
OpenAI News
· 1 min read
Introducing ChatGPT for Financial Services
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. 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.
Frontier research, shaped by financial expertise
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.
Design partners
Data is the foundation of all financial analysis
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.
Premium financial data, ready to use
Data providers
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Benchmarks
Original source
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