The Impact of Technological Innovation on The Finance Industry: A Comprehensive Overview of Historical Milestones, Current Tools, and Future Trends
COMS-BC3997-SP23
By: Lily Cai
Abstract
This academic paper investigates the impact of technology on the finance industry, including its potential to displace human workers in areas such as customer service and trading. The paper begins by examining the history of technological adoption in finance, highlighting the major milestones and breakthroughs that have transformed the industry over time. The paper then transitions to focus on current tools being utilized in finance and explores the positive impacts and potential drawbacks of increasing technologization in finance. Additionally, the paper examines the differences between traditional financial tools and newer technologies, assesses how current college curriculums may be falling short in preparing students for the workforce, and explores how companies leverage technology to streamline financial processes and services. Finally, the paper proposes potential future trends and technological developments that will likely shape the finance industry in the coming years based on research and experimentation. By exploring these various aspects, this paper aims to provide a comprehensive overview of how technology has been utilized in finance and its potential to transform the industry.
Methodology
There are two approaches employed in this research methodology. First, the research involves a comprehensive analysis of past cases in the field of computer science to determine the current state of the art in relevant areas. Additionally, the project experimented with existing tools to test their effectiveness and determine their limitations. These two approaches combined allow for more meaningful conclusions and develop novel solutions to address gaps in current knowledge and technology. By combining historical analysis and practical experimentation, the paper aims to create a nuanced understanding of the subject matter and contribute to the body of knowledge in computer science. This research aims to produce insights and solutions that can benefit practitioners and researchers in the field, both novice and experienced industry practitioners. Meanwhile also advances personal understanding of the complex challenges and opportunities in this ever-evolving field.
Working Progress Documentations
Below are some of the documentations for the weekly progress
January
The following would entail the early weeks, specificially weeks 1-4:
Weeks 1-2
Here is a brief description what I did weeks 1-2, written in a format that's almost like a diary:
The first portion of at least two weeks was thinking and writing the preliminary research proposal. Then, the issue became that I got COVID, causing a bit of a delay with the work. Below is a bit thought process of my initial reasonings:
As my undergraduate life draws closer, I reflect on what I have gained. It saddens me to realize that I haven't accomplished as much as I could have, not only in terms of computer science projects and GPA but also in general. However, I am certain that some of my professors, peers, and friends would disagree with this pessimistic view. With this research project, I aim to satisfy my curiosity and bring closure to my somewhat tumultuous undergraduate life in a way that would make me proud, even if no one else takes pride in my work. Rather than presenting it in the typical report format or opting for the "successful" approach, I wish to pursue this project in a manner that speaks to me and showcases my unique abilities.
Throughout my years of education, I have always been passionate about learning practical and applicable knowledge. I have come to realize that being able to observe the concrete changes and impacts that my efforts are creating is what motivates me to thrive and learn. One field that has always intrigued me is how technology is utilized in various sectors, not just within the tech industry. Specifically, I have been interested in exploring how algorithmic trading and the stock market function with the aid of technology. Observing how these trading strategies operate and their effectiveness in the real world is fascinating.
**Please see "Research Proposal.pdf" in the Midterm Folder for the proposal**: [Research Proposal](https://github.com/COMS-BC3997-SP23/website-cc4672/blob/main/Midterm/Research%20Proposal.pdf)
Weeks 3-4
It wasn't delightful when I realized that my original area might not be feasible for this semester. It's almost as if a person with huge ambitions and eagerness to sail shortly only realizes they don't know how to steer a ship or navigate. My misjudgment with the difficulty required to delve into this topic made it so that after conducting preliminary research, I concluded that studying algorithmic trading would demand skills such as machine learning, which may not be feasible to acquire quickly. After recovering from COVID, I spent a week or so trying to learn more about what I could do instead that relates to the topic but at the same time can give me both the technical and research suited for a beginner level. Therefore, I shifted my focus to a more general question: **How has technology been utilized in the financial world? **
**Please see "Some research up until 3.20.pdf" in the Midterm Folder for the part of the research conducted. The file includes both the research done on algorithmic trading and history of technology in finance**: [Background Research]( https://github.com/COMS-BC3997-SP23/website-cc4672/blob/main/Midterm/Some%20research%20up%20until%203.20.pdf)
Please know that just because I couldn't do a project on it during the semester does not mean that I cannot continue this research after graduation. Still, it indicates that solely focusing on algorithmic trading may not be optimal for me to derive presentable conclusions that satisfy my academic curiosity.
February
Weeks 4-8
In February, my focus was primarily on conducting interviews with experts in the finance industry to gather insights on the impact of technology on the sector. Based on the findings, I spent time drawing conclusions and determining the best programming languages to use in analyzing the data. After careful consideration, I ultimately settled on a combination of Excel, Python, SQL, and Java. Each of these languages has unique strengths that are well-suited for different aspects of the project, such as data organization and analysis, machine learning, and data visualization. Using a combination of these languages allows for a more comprehensive and nuanced analysis of the data, leading to more robust conclusions and insights. With the decision made on which languages to use, I moved forward with the project with a greater sense of direction and purpose. I ended up deciding to use the following languages and tools: Excel, Python, Java, and SQL.
Here are some key points I gained from talking to several people working in the industry:
* While technology has become an integral part of the finance industry, traditional financial tools such as Excel are still widely used for daily operations.
* Many finance professionals have yet to fully adopt more advanced technologies (from programming languages such as python to ChatGPT) due to steep learning curve and high costs associated with implementation.
* Some experts believe that the finance industry will continue to adopt new technologies at a slower pace compared to other industries due to regulatory constraints and clients' privacy issues.
March
Weeks 8-12
Due to midterms, my progress got slowed and I didn't accomplish as much as expected. It's also the midterm presentation, so I was busy doing that.
**Please see in the Midterm Folder for midterm project status update, which was an in-class presentation**: ["Project Midterm Status.pdf"]( https://github.com/COMS-BC3997-SP23/website-cc4672/blob/main/Midterm/Project%20Midterm%20Status.pdf)
(Note: for some reason the links doesn't work and display correctly)
April
Weeks 12-16
During the month of April, I focused on coding and learning as I identified several topics in which I lacked expertise. This process involved a significant amount of trial and error, which was often frustrating. However, I persevered and successfully compiled a final presentation folder that includes both functional and failed code, to better demonstrate the learning process. The code is available in both ipynb and py formats, and I have also included several Excel documents.
- Apple_Balance_Sheet.ipynb
- Copy of Financial Model Using Excel (COMS Project).xlsx
- Failed_Merge_PDF.ipynb
- Financial_Concepts_with_Explanations.html
- Financial_Concepts_with_Explanations.ipynb
- Financial_Concepts_with_Explanations.py
- Guided_SQL_Project.py
- MergePDF_PyPDF4.ipynb
- Project_Tracker.java
- Target_Balance_Sheet.ipynb
- apple_balance_sheet.py
- failed_merge_pdf.py
- mergepdf_pypdf4.py
- project-task-list.xlsx
May
It all came to an end, which was sad.
May was when I gave my final presentation and submitted the report. The presentation (ppt) was submitted on courseworks, and I have uploaded the final report.
**Please see the final report here**:[Final Report](https://github.com/COMS-BC3997-SP23/website-cc4672/blob/main/Final%20Presentation/COMS%20Project%20Report.pdf)
For any questions or clarifications, please don't hesitate to reach out to me.
Thank you!