Authenticator
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Case Study

Authenticator

Fintech · Security UX · Mobile2023Authenticator

Overview

Financial institutions depend on authenticator apps to bridge high-assurance security with everyday tasks. This project focused on the human layer: turning opaque permission and verification flows into language people could act on under stress — without diluting compliance requirements or engineering constraints. Role: UI/UX Designer, end-to-end. Scope: user research, IA, visual design. Tools: Figma, Maze, Hotjar.

Client
Authenticator
Year
2023
Category
Fintech · Security UX · Mobile
Methods
User InterviewsSupport Ticket AnalysisPlain Language RewriteUsability TestingPrototyping

The Challenge

73% of users couldn't understand the verification prompts, and 68% left angry or confused feedback after authentication.

Root causes: technical jargon in prompts obscured what action was required, countdown timers increased panic and errors instead of adding clarity, and there was no recovery path after failures — leaving users stuck and distrustful. Research across 8 user interviews and 200+ support ticket categories confirmed these as the dominant failure modes, not edge cases.

73%
Couldn't understand
Users who couldn't understand what the verification prompt was asking them to do
68%
Left frustrated
Users who left negative or confused feedback after authentication attempts
200+
Support tickets
Authentication-related tickets categorised as the primary research input

Key Insights

01

Jargon was the failure mode, not the flow

The authentication sequence itself was logically sound. The problem was every prompt was written by security engineers for compliance documentation — not for someone at 7am trying to log in to their bank account.

I have no idea what "validate your session token" means. I just want to check my balance.
02

Countdown timers amplified panic

Timer UIs are standard in authentication. But user testing showed the visual countdown actively increased error rates — users rushed, misread prompts, and failed verification. Removing the visual countdown (while keeping the technical timeout) reduced errors by 31%.

03

No recovery = no trust

When users failed authentication, there was no clear next step. The dead-end experience was the primary driver of negative feedback — not the verification itself, but the feeling of being trapped with no way forward.

Approach

Every screen was rewritten in plain language — prompts tell users exactly what's happening and what to do, no jargon, no ambiguity. The authentication flow was redesigned with clear action hierarchy and a calm visual language. Recovery paths were added at every failure state. Countdown timers were redesigned to reduce panic rather than amplify it. The result: confusion rate dropped from 73% to 12%, negative feedback from 68% to 8%, and average authentication time fell to 3.2 seconds.

01User Interviews
02Support Ticket Analysis
03Plain Language Rewrite
04Usability Testing
05Prototyping

Outcomes

73→12%
Confusion rate
Users who couldn't understand verification prompts
68→8%
Negative feedback
Users who left angry or confused after authentication
3.2s
Auth time
Average authentication time after redesign
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