Payspot
Designing a white-label payout experience for a global leader in digital payments
// Project Goals
We set out to design the PaySpot Wallet MVP for iOS and Android, creating a white-label mobile platform built specifically for creators, gig workers, and affiliates. The core challenge was taking brutal, complex fintech plumbing, such as KYC/KYB onboarding, multi-currency payouts, and prepaid cards, and wrapping it into a modular, intuitive UX. But we didn’t want to build a rigid, cold app.
The system had to be globally scalable and fully WCAG-compliant, yet flexible enough that entirely different partner brands could seamlessly apply their own visual identity without breaking the underlying design integrity.
// The Result
The MVP resonated deeply with users, driving high engagement and excellent reception. PaySpot successfully positioned itself as a premier wallet enabler, launching in the U.S. with EEA and LATAM markets lined up next. By focusing on raw user flow, we carved out a massive 25% reduction in onboarding steps. By designing with emotional intelligence and introducing approachable, human UX elements, we helped the platform secure a 72.4% flow completion rate. It proved to stakeholders that a highly accessible, compliant design system isn’t just a limitation; it’s the foundation of their future wallet ecosystem.
+72.4%
User activation rate
740%+
Monthly active users
6.3K+
Transaction completed
4.7/5
Customer satisfaction
From Wallet to Financial Agent
PaySpot started as a digital wallet designed for creators, freelancers and gig workers who often receive income from multiple sources, in different currencies and at irregular intervals. The original product focused on making it easier to receive payouts, manage balances, use cards and withdraw money. The next opportunity was to go beyond simply showing users what they had and start helping them understand what their financial situation actually meant.
I explored how PaySpot could evolve into an AI-native financial product that interprets activity across the account, recognizes useful patterns and helps users make better decisions about their money. Instead of acting as another chatbot layered on top of an existing wallet, the AI was designed to become part of the product itself, working across balances, transactions, payouts and financial goals to provide useful context exactly when it was needed.
Designing Controlled AI Autonomy
The core interaction model was built around four levels of involvement: understand, recommend, prepare and act. At the simplest level, Bella, PaySpot’s AI financial agent, can explain what has happened in the account or answer questions about income, spending and fees. As the level of involvement increases, she can identify opportunities, suggest actions and eventually prepare complete financial plans for the user to review.
The important principle was that increased intelligence should not automatically mean increased control. A recommendation can be generated freely, but moving money, paying someone or making a significant financial change requires an appropriate level of confirmation.
The aim was to make the system feel genuinely useful and proactive while keeping its behavior predictable. Users should always understand what Bella is proposing, what will happen if they approve it and which actions have already taken place.
Helping Users Make Better Financial Decisions
The biggest change was moving the experience away from simply displaying financial data and toward explaining what that data means. A traditional wallet might tell a user that €5,400 has arrived during the week. PaySpot AI can go further by identifying how much of that income may need to be reserved for taxes, which upcoming bills are already covered, how much should remain as a safety buffer and what amount is realistically available to spend.
The same model can help users think about larger decisions. Someone could ask whether they can afford to take a month off, reduce their workload or make a larger purchase, and the product could consider current cash, expected payouts, recurring expenses and personal preferences before presenting a clear forecast. The goal was not to replace financial judgment, but to reduce the amount of mental calculation required before making a decision and give users a clearer picture of the consequences.
Designing Trust Around an AI That Works With Money
Trust became one of the most important parts of the experience because an AI system operating around financial information needs much clearer boundaries than a general-purpose assistant.
Users should be able to see what Bella remembers about them, understand why a recommendation was made and correct assumptions when the system is uncertain. If Bella believes that a particular transaction is freelance income but only has moderate confidence, the interface should communicate that uncertainty and ask the user to confirm rather than quietly treating the assumption as fact. The same principle applies when something goes wrong.
If a multi-step financial plan fails halfway through because an exchange rate changes or a transaction cannot be completed, the system should stop safely, clearly explain what succeeded and what did not, and allow the user to decide what happens next. Transparency, reversibility and a visible activity history were treated as core parts of the product rather than secondary safety features.
From Reactive Banking to Proactive Financial Guidance
Traditional financial products are largely reactive. The user opens the app, navigates to a feature and performs an action. PaySpot AI explores what happens when that relationship becomes more proactive. The product can recognize that a regular payout is late, notice repeated currency conversion fees, anticipate that the user may fall below a preferred balance or identify an opportunity to organize newly received income. Instead of waiting for the user to search for a problem, the system can surface relevant information and prepare a useful next step.
That creates a fundamentally different interaction model, where the interface is no longer just a collection of financial tools but a layer of intelligence sitting across the entire wallet. The central idea behind the concept was simple: the original PaySpot showed users their money; the AI-native version was designed to help them make better decisions with it.
