LSEG与OpenAI合作：用可信数据扩展AI金融应用

What we've got now is much greater opportunity to access a huge wealth of data, even more than we've ever had the privilege of before. But actually do it in a very precise way. LSEG is really at the heart of financial markets and its role is to provide trusted [music] information and services across the ecosystem. People getting trust in AI starts with trust in data.

Any product that we're building, we're assessing not only from the data accuracy standpoint, though, we're also assessing the groundedness of the response. We're assessing the way the model is reasoning through the financial information. We're assessing the data surplus. We're assessing the data fidelity. We want to make sure all the data and analytics that we're building is as consumable by humans and by AI as well.

A lot of our customers have been doing a lot of heavy lifting on sort of like how those data models work, uh how to realign, rebase them, how to consume them in a scalable way.

We have many clients [music] who are using open AI as well. And they use things like ChatGPT and through capabilities like LSEG's MCP or model context protocol, [music] LSEG is able to provide its trusted data and services to those customers through ChatGPT.

Open AI is a crucial partner. We started working very, very closely with Open AI team to see how Open AI can [music] help us accelerate our operating model and how we can move together faster.

We can now think about scaling [music] best practices much more easily and still apply and embed a lot of the standards [music] and skills that we need to make sure that we're upholding the bar that we expected. The role of the analyst now [music] can expand substantially into other things. There is much more opportunity for them to do much deeper research, to do much more orthogonal insights in a way that they may not have had the time to do before.

Historically, [music] the cycle of the releases has been um around three or six months, depending on the product, depending on what you're building. Now, to all of our AI products we shrink the release cycle [music] to two weeks. So now we're releasing the products on a bi-weekly basis. The information moves faster and the decision process [music] is a lot faster and therefore the iterations are all faster.

The collective power of 27,000 employees really leaning into [music] the power of AI. It is extraordinary to imagine what that looks like. That is really exciting where we can move fast in a safe [music] scalable way and take advantage of some of the frontier capabilities of Open AI.