Blockchain analytics firm Chainalysis said cryptocurrency scam revenue dropped sharply in 2022, highlighting how the broader market downturn affected fraud activity across the sector. In its 2023 Crypto Crime Report, the firm estimated that scam revenue fell 46% year over year, declining from $10.9 billion in 2021 to just $5.9 billion in 2022.
The report suggests that the decline was driven primarily by market conditions rather than by the disappearance of scams themselves. According to Chainalysis, fraud operations tend to perform worse when digital asset prices are falling, as users become more cautious and speculative enthusiasm fades.
Bear Market Pressured Scam Performance
Chainalysis said scam revenue was still trending upward at the beginning of 2022, but the pattern changed dramatically in early May. That timing coincided with the collapse of Terra Luna and the deepening of the crypto bear market, after which scam revenue declined steadily for the rest of the year.
The firm drew a close connection between scam proceeds and broader market pricing, noting that scam revenue tracked bitcoin’s price movement almost perfectly. It also observed a lag of roughly three weeks between shifts in bitcoin’s price and subsequent changes in scam revenue, suggesting that deteriorating market sentiment eventually reduces the flow of funds into fraudulent schemes.
This relationship is important because it frames scam activity not only as a criminal issue, but also as one that is shaped by investor psychology and macro market trends. When prices are rising, opportunistic fraudsters may find it easier to attract victims with promises of high returns, exclusive access, or urgency-driven pitches. When prices collapse, those same tactics can become less effective.
Multiple Scam Categories Remain Active
Chainalysis said it tracks several categories of crypto scams, including giveaway scams, impersonation scams, investment scams, NFT scams, and romance scams. The breadth of those categories shows that fraudulent activity in crypto is not limited to one channel or one user segment. Instead, scams continue to evolve across social media, messaging apps, fake websites, and direct outreach tactics.
At the same time, the company emphasized that its figures represent a lower-bound estimate. In practice, the true amount lost to scammers could be higher, because blockchain investigators continue identifying new wallet addresses associated with fraud over time. As address attribution improves, historical estimates may be revised upward.
That caveat is especially relevant in the context of fast-changing scam tactics, where criminals routinely rotate wallets, domain names, and online identities. It means that even a year with a visible decline in measured revenue should not automatically be interpreted as a comprehensive reduction in total fraud losses.
“Pig Butchering” Continues to Draw Attention
Among the scam models referenced in the report, Chainalysis specifically mentioned “pig butchering” scams, a form of fraud that has gained significant attention from law enforcement and consumer protection agencies. In these operations, scammers typically spend time building trust with victims before persuading them to transfer funds into fake or manipulated crypto investment platforms.
The U.S. Federal Bureau of Investigation has issued multiple warnings about this type of scheme. Chainalysis also noted that in November, U.S. authorities seized seven domains allegedly used by pig butchering scammers. The enforcement action reflects growing concern among regulators and law enforcement agencies over the scale and sophistication of crypto-enabled fraud.
The reference to pig butchering is notable because it highlights a broader trend: some of the most damaging scams are no longer simple one-off phishing attacks, but highly organized social engineering operations designed to extract increasingly large sums from victims over time.
Lower Revenue Does Not Mean Lower Risk
While the 46% drop is substantial, the data does not suggest that crypto scams are no longer a serious issue. Instead, the report indicates that scammers earned less in a weaker market environment. Fraud risks remain present across many parts of the digital asset ecosystem, and some scam categories may continue to expand even during periods of falling prices.
Chainalysis explicitly warned that some scam types do not necessarily decline uniformly with the market. Combined with the fact that its estimates may rise as more scam-linked addresses are identified, the headline decline should be viewed with caution. The measured reduction in revenue is meaningful, but it does not eliminate the possibility that actual victim losses are broader than currently visible on-chain.
The report ultimately reinforces a core message for the crypto industry: market downturns may reduce scam profitability, but they do not remove the structural incentives for fraud. As long as digital assets remain attractive to retail users and cross-border transfers remain fast and difficult to reverse, scams are likely to remain a persistent threat.
What the Findings Suggest for the Industry
For exchanges, wallet providers, and compliance teams, the findings offer both reassurance and warning. On one hand, reduced scam revenue in 2022 may indicate that bearish sentiment can make fraudulent pitches less effective. On the other, the persistence of multiple scam categories shows that user education, transaction monitoring, and enforcement coordination remain essential.
For investors and everyday users, the lesson is straightforward: declining scam revenue should not be mistaken for declining exposure. Fraudsters continue adapting their methods, and periods of market stress can create new openings for impersonation, recovery scams, and emotionally manipulative schemes.
In that sense, the Chainalysis data is less a sign that the problem has faded and more an indication that crypto scams are deeply tied to market cycles. In bull markets, fraud may thrive on optimism and urgency. In bear markets, total revenue may fall, but the threat remains firmly in place.