Bank Of England Eyes ‘Temporary’ Stablecoin Ownership Cap In Proposed Regulatory Regime

bitcoinistPublished on 2025-11-11Last updated on 2025-11-11

Abstract

The Bank of England (BOE) has published the highly anticipated consultation paper on its proposed regulatory regime for stablecoins, set...

Trusted Editorial content, reviewed by leading industry experts and seasoned editors. Ad Disclosure

The Bank of England (BOE) has published the highly anticipated consultation paper on its proposed regulatory regime for stablecoins, set to be implemented in the second half of next year.

BOE Moves Forward With Stablecoin Holding Limits

On Monday, the Bank of England released a new consultation paper on its proposed regulatory framework for sterling-denominated systemic stablecoins, addressing backing rules and holding limits.

The BOE’s new framework is built on feedback received on the November 2023 Discussion Paper, reflecting the Bank’s efforts to draft “robust, future-proof” rules that are aligned with the regulator’s strategy to modernize UK retail payments.

Notably, the Bank has moved forward with a controversial proposal to cap stablecoin ownership to “mitigate financial stability risks stemming from large and rapid outflows of deposits from the banking sector.”

As reported by Bitcoinist, the central bank has been exploring restrictions on stablecoin ownership in the country for months, seeking to impose limits of £10,000 to £20,000 for individuals and £10 million for businesses. The plan resembles its proposed approach to the digital pound, also aimed at addressing financial stability risks.

Some crypto industry and payment groups heavily criticized the central bank’s proposal, arguing that it would put the UK at a disadvantage against the US and the European Union (EU).

Following the backlash, news media outlets reported that the BOE was exploring granting exemptions to businesses that need to hold large amounts of stablecoins, like crypto exchanges.

The consultation paper confirmed the holding limits proposal “to safeguard continued access to credit as the financial system gradually adapts to new forms of digital money.”

However, it clarified that the limits would be “temporary” and would be removed “once the transition no longer poses risks to the provision of finance to the real economy.” It also noted that an exemption regime will allow the largest businesses to hold more stablecoins if required.

New Regime Eyes Joint Regulatory Approach

As the announcement explained, the regime will only apply sterling-pegged stablecoins. Meanwhile, stablecoins used for non-systemic purposes, such as the buying and selling of crypto assets, will be supervised by the Financial Conduct Authority (FCA).

The BOE unveiled a joint regulatory approach with the FCA, with a document clarifying how rules will apply in practice set to be published in 2026. “If recognised as systemic by HM Treasury (HMT), they will transition into the Bank’s regime and will be jointly regulated, with the Bank overseeing prudential and financial stability risks, and the FCA continuing to supervise conduct and consumer protection,” the Bank detailed.

stablecoin

Proposed joint approach between the FCA and the Bank of England. Source: BOE

Among the key policy proposals covered in the consultation paper, the Bank suggested that systemic stablecoin issuers be allowed to hold up to 60% of backing assets in short-term UK government debt.

The BOE will provide issuers with unremunerated accounts at the Bank for the remaining 40%, aiming to ensure “robust redemption and public confidence, even under stress.”

Additionally, issuers considered systemic at launch or transitioning from the FCA regime will initially be able to hold up to 95% of their backing assets in short-term UK government debt to support viability as they grow.

A new policy also proposes central bank liquidity arrangements to issuers in times of stress, reinforcing financial stability by “providing a backstop should systemic issuers be unable to monetise their backing assets in private markets.”

Sarah Breeden, Deputy Governor for Financial Stability, affirmed that the BOE’s objective “remains to support innovation and build trust in this emerging form of money.”

“We’ve listened carefully to feedback and amended our proposals for achieving this, including on how stablecoin issuers interact with the Bank of England. These proposals are fit for a future where stablecoins play a meaningful role in payments, giving the industry the clarity it needs to plan with confidence,” she concluded.

stablecoin, bitcoin, btc, btcusdt

Bitcoin (BTC) trades at $106,139 on the one-week chart. Source: BTCUSDT on TradingView
Featured Image from Unsplash.com, Chart from TradingView.com
Editorial Process for bitcoinist is centered on delivering thoroughly researched, accurate, and unbiased content. We uphold strict sourcing standards, and each page undergoes diligent review by our team of top technology experts and seasoned editors. This process ensures the integrity, relevance, and value of our content for our readers.

Rubmar is a crypto enthusiast who likes learning and improving constantly. She enjoys reporting on the latest news and developments in the crypto industry. Rubmar also enjoys scrapbooking, crafting, simulation games, and watching football.

Trending Cryptos

Related Reads

Morgan Stanley Research Report Analysis: The Absence of Long-Term Agreements for Traditional Memory May Not Be Bad; DDR4 and SLC NAND Are in the Strongest Price Increase Cycle

Morgan Stanley's report on August 14, 2026, highlights a strong price upcycle in traditional memory chips, arguing that the absence of Long-Term Agreements (LTAs) is advantageous. The report focuses on three products where fundamentals are improving due to a widening supply-demand gap and increased pricing power: DDR4, SLC NAND, and NOR Flash. For DDR4, price hikes are forecasted at 50% in Q3 2026 and over 10% in Q4, driven by broad demand and accelerated supply exit. The lack of LTAs allows vendors to fully capture spot price gains. SLC NAND is identified as the highest-conviction call, with prices expected to surge over 50% in both Q3 and Q4 2026, supported by severe capacity constraints and demand migration from MLC. Supply tightness is projected to last into 2027. NOR Flash prices are also expected to rise further in Q4 2026, with momentum potentially extending into H1 2027, supported by industrial, automotive, and AI server demand. Morgan Stanley has raised earnings estimates for several companies, with AP Memory as the top pick, followed by GigaDevice, Macronix, Winbond, Powerchip, and Nanya Tech. The core thesis is that without LTAs, traditional memory suppliers have greater pricing flexibility to benefit from the current upcycle, which for DDR4 will last through H2 2026, and for SLC NAND and NOR Flash, potentially into H1 2027.

marsbit3m ago

Morgan Stanley Research Report Analysis: The Absence of Long-Term Agreements for Traditional Memory May Not Be Bad; DDR4 and SLC NAND Are in the Strongest Price Increase Cycle

marsbit3m ago

OpenAI Researcher Exposes ASI Timeline: Most Have Become Reality

In April 2025, a group of former OpenAI researchers published a 71-page document titled "AI 2027," outlining a timeline for Artificial Superintelligence (ASI). Their predictions, now being tracked by an independent project, show 51% are already confirmed, ahead of schedule, or on track. Notably, alarming predictions are arriving faster than anticipated. The forecast that AI would achieve top-tier human-level capabilities in cyber offense and defense by early 2027 was realized in April 2026, nine months early. Similarly, major Pentagon contracts with leading AI labs were signed 18 months earlier than predicted. The core mechanism for an intelligence explosion—Recursive Self-Improvement (RSI), where AI accelerates its own development—has not yet closed its loop. While AI, like Anthropic's Claude, now writes most new code, the bottleneck has shifted to human review and high-level research direction. A July 2026 study indicates the current AI-driven productivity gain in R&D is about 9%, below the estimated 15% threshold needed for a self-sustaining RSI feedback loop. However, underlying capabilities continue to accelerate rapidly. The "time horizon" metric for AI to autonomously handle tasks is doubling every three months, suggesting monthly-scale autonomous operation could be feasible by early 2027. Consequently, the original authors have revised their median prediction for fully automated AI programming forward to around mid-2028.

marsbit10m ago

OpenAI Researcher Exposes ASI Timeline: Most Have Become Reality

marsbit10m ago

Trading

Spot

Hot Articles

What is $BANK

Bank AI: A Revolutionary Step in the Future of Banking Introduction In an era marked by rapid advancements in technology, Bank AI stands at the intersection of artificial intelligence (AI) and banking services. This innovative project seeks to redefine the financial landscape, enhancing operational efficiency, security measures, and customer experiences through the power of AI. As we embark on this exploration of Bank AI, we will delve into what the project entails, its operational dynamics, its historical context, and significant milestones. What is Bank AI? At its core, Bank AI represents a transformative initiative aimed at integrating artificial intelligence into various banking operations. This project harnesses the capabilities of AI to automate processes, improve risk management protocols, and enhance customer interaction through personalised services. The primary objectives of Bank AI include: Automation of Banking Functions: By leveraging AI technologies, Bank AI aims to automate routine tasks, reducing the burden on human resources and enhancing efficiency. Enhanced Risk Management: The project utilises AI algorithms to predict and identify risks, thereby fortifying security measures against fraud and other threats. Personalisation of Banking Services: Bank AI focuses on offering tailored financial products and services by analysing customer data and behaviours. Improving Customer Experience: The implementation of AI-driven solutions, such as chatbots and virtual assistants, aims to provide users with more human-like interactions, revolutionising the way customers engage with banks. With these goals, Bank AI positions itself as a crucial player in rendering banking more efficient, secure, and user-centric. Who is the Creator of Bank AI? Details regarding the creator of Bank AI remain unknown. As such, no specific individual or organisation has been identified in the available information. The anonymity surrounding the project's inception raises questions but does not detract from its ambitious vision and objectives. Who are the Investors of Bank AI? Similar to the project's creator, specific information regarding the investors or supporting organisations of Bank AI has not been disclosed. Without this information, it is challenging to outline the financial backing and institutional support that might be propelling the project forward. Nevertheless, the importance of having a robust investment foundation is pivotal for sustaining development in such an innovative field. How Does Bank AI Work? Bank AI operates on several innovative fronts, focusing on unique factors that differentiate it from traditional banking frameworks. Below are key operational features: Automation: By applying machine learning algorithms, Bank AI automates various manual processes within banks. This results in reduced operational costs and allows human workers to redirect their efforts towards more strategic activities. Advanced Risk Management: The integration of AI into risk management practices equips banks with tools to accurately predict potential threats such as fraud, ensuring that customer information and assets remain secure. Tailored Financial Recommendations: Through continuous learning from customer interactions, the AI systems develop a nuanced understanding of user needs, enabling them to offer tailored advice on financial decisions. Enhanced Customer Interactions: Utilizing chatbots and virtual assistants powered by AI, Bank AI enables a more engaging customer experience, allowing users to have their queries resolved quickly, thus reducing wait times and improving satisfaction levels. Together, these operational features position Bank AI as a pioneer in the banking sector, establishing new benchmarks for service delivery and operational excellence. Timeline of Bank AI Understanding the trajectory of Bank AI requires a look at its historical context. Below is a timeline highlighting important milestones and developments: Early 2010s: The conceptualisation of AI integration into banking services began to gain attention as banking institutions recognised the potential benefits. 2018: A marked increase in the implementation of AI technologies occurred when banks started using AI tools like chatbots for basic customer service and risk management systems for improved security handling. 2023: The sophistication of AI continued to advance, with generative AI being introduced for more complex tasks such as document processing and real-time investment analysis. This year marked a significant leap in the capabilities afforded to banks by AI technology. 2024-Current Status: As of this year, Bank AI is on an upward trajectory, with ongoing research and developments poised to further enhance capabilities in banking operations. Continued exploration of AI applications hints at exciting developments yet to come. Key Points About Bank AI Integration of AI in Banking: Bank AI focuses on adopting artificial intelligence to streamline banking processes and improve user experiences. Automation and Risk Management Focus: The project strongly emphasises these areas, aiming to shift the burden of routine tasks while enhancing security frameworks through predictive analytics. Personalised Banking Solutions: By harnessing customer data, Bank AI enables tailored banking services that cater to individual user needs. Commitment to Development: Bank AI remains committed to ongoing research and development efforts, ensuring its adaptability and ongoing relevance as technology continues to evolve. Conclusion In summary, Bank AI exemplifies a crucial step forward in the banking industry, leveraging artificial intelligence to reshape operational paradigms, enhance security, and promote customer satisfaction. Despite gaps in information surrounding the creator and investors, the clear objectives and functional mechanisms of Bank AI provide a strong foundation for its ongoing evolution. As AI technology continues to advance and merge with the banking sector, Bank AI is well-positioned to significantly impact the future of financial services, enhancing the way we understand and interact with banking.

389 Total ViewsPublished 2024.04.06Updated 2024.12.03

What is $BANK

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of BANK (BANK) are presented below.

活动图片