Identity fraud detection in banking involves the use of advanced technology within financial institutions to identify identity impersonation attempts or the use of synthetic identities. These systems rely on document and biometric verification, behavioral analytics, database checks, and fraud pattern recognition to keep customer accounts secure, block the creation of fraudulent accounts, and protect the overall banking infrastructure. Mitek’s AI-powered solutions help banks detect threats early and respond proactively.
Use case/ examples of identity fraud detection in banking
Document fraud detection: Detecting mismatches between submitted ID documents and facial biometrics during online account onboarding processes, identifying inauthentic documents that might be manipulated, deepfakes, or not a live document, or detecting fraudulent loan applications by analyzing document data and biometric consistency.
Device fingerprinting: Flagging new account applications that are tied to devices or browsers that were blacklisted due to previous fraudulent or suspicious behavior.
Real-time scoring: Using AI and behavioral biometrics to assign real-time risk scores to logins, transaction attempts, and new account or loan applications.