AI-powered verification with real-time face matching, liveness detection, and automated document extraction. Reduce manual effort by up to 80% without compromising accuracy.
BASEKYC's AI video banking module brings machine learning directly into the live video KYC session. While the agent conducts the call, AI models work in the background -- comparing the customer's face against their ID photograph, running liveness checks to confirm the person is physically present, and extracting text from identity documents using advanced OCR.
The result is a dramatically faster verification process. Agents no longer need to manually compare photographs, type out document details, or second-guess whether a video feed is genuine. The AI handles the heavy lifting while the agent retains final decision authority, giving you the best of both worlds: speed and accountability.
The AI captures a live frame of the customer's face during the video call and compares it against the photograph on their submitted ID document. Using deep neural network embeddings, the system calculates a similarity score and flags mismatches instantly, giving agents a clear pass/fail indicator with detailed confidence metrics.
Prevent spoofing with multi-layered liveness verification. The system analyzes micro-expressions, head movement patterns, light reflection on skin, and pixel-level depth cues to confirm that a real, physically present person is on the other end of the call -- not a printed photo, recorded video, or digital mask.
Automatically extract names, dates, ID numbers, addresses, and other critical fields from captured documents during the video session. The OCR engine supports passports, national IDs, driver's licenses, utility bills, and bank statements across dozens of formats, populating customer records instantly and eliminating manual data entry.
The customer opens their secure video link and grants camera access. The AI immediately begins processing the video feed, running initial face detection and preparing for document capture. The customer experience feels natural -- no additional apps or plugins required.
In parallel with the live conversation, the AI runs face matching against the submitted ID, performs liveness checks, and extracts document data via OCR. Results appear on the agent's dashboard in real time with confidence scores, highlighted discrepancies, and recommended actions.
With AI pre-verification complete, the agent reviews the results, confirms or overrides as needed, and completes the session. What previously took 15-20 minutes of manual checking now happens in under 3 minutes, with higher accuracy and a complete digital evidence trail.
Every AI decision -- face match result, liveness verdict, OCR extraction -- is logged with the model version, input data hash, confidence score, and timestamp. This creates a complete, auditable record that satisfies RBI's requirements for technology-driven verification processes under the Master Direction on KYC and supports internal model governance frameworks.
AI models provide human-readable reasoning for every verification decision. When a face match fails or liveness detection flags a concern, the system explains why -- citing specific factors like facial landmark deviations or texture anomalies. This meets emerging IRDAI and SEBI expectations for explainable AI in financial services decision-making.
BASEKYC's AI models undergo regular bias audits across demographic groups -- age, gender, skin tone, and lighting conditions -- to ensure equitable accuracy. Testing results are documented and available for regulatory review, aligning with RBI's guidelines on responsible AI adoption and the Digital Personal Data Protection Act's fairness principles.
AI assists but never replaces the human decision-maker. Agents retain final authority to approve or reject any verification, regardless of AI scores. This human-in-the-loop design satisfies RBI's V-CIP requirement that authorized officials must conduct and take responsibility for the customer identification process.
Face Match Accuracy
AI Response Time
Liveness Standard
Languages Supported
Document Types
Uptime SLA
Integration Method
Data Encryption
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