MAS 演講稿 · 2026-09-11
「構建未來的金融體系：可信、互聯、有韌性」——新加坡金融管理局管理總監 Chia Der Jiun 先生在 Global FinTech Fest 2026 上的特別演講，2026年9月11日
要點
- • MAS推出Pathfin.ai，這是一個在金融業共享和配對經過驗證AI解決方案的平臺，擁有超過300個參與者，幫助較小規模的金融機構降低採用成本。
- • MAS於2025年與行業聯合釋出了兩本《AI風險管理手冊》，併發布了《AI風險管理指南》，為銀行、保險和資本市場行業設定了監管期望的治理和控制要求。
- • MAS釋出了《SAFR》白皮書，於2026年7月釋出，闡述了為AI代理實現執行時防護措施的框架，包括確定代理的身份和許可權、在執行前評估行動以及維護審計記錄。
- • 新加坡和印度於2023年啟動UPI-PayNow連線，以實現更便宜、更快速的跨境零售支付和匯款，自啟動以來交易量每年翻倍增長。
- • 新加坡和印度是Nexus的創始成員，這是一個多邊快速支付互連倡議，使每個支付系統能連線到共同框架併到達多個管轄地，而無需建立單獨的雙邊連線。
- • MAS與執法機構和銀行業合作，測試利用跨銀行和公私資料的AI模型來近即時檢測可疑賬戶和交易，預計在2026年底前釋出初步發現。
完整譯文（繁體中文）
MAS 英文原文譯文 · 翻譯日期: 2026-09-28
新加坡政府機構網站 如何識別 官方網站連結以.gov.sg結尾 政府機構通過.gov.sg網站進行溝通（例如go.gov.sg/open）。受信任的網站 受信任的網站 安全網站使用HTTPS 查詢鎖定圖示( )或https://作為額外防護措施。僅在官方、安全網站上分享敏感資訊。電子服務 MAS-Tx 目錄 我們是誰 聯絡我們 顯示選單 監管 返回 監管 訪問法規、更新和許可證資訊
存款類機構的法規、指導和許可
資本市場實體的法規、指導和許可
保險公司的法規、指導和許可
支付服務提供商和系統的法規、指導和許可
關於新加坡金融管理局在這些關鍵領域的方法、戰略和努力的資訊
新加坡金融管理局的監管方法以及其管理的法案下的工具
瞭解新加坡金融管理局發展和支援金融部門的戰略
發現是什麼使新加坡成為全球領先的金融中心
瞭解新加坡金融管理局如何共同建立智慧金融中心
獲取概念驗證、招聘、業務發展等資金
沙箱放鬆監管要求，以啟用創新的即時實驗
各種支付倡議，包括SGQR、FAST和PayNow
瞭解綠色金融中技術解決方案和專案的各種倡議。
通過數字資產解鎖金融服務未來的新可能性
世界上最大的金融科技社群節日，供連線、協作和共同建立
世界上首個使用國家數字身份和線上同意系統來保護金融資料安全的
瞭解新加坡如何成為綠色和可持續金融的領先中心
瞭解新加坡金融管理局為發展您的業務領域而制定的機會和計劃
閱讀關於為您的業務運營提供的支援的資訊
瞭解新加坡金融管理局及其合作伙伴如何建立金融專業人士和領導者的管道
閱讀關於新加坡金融管理局的貨幣政策框架、中央銀行運作和相關資訊
獲取有關SSB、新加坡政府債券、國庫券、新加坡金融管理局債券和新加坡金融管理局浮動利率票據的資訊
詳細瞭解新加坡的貨幣
訪問各種諮詢、專著、宏觀經濟評論和其他出版物
檢視新加坡金融部門、外匯儲備統計、匯率等資料
獲取最新的新聞、演講、更新和公告
瞭解在新加坡金融管理局工作和可用的各種機會
1 大家早上好。能夠參加全球金融科技節，這是世界上最大的金融科技活動之一，我倍感榮幸。人工智慧的拐點 2 讓我首先指出，在未來10年裡，我們都處於偉大技術變革的邊緣。三項技術脫穎而出。3 人工智慧的轉變已經到來。代幣化可能需要更長的時間來規模化，可能還需要幾年。量子計算的時間更遠一些。專家估計需要5-10年。但現在開始為量子彈性做準備還為時不晚。4 這三項技術都有深遠的影響，但讓我專注於人工智慧。這項技術發展最快，採用也在最快速地傳播。5 模型效能顯然在快速進步。眾所周知，人工智慧模型在許多特定任務中已經達到專家或專業水平，例如編碼、研究生級別的科學和數學，以及一般知識工作。6 仍然與人類表現存在差距的領域是那些需要複雜解釋、戰略判斷和決定，以及人類互動技能的領域。7 企業採用人工智慧正在快速進展。雖然很大比例的公司報告使用人工智慧，但報告取得顯著生產力收益的比例要小得多。8 報告生產力收益的公司比例可能會隨著員工和組織通過培訓以及流程和產品重新設計，更好地使用人工智慧而增加。9 隨著時間推移，我們可以期待人工智慧成為組織的基礎能力。那些能夠良好、安全地使用它的組織將創新更快、更好地服務客戶、並開啟新的機會。10 監管機構的挑戰是支援創新以獲得競爭力和增長；同時也要將其引導到安全和可持續的道路上。11 創新必須建立在信任和穩定的基礎之上，才能規模化。我們在新加坡金融部門所看到的 12 在新加坡的金融部門，我們看到廣泛的人工智慧採用。常見的使用案例包括欺詐檢測、信用承保、風險管理、監管合規、營銷、客戶服務和文件處理。這些用例已經超越試點階段，正在大規模部署。13 最大的、管理良好的金融機構不需要任何激勵。它們正在快速採用。我們對它們的關注是良好的治理——圍繞安全、護欄和問責制。14 人工智慧不應該只是被最大的金融機構掌握的競爭工具。如果我們要維持一個有競爭力的穩定金融系統來支援公眾和經濟，我們應該避免贏家通吃的動態。15 我們希望人工智慧的益處遍及整個行業。我們的目標應該是實現整個部門的可持續生產力提升。Pathfin.ai 16 為此，新加坡金融管理局啟動了Pathfin.ai。這是一個平臺和計劃，用於在整個行業中共享和匹配經過驗證的人工智慧解決方案。17 較小的金融機構可以降低查詢和部署有效人工智慧解決方案的成本和努力。如果一個解決方案已經被驗證且有效，我們希望讓其他機構更容易地找到並實施它。18 我們現在有超過300個參與者和越來越多的成功配對。作為一個整體系統解決問題 19 人工智慧也讓我們有機會在系統層面解決問題——這些問題是單個金融機構無法單獨解決的。20 檢測和破壞詐騙和欺詐就是一個例子。新加坡金融管理局與執法機構和銀行業合作。我們正在測試不同的人工智慧模型，利用跨銀行和公私資料，以改進對可疑賬戶和交易的近即時檢測。21 目標是更快地檢測、更快地干預和減少損失。我們預期到今年年底能獲得這項工作的成果。共同開發合理的實踐 22 為了在金融行業推廣合理的人工智慧治理和風險管理，我們發現新加坡金融管理局與行業合作非常有用。23 第一步是在2023年採取的。新加坡金融管理局和行業共同釋出了一份生成式人工智慧風險框架，以建立共同理解和基準。24 第二步在2025年採取。我們與行業共同釋出了兩本人工智慧風險管理手冊，以推廣良好實踐。這些推薦實踐適用於銀行、保險和資本市場部門。25 新加坡金融管理局還發布了一套人工智慧風險管理指南供公眾諮詢。這些指南規定了治理和風險管理的監管期望，以及人工智慧生命週期控制和能力。26 這些指南將與風險管理手冊相輔相成。前者將說明「是什麼」。後者將說明「如何做」。例如，指南要求金融機構進行風險重要性評估，而手冊提供瞭如何實施這些評估的示例。27 隨著技術快速發展，更新良好的人工智慧風險治理實踐將很重要。28 與行業的最新聯合舉措是SAFR——執行時代理金融的保障措施。隨著人工智慧代理承擔更多重要任務並獲得更多自主權，確保明確的問責制、監督和治理至關重要。29 SAFR在今年7月作為白皮書釋出。它規定了實施執行時保障措施的框架，例如建立代理的身份和許可權、在執行前根據控制措施評估代理行動，以及維持清晰的審計記錄。30 我們在人工智慧風險管理和治理領域的所有工作都是公開發表的。我們將其視為全球公共財富。印度也在這個領域進行重要工作。印度儲備銀行釋出了《人工智慧的負責任和道德啟用框架》，即FREE-AI。31 它規定了負責任人工智慧採用的原則和建議，將問責制、公平性、復原力和信任置於中心。這是對全球金融系統中人工智慧安全和負責任採用的重要貢獻。網路安全 32 讓我說幾句關於人工智慧時代的網路安全問題。這是一個分水嶺年份。33 首先是Mythos時刻——人工智慧能夠以速度和規模進行漏洞發現和利用。34 其次是OpenAI代理攻擊時刻——人工智慧代理自主工作並協力逃脫其控制並發動成功的網路攻擊。35 因此，隨著更強大的人工智慧模型，我們看到漏洞發現和網路攻擊的顯著增加也就不足為奇了。36 高嚴重程度的常見漏洞和暴露(CVE)在這一年增加了6倍，達到2200次，相比之下前3年的平均數。CrowdStrike報告稱人工智慧驅動的網路攻擊增加了89%。我們也知道，人工智慧正在通過深度偽造和其他手段實現更具說服力的欺騙。37 好訊息是，雖然漏洞發現和攻擊增加了，但報告的成功突破並未在同樣程度上激增。38 一個原因是針對有害使用的模型護欄。另一個是良好實施的多層網路防禦仍然有效。39 這些層包括強身份驗證、快速補丁、網路分段、模組化架構、訪問控制、端點檢測、資料庫監控、事件響應。這為我們爭取了時間。40 但我們必須預期模型會變得更強大，而決心堅定的各方會破壞護欄。41 我們必須利用這個時間加強多層網路防禦的合理實施，並引導我們的金融機構更廣泛地利用人工智慧進行網路防禦。42 人工智慧可用於首先發現和修復漏洞、執行連續程式碼掃描、加快測試和補丁速度、增強即時威脅檢測以及改進事件響應。43 在人工智慧治理和網路彈性的這些領域，當我們的金融系統面臨這些共同挑戰時，新加坡和印度的監管機構和行業有相當大的空間相互學習。前方是什麼 44 我們可以期待在未來幾年裡從技術和人工智慧中獲得什麼？技術的軌跡是從系統中移除摩擦——交易摩擦和決策摩擦。45 想象人工智慧被部署來最佳化現金流、現金管理、支付和投資。決定近乎瞬間做出，代理被部署執行。我們可以預期貨幣會以更小的激勵措施更快速地流動。46 管理資金業務的競爭將加劇。47 對金融行業的在位者和挑戰者都會有巨大影響。中央銀行和監管機構也必須開始考慮監管和金融穩定影響。48 這些是嚴肅的問題，全球金融科技節等平臺可以通過對話和交流做出真正的貢獻。新加坡-印度夥伴關係 49 讓我轉向新加坡和印度之間的金融夥伴關係。我們已經建立了強大和持久的夥伴關係支柱。50 2018年，印度政府經濟事務部與新加坡金融管理局簽署了一份諒解備忘錄，以加強金融創新合作。2022年，與國際金融服務中心管理局(IFSCA)簽署了一份諒解備忘錄，以加強監管合作。2025年，與印度儲備銀行簽署了一份關於數字資產合作的諒解備忘錄。51 2023年，我們的總理啟動了UPI-PayNow連線。這使得更便宜、更快速和安全的跨境零售支付和匯款成為可能。這是印度首個跨境即時支付系統連線，也是新加坡的第二個。交易量自推出以來每年都增加了一倍多。我們預期今年的交易量增長會更快。52 下一步是Nexus，多邊快速支付互連倡議。新加坡和印度都是Nexus的創始成員。而不是每個國家都建立單獨的雙邊連線，每個支付系統連線一次到共同框架併到達多個司法管轄區。53 PayNow-UPI展示了雙邊可以實現什麼。Nexus為我們提供了將這一理念擴充套件到多邊規模的機會。54 印度的UPI是全球數字支付創新和領導力的明確示範。它為許多國家尋求民主化獲取快速和廉價支付服務而充當了北極星。55 新加坡金融管理局今年早些時候釋出了一個路線圖，以指導我們數字支付基礎設施的進一步發展。印度的UPI是新加坡金融管理局的重要參考之一。56 在金融科技夥伴關係領域，這是關於將公司聚在一起——來自印度和新加坡的金融科技和金融機構尋找合作和夥伴關係的機會。57 讓我舉個例子。58 Pints AI，一家新加坡人工智慧金融科技公司和2023年新加坡-印度駭客馬拉松的贏家，與一家大型印度保險公司合作。他們利用人工智慧顯著提高了為保險公司承保人執行自動檢查和準備資訊的效率和速度。這是人工智慧資訊準備能力與人類專家判斷和決策的配對。59 兩個國家、兩家規模差異很大的公司、一個問題、一個切實的解決方案。這就是良好的金融科技夥伴關係的樣子。各方現在正在開發一份白皮書，將其轉變為其他金融機構的實際參考。60 我們希望看到更多這樣的情況。新加坡金融科技節(SFF)和全球金融科技節(GFF)是這些夥伴關係可以開始的地方。我們希望鼓勵來自我們兩個國家的創新金融科技和金融機構充分利用這兩個平臺。總結 61 讓我總結一下。62 我們正處於重大變革的邊緣。人工智慧是發展最快、採用最快的技術。63 金融機構的流程將被重新設計和改造。員工需要接受培訓，以便從人工智慧的使用中獲得最大的益處。64 當人工智慧被部署在更復雜的功能中並獲得更多自主權時，它必須伴隨強大的治理和控制。隨著人工智慧的進步，也將對網路安全和我們金融基礎設施的彈性產生重大影響。65 金錢的使用、交易和轉移方式也可能被改造。監管機構採取的方法必須跟上這些快速發展的步伐。66 創新和技術既帶來機遇，也帶來挑戰。印度和新加坡有許多共同點可以分享，並可以從彼此的方法中學習，以實現一個共同目標，即技術和創新帶來安全和可持續的益處。67 我祝願各位在全球金融科技節上有成果豐碩的連繫和新的靈感。
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中國，2026年9月18日…新加坡金融管理局(MAS)和中國人民銀行(PBC)於2026年9月17日在中國南寧召開了第四屆新加坡-中國綠色金融工作組(GFTF)年度會議。
新加坡金融管理局(MAS)和中國證券監督管理委員會於2026年6月29日在新加坡召開了第十屆年度監管圓桌會議。
在2026陸家嘴論壇上，新加坡金融管理局常務董事謝德俊先生分享了對經濟展望、在高度政策不確定的環境中增強韌性的必要性、擴大區域經濟和金融合作以及繼續支援國際金融機構的看法。
英文原文
MAS 官網原始記錄 · 抓取日期: 2026-09-28
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1 Good morning to all. It is a great pleasure to participate in the Global FinTech Festival, one of the largest FinTech events in the world. The AI Inflection Point 2 Let me start by noting that we are all standing on the cusp of great technological transformation over the next 10 years. Three technologies stand out. 3 The AI transformation is already upon us. Tokenisation may take a little more time to scale, perhaps another few years. Quantum computing is a little further out. Experts estimate 5-10 years. But it is not too early to prepare now for quantum resilience. 4 All three technologies have far reaching consequences but let me focus on AI. The technology is advancing the most rapidly, and adoption is spreading the fastest. 5 Model performance is clearly advancing rapidly. It is well known that AI models already perform at expert or specialist level in many defined tasks, such as in coding, graduate-level science and mathematics, and general knowledge work. 6 Where there are still gaps to human performance are in areas requiring complex interpretation, strategic judgement and decisions, and human interaction skills. 7 Corporate adoption of AI is progressing rapidly. While a high proportion of companies report using AI, a much smaller proportion report significant productivity gains. 8 The proportion of firms reporting productivity gains are likely to increase as employees and organisations become better users of AI through training and process and product redesign. 9 In time to come, we can expect AI to become a foundational capability for organisations. Those that use it well and safely will innovate faster, serve customers better, and unlock new opportunities. 10 The challenge for regulators is to support innovation for competitiveness and growth; and also steer it on a course that is safe and sustainable. 11 Innovation must be founded on trust and stability if it is to scale. What We Are Seeing in Singapore's Financial Sector 12 In Singapore's financial sector, we are seeing wide AI adoption. Common use cases include fraud detection, credit underwriting, risk management, regulatory compliance, marketing, customer service and document processing. These use cases have moved beyond pilots and are being deployed at scale. 13 The largest, well-managed financial institutions need no encouragement. They are in rapid adoption. Our focus with them is good governance — around safety, guardrails, and accountability. 14 AI should not only be a competitive tool wielded by the largest financial institutions. We should avoid a winner-takes-all dynamic if we are to maintain a competitive and stable financial system to support the public and the economy. 15 We want the benefits of AI to spread across the whole industry. Our aim should be for a sustainable productivity uplift for the entire sector. Pathfin.ai 16 To that end, MAS launched Pathfin.ai. This is a platform and programme to share and match validated AI solutions across the industry. 17 Smaller financial institutions can lower the cost and effort of finding and deploying effective AI solutions. If a solution has been validated and works, we want to make it easier for others to find and implement it. 18 We now have over 300 participants and a growing number of successful matches. Solving Problems as a Whole System 19 AI also gives us an opportunity to solve problems at the system level — problems no single financial institution can solve alone. 20 Detecting and disrupting scams and fraud is an example. MAS is working with the law enforcement agency, and the banking industry. We are testing different AI models, drawing on cross-bank and public-private data, to improve the detection of suspicious accounts and transactions in near-real time. 21 The aim is to detect sooner, intervene faster and reduce losses. We expect to have findings from this work by the end of this year. Developing Sound Practices Together 22 To propagate sound AI governance and risk management in the financial industry, we have found it very useful for MAS to collaborate with the industry. 23 The first step was taken in 2023. MAS and the industry collectively published a Gen AI risk framework to establish a common understanding and baseline. 24 The second step was taken in 2025. We published jointly with the industry two AI Risk Management Handbooks to promote good practices. These recommended practices were applicable across the banking, insurance, capital markets sectors. 25 MAS has also issued a set of Guidelines for AI Risk Management for public consultation. These guidelines set out supervisory expectations for governance and risk management, as well as AI life cycle controls and capabilities. 26 The Guidelines will work in tandem with the Risk Management Handbooks. The first will set out the what. The latter will set out the how. For example, the Guidelines require financial institutions to perform risk materiality assessments, while the Handbook provides examples of how such assessments can be implemented. 27 Updating good AI risk governance practices will be important as the technology progresses fast. 28 The latest joint initiative with industry is SAFR — Safeguards for Agentic Finance at Runtime. As AI agents take on more consequential tasks and are given more autonomy, it is essential to ensure clear accountability, oversight and governance. 29 SAFR was published as a white paper in July this year. It sets out a framework for implementing runtime safeguards such as establishing an agent's identity and authority, evaluating agent actions against controls before execution, and maintaining a clear audit record. 30 All our work in this space of AI risk management and governance is published. We see this as a global public good. India too is undertaking important work in this area. The Reserve Bank of India has published the Framework for Responsible and Ethical Enablement of Artificial Intelligence, or FREE-AI. 31 It sets out the principles and recommendations for responsible AI adoption, placing accountability, fairness, resilience and trust at the centre. This is an important contribution to safe and responsible adoption of AI in the global financial system. Cybersecurity 32 Let me say a few words about cybersecurity in an AI age. This has been a watershed year. 33 First was the Mythos moment — AI capable of vulnerability discovery and exploitation at speed and scale. 34 Second was the Open AI agent attack moment — AI agents working autonomously and in concert to escape its controls and launch successful cyber breaches. 35 It is therefore no surprise that with more capable AI models we have seen a significant increase in vulnerability discovery and also cyber attacks. 36 High severity Common Vulnerabilities and Exposures (CVEs) went up 6 times this year to 2200 compared to the average of the preceding 3 years. Crowdstrike reports an 89% increase in AI-enabled cyber attacks. We know also that AI is enabling more persuasive deception through deepfake and other means. 37 The good news is that while vulnerability discovery and attacks have gone up, reported successful breaches have not surged to the same extent. 38 One reason is model guardrails against harmful use. Another is that a well-implemented multi-layered cyber defence is still effective. 39 These layers include strong authentication, rapid patching, network segmentation, modular architecture, access control, endpoint detection, database monitoring, incidence response. This has bought us time. 40 But we have to expect models to get more capable, and determined parties to jailbreak guardrails. 41 We have to make use of this time to strengthen sound implementation of multi-layered cyber defences, and steer our financial institutions to make greater use of AI for cyber defence. 42 AI can be used to discover and fix vulnerabilities first, perform continuous code scanning, enable faster testing and patching, strengthen real-time threat detection, and enhance incident response. 43 In these areas of AI governance and cyber resilience, there is considerable scope for regulators and industry in Singapore and India to learn from one another as our financial systems face these common challenges. What Lies Ahead 44 What can we expect from technology and AI in the years ahead? The trajectory of technology is that it is taking frictions out of the system — transaction frictions and decision frictions. 45 Imagine AI being deployed to optimise cashflows, cash management, payments, investments. Decisions are made near instantaneously and agents are deployed to execute. We can expect money to move around more quickly for smaller incentives. 46 Competition for the business of managing money will be heightened. 47 There will be large implications for incumbents and challengers in the financial industry. There will also be regulatory and financial stability implications that central banks and regulators have to start considering. 48 These are serious questions where platforms like the GFF can make a real contribution through dialogue and exchanges. The Singapore-India Partnership 49 Let me turn to the financial partnership between Singapore and India. We have built strong and enduring pillars of partnership. 50 In 2018, the Department of Economic Affairs of the Government of India signed an MOU with MAS to strengthen financial innovation cooperation. In 2022, an MOU was signed with the International Financial Services Centres Authority (IFSCA) to enhance supervisory cooperation. In 2025, an MOU was signed with the Reserve Bank of India on digital asset cooperation. 51 In 2023, our Prime Ministers launched the UPI-PayNow linkage. This enabled cheaper, faster and safe cross-border retail payments and remittances. This was India's first cross-border real time payment systems linkage and Singapore's second. Transaction volumes have more than doubled each year since launch. We expect volumes this year to grow even faster. 52 The next step is Nexus, the multilateral fast-payment interconnection initiative. Singapore and India are both founding members of Nexus. Instead of every country building a separate bilateral connection, each payment system connects once to a common framework and reaches multiple jurisdictions. 53 PayNow-UPI showed what can be achieved bilaterally. Nexus gives us the opportunity to take that idea to multilateral scale. 54 India's UPI is a clear demonstration of innovation and leadership in digital payments globally. It has served as a north star for many countries seeking to democratise access to fast and cheap payments services. 55 MAS published earlier this year a roadmap to guide the further development of our digital payments infrastructure. India's UPI was among the important references for MAS. 56 In the area of FinTech partnership, it is about bringing companies together — FinTechs and financial institutions from India and Singapore finding opportunities for collaboration and partnership. 57 Let me give one example. 58 Pints AI, a Singapore AI FinTech and winner of the 2023 Singapore-India Hackathon, partnered with a large Indian insurer. They used AI to significantly raise the efficiency and speed for running automated checks and preparing information for the insurer's underwriters. A pairing of AI capabilities for preparing information with human expert judgement and decision-making. 59 Two countries, two firms of very different sizes, one problem, one practical solution. That is what good FinTech partnership looks like. The parties are now developing a white paper to turn this into a practical reference for other financial institutions. 60 We want to see more of this. The Singapore FinTech Festival (SFF) and GFF are where these partnerships can begin. We want to encourage innovative FinTechs and financial institutions from both our countries to use both these platforms well. Closing 61 Let me conclude. 62 We are on the cusp of significant transformation. AI is the technology advancing most quickly and adopted most rapidly. 63 Processes in financial institutions will be redesigned and transformed. Employees will need to be trained so as to get the most benefits out of AI use. 64 As AI is deployed in more complex functions and given more autonomy, it must be accompanied by strong governance and controls. As AI advances, there will also be significant implications for cyber security and the resilience of our financial infrastructure. 65 How money is used, transacted and moved could also be transformed. The approaches that regulators take have to keep pace with these rapid developments. 66 Innovation and technology brings both opportunities and challenges. India and Singapore have much common ground to share and learn from each other's approaches, towards a common objective that technology and innovation brings safe and sustainable benefits. 67 I wish you all fruitful connections and new inspiration at the Global FinTech Festival.
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China, 18 September 2026… The Monetary Authority of Singapore (MAS) and the People’s Bank of China (PBC) held the 4th annual Singapore-China Green Finance Taskforce (GFTF) meeting in Nanning, China on 17 September 2026.
MAS and the China Securities Regulatory Commission held their 10th annual supervisory roundtable in Singapore on 29 June 2026.
At the Lujiazui Forum 2026, Mr Chia Der Jiun, Managing Director of the Monetary Authority of Singapore, shared perspectives on the economic outlook, the need to build resilience amid an environment of high policy uncertainty, expanding regional economic and financial cooperation, and continued support for international financial institutions.