# Junior Bankers Spend Hours Building Models And Pitchbooks. OpenAI Wants ChatGPT To Do That Work. > Source: > Published: 2026-09-14 10:52:01+00:00 # Junior Bankers Spend Hours Building Models And Pitchbooks. OpenAI Wants ChatGPT To Do That Work. ## Morgan Stanley and Evercore helped shape the specialized ChatGPT product as OpenAI pushes deeper into work traditionally handled by Wall Street analysts. OpenAI is taking ChatGPT deeper into investment banking with a new financial-services product that can build models, analyze companies and prepare client presentations, putting artificial intelligence directly into tasks that have traditionally occupied much of a junior banker's working day. [ChatGPT for Financial Services](https://openai.com/index/introducing-chatgpt-financial-services/) was developed with Morgan Stanley and Evercore as design partners and is initially focused on investment banking and equity research. The company said the product can perform comparable-company and valuation analysis, build leveraged buyout models, screen potential buyers, analyze earnings and prepare pitchbooks. The product is a specialized version of ChatGPT Work powered by GPT-6 Astra, OpenAI's newest model for complex professional tasks. Unlike a general-purpose chatbot that requires users to find and supply much of the financial information themselves, the new service comes with financial data integrated directly into the platform. OpenAI has built in premium data from Daloopa, PitchBook and LSEG News, allowing bankers to retrieve financial statements, company information and other material while conducting research. Firms can also connect their existing data subscriptions and internal information. The company said figures and claims generated during research are accompanied by granular citations that allow employees to trace them back to their source. Bankers can inspect supporting tables and passages and review the evidence behind an analysis before using it in client work. That verification is particularly important for tasks such as valuation and financial modeling, where an incorrect figure can flow through calculations and affect the final analysis. OpenAI said GPT-6 Astra can read figures, tables and notes in financial documents, perform financial analysis and turn the results into spreadsheets, documents and presentation slides. Nick Turley, OpenAI's vice president of product, demonstrated the system evaluating a potential acquisition target and turning the analysis into a PowerPoint presentation using a bank's own template, [Forbes](https://www.forbes.com/sites/gabrielalinzainescu/2026/09/11/openai-targets-junior-banker-work-with-chatgpt-for-financial-services/) reported. The system selected comparable companies, worked with pricing data, checked charts against underlying figures and produced explanations for market movements. OpenAI has stopped short of presenting the product as a replacement for junior bankers. Asked whether it could reduce banks' need to hire analysts, Turley described the technology as a productivity tool and compared its introduction to the adoption of Microsoft Excel. The tasks being automated, however, overlap closely with work routinely assigned to analysts and associates at investment banks. Junior bankers can spend substantial amounts of time assembling financial models, gathering company information, updating valuation comparisons and preparing presentations for senior bankers and clients. OpenAI said its work with Morgan Stanley and Evercore helped identify data access and the creation of high-quality financial documents as two of the biggest problems for banking teams. The companies are design partners rather than announced customers for the finished product, and OpenAI has not disclosed which financial institutions have signed up for the service. The launch comes as financial institutions increasingly incorporate generative AI into research and other employee workflows. It also arrives as economists examine whether automation is beginning to affect employment opportunities for younger workers in occupations where AI can perform a significant share of existing tasks. An August update from [Stanford University's Digital Economy Lab](https://digitaleconomy.stanford.edu/news/canariesaug26/) found that employment among workers ages 22 to 25 in highly AI-exposed occupations was about 19% below the level it would have reached had it kept pace with employment among similarly aged workers in less-exposed occupations. Experienced workers in the same highly exposed occupations did not show a comparable gap. The researchers said the difference appears to be driven primarily by reduced hiring of young workers rather than increased layoffs. They also cautioned that their research does not establish widespread economy-wide job displacement from AI and that the estimates are sensitive to how the effects are measured. Research from the [Federal Reserve Bank of Dallas](https://www.dallasfed.org/research/economics/2026/0106) has found a similar difference between younger and more experienced workers. Its January analysis found lower employment among young workers in occupations with high AI exposure, largely because fewer people entering the labor force were moving directly into those jobs rather than because existing employees were being laid off. A separate [Dallas Fed analysis](https://www.dallasfed.org/research/economics/2026/0901) published this month found that job postings declined in occupations whose tasks are more easily automated by generative AI. Among firms more exposed to AI, postings for automatable positions fell by about 8% to 9% by early 2026, the researchers found. OpenAI is initially concentrating the product on investment banking and equity research, with its work with financial institutions expected to inform improvements to the system and its expansion into other areas of financial services. The company said future models will also become available through the product as they are released. © Copyright IBTimes 2026. All rights reserved.