Integrating AI With

User Research & Design

Project Info

Team

Duration

Tools

Myself
Damaris Adeniji
Mikaela Thompson
Max Berent-Spillson
Madison Braile
Frida Montano
Vipula Shirse
Aishwarya Gorantla
Jemima Mohan

Fall 2024
≈14 Weeks

Activities

Personal Contributions

Overview

Research Approch

Every successful project starts with a well-structured, strategic timeline, and the Double Diamond Method helped identify problems while keeping the focus on Microsofts users.

Design Context

approached us with the question: "How might we utilize AI in financial services to solve customer challenges?" This project aims to explore common challenges faced by financial services customers, identify AI opportunities and trends, and develop a prototype to demonstrate solutions. The focus will also include evaluating risks and concerns associated with AI implementation in this industry.

Project Goals

Gain knowledge on existing opportunities and challenges witin AI with the FSI industry.

Discover a safe & secure way for Microsoft to utilize AI for their FSI customers.

Boost FSI customer's confidence in utilizing Microsoft artificial intelligence products within their business operations.

Phase 1
Exploring the Problem Space

Guiding Question

How can we integrate AI into the financial services industry while addressing customer needs?

My team and I was very unfamiliar with AI, FSI, and the needs for Microsoft Users. We began researching to better understand the potential usage of AI in the financial services industry and explore how our solutions could address the specific needs of Microsoft's FSI customers.

Research Goals

Secondary Research Methods

We conducted Literature Review, SWOT Analysis, Comparative Analysis to learn more about the problem space.

Literatures Reviewed
AI Experts, FSI Experts, and Cybersecurity Experts

50+

4

Competitor Groups Analyzed
#1:Types of AI
#2: Tools in FSI
#3: Microsoft Competitors
#4: How Microsoft Customers use AI

Literature Review

My team conducted a Literature Review to explore AI applications, trends, and challenges in the Financial Services Industry (FSI). We separated our research into 2 sections AI and FSI.

AI Key Findings:

FSI Key Findings:

Comparative Analysis

We conducted 4 comparative analyses to understand how Microsoft’s competitors and customers are using AI. This helped us identify existing AI applications, uncover design opportunities, and prioritize efforts with addressing key concerns.

#1: Types of AI
#2: Tools in FSI
#3: Microsoft Competitors
#4: How Microsoft Customers use AI

Groups Analyzed

Key Findings:

SWOT Analysis

By using the groups analyzed from the Comparative Analysis we created a SWOT Analysis to identify the key affordances and challenges associated with AI use by assessing the strengths, weaknesses, threats, and opportunities.

So What?:

This SWOT guided us to think of questions like creating a streamlined user experience, ensuring transparency, addressing AI bias, when using artificial intelligence.

Phase 2
Defining the Problem Space

Interviewing Industry Experts

To improve our research, our team interviewed three types of industry experts to gain a deeper understanding of our problem space.

Interviews Conducted
AI Experts, FSI Experts, and Cybersecurity Experts

10

2

AI Experts

6

FSI Experts

Cybersecurity Experts

2

Why did we interview these three demographics?
By interviewing AI, FSI and CS experts in multiple rounds, we were able to gain a holistic view of the constraints and opportunities with artificial intelligence and how it could be realistically integrated into FSI.

How where these interviews conducted?

All the interviews were conducted via Zoom or Teams, as our participants were located in different states. Each session included one interviewer to facilitate the conversation, while two notetakers documented the findings—one capturing key insights on virtual sticky notes and the other recording detailed notes in a document.

As a team leader, I facilitated two interviews and took notes during one interview.

Facilitating an Interview with 2 FSI Experts

Interview Findings

AI can help with improving cybersecurity while also simultaneously creating more cybersecurity issues through data breaches and privacy leaks.

AI is generally viewed as a positive yet risky advancement by FSI experts as most financial services institutions are reluctant to implement it.

AI could help provide personalization features to enhance customers experiences, especially for areas like customer service.

AI can be utilized to achieve financial services companies’ goals such as reduced costs, improved productivity, and higher profit margins.

Some daily banking tasks can be tedious, making the job of FSI workers more challenging.

Prioritization Matrix

Refining and narrowing AI opportunities to solve customer challenges.

Developed and refined our 'How Might We' statements based on feasibility, research, and impact and selected the statement:

"How can we utilize AI solutions to boost fraud detection and increase FSI customer business efficiency?"

Organized sticky notes into a prioritization matrix and synthesized key insights. Highlighted important findings using lightening icons to refine focus areas.

Concept Generation

After creating our 'How Might We' statement, we next needed to identified a problem to solve by analyzing insights gathered from interviews and research.

After generating problem spaces that we could focus on, we narrowed our scope to three key ideas for further expansion and ultimately decided 'Automated Wire Transfers' from expert feedback and its potential impact on efficiency and security.

Automated Loan and Credit Card Approvals

Automated Wire Transfers

Real-Time Credit Score Checks

Phase 3
Creating a Solution

Initial Design Direction

We decided to create a website, powered by Microsoft, that provides users with an easy and trustworthy way to complete a wire transfer. With current wire transfer options often being complex, time-consuming, non-intuitive, and prone to security concerns, our app aims to streamline the process with a user-friendly interface, robust security features, and a transparent process. This app also saves FSI employees time by reducing manual processing, minimizing errors, and providing automated tracking and reporting features.

User Needs

A more efficient and easy way to complete a wire transfer for users and FSI employees.

Desired Outcome

Users will experience a faster, more efficient wire transfer process with reduced complexity and effort.

An intuitive, step-by-step guide that simplifies wire transfers for first-time users.

First-time users will confidently navigate the wire transfer process with a clear, step-by-step guide that ensures a smooth experience.

Making foreign currency exchanges in wire transfers simple and easy to understand.

Users will easily understand foreign currency exchange rates and fees, making informed decisions with confidence during wire transfers.

We imagine a site that offers a simple, efficient space for users to manage their wire transfers reducing time for FSI employees while increasing safety.

Sketching the Wire Transfer Process

Through a collaborative whiteboarding session, our team mapped out how to integrate AI and improvements into the wire transfer process. This visual approach allowed us to build on each other's ideas and create a more cohesive plan for our project.

Mid-Fi Prototypes

Sign-in page that allows users to log in with their Microsoft account.

A dashboard homepage that displays the status of recent transfers and highlights the latest transactions.

Dashboard homepage, showcasing the most recent transfers’ status and recent transfers.

A calendar feature that offers AI-powered suggestions for conversion rates throughout the month.

Transfer sender and banking information.

Verifying about amount they want to transfer & submitting the transfer.

User Feedback Key Insight

Users expressed more need for direction and clarity while submitting a wire transfer.

Using our mid-fidelity prototypes, we conducted think aloud usability testing with 3 participants and gained feedback from 5 Microsoft experts.

Insight

There was an absence reassurance and guidance of AI’s role.

Design Opportunity

More clarity on how the wire transfer works, where AI is being implemented, and the human oversight.

Insight

User suggested a clear navigation on what step you are on.

Design Opportunity

Incorporating user-friendly features like navigation & progress bars.

Insight

Users struggled to understand the currency exchange rates during the transfer process.

Design Opportunity

Simplify presentation of currency exchange information and fees with clear explanations and visual cues.

Design Pivot

After receiving feedback from user feedback, we decided to pivot our web to mobile, as mobile apps are expected to remain dominant in the long term, while desktop usage is anticipated to decline.

High-Fi Prototyping

After getting our user feedback, we moved to high fidelity prototypes, refining the experience and interaction points within our designs. We also added interactivity to our designs, simulating the flow and experience a user would experience when engaging with our solution.

Defining User's Needs

AI Predictions

AI Automated Fraud Check

High-Fi Prototype Demo

Final Takeaway

This project started with a very large problem space, which was challenging to overcome, but I tried to tackle each challenge by collaborating with my team, asking questions, and and seeking feedback. This project gave me a new prospective on how to balance creativity with real-world impact. It also taught me the importance of adaptability and teamwork in solving complex problems.

Integrating AI With

User Research & Design

Project Info

Team

Duration

Tools

Myself Damaris Adeniji Mikaela Thompson Max Berent-Spillson Madison Braile Frida Montano Vipula Shirse Aishwarya Gorantla Jemima Mohan

Fall 2024 ≈14 Weeks

Activities

Secondary Research

Comparative Analysis

SWOT Analysis

User Interviews

Prioritization Matrix

Wireframing

Usability Testing

High-Fi Prototype

Personal Contributions

As a team lead, I led meetings collaborating with Microsoft to align on project goals, share progress updates in meetings, and refine strategies.

Led 2 user interviews with tech professionals to gather insights into customer needs, challenges, and expectations within the financial services industry.

Collaborated with my co-leads to conduct research workshops, analyses and interactive high-fi prototypes.

Overview

Research Approch

Every successful project starts with a well-structured, strategic timeline, and the Double Diamond Method helped identify problems while keeping the focus on Microsofts users.

Project Goals

Gain knowledge on existing opportunities and challenges witin AI with the FSI industry.

Discover a safe & secure way for Microsoft to utilize AI for their FSI customers.

Boost FSI customer's confidence in utilizing Microsoft artificial intelligence products within their business operations.

Phase 1 Exploring the Problem Space

Guiding Question

My team and I was very unfamiliar with AI, FSI, and the needs for Microsoft Users. We began researching to better understand the potential usage of AI in the financial services industry and explore how our solutions could address the specific needs of Microsoft's FSI customers.

Research Goals

​​

Understand AI Opportunities, Trends, and the Needs of Microsoft FSI Customers.

​

Recognize Affordances, Challenges, and Drawbacks of AI Usage in the Financial Service Industry.

Secondary Research Methods We conducted Literature Review, SWOT Analysis, Comparative Analysis to learn more about the problem space.

Literatures Reviewed AI Experts, FSI Experts, and Cybersecurity Experts

50+

4

Competitor Groups Analyzed #1:Types of AI #2: Tools in FSI #3: Microsoft Competitors #4: How Microsoft Customers use AI

Literature Review

My team conducted a Literature Review to explore AI applications, trends, and challenges in the Financial Services Industry (FSI). We separated our research into 2 sections AI and FSI.

AI Key Findings:

FSI Key Findings:

Comparative Analysis

We conducted 4 comparative analyses to understand how Microsoft’s competitors and customers are using AI. This helped us identify existing AI applications, uncover design opportunities, and prioritize efforts with addressing key concerns.

#1: Types of AI #2: Tools in FSI #3: Microsoft Competitors #4: How Microsoft Customers use AI

Key Findings:

SWOT Analysis

By using the groups analyzed from the Comparative Analysis we created a SWOT Analysis to identify the key affordances and challenges associated with AI use by assessing the strengths, weaknesses, threats, and opportunities.

So What?:

This SWOT guided us to think of questions like creating a streamlined user experience, ensuring transparency, addressing AI bias, when using artificial intelligence.

Phase 2 Defining the Problem Space

Interviewing Industry Experts

To improve our research, our team interviewed three types of industry experts to gain a deeper understanding of our problem space.

Interviews Conducted AI Experts, FSI Experts, and Cybersecurity Experts

10

2

AI Experts

6

FSI Experts

Cybersecurity Experts

2

Why did we interview these three demographics? By interviewing AI, FSI and CS experts in multiple rounds, we were able to gain a holistic view of the constraints and opportunities with artificial intelligence and how it could be realistically integrated into FSI.

How where these interviews conducted?

Facilitating an Interview with 2 FSI Experts

Interview Findings

AI can help with improving cybersecurity while also simultaneously creating more cybersecurity issues through data breaches and privacy leaks.

AI is generally viewed as a positive yet risky advancement by FSI experts as most financial services institutions are reluctant to implement it.

AI could help provide personalization features to enhance customers experiences, especially for areas like customer service.

AI can be utilized to achieve financial services companies’ goals such as reduced costs, improved productivity, and higher profit margins.

Some daily banking tasks can be tedious, making the job of FSI workers more challenging.

Prioritization Matrix

Refining and narrowing AI opportunities to solve customer challenges.

Developed and refined our 'How Might We' statements based on feasibility, research, and impact and selected the statement:

"How can we utilize AI solutions to boost fraud detection and increase FSI customer business efficiency?"

Organized sticky notes into a prioritization matrix and synthesized key insights. Highlighted important findings using lightening icons to refine focus areas.

Concept Generation

After creating our 'How Might We' statement, we next needed to identified a problem to solve by analyzing insights gathered from interviews and research.

Myself
Damaris Adeniji
Mikaela Thompson
Max Berent-Spillson
Madison Braile
Frida Montano
Vipula Shirse
Aishwarya Gorantla
Jemima Mohan

Fall 2024
≈14 Weeks

Phase 1
Exploring the Problem Space

Secondary Research Methods

We conducted Literature Review, SWOT Analysis, Comparative Analysis to learn more about the problem space.

Literatures Reviewed
AI Experts, FSI Experts, and Cybersecurity Experts

Competitor Groups Analyzed
#1:Types of AI
#2: Tools in FSI
#3: Microsoft Competitors
#4: How Microsoft Customers use AI

#1: Types of AI
#2: Tools in FSI
#3: Microsoft Competitors
#4: How Microsoft Customers use AI

Phase 2
Defining the Problem Space

Interviews Conducted
AI Experts, FSI Experts, and Cybersecurity Experts

Why did we interview these three demographics?
By interviewing AI, FSI and CS experts in multiple rounds, we were able to gain a holistic view of the constraints and opportunities with artificial intelligence and how it could be realistically integrated into FSI.

Phase 3
Creating a Solution