OpenAI’s Secret Project Mercury: How Wall Street Expertise is Shaping the Future of Banking AI

The Wall Street Brain Trust Behind OpenAI’s Financial Revolution

OpenAI is quietly assembling a team of financial industry veterans in a covert initiative that could fundamentally transform how investment banks operate. Codenamed Project Mercury, this secretive program enlists former employees from elite financial institutions including JPMorgan Chase, Morgan Stanley, and Goldman Sachs to train AI systems specifically for banking tasks. These experts are being compensated at premium rates—$150 per hour—to develop financial models and craft precise prompts for transactions ranging from corporate restructurings to initial public offerings.

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The Investment Banking Grind: Prime Target for AI Disruption

Investment banking analysts typically endure brutal work schedules, often exceeding 80 hours per week during active deals. Their days are consumed by building intricate financial models in Excel, creating PowerPoint presentations, and responding to endless revision requests from senior bankers. This culture of relentless refinement has become so notorious that it spawned Wall Street’s infamous “pls fix” meme, symbolizing the constant cycle of minor adjustments that define junior bankers’ existence.

The timing for AI intervention couldn’t be more opportune. As one banking analyst anonymously confessed, “The repetitive nature of these tasks makes them ideal candidates for automation, but we’re now facing legitimate concerns about how this will impact entry-level positions that have traditionally served as crucial training grounds for future finance leaders.”, according to related coverage

Project Mercury’s Unconventional Recruitment Process

What makes Project Mercury particularly innovative is its almost entirely automated selection methodology. According to sources familiar with the program, the application process involves minimal human interaction, instead relying on a sophisticated AI-driven assessment system.

The selection process unfolds in three distinct phases:, according to recent innovations

• AI Interview: A 20-minute conversation with an AI chatbot that questions candidates based on their submitted resumes
• Financial Statement Analysis: A comprehensive test evaluating applicants’ understanding of financial statements and accounting principles
• Modeling Challenge: A practical financial modeling test simulating real-world banking scenarios

The Contractor Experience: Flexibility with Precision

Selected participants enjoy significant flexibility while maintaining rigorous standards. Contractors are expected to submit approximately one model per week, working remotely according to their schedules. The instructions emphasize using simple, clear language when writing prompts before executing the actual financial models. Each submission undergoes thorough review, with participants receiving detailed feedback and opportunities to correct issues before their work integrates into OpenAI’s developing systems.

The project has attracted talent from diverse financial backgrounds, including former employees of Brookfield Corp., Mubadala Investment Co., Evercore Inc., and KKR & Co. The participant pool also includes current MBA candidates from prestigious institutions like Harvard University and MIT, creating a unique blend of academic theory and practical industry experience.

Broader Implications for the Financial Industry

Project Mercury represents a strategic move by OpenAI to enhance the business utility of its AI technology across multiple sectors. Despite reaching a $500 billion valuation, OpenAI continues to focus on developing practical applications that can generate sustainable revenue. The financial industry, with its complex workflows and high-value transactions, presents an ideal testing ground for sophisticated AI systems.

OpenAI’s official statement acknowledges collaborating with domain experts “to improve and evaluate the capability of our models across different domains,” though they note that “experts are recruited, managed and compensated by third party suppliers.” This approach allows the company to leverage specialized knowledge while maintaining operational flexibility., as our earlier report

The Future of Banking Talent Development

As AI assumes more routine analytical tasks, the financial industry faces fundamental questions about how to develop future banking professionals. The traditional model—where junior analysts learned core skills through hands-on model building and presentation preparation—may require significant restructuring. Industry observers suggest that rather than eliminating entry-level positions, the nature of these roles will evolve toward more strategic, interpretive functions that leverage AI-generated analysis.

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Several startups are already developing specialized AI tools for investment banking, but OpenAI’s direct engagement with financial experts through Project Mercury suggests a more comprehensive approach to understanding and automating the nuanced demands of high-stakes financial transactions.

The success of initiatives like Project Mercury could ultimately redefine the relationship between human expertise and artificial intelligence in finance, creating new opportunities for professionals who can effectively bridge both domains.

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