OpenAI has introduced ChatGPT for Financial Services, a specialized version of its enterprise platform ChatGPT Work developed with design partners Morgan Stanley and Evercore. According to OpenAI Vice President of Product Nick Turley, the offering runs on the company’s latest and most advanced model, GPT-6 Astra.
The new product targets work that has long been handled by Wall Street’s junior bankers, including analysts and associates. It is designed to research companies, analyze financial data and produce the presentations and pitchbooks used in investment banking.
During the launch briefing, Turley said OpenAI is effectively teaching ChatGPT to conduct research like an analyst and support its conclusions the same way. The release also highlights OpenAI’s broader push into enterprise software as it moves toward what markets widely expect to be a major IPO.
In a live demonstration, Turley showed the platform assessing a potential M&A target, pulling financial metrics from industry-standard data sources and generating a formatted PowerPoint deck based on a bank’s pre-set style guide. He said making visually appealing slides is easy, but making slides that truly make sense is harder: the system has to choose relevant peers, pull prices into a spreadsheet, verify charts against the data and explain the selloff and the rebound.
What sets the product apart
Compared with ChatGPT Work, the new financial-services version includes native access to data from LSEG, Daloopa and Pitchbook. That gives the system financial statements, earnings transcripts and other specialist content, along with automated access to users’ existing market-data subscriptions.
Other finance-specific features include citations that let users trace information back to source filings and audit charts, as well as administrative controls for sensitive deal materials.
Turley said demand for the version, which is initially aimed at investment banking and equity research, is strong, though he declined to identify banks that have signed up. Asked by CNBC whether the product could reduce banks’ need to hire junior bankers, he framed it as a tool to increase productivity per employee.
In his view, if analysts and bankers in some parts of the industry are working 100-hour weeks, this kind of technology could have an impact similar to Microsoft Excel’s earlier transformation of finance by helping professionals produce better analysis faster.
At the same time, the launch raises deeper questions for an industry built on a rigorous apprenticeship model. If generative AI can complete multi-step tasks such as research and pitchbook formatting in minutes, Wall Street may have to rethink both how it trains its next generation of dealmakers and how many it needs.
CNBC noted that last month Chris Churchman, the Goldman Sachs partner overseeing one of the bank’s flagship AI projects, warned that automating tasks that help train junior bankers risks causing “cognitive atrophy” in the next generation of financiers. He argued that reasoning remains essential, even as some of that work is increasingly delegated to technology.
