Binance says its AI-driven risk detection systems protected more than 7.7 million users and blocked an estimated $4.64 billion in potential losses during the first half of 2026. The exchange framed the figures as evidence that automated monitoring is now catching scams, account takeovers and fraudulent trades before they cause damage, describing the number as "a scam prevented, an account secured, or a fraudulent trade stopped" behind every case.
Binance did not break down the $4.64 billion figure by incident type or disclose the specific detection methods behind the AI systems, framing the release as a summary of six months of activity rather than a detailed transparency report.
The scale of the problem the tools are fighting
The claim lands against a backdrop of a worsening industry-wide fraud problem. Chainalysis estimated that $17 billion was stolen through crypto scams and fraud in 2025 alone, with impersonation scams growing roughly 1,400% year-over-year. The blockchain analytics firm also found that AI-enabled scams were about 4.5 times more profitable for attackers than traditional ones, meaning exchanges are increasingly using the same class of technology, automated pattern detection and AI-driven monitoring, to defend against attacks that are themselves growing more automated.
Self-reported figures, no independent audit
As with most exchange-published security statistics, the $4.64 billion and 7.7 million figures come directly from Binance's own systems rather than an independent audit, and the company has not said whether the number reflects funds actually recovered or losses modeled as having been avoided. Even so, the scale of the figure underscores how central automated fraud detection has become to exchange operations as scam volumes and sophistication continue to rise industry-wide.
