Money laundering costs the global economy $800 billion to $2 trillion annually. Traditional detection systems are slow, rule-based, and easily evaded by sophisticated criminals.

FraudNets is an AI-powered real-time fraud detection system that identifies suspicious transaction patterns as they happen. It uses Graph Neural Networks to detect complex schemes like circular money flows (where money moves in a cycle between accounts), smurfing (breaking large amounts into smaller transactions to avoid detection thresholds), and other anomalies that humans might miss.

The system provides a visual 3D network graph that helps investigators trace money trails instantly, making complex financial networks easy to understand. Fraudulent accounts are recorded on an Ethereum blockchain, creating a shared, tamper-proof blacklist that can be used across institutions.

Banks, fintech companies, and regulators can use FraudNets to reduce compliance costs, build fraud-resistant platforms, and monitor suspicious activities in real-time.