The Rationalization of Investment Bankers Ashline Bussanmas


Investment banking has long been associated with complex transactions and strategic deals. However, as we step into the digital age, the landscape is shifting. Technology has become a catalyst for transformation within the industry. Investment bankers continue to find themselves balancing the innovation of technology with the implications of automation, artificial intelligence (AI), and data-driven decision-making. Rationalization allows investment bankers to better explain how to best utilize technology in their day to days.

The History of Investment Banking

In order to best understand the rationalization that has occurred in investment banking, it is important to explore the history. Prior to major technological advancements, the day-to-day of a 19th century investment banker looked radically different. Often, these bankers would act as brokers in their communities trading different commodities. These commodities consisted of high valued goods such as spices, silk and metals (Finance Institute, n.d.). Many of the bookkeeping tasks that were associated with jobs like these had to be done manually.

The Prolonged Bull Market

It wasn't until decades later that investment banking began to take its modern-day shape in America. The industry was described by many experts as a "prolonged bull market." This meant that prices were consistently rising. The rise of prices encouraged consumers to buy which fostered an environment that allowed investment banking to flourish. The extended increase in the market took place until the stock market crashed around 1929. Inevitably, it was this prolonged bull market that catapulted later technological inventions.

Policy in Investment Banking

The booming early 1900s saw policy changes to ensure banking stability. The 1933 Glass-Steagall Act separated commercial and investment banking, aiming to reduce conflicts of interest and protect clients. This act increased regulations and made investment bankers liable for bad investments. It essentially created a fairer and more secure banking environment.

The Technological Shift Investment Bankers Experienced

The early 1900s policy changes paved the way for technological innovation in investment banking. The 1970s saw the arrival of the SWIFT machine, the first e-payment system, which revolutionized transactions. Algorithmic trading emerged around the same time, enabling automated market interaction. Finally, the World Wide Web's invention in the late 20th century transformed information access, allowing bankers to ditch faxes and calls for online research. This period marked the start of a significant efficiency push in the industry.

Rationalization in Investment Banking

George Ritzer's concept of rationalization, focusing on efficiency, predictability, control, and calculability, sheds light on past transformations in investment banking. This framework, emphasizing streamlined processes, measurable goals, systematic operations, and standardized procedures, helps us understand the "why" behind these changes. By analyzing future innovations through this lens, we can anticipate the driving forces that will shape the industry moving forward.

Efficiency in Investment Banking

Investment banking has seen a constant push for efficiency. The late 70s ushered in the SWIFT system, algorithmic trading, and the web, all streamlining daily tasks. Thus, we know automation is a key driver of efficiency. A Goldman Sachs report found that by 2017, half the steps in an IPO underwriting were automated (HCLTech, 2023). This trend of automation and innovation is expected to continue with banks, globally, expected to invest nearly $300 billion in AI by 2030 (Markets Media, 2019).

Predictability in Investment Banking

Companies, just like they strive for efficiency, also prioritize predictability for their clients. This is evident in the user-friendly design of financial institutions' websites, with features like chat boxes and contact options, which empower clients and free up bankers' time. Another key way investment bankers optimize predictability is through financial modeling. These models and software help bankers make informed predictions about future market behavior, leading to better financial decisions. Modern bankers are expected to be proficient in various financial modeling software, from basic tools like Excel to advanced platforms like FactSet and Capital IQ. These platforms offer a range of services focused on predictability, including financial projections, analytics, and forecasting tools.

Control in Investment Banking

Investment banks, acknowledging Ritzer's control methods, utilize ERM (Enterprise Risk Management) to manage uncontrollable workplaces. Given the unpredictable nature of global markets and potential threats, banks focus on controllable aspects - their employees. This is done by implementing a seven-step control process mentioned by the ERM study. The study includes enforcing ethical values, promoting competence, and establishing clear structures. However, this rigid approach with strict schedules and punishments can lead to a stressful, impersonal work environment for bankers.

Calculability in Investment Banking

Investment bankers leverage calculability to maximize workday productivity through KPIs (key performance indicators). KPIs track various aspects of investment operations, categorized as strategic, operational, or functional. These metrics allow bankers to quantify performance and identify trends, crucial for predictability in the ever-changing market. For instance, AUM (assets under management) monitors the total amount of money managed for clients. Tracking AUM growth rate helps bankers identify trends and make informed decisions.

Irrationalities in Investment Banking

While efficiency, predictability, control, and calculability benefit investment banking, Ritzer cautions against over-rationalization leading to irrationalities. Focusing heavily on one area, like calculability (quantity), can compromise quality. Ritzer highlights potential downsides like inauthenticity, disenchantment, homogenization, and dehumanization. It's crucial to consider both the benefits of rationalization and the potential negative consequences.

Mutual Funds Leading to a Lack of Authenticity

Ritzer argues over-rationalization leads to a decline in authenticity. Investment banks, for example, create standardized products like mutual funds to appeal to a broad audience. While convenient, these lack personalization and may not align with individual goals. This lack of transparency and customization weakens the connection between investors and bankers.

Lack of Women in Leadership Positions

Ritzer's concept of inauthenticity goes beyond products. Investment banking, for instance, has a gender gap in leadership positions. While women comprise a significant portion of the overall workforce, their numbers dwindle dramatically in higher positions. This lack of authentic representation within the industry can contribute to feelings of isolation and stress for women in investment banking.

Growing Job Displacement

Ritzer's critique extends to efficiency. While advancements like AI streamline tasks for bankers, a recent Goldman Sachs study suggests a potential downside: job displacement. The study predicts AI could eliminate or degrade nearly 300 million jobs, potentially leading to job losses despite economic growth. While companies benefit from cost savings and potential GDP increase, individual bankers may face the brunt of increased efficiency.

Technology Can Breed Unhealthy Work Environments

While technology improves efficiency in investment banking, it also creates a paradox of longer hours. Always-on connectivity allows bankers to work outside traditional hours, leading to unpredictable and extended schedules driven by market demands and client needs. This volatility in work hours can negatively impact mental and physical health, potentially dehumanizing bankers in the process.

Algorithmic Trading can Lead to Disenchantment

The passage argues that while technology brings efficiency, it can also have downsides. Algorithmic trading, for instance, automates tasks so much that workers lose the thrill and challenge of the job (disenchantment). This is because these algorithms can make rapid trades, eliminating the need for human analysis and decision-making. As a result, investment bankers are left with dull, repetitive tasks.


Analyzing investment banking through the lens of rationalization, we see a clear link between technological advancements and their impact on the industry. From the SWIFT e-pay system to AI, technology has transformed the daily lives of bankers compared to the 1970s. This relentless pursuit of efficiency, control, predictability, and calculability has been driven by leaders seeking an edge. The importance of rationalization lies in its ability to predict future strides. By analyzing past successes in achieving these goals, leaders can identify areas for further technological integration. However, the text also highlights the need for balance, acknowledging the potential downsides of over-rationalization, such as job losses and mental health issues. In conclusion, rationalization has demonstrably shaped investment banking and will continue to be a key driver of future advancements, but its application requires a thoughtful approach to ensure a positive impact on both efficiency and the human element within the industry.


A&E Television Networks. (n.d.). Glass-Steagall Act.

Bank of 2030: The Future of Investment Banking. Deloitte. (n.d.-a).

Barney_Stinson,, AndyLouis, Poignant, Kuzzzz, BoBandy, & IB-9ari0. (2022, December 11). WSO 2022 investment banking work-conditions survey (part 1/3). Wall Street Oasis.

Chen, J. (n.d.). Algorithmic trading: Definition, how it works, Pros & Cons. Investopedia.

Cucinelli, D. (1970, January 1). Internal controls and risk culture in Banks. SpringerLink.

Daly, R. (2019, April 10). Banks to invest $300 billion in AI by 2030. Markets Media.

Do investment bankers have a good work-life balance?. Do Investment Bankers Have a Good Work-Life Balance? (n.d.).

How organizational forms contribute to elite reproduction. (n.d.).

Is nav transparent? | value research. (n.d.-b).

Kagan, J. (n.d.). Investment banker: What they do, required skills, and examples. Investopedia.

Kelly, J. (2024, February 20). Goldman Sachs predicts 300 million jobs will be lost or degraded by Artificial Intelligence. Forbes.

Littleton, C. (2016, April 12). Women on wall street face steep climb to the top. Variety.

Marketing-Specialist. (2024, March 27). Top investment banking software picks in 2024. Virtual Data Room Providers.

MorningBrew. (2021, May 18). 8 charts that explore racial disparities in the banking industry. Morning Brew.

Seth, S. (n.d.). What is the Swift Banking System?. Investopedia.

The history of Investment Banking. International Finance Institute - The Global Leader in Finance and Investment Banking Training. (n.d.-a).

Tracking and calculating key performance indicators for investment banks. FinModelsLab. (2023, July 17).

Twin, A. (n.d.). Kpis: What are key performance indicators? types and examples. Investopedia. indicators%20(KPIs)%20 measure,(liquidity%20and%20cat%20 availability)

What role does technology play in investment banking?. HCLTech. (n.d.).

Which tools do investment bankers use? - software career guide. Which Tools Do Investment Bankers Use? - Software Career Guide. (n.d.-a).

Don’t fear ai. the Tech will lead to long-term job growth. World Economic Forum. (n.d.).

Yahoo! (n.d.). Chart of the day: The long-term bull market in stocks is alive and well, Bank of America says. Yahoo! Finance.