Binance AI Security Tools Help Prevent $10.53 Billion in Crypto Fraud

Binance says its artificial intelligence powered security systems helped prevent more than $10.53 billion in user losses linked to scams and fraud between early 2025 and March 2026. The company revealed that its growing use of AI has strengthened protection against increasingly advanced cyber threats targeting crypto users.

According to the latest figures, more than 5.4 million users were protected during the 15-month period. Binance introduced over 24 AI-focused security initiatives and deployed more than 100 fraud detection models to reduce risks across its platform.

AI-Powered Crypto Scam Detection Expands

The exchange warned that AI is making scams harder to identify, as criminals are now using deepfakes, phishing tools, fake trading platforms, voice cloning, and impersonation tactics to trick investors. Binance said the falling cost of these technologies has made fraud easier to carry out on a larger scale.

To strengthen defenses, the company blacklisted around 36,000 malicious wallet addresses and improved fraud monitoring systems. Binance also adopted computer vision technology to spot fake payment confirmations and real time language analysis to identify suspicious scam patterns.

Binance Fraud Prevention Data in 2026

In the first quarter of 2026 alone, Binance reported blocking 22.9 million scam and phishing attempts, helping secure nearly $1.98 billion in user funds. The company added that AI-based decision systems now handle 57% of fraud controls, contributing to a 60% to 70% lower card fraud rate compared with wider industry benchmarks.

Rising AI Threats in the Crypto Industry

The wider crypto sector continues to face growing pressure from cybercrime. Fraud schemes using fake identities and social engineering methods have become more sophisticated, raising concerns about investor safety. As attackers adopt smarter tools, crypto platforms are increasingly turning to AI-driven security to strengthen protection and reduce financial losses.