Digital Identity and Fraud Protection

Synthetic IDs often look perfect on paper and have little or no history. Feedzai spots them by comparing each applicant’s behavior and signals to peer groups in real time. Our AI captures risk signals like keystrokes and form-flow patterns, device and network intelligence, and data consistency checks, then benchmarks them against what genuine applicants look like at your institution and across similar populations. It also links shared devices, phones, emails, and addresses to uncover clusters that reuse the same infrastructure.

As risk rises during the application, Feedzai scores it step by step and can auto-block, step up verification, or route to review before an account is created. This cuts synthetic losses, reduces manual reviews, and keeps onboarding smooth for legitimate customers.

Behavioral biometrics captures how a user typically interacts with input devices, creating a unique behavioral profile. Deviations from established patterns can indicate a potential Account Takeover (ATO) risk, signaling that the user may not be legitimate.

Feedzai continuously monitors sessions by processing incoming data to consolidate, analyze, and enhance information. This dynamic “continuous risk monitoring” allows for evolving risk assessments and alerts as the session progresses, detecting fraudulent activities and anomalies post-login by monitoring user behavior along with device and network context.

Ongoing research into fraud and identity signals helps detect new fraud methods. It provides insights and risk indicators aligned with known fraud patterns. Customizable risk strategies, including bespoke rules and adaptable risk scores, balance fraud capture with operational constraints, ensuring effective false positive management.