Wall Street goes on-chain: JPMorgan executes landmark debt issuance on Solana

ambcryptoОпубликовано 2025-12-11Обновлено 2025-12-11

Введение

J.P. Morgan has executed a landmark $50 million commercial paper issuance for Galaxy Digital on the Solana blockchain, with Coinbase and Franklin Templeton as buyers. This represents one of the first U.S. debt issuances on a public blockchain, signaling growing institutional adoption of open networks. The transaction was settled entirely in USDC, highlighting Solana’s capability to support high-throughput, low-cost institutional settlements. The move underscores a shift toward tokenized real-world assets and positions Solana as a leading infrastructure for next-generation capital markets.

J.P. Morgan has completed one of the first-ever U.S. commercial paper issuances on a public blockchain — and it chose the Solana network to do it.

The bank arranged a U.S. Commercial Paper [USCP] issuance for Galaxy Digital Holdings LP, with Coinbase and Franklin Templeton purchasing the tokenized security.

The move marks one of the earliest debt issuances executed on a public blockchain and a major milestone in the institutional adoption of open networks.

The official publication didn’t mention the value of the issuance, but Reuters reported that it’s worth $50 million.

“This trade demonstrates institutional appetite for digital assets and our capability to securely bring new instruments on-chain using Solana,”

said Scott Lucas, Head of Markets Digital Assets at J.P. Morgan.

Why Solana? Data shows a network ready for institutions

Solana has spent most of 2025 building a compelling case for enterprise-level finance. According to DeFiLlama data, Solana’s TVL and transaction activity have climbed steadily throughout the year, even as volatility hit broader crypto markets.

The chart shows:

  • TVL rising from ~$6B at the start of 2025 toward ~$10–12B mid-year
  • Transaction counts remaining consistently high
  • A clear upward shift into Q4, coinciding with growing institutional experimentation

For a bank like JPMorgan, which requires throughput, cost efficiency, and deterministic settlement, Solana offers the lowest-latency public infrastructure currently available.

This issuance confirms that the chain is now being utilized for real-world financial instruments, not just crypto-native activities.

USDC settlement, tokenized debt, and a new playbook for money markets

J.P. Morgan not only created the USCP token but also facilitated on-chain delivery-versus-payment settlement.

Crucially, both issuance and redemption are settled directly in USDC, which is issued by Circle.

The bank emphasized the significance of this design:

“Both the issuance and redemption proceeds will be paid in USDC stablecoins issued by Circle, representing another market first for the USCP market.”

For Galaxy, this marks its first-ever commercial paper issuance — now executed entirely on a public blockchain.

Galaxy’s Jason Urban said:

“This issuance is a clear example of how public blockchains can improve the way capital markets operate.”

He added:

“We’re putting into practice the model we’ve long believed in: open, programmable infrastructure that supports institutional-grade financial products.”

Franklin Templeton echoed the same shift:

“We’ve entered a new era where institutions are no longer just experimenting with blockchain — we’re transacting on it in a big way.”

A watershed moment for public blockchains

JPMorgan’s decision to use Solana — instead of a permissioned or private chain — signals a turning point in institutional confidence.

With stablecoin settlement, tokenized money-market instruments, and support from global asset managers, the deal positions Solana as a foundation layer for next-generation capital markets.


Final Thoughts

  • JPMorgan’s $50M pilot on Solana signals that public blockchains are entering mainstream capital-markets infrastructure, not just crypto-native use cases.
  • If more issuers adopt tokenized debt, Solana could become a preferred platform for high-throughput institutional settlement, accelerating the RWA narrative heading into 2026.

Похожее

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

In recent months, the rapid growth of the AI industry has attracted significant talent from the crypto sector. A persistent question among researchers intersecting both fields is whether blockchain can become a foundational part of AI infrastructure. While many previous AI and Crypto projects focused on application layers (like AI Agents, on-chain reasoning, data markets, and compute rentals), few achieved viable commercial models. Gensyn differentiates itself by targeting the most critical and expensive layer of AI: model training. Gensyn aims to organize globally distributed GPU resources into an open AI training network. Developers can submit training tasks, nodes provide computational power, and the network verifies results while distributing incentives. The core issue addressed is not decentralization for its own sake, but the increasing centralization of compute power among tech giants. In the era of large models, access to GPUs (like the H100) has become a decisive bottleneck, dictating the pace of AI development. Major AI companies are heavily dependent on large cloud providers for compute resources. Gensyn's approach is significant for several reasons: 1) It operates at the core infrastructure layer (model training), the most resource-intensive and technically demanding part of the AI value chain. 2) It proposes a more open, collaborative model for compute, potentially increasing resource utilization by dynamically pooling idle GPUs, similar to early cloud computing logic. 3) Its technical moat lies in solving complex challenges like verifying training results, ensuring node honesty, and maintaining reliability in a distributed environment—making it more of a deep-tech infrastructure company. 4) It targets a validated, high-growth market with genuine demand, rather than pursuing blockchain integration without purpose. Ultimately, the boundaries between Crypto and AI are blurring. AI requires global resource coordination, incentive mechanisms, and collaborative systems—areas where crypto-native solutions excel. Gensyn represents a step toward making advanced training capabilities more accessible and collaborative, moving beyond a niche controlled by a few giants. If successful, it could evolve into a fundamental piece of AI infrastructure, where the most enduring value in the AI era is often created.

marsbit11 ч. назад

Gensyn AI: Don't Let AI Repeat the Mistakes of the Internet

marsbit11 ч. назад

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

A US researcher's visit to China's top AI labs reveals distinct cultural and organizational factors driving China's rapid AI development. While talent, data, and compute are similar to the West, Chinese labs excel through a pragmatic, execution-focused culture: less emphasis on individual stardom and conceptual debate, and more on teamwork, engineering optimization, and mastering the full tech stack. A key advantage is the integration of young students and researchers who approach model-building with fresh perspectives and low ego, prioritizing collective progress over personal credit. This contrasts with the US culture of self-promotion and "star scientist" narratives. Chinese labs also exhibit a strong "build, don't buy" mentality, preferring to develop core capabilities—like data pipelines and environments—in-house rather than relying on external services. The ecosystem feels more collaborative than tribal, with mutual respect among labs. While government support exists, its scale is unclear, and technical decisions appear driven by labs, not state mandates. Chinese companies across sectors, from platforms to consumer tech, are building their own foundational models to control their tech destiny, reflecting a broader cultural drive for technological sovereignty. Demand for AI is emerging, with spending patterns potentially mirroring cloud infrastructure more than traditional SaaS. Despite challenges like a less mature data industry and GPU shortages, Chinese labs are propelled by vast talent, rapid iteration, and deep integration with the open-source community. The competition is evolving beyond a pure model race into a contest of organizational execution, developer ecosystems, and industrial pragmatism.

marsbit13 ч. назад

Why is China's AI Developing So Fast? The Answer Lies Inside the Labs

marsbit13 ч. назад

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

Corning, a 175-year-old glass company, is experiencing a dramatic revival as a key player in AI infrastructure, driven by surging demand for high-performance optical fiber in data centers. AI data centers require vastly more fiber than traditional ones—5 to 10 times as much per rack—to handle high-speed data transmission between GPUs. This structural demand shift, coupled with supply constraints from the lengthy expansion cycle for fiber preforms, has created a significant supply-demand gap. Nvidia has invested in Corning, along with Lumentum and Coherent, in a $4.5 billion total commitment to secure the optical supply chain for AI. Corning's competitive edge lies in its expertise in producing ultra-low-loss, high-density, and bend-resistant specialty fiber, which is critical for 800G+ and future 1.6T data rates. Its deep involvement in co-packaged optics (CPO) with partners like Nvidia further solidifies its position. While not the largest fiber manufacturer globally, Corning's revenue from enterprise/data center clients now exceeds 40% of its optical communications sales, and it has secured multi-year supply agreements with major hyperscalers including Meta and Nvidia. Financially, Corning's optical communications revenue has surged, doubling from $1.3 billion in 2023 to over $3 billion in 2025. Its stock price has risen nearly 6-fold since late 2023. Key future catalysts include the rollout of Nvidia's CPO products and the scale of undisclosed customer agreements. However, risks include high current valuations and potential disruption from next-generation technologies like hollow-core fiber. The company's long-term bet on light over electricity, maintained even through the telecom bubble crash, is now being validated by the AI boom.

marsbit13 ч. назад

3 Years, 5 Times: The Rebirth of a Century-Old Glass Factory

marsbit13 ч. назад

Торговля

Спот
Фьючерсы

Популярные статьи

Обсуждения

Добро пожаловать в Сообщество HTX. Здесь вы сможете быть в курсе последних новостей о развитии платформы и получить доступ к профессиональной аналитической информации о рынке. Мнения пользователей о цене на SOL (SOL) представлены ниже.

活动图片