Nasdaq 執行長談 24/7 交易、代幣化與 AI 金融新時代

0:00邁向全天候交易：Nasdaq 的轉型之路

0:00那我們就開始吧。Nasdaq 最近有很多令人興奮的新發展。請談談推動 24/7 全天候交易的進展，哪些部分順利，哪些還需要時間？So let's get started. Nasdaq is doing a lot of exciting stuff. Talk about the move to 24/7 trading and how it's progressing, what's working, what might be taking a little longer.

0:22當然。Joanna，你也知道，我們一直在努力將 Nasdaq 轉型為一個服務全球金融體系的科技公司。這其中很重要的一環，就是打造全球最現代化的市場。當我們思考未來的交易和基礎設施時，不只是作為市場營運者，我們同時也為全球 135 個市場營運者和監管機構提供技術，並為全球數百家券商和銀行提供核心交易基礎設施技術。Sure. Well, as you know, Joanna, we've been on a journey to really transform Nasdaq into a global technology company that serves the full financial system. And a big part of that has been to really architect the world's most modern markets, as we think about the future of trading, the future of trade infrastructure, not only as a market operator, but also we provide our technology to 135 other market operators and regulators around the world, and we provide core trade infrastructure technology to hundreds and hundreds of broker-dealers and banks around the world.

0:59我們對於自己扮演的角色感到非常自豪，但這也意味著我們肩負很大的責任。現在市場對於「永遠開市」的需求非常強烈，這是有充分理由的。第一步是美國股票市場將於今年 12 月 6 日開始 23.5 小時交易。雖然現在有 24/5 的交易，但還沒在交易所實現。我們正在邀請全球進入我們的市場，這是邁向全天候交易的重要第一步。We're really proud of the role we play, but that also means we have a lot of responsibility. There is a huge push, and there's, for good reason, towards always-on markets. The first step of that will be 23.5 trading in U.S. equities starting in December 6 of this year. Now, that trading occurs 24/5 today. But not in the exchanges. So the exchanges are coming to the world. We're inviting the world into our markets. We're very, very excited about it, and I think that that's a first step towards always on.

1:35從 23/5 走向 24/7，對整個產業來說是巨大的挑戰。我會說，最簡單的部分其實是交易所基礎設施。我們目前已經為全球其他市場營運者提供 24/7 的技術，所以這部分我們很熟悉。但當你從有時間維護、修補系統，甚至有週末可以升級，轉變為完全沒有休息時間時，系統架構就完全不同了。幕後的風險管理、擔保品管理等，都必須改為全時即時處理，這也是為什麼資產代幣化這麼重要。Moving from 23/5 to 24/7 is actually a massive lift for the entire industry. I would say the easiest part is the exchange infrastructure. We provide 24/7 technology to other market operators around the world today. So that part we fully understand how to architect. But when you move from having time off either to manage your systems or patch the systems or make sure that you're upgrading things and you have, like, the luxury of a weekend. You architect your systems differently. And if you're behind the scenes managing trade risk, risk management, collateral management, you have blocks of time where you can do batch processing or things like that that allow you to, you know, have a different infrastructure to support your activity. You move to always on, everything has to be real time all the time. Risk management has to be real time all the time. You have to think about collateral management and the flow of capital needs to be real time all the time, why tokenization is so important. But also it means that every bank and broker's infrastructure needs to change. So we're building that into our trade infrastructure technology while we're also bringing our markets into this environment.

2:45資產代幣化：資本流動與市場融合

2:45那麼，能不能多談談資產代幣化？你觀察到傳統金融市場在這方面的發展，以及它的優缺點？Okay, so talk a little bit more about tokenization and what you're seeing on that front in terms of. Now, how traditional financial markets are moving toward it, and what are the benefits and drawbacks?

2:57其實這很有趣，因為我們看到散戶和機構的興趣正在融合。我認為這一年來，尤其是美國國會通過 GENIUS Act 之後，這種趨勢更加明顯。這項法案為穩定幣成為美國銀行體系核心基礎設施鋪平了道路。如果我們能將貨幣代幣化，就能讓資本流動也代幣化。這樣一來，許多原本卡在全球各地擔保品池的資本，例如國債、股票、其他固定收益產品、貨幣市場基金，都能變得更流動，釋放出數百億美元的資本。Yeah. Well, I think actually it's been really interesting to see the convergence of retail interest and institutional interest come together. And I would argue that it's really been in the last year, partially on the back of the GENIUS Act getting approved by the U.S. Congress because it cleared the way for the rules of the road for stablecoin to be a part of the core infrastructure in the U.S. banking system. And that's important because it means that if we can tokenize money, then we can tokenize the flow of capital. And if we can tokenize the flow of capital, there are a lot of forms of capital that really get stuck in different collateral pools around the world today, whether it's treasuries, equities. Other fixed income products, money market funds. But if you tokenize all those instruments along with the flow of money, then the collateral becomes very fluid, and that will free up tens and tens of billions of dollars of capital that's trapped with bank capital that's trapped within the collateral pools today.

3:56因此，機構現在非常有動力把這些基礎設施建起來。散戶生態系其實早就領先十年，他們希望隨時隨地交易任何資產。如果能把資產代幣化，資金就能靈活流向各種可交易工具。這種需求已經存在一段時間，但過去一年機構和散戶的興趣真正融合，推動了代幣化的巨大動能。So there's suddenly this institutional interest towards Wow, I can use that collateral and put it to work. So I'm very motivated to put that infrastructure in place. The retail ecosystem, as we know, has been kind of 10 years ahead. Retail investors want to be able to trade anything, all the time, anywhere. And if they can put it into a tokenized form and keep it there, it allows them to move their capital into lots of different tradable instruments. So that interest has been there for a while, but that convergence has really come in the last year, and that's why you're seeing so much momentum now towards tokenization.

4:32AI 與風險管理：金融科技的未來

4:32那人工智慧的角色呢？現在大家都會問這個問題。你觀察到 AI 如何改變交易所、代幣化等一切？Oh, interesting. So what's the role of artificial intelligence? We've got to ask about that these days, right? So what are you seeing with that? How is that changing exchanges, tokenization, everything?

4:45很有趣的是，這些技術正好同時發展。當你必須隨時即時管理風險時，光靠人力會非常困難。因此我們大量運用 AI 在反金融犯罪領域，例如反洗錢、詐騙偵測等。我們的 AI 能力非常先進，服務全球 2,800 家銀行，無論是傳統演算法還是生成式 AI，都能大幅提升效率與效果，協助揪出犯罪分子。It's so interesting that these technologies are actually coming together at the same time, because as I mentioned, if you have to manage risk real time all the time, and you have to think about that, having a lot of humans in that loop is going to be very difficult. So bringing AI into the risk management frameworks, we leverage AI very extensively in anti-financial crime. So, you know, AML, so anti-money laundering, fraud detection, that we have very advanced AI capabilities. We serve 2,800 banks with our anti-financial crime technology, and the AI capabilities there, both algorithmic and Gen AI, is just amazing in terms of how to create more efficiency, but really much more effectiveness in rooting out criminal actors.

5:32另外在交易基礎設施方面，AI 也很重要。當你要 24/7 管理多種資產、數十億資本的風險和擔保品時，AI 可以大幅協助。我們在 Calypso 平台內推出一系列數位代理人，初期會給客戶風險建議，未來銀行甚至可能讓 AI 直接主導操作，讓人力退出 24/7 環境。AI 對於全天候交易至關重要，也會以許多方式改變金融業。But then you also have, as I mentioned, kind of trade infrastructure, and you'd say, well, why does that matter? Well, if you're managing risk 24/7 across multiple instruments with billions of capital, you need to make sure that you're properly reflecting your risk and you're properly reflecting your collateral, then moving that collateral. And AI can be hugely helpful. So we've launched a series of digital agents inside our Calypso platform, which is our trade infrastructure platform, that allows for clients. First, we would make recommendations in terms of how they, you know, what the risk recommendations are. But over time, we would expect that the banks would start to use that to actually drive the actual behavior. They may take the human out of the loop in a 24/7 environment. So. AI is critical for 24/7, but it also will change finance in many other ways. Right. Okay.

6:24Nasdaq 策略與全球市場布局

6:24能否談談 Nasdaq 的整體策略？你們現在的重點是什麼？Can you talk a little bit about Nasdaq's overall strategy, kind of 40,000-foot level? What are you focusing on? Some of it you've talked about already, but just in general, where is the exchange headed?

6:38我們聚焦三大策略支柱。第一是打造全球最現代化的市場。第二是確保市場的誠信，例如反金融犯罪、風險管理、監控等技術都要最先進，保障全球金融體系安全。第三是推動創新經濟。我們很幸運成為全球最具創新力企業的上市地，也能基於 Nasdaq 100 指數等推出可投資產品，目前我們指數相關的資產管理規模已突破一兆美元，對整個體系產生巨大影響。Yeah, so, well, we've been focused on three key pillars of our strategy because as we've grown and expanded the business to really leveraging the market infrastructure and having a bigger impact on the industry, we've been really excited about three key elements. So the first is, as I said, architecting the world's most modern markets. How do we really drive that? But the second is really driving, I would say, protecting the markets with integrity, and so making sure that, as I said, anti-financial crime, risk management, surveillance, those technologies are as advanced as possible to keep the world's financial system safe and secure. And then the third is powering the innovation economy. We are very fortunate to be the home of the most innovative companies in the world. But we also have the opportunity to create investable products on the back of our listings with the Nasdaq 100 index and other Nasdaq indexes. And we just crossed a trillion dollars in AUM, assets under management associated with our indexes. So we're really proud of the fact we have such a huge impact today across the system.

7:46IPO、AI 與新經濟浪潮

7:46那 IPO 管線和那些大型公司準備上市的情況如何？這跟代幣化和 AI 有什麼關聯？What about the IPO pipeline and just these— Mega companies that are looking to go public, what are you seeing with that, and how is that playing into the tokenization AI theme?

7:58其實你說得沒錯，過去一年有幾家推動市場代幣化的公司已經上市，主要集中在第一、二季。同時我們也看到 AI 基礎設施、模型公司本身，以及整個 AI 交易規模都非常龐大。能源、建設、資料中心、記憶體、半導體等硬體產業，以及 SpaceX 今年也上市，還有未來會在 AI 基礎上誕生的應用公司。這是一個全新的經濟體，將需要大量資本，而公開市場正是重要資本來源，私募市場也一樣。公私市場的融合越來越明顯，未來還會有更多優秀公司上市。Well, I think that—well, actually, you're right, because I think you've seen several companies that are really driving the tokenization of markets come public earlier in the year. That happened primarily, I would say, in Q1 and into Q2. And then we've seen, of course, the AI build-out, you know, the infrastructure that supports AI, the model companies themselves, as well as, you know, just the overall AI trade is enormous, let's just say. So you've got the energy companies, the construction companies, data center companies. Memory companies, semiconductor companies. So there's hard tech, there's hard infrastructure, there's energy, and then there's also, of course, all the applications, the model companies themselves, with SpaceX going public earlier this year as an example of that, and then also all the application companies that are going to be built on the back of AI. It is a new economy. That's being created today. I mean, it's incredible, and it will require a lot of capital. So we're very proud of the fact that the public markets are a great source of that capital, in addition to the private markets. I think it's been a real convergence of public and private, and we'll see. We'll see how we continue to see these great companies come to market.

9:14全球市場成長與區域機會

9:14你認為哪些地區最令人期待？亞洲或其他國家有什麼成長機會？美國市場雖然很大，但你還看到哪些亮點？What are you seeing as some of the more exciting geographies, whether it's, say, Asia or specific countries? What are you looking at for growth? I know the U.S. markets are always seen as so big and dominant, but what else are you seeing?

9:30我們在全球營運，支持世界各地的交易所和經濟體。東南亞多年來一直是 Nasdaq 的成長重點，因為亞洲在資產代幣化和加密生態系成熟度上領先，我們有很多機會為加密交易所和主流交易所提供技術，也協助銀行和券商提升風險管理效率。拉丁美洲近年來也成長很快，當地金融生態系和經濟體大幅成熟，現在比十年前更廣泛採用我們的技術。當然，美國和歐洲仍是最大市場，我們在北歐營運多個市場，瑞典是歐洲最成功的市場之一，上市公司數量領先，散戶投資活躍，也是我們的重要成長市場。Well, we operate globally, and we're really proud of the fact that we support exchanges and economies all over the world, and— So where we've seen growth in Nasdaq's business, Southeast Asia has been a growth area for us for many years, and it continues to be. I think because of the fact that Asia has been the home to really kind of the, I would say, the leader of tokenization and the maturation of the crypto ecosystem, we've seen a lot of opportunity to provide our technology to crypto exchanges. And to the ecosystem and mainstream exchanges as well across the region, and banks and brokers that want to manage risk in a more streamlined way. And then I think that Latin America actually has been a big growth area for us. They really worked hard to mature the entire financial ecosystem and economies there. And so they're leveraging our technology much more extensively today than we saw 10 years ago. That's been a huge growth area for us. But of course, U.S. and Europe continue to be the largest markets. We operate most of the markets in the Nordics. They're NASDAQ markets. Sweden is the most successful market in Europe, and we're really, really proud of that. They have more listings than most other countries in Europe. They're very active, lots of retail investment, so that's actually been a good growth market for us too.

10:52即時風險管理與主流金融融合

10:52我們再深入談談風險管理。當一切都即時化，挑戰也變大。你能多談談這部分嗎？現場很多人都需要面對風險管理。So let's go a little more into risk management. As we talked about, it does, when you get to real time, it gets more challenging. Can you just talk about that a little bit? Because I think most people in the crowd would need to deal with risk management on some level.

11:08在代幣化生態系，特別是衍生品領域，有所謂自動去槓桿（auto deleveraging）機制，這是他們處理結算失敗或單一參與者風險過高時的獨特方式。雖然這在目前的加密圈很有效，但我認為未來會演化成更適合主流金融的模式。舉例來說，現貨加密市場很難放空，所以產業會用衍生品和永續合約來創造槓桿和保證金，這些在現貨市場較難做到。美國現貨股票市場則有大量保證金和淨結算機制，這些都提升了資本效率。主流金融已經解決了很多這類問題，未來要把代幣化導入主流金融，做法可能會和加密圈不同。Yeah, and it's interesting because, as most of you all know, within a tokenized ecosystem, particularly in the derivative space, they have something called, you know, auto deleveraging. So there's a very unique way for them to manage any sort of— Failure, settlement failure. Think of it that way. Or the risk that's kind of one participant's taking on too much risk, or they have a position that they've gone onto the wrong side of a position, and they have to kind of manage through the cascading of that through this auto-deleveraging tool. I think it's a very interesting and unique capability, but I have a feeling that it will mature into something that probably will be more appropriate for mainstream finance. You know, right now that sits in a very confined, defined ecosystem. I'll give you an example. You know, in cash crypto, you really have a hard time shorting crypto. You can't take the other side of that. So the industry uses derivatives and kind of perpetual futures, essentially. But then they have that to create margin and leverage and other things that are also harder to do in the cash markets. In U.S. cash equities, there's a lot of margin, you know, there's a lot of, and there's also net settlements. So there's a lot of netting that happens as you trade throughout the day. That creates a lot of capital efficiency. So we already have a lot of those problems solved and— baked into our market ecosystem. So what we're going to have to do to kind of bring tokenization into mainstream finance might look a little different than how the crypto ecosystem works today, because some of those issues have already been solved in the mainstream financial ecosystem.

12:50未來金融機構要管理 24/7 的風險，若 CLARITY Act 通過，機構可能會將加密資產納入投資組合。這時候，即時管理數十億美元風險需要極高的專業，確保不會隨時站錯邊、不讓資產負債表暴露過多風險。我們很期待 Calypso 平台的 agentic 能力，因為它是全球經濟體核心的風險管理平台之一。So it's going to be interesting. But for a financial firm, if you're managing risk and you're suddenly an institutional firm and you're looking at, I want First of all, everything's going to go 24/7. I might introduce crypto into my cadre if the CLARITY Act ever gets approved. That will make it so the institutional ecosystem in the U.S. becomes more interested in that. Then they, I mean, managing billions and billions of dollars of risk in real time requires great, I mean, great skill. Making sure you're not on the wrong side of the trade at any given moment, making sure that you're not putting your balance sheet to risk. So we're very excited about the agentic capabilities we're creating within Calypso, because Calypso is one of the core risk management platforms for the world's economies. So we're very excited about what we're doing there. Okay.

13:40即時支付與反洗錢新挑戰

13:40你們如何應對反詐騙、反洗錢？延長交易時間和資產代幣化帶來哪些新挑戰？And how have you been dealing with anti-fraud, anti-money laundering? What— New dimensions does, say, the move to longer trading hours, tokenization bring?

13:49我們已經為 24/7 營運的市場提供監控技術。AML 和詐騙偵測方面，最大變化是即時支付的普及。以前收到電匯可以花 15 分鐘審查，現在一切都變成即時，連美國聯準會都推出 FedNow。銀行，特別是社區銀行，非常擔心如何應對這種變化。過去靠人力審查，現在我們提供先進演算法協助即時支付風險控管。即時阻止可疑支付和過去有 15 分鐘審查時間完全不同。Well, actually, we already provide surveillance technology to markets that operate 24/7. But I think on AML and fraud detection, what's interesting is it's been the move to real-time payments. So, and so, I mean, it used to be that you'd have time, you know, you get a wire. You spend 15 minutes reviewing the wire. You decide whether or not you're going to send that wire, and everything happens in human time. Well, as we know, the entire ecosystem has gone to real-time payments, and even the Fed, the New York Fed is built, or the U.S. Fed has built FedNow. So everything is moving to real-time and 24/7. So the banks, especially community banks, are very concerned about how do they manage that. They've always managed that kind of risk with humans. So now what we're doing is we're giving them very advanced algorithmic capabilities to manage real-time payments. To stop the payment before it goes is very different than, you know, stopping the payment before it goes in real time is very different than having 15 minutes to review a case before you send something.

14:54我們的 AI 能辨識不同犯罪行為的拓撲，例如兒童人口販運、恐怖組織、詐騙等，各自有不同行為模式。我們建立了能辨識這些行為的模型，並利用 Gen AI 分析跨銀行的網路行為。我們的平台能整合 2,800 家銀行的資料，追蹤全美支付網路，這是單一銀行無法做到的，必須靠整個體系合作。我們對這方面的成就非常自豪。So. That algorithmic capability with AI, we have very specific topologies of what kind of criminal behaviors exist in the system. Like a child trafficker behaves differently than a money launderer, you know, or I should say not a money launderer, than a terrorist network behaves differently than just a fraudster. And then fraudsters behave differently whether you're, you know, unfortunately they have things like elder abuse, they have— You know, their love scams and other things, they actually behave differently too. So we've built topologies that can identify different types of criminal behavior based on their behavior in the banking system. We then can look at networks now, which is really cool. We've brought in a lot of metadata leveraging Gen AI now, where we can look at networks much more holistically across the system. To understand how the networks operate across banks. And we have a very unique platform where we are able to bring the data together across 2,800 banks. So we can look at payor and payee across the entire banking system across the United States. So it's a very, very powerful capability when you bring big data together to solve the problem. This is not a problem that an individual bank can solve. This is only a problem that That the entire system has to solve together. So we're very proud of what we've done there to create that system.

16:13未來展望：24/7 資產交易與財富新機會

16:13你對 fintech、加密、AI 領域最期待什麼？未來哪些趨勢可能真正改變世界？What has you most excited in, say, the fintech, crypto, AI space? What are you looking at that maybe down the road you see as potentially becoming really useful?

16:24我認為最重要的是這個大趨勢：未來全球每一種資產都有機會 24/7 交易，雖然這是長遠目標，並非每個資產都足夠有流動性，但如果都能全天候交易，全球金融體系的連結性和網路效應會大幅提升。這讓全球 80 億人都能參與原本無法觸及的資產，帶來財富創造新機會，同時也讓大家更重視風險管理，學會主動掌控財務，思考短期與長期的財富規劃。看到這些技術融合真的很令人興奮。Well, I would argue that— It's more just the meta trend that's happening here. I mean, if we think about every asset class in the world having the opportunity to trade 24/7, and that's a long-term vision, I'll be honest. Not, you know, there's not every asset is liquid enough to support a 24/7 environment. But let's just argue that they all can trade 24/7. And you think about the, the— The interconnectivity and the network capability of the entire financial system. It brings the world closer together. It makes it so that investors can express—8 billion people can be investors across asset classes that maybe were not accessible to them before. It allows everyone to think differently about both their opportunities for wealth creation, but also the need for them to really be mindful of risk management. And taking control over their money and making sure that they're thinking both short term, but also long term about how to drive that wealth and change their lives. So it's very, very exciting to see all these technologies come together. Excellent.

17:30我們就到這裡，謝謝你，Adena。非常感謝你的分享。I think we're going to leave it there, but thank you so much for your time, Adina. Really appreciate it. Thank you. Thank you.