Face Verification: Match Selfies to IDs and Find Duplicate Accounts
Facial verification that answers one question — is this the same person? Match a live selfie to the ID photo, confirm returning customers and search your whole user base for duplicates with one face engine and one API.
- TOP-24, NIST FRVT 1:1 Verification
- 1:1 + 1:N in one engine
- Liveness built in
- Our own face engine
Face technology tested by NIST and trusted by banks, fintechs and exchanges.
- TOP-24, NIST FRVT 1:1 Verification
- 1:1 and 1:N in one engine
- Built-in liveness
- Cloud, on-premises or hybrid
What Face Verification Does
Face verification compares faces to confirm identity. It works one-to-one — is this selfie the person on the ID? — and one-to-many — have we seen this face before?
Selfie vs ID photo (1:1)
Selfie verification at onboarding: the live selfie is matched to the photo on the passport, ID card or driver’s license.
Returning customers (1:1)
Re-verify a known customer by matching a new selfie to the face saved at onboarding — for account recovery, high-risk changes or payouts.
Search across your users (1:N)
A new face is searched against all your existing customers, so one person cannot open ten accounts under ten names.
Your own face blacklist
Upload faces of known fraudsters; a match blocks the session automatically.
How Face Matching Works
A fraction of a second per comparison, a clear score for your rules.
Accuracy You Can Check: TOP-24 in NIST FRVT 1:1 Verification
What the NIST result means
NIST, the US National Institute of Standards and Technology, runs the Face Recognition Technology Evaluation (FRTE) — the best-known independent benchmark for face recognition.
Our algorithm placed TOP-24, NIST FRVT 1:1 Verification.
Independently tested
TOP-24, NIST FRVT 1:1 Verification.
Reliable with glasses, beards, masks and low light
Accuracy holds when customers change their hairstyle, grow a beard, wear glasses or a medical mask, or take a selfie in a dim room.
Global ranking
TOP-24, NIST FRVT 1:1 Verification.
One Person, One Account: 1:N Duplicate Detection
Promo and bonus abuse
Stop the same person from claiming welcome bonuses again and again with new accounts.
Money mule and fake accounts
Accounts opened by one person under several identities are a common sign of mule networks — a growing concern for banks and e-wallets across Southeast Asia.
Loan stacking
Catch borrowers who apply under different names to take several loans at once.
Fraudsters reuse their own face with different names and documents.
A 1:N search compares every new face with your entire customer base and flags anyone who is already there.
Face Verification Plus Liveness
Face match
A face match only proves that two images show the same face.
Not a photo, a screen or a deepfake.
Liveness detection
Liveness detection proves that the face belongs to a real person in front of the camera.
Same step
Every face verification can run with liveness in the same step.
Real person
A real person in front of the camera.
Face Checks Beyond Matching
Age from the face vs date of birth
Compare the age the face suggests with the date of birth on the document, so a borrowed ID stands out.
Gender vs the document
Flag a mismatch between the face and the gender on the ID.
A second face in the frame
Detect someone else in the shot, a common sign of coached or assisted fraud.
Masks and accessories
Detect medical masks, glasses and other accessories that affect the check.
Face Recognition API for Developers
Choose Your Integration Path
Every integration includes:
- step-by-step implementation guides
- sandbox with test data
- dedicated technical support
- an account manager who speaks both business and tech
- regular check-ins
Back-office included
- scenario builder
- stop-lists
- manual review and analytics
Face Verification in Southeast Asia
Regulators across the region expect remote onboarding to match the customer’s face to an official photo. Last reviewed: October 2026.
Singapore
- When a face match is expected
- Remote onboarding where Singpass Myinfo is not used (MAS)
- Matched against
- ID or passport photo
- When a face match is expected
- Remote onboarding under the BNM e-KYC Policy Document
- Matched against
- ID photo (MyKad / passport)
- When a face match is expected
- Remote onboarding under OJK rules
- Matched against
- ID photo; national population data where the institution has access
- When a face match is expected
- Electronic KYC by banks and e-money issuers (BSP)
- Matched against
- ID photo; PhilSys authentication where available
- When a face match is expected
- Account opening; transfers above VND 10 million (SBV Decision 2345)
- Matched against
- Chip ID photo / national population data
- When a face match is expected
- Remote onboarding; large mobile banking transfers (Bank of Thailand)
- Matched against
- ID card / DOPA data
Face Verification Solutions by Industry
-
Banks and digital banks
Selfie-to-ID at account opening and face re-checks before high-risk changes.
-
E-wallets and payments
One person, one wallet: 1:N search at account upgrade.
-
Digital lending
Stop loan stacking and borrowed identities.
-
Crypto exchanges
Block multi-accounting before the first deposit.
-
Gig and delivery platforms
Confirm that the driver or courier on shift is the one who passed verification.
-
Telecom and SIM registration
Match the SIM buyer’s face to the ID.
Face Verification Service Pricing
BASIC package — from $0.44 per check
Document recognition plus selfie or liveness, face comparison and checks against your person lists.
Face matching included
Face matching is included in our BASIC package.
Face API pricing
Need face search or face matching on its own via API? Ask us for API pricing.
Why Choose NeuroVision Face Verification Software
TOP-24, NIST FRVT 1:1 Verification
Independent results, not lab claims.
1:1 and 1:N in one engine
Selfie checks, re-verification and duplicate search with one API.
Our own face engine
No third-party licenses.
Built-in liveness
Active liveness that stops photos, screens, masks and deepfakes in the same step.
Cloud, on-premises or hybrid
Biometric data never has to leave your jurisdiction.
One API for KYC, login and payments
The same engine powers onboarding, face login and NeuroPay.
Biometric Data Privacy
You decide what is stored and for how long
Original images are kept for 3 months by default, then per your plan.
Data stays in your jurisdiction
On-premises or hybrid deployment keeps templates and personal data in your country.
Biometric data never has to leave your jurisdiction
Not sure which product fits? Tell us about your flow
We’ll map your onboarding and compliance steps to the right modules and set up a pilot on your real traffic.
Face Verification FAQ
Didn’t find your answer?
Face verification confirms that two face images belong to the same person — for example, a live selfie and the photo on an ID. It is a core step of remote identity verification.
Face verification checks whether a face matches one specific person (1:1). Face recognition, or identification, searches for a face among many (1:N). NeuroVision does both with one engine.
1:1 compares a face with one reference image; 1:N searches a face across a list or database — useful for finding duplicate accounts and blacklisted users.
Our algorithm was tested by NIST and placed TOP-24, NIST FRVT 1:1 Verification — an independent benchmark, not our own lab.
Not when it runs with liveness detection, which confirms a real person is in front of the camera.
Most failures come from poor capture: low light, blur, a covered face or a worn ID photo. Guided capture, quality checks before matching and a threshold tuned to your risk reduce failed checks.
Face matching is part of our BASIC KYC package, from $0.44 per check including the document check. Contact us for face API pricing.
Use our Web SDK, iOS and Android SDKs or the REST API — the same integration as our KYC checks.
