Bill Pay Optimization
Team
AP Trust
Role
Product designer
Duration
12 weeks
Problem
Customers knew how to pay—but not what to optimize.
Research showed that over 60% of payment runs required manual adjustments before processing, while 37% of customers paid at least one bill late, often due to competing priorities and limited visibility.
Customers spent time comparing invoices, bank balances, payment methods, and due dates instead of focusing on business outcomes. The product executed payments reliably but offered little guidance on making better payment decisions.
Before Prioritization: Bills grid
Before Prioritization: Bills grid
Strategy
From executing payments to recommending payment strategies.
Rather than automating decisions outright, I introduced a human-in-the-loop framework where BILL analyzed payment context and surfaced transparent recommendations with clear reasoning.
Every recommendation needed to be explainable, actionable, and easy to override, establishing reusable decision patterns that could scale across payment methods, customer preferences, and future AI capabilities.
Solution
An AI-assisted payment planning experience.
I redesigned both the unpaid bills and payment workflows to prioritize decisions instead of transactions. BILL intelligently surfaced which bills required attention, recommended optimal payment timing, funding accounts, payment methods, and delivery speeds, while explaining the reasoning behind every suggestion.
Customers retained full control, but repetitive analysis shifted from the user to the product, reducing cognitive load without sacrificing trust.
AI as a Co-pilot
AI for decision support
AI prepared plan
Results
Less decision fatigue, greater confidence, stronger foundation for AI.
The project established a scalable decision-making framework that repositioned BILL from a payment execution platform to an intelligent financial planning partner.
More importantly, it introduced interaction patterns for explainable recommendations, human oversight, and contextual decision support—creating the foundation for future agentic payment experiences where AI can proactively prepare, optimize, and orchestrate payment plans while keeping customers in control.
Reflection
From payment execution to autonomous financial orchestration.
Today, I would evolve the experience into an AI payment agent that continuously monitors cash flow, predicts payment risks, negotiates trade-offs across competing priorities, and prepares an optimized payment plan for approval.
The product becomes less about configuring individual payments and more about orchestrating financial decisions with AI while maintaining transparency, explainability, and human oversight.