Ripple takes RLUSD multichain: Stablecoin expands to L2s with Wormhole

ambcrypto2025-12-15 tarihinde yayınlandı2025-12-15 tarihinde güncellendi

Özet

Ripple has expanded its U.S.-regulated stablecoin, RLUSD, to Layer 2 networks including Optimism, Base, Ink, and Unichain using Wormhole’s Native Token Transfers (NTT) standard. This enables native multichain issuance, reducing bridge risks and ensuring regulatory compliance. RLUSD is the first U.S. Trust-regulated stablecoin on these L2s. Backed by a NYDFS Trust Charter and with a pending OCC application, it aims to be the first dual-regulated stablecoin. The expansion enhances utility for both XRP and RLUSD, strengthening Ripple’s role in institutional DeFi and cross-chain liquidity.

Ripple has expanded its U.S.-regulated stablecoin, Ripple USD [RLUSD], to Layer 2 networks for the first time. This marks a major step toward a multichain strategy ahead of its full launch next year.

The testing rollout begins on Optimism, Base, Ink, and Unichain, and is powered by Wormhole’s Native Token Transfers [NTT] standard — a system designed to move assets across chains without relying on wrapped tokens or traditional bridge architectures.

The move positions RLUSD as the first U.S. Trust-regulated stablecoin to deploy natively on these L2 ecosystems.

RLUSD goes multichain with native issuance on L2s

Unlike bridged assets, Wormhole’s NTT framework enables RLUSD to maintain native issuance and control across every supported chain.

This approach reduces bridge risk, preserves liquidity integrity, and creates a regulatory-compliant pathway for institutional DeFi expansion.

According to the announcement, Optimism serves as the entry point, with Base, Ink, and Unichain interconnected through the same NTT infrastructure — allowing Ripple to scale RLUSD across multiple environments without fragmentation.

Ripple’s SVP of Stablecoin, Jack McDonald, said the expansion reflects rising institutional demand for a fully compliant stablecoin that can move across chains with predictable oversight.

“Stablecoins are the gateway to DeFi and institutional adoption,” he said. “By launching RLUSD on these L2 networks, we are setting the standard where compliance and on-chain efficiency converge.”

Why regulation matters more than ever

RLUSD launched under a New York Department of Financial Services [NYDFS] Trust Charter, one of the most stringent regulatory frameworks in crypto.

Last week, AMBCrypto also reported that Ripple has applied for an OCC charter. If approved, this would make RLUSD the first stablecoin simultaneously overseen at both the state and federal levels.

No existing major stablecoin, including USDC or USDT, operates under this dual structure.

Ripple now holds more than 75 licenses globally, with recent approvals in Dubai and Abu Dhabi further strengthening RLUSD’s international reach.

Utility boost for both Ripple XRP and RLUSD

The multichain expansion is designed to strengthen XRP’s role in cross-chain liquidity.

Hex Trust recently issued wrapped XRP [wXRP] to support interoperability, enabling XRP holders to pair wXRP with RLUSD on supported chains for swaps, payments, lending, or yield-generating applications.

Data from DefilLama shows that Ethereum currently has the highest share of RLUSD [79.2%] worth over $1 billion, while the remaining 20.8% is on XRPL.

Final Thoughts

RLUSD’s L2 expansion sets a new regulatory benchmark for multichain stablecoins and positions Ripple as a direct challenger to USDC’s dominance.
The move enhances utility for both XRP and RLUSD, creating a deeper role for Ripple in institutional DeFi and cross-chain liquidity.

İlgili Okumalar

Actually, the Largest Use Case for Stablecoin Payments Is Not Cross-Border

Based on an analysis of $15.2 billion in identified on-chain stablecoin transfers, the data reveals that cross-border remittances represent only a portion of stablecoin demand. The dominant use case is domestic transfers, accounting for 62.6% ($9.5B) of the identified volume. Key markets include Turkey, South Korea, Mexico, Indonesia, and the US. This indicates stablecoins are widely used for domestic payments, transactions, and dollar-denominated savings within countries. Furthermore, 73.0% of all identified transaction volume (including domestic) stays within the sender's broader geographic region. The Asia-Pacific (APAC) region leads in stablecoin activity, contributing 41.0% of total sent volume and 41.6% of global domestic volume. It also shows a net inflow of funds, with Indonesia, Singapore, and South Korea being notable recipients. Major cross-border corridors already exist, such as Turkey-Indonesia and US-Mexico. Within APAC, corridors like Taiwan-Indonesia and Indonesia-South Korea show significant bilateral flows. For institutions, the key market opportunities currently lie in domestic settlement services and developing cross-border payment channels within the APAC region, which combines the largest transaction scale, high domestic usage, and positive net inflows.

marsbit32 dk önce

Actually, the Largest Use Case for Stablecoin Payments Is Not Cross-Border

marsbit32 dk önce

$2 Trillion: Countdown to AI's Largest IPO in History

The countdown for the largest IPO in AI history, a potential $2 trillion listing for Anthropic, is underway for October. The staggering valuation, reportedly projected by several investors, contrasts with the company's own internal restraint on setting a public target. Founded five years ago by former OpenAI core members, Anthropic's growth has been meteoric. Annual recurring revenue (ARR) surged from ~$9B in late 2025 to $47B by May 2026, with Q2 2026 revenue of $11.5B marking a 14x year-over-year increase. Bank valuations are even based on internal 2028 revenue forecasts of $190-200B. A key growth driver is Claude Code, its AI coding assistant. Its ARR quintupled in five months to $2.5B by February 2026, now constituting nearly 20% of total revenue. Surveys indicate Anthropic commands roughly 40% of enterprise LLM spending, doubling OpenAI's share in programming-specific use. However, alongside this explosive growth, reports detail significant internal cultural strife. Critics describe a divisive "priesthood" of PhD executives, led by CEO Dario Amodei, who promote a "save humanity" narrative that some employees find cult-like and alienating. This has reportedly created a demoralized workforce and a covert "underground network" of dissent among engineers torn between lucrative pre-IPO equity and a toxic work environment. Anthropic now faces a pivotal paradox: pursuing its mission of "safe" AI requires immense capital for compute, yet that capital demands relentless commercial growth. As it approaches its historic IPO, the company must navigate intense regulatory scrutiny, soaring operational costs, and internal tensions—any of which could destabilize its post-listing trajectory, much like SpaceX's significant post-IPO stock drop. The stage is set for a defining moment in tech history.

marsbit1 saat önce

$2 Trillion: Countdown to AI's Largest IPO in History

marsbit1 saat önce

AI Boosting Efficiency and Cutting Costs Makes VC Increasingly Expensive

"AI for Cost Reduction Makes VC Funding More Expensive" Despite the "cost-reduction and efficiency" narrative of AI, venture capital (VC) investment in the AI sector is becoming increasingly costly. While AI tools lower the initial costs for many startups—with team sizes shrinking across funding stages—the market is polarizing. For top-tier AI teams, especially those from leading companies like Google and OpenAI, funding rounds are now larger and valuations are higher than ever at the seed and early stages. For example, new ventures by prominent researchers are securing billions in funding with valuations reaching tens of billions before having a mature product. This creates a "barbell" market: lightweight startups need less capital, while elite AI firms attract massive investments early on. This dynamic raises the cost for VCs to acquire and maintain meaningful ownership stakes. As valuations soar early, securing the same equity percentage requires significantly larger capital commitments. VCs must now invest more upfront and reserve substantial funds for follow-on rounds to avoid dilution, prompting large firms like Accel and a16z to raise massive new funds. Consequently, capital is concentrating intensely in a few perceived winners like OpenAI and Anthropic, widening the gap between large and small VC funds. While high valuations bake in future growth expectations, they also compress potential returns, demanding that portfolio companies achieve unprecedented scale. For major VCs, the core strategy is clear: secure early positions in potential winners and maintain the capital to keep investing as valuations rapidly escalate.

marsbit2 saat önce

AI Boosting Efficiency and Cutting Costs Makes VC Increasingly Expensive

marsbit2 saat önce

An Eight-Year Investment Takes a Sharp Turn: Why Did Ethereum Suddenly Abandon Poseidon?

On August 13, Ethereum researcher Justin Drake announced a significant shift in Ethereum's Layer-1 cryptographic roadmap: abandoning the SNARK-friendly hash function Poseidon in favor of traditional functions like SHA2 or BLAKE2. This decision ends eight years of research and investment, marking a major revision to the post-quantum security strategy. Poseidon, introduced in 2019, was highly efficient for zkRollups and zkVMs within SNARK circuits. However, its need for prolonged cryptanalysis and the pressing timeline for quantum resistance revealed limitations. Recent breakthroughs in SNARK design, specifically using binary fields, now enable traditional, battle-tested hash functions to perform as efficiently as Poseidon within SNARKs. Benchmarks show modern laptops can now verify over a million traditional hash calls per second. This change is partly driven by accelerated concerns over quantum computing threats. Reports warn that "Cryptographically Relevant Quantum Computers" could break current blockchain signatures like ECDSA by the early 2030s, risking trillions in assets. Ethereum's response focuses on hash-based post-quantum signature schemes, deemed more quantum-resistant than some lattice-based alternatives under pressure from AI cryptanalysis. Ethereum's updated post-quantum roadmap targets a production-ready "leanVM" for signature aggregation by 2027, with full deployment across consensus, execution, and data layers by 2028. The shift to mature hash functions like SHA2 reduces reliance on newer algorithms and aligns with the goal of using widely analyzed cryptographic primitives. Other major blockchains are also preparing. Solana's core teams have independently chosen the NIST-standardized Falcon signature scheme for its compact size. Starknet plans a phased migration, starting with replacing its Pedersen hash with BLAKE2. Ethereum's move signifies a strategic pivot towards proven security foundations for the quantum era.

marsbit3 saat önce

An Eight-Year Investment Takes a Sharp Turn: Why Did Ethereum Suddenly Abandon Poseidon?

marsbit3 saat önce

Programmers Worldwide Are Wasting Money on Anthropic! The Company Can't Stand It Anymore

Anthropic recently published guidelines to help developers using Claude Code reduce unnecessary token costs. The key recommendations include: 1) Clear (/clear) conversations after completing a task to avoid carrying irrelevant file reads and command outputs into the next task. 2) Set the model and reasoning effort level at the start of a session, as switching mid-session invalidates the prompt cache, requiring a full-price recalculation of the entire dialog history. 3) Attach files using @ references instead of typing paths manually to avoid extra tool calls and searches that bloat the context. 4) Add quiet flags to verbose commands (e.g., in CLAUDE.md) to minimize lengthy output in the dialog history. 5) Use /compact while the session cache is still warm (before breaks) to compress the dialog at one-tenth the cost. 6) Offload large-output tasks to a sub-agent, which runs in an isolated context and only returns conclusions, preventing intermediate outputs from polluting the main dialog. The article explains token pricing: input tokens (prefill) are processed in parallel, while output tokens (decode) are generated serially, making output tokens five times more expensive. Caching is crucial for savings—if a request's prefix (system prompt, CLAUDE.md, dialog history) matches the previous one byte-for-byte, reading it costs only 10% of the standard input price. However, cache invalidation occurs when changing models, effort levels, fast mode, compressing dialogs, after cache expiration, or when resuming old sessions. Dialog history also grows quadratically (O(n²)) as file contents and command outputs accumulate, increasing costs per round. Proactive context management—like isolating noisy tasks, using /rewind to trim unproductive turns, and task-based session clearing—is becoming an essential skill for cost-effective AI-assisted development.

marsbit5 saat önce

Programmers Worldwide Are Wasting Money on Anthropic! The Company Can't Stand It Anymore

marsbit5 saat önce

İşlemler

Spot