attackers insider access from day one.
MAS recommends that institutions:
Deepfakes don’t need to touch an institution’s systems to hurt it. A convincing fake can move markets or damage trust in minutes.
Deepfakes don’t need to touch an institution’s systems to hurt it. A convincing deepfake of an executive, a spokesperson or a public official can move markets or damage trust in minutes.
MAS recommends that institutions:
| Threat | What it looks like | Controls MAS recommends |
|---|---|---|
| Biometric bypass | Deepfaked faces or injected video pass KYC and login checks | Document tamper checks, liveness detection, deepfake security testing, endpoint protection |
| Social engineering | A cloned face or voice of an executive requests a payment | Awareness training, sender verification, audio and endpoint detection, MFA, separation of duties |
| Misinformation | Fake images or video move markets or damage a brand | Brand-abuse monitoring, deepfake incident response, sector information sharing |
No. It’s an information paper, published on 18 September 2025 (reference MAS/TCRS/2025/06). It sets out MAS’s view of the threat and the controls it recommends, and the controls it recommends, and it doesn’t create new requirements.
Deepfakes that defeat biometric authentication, social engineering and impersonation scams, and misinformation or disinformation that damages market and brand confidence.
Checking identity documents for tampering, adding liveness detection to facial authentication, testing regularly against deepfake attacks, and protecting endpoints against injection attacks.
MAS’s recommendations span fraud, security, compliance and communications teams, from onboarding controls to incident response and brand monitoring. No single team covers all three threats on its own.
Reality Defender detects AI-generated voice, video, and images in the calls, video meetings, and uploaded files where these attacks start, through our platform and API. Each check returns Authentic, Suspicious, or Manipulated, so the onboarding or fraud team decides on a signal instead of a guess.
Talk to our team about detecting deepfakes in customer onboarding.