OpenAI is taking ChatGPT deeper into Wall Street with a new version built specifically for financial institutions. Called ChatGPT for Financial Services, the new offering combines GPT-6 Astra with built-in financial data, research tools, financial modeling capabilities, and document-generation workflows designed for investment banking and equity research teams.

OpenAI announced the product on September 10, describing it as a tailored ChatGPT Work experience designed to help financial professionals develop research, build financial models, and prepare customized materials for clients. The product was shaped through design partnerships with Morgan Stanley and Evercore.

Rather than requiring financial teams to stitch together a general-purpose AI model with multiple data providers and connectors, OpenAI is putting much of that infrastructure directly into the product.

ChatGPT gets built-in financial data

Data is one of the biggest differences between ChatGPT for Financial Services and the standard ChatGPT experience.

OpenAI says the product includes premium financial datasets from providers including Daloopa, PitchBook, LSEG News, Crunchbase, and Fiscal.ai. The data covers areas such as financial statements, earnings transcripts, company fundamentals, private companies, funding activity, acquisitions, and financial news.

The data is indexed and hosted on OpenAI’s infrastructure, allowing the company to improve retrieval and latency while adding more detailed source tracing. Financial professionals can trace figures and claims back to specific tables and passages, with supporting information highlighted for review.

That matters particularly in financial analysis, where knowing the number is only half the job. Analysts also need to understand where a figure came from, which period it represents, and what assumptions or adjustments were made.

OpenAI gives the example of a banker performing a P&L normalization analysis. ChatGPT can inspect the reconciliation and notes behind an adjusted EBITDA figure, identify which costs were excluded, and help the user determine how the result could be used in a valuation.

The company is also working with existing financial-data subscriptions. OpenAI says integrations with S&P Capital IQ, LSEG, MSCI, Dow Jones Factiva, and Moody’s are being developed so users can access data they already have permission to use through their existing subscriptions.

GPT-6 Astra handles the analysis

At the center of the product is GPT-6 Astra, OpenAI’s newest flagship model.

OpenAI says Astra is designed around three capabilities that are particularly important for financial-services work: information retrieval, financial reasoning, and artifact generation. It can work through figures, tables, and notes in financial documents, perform analysis on supplied inputs, and turn the resulting work into documents, spreadsheets, and presentations.

The system can also research across multiple sources, trace figures across different periods, and interpret annotations in public financial data. Once the analysis is complete, users can create interactive charts and visualizations to compare company performance while retaining access to the underlying data and sources.

This is where OpenAI is positioning the product differently from a simple financial chatbot. The goal is not just to answer questions about companies or markets, but to participate in the workflow that comes after the research.

OpenAI says examples include value analysis, LBO modeling, buyer screening, earnings analysis, and PitchBook preparation.

From research to finished client materials

The new product also connects analysis with the documents financial teams actually produce.

Administrators can publish Excel, Word, and PowerPoint templates through a dedicated administration interface. Firms can configure their own templates and style guides so teams can turn analysis into valuation models, research notes, and pitchbooks using the organization’s preferred formats.

That could reduce one of the more mundane parts of financial work: taking information gathered and analyzed in one system and repeatedly reshaping it into the firm’s required documents.

OpenAI is effectively trying to keep that process inside ChatGPT, from research and analysis through to the final artifact.

The company says its early collaboration with Morgan Stanley and Evercore helped identify reliable data access and high-quality artifact creation as two of the biggest pain points for their teams. The initial focus is therefore investment banking and equity research, with OpenAI planning to use its partnerships to inform future product improvements and expansion into other areas of financial services.

More than 50 financial connectors

ChatGPT for Financial Services also builds on OpenAI’s broader connector ecosystem.

The company says more than 50 connectors are available across the ecosystem, including integrations involving Datasite, Box, Preqin, FactSet, and Intapp. OpenAI has also optimized some commonly used financial MCP connections so teams can spend less time troubleshooting data-provider integrations.

That combination of native financial data, existing subscriptions, and connectors gives financial institutions several ways to bring information into the same ChatGPT workspace.

Enterprise security and governance

Security and governance are particularly important when an AI system is being used around confidential financial information and material non-public information.

OpenAI says ChatGPT for Financial Services builds on the security controls available with ChatGPT Enterprise, including SAML single sign-on, SCIM provisioning, and role-based access controls.

Business data is not used to train OpenAI’s models by default, while data is encrypted both at rest and in transit. Administrators can configure workspace retention, and compliance teams can export supported workspace logs through the OpenAI Compliance Platform for existing audit and investigation workflows.

Firms can also control access to skills and apps based on employee roles, enable or disable supported read and write actions, and create multiple workspaces to establish information barriers.

Those controls are designed to make the system fit into existing enterprise environments rather than operate as a standalone consumer AI tool.

OpenAI’s bigger push into professional work

ChatGPT for Financial Services arrives shortly after OpenAI introduced GPT-6 Astra, which the company positions as its most capable model for professional work.

Astra is being deployed across areas including software engineering, computer use, browsing, science, cybersecurity, and other professional workflows. OpenAI has also emphasized its ability to work with complex tasks that require multiple steps and tools.

The financial-services launch shows how OpenAI is beginning to turn those general capabilities into specialized enterprise products.

Instead of asking financial institutions to figure out how to adapt a general-purpose AI model to their workflows, OpenAI is building those workflows into the product itself. The financial data, source citations, modeling capabilities, connectors, templates, and enterprise controls are all part of the same experience.

For banks and investment firms, that makes ChatGPT less like a general office assistant and more like an AI workspace designed around the way financial analysis is actually performed.

Availability

ChatGPT for Financial Services is currently available to eligible financial institutions. OpenAI says interested organizations can contact its sales team or their existing OpenAI account team.

The launch initially centers on investment banking and equity research, but OpenAI says its partnerships with financial institutions, data providers, and software companies will help it expand into additional financial-services categories over time.

With GPT-6 Astra providing the underlying reasoning capabilities and licensed financial data becoming directly accessible within the product, OpenAI is making a much more explicit push to put ChatGPT inside the core research and production workflows of financial firms.