Case study Fintech · White-label banking Mobile 2-week project

Increasing onboarding completion by 30% and cutting time by 4 minutes

In a white-label banking product, compliance made account creation long and bureaucratic — and half of new users never finished it. In two weeks, I turned evidence from data, app-store reviews and support tickets into a shorter, clearer flow.

My role: UX Research · Interaction Design · High-fidelity Prototyping
↓ 4 minonboarding time (from a 16 min 43 s average)
↓ 10%drop-off during onboarding
↓ 46%onboarding-related support tickets
Redesigned banking onboarding screens

TL;DR — the 30-second version

The challenge

Onboarding in a compliance-heavy banking product had become long and bureaucratic. 50% of users dropped off before completing account creation, taking almost 17 minutes on average — and flooding support with avoidable tickets.

What I did

I combined BI dashboards, app-store reviews, support-team insights and a heuristic evaluation to locate the friction, then redesigned the flow around three moves: clearer communication, error feedback at the right moment, and fewer steps.

The impact

Onboarding got 4 minutes faster, drop-off fell 10% and onboarding-related support tickets dropped 46% — turning a high-friction entry point into a faster path to adoption.

01 — Where the flow was breaking

Half of all sign-ups never finished creating their account.

Because it is a regulated banking product, onboarding cannot simply skip steps: identity, documents and security checks are non-negotiable. But the experience around those requirements had grown long, bureaucratic and hard to complete — and it was hurting adoption where it matters most: the first session.

Before touching any screen, I triangulated four sources of evidence to understand where and why users were giving up.

50.51%drop-off during onboarding (BI dashboards)
16m 43saverage completion time
35%of app-store complaints were about onboarding
BI dashboard showing onboarding drop-off funnel
Data

Funnel analysis pinpointed the steps where users abandoned — half of them before finishing account creation.

App store reviews complaining about onboarding
User feedback

App-store reviews put words to the numbers: confusion, repeated errors and frustration during sign-up.

Support insights on most common onboarding issues
Support insights

The support team's top tickets: names typed differently from ID documents, mother's name mismatches, and a temporary password users never noticed.

Together, the evidence pointed to four compounding problems:

Insight 1Vague, generic error messages left users guessing what went wrong — leading to repeated mistakes and support calls.
Insight 2Too many steps and unnecessary inputs stretched completion time — raising drop-off.
Insight 3Users depended on support for simple actions the interface could handle — raising operational cost.
Insight 4Errors surfaced too late in the flow, forcing users to backtrack or restart.

02 — The decisions that changed the flow

Three moves, each anchored in a piece of evidence.

1

Say what went wrong — precisely, and in plain language

EvidenceVague error messages were the #1 theme in reviews and support tickets — names and documents rejected without explanation.
HypothesisUsers weren't failing the requirements; they were failing to understand them.
Design decisionAdded precise input guidance aligned with compliance rules, and replaced generic feedback with specific, actionable error messages.
Expected effectFewer input errors on first try; fewer tickets asking "why was I rejected?".

The compliance rules didn't change — the communication around them did. Instructions now anticipate the three most common mistakes (abbreviated names, document mismatches, unnoticed temporary password) before they happen.

2

Move feedback to the moment of the mistake

EvidenceErrors were displayed late in the flow, often after users had already progressed — forcing restarts and backtracking.
HypothesisThe cost of an error is proportional to how far the user has moved past it.
Design decisionValidation now fires at the exact moment each error occurs, field by field, instead of at the end of a step.
Expected effectNo rework: users fix problems while the context is still on screen.
3

Shorten the path — and let users help themselves

EvidenceThe flow demanded too many steps and inputs; users relied on support for corrections the UI could allow; the OTP code often went unnoticed.
HypothesisEvery input that could be removed, automated or self-served would pay back in completion time and ticket volume.
Design decisionReorganized the flow to ask essential data first, removed unnecessary inputs and confirmation steps, implemented automatic OTP detection, and let users correct their own data in place.
Expected effectA measurably shorter flow and less dependency on human support.
Redesigned onboarding flow screens, part 1
Essential data first: the reorganized flow front-loads what compliance actually needs.
Redesigned onboarding flow screens, part 2
Self-service corrections and automatic OTP detection remove the two biggest support triggers.

03 — The final design

Less to read, less to type, nothing left unexplained.

The redesigned onboarding removes friction, simplifies decision-making and guides users toward completion. Compare the same journey before and after:

Before Onboarding before the redesign
Long forms, generic errors at the end of each step, and a temporary password easy to miss.
After Onboarding after the redesign
Essential data first, inline validation at the moment of error, and clear guidance written around real user mistakes.

Click any image to inspect it at full size.

04 — Results, with context

What changed after launch.

↓ 4 minaverage onboarding time — a ~24% reduction from the 16 min 43 s baseline
↓ 10%drop-off during onboarding, against the 50.51% baseline
↓ 46%onboarding-related support tickets

These are before/after comparisons of the same product metrics tracked in the BI dashboards that informed the redesign. Other initiatives may have contributed during the same period; the strongest causal signal is the 46% fall in onboarding support tickets, which maps directly to the communication and self-service changes.

Nota para revisão (visível de propósito): o título menciona "+30% na conclusão do onboarding". Confirmar a base de cálculo e a janela de medição desse número em relação à queda de 10% no drop-off antes de publicar.

05 — What I took from this

Clear communication is a design material in complex flows. In a regulated product, I couldn't remove the requirements — but rewriting how they were asked changed the outcome.

Small UX changes move business metrics. Inline validation and automatic OTP detection are modest interventions with outsized effects on time and ticket volume.

Data plus qualitative insight beats either alone. Dashboards showed where users left; reviews and support tickets explained why. The redesign only worked because both were on the table.

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