Microsoft Wallet x CoPilot

Enhancing Microsoft Wallet with AI capabilities to create a personalized financial assistant that helps users manage payments, passwords, taxes, budgeting, and more across various platforms.

Process

Stake holder Interviews –

I was solely responsible for User experience and user Interface Design and led all the design process, conducting various rounds of qualitative and quantitative research and creating sketches, wireframes, mockups, and prototypes, while collaborating closely with the developers to ensure the quality of implementation.

Execute the Roadmap

Continue to deliver quality digital experiences across the NFL, NBA, NHL, F1, and Utah.

Overview

Microsoft Wallet, integrated into the Microsoft Edge browser, struggled to engage users beyond basic autofill and payment options. Its unclear purpose led to low adoption and stagnant growth. User research revealed American adults faced financial hurdles—67% struggled with budgeting, 48% feared tax mistakes, and many found group payments tedious—highlighting a need for a more valuable, browser-based tool.

TLDR; Solution

Reimagined Wallet in MS Edge as an AI-powered financial companion, driven by Copilot. Leveraging real-time interaction, multimodal fusion, and personalization, Copilot would handle tasks like bill splitting and tax planning within the browser, tailored to users’ needs. Starting with low-to-medium risk features, aimed to boost trust and utility seamlessly.

Design Process

This exploration sprint unfolded in two phases:

Phase 1: Ideation

User Research: Analyzed data from Pew Research, Federal Reserve, and Gallup, plus interviews with 18 users of varying financial literacy. Pain points included budgeting, tax complexity, and group payment tracking—tasks ripe for browser-based solutions.

HMW & Affinity Mapping: Using “How Might We” questions tied to AI capabilities (real-time interaction, multimodal fusion, personalization) and Edge’s ecosystem (e.g., autofill, browsing data), I worked with fellow designers to generate ideas and clustered them via affinity mapping.

Prioritization: A matrix ranked ideas by user value and risk. Low-risk features like bill splitting (leveraging Edge’s form-filling) and medium-risk tax consulting (using browsing history insights) topped the list for feasibility and impact.

Phase 2: Design exploration

Persona Development: Crafted “Kate,” a 30-year-old social media specialist from Seattle, who uses Edge daily but lacks time for financial management. She represented our target user—busy, financially stretched, and needing browser-integrated tools.

AI Sub-Roles in Edge: We designed various Copilot features, I contributed in designing Copilot within Wallet as Kate’s:

- Accountant (Low Risk): Automating bill collection and payment splits for group trips, pulling data from Edge tabs or receipts uploaded via the browser.
- Tax Consultant (Medium Risk): Simplifying tax prep with document checklists and savings tips, informed by Edge’s browsing insights.

Prototyping: Mockups (e.g., a Wallet sidebar in Edge for receipt uploads, tax review overlays) showcased seamless integration into the browsing experience.

Trust Principles: We prioritized confidentiality (secure Edge data handling), transparency (explainable AI decisions in-browser), and accuracy (precise financial calculations) to foster trust.

As an exploration, we paused at conceptual designs, setting the stage for future validation within Edge.

Core Needs:

Where is Chelsea ? (Premier, Champions, FA cup)
How did Chelsea do in their last match?
Who do they play next?
Who scored, where can I see it?
How many points ahead / behind are they?

Frustrations:

I want to take part in the match day experience
Chelsea should give me unique content
No reason to go to Chelsea’s website on a daily basis
Memberships and logins make no sense

Motivations:

Plays football themselves
Interested in every aspect of the game / sport
Follow football gives him aspiration in his everyday life
Fan by choice Identification and personal pride

Goals:

Would like to feel closer to Chelsea and the community
Socialize with other Chelsea fans
Find information about his favourite player
Watch videos from the previous match

Ideation

For Ideation stage I worked with CFC stakeholders to brainstorm and ideate ideas together. The process was made super productive by conducting design thinking inspired workshop which included my team and CFCs.

For workshop ideation process I divided task in 3 steps for better clarity and increased participation.

Step 1: Identified Key stages

We identified the key stages that the customer passes through in their interaction with your company. 1. Preparing to attend
2. Travel to Stadium
3. Arrival
4. During Match
5. After Match

Step 2: Decided on the things we want to know

Asked questions like “What do you want to know about each of the key stages in their interaction. What tasks does the user want to complete at a particular stage in the journey? What questions does the user have at that stage?”

How does the user interact with the organization at this point in the journey? Devices? What is the user feeling at this stage in the process, and how does the organization let this user down at this stage? What could be improved?

Step 3: Divide and Conquer

In groups of two we worked through our exercises.

After Ideation, team created basic User journey to help understand the user better. Then proceeded with IA and card sorting sorting activity. This helped in prioritization of content.

The Ideation workshop gave clear purpose statement –

“Create a world class digital experience for Club Chelsea members (and guests), to enhance overall hospitality experience, increase bookings, and to create additional commercial opportunities”.

Design Principles

Emotion Driven:

We lead with emotion in both the way we present the experience and the way we tell stories with the content & data.

Habit Forming:

Through behavioural design principles, aim was to create a habit forming experience that fits into the daily lives of fans.

Mobile First:

Our mobile-first methodology ensured that digital experience is designed from ground up fitting smallest yet personal form factor.

I created certain UX artifacts like User Journey map, User personas then we did card sorting for IA. Followed by iterative wireframing method to improve designs and usability based on feedback. Divided wireframing task between designers based on the user flows and to ensure consistency, we created components first before starting wireframing. After designers finished assigned user flows, we reviewed all the screens from each user flow and helped each other by critiquing and suggesting better ideas to make sure that we are producing the best quality we can make.

Once the design reached to a solid state in Lo-fi mode, developers were brought in to provide their feedback on feasibility. I later worked on high-fidelity prototypes.

Design System

Prototype
This illustrates how a user navigates through Play Predictor section in the app. It shows how someone can view upcoming game, submit their predictions, view results, earn points, check leaderboard, read rules.

Design team used Zeplin for handing over assets to developers.

Outcome

This sprint didn’t reach implementation before my departure, but it redefined Microsoft Wallet’s potential within Edge. Here’s what we achieved and projected:

Insights Gained: Pinpointed key user challenges—budgeting (67% of adults), taxes (48% fear mistakes), and accounting (e.g., Kate’s split-payment woes)—and mapped AI solutions to Edge’s capabilities.
Conceptual Impact: Copilot’s integration promised a 3x increase in Wallet’s value by automating tasks and personalizing guidance within the browser, based on sprint team feedback.
Team Alignment: 90% of participants (designers, commerce team) agreed Wallet in Edge could stand out among browser-based tools, per post-sprint survey.
Next Steps Defined: Low-risk features like bill splitting were prioritized for Edge prototyping, with tax tools slated for user testing—outlining a clear roadmap.

Hypothetically, these could drive a 25% usage bump in Edge within six months, based on similar tools. This sprint showcased how AI could transform Wallet into a standout browser feature.