BoE Faces Pushback Over Proposed Stablecoin Ownership Limits

TheCryptoTimesPublicado a 2025-09-15Actualizado a 2025-09-15

The Bank of England (BoE) is facing criticism from cryptocurrency and payment groups over its proposal to impose strict restrictions on stablecoin ownership. This initiative would make the United Kingdom’s regulations tougher than those in the US or the EU. 

According to the press release, the central bank plans to cap individual ownership of systemic stablecoins, tokens widely used or likely to be used for UK payments, at £10,000 to £20,000 ($12,500 to $25,000), and business ownership at £10 million ($12.5 million). The BoE argues these limits are necessary to protect the banking system from deposit drainage and financial stability risks, such as sudden credit shortages for businesses and households.

The global stablecoin market is worth about $288 billion, mostly driven by USD-based tokens, and Coinbase expects it to grow to $1.2 trillion by 2028. In July, the US introduced the GENIUS Act, a law that creates a regulatory framework for stablecoins in its financial system.

In contrast, the BoE’s proposed caps have sparked concerns about stifling innovation and placing the UK at a competitive disadvantage. Tom Duff Gordon, Vice President of International Policy at Coinbase, stated, “Imposing caps on stablecoins is bad for UK savers, bad for the City, and bad for sterling.” He further added that, “No other major jurisdiction has deemed it necessary to impose caps.”

Industry executives argue the limits would be costly and complex to enforce. Simon Jennings, executive director of the UK Cryptoasset Business Council, noted that stablecoin issuers lack visibility into token holders, requiring expensive systems like digital IDs or wallet coordination to implement caps. 

BoE’s stablecoin limits spark tensions and delay UK crypto edge

The debate has heightened tensions between the BoE and the Treasury, especially after BoE Governor Andrew Bailey intervened to delay a fintech banking license for Revolut. Chancellor Rachel Reeves has pledged to advance blockchain technology, including stablecoins, to support UK financial innovation. 

The BoE has described the limits as potentially “transitional” to help the financial system adapt to digital currencies. It plans to release a consultation on stablecoin regulation later this year. Gilles Chemla, a professor at Imperial Business School, warned that the UK risks falling behind in stablecoin regulation. “London has the talent and markets to lead the digital economy, but delays in regulatory frameworks are eroding that edge,” he said.

On July 3, 2025, the Bank of England cautioned that the growing popularity of stablecoins could undermine public confidence in conventional currency.

Also Read: UK Crypto Petition Backed by Coinbase Passes 5,000 Signatures


Mobile Only ImageMobile Only Image

Lecturas Relacionadas

Tras tres años de retraso, el último artículo de la exalumna de la Universidad de Pekín, Lilian Weng, se viraliza

"Tras tres años sin actualizar su blog, la ex vicepresidenta de OpenAI y cofundadora de Thinking Machines, Lilian Weng, publica un extenso análisis que cuestiona la fiabilidad de las 'Scaling Laws', las leyes de escalamiento que han guiado inversiones billonarias en IA. El artículo desmonta que la mejora del rendimiento de los modelos de lenguaje (LLM) al aumentar parámetros, datos y computación sea tan predecible como se creía. Expone divergencias clave: en 2020, OpenAI concluyó que el tamaño del modelo debía crecer más rápido que los datos, mientras que DeepMind (2022) defendió un crecimiento proporcional, un desacuerdo atribuido a diferencias metodológicas y al tamaño limitado de los experimentos iniciales. Más críticamente, Weng revela que la metodología del influyente estudio 'Chinchilla' de DeepMind contenía errores, como una función de pérdida que no convergía correctamente, lo que significa que la 'fórmula óptima' utilizada durante años por la industria podría no serlo. El análisis subraya un problema fundamental: las leyes clásicas asumen datos únicos e infinitos, pero los textos de alta calidad se agotan. La repetición de datos en el entrenamiento degrada el rendimiento, especialmente en modelos grandes. Esto explica el cambio de la industria hacia el aprendizaje por refuerzo, el cómputo en tiempo de prueba y los datos sintéticos. En resumen, el artículo argumenta que la era de la escalabilidad simple ('scale is all you need') toca a su fin, y que el progreso futuro de la IA dependerá de refinamientos metodológicos precisos y de nuevas vías para superar la limitación de datos."

marsbitHace 54 min(s)

Tras tres años de retraso, el último artículo de la exalumna de la Universidad de Pekín, Lilian Weng, se viraliza

marsbitHace 54 min(s)

Trading

Spot
Futuros
活动图片