Why SWIFT’s Latest Global Payments Infrastructure Is Bullish For XRP Holders

bitcoinistPublished on 2026-03-26Last updated on 2026-03-26

Abstract

Crypto analyst Archie argues that SWIFT's new global payments infrastructure is a bullish development for XRP holders. He highlights that over 50 banks committed to SWIFT's new framework are confirmed RippleNet partners, including major institutions like Bank of America, Citi, and JPMorgan. Archie states this is not competition but an adoption wave, as SWIFT is building on top of Ripple's existing bank network, validating Ripple's vision. He believes this provides massive, institutional-grade confirmation for XRP's utility. Separately, Franklin Templeton's head of digital assets discussed institutional adoption, noting his firm is using the XRP Ledger to tokenize a fund, signaling real-world use rather than speculation. XRP price was around $1.41 at the time of writing.

Crypto pundit Archie has explained why SWIFT’s new global payments infrastructure is bullish for XRP holders. This came as the pundit highlighted how SWIFT’s major partners use Ripple’s RippleNet, which involves the altcoin.

Why SWIFT’s Payments Framework Is Bullish For XRP Holders

In an X post, Archie stated that SWIFT just gave XRP holders the ultimate bull signal. He noted that every bank named in their new retail payments framework is a Ripple partner. Over 50 banks are said to have committed to SWIFT’s global payments framework, which is expected to roll out this year.

Archie reiterated that all the banks that SWIFT has highlighted are confirmed RippleNet partners. These banks include Akbank, ANZ, Axis Bank, and Bank Alfalah. Furthermore, the pundit noted that the full participant list for SWIFT’s payments infrastructure includes banks linked to Ripple, which he believes is bullish for holders.

These banks include Santander, BBVA, Standard Chartered, HDFC Bank, ICICI Bank, State Bank of India, and BNI, as well as Wall Street giants such as Bank of America, Citi, Deutsche Bank, HSBC, and JPMorgan. The analyst said that many of these banks have documented Ripple pilots or RippleNet usage.

Archie noted that SWIFT already routes over 44 million messages daily across 11,500 institutions. As such, this move with Ripple’s partners could draw more attention to the XRP ecosystem. The pundit stated that SWIFT’s move isn’t a competition but rather a continuation of traditional finance (TradFi), quietly admitting that Ripple’s vision was correct, especially as SWIFT is directly building on top of the crypto firm’s existing bank network.

In line with this, the pundit declared that XRP’s real-world utility just got a massive boost, with institutional-grade confirmation. He added that the adoption wave is breaking, with institutions potentially showing interest in the altcoin.

When The Altcoin Will Truly Gain Institutional Adoption

During an interview on the Paul Barron podcast, Franklin Templeton’s head of digital assets, Roger Bayston, said that the token will gain institutional adoption when companies realize how they can use the XRP Ledger to solve real business problems. He opined that a lot of these institutions do not yet understand how they can use the distributed ledger inside of their information-based businesses.

It is worth noting that Franklin Templeton already revealed plans to tokenize its money market fund on the Ledger. Bayston signaled that they were betting big on the toekn as they plan to use the network to boost their operations. He said that they didn’t buy XRP to speculate but to use the altcoin as they operate the tokenized fund on the network.

At the time of writing, the XRP price is trading at around $1.41, up in the last 24 hours, according to data from CoinMarketCap.

XRP trading at $1.42 on the 1D chart | Source: XRPUSDT on Tradingview.com

Related Questions

QAccording to crypto pundit Archie, why is SWIFT's new global payments infrastructure considered bullish for XRP holders?

ABecause every bank named in SWIFT's new retail payments framework is a confirmed RippleNet partner, and SWIFT is building on top of Ripple's existing bank network, which draws more attention to the XRP ecosystem and confirms Ripple's vision.

QWhich specific banks were mentioned as being both part of SWIFT's framework and RippleNet partners?

AThe banks mentioned include Akbank, ANZ, Axis Bank, Bank Alfalah, Santander, BBVA, Standard Chartered, HDFC Bank, ICICI Bank, State Bank of India, BNI, Bank of America, Citi, Deutsche Bank, HSBC, and JPMorgan.

QWhat did Franklin Templeton's head of digital assets, Roger Bayston, say about when XRP will gain institutional adoption?

AHe stated that XRP will gain institutional adoption when companies realize how they can use the XRP Ledger to solve real business problems, as many institutions do not yet understand how to use the distributed ledger in their information-based businesses.

QWhat specific action has Franklin Templeton taken regarding the XRP Ledger?

AFranklin Templeton has revealed plans to tokenize its money market fund on the XRP Ledger and is using the network to boost their operations, not for speculation.

QWhat was the price of XRP and its 24-hour performance at the time the article was written?

AXRP was trading at around $1.41, up in the last 24 hours.

Related Reads

How to Do Research Well: Deliberately Practice the Real Skills That Matter

No one truly teaches you how to do research. You're often given a desk, a pre-selected problem, and vague instructions to "create something new." Consequently, many people reverse-engineer the job based on visible outputs—papers, posts, announcements—learning only how to *appear* like a researcher rather than how to *become* one. True research capability is built from stacking small, trainable skills, nearly all of which can be developed through deliberate practice. **Pick Your Own Problem:** Most researchers absorb problems from advisors or trends, lacking the underlying reasoning. Choosing a problem you genuinely care about, as John Schulman advises, leads to original work. Develop "taste" like a muscle: predict experiment outcomes, guess paper results from methods, and track which findings remain important over time. **Upgrade Your Inputs:** Relying on shared reading lists (arXiv hot lists, filtered group chats) leads to unoriginal conclusions. Undervalued old literature often holds crucial insights (e.g., MoE, LSTM, backpropagation). Richard Sutton's "The Bitter Lesson" or Claude Shannon's 1952 talk on creative thinking are more predictive than lengthy modern surveys. Breadth matters as much as depth: draw from neuroscience, mechanism design, hardware knowledge, and honest statistics. Read papers directly, especially appendices and limitations sections. **Write Everything Down:** As Paul Graham noted, writing exposes flaws in seemingly mature ideas. Writing is the cheapest defense against self-deception. Following Feynman's principle, Darwin programmatically wrote down facts contradicting his theory to combat memory bias. Maintain a detailed log of hypotheses, setups, predictions, results, and updated understandings. Reviewing past logs fosters essential humility.

marsbit45m ago

How to Do Research Well: Deliberately Practice the Real Skills That Matter

marsbit45m ago

Following US Ban on Fable 5, Zhipu AI's Stock Soars 47%

On June 15th, shares of Zhipu AI surged dramatically on the Hong Kong stock market, peaking at a 47.6% gain before closing 32.82% higher. This sharp increase was directly triggered by two recent industry events. On June 12th, Anthropic announced it was suspending global access to its latest flagship models, Claude Fable 5 and Claude Mythos 5, to comply with a U.S. government export control order. The next day, Zhipu AI announced it would open access to its latest open-source flagship model, GLM-5.2, under the permissive MIT license. The Anthropic incident highlighted a critical issue beyond raw model capability: the risk of sudden, unpredictable loss of access to advanced AI models, especially for developers and enterprises deeply integrated with them. This has shifted industry and market focus toward factors like stability, sustainable access, and controllability. Zhipu's move, promoting "frontier intelligence for all," positions its openly available model as a reliable and accessible alternative. The GLM-5.2 model emphasizes "Long Horizon Task" capabilities with a 1M context window, targeting complex, multi-step coding and engineering workflows where maintaining context is crucial. Analysts note this event exposes the risk of dependency on closed-source models subject to single jurisdictional controls, potentially accelerating a shift toward domestic base models and localized deployments. The market's reaction signals a new valuation dimension in AI: providers who can offer stable, long-term, and sustainably accessible AI capabilities are gaining strategic importance.

marsbit1h ago

Following US Ban on Fable 5, Zhipu AI's Stock Soars 47%

marsbit1h ago

Fully Entering the AI Era: Alipay Bets on Conversation, WeChat Holds Fast to Social

In May 2026, Alipay announced over 300 million AI payment transactions. Shortly after, WeChat opened its mini-programs for AI integration, sparking controversy by requiring developer source code access. This highlights their diverging approaches to AI integration. Alipay is testing "Project Treasure," an optional AI-native interface replacing traditional app grids with a conversational window. Users can command complex tasks (e.g., "book a ride and order coffee") handled end-to-end by AI. This shift follows an abandoned standalone AI app, focusing instead on enhancing its existing user base. For unmodified mini-programs, Alipay's AI uses "screen-reading" to simulate user interactions, bypassing the need for developer overhaul. It also introduced "Token Pay" for micro-transactions and "AI Wallets" for autonomous agent spending. WeChat, prioritizing its core social function, is taking an embedded approach. Its AI agent will operate within existing contexts like group chats and official accounts, assisting without a separate interface. To enable this, WeChat offers developers two paths: granting source code access for direct AI control ("Automatic Mode") or manually encapsulating services into standardized "Skills." Both place significant burden on developers. Key differences emerge in handling legacy services: WeChat demands developer cooperation (code or labor), while Alipay's screen-reading offers immediate, if potentially less stable, compatibility. Alipay's 3 billion AI transactions demonstrate user acceptance of AI-driven commercial actions. The divergent strategies may reshape mini-program ecosystems—Alipay passively "AI-fying" services, WeChat potentially favoring resource-rich developers—and set competing technical standards. Ultimately, the competition centers on where users entrust the command to "help me get things done."

marsbit1h ago

Fully Entering the AI Era: Alipay Bets on Conversation, WeChat Holds Fast to Social

marsbit1h ago

Trading

Spot
Futures

Hot Articles

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 S (S) are presented below.

活动图片