Introducing ChatGPT for Financial Services

What happened

We’re introducing ChatGPT for Financial Services, a tailored ChatGPT Work experience that combines built-in financial data with GPT‑6 Astra⁠’s reasoning to help teams develop research, financial models, and customized client materials. This product has been shaped by our design partnership with Morgan Stanley and Evercore.

It can be challenging to effectively use MCP connectors for data providers. We have focused on making some of the most used MCPs in financial services like S&P Global and FactSet optimized for immediate use in the product, so teams can spend less time troubleshooting requests and more time on analysis. Our broader connector ecosystem includes over 50+ connectors including Datasite, Box, Preqin, and Intapp.

GPT‑6 Astra is state of the art across three of the core capabilities required for financial services work: information retrieval, financial reasoning, and artifact generation. It can navigate and understand figures, tables, and the supporting notes in financial documents. It can take inputs, run financial analysis, and draw conclusions. And it can take all of this work and accurately synthesize it into documents, spreadsheets, and slides.

We’ve built fundamental capabilities into the product so that it can research across multiple sources, trace figures across different periods, and interpret annotations in public data. Once that analysis is complete, teams can build interactive charts and visualizations. In ChatGPT for Financial Services, administrators can publish Excel, Word, and PowerPoint templates through a dedicated admin page.

With firm templates and style guides configured, teams can turn their analysis into valuation models, research notes, and pitchbooks in their firm’s format and style. Protecting material non-public information and client confidentiality is critical for financial institutions. ChatGPT for Financial Services builds on ChatGPT Enterprise’s SAML SSO, SCIM provisioning, and role-based access controls. Your firm’s business data is not used to train our models by default.

Why it matters

The collaboration has enabled us to pinpoint where OpenAI can solve the biggest challenges for financial institutions and has guided us on the solutions that will help every banker in their day-to-day work. Built-in premium data from providers like Daloopa, PitchBook, LSEG News, and Crunchbase remove the challenges with MCP connectors and access to data.

This data is indexed and hosted by OpenAI to enable higher accuracy and new features like granular citations so that bankers can trace figures and claims back to their sources, and check the evidence as their analysis develops. The product also offers state of the art frontier intelligence, including GPT‑6 Astra, natively and will continue to have newer models available out of the box as they are released.

Firms can also centrally manage access and data connections, supported by ChatGPT’s enterprise security and governance controls. Our early work with Morgan Stanley and Evercore has helped steer where we have started: investment banking and equity research. Reliable access to data and high quality artifact creation proved to be the biggest pain points for their teams.

Our work with partners will inform post training, product improvements, and our expansion into other financial services categories. ChatGPT for Financial Services brings together the financial data teams need, with the depth of detail expected. We’ve included premium financial data, streamlined existing provider connections, and improved MCP performance.

ChatGPT for Financial Services includes datasets from providers like Daloopa, PitchBook, LSEG News and Crunchbase covering earnings transcripts, financial statements, company fundamentals, private companies, and more. Teams can start working with these datasets immediately, with no separate contracts to negotiate or connectors to set up. We index and host this data on OpenAI infrastructure, allowing us to improve retrieval, latency, and how we surface it in the product experience.

For a banker running a P&L normalization analysis, that means being able to inspect the reconciliation and notes behind an adjusted EBITDA, understanding which costs were excluded, and deciding how to use it in a valuation. Our partners are central to this work and as we expand coverage, we will continue to deepen our models’ understanding of these datasets.

We will post train our models to find, interpret, and use this data like we know the best analysts can. We know many customers already have existing data subscriptions. So we’re working with S&P Capital IQ, LSEG, MSCI, Dow Jones Factiva, and Moody’s on shared sign-in and entitlement integrations. Providers will be able to recognize users through their ChatGPT sign-in to enable automatic access to data they’re already entitled to.

What to watch

It is encrypted at rest and in transit, and admins can configure workspace retention. Compliance teams can export supported workspace logs through the OpenAI Compliance Platform into their existing audit and investigation workflows. Firms can manage access to skills and apps by role and enable or disable supported app read and write actions. Multiple workspaces can also be created to enforce information barriers.

ChatGPT for Financial Services is one way we serve customers across the industry, but we recognize that it will require a range of solutions to address the needs of the finance industry.