The Silent Problem Undermining Your Usability Tests
There is a moment that happens in almost every usability testing session. A participant reaches the login screen, types something into the input field, and then glances up — checking whether they are "doing it right." That brief, almost imperceptible pause tells you everything you need to know. The participant has already figured out that this is not a real product, and every data point you collect from that moment forward is filtered through that awareness.
For most product teams, this is an uncomfortable truth: the prototype lying at the heart of your research may not be honest with your users. And if your users do not believe in the experience, your findings will reflect how people behave in a demonstration — not how they behave in a real product.
The good news is that the fix is far more targeted than rebuilding your entire prototype from scratch. You just need to identify the single moment where user trust is either established or broken, and make that one interaction feel completely real.
Why Financial Products Face a Sharper Version of This Problem
In most product categories, participants can tolerate a certain amount of prototype roughness. They adjust, they lean in, they follow the script. But in financial product testing, the stakes feel different — to the participant and to the data.
Finance users are trained, often by years of experience with real banking apps, to notice when something feels off. A balance that does not quite add up. A form field that accepts any random string of characters. A login that skips authentication entirely and just lets them straight through. These are not minor friction points. They are trust signals, and when they fail, participants do not quietly move on. They stop mid-session to flag the inconsistency. They disengage. They shift from genuine user behavior into performance mode.
The result is a research session that tells you how people interact with a prototype that they know is fake, which is a fundamentally different and far less useful dataset than how they would interact with a shipped product.
In a banking application, the trust-establishing moment is unambiguous: it is the login. Get the login right, and users stop second-guessing the experience. They lean into the flow. The rest of the session produces data you can actually act on.
What a High-Fidelity Login Flow Actually Looks Like
Building a login that behaves like a shipped product does not mean writing production code or spinning up a backend. It means recreating the specific behaviors that users associate with legitimacy. For a mobile banking app, those behaviors cluster around a handful of interactions:
- Text inputs that respond correctly to focus, typing, and clearing
- A password field that masks characters as expected
- Credential validation that distinguishes between correct and incorrect entries
- A live error state with appropriate messaging when credentials fail
- A biometric authentication animation — Face ID or Touch ID — that feels indistinguishable from the real iOS or Android experience
None of these require engineering involvement. All of them can be built inside ProtoPie Studio without writing a single line of code, using the free plan.
How ProtoPie Makes This Possible Without Code
ProtoPie is a prototyping tool built specifically for the kind of interaction complexity that Figma and traditional prototyping tools struggle to handle. Where most tools let you link screens together, ProtoPie lets you define conditional logic, respond to real device inputs, and create layered micro-interactions that feel native rather than assembled.
For a banking login prototype, the workflow looks roughly like this. You bring your login UI in from Figma — or any supported design tool — and import it into ProtoPie Studio. From there, you assign behaviors to each element. The email input responds to keyboard focus. The password field masks characters as the user types. The submit button triggers a validation check against a set of defined credentials, and if those credentials do not match, the prototype surfaces an error state with a shake animation and a clear error message.
When the correct credentials are entered, the flow advances to a Face ID prompt. This is where a Lottie animation becomes your best asset. Using a Face ID Lottie file — there are several free options available on LottieFiles — you can time the biometric animation to match the actual cadence of iOS authentication. The result is a moment in the prototype that participants consistently respond to as if it were real, because visually and temporally, it is indistinguishable from the real thing.
The Research Payoff: Better Data From the Same Participants
The argument for investing time in a high-fidelity login flow is not aesthetic. It is methodological. When participants trust the prototype, they stop monitoring themselves and start behaving naturally. They forget to check whether they are "doing it right." They make genuine decisions, express genuine confusion, and complete or abandon tasks for genuine reasons.
That shift in participant behavior produces findings that are substantially more predictive of real-world product performance. Teams that have rebuilt their login flows to include real validation and biometric animation consistently report that usability sessions feel different — more like watching someone use the actual product, less like facilitating a roleplay around a wireframe.
Start With the Moment That Matters Most
You do not need to rebuild your entire prototype to get honest data from your users. You need to identify the single interaction that either earns or destroys trust, and make that interaction real.
For financial products — and increasingly for any product that handles personal data or sensitive decisions — that moment is authentication. Build the login like it shipped, and the rest of the session will follow.
ProtoPie Studio is free to start, and everything described in this tutorial runs on the free plan. If your current prototype is asking users to suspend disbelief at the front door, it is worth an afternoon to fix it.