Bank of Korea Urges Bank-Led Won Stablecoin Issuance

TheNewsCryptoPublished on 2026-02-23Last updated on 2026-02-23

Abstract

The Bank of Korea (BOK) has urged that the issuance of Korean won-pegged stablecoins should be led by commercial banks, warning that private issuance could undermine monetary policy and create foreign exchange and financial stability risks. In a report submitted to the National Assembly, the central bank described stablecoins as "currency-like substitutes" and emphasized that their rollout must consider broader economic impacts, not just industrial profits. The BOK expressed concerns that stablecoins could be used to circumvent foreign exchange regulations and stressed that non-bank issuers might conflict with Korea’s separation of banking and commerce principles. It recommended that banks, which are subject to strict regulatory standards, should be the primary issuers, with any expansion beyond banks proceeding cautiously after risk assessments. The report reflects ongoing debates among policymakers about who should be allowed to issue won stablecoins and echoes the BOK’s previous warnings on the matter. While acknowledging stablecoins' potential role in the digital asset revolution, the bank proposed structural safeguards, including a bank-focused consortium model and a statutory interagency policy body for oversight. The BOK cited the U.S. GENIUS Act as an example of cross-agency supervision. However, this bank-led approach has faced opposition from industry members, including some policymakers, who argue that clearer rules for issuers could sufficiently mitigate risks.

The central bank of South Korea has allegedly renewed its push to keep Korean won-pegged stablecoin issuance in the hands of commercial banks, alerting policymakers that privately issued digital tokens could diminish monetary policy and create new foreign-exchange and financial-stability risks.

Recently, a report was submitted to the National Assembly Strategy and Finance Committee of South Korea. The Bank of Korea (BOK) mentioned won stablecoins as “currency-like substitutes” and said their rollout must account not only for industrial profits but also for monetary policy, foreign exchange stability and financial risks, as per the report.

The central bank restated concerns that stablecoins could be used to avoid foreign exchange regulations, comprising earlier reporting needs, and claimed that permitting non-bank bodies to issue them independently could conflict with the separation of banking and commerce principles of Korea.

It also mentioned that banks, which are subject to capital, governance and compliance standards, should be allowed first, with any widening beyond banks advancing slowly after risk assessments.

The report lands as policymakers debate a postponed stablecoin framework, with one of the prominent sticking points being who should be eligible to issue won-pegged tokens and how much control banks should hold in any issuing body.

The Echo of Previous Warnings

The bank allegedly stated programmable stablecoins could back the digital asset revolution and function as payment tools, but it also floated structural safeguards, including a bank-focused consortium model and a statutory interagency policy body that could systemise approvals and supervision over regulators.

As per the reports, the Bank of Korea also quoted the GENIUS Act framework of the United States as an example of cross-agency supervision that comprises the Treasury Department, the Federal Reserve and the Federal Deposit Insurance Corporation.

The report reflects its previous warnings, which claim that banks should be heading the introduction for stablecoin issuance since they are so far subject to strict regulatory needs. Although, this approach has witnessed a repulsion from the members of the industry, including some policymakers.

The chair of the Kaia DLT Foundation, Sangmin Seo, has earlier mentioned that the argument for banks heading the stablecoin launch is short on logical foundation. Seo mentioned that setting clearer rules for issuers can reduce risks.

Highlighted Crypto News Today:

Arthur Hayes Reveals Portfolio Bet on Commodities and Crypto

TagsGenius ACTKoreaStablecoin

Related Questions

QWhat is the Bank of Korea's main stance on who should issue won-pegged stablecoins?

AThe Bank of Korea's main stance is that the issuance of won-pegged stablecoins should be led by and kept in the hands of commercial banks.

QWhat are the three main areas of risk the BOK says stablecoin rollout must account for?

AThe three main areas of risk are monetary policy, foreign exchange stability, and financial risks.

QAccording to the BOK report, what principle could allowing non-banks to issue stablecoins conflict with?

AIt could conflict with Korea's principle of the separation of banking and commerce.

QWhich U.S. regulatory framework did the Bank of Korea cite as an example of cross-agency supervision?

AThe Bank of Korea cited the U.S. GENIUS Act framework as an example.

QWho is Sangmin Seo and what was his criticism of the bank-led stablecoin model?

ASangmin Seo is the chair of the Kaia DLT Foundation. He criticized the bank-led model, stating that the argument for banks heading the stablecoin launch is short on logical foundation and that setting clearer rules for issuers can reduce risks.

Related Reads

The King of Blind Date Attire in Korea: How SK Hynix Made a Comeback Against Samsung?

In South Korea's dating scene, SK Hynix employees are now highly sought after, a status shift fueled by the company's astronomical profits and employee bonuses, projected to reach up to 6.1 million RMB per person by 2027. This marks a dramatic reversal for the long-time second-place player in memory semiconductors, which has now surpassed its rival Samsung in annual operating profit. The turnaround story began in 2008 when a struggling Hynix, emerging from bankruptcy restructuring, took a risky bet by agreeing to develop High Bandwidth Memory (HBM) with AMD. At the time, HBM had no clear market beyond high-end graphics cards and was a costly, complex technology. Major players like Samsung, pursuing its own HMC technology, declined. For Hynix, with only memory as its core business, it was a gamble born of necessity. The pivotal moment came in 2012 when SK Group Chairman Chey Tae-won acquired Hynix. Defying industry downturns, he invested heavily in R&D and fabrication, sustaining the HBM project through over a decade of commercial uncertainty and internal challenges. A key break occurred around 2016-2017 when Samsung faced production issues supplying HBM2 for Google's TPU, allowing SK Hynix to gain a crucial foothold in the data center market. The AI explosion post-ChatGPT in 2022 was the catalyst, turning HBM into a critical bottleneck for AI accelerators like NVIDIA's GPUs. By 2025, SK Hynix captured 62% of the global HBM market, leaving Samsung at 17%. For the first time, its annual operating profit exceeded Samsung's. Analysts point to the "innovator's dilemma" to explain Samsung's miss: its vast, successful business portfolio made it risk-averse, preventing an all-in bet on the initially niche HBM technology. In contrast, SK Hynix, as a challenger with its back against the wall, had no choice but to commit fully. The story highlights how Korea's chaebol system allows for ultra-long-term bets beyond quarterly pressures. However, SK Hynix's lead isn't guaranteed. Samsung is aggressively catching up on HBM4, and challenges like customer concentration (heavy reliance on NVIDIA) and technical hurdles in advanced packaging remain. The narrative underscores a market truth: the greatest alpha often comes from betting on uncertain, long-term directions others dismiss, much like HBM in 2008.

marsbit12m ago

The King of Blind Date Attire in Korea: How SK Hynix Made a Comeback Against Samsung?

marsbit12m ago

Understanding Hash in One Article: The "Browser Miner" on Ethereum

Hash is an Ethereum-based ERC-20 token described as a "browser-minable post-quantum token." Its key features include enabling browser-based GPU mining without specialized hardware, a fixed supply cap of 21 million tokens, immutable and permissionless smart contracts with no team allocation or pre-mining, and an emphasis on post-quantum security using Keccak256 hashing. The mining mechanism is a simplified on-chain proof-of-work where miners solve unique challenges tied to their wallet address. Key design elements prevent answer theft, with epochs resetting every 100 blocks (~20 minutes) and a per-block minting limit. Emission follows a Bitcoin-like halving schedule every 100,000 mints, starting at 100 tokens per mint. Projections suggest all tokens could be mined within approximately 294 days if a target rate of one mint per minute is sustained. Hash emphasizes "post-quantum" security by leveraging hash-based primitives like Keccak256, which are considered more resistant to quantum attacks compared to elliptic-curve cryptography. While not a fully post-quantum asset, it aligns with Ethereum's broader post-quantum research narrative. The project completed its Genesis sale at $0.03 and began trading on Uniswap, with its price reaching around $0.19. The initial circulating supply is small, with 5% sold in Genesis and 5% allocated to liquidity. The majority (47.6% of total supply) is allocated to early-stage mining, leading to a front-loaded emission schedule. This structure, combined with low initial liquidity, makes Hash a high-volatility, high-risk project dependent on sustained miner participation and market demand to absorb new supply.

marsbit26m ago

Understanding Hash in One Article: The "Browser Miner" on Ethereum

marsbit26m ago

OpenAI's Largest Internal Wealth Creation: 600 People Cash Out a Total of $6.6 Billion, 75 Take Home the Maximum $30 Million Each

A Wall Street Journal report reveals OpenAI's unprecedented pre-IPO wealth creation. In a single employee stock sale last October, over 600 current and former employees sold shares, collectively cashing out approximately $6.6 billion. Due to high investor demand, the company tripled the individual sale cap to $30 million, with about 75 employees selling the maximum amount. This event represents the largest such transaction in tech industry history for a private company. OpenAI's valuation was $500 billion for this tender offer. Employees with over two years of tenure were eligible, allowing many post-ChatGPT hires their first liquidity event. The company's stock has reportedly grown over 100-fold in seven years. Following a restructuring, employees collectively hold about 26% of OpenAI. The scale of executive wealth is also staggering. In court testimony related to Elon Musk's lawsuit, President and co-founder Greg Brockman confirmed his OpenAI stake is worth around $30 billion. Analysis indicates about 165 current and former employees hold a combined ~$164.9 billion in equity, averaging nearly $1 billion per person in paper wealth. OpenAI's per-employee stock-based compensation is estimated to be 34 times the average of major tech firms before their IPOs. OpenAI continues its rapid ascent, closing a $122 billion funding round at an $852 billion valuation in March. With monthly revenue hitting $2 billion, over 900 million weekly ChatGPT users, and plans for a potential trillion-dollar IPO in late 2026, this wealth-creation engine shows no signs of stopping.

链捕手48m ago

OpenAI's Largest Internal Wealth Creation: 600 People Cash Out a Total of $6.6 Billion, 75 Take Home the Maximum $30 Million Each

链捕手48m ago

Trading

Spot
Futures

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.

152 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