# Deepfake detection

Generative AI is making it easier than ever before to create synthetic images and videos. Secure your business against evolving deepfakes with advanced identity verification technology.

A growing challenge

## The rise of deepfakes

Deepfakes are digitally manipulated images and videos created with generative AI. Once a novelty, they are now a serious fraud weapon. With this technology evolving rapidly, many legacy verification systems are struggling to keep up.

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Difficult to detect

68% of people cannot distinguish between a real image and a deepfake.

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A costly challenge

AI-enabled fraud losses are forecast to surge from $12.3B in 2023 to $40B by 2027.

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Language limitations & special characters

An AI deepfake tool can cost under $20/month, and a convincing fake can be generated in just 35 seconds.

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Reading tricky symbols

Deepfake incidents in fintech skyrocketed by 700% in 2023 alone.

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## How fraudsters leverage deepfakes to commit identity fraud

Malicious actors are exploiting the ready availability of AI tools to deceive both individuals and automated systems.

Generating synthetic and deepfaked identities

**Fraudsters** use generative AI tools to produce realistic images and videos, from face swaps and morphs to entirely fake identities. These synthetic assets are the building blocks of large-scale fraud.

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Injecting deepfakes into an IDV flow

**Fraudsters** deceive identity verification systems with digital attacks that replace genuine camera feeds with manipulated videos or images, simulating legitimate verification to open fraudulent accounts.

## Start shielding against deepfakes today

Transform your defenses to meet emerging, AI-enabled fraud vectors with Incode’s deepfake detection.

Our technology

## How our deepfake detection works

Incode protects against deepfakes with multi-layered defenses that combine AI detection, government database verification, and continuous fraud research.

### Preventing injection attacks

Incode stops fraud at the root. Our native SDKs block device emulation and virtual cameras before the capture process even starts.

### Detecting deepfake fraud attempts

Advanced AI analyzes biometric and visual signals such as blurriness, iris presentation, light reflection, and texture anomalies to identify synthetic images and videos.

### Verifying against the Government System of Record (GSOR)

Incode partners with government identity issuers worldwide to enable deterministic verifications, surpassing traditional methods in accuracy.

### Continuous AI fraud research

Our in-house R&D team and Fraud Lab continuously train AI and ML models with real-world data, strengthening detection against the latest deepfake techniques.

Business benefits

## Why Incode?

Incode helps your business confidently detect and prevent AI-driven deepfake incidents, so your customers remain protected and your operations secure.

**Holistic protection**  
Every interaction is verified as a real, live person, effectively reducing the risk of sophisticated deepfake attacks.

**Unmatched accuracy**  
Advanced facial recognition and biometric matching deliver higher precision than legacy verification methods, reducing costly false positives.

**Multi-layered defense**  
Verification processes analyze both biometric signals and identification documents, detecting even subtle signs of synthetic manipulation.

**Real-time fraud detection**  
The Incode Fraud Network analyzes millions of data points instantly to stop suspicious activity before it impacts your business.

**Frictionless user experience**  
Incode balances security with speed, enabling seamless onboarding and reducing user drop-offs while maintaining compliance.

## Industry-leading liveness detection and identity verification

Incode is an industry leader in identity verification, committed to the highest standards of data protection and security.

## Incode leads G2’s Index for Identity Verification with top customer ratings

### Frequently Asked Questions

### What is deepfake detection?

Deepfake detection is the process of identifying AI-generated synthetic media — altered videos, images, or audio — used to impersonate real people. In identity verification, it prevents fraudsters from using deepfakes to bypass biometric checks.

### How does AI deepfake detection work?

AI deepfake detectors analyze visual signals, pixel-level artifacts, temporal inconsistencies, and biological signals (like subtle blood flow patterns in skin) that are absent or distorted in synthetic media. Multi-layer models catch both naive and sophisticated deepfakes.

### Why is deepfake detection important for businesses?

Deepfake incidents in fintech skyrocketed 700% in 2023, and AI-enabled fraud losses are forecast to rise from $12.3B in 2023 to $40B by 2027. Without deepfake detection, any biometric onboarding or authentication system is vulnerable to impersonation attacks.

### Can deepfake detection stop account takeover fraud?

Yes. Deepfake detection integrated into biometric re-authentication catches impersonation attempts at login, MFA reset, and password recovery — the most common account takeover vectors exploiting biometric systems.

### What types of deepfakes can be detected?

Leading detection systems cover face swaps, AI-generated synthetic faces, video injection attacks (virtual cameras), and morphed identity documents. Incode's Deepsight platform detects all major categories with a 68x better false-positive rate in identity verification compared to the next-best commercial technology.