Payvanta: Project Overview Identity Verification · Liveness

eKYC

Merchant identity verification combines Thai national ID OCR, a government DOPA registry check, and a liveness face match into a single camera-based session. For juristic entities, director verification runs as a separate, asynchronous flow.

RoleProduct Designer
ProductPayvanta
TypeMerchant Onboarding (PSP)
Year2026
The Problem

A payment platform cannot take your word for who you are

Before granting access to accept payments, a platform has a legal and regulatory obligation to confirm the identity of every person applying. eKYC replaces in-person verification with a camera-based flow, adding a liveness check to confirm that a real person, physically present, is the one submitting.

Individual eKYC

Three-check verification in a single camera session

The process is the same whether it is the applicant or a director. For juristic applicants, the person filing is the person of attorney (POA), who completes eKYC as part of the main flow. Each listed director completes theirs separately afterward via a dedicated link.

1
ID Document Verification Front and back of the Thai national ID card are captured in a single session.
2
DOPA Check Government ID registry lookup. Returns Valid, Invalid, or Expired. A DOPA result is required before the face match can proceed.
3
Liveness Captures a live photo of the applicant's face, checks image quality, and stores it for comparison against the ID card photo. The comparison happens asynchronously after submission.
ID card scan step ID card camera
DOPA identity verification flow diagram
Selfie step Liveness camera
Status Cascade

What determines the final eKYC result

Each submission is evaluated across three dimensions: card photo quality, whether OCR-extracted fields were edited, and how closely the selfie matches the ID.

Pass

All checks pass with no field edits. Application proceeds automatically without requiring manual review of eKYC data.

Need Review

One or more checks returned below-threshold results, or the applicant edited OCR-extracted fields. Surfaced for manual review in the reviewer workspace.

Failed

Camera system error or face match could not be completed. Requires a re-capture or follow-up by the operations team.

ID Document Verification

How the ID card capture works

The applicant positions the card within the frame and captures. The system then performs OCR extraction and document verification.

ID document verification flow diagram

Each failed capture returns a specific error code mapped to a targeted retake prompt.

Liveness Capture Design

A selfie that proves the person is present

The applicant taps to shoot when ready, with real-time guidance to frame the shot correctly.

Liveness verification flow diagram
ID Document Capture

Capture design decisions

1

Manual capture: the user decides when to shoot

2

Five attempts: not three, not ten

3

Specific errors so the next attempt corrects the right thing

4

Hard fail redirects out, not into a loop

eKYC: Director Verification

Each director verifies separately after submission

Each director completes their own eKYC through a separate link after the application is submitted. The POA coordinates delivery.

Applicant
Link received
eKYC form
Review
POAforwards link
Director 1receives link
Director 2receives link
Director 3receives link
Director 1completes eKYC
Director 2completes eKYC
Director 3completes eKYC
Back officereview
POAforwards links
Director 1receives link
Director 2receives link
Director 1completes eKYC
Director 2completes eKYC
Back officereview
Placement Decision

Why eKYC sits at the end of the flow

Early placement filters intent but risks abandonment before any contact data is captured. Late placement preserves lead quality.

Rationale

eKYC is positioned at steps 12–13 because the primary risk is lead loss, not intent filtering. Contact details and business information are already captured before this point. The friction spike is mitigated by listing camera scan as a requirement on the intro page, so it reads as the final step rather than an unexpected gate.

Outcome

No friction on the verification step itself

Testing covered 8 participants (2 moderated, 6 unmoderated). Each session included a forced fail followed by a pass for both ID document capture and liveness, testing whether the system communicated what went wrong and guided recovery clearly.

No participant struggled to understand what the AI model was evaluating. Error messages were specific enough that retakes felt instructional rather than punitive. The session completion rate was 100%, though this reflects both motivated participants and a prototype that had been iterated to address known issues before testing began.

Explore the work

Modules of the ecosystem

This case study covers registration and identity verification. Each module was designed independently and built to hand off cleanly to the next.