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Home»Cryptocurrency & Free Speech Finance»AI, Impersonations Drove Crypto Scam Losses to Record $17 Billion in 2025: Chainalysis
Cryptocurrency & Free Speech Finance

AI, Impersonations Drove Crypto Scam Losses to Record $17 Billion in 2025: Chainalysis

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AI, Impersonations Drove Crypto Scam Losses to Record  Billion in 2025: Chainalysis
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In brief

  • Chainalysis estimates crypto scams generated over $17 billion in losses for 2025.
  • Impersonation scams grew more than 1,400% year over year, driven in part by AI tools.
  • AI-enabled scams generated 4.5 times more revenue per operation than traditional scams.

In 2025, crypto scams became faster, more convincing, and more profitable as artificial intelligence and impersonation tactics pushed estimated losses to a record $17 billion, according to a new report by blockchain analytics firm Chainalysis.

The sharp increase reflects not just more scams, but more effective ones. According to Chainalysis’ report released Tuesday, the average scam payment rose to $2,764 in 2025, up from $782 a year earlier—a 253% increase.

“On a time-weighted basis, you get faster scale and better believability,” Chainalysis Head of Research Eric Jardine told Decrypt in an interview. “Over 70% of AI-enabled scams exist in the top 50th percentile of transfer volume. You’re getting bigger faster, and pulling in more money per transfer.”

Scams with on-chain links to AI vendors generated an average of $3.2 million per operation, about 4.5 times more than scams without those links, Chainalysis found. The pattern is tied to the use of face-swap software, deepfakes, and large language models sold by Chinese vendors, often through Telegram channels.

“Once you move into these deepfake-type scenarios where people look, for all intents and purposes, like someone you know or a person of authority you’ve dealt with before, the believability goes up,” Jardine said. “That means you’re more likely to be scammed, and it also lets scammers scale those operations in a way that’s really problematic.”

Government impersonation has become so effective that scams using deepfaked images of government officials grew more than 1,400% in 2025 as criminals posed as workers from government agencies, financial institutions, and crypto platforms.

One of the most expansive phishing operations targeted U.S. residents with fraudulent “E-ZPass” toll alerts, a campaign Chainalysis traced to a Chinese group known as “Darcula” or the “Smishing Triad.” Despite the massive scale of the attack—which sent out as many as 330,000 texts in a single day—the underlying infrastructure was remarkably inexpensive, with sophisticated phishing kits likely costing the scammers less than $500.

“Scams have a numbers game and a believability dimension. Long-run relational scams, like “pig butchering,” have a higher average scammed amount than a YouTube giveaway scam. You’re essentially trading off scale for believability,” Jardine said.

Pig butchering scams are long-running fraud schemes in which scammers build relationships—often posing as romantic or investment partners—before persuading victims to transfer increasingly large sums of money. They’re named as such because scammers are “fattening up” victims before swindling them.

In December, a woman in San Jose, California, used ChatGPT to determine that a new romantic partner was a pig-butchering scammer after losing nearly $1 million in cryptocurrency.

Impersonation scams are increasingly abandoning centralized exchanges for decentralized finance options like DEXs, DeFi bridges, and protocols to move their loot. This change, Jardine explained, is part of a broader trend toward the decentralization of scam operations, as criminals leverage the permissionless nature of these tools to keep their funds moving.

According to Jardine, while AI’s use in scams is growing, basic automation is usually sufficient to move funds on‑chain. Instead, more advanced AI tools could be used “at that final point of reintegration” to create fake, KYC‑compliant exchange accounts in bulk, helping scammers cash out into traditional currencies.

That ability to automate and scale the final step of cashing out helps sustain the physical aspects of the scam operations that have taken root in parts of Southeast Asia.

In recent years, so-called scam compounds have emerged across Myanmar and Cambodia, turning “pig butchering” into a massive industry fueled by human trafficking and forced labor. These operations, often run by Chinese organized crime networks, use specialized laundering channels to flip stolen crypto into luxury assets. The scale of this crisis was underscored in December when the U.S. Department of Justice moved to shut down domains linked to a major compound in Myanmar.

“These cases demonstrate the scale of modern cryptocurrency scam operations and their increasing integration with traditional organized crime,” Chainalysis said in the report. “They also reveal the human cost of these schemes, which exploit both financial victims and the trafficked individuals forced to operate them, itself an unspeakable crime.”

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