In 2025, fraud is no longer just about stolen credentials or leaked data. With AI tools now capable of generating realistic faces, voices, and identities from scratch, fraudsters can create convincing digital personas in mere minutes. This shift has moved deepfakes from online novelty into a real business risk.

Today, deepfakes are actively used to bypass KYC checks, impersonate legitimate users, and manipulate financial transactions. Over 8 million deepfake videos were shared globally in 2025 alone, demonstrating the rapid growth of this technology. 

If you run a fintech or digital platform, the stakes are even higher. Remote onboarding and instant transactions create the perfect conditions for deepfake-enabled fraud to slip through.

 This article breaks down how deepfake fraud works in practice, where your platform is most vulnerable, and how you can detect and prevent it.

What Deepfake Fraud Really Means in 2025

Over the years, deepfakes have evolved from a tool for making entertaining videos into a way fraudsters impersonate people or bypass identity checks. Unlike traditional fraud, these synthetic identities don’t require stolen credentials and are much harder for manual reviews or simple passwords to catch. 

2025 has become a tipping point because advanced AI tools are now widely accessible. Platforms like DeepFaceLab and Synthesia can generate realistic images and produce fake ID documents in minutes.  Digital businesses now face the challenge of spotting AI-generated faces, videos, and documents that can pass surface-level checks.

How Deepfakes Are Used in Real Fraud Scenarios

Now let’s take a look at real‑life scenarios where deepfake fraud is already being used to trick businesses and bypass identity checks.

1. Identity Fraud During Digital Onboarding

Fraudsters are using AI to generate fake faces and videos that look real enough to slip past onboarding systems. In a 2024 study, Indonesian banks reported over 1,100 attempts where synthetic facial images were used to bypass digital KYC systems, using virtual camera software to simulate a live person in front of verification cameras.

How it works:

• AI‑generated faces used for selfie and liveness checks
• Deepfake videos replayed to bypass facial verification
• Synthetic IDs paired with fake biometrics

Business impact: Fake accounts can be used later to commit fraud or abuse platform features, putting your business and customers at risk.

2. Payment & Authorised Push Payment (APP) Fraud

Deepfakes are also being used to impersonate executives and trick employees into approving large payments that feel “legitimate.” A notable Hong Kong Arup Engineering fraud case in 2024  involved a finance worker joining a video call where everyone, including the CFO, was a deepfake, resulting in transfers totalling over $25 million to fraudster‑controlled accounts. 

How it works:

• Deepfake voice or video impersonating CEOs or finance leaders
• Urgent payment requests framed as internal approvals
• Transactions appear as authorised.

Business impact: These scams result in large transfers that are difficult to reverse and can have a severe impact on revenue.

3. Account Takeover & Customer Support Manipulation

Deepfake voices and AI‑generated personas can trick support teams into thinking they’re talking to real customers, leading to unauthorised access. Fraudsters clone customer voices or mimic interaction patterns, convincing support agents to reset credentials or change account details.

How it works:

• Deepfake voices impersonating customers
• AI chatbots mimicking real user behaviour
• Social engineering supports teams in resetting access

Business impact: Legitimate accounts get hijacked, eroding customer trust and increasing fraud losses.

4. Chargeback & Payment Dispute Fraud

Deepfake identities can also be used to make purchases and then challenge transactions using convincing AI content. Criminals create convincing deepfake IDs and documentation to support false claims that an order was never received or wasn’t authorised, leading to chargebacks.

How it works:

• Deepfake IDs or videos are used to support dispute claims
• Multiple accounts were created for repeat chargeback attempts
• Exploits refund and payment dispute processes

Business impact: Businesses lose revenue and incur higher processing fees from false disputes and repeated chargebacks.

Why Traditional Fraud Controls Fail Against Deepfakes

Traditional fraud checks worked when scams mostly involved stolen credentials or simple identity manipulation. But over time, AI‑powered deepfakes have made it far less effective. Here’s why:

1. Document checks alone are no longer reliable

AI can generate highly realistic IDs that pass standard visual inspections. Even trained human reviewers can be fooled, with a 2021 study from the University of Cambridge showing that deepfake-generated faces can bypass verification systems up to 60% of the time. This makes relying only on document validation a weak line of defence.

2. Manual reviews don’t scale against AI-generated inputs

Fraud teams struggle with the growing volume of synthetic identities. What might take a few minutes per case can multiply into thousands of suspicious accounts, creating bottlenecks and increasing the likelihood of missed fraud. Automated solutions with behavioural monitoring are now essential for keeping up with the speed and scale of deepfake attacks.

3. Static rules fail against adaptive fraud tactics

Deepfake fraud constantly evolves, with new AI tools enabling fraudsters to refine their techniques quickly. Fixed thresholds or rigid “if/then” rules become outdated almost as soon as they’re implemented, missing creative or unexpected attack patterns. Businesses need updated systems to respond to these adaptive threats.
 

Key takeaway: Deepfake fraud is rarely a single event; it layers over multiple steps and interactions. Businesses must move beyond one-time checks and static identity check rules to stay ahead.

How You Can Detect and Prevent Deepfake Fraud with Dojah

With deepfake fraud on the rise, you need a smarter way to verify users and protect your platform from synthetic identities. Here’s how Dojah’s product suite helps you spot and prevent deepfake fraud at every step:

1. Identity & Document Verification 

With Dojah’s EasyOnboard, you can validate government IDs and cross-check documents that the person registering is authentic. This prevents fake accounts from slipping through, even if someone tries to use a stolen or AI-generated ID.

 For example, you can instantly detect a mismatched document or manipulated ID before an account is created on your digital platform.

2. Behavioural Risk Monitoring 

Dojah’s Profiled Risk continuously monitors user behaviour to detect unusual patterns that signal potential deepfake fraud. It tracks interaction speed, device and location inconsistencies, and multiple failed verification attempts.

 For instance, if a user suddenly logs in from two different countries within hours or shows strange transaction activity, Profiled Risk flags it immediately, allowing your team to intervene before fraud occurs.

3. Continuous Monitoring Across Transactions

Protecting your platform doesn’t stop at onboarding. Dojah’s EasyDetect monitors sessions and transactions in real-time, helping to catch unusual behaviour or high-risk activity. Even if a fraudster passes initial checks, ongoing monitoring ensures they can’t hide in plain sight.

 A previously verified account attempting unusually large transfers can be flagged automatically for review, preventing potential losses.

4. Biometric & Liveness Verification 

Deepfake fraud includes both document and video formats; fraudsters use AI to mimic real people on camera. EasyOnboard’s biometric and liveness checks confirm that the person behind the ID is actually present and an authentic human. 

This helps prevent synthetic identities from sneaking through while keeping onboarding smooth for legitimate users.

Prevent Deepfake Fraud and Stay Ahead with Dojah

Deepfake fraud highlights how quickly identity threats are evolving and why traditional, one-time checks can no longer protect digital platforms. As fraudsters adopt AI, businesses need smarter verification methods to spot synthetic identities before they cause damage.

Just like teams dealing with onboarding fraud and account takeovers, your fintech or digital platform can reduce risk by combining identity verification and continuous risk detection with Dojah. 

Trusted by over 500 businesses in Africa and with more than 50 million identities verified, Dojah helps digital platforms in Africa detect fake identities early, monitor behaviour over time as they scale.

Protect your platform from synthetic identities before they cause damage. Book a demo to see how Dojah protects your platform against deepfake fraud