Introducing ChatGPT for Financial Services

推出面向金融服务的 ChatGPT

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.

我们正式推出面向金融服务的 ChatGPT（ChatGPT for Financial Services），这是一种量身定制的 ChatGPT 工作体验，它将内置的金融数据与 GPT-6 Astra 的推理能力相结合，旨在帮助团队开展研究、构建金融模型并制作定制化的客户材料。

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.

该产品得益于我们与摩根士丹利（Morgan Stanley）和 Evercore 的设计合作伙伴关系。此次合作使我们能够精准定位 OpenAI 在哪些方面可以解决金融机构面临的最大挑战，并指导我们开发出能够帮助每一位银行家处理日常工作的解决方案。

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.

来自 Daloopa、PitchBook、LSEG News 和 Crunchbase 等提供商的内置优质数据，消除了 MCP 连接器和数据访问方面的难题。这些数据由 OpenAI 进行索引和托管，从而实现了更高的准确性，并支持细粒度引用等新功能，使银行家能够将数据和观点追溯到原始来源，并在分析过程中随时核实证据。

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.

该产品还原生提供了包括 GPT-6 Astra 在内的最前沿智能技术，并将随着新模型的发布持续提供开箱即用的最新版本。企业还可以在 ChatGPT 企业级安全和治理控制的支持下，集中管理访问权限和数据连接。

Frontier research, shaped by financial expertise

由金融专业知识塑造的前沿研究

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.

我们与摩根士丹利和 Evercore 的早期合作帮助我们确定了切入点：投资银行和股票研究。事实证明，可靠的数据获取和高质量的成果产出是他们团队面临的最大痛点。我们与合作伙伴的共同努力将为后续训练、产品改进以及向其他金融服务领域的扩展提供参考。

Data is the foundation of all financial analysis

数据是所有金融分析的基础

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.

面向金融服务的 ChatGPT 汇集了团队所需的金融数据，并提供了预期的深度细节。我们整合了优质金融数据，简化了现有的提供商连接，并提升了 MCP 的性能。

Premium financial data, ready to use

优质金融数据，即刻可用

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.

面向金融服务的 ChatGPT 包含了来自 Daloopa、PitchBook、LSEG News 和 Crunchbase 等提供商的数据集，涵盖了财报电话会议记录、财务报表、公司基本面、私营企业等信息。

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.

团队可以立即开始使用这些数据集，无需协商单独的合同或设置连接器。我们将这些数据索引并托管在 OpenAI 的基础设施上，从而优化了检索速度、延迟以及在产品体验中的呈现方式。

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.

对于进行损益（P&L）标准化分析的银行家来说，这意味着能够检查调整后 EBITDA 背后的调节表和注释，了解哪些成本被剔除，并决定如何在估值中使用这些数据。

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.

我们的合作伙伴是这项工作的核心。随着我们扩展覆盖范围，我们将继续加深模型对这些数据集的理解。我们将通过后期训练，使模型能够像顶尖分析师一样去发现、解读和使用这些数据。