Solutions
Pig butchering scams
Detect the fake faces and forged proof behind long-con romance and investment scams — before your users are drained.
$5.8B
reported U.S. losses to crypto-investment ('pig butchering') scams in 2024Source: FBI IC3
- Flags AI-generated profile photos at signup
- Catches deepfake faces on video calls
- Screens forged statements and payment proofs
The threat
Scammers spend weeks building trust with a fabricated persona, using AI-generated profile photos and deepfake video calls, then steer the victim into a fake investment platform. By the time the money moves, the 'person' never existed.
Detection at every stage of the con
Pig butchering touches several products before money moves, and ScamAI scores the media at each one through the REST API: profile photos at signup, video-call frames for face swaps, and the fake dashboards, statements, and payment proofs shown to victims. Each result is a separate chance to break the con before the savings leave.
Weeks of runway means weeks of chances to intervene
Pig butchering is slow by design, and that patience is its weakness: every stage leaves synthetic media behind, from the generated profile photo to the deepfaked call to the fake trading dashboard and the forged withdrawal-fee invoice. Detecting any one of them interrupts the con while the victim has lost little or nothing (the FBI counted $5.8B in reported U.S. losses in 2024).
/ROI
What this is worth
- Loss avoidance: as an illustration, at 50,000 checks a month, catching just 0.2% more synthetic media is ~100 frauds stopped — at a $10k average loss, that's ~$1M a month that never walks out the door.
- Review time: evidence-backed results cut manual review from minutes to seconds, so analysts handle the small flagged fraction instead of screening everything.
- One integration: a single REST API covers faces, documents, and devices — no second vendor, no second review queue.
Common questions
What is a pig butchering scam?
Pig butchering is a long-con investment scam: the fraudster builds a weeks-long relationship with the victim — often romantic, started on a dating app or through a wrong-number message — then introduces a fake investment platform showing fabricated returns. The victim invests more, fattening the pig, until the scammer disappears with everything. The persona is synthetic, built on AI-generated photos and deepfaked video calls. The FBI attributed $5.8B in reported U.S. losses to these crypto-investment scams in 2024.
How can platforms detect romance scammers using AI-generated photos?
AI-generated profile photos carry statistical artifacts that detection models identify even in flawless-looking images — inconsistencies in how generators render texture, lighting, and facial detail. Screening at signup catches synthetic personas before they contact anyone, and rescreening when an account shows scam-pattern behavior catches personas that changed photos later. ScamAI's REST API returns a scored result per image, so trust and safety teams can gate, review, or ban on thresholds they control instead of waiting for user reports.
How can banks stop pig butchering before the money is gone?
Banks usually meet pig butchering at the transfer, when a customer moves unusual sums to crypto exchanges or unfamiliar accounts. The intervention problem is that victims defend the scam — they believe the investment is real. Forensic evidence changes those conversations: screening the proof the victim was shown — platform screenshots, account statements, payment confirmations — produces a manipulation result a banker can show the customer. Proving the document is forged is more persuasive than saying the relationship is fake.
See the fake flagged before the money moves
15 minutes, on your own media. Pick a slot and leave with a result.