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Fraud Risk Level Detection

Validates that a real person is performing the registration by combining Liveness with Behavioral Alert — no document capture or government identifier required.

What this use case solves

Fraud Risk Level Detection addresses the challenge of validating that a real person is performing the registration, without requiring document capture or identity verification through a government identifier — all within a single process.

By combining Liveness with Behavioral Alert, the pipeline confirms the presence of a real person in front of the camera and, simultaneously, checks whether that face carries risk signals in the Unico network. The result is an onboarding decision based on behavioral trust, not just documentary data.

Use this use case when:

  • Your operation suffers from fraud where the identity is legitimate but the intention is criminal.
  • You need to identify and block identity fraud attempts where users open accounts with synthetic identities.
  • You need to identify and block Mule Account attacks, where users open multiple accounts across different institutions to launder money.
  • You want to mitigate Bust-out Fraud by detecting users who generate sudden hyperactivity in the network.
  • Your business model requires that each individual holds at most one active account per operator (or per country).

Do not use this use case when:

  • You only need to validate the static integrity of a document against a government database → use Onboarding.
  • You only need to know if this face is the same one that completed onboarding → use 1:1 Validation.

Capabilities involved

Pipeline executed within a single process:

CapabilityRole in the flow
Liveness (Optional)Confirms that the selfie belongs to a living person, mitigating deepfake or injection attacks. Ensures input integrity before behavioral analysis.
Fraud Risk ClassificationCross-references transaction data (face, code, history) with the global network history. Applies statistical models to generate the final risk level for that transaction.

Prerequisites

  • Bearer token — OAuth2 authentication via Client Credentials. See Authentication.
  • APIKEY enabled — Key configured for V3 with behavioral analysis permission. See Environments.
  • Primary key (subject.code) — The identifier performing the transaction: document number, email, or phone number.
Maximize Risk Level accuracy

It is highly recommended to send metadata and context alongside the request. This includes registration data (name, date of birth, gender, and other information), email, phone, and clientReference. Using our Liveness solution also enriches the analysis with device risk, location, and additional behavioral signals.

Step-by-step implementation

Integration via native SDK — capture runs inside your app using the Unico SDK for Android, iOS or Flutter.

  1. Install the SDK — add the Unico SDK dependency for your platform. See the setup guide for Android, iOS or Flutter.
  2. Create a process — call Create Process with the appropriate flow value and the user's identifier. Use the returned token to initialize the SDK.
  3. Start the capture — the SDK renders the camera UI and performs liveness detection on-device, returning the captured payload.
  4. Query the result — call Get Process to retrieve the capability results.
  5. Apply business rules — evaluate the response fields to approve, deny or escalate.
Android

Native Android SDK for in-app capture.

iOS

Native iOS SDK for in-app capture.

Flutter

Cross-platform Flutter SDK for in-app capture.