Holistic Fraud Detection
Graph-based models connect identities, accounts, and devices, offering a comprehensive view to identify fraud rings and hidden risks.
Real-Time Risk Prevention
Native graph storage enables ultra-fast traversal of complex relationships, allowing real-time responses to emerging threats and reducing financial exposure.
Automated Risk Analysis
Advanced graph algorithms, e.g., community detection, automate risk scanning across real-time, near-real-time, and post-event phases for continuous protection.
Uncover hidden patterns in financial transactions with deep graph traversal, enabling the detection of money laundering schemes such as circular fund flows, layering transactions, or inconsistent documentation. By analyzing massive-scale data relationships, NebulaGraph empowers organizations to trace complex transaction paths and identify illicit activities in real time.
Trace suspicious activities across decentralized systems, enabling the identification of account takeovers in Web3 environments where anonymity and decentralization prevail. By uncovering shared wallets, devices, or transaction paths, NebulaGraph empowers organizations to trace the flow of stolen assets and identify clusters of fraudulent activity, such as those linked to a single IP address.
Visualize connections among entities to expose collusion and staged losses, enabling insurance companies to map interactions between policyholders, claimants, and adjusters. By uncovering shared devices, IP addresses, and social network connections, NebulaGraph helps customers detect fraudulent activities like duplicate claims or staged accidents.
