Standard Chartered, Coinbase deepen alliance to build institutional crypto infrastructure

cointelegraphОпубліковано о 2025-12-14Востаннє оновлено о 2025-12-14

Анотація

Standard Chartered and Coinbase have expanded their partnership to build crypto infrastructure for institutional clients. The collaboration will explore offerings across trading, prime services, custody, staking, and lending. The partnership combines Standard Chartered’s banking and custody expertise with Coinbase’s institutional crypto platform to develop secure, compliant digital asset services. This builds on their existing relationship in Singapore, where Standard Chartered provides real-time SGD transfers for Coinbase. Separately, the US OCC conditionally approved national trust bank charters for five crypto-related firms, including BitGo, Fidelity, Paxos, Circle, and Ripple. Coinbase is also expected to announce new products soon.

Standard Chartered and Coinbase have expanded their partnership to build crypto infrastructure for institutional clients.

As part of the partnership, the duo will explore offerings across trading, prime services, custody, staking and lending, the British multinational bank announced on Friday.

“We aim to explore how the two organisations can support secure, transparent and interoperable solutions that meet the highest standards of security and compliance,” Margaret Harwood-Jones, global head of financing and securities services at Standard Chartered, said.

The two firms said the partnership combines Standard Chartered’s cross-border banking and custody expertise with Coinbase’s institutional crypto platform. The goal is to develop an integrated suite of services that allows institutions to trade and manage digital assets within a secure and compliant framework.

Related: Coinbase opens Solana DEX access as CeFi and DeFi converge

Standard Chartered, Coinbase build on Singapore partnership

The announcement builds on an existing relationship in Singapore, where Standard Chartered already provides banking connectivity for Coinbase, enabling real-time Singapore dollar transfers for the exchange’s customers.

Last year, Crypto.com also partnered with Standard Chartered to roll out global retail banking services that allow users in more than 90 countries to deposit and withdraw US dollars, euros and UAE dirhams through its app.

Meanwhile, Coinbase is set to announce new products next week that could include prediction markets and tokenized stocks.

Related: Pantera, Coinbase back Surf’s $15M push to build crypto-native AI models

Bank regulator clears path for crypto trust banks

On Friday, the US Office of the Comptroller of the Currency conditionally approved national trust bank charter applications for five companies linked to the digital asset sector.

The approvals cover BitGo, Fidelity Digital Assets and Paxos, which plan to convert existing state-chartered trust companies into national trust banks, as well as new applicants Circle and Ripple.

Magazine: 2026 is the year of pragmatic privacy in crypto — Canton, Zcash and more

Пов'язані питання

QWhat is the main focus of the expanded partnership between Standard Chartered and Coinbase?

AThe main focus is to build crypto infrastructure for institutional clients, exploring offerings across trading, prime services, custody, staking, and lending.

QHow does the partnership leverage the strengths of both Standard Chartered and Coinbase?

AIt combines Standard Chartered's cross-border banking and custody expertise with Coinbase's institutional crypto platform to develop secure and compliant digital asset services.

QWhat existing relationship did Standard Chartered and Coinbase have in Singapore prior to this announcement?

AStandard Chartered already provides banking connectivity for Coinbase in Singapore, enabling real-time Singapore dollar transfers for the exchange's customers.

QWhat other major crypto exchange has Standard Chartered partnered with recently, and what service did they provide?

AStandard Chartered partnered with Crypto.com to roll out global retail banking services allowing users in over 90 countries to deposit and withdraw US dollars, euros, and UAE dirhams.

QWhat significant regulatory development for crypto companies was announced on the same day?

AThe US Office of the Comptroller of the Currency conditionally approved national trust bank charter applications for five digital asset companies: BitGo, Fidelity Digital Assets, Paxos, Circle, and Ripple.

Пов'язані матеріали

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

This article introduces a novel training paradigm for generative models called Explorative Modeling (XM), which enables true end-to-end training. Traditionally, powerful generative models like autoregressive and diffusion models are not trained end-to-end. They are trained to predict a single small step but require iterative multi-step sampling for inference. This "exposure bias" leads to error accumulation and limits performance. The core challenge XM addresses is "mode blurring." In generative tasks, a single input (e.g., "generate a dog") corresponds to many valid outputs (multiple modes). Standard training objectives like reconstruction loss force the model to average these modes, producing unrealistic, blurry outputs. To avoid this, existing models break generation into many small, almost deterministic steps, sacrificing end-to-end training. XM tackles this by restructuring the training loop itself. Its key insight is to amplify "generative expressivity." For each training input, instead of generating one sample, the model generates K candidate outputs. Only the candidate closest to the real data is used for computing the loss and updating the model via backpropagation. This simple "best-of-K" mechanism is implemented as a short for-loop. By exploring multiple possibilities, the model learns to distribute its guesses across different modes rather than collapsing to their uninformative average. The paper demonstrates that "exploration" acts as a new, powerful scaling axis. Gains from XM increase with model size, data scale, and compute. Experiments show improvements in FID scores for image generation and significant efficiency gains, sometimes outperforming larger models without exploration. When pushed to the limit, XM enables fully single-step, end-to-end generative models. In robotics tasks, an "Explorative Policy" matched the performance of a 100-step Diffusion Policy with a single forward pass, drastically improving inference speed. While the best-of-K concept is not entirely new, the authors' contribution lies in formally understanding it as a direct method to boost generative expressivity without fragmenting the generation process. This work suggests that as models scale, enhancing exploration during training may become crucial for overcoming fundamental performance bottlenecks.

marsbit50 хв тому

Can Generative Models Finally Be Trained End-to-End? The Core Is a For Loop

marsbit50 хв тому

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

The AI boom is facing an unexpected bottleneck: a severe shortage of skilled construction workers and electricians. As tech giants like Meta, OpenAI, and Alphabet race to build massive data centers—such as OpenAI's $16 billion "Stargate" project—they are hitting a critical labor wall. The U.S. needs an estimated 130,000 more electricians, 240,000 construction workers, and 150,000 supervisors by 2030 for AI infrastructure alone, but tens of thousands of electrician jobs go unfilled each year. While AI companies offer high premiums, with electricians earning up to $280,000 annually, worker scarcity still causes massive losses—delays on a single project can cost $14.2 million per month. The complexity of building AI data centers, which require immense power (equivalent to powering hundreds of thousands of homes), sophisticated electrical systems, and advanced liquid cooling solutions, demands highly skilled technicians who are in short supply. To combat this, companies are investing heavily in training. Meta has committed $115 million to a free training school offering tuition, housing, and stipends, targeting 5,000 new workers. OpenAI is partnering with unions to secure skilled labor. These efforts are paying off, with a significant rise in Gen Z interest in trade schools over college. However, the power demands are staggering. AI data centers are driving a rapid surge in electricity consumption, projected to account for up to 12% of U.S. power use by 2028 and raising costs for consumers. Furthermore, the construction boom is project-based, leading to a potential future glut of trained workers once building peaks, which could depress wages industry-wide. The race for AI supremacy now depends as much on skilled hands as on advanced chips.

marsbit2 год тому

Annual Salary of Millions Competing for Electricians, Meta Rushes to Open Its Own Technical School

marsbit2 год тому

Торгівля

Спот
活动图片