Binance Stopped 22.9 Million Scam Attempts in Q1 2026. AI Did Most of the Work

[nihalsari]

Crypto exchanges are not waiting passively while AI-powered fraud scales against them. Binance disclosed that in Q1 2026 alone, its systems stopped 22.9 million scam attempts and protected approximately $1.98 billion in user funds — part of a cumulative $10.53 billion in prevented losses across more than 5.4 million users from the start of 2025 through March 2026. The infrastructure behind those numbers includes over 100 AI models and 24 dedicated security initiatives, with AI-driven decisioning now handling 57% of fraud controls and cutting card fraud rates 60% to 70% below industry benchmarks. The exchange also blacklisted over 36,000 malicious addresses and issued more than 9,600 real-time warnings daily during the period, creating a continuous detection and response loop that operates at a speed no human security team could replicate.

The scale of Binance's AI security deployment illustrates the asymmetry that now defines crypto fraud defense: the only realistic response to AI-powered attacks operating at millions of attempts per quarter is AI-powered defense operating at the same throughput. Traditional rule-based fraud detection systems designed around known attack patterns cannot keep pace with adversarial AI that generates novel variations continuously and probes for gaps faster than human analysts can document them. The 57% AI decisioning share Binance reported is not a ceiling — it reflects an industry in transition toward systems where AI handles the detection and initial response layer entirely, with human oversight focused on edge cases and policy decisions rather than transaction-level review. The exchanges that move fastest toward that model will be the ones best positioned to protect users as attack sophistication continues to rise.

[etfs]

22.9 million scam attempts blocked, Q1 alone

[etfs]

100 AI models running security, arms race confirmed