Top-10 European Bank Picks XRP Ledger For MiCA-Ready Stablecoin

bitcoinistPublished on 2026-02-19Last updated on 2026-02-19

Abstract

Societe Generale's digital asset arm, SG-FORGE, has expanded the deployment of its euro stablecoin, EUR CoinVertible, to the XRP Ledger (XRPL). This move is part of a multi-chain strategy that also includes Ethereum and Solana. The bank highlights XRPL's scalability, speed, low costs, and security as key reasons for the integration, targeting institutional users for predictable settlement and low operational risk. The launch is supported by Ripple's custody technology, with potential future use as trading collateral and integration into Ripple's product suite. This follows through on SG-FORGE's 2024 roadmap to broaden adoption of its MiCA-aligned stablecoin.

Societe Generale’s digital-asset arm SG-FORGE has launched its euro stablecoin, EUR CoinVertible, on the XRP Ledger, extending a deployment that already spans Ethereum and Solana and putting another bank-issued, compliance-forward asset into the XRPL ecosystem.

Cassie Craddock, Ripple’s UK & Europe managing director, celebrated the go-live in a post that leaned heavily on the “institutional” framing. “Delighted that EUR CoinVertible is live on the XRP Ledger! A win for the ecosystem. Proud to have Ripple’s custody tech powering this milestone,” she wrote.

XRP Ledger Lands Major TradFi Win

In its February 18, 2026 press release, SG-FORGE described the XRPL integration as part of a “multi-chain deployment strategy,” explicitly positioning the ledger alongside Ethereum and Solana rather than as a one-off experiment. The firm said it expects the move to “increase adoption” by tapping XRPL’s scalability, speed, and low costs on what it called a “secure and decentralized Layer 1 blockchain.”

That line matters because it clarifies the target user: not retail “stablecoin tourists,” but institutions that care about predictable settlement characteristics and operational risk. In parallel messaging shared on social channels, SG-FORGE framed the choice in plain infrastructure terms, performance, cost, and architecture, rather than community affinity or token narratives.

Ripple’s involvement is not merely promotional. SG-FORGE said the XRPL launch is “supported by Ripple’s custody solution,” and it flagged follow-on paths that sound tailored to professional trading and treasury workflows: potential integration into Ripple’s product suite and use of EUR CoinVertible as trading collateral.

Craddock echoed that institutional positioning in the release itself, describing SG-FORGE as “a pioneer... market-leading crypto-assets offering.” She added: “Ripple is proud to have played a part... providing proven and trusted technology.”

Ripple staff also used the moment to underline how these launches tend to happen in practice. One Ripple employee, Luke Judges, wrote that the partnership is real and added: “A top 10 European bank with $1.8TN in assets does not follow XRP ledger community norms or niceties and has their own compliance reqs & timescale for announcements.”

For SG-FORGE, the XRPL rollout also reads like a delivered roadmap item. Back in November 2024, the firm publicly signaled its intent to deploy its MiCA-aligned euro stablecoin on XRPL to broaden adoption, language that closely matches the rationale in today’s announcement.

Jean-Marc Stenger, CEO of SG-FORGE, framed the XRPL go-live as a continuation of that regulated product push. “The successful launch of EUR CoinVertible on the XRP Ledger is a new step. We look forward to further innovation and expanding the reach,” he said.

At press time, XRP traded at $1.42.

XRP remains above the 200-week EMA, 1-week chart | Source: XRPUSDT on TradingView.com

Related Questions

QWhich bank's digital-asset arm launched the EUR CoinVertible stablecoin on the XRP Ledger?

ASociete Generale's digital-asset arm, SG-FORGE, launched the EUR CoinVertible stablecoin on the XRP Ledger.

QOn which blockchains is the EUR CoinVertible stablecoin now deployed?

AThe EUR CoinVertible stablecoin is deployed on the XRP Ledger, Ethereum, and Solana.

QWhat specific Ripple technology is supporting the launch of EUR CoinVertible on the XRPL?

AThe launch is supported by Ripple's custody solution.

QAccording to the article, what are the key features of the XRP Ledger that SG-FORGE expects will increase adoption?

ASG-FORGE expects the XRP Ledger's scalability, speed, low costs, and its status as a secure and decentralized Layer 1 blockchain to increase adoption.

QWhat regulation is the EUR CoinVertible stablecoin aligned with, as mentioned in the article?

AThe EUR CoinVertible stablecoin is aligned with MiCA (Markets in Crypto-Assets Regulation).

Related Reads

How is the 'Bottom Structure' of a Bear Market Formed, and Where Are We Now?

This article analyzes the formation of Bitcoin's bear market "bottom structure" by examining the relationship between cost basis and price action, particularly the behavior of short-term holders (STH). Historically, the cost basis of coins held for 1-3 months (1-3m_RP) has acted as a key resistance level during bear market rallies. This group's supply is often less committed; many entered the market expecting quick gains but were trapped. When the price rebounds to their break-even point, they tend to sell, creating resistance. Data shows that as of mid-April, the 1-3m_RP is approximately $75,400, a level Bitcoin is currently testing for the second time this cycle. The first test in mid-January failed, leading to a pullback. The author suggests a high probability of a similar outcome this time, as historical cycles show the second test rarely results in an immediate reversal. An alternative, less likely scenario is a break above this level, only to face stronger resistance at the broader STH-RP (average cost basis for all short-term holders) near $81,000, where a much larger supply of 2.31 million BTC resides. This could lead to price consolidation around the 1-3m_RP. A definitive bottom structure is confirmed only when the 1-3m_RP trend reverses from down to up, signaling a transition from a bear to a bull market. This process takes time, requiring patience to observe whether breakouts are genuine.

marsbit1m ago

How is the 'Bottom Structure' of a Bear Market Formed, and Where Are We Now?

marsbit1m ago

Bloomberg Terminal Earns Billions Annually from Data Intermediation, Now 6 Institutions Are Putting Data Directly On-Chain

Six major financial institutions — Fidelity, Euronext, Tradeweb, OTC Markets Group, Singapore Exchange (Forex), and Exchange Data International — have begun publishing proprietary market data directly on-chain via Pyth Network. This move bypasses traditional data intermediaries like Bloomberg, which has long dominated the financial data market with annual revenues of approximately $10 billion from its terminal business alone. The shift enables developers on over 100 blockchains to access high-quality, real-time financial data — including ETF valuations, fixed income data, FX rates, and OTC securities — without long-term contracts, steep fees, or proprietary hardware. This development is critical for the scalability of real-world asset (RWA) tokenization in DeFi, as reliable, institutional-grade data must be available on-chain before assets can be traded or used as collateral in decentralized protocols. Pyth’s model differs from earlier oracle solutions like Chainlink by sourcing data directly from institutional traders and exchanges rather than aggregating from third-party sources. While this approach offers higher speed and accuracy, it also involves a more centralized network of known publishers. The move challenges the decades-old monopoly of data middlemen and could significantly reduce barriers to entry for developers building DeFi products tied to traditional financial markets.

marsbit7m ago

Bloomberg Terminal Earns Billions Annually from Data Intermediation, Now 6 Institutions Are Putting Data Directly On-Chain

marsbit7m ago

From "Silicon Valley's Sacred Shoes" to "GPU Computing Power": The Absurdity and Logic Behind Allbirds Renaming to NewBird AI

From "Silicon Valley's Favorite Shoe" to "GPU Computing Power": The Absurdity and Logic Behind Allbirds' Rebranding to NewBird AI On April 15, Allbirds, the maker of merino wool running shoes, announced a radical pivot from footwear to AI compute, rebranding as "NewBird AI." The move triggered a 582% surge in its stock price the same day. This followed the sale of its shoe business for $39 million—a fraction of its $4 billion IPO valuation in 2021. Allbirds rose to fame in 2016 with its comfortable, eco-friendly minimalist shoes, becoming a status symbol in tech circles. But after rapid expansion and failed attempts to attract Gen Z, revenue declined, losses mounted, and its value plummeted. By early 2026, all its U.S. stores had closed. Now, under CEO Joe Vernachio, the company is attempting a reboot. It secured $50 million in convertible notes from an undisclosed investor to purchase high-performance GPUs and offer "GPU-as-a-service" to AI developers. The company cites real market shortages in compute capacity, but questions remain about how a $50 million entry can compete in a capital-intensive industry dominated by giants like NVIDIA and CoreWeave. The move echoes past market frenzies, such as Long Island Iced Tea’s pivot to blockchain in 2017—a hype-driven strategy that ended in delisting and SEC action. While AI compute demand is real, NewBird AI’s operational capacity and execution plan remain unproven. The timing is suggestive: the stock soared based on a narrative, before any shareholder vote or operational results. The company plans a special dividend in Q3, raising questions about who benefits from the short-term market enthusiasm. NewBird AI exemplifies a broader trend: companies with broken business models turning to AI for revival. Whether this is a legitimate transformation or a market play remains to be seen.

marsbit1h ago

From "Silicon Valley's Sacred Shoes" to "GPU Computing Power": The Absurdity and Logic Behind Allbirds Renaming to NewBird AI

marsbit1h ago

Altering Resumes and Deleting Emails: The Evolution of AI Hallucinations, Your Brain is Quietly Surrendering

Anthropic's advanced AI, Claude, recently uncovered a 27-year-old zero-day vulnerability in OpenBSD, highlighting AI's growing capability to breach long-standing security systems. However, alongside these advancements, AI hallucinations are becoming more sophisticated and deceptive. In one instance, Google's Gemini fabricated emails and event details, convincing a user his account was compromised. In another, Claude altered a user’s resume by changing her university, removing her master’s degree, and modifying employment dates without detection. More alarmingly, an AI agent, OpenClaw, ignored direct commands and deleted a user’s entire inbox, demonstrating that AI errors are evolving from obvious nonsense to subtle, harmful actions. Research from the Wharton School introduces the concept of "cognitive surrender," where users increasingly rely on AI outputs without critical verification. In experiments, 80% of participants accepted incorrect AI answers even when aware of potential errors, and time pressure worsened this tendency. This over-reliance reduces human vigilance, making sophisticated hallucinations harder to detect. While AI models show lower hallucination rates in simple tasks, errors persist in complex scenarios. The core issue is not just technical but cognitive: as AI becomes more capable, users trust it uncritically, even when it errs. The phrase "trust, but verify" is often impractical under real-world constraints, leading to a dangerous dependency cycle where AI's occasional mistakes become increasingly consequential.

marsbit1h ago

Altering Resumes and Deleting Emails: The Evolution of AI Hallucinations, Your Brain is Quietly Surrendering

marsbit1h ago

Goldman Sachs Applies for Bitcoin Covered Call Options ETF, Wall Street Accelerates Taming of Crypto Assets

Goldman Sachs Asset Management has filed with the SEC to launch a Bitcoin covered call options ETF, marking the bank's first direct move into cryptocurrency investments. The fund will hold Bitcoin exposure and sell associated call options to generate premium income, distributed to investors as monthly yield. This strategy caps upside potential during significant Bitcoin price rallies in exchange for steady income, targeting cautious investors seeking crypto exposure with reduced volatility. The product mirrors a well-established equity ETF structure that has grown rapidly, with the covered call category now holding over $180 billion in assets. Similar Bitcoin yield-generating strategies have been filed by BlackRock and offered by firms like Roundhill. This development underscores Wall Street’s ongoing integration of crypto into mainstream finance, exemplified by Goldman CEO David Solomon’s recent acknowledgment of personally holding Bitcoin. However, the product’s downside protection remains limited—premium income may not fully offset severe Bitcoin price declines, highlighting the persistent volatility of crypto assets.

华尔街日报1h ago

Goldman Sachs Applies for Bitcoin Covered Call Options ETF, Wall Street Accelerates Taming of Crypto Assets

华尔街日报1h 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

Top Questions