Introduction
BAF (Biometric Anti-Fraud) is a technology stack for intelligent processing, analysis and recognition of images with an application scenario for remote human identification.
Applies AI and machine learning to recognize faces and determine such facial attributes as face liveness, image quality assessment, etc.
Designed for embedding in corporate and government remote customer services.
Implements cross-platform (iOS, Android, WEB) self-registration and authorization scenarios with anti-spoofing checks of the face image and checks for matching a selfie with a photo in the document.
Used for authorization or registration of users, BAF provides measures to detect forgery of persons and (optionally) documents.
Registration scenario uses remote facial liveness detection and identification (1:N) algorithm. Authorization scenario uses remote facial liveness detection and verification (1:1) algorithm.
Face and Document Checks
Depending on the subsystems selected and the use cases, the following checks are available:
Basic checks:
- Comprehensive selfie liveness check
- Comprehensive image quality check
- Comprehensive check of user's environment change
- Comprehensive blacklist check
- Risk alerts
Additional (optional) checks:
- Matching of a selfie face with a document face
- Document check for forgery
- Liveness reflection check (BETA video stream processing service. In this version, saving the video of an attempt to login or register is available)