For centuries, central banks have issued money and safeguarded its value. That mandate has not changed. What has changed is the technological environment around it. Consumers increasingly pay digitally, financial institutions explore new technologies, and new players and infrastructures are reshaping how money is used across the economy. If central banks want to ensure that money remains stable, trusted and usable, they must help bring it up to date with technological developments. In contrast, if central bank money does not adapt to technological change, it risks losing relevance in key parts of the economy. This would weaken the role of public money as an anchor of stability, as well as increase fragmentation and the risk of instability in the financial system. We believe the appropriate policy response is not to resist digitalisation but rather to extend central bank money into this new technological environment while preserving its core attributes: safety, uniformity and reliability. Keeping pace with the digitalisation of money and payments Let me start by outlining how digitalisation is having an impact on every layer of our monetary and payment systems, and the specific challenges this raises for the euro area. Retail payments are becoming increasingly digital and platform-based. Wholesale financial markets are evolving as tokenisation and distributed ledger technology (DLT) develop. Used in the right way, digitalisation could help reduce costs and speed up cross-border payments, while avoiding the risk of further fragmentation. Policy responses need to be coherent on those three fronts, ensuring that innovation, efficiency and integration advance without undermining financial stability and trust in central bank money. These responses must also reflect the specific conditions in each jurisdiction. In the euro area, we face three main challenges. First, for retail payments we do not have a European digital means of payment that works consistently and seamlessly across the entire euro area. The solutions offered by European private digital payment providers are only available at national level and for certain use cases, while central bank money exists solely in the form of banknotes and coins, which of course cannot be used for online transactions. As a result, we rely heavily on a few non-European providers for retail payments, and this dependence clearly poses a risk. Second, in wholesale markets, most large-value transactions between euro area financial institutions are currently settled in central bank money through TARGET services. But this could change if central bank money does not adapt to tokenisation, which has the potential to transform financial markets. Tokenisation and DLT promise to make capital markets more efficient. Yet without tokenised central bank money at its core, the new ecosystem would rely on fragmented pools of settlement assets. Third, cross-border payments remain too slow, too costly and too opaque. Digital transformation could further increase fragmentation in this area. For a highly open economy like the euro area, where external trade accounts for around half of GDP, this is a significant concern. Modernising central bank money We are addressing these problems with the three key pillars of our comprehensive payment strategy.[1] First, we are getting ready to potentially issue a digital equivalent of cash: the digital euro. Second, we will make it possible to settle DLT‑based transactions in central bank money as of September this year. Third, we are working on interlinking fast payment systems to enhance global cross‑border transactions. In the face of technological change, it is our duty to reshape how we provide public money, such that it remains a risk‑free settlement asset and a foundation of trust on which the private sector can innovate and develop. Private payment solutions can bring efficiency, new functionalities and customer‑facing advancements. The role of central banks is not to replace the private sector. Instead, we must ensure that public money continues to anchor the financial system as technology evolves. In the euro area, we are applying this principle across the board. A digital euro for retail transactions Digitalisation is transforming the way households and firms make everyday payments, yet access to central bank money remains confined to cash. This raises a vitally important question: how can public money remain usable and relevant in an increasingly digital economy? The digital euro is intended as a digital form of cash for day-to-day use in retail payments. The objective is not to replace physical cash or private payment solutions. Instead, we want to complement existing means of payment by ensuring that central bank money is always an option and is accepted throughout Europe. The digital euro is designed as a payment instrument, not as an investment product. We envision it as part of a broader public‑private payments ecosystem. It will not yield interest, and individual holdings will be capped to preserve financial stability and ensure banks continue to provide credit to the economy.[2] We are convinced that people should always have access to a public option to pay digitally, wherever they are in the euro area – the digital euro can make this a reality. It will be available both online and offline, supporting resilience and protecting privacy. And, by helping to reduce reliance on a few dominant players, it will cut costs for merchants and ultimately lower prices for consumers. The digital euro will also have legal tender status, and common standards adopted by virtually all points of sale across the euro area will facilitate its acceptance everywhere. Banks and other providers will be free to use this public infrastructure and thus to scale up the payment services they offer at European level. This will make it easier for private payment solutions to be rolled out throughout the euro area. We have recently signed agreements with three European standard‑setting organisations – European Card Payment Cooperation, nexo standards and the Berlin Group – so that their technical standards can be used for acceptance of digital euro online payments at points of sale.[3] By leveraging these open standards and working closely with the respective standardisation bodies, the ECB minimises adoption costs for the market. This approach will simplify digital euro acceptance, create a uniform user experience across the euro area and enable European payment schemes to expand without requiring technical upgrades to payment terminals. Assuming that European co-legislators adopt the Regulation on the establishment of the digital euro this year, a pilot exercise and initial transactions could take place as of mid-2027, and the digital euro could be ready for first issuance in 2029. Importantly, we will not need to wait until then to see the incentives materialise for private payment providers to expand their existing product offerings and geographical reach. Merchants will likely start to adopt these standards immediately after adoption of the digital euro Regulation. This step will remove any remaining uncertainty in this area, which has been under discussion for almost three years. A tokenised euro for wholesale transactions Let me now turn to wholesale transactions. Financial markets are undergoing structural change. By representing financial assets as digital tokens – or, put simply, files – tokenisation makes it possible to transfer and update assets more efficiently than is currently the case. It allows the entire life cycle of an asset – from trading to settlement to custody – to run on the same platform, available 24/7. And it supports automation through smart contracts. In a nutshell, tokenisation holds the promise of faster transactions with lower processing costs. However, this promise is predicated on the possibility of having on-chain settlement assets in tokenised form.[4]These may be either private or central bank liabilities, as is already the case today. Stablecoins are currently the leading private solution. They got off to an early start by offering a tokenised settlement asset widely used in crypto markets. More recently they have been put forward as a solution to improve cross-border payments. They can also be used to settle on-chain transactions of tokenised traditional assets. They offer speed, programmability and continuous availability. Stablecoins nevertheless carry credit and liquidity risk and may have an impact on financial stability.Their safety depends on the quality and liquidity of reserves, the robustness of redemption arrangements, and effective regulatory oversight. If widely adopted, they may bring about profound change in the role played by commercial banks in maturity transformation and as the major channel for financing the real economy.[5] But stablecoins are only one of several possible tokenised settlement assets. Tokenised deposits, for example, could offer a private alternative. Time will tell which of these private solutions will prevail or if they will manage to coexist.[6] In any event, in the Eurosystem we think that all forms of tokenised private money will benefit from the availability of tokenised central bank money. Central bank money provides risk-free settlement, ensures payment finality and supports confidence in market infrastructure. These aspects will help the tokenised ecosystem grow and will support integration. With a larger market, demand for all forms of tokenised settlement assets, including private ones, will increase. The result will be similar to the current system where public and private settlement assets coexist. To make sure that Europe reaps the benefits of tokenisation and supports the creation of an integrated European market for digital assets, the Eurosystem is pursuing a staggered approach.[7] We are connecting market DLT platforms to our existing TARGET services to be able to settle tokenised asset transactions in central bank money. As part of our Pontes project, this service will be available as of the third quarter of this year. We are working continuously with the private sector to establish a longer-term vision for how a fully integrated tokenised ecosystem could operate, including by inviting feedback on the Appia roadmap published earlier this year. We aim to present a comprehensive blueprint in 2028.[8] This work complements the European Commission’s efforts to remove regulatory barriers to the wider use of tokenisation. In particular, the Commission has proposed extending and simplifying the DLT Pilot Regime to enable firms to test and scale DLT applications. At the same time it is reforming the Central Securities Depositories Regulation to enable large-scale activities of central securities depositories using DLT. Looking ahead, it will also be important to consider whether fostering an integrated European market for digital assets would benefit from a dedicated EU legal framework allowing tokenised assets to be issued, held and transferred seamlessly across the EU.[9] Interlinked fast payment systems for cross-border payments Finally, let me turn to cross-border payments. Despite technological progress, cross-border payments remain comparatively slow, expensive and opaque when measured against domestic payments. These frictions affect households, firms and financial institutions. They hamper international trade and financial integration and make remittances slow and costly.[10] Addressing these frictions is a shared international policy objective which we are pursuing by giving strong support to the G20 cross-border payments agenda.[11] But these frictions could worsen if new technologies increase fragmentation. We therefore need to overcome this risk. The Eurosystem’s TIPS infrastructure already offers instant payments not only in euro but also in other currencies, including the Swedish krona and the Danish krone. But to take our response to cross‑border inefficiencies even further, we are working on interlinking fast payment systems available in many other countries, including outside the European Union.[12] This interlinking will allow payments to move seamlessly across borders without undermining countries’ monetary sovereignty, as could happen with the spread of stablecoins denominated in a dominant currency. This approach builds on existing infrastructures rather than replacing them with entirely new global systems. It promotes trust and protects the monetary sovereignty of the participating jurisdictions. Conclusion Let me conclude. Across retail, wholesale and cross‑border payments, our goal is to preserve trust and stability, as technology reshapes how money is used. The private sector will continue to drive innovation. By modernising central bank money where needed and making sure it is available across all domains, the public sector must make sure that it continues to be the anchor underpinning the financial system. Thank you. ECB (2026), The Eurosystem’s comprehensive payments strategy, 31 March. Cipollone, P. and Elderson, F. (2026), “Digital euro: an opportunity for banks”, The ECB Blog, 27 March. ECB (2026), “ECB signs agreements with European standard setters to facilitate digital euro payments”, press release, 24 April. See Cipollone, P. (2026), “Sparking the transformation of finance: tokenisation and the role of central banks”, keynote address at the 24th Annual Symposium on “Building the Financial System of the 21st Century: an Agenda for Europe and the United States”, hosted by the Harvard Law School and the Program on International Financial Systems, Washington DC, 15 April. See Altavilla C., Boucinha M., Burlon L., Adalid R., Fortes R. and Maruhn F. (2026), “Stablecoins and Monetary Policy Transmission”, Working Paper Series, No 3199, ECB, Frankfurt am Main, and Cipollone, P. (2026), “Digital assets, payment efficiency and monetary policy”, speech at a workshop on digital assets and monetary policy transmission organised by the European Central Bank, Banca d’Italia, the Euro Area Business Cycle Network and the Centre for Economic Policy Research, Rome, 4 May. See Lagarde, C. (2026), “Stablecoins and the future of money: separating functions from instruments”, speech by Christine Lagarde, President of the ECB, at the Banco de España LatAm Economic Forum in Roda de Bará, 8 May. See Cipollone, P. (2026), “Building the rails for Europe’s tokenised financial markets”, keynote speech at an event on “Building Europe’s integrated digital asset ecosystem: from vision to implementation” hosted by the House of the Euro, Brussels, 23 March. ECB (2026), Appia – paving the way for a future-ready, integrated financial ecosystem leveraging tokenisation and DLT. See Cipollone, P. (2026), “Building the rails for Europe’s tokenised financial markets”, op. cit. See Panetta, F. (2026), “Interconnect to stabilize: cross-border payments in a fragmenting world”, keynote speech at the Embassy of Italy to the United Kingdom on ”Cross-Border Payments at a Turning Point”, London, 5 May. See paragraph 16 in G20 (2020), G20 Riyadh Summit Leaders’ Declaration, 22 November; Financial Stability Board (2020), Enhancing Cross-border Payments – Stage 1 report to the G20, 9 April; Committee on Payments and Market Infrastructures (2020), Enhancing cross-border payments: building blocks of a global roadmap – Stage 2 report to the G20, Bank for International Settlements,13 July; and Financial Stability Board (2020), Enhancing Cross-border Payments – Stage 3 roadmap, 13 October. See Cipollone, P. (2026), “The quest for cheaper and faster cross-border payments: regional and global solutions”, speech at the BIS Annual General Meeting, Basel, 27 June.

The Swedish Financial Supervisory Authority (FI) issues Norion Bank AB (Norion) a remark and an administrative fine of 90 million kronor for violations of anti–money laundering regulations. Summary Norion Bank AB (Norion or the bank) has authorisation to conduct banking business in accordance with the Banking and Financing Business Act (2004:297). Pursuant to this authorisation, the bank offers different types of loans, for example corporate and real estate loans, and deposit accounts, for example savings accounts. The bank also offers other types of financial services and products, such as factoring and payment services. The bank’s customer base includes both natural persons and legal entities.  Finansinspektionen has investigated, among other things, Norion’s compliance with customer due diligence provisions set out in the Anti-Money Laundering and Counter-Terrorist Financing Act (2017:630). The authority has reviewed the measures the bank has taken with regard to customers who are legal entities. The investigation shows that Norion has not taken necessary measures to sufficiently assess whether customers associated with a medium or high risk of money laundering and terrorism financing had beneficial owners who were politically exposed persons or family members or known colleagues of such a person. Neither has the bank taken any enhanced customer due diligence measures to obtain more detailed information about high-risk customers’ business activities or financial situation or the source of their money. There are no grounds on which to forego an invention against Norion. However, the violations are not so severe as to present cause to consider withdrawing Norion’s authorisation or issuing the bank a warning. Finansinspektionen is therefore issuing Norion a remark that, in order to be an adequate intervention, will be accompanied by an administrative fine of SEK 90 million.   Press Office    +46 (0)8-408 980 33

Gold-i, a global leader in FX and crypto trading technology, is offering its clients access to the largest onchain options exchange, Derive.xyz through its ultra-low latency multi-asset liquidity management and distribution platform, MatrixNET. This is Gold-i’s second DeFi integration, following on from its recent integration with Hyperliquid, a decentralised exchange for perpetual futures and spot crypto trading. By integrating Derive.xyz into MatrixNET, Derive’s liquidity can be accessed by Gold-i’s large client base of brokers, prop trading firms and fund managers via a range of platforms including MT4, MT5, DXtrade and CLEO. The integration also creates opportunities for Gold-i to expand to Derive’s client base of treasuries and foundations. Nick Forster, CEO, Derive.xyz said, "Being the first options protocol integrated into MatrixNET is a meaningful milestone; it signals that institutional infrastructure is taking onchain derivatives seriously. More importantly, it opens a door that wasn't there before. Institutional users of MatrixNET can now access Derive's onchain options liquidity directly, without friction. TradFi and onchain are converging, and this integration is exactly the bridge we always knew was coming." Tom Higgins, CEO, Gold-i added, “Derive is a market leader in the rapidly growing niche area of onchain options, currently doing about 90% of onchain options volume. Integrating Derive into MatrixNET aligns perfectly with our strategy of connecting clients to the best liquidity venues across both TradFi and DeFi. “Having had a fantastic response from clients since announcing our Hyperliquid integration, we believe this latest integration will further enhance our offering, enabling clients to access new opportunities through a seamless, institutional-grade environment.” Gold-i’s MatrixNET, trusted by brokers, fund managers, prop trading firms and crypto institutions worldwide, empowers users with a multitude of routing and aggregation methods and the ability to tailor execution models to suit the unique preferences of different client types. Amongst the many benefits, Gold-i’s ultra-low latency liquidity management platform enables institutional clients to access deep liquidity pools, achieve better prices, gain more clients and reduce toxic trading.

The Depository Trust & Clearing Corporation (DTCC) is in the final stages of preparing for the National Securities Clearing Corporation's (NSCC) transition to 24-hour, 5-day-a-week (24x5) trading, set to go live on June 28. This move represents a major expansion of access to U.S. equities markets, driven by growing demand from global retail investors who wish to trade across different time zones. Val Wotton, Managing Director and Global Head of Equities Solutions at DTCC, commented on the upcoming launch, stating, "With one month to go... the industry is entering the final stage of readiness for a significant expansion in access to U.S. equities markets." Wotton highlighted that this milestone is a crucial step toward creating a more accessible and globally connected marketplace. In the lead-up to the go-live date, DTCC has been collaborating closely with its members and infrastructure partners to ensure a smooth transition. The focus has been on maintaining the resilience of clearing, risk management, and liquidity processes as trading activity extends over a longer day. "We remain focused on supporting a smooth transition and enabling market participants to operate confidently in an environment that expands access and participation in U.S. markets,” Wotton added. The initiative aims to provide a robust framework that supports the extended trading hours while ensuring market stability and security.

Thank you Linda, and thanks to the Institute of International Economic Law at Georgetown Law for having me. I have to begin by reminding you that my views are my own as a Commissioner and not necessarily those of the Commission or my fellow Commissioners. Given that this workshop is part of the PETshop series, I feel I need to start with a twist on the Pet Shop Boys’ famous line: “You’ve got the brawn; You’ve got the brains; Go make good privacy tech.” I signed on to be part of this conference very early on in the planning process, because privacy-enhancing technologies and the policy issues they raise are very important to me and should be to everyone in government. We regulators serve the American people, and privacy is integral to people’s safety in this digital world. Their need for privacy should be our concern. Too often, though, the discourse in this city about privacy casts anyone who demands it in a negative light. I have watched in troubled amazement as the goal of facilitating government surveillance drives regulatory decisions and expectations about how products and services should be built. The legitimate needs of people for products that protect their privacy take a backseat. Empowering government to be able to identify, pursue, and punish the bad guys is important to the security of the nation and its people, but so too is empowering people to protect information about their lives, including their financial lives. Helping people to keep financial transactions private obstructs criminals who seek to steal and terrorize. We cannot let a legitimate desire for security from reprobate nation states and criminal organizations steal the freedom that defines this nation and its people. I urge us as a society to view technologies as an opportunity to increase people’s ability to protect themselves from bad actors, not as an opportunity for the government to watch more of what its citizens do. These new technologies should be an opportunity for us to refocus government surveillance on bad actors and activities that are most likely to be nefarious and away from the everyday actions of innocent people. So often in a discussion about privacy, we talk about how we can balance the need to keep personal information private with the need to defend our nation. But little focus is often given to the fact that these interests are not diametric opposites. In fact, privacy can help enhance investor protection. We think about this fact in the context of the Crypto Task Force’s work. Current regulations require transfer agents to record the name and physical address of security holders. Permissionless crypto networks allow for the movement of funds through pseudonymous public wallet addresses. On many crypto networks, these addresses allow anyone to verify exactly where a certain asset resides. The address also allows for a degree of privacy; my public address is just a code of alphanumeric characters with no personally identifiable information. If transfer agents were given the flexibility to record that securities reside on the blockchain at a public address, we could save investors the risk of having to hand over information about where they live to people they have never met and rarely interact with. Another honeypot of data would be spared. I understand skepticism and fear about technology. Over the weekend, I listened to a Lone Ranger episode on an old-time radio show. I identified with the curmudgeon who tried to block the telegraph lines from crossing his land. He changed his tune when the same telegraph he condemned enabled his daughter to get the lifesaving medicine she needed. That old radio show is a good reminder for all of us that first impressions of technology are often incomplete. In an environment full of curmudgeons, this group is a breath of fresh air. I appreciate your efforts to show us how we can use new technology to preserve privacy while allowing regulatory agencies to pursue their legitimate responsibilities. You recognize the legitimate concerns about the technology but are optimistic enough to think you can build solutions that address them without compromising fundamental rights. If you have technologies that you think could accomplish the goals of Know Your Customer (KYC) and anti-money laundering regulations while limiting the collection and storage of personally identifiable information, please reach out and talk with the Crypto Task Force. Thank you for your time. I’m happy to take questions and make this more of a dialogue.

Fiserv, Inc. (NASDAQ: FISV), a leading global provider of payments and financial technology, and Cognition, the AI agent lab, today announced a strategic partnership to deploy Cognition’s AI software engineer, Devin, to accelerate the modernization of core banking technology and shorten the time it takes for new capabilities to reach Fiserv financial institution clients. By shortening release cycles and strengthening platform performance, the partnership supports Fiserv’s ability to deliver innovation at speed, while maintaining stability, security, and resilience. Modernization is among the most significant and historically slowest initiatives in financial services. Devin is uniquely suited to accelerate this work, operating at scale across complex codebases. Fiserv plans to deploy Devin across core platform modernization and other strategic engineering initiatives — executing complex engineering work in parallel and accelerating the pace at which Fiserv ships new capabilities to clients. As part of the deployment, Fiserv is also strengthening governance and security controls for AI-assisted development to help protect the integrity of the software lifecycle.  This partnership builds on Fiserv's broader commitment to embed AI across its technology operations and product development in ways that translate into tangible client value. Devin's ability to take on end-to-end engineering tasks including understanding codebases, writing, and testing code, and iterating autonomously, extends engineering capacity so teams can focus on delivering high-quality improvements that matter most to clients, from shipping enhancements, strengthening quality checks, to improving platform resilience. The collaboration reflects Fiserv's strategy to bring AI into every part of how it serves financial institutions — from the technology and engineering that power Fiserv platforms, to the operations that support them. "Speed matters more than ever in banking, and our clients are counting on us to deliver. With Devin, we can accelerate modernization of the platforms our clients run their business on, ship new capabilities faster, and free our teams to focus on the work that matters most," said Dhivya Suryadevara, Co-President of Fiserv. "Fiserv is exactly the kind of organization where Devin creates compounding value — massive scale and an engineering organization that has ambitious goals for what it needs to build and maintain," said Russell Kaplan, Co-Founder and President, Cognition. "We are proud to partner with Fiserv to help teams deliver measurable improvements, so clients see faster access to new capabilities, more consistent releases, and continued focus on quality and security." Fiserv is among a growing number of financial services organizations deploying Devin to accelerate product delivery, modernize platforms, expand automated testing, and strengthen governance for AI-assisted development ensuring innovation reaches clients faster and more reliably.

The Stock Exchange of Thailand (SET) has been monitoring trading activity of securities in the ETRON sector and has observed that, over the past week, prices and trading volumes have increased significantly. This was partly driven by strong operating results and investment plans announced by companies involved in AI and Data Center businesses, both domestically and internationally. However, certain securities within this sector have seen prices, trading volumes, and turnover ratios rise substantially, with Price-to-Earnings (P/E) and Price-to-Book Value (P/BV) ratios reaching elevated levels, reflecting speculative activity beyond fundamental support. If abnormal trading conditions are detected, such as prices, volumes, or turnover ratios reflecting excessive speculation without fundamental support, or if trading conditions remain inconsistent with fundamentals even after the market surveillance measures have been applied, SET will consider imposing the Market Surveillance Measures Level 1 or escalating to higher-level measures  (Level 2 and 3) as appropriate. Currently, CCET and SMT are subject to the Market Surveillance Measures Level 1, and DELTA remains in its Cooling Period and may be subject to an escalation of measures. Therefore, SET urges all investors to carefully consider fundamental data and other material information before making any trading decisions. Remark: Under the Market Surveillance Measures, securities companies are required to comply with the following:              Level 1: Excluded from credit limit calculation; purchase by Cash Balance only (100                          percent cash payment required)             Level 2: All Level 1 measures, plus prohibition on net settlement and trading via auction                           method only.             Level 3: A one-day suspension of trading, followed by all Level 2 measures upon                           resumption of trading.   Cooling Period: During the one-month period following removal of the Market Surveillance Measures, if any abnormality is detected, the security will be reinstated under the Market Surveillance Measures or placed under a higher level of measures if the trading abnormality has increased.

Oxford Risk, the leading behavioural finance fintech serving wealth managers, advisers, banks, and pension providers, today publishes new research revealing that standard risk-profiling approaches can materially underestimate the level of investment risk that is suitable for many investors. The analysis, based on 87,109 investors assessed using Oxford Risk’s suitability tools, compares each investor’s Attitude to Risk with their Suitable Risk Level. It finds that, where suitability is assessed only by reference to Attitude to Risk, or where Risk Capacity is not modelled systematically, many investors would be placed in portfolios that are too cautious for their overall financial position. Oxford Risk’s modelling suggests that placing investors at their modelled Suitable Risk Level, fully accounting for both upward and downward differences from Attitude to Risk, produces an aggregate projected growth differential of 7.5% over 10 years in an average market, rising to 17.6% in a very good market. These figures compare modelled outcomes from investing clients according to Attitude to Risk alone with investing them according to their Suitable Risk Level. Attitude to Risk reflects an investor’s stable, long-term willingness to accept the possibility of lower long-term outcomes for a greater chance of higher long-term returns. Suitable Risk Level is the risk level appropriate for the investor’s investible assets once the full suitability picture is considered, including Risk Capacity, Behavioural Capacity, Knowledge and Experience, and relevant preferences. Put simply, Attitude to Risk is not being changed. It remains the anchor for the investor’s overall willingness to take risk. But where an investor has strong wider financial circumstances, including total wealth, future earnings, spending resilience, and limited reliance on current investible assets, those investible assets may need to take more risk to ensure the investor’s overall financial position is aligned with that willingness. The cost of under-risking The findings show a significant asymmetry in how suitability may affect investment risk levels. Across the sample, 55% of investors had a higher Suitable Risk Level than their Attitude to Risk alone would indicate, compared with 14% whose Suitable Risk Level was lower. This matters because the industry has traditionally focused heavily on preventing investors from taking too much risk. That remains essential. But Oxford Risk’s analysis shows that the opposite problem can also be material: investors may be left too conservatively positioned if their financial capacity to take risk is not properly captured and systemised. Even across the full sample, where upward and downward differences partly offset each other, the modelled effect remains material. For individual investors whose Suitable Risk Level differs significantly from their Attitude to Risk, the difference in long-term outcomes can be much larger. For wealth managers and advisers, these figures represent not just a client outcome issue, but a commercial one. Across a client base of meaningful scale, systematic under-risking can become a significant drag on AUM growth and on the long-term value that advice delivers. A structural gap in suitability practice Greg Davies, Head of Behavioural Finance at Oxford Risk, said: “The industry has spent years making sure investors are not put into portfolios that are too risky for them. That is right. But it is only half the suitability challenge. “Our research shows that more than half of investors in this sample had a higher Suitable Risk Level than their Attitude to Risk alone would indicate. This is not about encouraging reckless risk-taking. It is about recognising that Attitude to Risk is only one part of suitability. “For many investors, especially those with strong Risk Capacity, their investible assets need to take more risk so that their overall wealth position is aligned with their underlying willingness to take risk. If firms only systemise the reasons to reduce risk, but not the reasons to take more, clients can be left too conservatively positioned. The cost compounds quietly over time.” James Pereira-Stubbs, Chief Client Officer at Oxford Risk, said: “For wealth managers, this is not a niche modelling issue. It is a growth, client outcome, and Consumer Duty issue. Firms need to show that they are helping clients take the right level of risk, not simply avoiding excessive risk. “At scale, small systematic errors in risk matching can compound into material foregone wealth for clients and lower AUM growth for firms. Better suitability is not a brake on growth. Done properly, it is one of the foundations of it.” The research highlights the particular challenge in the mid-range Attitude to Risk bands, including Medium Low, Medium, and Medium High, where investors with apparently similar Attitudes to Risk can have very different Suitable Risk Levels. This reflects the complexity of factors that bear on suitability at these levels, including current wealth, future earnings, spending needs, reliance on investible assets, Knowledge and Experience, and Behavioural Capacity. Oxford Risk argues that addressing this blind spot requires a more systematic approach to suitability: one that treats Attitude to Risk as a stable anchor, models Risk Capacity at the level of the investor’s total wealth and financial circumstances, and applies the same rigour to identifying when investors can appropriately take more risk as it does to identifying when they should take less. In practical terms, this means moving beyond risk questionnaires that produce a single score, towards suitability frameworks that combine psychological willingness, total-wealth Risk Capacity, behavioural resilience, Knowledge and Experience, and relevant investor preferences. Methodology note The model compares projected 10-year outcomes from investing according to Attitude to Risk alone with projected outcomes from investing according to Oxford Risk’s Suitable Risk Level, using Oxford Risk’s risk-level return assumptions under average and very good market scenarios. The analysis assumes a standard investment value of £100,000 for each investor, so that the results reflect differences in suitable risk positioning rather than differences in client wealth.

BMLL, the leading, independent provider of harmonised, Level 3, 2 and 1 historical data and analytics to the world’s financial markets, today welcomes Five Rings to its Client Product Advisory Board (CPAB).  Five Rings is a New York-based proprietary trading firm founded with a vision of combining quantitative expertise, rapid innovation, and highly-scalable technology to succeed in today’s global markets, trading in various domestic and international markets, both established and esoteric.  They join the CPAB in support of its mission to elevate the standard of historical market data for the benefit of the entire industry and to offer its breadth of technological and market structure expertise  to help shape BMLL’s future product roadmap. Five Rings values BMLL Data Lab, the scalable Python research sandbox that provides access to full-depth, Level 3 order book data; and BMLL Data Feed for flexible data delivery.  With experience in quantitative trading across asset classes, Five Rings relies on high-fidelity data to explore new market opportunities, to make effective data-driven decisions, and to enhance its quantitative research and analytics workflows. BMLL added OPRA options data in November 2024, and today, over seven years of historical, nanosecond unconflated OPRA options data are available to market participants globally, complementing BMLL’s existing US equity and futures datasets. OPRA options data is immediately available via BMLL Data Lab and BMLL Data Feed, via AWS S3, and at multiple levels of conflation that suit clients’ individual specific requirements. Parker Lim, Head of Special Projects, Five Rings, said: “We work in teams of quantitative researchers, developers, and traders, continuously seeking new opportunities and deploying our strategies. BMLL’s high-quality data and research environment have become instrumental as we continue to expand into new markets and modes of execution, enabling us to perform reliable quantitative analysis to move quickly from insight to implementation.”  BMLL Chief Executive Officer, Paul Humphrey, said: "The CPAB continues to gain strong momentum as a client-led initiative, and we’re delighted to welcome a highly sophisticated firm like Five Rings to the community. Leading firms like theirs are placing trust in our data normalisation capabilities and are increasingly leveraging our historical data to shape their global strategies.  While their involvement gives them visibility of and input into the evolution of BMLL’s product offering, their contribution to the CPAB provides us with valuable insight as we look to elevate the standard of historical market data across the industry.” Launched in February 2025, in response to client requests, the CPAB is a forum that aligns the leading sovereign wealth funds, asset managers, banks, liquidity providers, and proprietary trading firms around a common goal: to set the standard of historical data across the industry. Specifically, member firms collaborate and define best-in-class data symbology and normalisation processes and protocols, data delivery methods and coverage needs, and make these available to the wider market.  Globally, BMLL’s historical market data now covers more than 100 trading venues, spanning global equities, ETFs, futures and US equity options; its equities offering covers 100% of the MSCI World Index.

Nasdaq (Nasdaq: NDAQ) announces that trading in BioMar Group A/S (ticker: BIOMAR TEMP) commences today on the Nasdaq Copenhagen Main Market. BioMar is a Large Cap company within the Supersector and the 12th company to be admitted to trading on Nasdaq’s Nordic and Baltic markets* in 2026.  BioMar is the world’s third-largest global producer of feed for high-value farmed fish and shrimp by volume, supporting a more efficient and sustainable global aquaculture industry through innovation and partnerships.  “Our listing on Nasdaq Copenhagen marks a major and exciting milestone in BioMar’s history. I would like to thank our new shareholders for the trust and confidence you have shown in us. Your support confirms a shared belief in the need to prioritise building better food systems, and that efficient and sustainable feed solutions will be fundamental to the future of aquaculture. I am happy to witness that cornerstone investors, a broad range of institutional investors, and so many retail investors are joining us on this long-term journey. Alongside our leadership team, I look forward to shaping BioMar’s future as a listed company, driving innovation and long-term value creation,” says Carlos Diaz, CEO of BioMar Group.  “We are pleased to welcome BioMar Group to the Nasdaq Copenhagen Main Market. This listing marks an important milestone for the local capital market, and we look forward to following BioMar’s journey as a listed company. We are committed to supporting its continued growth, innovation and contribution to a more sustainable aquaculture industry,” says Carsten Borring, Head of Listings, Nasdaq Copenhagen.   *Main markets and Nasdaq First North at Nasdaq Copenhagen, Nasdaq Helsinki, Nasdaq Iceland and Nasdaq Stockholm as well as Nasdaq Baltic 

The European Securities and Markets Authority (ESMA), the EU's securities markets regulator, has published the following question and answer: EU ESG Ratings Regulation (ESGRR) Defined ranking system (2853) Transitional provisions (2854) ESG rating providers established after date of entry into force (2855) Material changes to registration information (2856) Market Abuse Regulation (MAR) Regulation Annually conducted audit under Commission Delegated Regulation (EU) 2016/957 (2839) Markets in Crypto-Assets Regulation (MiCA) Exemption from white paper requirements when offering a crypto-asset other than an ART or EMT (2671) Questions and Answers section

Good morning. It is an honor to be here at the Bank of Japan, and I appreciate the opportunity to speak with you today.1 I am looking forward to our discussion, but first I want to share some framing thoughts. I will briefly discuss three developments in the global economy that I am monitoring, and then I will update you on my outlook for the U.S. economy and the path of monetary policy. The first global development I am tracking is the significant increase in energy prices due to the conflict in the Middle East. The rise in crude oil prices poses downside risks to growth and upside risks to inflation around the globe. Elevated energy prices are particularly challenging for countries like Japan that are net energy importers. While being a net energy exporter buffers the U.S. to an extent against energy shocks, it is not immune to the effects of disruption to global supply. Gasoline prices in the U.S. increased significantly since the onset of the conflict and remain notably elevated. I am watching whether higher energy prices will start to weigh on consumer spending. The second development is the rapid advancement of artificial intelligence (AI) technology. As a central banker, I am optimistic about AI's promise to drive productivity and growth, though I am also monitoring its effects on the labor market and inflation. And the third development is the effects of disrupted trade flows on the global economy. Since the pandemic, there have been multiple disruptions to global trade that have affected both supply and price levels. Against this global backdrop, my focus, of course, is on the U.S. economy. Recent economic growth in the U.S. has been solid, though I expect a more modest pace of growth this year as households face high energy costs. The U.S. labor market is broadly stable, with both hiring and firing at relatively low levels. I see risks to the labor market as somewhat skewed to the downside. Disinflation in the U.S. stalled over the preceding year, largely because of increased tariffs. In recent months, inflation moved notably higher because of higher energy costs. I expect inflation to decline later this year as the effects of tariffs and the energy shock wane, but I view risks around my inflation outlook as tilted to the upside. I am firmly committed to returning inflation to the Federal Open Market Committee's (FOMC) 2 percent target, aligned with our dual-mandate objectives of price stability and maximum employment given to us by Congress. At our last meeting, in late April, the FOMC decided to maintain the target range for the federal funds rate at 3-1/2 to 3-3/4 percent. I believe this policy stance leaves us well positioned to respond to economic developments based on the incoming data, the evolving outlook, and the balance of risks. I have not prejudged the next meeting and look forward to engaging with my colleagues about the policy necessary to best achieve our dual-mandate goals. Thank you once again for the opportunity to speak with you today. I look forward to our discussion. 1. The views expressed here are my own and are not necessarily those of my colleagues on the Federal Reserve Board or the Federal Open Market Committee. 

Under the U.S. G20 Presidency, G20 and Paris Club members have published a template MOU to demonstrate the features of a sovereign debt treatment by official bilateral creditors under the Common Framework.  Publishing the template achieves a key deliverable for the U.S. G20 Presidency.  The template outlines the general terms and conditions between borrowing countries and their official bilateral creditors, which will help to increase the transparency of the process and improve the speed and clarity of debt restructurings.  Such transparency not only improves the monitoring of debt developments and helps to address vulnerabilities, it also facilitates coordinated action to achieve faster debt workouts. To view the template MOU, click here. 

The Commodity Futures Trading Commission today announced it has filed a complaint in the U.S. District Court for the Southern District of New York against Michele Spagnuolo, a resident of Switzerland. The complaint alleges that Spagnuolo, a Google employee, engaged in insider trading on Polymarket.com using sensitive nonpublic information regarding Google’s official Year in Search list for 2025. In the complaint, the CFTC seeks restitution, disgorgement, civil monetary penalties, trading and registration bans, and a permanent injunction against further violations of the Commodity Exchange Act and CFTC regulations, as charged. “As I have said repeatedly, the Commission will not tolerate fraud, manipulation, or insider trading, regardless of the technology or platform that is used,” said Chairman Michael S. Selig. “Today’s action further underscores our commitment to rooting out insider trading and promoting market integrity in prediction markets.” “Employees who are entrusted with confidential business information cannot misappropriate that information for personal financial gain,” said Director of Enforcement David I. Miller. “As this and other enforcement actions show, the Division is a cop on the beat in policing the illegal use of inside information in the prediction markets and other markets within the CFTC’s jurisdiction. We will continue to take action to protect markets from insider trading and other forms of fraud, abuse, and manipulation.” Case Background According to the complaint, during the Relevant Period, Spagnuolo was a software engineer at Google. As a result of his employment, Spagnuolo acquired sensitive nonpublic information concerning the results of Google’s official Year in Search list for 2025. As a Google employee, Spagnuolo owed a duty of trust and confidence to Google to maintain the confidentiality of that information and not use it for personal gain. In violation of those duties, from at least October 2025 through at least December 2025, Spagnuolo purchased “Yes” or “No” shares on at least twenty-three of the 2025 Year in Search List contracts on Polymarket.com, including “#1 Searched Person on Google this year” and “Top 5 Most Searched People on Google 2025,” with near-perfect accuracy. The complaint alleges that Spagnuolo, who used the Polymarket handle “AlphaRaccoon,” generated approximately $1.2 million in profits through his trading. Parallel Criminal Action On May 27, 2026, the U.S. Attorney’s Office for the Southern District of New York announced the unsealing of a criminal complaint against Spagnuolo in the same court alleging conduct similar to that alleged in the CFTC’s complaint.  The CFTC appreciates the assistance of the U.S. Attorney’s Office for the Southern District of New York. RELATED LINKS Complaint: Michele Spagnuolo

The Commodity Futures Trading Commission today announced it has joined Gemini Trust Company LLC in a motion for relief from judgment in CFTC v. Gemini Trust Company LLC, originally filed in the U.S. District Court for the Southern District of New York in June 2022 [See CFTC Press Release No. 8540-22]. The parties entered into a consent order in January 2025 [See CFTC Press Release No. 9031-25]. The CFTC conducted a comprehensive review of the history of the investigation, the evidence, the charging decision, the litigation tactics in the matter, and considered changes in federal digital asset policy resulting in the resolution of numerous digital asset investigations and cases across multiple government agencies. As a result, the CFTC concluded the complaint should not have been filed — and would not have been under current enforcement standards. In particular, the review found that: (1) the complaint was largely based on a whistleblower’s account known to be lacking in credibility; (2) instead of focusing on alleged fraudsters, the investigation pursued Gemini, who was a fraud victim, for purported false statements to the CFTC during a registration application process; (3) there were serious questions about the strength of the evidence against Gemini; (4) requested evidentiary support was withheld from a Commissioner while the CFTC voted on the complaint against Gemini; (5) the complaint put the CFTC’s internal deliberations at issue but then litigation counsel invoked the deliberative process privilege and interposed objections to prevent Gemini from obtaining evidence necessary to defend itself; and (6) personnel improperly influenced the CFTC’s regulatory authority to create settlement leverage.  These findings not only call into question the CFTC’s enforcement process in this instance but also demonstrate the necessity of the federal government’s revised enforcement approach and standards, including in the digital asset space.  Accordingly, the CFTC determined that continuing enforcement of the consent order’s prospective provisions serves neither the CFTC’s mission nor the public interest. The parties are now jointly moving the court to vacate the consent order as to the prospective provision because the consent order’s non-prospective provisions, such as its imposition of a civil monetary penalty, have already been satisfied, and applying the remaining provisions — including injunctive relief — prospectively would not be equitable. RELATED LINKS Motion for Relief Motion and Memorandum Exhibit A Exhibit B Exhibit C Exhibit D Exhibit E Exhibit F Exhibit G Exhibit H Exhibit I Exhibit J Exhibit K Exhibit L Exhibit M  

Please see attached an announcement regarding upcoming amendments to the NZC Clearing & Settlement Procedures and NZX Derivatives Market Procedures to effect de-listing on 29 June 2026 of the Exchange Traded Options listed on the NZX Equity Derivatives Market. Downloads Delisting of NZX Options on Equity Securities: Procedure Amendments

MarketAxess Holdings Inc. (Nasdaq: MKTX), the operator of a leading electronic trading platform for fixed-income securities, today announced that it will be participating in the following upcoming investor conferences: Chris Concannon, Chief Executive Officer, will participate in a fireside chat at the Piper Sandler Global Exchange & FinTech Conference at 11:00 a.m. ET on June 4, 2026. Chris Concannon and Ilene Fiszel Bieler, Chief Financial Officer, will participate in a fireside chat at the Morgan Stanley US Financials Conference at 2:30 p.m. ET on June 9, 2026. The live webcasts and replays for both fireside chats will be available on the events and presentations section of the MarketAxess Investor Relations homepage, https://investor.marketaxess.com/events-and-presentations.

Thank you, Neale, for that kind introduction. Being back on Stanford's campus is always an honor and conjures up great memories. I spent several formative years here—first as a student in the AEA Summer Program, which prepares students to pursue graduate study in economics, and then as a National Fellow at the Hoover Institution. To say that these stints at Stanford were transformative would be an understatement. The summer program prepared me for and set me on a new intellectual and career journey, and my three years here as a postdoc set out an entirely new line of research inquiry. In fact, I started my research on patents and innovation or the economics of innovation here and benefitted greatly from my interaction with economists here at the Stanford Institute for Economic Policy Research (SIEPR), the economics department, the business school, the law school, and Hoover, including Kenneth Arrow, Tim Bresnahan, Jeremy Bulow, Milton Friedman, Avner Grief, Mitch Polinsky, Paul Romer, and Gavin Wright. From my decade spent in the Bay Area—here and at Berkeley, I witnessed how seriously new ideas are taken, examined, implemented, and spread. It is always invigorating to return to such a center of innovation.1 I applaud SIEPR for holding this event to discuss artificial intelligence (AI) and its power to influence the trajectory of the economy and transform the financial system. I know many in this room are grappling with how to harness this technology's obvious multidimensional promise while being mindful of important risks. Having adopted machine learning in the AEA Summer Program in 2018 when I was director and having used it in my research before coming to the Fed, I arrived at the Board of Governors in 2022 raising questions about and urging the study and adoption of AI. So, rest assured, policymakers at the Federal Reserve are also deeply engaged. Today, I will start by offering my latest economic outlook, with a focus on implications of AI for both sides of our dual mandate of maximum employment and price stability. Then, consistent with my long-standing support for responsible innovation, I will address the benefits AI could deliver for the financial system before addressing some of the risks and vulnerabilities the technology presents to financial stability. I will conclude by sharing how the Fed itself is embracing the power of AI to help ensure the financial system remains sound and resilient. Economic OutlookTo set the stage, I will begin with my economic outlook. Allow me to begin with inflation. Inflation is clearly moving in the wrong direction. Based on the latest data, it is estimated that the personal consumption expenditures (PCE) price index rose 3.8 percent over the 12 months ending in April. That reading is well above our 2 percent target. The recent rise in gasoline prices due to the conflict in Iran was the primary driver. But even when one excludes the volatile food and energy components, core PCE inflation is estimated to have risen by 3.3 percent over the 12 months ending in April—its highest reading since 2023. Inflation has been pushed up by shocks that should, in theory, be temporary and short lived. Tariffs should result in only a one-time shift upwards in the price level, and the effects of tariffs on inflation should begin to abate soon. The path of energy prices is tied to the ongoing conflict, the results of which are highly uncertain. Still, most forecasters and market participants, as reflected in oil futures, expect that oil and gasoline prices should decline, to some extent, by the end of the year. Nonetheless, even temporary and short-lived shocks could influence inflation over the medium term. Firms may embed these shocks into their pricing decisions, and workers may incorporate them into wage negotiations. Moreover, yet another shock to prices could be layered on from the heightened investment demand due to AI. To date, companies have announced more than $1.5 trillion in data-center plans, only a small portion of which have been realized.2 Those figures suggest that substantial AI-related investment remains in the pipeline from data centers alone. Effects of this demand on prices are apparent. Prices have risen significantly for chips, other high-tech equipment, and software. Wages in specialty trades in construction have picked up notably. Electricity and water prices have each increased by about 5 percent over the past year. Further, in the coming years, firms may expand along the intensive margin, but they may also expand along the extensive margin and undertake new AI-related capital expenditure, such as in robotics. In contrast to inflation, the labor market appears to be largely stable. The unemployment rate, 4.3 percent in April, has remained unchanged, on net, since last summer. The rate is in line with estimates of the natural rate of unemployment, suggesting that the supply and demand of labor are roughly balanced. Despite some high-profile announcements of layoffs, initial claims for unemployment insurance remain low and stable. However, I view the downside risks to the labor market as being elevated. One factor is heightened uncertainty about output due to the Middle East conflict. A softening in demand could lead to a softening in the labor market. Uncertainty may also weigh on firms' hiring plans, which may be one reason for the current low-hire environment. Furthermore, I have been and will continue to be highly attentive to AI developments and how they will affect the labor market. We could be approaching the most significant reorganization of work in generations. Even if, in the long run, new jobs are created, I am aware that the timing of costs and benefits of AI may differ. Specifically, AI-related job loss could precede job gains. Although we do not have conclusive evidence of this occurring yet, it may still be on the horizon, and increased churn in the labor market could be anticipated. Businesses are adopting AI at an increasing rate, but many have not yet used it to change the way they organize work. Indeed, the vast majority of small business respondents in the Federal Reserve's 2025 Small Business Credit Survey say that their labor costs have not changed as a result of AI.3 Yet, many businesses I hear from expect that AI will lead them to fundamentally change their business practices in the future. Finally, I will turn to economic growth. Here, I am optimistic. Over the past year, gross domestic product (GDP) growth has remained robust. Labor productivity growth has exceeded its pre-pandemic average. I do not need to report this in the middle of Silicon Valley, but business creation has remained high. Having done research on innovation and its macroeconomic effects for the 20 years before I came to the Fed, I believe AI is a technology like none other I have seen in my lifetime. But as a student of Paul Romer and endogenous growth more generally, I have been waiting for this moment when the post-WWII investment in the knowledge economy would increase the arrival rate of ideas. As firms incorporate AI more systematically into their production processes, I expect that AI will further boost productivity growth, contributing to my expectation that GDP will grow robustly in the near to medium term. What does this mean for monetary policy? I see elevated risks to both sides of our mandate, and from a risk-management perspective, I currently believe that the right course of action is to hold rates steady. However, I want to be clear about my risk assessment: The risks remain tilted toward higher inflation.4 In my baseline forecast, disinflation should resume in upcoming months without having to raise rates. Similarly, I expect the labor market will remain stable without having to lower rates. After five years of above-target inflation, I am particularly attuned to the risk that elevated inflation will become embedded in price- and wage-setting behavior. As such, I am prepared to raise rates, if the expected disinflation does not appear in a timely manner. Likewise, I will continue to monitor labor-market developments, as well, and would be prepared to adjust my policy stance downward should the labor market deteriorate. Responsibly Supporting InnovationI will now turn to the theme of this conference: AI's effect on innovation, resilience, and risk in the financial system. I am excited to discuss this topic for at least two reasons. First, as an economist who began studying the economics of innovation in earnest on this campus some time ago, I see great benefit that could come to the financial system from AI. Second, I serve as the chair of the Federal Reserve Board's Committee on Financial Stability. As a policymaker, figuring out how to encourage innovation, while ensuring the risks are contained and the system remains resilient, is a major preoccupation. Overall, I would like to stress that I believe in experimentation. This approach thrives in Silicon Valley, and we are embracing it at the Fed, as well. That is why I cofounded the EmergingTech Economic Research Network, the System-wide effort to share AI research and results of AI experiments, and also why I have been encouraged to see staff at the Fed looking for ways to adopt AI technology in new and imaginative ways over the past several years.5 Not every effort will be a success, and, as I learned from my training here and at Berkeley, that is okay. We are seeing results from this experimentation-driven mindset, which I will talk about shortly after I discuss the broader benefits of AI-driven innovation in the financial system. Benefits to Financial System of AII am optimistic about AI's promise to boost productivity and increase the arrival rate of ideas, which will support growth, lead to the creation of new firms that will produce new jobs, and put downward pressure on inflation. Within the financial sector, specifically, I am excited about the benefits from AI we are starting to see. The financial sector is adapting to the current generation of AI tools and increasing its adoption, initially in highly manual or resource-intensive areas. This transition includes in compliance functions, call centers, and back-office operations. Generating novel analytics has also become faster and more flexible. Using AI as a coding tool is helping the financial sector tackle age-old problems, such as updating legacy code and integrating systems. Next-generation models should more broadly adopt and integrate into client- and market-facing applications. Large technology and financial services firms, those who provide the hardware, software, and systems that underlie much of the global economy, use advanced AI tools to scan for potential cyber vulnerabilities that could be exploited. Further, AI adoption offers many opportunities for our financial system to be improved. These tools could allow firms to improve access to credit, allocate capital more efficiently, and speed processes. For example, AI could enable firms to accomplish the following: Develop new and better products that are more customized to individuals, broadening access to sophisticated financial products. Provide retail investors with the tools necessary to identify trends and emerging risks earlier. And leverage the benefits of efficiency gains to allocate more capital to lending and investments, which could lead to more economic activity and growth, as I mentioned earlier. Risks and Vulnerabilities Related to AIBroadly, I see AI as stimulating economic growth, which all else equal, should support financial stability. However, as a policymaker, I understand that innovation can lead to increased risk, if not monitored appropriately. I think about this likelihood both through the lens of AI's interactions with long-standing vulnerabilities and of the risk a hypothetical AI shock would present to the system. AI might introduce vulnerabilities to the financial system through a number of channels. One of the most commonly cited is the increased prevalence of AI-driven algorithmic trading. Traditional algorithms are fast, simple rules operating at nanosecond frequencies, but they are relatively rigid and hard coded. Generative AI and machine learning add self-learning based on historical experience, adaptation based on current market conditions, and analysis of unstructured data, such as text. Policymakers and academics have noted that, increasingly, AI-driven algorithmic trading may generate financial-stability risks, such as more correlated trading, endogenous model collusion, potential market manipulation, and greater market concentration. Another potential risk comes from the probability that AI may displace or disrupt entire sectors. For example, concerns about AI disruption risk have affected speculative-grade bonds in the technology sector, where spreads have increased, as our Financial Stability Report noted earlier this month.6 These trends reflect AI disruption concerns in the software industry and arose after a large AI firm introduced products aimed at that sector. Concerns about credit exposure to software also contributed to the wave of redemptions that have put significant pressure on both traded and nontraded perpetual business development companies in recent months.7 Another emerging trend that may have implications for financial stability relates to the fact that firms are increasingly tapping debt markets to finance the capital investments relating to AI infrastructure. Many of the hyperscaler firms have executed large investment-grade bond deals in recent months to fund AI capital expenditures.8 In addition, smaller data-center developers are raising debt from private debt funds, as well as asset-backed credit markets, to fund their investments.9 While many of the largest investors are also strong borrowers, the increasing use of leverage to finance investments in an emerging technology carries risk, and a sustained boom in debt issuance could eventually represent a financial-stability concern. I will note that even under very ambitious investment and debt-issuance projections, we would be unlikely to return to peak leverage levels observed before the Global Financial Crisis. Cyber RiskAnd, of course, we cannot talk about risk without discussing cyber risk. Recent advances in the ability of large language models (LLMs) and agentic AI systems to detect, exploit, and create new vulnerabilities have introduced new challenges in safeguarding system security for financial institutions, infrastructure, and third-party service providers. Very powerful AI tools, such as Anthropic's Mythos Preview model, have demonstrated the ability to detect previously undetectable vulnerabilities in software applications that support important and widely used computer systems. Non-malicious cyber events, such as software malfunctions, have also caused disruptions to the provision of financial services. AI can make developing software—particularly writing code—faster and easier. However, by contributing to the rapid proliferation of code, the aggressive use of AI may indirectly strain current security review processes. The ultimate implications of AI for cybersecurity remain unclear. Advanced AI coding agents can be used to enhance the security of many important computer systems to prevent future AI-related cyberattacks.10 It remains possible that AI makes financial institutions more resilient regarding cyberattack vulnerabilities. AI at the FedJust like financial firms and other entities across the economy, the Fed is also working to responsibly deploy AI to advance our mission and to improve our own work. To be clear, as I said at the NBER Summer Institute last year, the Federal Open Market Committee is not using AI in developing or setting policy11. But many parts of the Fed system are using AI for a variety of other tasks, particularly in the area of financial stability, and we already see tangible benefits. By using AI ourselves, we can improve our analysis of the financial sector and are better able to highlight vulnerabilities—whether they are new ones introduced by AI or old ones that we may have missed. The use of AI can make us better at our job with enhanced monitoring and improved analysis. I would like to share two specific ways that we are using AI to advance our critical mission of monitoring financial stability. First, newly formed teams of experts within the Division of Financial Stability are analyzing technological risks to financial stability. These collaborative groups assess how cyber, AI, and quantum computing create both vulnerabilities and opportunities. For example, economists Anne Lundgaard Hansen at the Richmond Fed and Seung Jung Lee at the Board have investigated the effect of generative AI adoption on financial stability through laboratory-style experiments using LLMs.12 Their research on herd behavior in investment decisions in a stylized lab setting found that AI agents make more rational decisions than humans. The research suggests that agents are more likely to make decisions based on data and analysis, rather than simply following general market trends. This outcome could potentially lead to fewer asset price bubbles arising from animal spirits. These innovative teams have also developed practical tools for our mission. One team designed a method to construct a small, cost-efficient AI model that can classify a large amount of text just as accurately as a larger model, using a technique called "active knowledge distillation." The method achieves up to an 80 percent reduction in computation costs while maintaining accuracy.13 This efficiency matters, because financial-stability analysis increasingly requires processing vast amounts of unstructured text data, including regulatory filings, earnings calls, and news articles. Another interesting project applied natural language processing to decades of Beige Book data, finding that even when controlling for traditional metrics, the sentiment in these anecdotal compilations provides meaningful explanatory power in forecasting recessions.14 Second, the staff from the Board and all 12 Reserve Banks recently participated in an agentic AI sprint. This event encouraged experimentation and explored what agentic AI could do for financial-stability analysis. It was great to see all the AI systems that could reason through problems, decide which analytical approaches to use, and complete complex tasks with minimal human intervention. A valuable insight we found in one of the projects was that agentic AI systems can be more systematic in identifying network-based risks than our standard approaches. This outcome was not because we do not understand their theoretical importance, but because, in many cases, we lack the capacity to comprehensively analyze complex empirical structural patterns of networks at scale. This type of systematic capability translates into potentially meaningful efficiency gains for financial-stability work. For example, other prototypes demonstrated that they could select, run, and analyze many financial-stability–relevant scenarios that would be prohibitively time-consuming using traditional methods. This development enables the kind of thorough analysis that humans would struggle to complete in a reasonable time frame. However—and this is critical—systematic coverage without accuracy would be worse than a selective approach. The most promising approaches build verification into the system architecture itself. These approaches have multiple agents confer before reaching a consensus and include mechanisms that force the agents to consider contrarian perspectives. This process, in turn, can be crosschecked by researchers. If that sounds familiar at a place like Stanford, it should. What I just described for AI agents are the same types of methods that have yielded breakthrough thinking from humans for centuries. ConclusionThe totality of our experience with AI leads us to the conclusion that, alongside experimentation, strong governance and risk management must be our foundation. The most promising approaches augment human judgment with AI capabilities while building verification into the architecture itself. The urgency is real. AI is advancing rapidly, and financial institutions are adopting these technologies apace. As policymakers, we must understand these systems through hands-on experience. By building our own AI capabilities, we gain invaluable insights into both the promise and risks these technologies bring to the financial system. With appropriate governance frameworks, autonomous intelligence can potentially expand our analytical capabilities. These tools could enhance our capacity to identify and respond to evolving threats. But we proceed with both optimism and caution, as warranted at this moment of a technological inflection point. Thank you again for the opportunity to return to Stanford and to speak at this timely and important event. I look forward to our discussion. 1. The views expressed here are my own and are not necessarily those of my colleagues on the Federal Reserve Board or the Federal Open Market Committee.  2. See Eirik Eylands Brandsaas, Daniel Garcia, Robert Kurtzman, Joseph Nichols, and Adelia Zytek (2025), "Estimating Aggregate Data Center Investment with Project-Level Data," Finance and Economics Discussion Series 2025-109 (Washington: Board of Governors of the Federal Reserve System, December). For updated data and publicly available results, see Eirik Brandsaas (2026), "Estimating Aggregate Data Center Investment with Project-Level Data," DataCenterPublic, GitHub repository, https://github.com/eirikbrandsaas/DataCenterPublic.  3. See Federal Reserve Banks (2026), "2026 Main Street Metrics: Trends over Time from the Small Business Credit Survey," March 23.  4. See Lisa D. Cook (2026), "Economic Outlook," speech delivered at the Economic Club of Miami, Miami, Florida, February 4.  5. Further information regarding the EmergingTech Economic Research Network is available on the Federal Reserve Bank of San Francisco's website at https://www.frbsf.org/research-and-insights/emerging-tech-economic-research-network.  6. See Board of Governors of the Federal Reserve System (2026), Financial Stability Report (PDF) (Washington: Board of Governors, May).  7. See Paula Seligson, Olivia Fishlow, Rene Ismail, Davide Scigliuzzo, and Laura Benitez (2026), "Private Credit's Gate-Crashers Are Forcing Funds into a Brutal Spot," Bloomberg, March 8.  8. See Anhata Rooprai, Zaheer Kachwala, and Johann M. Cherian (2025), "Tech Companies Tap Debt Markets to Fund AI and Cloud Expansion," Reuters, November 24 (updated May 11, 2026), https://www.reuters.com/business/media-telecom/tech-companies-tap-debt-markets-fund-ai-cloud-expansion-2026-05-11.  9. See Paula Seligson (2026), "The $3 Trillion AI Data Center Build-Out Spurs a Debt Market Boom," Bloomberg, February 2.  10. See Saeed Azhar, Tatiana Bautzer, Michelle Price, and Francesco Canepa (2026), "Anthropic's Mythos Sends U.S. Banks Rushing to Plug Cyber Holes," Reuters, May 12, https://www.reuters.com/business/finance/anthropics-mythos-sends-us-banks-rushing-plug-cyber-holes-2026-05-12.  11. See Lisa D. Cook (2025), "AI: A Fed Policymaker's View," speech delivered at the National Bureau of Economic Research, Summer Institute 2025: Digital Economics and Artificial Intelligence, Cambridge, Mass., July 17.  12. See Anne Lundgaard Hansen and Seung Jung Lee (2025), "Financial Stability Implications of Generative AI: Taming the Animal Spirits," Finance and Economics Discussion Series 2025-090 (Washington: Board of Governors of the Federal Reserve System, September).  13. See Viviana Luccioli, Rithika Iyengar, Ryan Panley, Flora Haberkorn, Xiaoyu Ge, Leland Crane, Nitish Sinha, and Seung Jung Lee (2025), "LLM on a Budget: Active Knowledge Distillation for Efficient Classification of Large Text Corpora," Finance and Economics Discussion Series 2025-108 (Washington: Board of Governors of the Federal Reserve System, December).  14. See Shengwu Du, Flora Haberkorn, Isabel Kitschelt, Seung Jung Lee, Anderson Monken, Dylan Saez, Kelsey Shipman, and Sandeep Thakur (2026), "Do Anecdotes Matter? Exploring the Beige Book through Textual Analysis from 1970 to 2025," Finance and Economics Discussion Series 2026-004 (Washington: Board of Governors of the Federal Reserve System, January). 

At the end of the settlement date of May 15, 2026, short interest in 3,727 Nasdaq Global MarketSM securities totaled 17,000,786,423 shares compared with 16,707,836,595 shares in 3,714 Global Market issues reported for the prior settlement date of April 30, 2026. The mid-May short interest represents 2.74 days compared with 2.84 days for the prior reporting period. Short interest in 1,640 securities on The Nasdaq Capital MarketSM totaled 3,909,823,972 shares at the end of the settlement date of May 15, 2026, compared with 3,896,400,254 shares in 1,644 securities for the previous reporting period. This represents a 1.28 day average daily volume; the previous reporting period’s figure was 1.15. In summary, short interest in all 5,367 Nasdaq® securities totaled 20,910,610,395 shares at the May 15, 2026 settlement date, compared with 5,358 issues and 20,604,236,849 shares at the end of the previous reporting period. This is 2.25 days average daily volume, compared with an average of 2.22 days for the prior reporting period. The open short interest positions reported for each Nasdaq security reflect the total number of shares sold short by all broker/dealers regardless of their exchange affiliations. A short sale is generally understood to mean the sale of a security that the seller does not own or any sale that is consummated by the delivery of a security borrowed by or for the account of the seller. For more information on Nasdaq Short interest positions, including publication dates, visit https://www.nasdaq.com/market-activity/quotes/short-interest or http://www.nasdaqtrader.com/asp/short_interest.asp. About Nasdaq:Nasdaq (Nasdaq: NDAQ) is a leading global technology company serving corporate clients, investment managers, banks, brokers, and exchange operators as they navigate and interact with the global capital markets and the broader financial system. We aspire to deliver world-leading platforms that improve the liquidity, transparency, and integrity of the global economy. Our diverse offering of data, analytics, software, exchange capabilities, and client-centric services enables clients to optimize and execute their business vision with confidence. To learn more about the company, technology solutions, and career opportunities, visit us on LinkedIn, on X @Nasdaq, or at www.nasdaq.com.      A photo accompanying this announcement is available at https://www.globenewswire.com/NewsRoom/AttachmentNg/51b94df8-fad2-4988-b76c-0883b4bfb7eb

NYSE today reported short interest as of the close of business on the settlement date of May 15, 2026. SETTLEMENT DATE EXCHANGE TOTAL CURRENT SHORT INTEREST TOTAL PREVIOUS SHORT INTEREST (Revised) NUMBER of SECURITIES with a SHORT POSITION NUMBER of SECURITIES with a POSITION >= 5,000 SHARES 05/15/2026 NYSE 18,301,453,546 17,624,442,907 2,882 2,602 05/15/2026 NYSE ARCA 2,302,820,999 2,240,615,089 2,607 1,814 05/15/2026 NYSE AMERICAN 949,802,659 934,780,117 311 265 05/15/2026 NYSE GROUP 21,554,077,204 20,799,838,113 5,800 4,681 *NYSE Group includes NYSE, NYSE American and NYSE Arca           Reports will be archived here.