Reducing Friction

Optimizing Loan Application Flows in PayPal Checkout

My Role

Led the redesign of all six US and UK PayPal credit products for the new checkout framework. I ran the project on an AI-assisted workflow — using ChatGPT and Figma's AI tools at each stage — to move from discovery to stakeholder-ready designs in 1.5 months across six products.

Timeline

1.5 months

Platforms

iOS/Android mobile and desktop

Problem

Paying with a credit card is seamless and nearly instant, while using a PayPal installment credit product requires customers to complete a rigorous, multi-step application at every checkout. This added friction disrupts the purchase flow, hurting conversion, repeat usage, and adoption of one of PayPal's key revenue-driving products.

While this CEO-prioritized initiative optimized six credit products across the United States and United Kingdom, this case study highlights Pay in 4, which saw the most significant product and design changes.

Requirements & Discovery

With six product teams, leadership, and cross-functional feedback, I used ChatGPT to structure the problem space based on meeting notes for each stakeholder team — mapping each product's funnel, success metrics, and the constraints unique to US vs. UK credit regulation — so kickoff started from sharp, prioritized questions rather than a blank page.

Competitive Analysis

I fed competitor installment flows into ChatGPT for a structured teardown — step counts, friction points, and patterns for returning users — and combined those takeaways with internal research to define the leanest possible Pay in 4 flow.

Design System Gap → Build Plan

Because PayPal UI 4.0 wasn't ready, my team had to build components ourselves. I used Figma First Draft to generate first-pass components and layouts, then refined them against PayPal's standards — fast-tracking 40+ iterations through stakeholder review instead of designing each from scratch.

Execution & Iteration

I reduced the Pay in 4 funnel from three steps to one across both markets, using ChatGPT to unify content across all six products and to critique flows for friction and accessibility before team and leadership reviews — so review time went to decisions, not cleanup.

Impact

2023

H1 2024

Credit product utilization

38%

47%

Credit product conversion

51%

79%

Increase of 27%

Increase in annual revenue

$784M

208%

Increase in conversion

$598M/mo.

Trending total purchase volume

Things I Did:

Ran an AI-assisted discovery-to-handoff workflow across six credit products, contributing ~$784M to PayPal's bottom line.
Used ChatGPT to accelerate discovery, competitive synthesis, and content unification; used Figma First Draft to generate and iterate 40+ component drafts.
Cut the Pay in 4 funnel from three steps to one (US + UK), driving a 208% increase in conversion.

Back to Homepage Prototype

Overall Impact