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Claude/ChatGPT Prompt to Build a Fintech KYC Onboarding Flow UI

Design a low-friction KYC onboarding UI: ID capture, selfie liveness check, address, and a clear pending/approved/failed status.

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prompt.txt

                                

What this prompt does

This prompt makes the AI act as a senior product engineer specifying a regulated KYC onboarding flow, and it asks for working component code rather than pseudocode. It lays out five build steps plus a status screen: country and ID-type selection, ID front/back capture with glare and blur detection, a selfie liveness check, address details with proof-of-address upload, and a review-and-submit screen. The [id_types] placeholder constrains which documents the first step offers, and [provider] names the verification service the liveness step is wired to.

The structure works because KYC drop-off concentrates at failure points, and the prompt forces those into the design from the start. The status screen must handle pending, approved, and failed, with a clear reason and a retry path, so a rejection becomes recoverable instead of a dead end. The [stack] variable keeps the generated component files aligned with your framework, and the requested state-machine note documents how transitions between steps and statuses actually flow. Because each capture step carries its own guide frame, glare/blur detection, and retake affordance, the spec accounts for the messy real-world conditions, like poor lighting or a blurry document photo, that derail verification in production rather than in a clean demo.

When to use it

  • Building KYC or identity verification for a regulated fintech product
  • Integrating a provider like the one named in [provider] and needing the UI around it
  • You need a clear failed-verification recovery path designed before styling
  • Supporting a specific set of documents via [id_types]
  • Mapping the step-to-step state machine for a multi-step onboarding flow
  • Generating component files in a known [stack] rather than abstract UX notes

Example output

You get step component files, one per onboarding step, plus a short state-machine note describing transitions between steps and between the pending, approved, and failed statuses. The capture steps include the live guide frame, glare/blur detection, and retake affordances; the status screen spells out each status with its reason and retry path. It is structured to drop into a real project rather than to be admired as a mockup.

Pro tips

  • Fill [id_types] with exactly the documents you accept; it drives the eligibility messaging in step one
  • Set [provider] to your real liveness vendor so the selfie step is wired to the correct integration points
  • Push hardest on the failed status: ask the model to expand the reason copy and retry path, since that is where verified users are lost
  • Keep [stack] accurate so the component files match your framework's conventions
  • If the state-machine note is thin, ask for an explicit transition table covering every status
  • Request that step five show exactly what data gets submitted; transparency at submit reduces abandonment

Frequently Asked Questions

Does this prompt return real code or just a description?
It explicitly asks for working component code, not pseudocode, plus a state-machine note. You get step component files structured to use in a project rather than a written mockup description.
Can I plug in my own KYC provider?
Yes. The `[provider]` variable names the verification and liveness service, and the selfie step is wired to it. Set it to your actual vendor so the integration points line up.
How does it handle a failed verification?
The status screen handles failed alongside pending and approved, with a clear reason and a retry path. The prompt deliberately emphasises recovery so a rejection is not a dead end for the user.
Which document types does it support?
Whatever you list in `[id_types]`, such as passport, national ID, or driver's license. The first step offers selection from those types with eligibility messaging, so an accurate list matters.
Engr Mejba Ahmed

Need this built for real?

Engr Mejba Ahmed

AI Developer · Software Engineer

I'm Mejba — I design and ship production AI systems, automations, and full-stack apps. If you want this turned into a working solution for your team, let's talk.

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Engr Mejba Ahmed

Engr Mejba Ahmed

Claude Code Expert · Online

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