OpenAI has reportedly hired over 100 former bankers and consultants from top firms such as Morgan Stanley, JPMorgan Chase and Goldman Sachs as part of a new secret initiative, codenamed “Mercury.” The project’s goal is to train AI systems to perform advanced financial modelling and automate consulting tasks that are typically handled by junior investment banking analysts.
These tasks include building IPO models, conducting restructuring analyses, and preparing leveraged buyout projections, according to a WSJ report.
According to multiple reports, OpenAI is paying these ex-bankers around $150 an hour to help refine its models. Meanwhile, consultants contribute by writing prompts, testing model accuracy, and providing expert feedback on AI-generated financial outputs. This extensive feedback loop is crucial for teaching the system how to give outputs with the precision expected on Wall Street.
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The focused hiring effort aligns with OpenAI’s broader enterprise strategy, positioning the company in direct competition with major consulting and advisory companies. OpenAI is also expanding its bespoke AI consulting arm, in which engineers and domain specialists are directly engaged in client operations across finance, government, and large enterprises.
Through Project Mercury, Sam Altman-led OpenAI is developing tools to build and revise complex Excel-based transaction models, analyse financial statements, and generate detailed pitch decks — tasks that often consume hundreds of analyst hours.
These powerful new tools, designed to operate with minimal human input, are already being tested in partnership with financial institutions.
For instance, Morgan Stanley, which already utilises OpenAI’s tech in its Wealth Management division, is involved in early access programmes.
These pilots demonstrate how AI can be integrated into banking workflows. They combine the firm’s proprietary data with OpenAI’s generative models to deliver insights for client portfolios, investment ideas, and market summaries.
Future impact of the project
OpenAI’s deepening ties with banking giants became more evident when the tech company recently secured a $4 billion credit facility from JPMorgan Chase and others. Ironically, JPMorgan is also aggressively advancing its own AI agenda, aiming to become the world’s first “fully AI-powered megabank.”
Experts suggest that OpenAI’s banker-led AI training could significantly boost productivity in investment banking. By offloading repetitive modelling tasks, analysts can focus on higher-value work, signalling a shift in financial services where AI becomes a core productivity tool instead of a mere experimental add-on.
By embedding industry veterans into the training process, OpenAI is shaping its tools around the best practices and compliance standards of top-tier banks. These experts help the company develop products that aim to set a new benchmark for accuracy and reliability in financial automation, an area where generic AI tools have historically fallen short.
As OpenAI grows its consulting and enterprise services, Mercury could serve as a blueprint for how AI is increasingly changing white-collar work, not just in banking, but across other professional services that rely on accuracy and process discipline.
