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The Impact of AI on Foreign Exchange Traders at Work

Exploring how AI can enhance the workflow and decision-making of foreign exchange traders by combining financial expertise with user-centered design insights.

Type of Project:

Type of Project:

Sponsored Projects with Bentley Hughey Center for Financial Services

Sponsored Projects with Bentley Hughey Center for Financial Services

Role:

Role:

UX Researcher

UX Researcher

Team:

Team:

1 Project Manager, 2 UX Researchers

1 Project Manager, 2 UX Researchers

Date

Date

09/13/2024 - 12/12/2024

09/13/2024 - 12/12/2024

I served as a UX Researcher, responsible for deciding on the research approach and methods to first understand the life of a foreign exchange trader. I was also in charge of recruiting foreign exchange traders, conducting usability testing, and creating participant interview scripts for my team to follow.

Skills gained from this sponsored project: Moderating & Note-taking / Usability Testing / Persona / Journey Map

Problem Context

Foreign exchange traders work in high-pressure environments where they rely on a combination of technical analysis, intuition, and real-time data to make decisions. However, the overwhelming amount of data and the challenge of navigating multiple platforms often hinder decision-making efficiency.

Through the collaboration between Bentley’s Human Factors in Information Design Program and the Trading Room, our team aims to understand the foreign exchange trader's user experience, focusing on their workflow and exploring how AI can improves their routines.

Research Questions

To better understand key pain points and opportunities for improvement in foreign exchange trader workflow and decision-making

Our research questions aim to uncover the key activities, challenges, and emotional experiences traders encounter in their work and how they utilize technology and data to support their decision-making.

Expected Business Impact

This project begins the HFID program's collaboration with the Bentley Trading Room to:

  • Align the trading room's user experience with real-world foreign exchange practices

  • Recommends improvements to the Bentley Trading Room's user experience based on foreign exchange traders' work routines

  • Strengthen the HFID program’s partnership with the Bentley Trading Room to create a realistic, immersive trading environment for students

Process

Our Approach

Qualitative Research Method: 1:1 interview

I chose this method because it allows our group to gather in depth insights by asking them questions to explore trader's decision making process. A one-one interview also allow us to ask follow up questions to deppended understanding the varied experiences of traders and clarify their responses.

To understand how we could improve foreign exchange traders workflow and what technology could help with their decision making process, we find experienced foreign exchange traders. Our methodology involves gathering insights through interviews to explore the following key points in our test plan:

  1. Foreign exchange traders experiences, workflows, and tools in their day-to-day activities

Understanding the daily activities of foreign exchange traders will help us better understand the difficulties they encounter, the resources they use, and how they communicate with different data sources. Through improved tools and simplified procedures, we will be able to pinpoint inefficiencies, ascertain how technology influences their decision-making process, and identify areas for improvement.

  1. Foreign exchange traders’ technology, data usage, and views on AI tools in decision-making

By researching the technology and data traders use, how they interact with systems, and the value they place on data, we can identify the most trusted tools, the types of data used in decision-making, and whether the technology supports their needs.Understanding their view on AI is important for us to determine how open foreign traders are towards trusting AI insights and any concerns they have about AI tools

Usability Testing

Participant Screening

Both types of foreign exchange traders are important to explore, as individual traders use their own capital while institutional traders rely on firm capital. Their day-to-day work varies due to differences in work environments, resources, and access to data and technology. This approach helped us understand how AI technology could better integrate into their decision-making processes or support their daily work, offering valuable insights for students in the Bentley Trading Room who may wish to pursue one type of trading over the other.


Recruitment process

UserTesting

We chose this platform is because we can easily screen out specific number of foreign exchange traders with 3+ years of experience, ensuring they have varied expertise across different markets and open to share their job and responsibilities. 

Alumni Network

Jay, founding director of the Bentley Hughey Center for Financial Services/Trading Room introduced us to Lucy Slowe, a Bentley alumna who interned at Bentley's Trading Room. Lucy is currently working as an institutional foreign exchange trader at State Street Bank, bringing invaluable real-world experience to the project.

Research Methods Question

Coming from a design background, I don't have a deep understanding of what is specifically a foreign exchange trader, I did some of my own research through watching videos of what is a foreign exchange trader.

Goal: To prepared for the user interview I had prepared a interview script for my group with questions to understand foreign exchange traders, how the two types of traders difference in workflow, resource, background, decision-making, and the use of AI, and just to understand how it would help them in decision-making process. Some questions I sought to answer were:

Why do I need to ask these type of questions?

After observing these experiences and learning more about foreign exchange traders, it was time to get to work on consolidating our data and providing helpful recommendations for improvement to the the forex traders.

Analysis

Analysis

Analysis and Report Toolkit

Analysis and Report Toolkit

While UserTesting automatically recorded the meeting, I also took notes on a Google Doc to capture their emotions, reactions, and key phrases that stood out to me as I wrote them down. I was multitasking during the interview instead of just reading from the script.

While UserTesting automatically recorded the meeting, I also took notes on a Google Doc to capture their emotions, reactions, and key phrases that stood out to me as I wrote them down. I was multitasking during the interview instead of just reading from the script.

Data Analysis Process

Data Analysis Process

After each of us has finished our user interviews, we met up through Zoom to share our insights that we gathered from both instituitional and individual Forex Traders to a FigJam table, which included details like company, specialization, work experience, tools, decision-making, challenges, and thoughts on AI.

After each of us has finished our user interviews, we met up through Zoom to share our insights that we gathered from both instituitional and individual Forex Traders to a FigJam table, which included details like company, specialization, work experience, tools, decision-making, challenges, and thoughts on AI.

Table: Individual Foreign Exchange Trader Interview Insights

Table: Individual Foreign Exchange Trader Interview Insights

Table: Insituitional Foreign Exchange Trader Interview Insights

Table: Insituitional Foreign Exchange Trader Interview Insights

From Table to Key Insights

After hearing each insight gathered on each of our participant. We then identified common themes and extracted insights for both institutional and individual traders.

Institutional Foreign Exchange Traders

1. Heavy Reliance on Real-Time Data & News for Trading Decisions




2. Risk Management and Trading Strategies Are Central to Daily Operations




3. Emotion and Psychological Pressure in Trading




4. Integration of AI and Automation in Trading Operations


Individual Foreign Exchange Traders

1. Balancing Trading with Personal Life or Full-Time Jobs is a Key Challenge




2. Challenges with Information Latency and Market Timing




3. Emotional Control and Discipline are Key Challenges




4. Integration of AI and Automation in Trading Operations

Key Insights Into Persona

Key Insights Into Persona

Based on our participant interviews and the common themes we identified during our discussions, two main personas emerged. Each persona includes a brief bio detailing their work experience and areas of specialization, along with a summary of their daily workflow. Additionally, I incorporated personality traits to provide a deeper understanding of their character, collaboration skills, and how their work shapes their personality, as both tend to be cautious and less of risk takers.

Based on our participant interviews and the common themes we identified during our discussions, two main personas emerged. Each persona includes a brief bio detailing their work experience and areas of specialization, along with a summary of their daily workflow. Additionally, I incorporated personality traits to provide a deeper understanding of their character, collaboration skills, and how their work shapes their personality, as both tend to be cautious and less of risk takers.


Persona: Institutional Trader


Persona: Institutional Trader


Persona: Individual Trader


Persona: Individual Trader

Personas to User Journey Map

Personas to User Journey Map

With a better understanding of the two personas and insights from participants interviews, we proceeded to create a journey map showing the various stages of both individual and institutional foreign exchange traders' daily workflows.

With a better understanding of the two personas and insights from participants interviews, we proceeded to create a journey map showing the various stages of both individual and institutional foreign exchange traders' daily workflows.


User Journey Map: Institutional Trader


User Journey Map: Institutional Trader

In general, they went through 4 main stages: gathering information, using that information to build strategy with their team, and executing that strategy suing specialized trading software, and monitoring the trade and adjust the strategy as needed.

In general, they went through 4 main stages: gathering information, using that information to build strategy with their team, and executing that strategy suing specialized trading software, and monitoring the trade and adjust the strategy as needed.


User Journey Map: Individual Trader


User Journey Map: Individual Trader

In general, they went through four main stages, different from institutional foreign exchange traders. They started by checking the market movements and also captured feelings of nervousness about market shifts during off hours. In the building strategy phase, they analyze past trends, use forecasting tools, and develop strategies while managing risks and time constraints. In the execution phase, traders place and adjust trades in real-time using platforms like MetaTrader while managing market fluctuations and emotional pressure. In the monitoring and assessing phase, traders evaluate performance, refine strategies, and manage stress using dashboards and collaboration tools.

In general, they went through four main stages, different from institutional foreign exchange traders. They started by checking the market movements and also captured feelings of nervousness about market shifts during off hours. In the building strategy phase, they analyze past trends, use forecasting tools, and develop strategies while managing risks and time constraints. In the execution phase, traders place and adjust trades in real-time using platforms like MetaTrader while managing market fluctuations and emotional pressure. In the monitoring and assessing phase, traders evaluate performance, refine strategies, and manage stress using dashboards and collaboration tools.

Recommendations and Next Steps

Balancing Efficiency and Skepticism in AI

  • AI and automation are being used to improve trading efficiency, most of the effort is put into improving data analysis and speeding up trade execution

  • But for now, institutional foreign exchange traders view AI with a degree of skepticism about reliability, prefer "human in the loop" due to the sensitivity of trading decisions

Interview Trading Room Managers and Students

  • Interview students to understand how the current curriculum aligns with industry practice

  • Explore opportunities to better prepare students for real-world challenges by aligning the curriculum with the evolving needs of the trading industry, especially in terms of AI integration and decision-making

Explore other finance positions 

  • Conduct additional research on various finance positions to uncover further opportunities for aligning education with industry expectations and addressing the broader impact of AI and automation across different sectors

Reflection

What I learned

Throughout this project, I have dedicated significant effort and gained valuable insights, notably by taking a role as a UX Researcher. I monitored 3 user testings and creating the user interview script.

Combining observational research and interviews: Combining interviews with observations helped us better understand how traders how make quick decisions, especially when it's hard to explain things verbally.

Screener specificity: I found in our first round of recruitment that it was much easier to recruit individual traders than institutional. As a result, I told the team we should run a second round of research with more specific screener questions.