Oobit, Backed by Tether, Expands to Crypto-to-Bank Transfer

TheNewsCryptoPublished on 2026-02-25Last updated on 2026-02-25

Abstract

Oobit, a cryptocurrency payment application backed by Tether, has expanded its services by launching a crypto-to-bank transfer function. This feature allows users to move funds from self-custody wallets directly to bank accounts using domestic payment networks. It currently supports major fiat currencies including the US Dollar, Euro, Philippine Peso, and Mexican Peso, and works with cryptocurrencies such as Bitcoin, Ethereum, Solana, XRP, Cardano, and stablecoins like USDT and USDC. According to CEO Amram Adar, this service differentiates itself from traditional off-ramp providers by keeping all core aspects—including user relationships, transaction experience, and wallet custody—within Oobit’s ecosystem. Transfer limits range from approximately €10 to $50,000, with fees including a fixed $1 or 1% transaction charge, plus a 0.5% spread on conversions to US Dollars. The move aims to enhance seamless fund movement and strengthen Oobit's position in the competitive crypto payments market.

Oobit, a crypto payment application, has announced the roll out of the crypto-to-bank transfer functionality. This builds on the existing offering to its users, gaining an edge in the competitive market while remaining different from traditional off-ramp providers. Backed by Tether, Oobit has provided additional crucial information to clarify details about the function.

Crypto-to-Bank Transfer by Oobit

Oobit has announced the expansion of in-store spending and peer-to-peer transfers. The payment app has said that it will now offer the crypto-to-bank transfer functionality by connecting self-custody wallets to local banks. Essentially, the feature moves funds into bank accounts using domestic payment networks.

The new function of Oobit currently supports the US Dollar, euros, Philippine pesos, and Mexican pesos. Supported networks include the Automated Clearing House (the US), Single Euro Payments Area (Europe), and SPEI Network (Mexico).

Supported cryptocurrencies cover Ethereum, Bitcoin, Solana, XRP, and Cardano. This is in addition to stablecoins, namely USDC, USDT, EURR, and EURC, along with Dogecoin, a meme coin.

Oobit CEO Amram Adar Speaks

The CEO of Oobit, Amram Adar, interacted with the media. Amram clarified that the new functionality was different from traditional off-ramp providers as it would keep every core aspect within the ecosystem. Critical elements cover end-user relationship, transaction experience, and wallet custody.

He added that funds of users would be held in the native wallet infrastructure until a bank transfer is initiated. Simply put, every action pertaining to the crypto-to-bank function of Oobit will remain well-within the boundaries of the ecosystem.

Community members have reacted to the development. Some of them have pointed out that it is more about the rails and not just about the application. A few said that the focus is more on seamless movement and settlement of funds.

Information About App Backed by Tether

Oobit has, however, fixed a few criteria around the transfer process. The minimum amount has to be around 10 euros, or $11.70. The maximum limit can go as high as $50,000. The fee structure is a fixed $1 charge or a transaction fee of 1%. This is on top of a 0.5% spread, which applies to the conversion from crypto to the US Dollar.

Distributed Technology Research, or DTR, imposes a fixed fee in the range of 65 cents and 2 euros. Alternatively, it can take a fee based on a percentage between 0.65% and 1%, based on the currency in question. The launch of crypto-to-bank functionality by Oobit has reportedly given it an edge over its competitors in the market.

Highlighted Crypto News Today:

AI Cryptos Soar as the Artificial Intelligence Sector Eases with Wall Street

TagsCryptoTether

Related Questions

QWhat new functionality has Oobit announced for its crypto payment application?

AOobit has announced the roll out of the crypto-to-bank transfer functionality, allowing users to connect self-custody wallets to local banks and move funds into bank accounts using domestic payment networks.

QWhich fiat currencies and cryptocurrencies are supported by Oobit's new transfer service?

AThe service supports the US Dollar, euros, Philippine pesos, and Mexican pesos. Supported cryptocurrencies include Bitcoin, Ethereum, Solana, XRP, Cardano, as well as stablecoins USDC, USDT, EURR, EURC, and the meme coin Dogecoin.

QHow does Oobit's CEO, Amram Adar, differentiate the new feature from traditional off-ramp providers?

AAmram Adar clarified that Oobit's functionality keeps every core aspect within its own ecosystem, including the end-user relationship, transaction experience, and wallet custody, unlike traditional off-ramp providers.

QWhat are the fee structures and transfer limits for Oobit's crypto-to-bank service?

AThe minimum transfer amount is around 10 euros or $11.70, and the maximum limit is up to $50,000. Fees include a fixed $1 charge or a 1% transaction fee, plus a 0.5% spread for conversion from crypto to US Dollar.

QWhich company backs the Oobit payment application, as mentioned in the article?

AOobit is backed by Tether, the company behind the USDT stablecoin.

Related Reads

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

US banking trade groups are urging revisions to the stablecoin yield compromise in the upcoming CLARITY Act ahead of a key committee markup. The Act currently aims to ban all passive, deposit-like interest on stablecoins to prevent competition with traditional bank savings, while allowing rewards tied to active uses like staking or transactions. In a letter, groups including the American Banking Association and Bank Policy Institute proposed stricter language to eliminate perceived loopholes for passive yield and prevent deposit flight from banks. However, these efforts are reportedly viewed as minor by some lawmakers. The Senate Banking Committee is scheduled to mark up the bill on May 14, a critical step before it can advance through Congress.

bitcoinist10h ago

CLARITY Act: Banking Trade Groups Push For Yield Agreement Revision – Details

bitcoinist10h ago

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

Finance CEO Raoul Pal prefers Solana over Bitcoin, citing its high throughput and low transaction costs as better suited for the future crypto-AI era. He believes Solana is ideal for machine-to-machine microtransactions and AI-driven DeFi activity, predicting AI agents will soon dominate DeFi users. While Bitcoin serves as a store of value, Pal sees higher growth in networks built for mass, automated transactions. This view was highlighted at Consensus 2026, where AI integration and crypto infrastructure were key themes.

bitcoinist10h ago

This Finance CEO Picks Solana Instead Of Bitcoin — Here’s Why

bitcoinist10h ago

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.

marsbit11h ago

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

marsbit11h ago

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.

marsbit13h ago

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

marsbit13h ago

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.

marsbit13h ago

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

marsbit13h 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