How to detect Deepfake?
- Mariela
- Jul 3
- 3 min read
Updated: 6 hours ago
TL;DR
Basic training goes a long way. Train your team to recognize the most common signs of AI-generated fraud. Look for unnatural text, poor lip-sync, perfect lighting and composition, style of the image, blurry edges, and lighting that doesn't make sense. AI models still struggle with physics, often producing inconsistent shadows, reflections, and unrealistic light direction.
If your business processes large volumes of potentially fraudulent data, combine human expertise with AI-powered fraud detection and automated verification.
Synthetic fraud isn't new. Criminals have been forging documents, manipulating images, and creating fake identities for decades. What has changed is the speed, scale, and quality made possible by generative AI.
Today, creating convincing deepfake images requires little technical expertise. Popular generative AI tools, including models from OpenAI, Anthropic, and Midjourney, can be misused to produce realistic identity documents, receipts, fake news, and other fraudulent content in minutes.
Let's see what we can do about it!
Synthetic fraud has always been a thing
Way before generative AI was in the picture, bad actors were already working the system. They used Photoshop to create fake IDs, bought sketchy templates off dark web forums, and found ways to slip through the cracks of outdated KYC systems. Just check out this crazy story we followed through from the day one.
Manual review teams have been battling forged passports, mismatched selfies, and suspicious PDFs for years. The tools are changing, but the intention hasn’t.
What’s different now?
Fraud has gone from slow and manual to explosive and automated.
AI didn’t invent a new type of fraud, it just supercharged it.
What do the numbers say?
AI Fraud is exploding!
Think we’re exaggerating? The data speaks for itself:
Identity fraud rose 42% in 2024, fueled by fake documents and deepfake biometrics.
Face swap attacks: spiked 704% in just six months.
Over 30% of enterprises are expected to question standalone biometric security by end of 2026.
And the worst thing: since 2019, ID fraud has surged over 600%, driven by tools powered by generative AI.
What’s Changed: Speed, Scale, and Accessibility
Generative AI makes it easier for more people to commit fraud, faster than ever.
We're not talking about some elite hacker sitting in a basement. These days, it’s anyone with a smartphone and a basic prompt. Deepfakes? Two clicks. Convincing documents? Copy, paste, done.
Check out these examples:
This new pace means traditional fraud detection systems, especially ones relying on manual checks or outdated rules, just can’t keep up.
But you don’t need to panic.
How to detect and stop AI fraud (Deepfake)?
We’ve seen this trend unfolding in real-time and you can do a lot just by educating your team on how this evolves and what to look for:
Focus on the text: AI still struggles with realistic text. Look for smudged letters, weird spacing, or inconsistent fonts. If the text looks off or feels unnatural, it probably is, even though new image generation models are getting much better.
Image style too perfect: Real photos are messy: bad lighting, shaky hands, off-center shots. AI images often look too perfect: smooth lines, perfect lighting, and strangely ideal compositions. If it resembles a stock photo or feels cartoonish, be suspicious.
Watch the face: The mouth says “yes,” but the lips say something different or stay still. AI has trouble syncing speech with mouth movement in real-time video. If it feels like a bad dub or the mouth is blurry or out of sync, that’s your red flag.
Focus on physics: GenAI still struggles with realistic physics. Look for inconsistent shadows, incorrect light direction, unnatural reflections, or impossible light bending (refraction). If the lighting doesn’t match the scene or the shadows don’t align properly, it’s likely AI-generated.
Edges that wiggle: Look closely at where the person meets the background. Flickering edges, ghostly outlines, or smudgy hair are classic signs of fakery.
When you have a high volume of incoming data, manual checks are not enough to stop machine-generated fraud.
Here are some ways to stay ahead:
Capture data intelligently: Not just uploading a file, but analyzing it for manipulation, forgery markers, and metadata inconsistencies. Own the data capture!
Multi-layer verification: Don’t just trust the document, verify the user. Cross-check identities, behaviors, metadata, deepfakes, and frequent fraud vector.
Real-time fraud triggers: Adjust your flow to support real-time detection and response instead of reacting too late.
Modern fraud needs modern tools: automated, layered, and always evolving.
Fight AI With AI
AI has made fraud easier. But the good thing is that it can also make your defenses smarter, faster, and more adaptive.
This isn’t the time to unplug and panic.
It’s time to fight AI with AI, because the same technology that speeds up fraud can also stop it in its tracks.
Let’s use AI to fight AI, before the bad guys do it better.
Want to stop fraud in your business?