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JPMorgan Chase has launched a product called a “deposit token” that will serve as a digital representation of commercial bank money and will be available only to the bank’s institutional clients. The tokens, known as JPMD, are minted by JPMorgan and transmitted to participating institutional clients, including Coinbase, via smart contract transactions on the Base network. At all times, each unit of JPMD is fully backed by a corresponding fiat deposit, ensuring parity between on-chain representation and off-chain liability. The JPMD launch marks the first time a major commercial bank has deployed deposit-based products on a public blockchain, but the timing isn’t coincidental. Though modest in immediate scale, being entirely in-house, J.P. Morgan’s deposit token pilot provides insight into how large financial institutions may navigate the evolving demands of settlement efficiency, regulatory compliance, and market participation in a tokenized environment. Against the backdrop of regulatory and marketplace momentum in the U.S., it is increasingly evident that the architecture of digital finance may not be defined solely by startups and technologists. Large, regulated institutions are increasingly not merely adapting to this evolution; but they are beginning to shape it in their own image. Other major banks such as Bank of America, Citigroup, Wells Fargo and others, have reportedly been in talks to launch joint stablecoins or tokens. JPMorgan’s early move positions it as the first among equals. Although, as the bank stresses, JPMD is a deposit token and not a stablecoin. At a technical level, the JPMD token is conceived as a digital representation of U.S. dollar deposits held at JPMorgan. These tokens are issued in direct correspondence with balances in client accounts and are not free-floating or algorithmically stabilized. JPMorgan’s strategic intent appears twofold. First, by utilizing a regulated deposit token rather than a conventional stablecoin, JPMorgan is aiming to preserve the structural rigor of traditional commercial banking within a digital framework. Second, the decision to conduct the pilot on Base, a Layer 2 Ethereum-compatible network operated with institutional oversight mechanisms, may suggest a cautious but deliberate attempt to balance interoperability with control.

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The Securities and Exchange Commission (SEC) posted a memo detailing a meeting between its Crypto Task Force and JP Morgan. While the task force primarily handles cryptocurrency issues, it also oversees tokenization matters that increasingly affect traditional finance (TradFi) companies. JP Morgan’s meeting agenda revealed three key discussion points: an overview of its existing digital finance services including repo solutions and debt platforms, analysis of how capital markets activity might migrate to public blockchains, and plans for future regulatory engagement. The discussion likely centered heavily on tokenized collateral, an area where multiple regulators are actively involved. The CFTC is currently running tokenized collateral pilots for derivatives margin posting, and the DTCC is launching its own platform. The CME is also participating in this space. Tokenization offers a solution by allowing institutions to transfer tokenized securities directly to meet margin requirements without selling underlying assets. JP Morgan’s recent announcement of JPMD deposit tokens on the Base public blockchain further addresses cash collateral needs, providing an alternative to stablecoins. The bank already operates a tokenized collateral solution on its permissioned blockchain, Kinexys, alongside an intraday repo solution called Digital Financing and a bond issuance platform called Digital Debt Services. However, using permissioned blockchains creates integration challenges that public blockchains can ease.

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Citigroup’s Jane Fraser is on a mission to modernize the global bank. Three executives have been appointed to ensure AI plays a big role in that. As part of the push, the firm — which has long struggled with its reputation issues, some of which are directly tied to tech — said it’s unveiling new tools, pilot programs, and a broader effort to embed AI across its operations. The internal memo, which went out to Citi’s roughly 200,000 employees, reveals the scope and ambition of the bank’s AI efforts, which will be overseen by new co-sponsors of Citi’s AI strategy, who are part of the Executive Management Team, include Gonzalo Luchetti, head of US personal banking; Tim Ryan, head of technology and business enablement; and Anand Selva, the firm’s chief operating officer. “We are focusing on accelerating our AI strategy—connecting teams and partners, prioritizing resources and expediting use cases across our businesses and functions,” the three leaders. To realize the push, the bank will rely on some of its $12 billion annual tech budget, though it’s unclear how much is specifically dedicated to AI. But it comes as much of Wall Street, from JPMorgan to Goldman Sachs, races to integrate the technology into everything from consumer service to trading to internal operations. “AI is reshaping how we operate, serve our clients and scale our business,” they added. “We firmly believe that to be competitive in this digital evolution, we must be an AI-ready workforce—nimble and ready for what this technology can unlock.” They explained that Citi is scaling its generative AI capabilities across the company, with more than

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U.S. Bank recently launched two new products to its SMB offering: a spend management platform as well as an all-in-one checking account called Business Essentials that will help SMBs accept card payments with same-day access to funds. It also comes with a free mobile card reader, no maintenance fees, and the ability to integrate a business’ accounting into budget management software. These products are a result of a years-long strategy at US Bank that combines fintech acquisitions, like that of Bento Technologies which the firm acquired in 2021, with internal innovation to build products that can serve SMBs holistically and at scale.  The Bento Technologies acquisition came as a part of the bank’s vision to bring banking and payment services into an interconnected ecosystem focused on simplifying cash flows and management for SMBs, says Shruti Patel, Chief Product Manager for Business Banking at the firm. Fintech acquisitions allow US Bank to plug capabilities into their systems that might have otherwise taken them years to build but there is always a risk of integrations leading to a choppy and fragmented experience for customers. US Bank was able to avoid this by keeping the main thrust of integration efforts aligned with and optimized for customer experience.  The bank’s recent spend management tool is a result of teams like business banking, payments, IT,  project teams, as well as the employees who joined from Bento owning the build regardless of where they were based in the country.  “Team members were located everywhere from San Francisco to Minneapolis to Chicago. It was a real cross-bank collaboration,” she said.  Banks need to integrate generative AI into their SMB spend management and cash flow tools to compete with fintech innovations like Lili’s Accountant AI, as small business owners increasingly use AI for content creation, data analysis, and marketing strategies while seeking faster answers and more efficient business execution. The possibilities for banks are massive: Integrating Gen AI in bank-offered spend management and cash flow management tools can help SMB owners get answers faster and execute business plans more efficiently. More broadly, CX is trending towards enabling a higher level of automation, where jobs to be done are executed by Gen AI and monitored by employees. Banks have yet to catch up onto this change and their movement is likely to be the same slow and deliberate gait we have seen in years past but it doesn’t mean that the C-suite is sleeping on this innovation. iIt’s just prioritizing the back office: “We are incorporating AI into our own operations and in innovations that benefit clients. For example, to make our interactions with customers as frictionless as possible, our customer service teams use AI for call transcriptions, knowledgebases that give the representatives quicker access to the information they need, and personalized product recommendations. We’re exploring a number of ways to use AI, including investing in our own data and technology infrastructure so we can deploy AI at speed and scale. We will continue to look at innovations that can help our clients save time and money and improve their operations,” said Patel.

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• Celent, now part of GlobalData, recognises 17 model banks and declares JP Morgan Chase as the overall model bank of the year.. JP Morgan Payments launched several concurrent initiatives that markedly improved its end-to-end payments and treasury services, driving business value for corporate clients and ecosystem partners. Specifically, the bank is recognised for the success of four initiatives, namely:
• Payments Development Portal: a strategic digital platform to connect developers with JPM’s payments infrastructure.
• Integrated Solutions Plugin: an embedded banking solution integrating popular middle-market resource planning systems.
• API Multibank Reporting: a reporting product that recognises multibank reporting by using the API connectivity channel to retrieve information from non-JPM accounts.
• Cash Flow Intelligence: an AI-driven analytics and cash forecasting solution providing visibility into clients’ cash flows.
• The 2025 Model Bank programme attracted 140 nominations from around the world. Every region was well represented with the nominations well balanced across all asset tiers. Of the 18 winning banks, six are headquartered in the US and three in Canada. India and the UK each have two winners with institutions from the Philippines, Chile, Brazil, Vietnam and Romania also recognised. A common theme across all categories is the winning banks success in combining technology, talent, and processes to modernise platforms, enhance customer value, and lead with impact

 

https://www.retailbankerinternational.com/news/celent-reveals-2025-model-banks/

• Bank of America: Award for the Edge in Actionable Analytics: Celent selected Bank of America’s CashPro Data Intelligence for this year’s Model Bank Award for developing an Edge in Actionable Analytics. The bank has demonstrated a commitment to engage with its corporate client community and develop self-service, rich data and analytics tools that help all corporate clients meet their working capital and operational goals.
• Bank of Montreal: Award for Payments Innovation: BMO is recognised for six recent initiatives spanning the entire client lifecycle, from sales and onboarding to servicing and support. The six initiatives address specific client pain-points around payments and were executed with care and attention, and collectively merit recognition.
• Citi: Award for Corporate Integration. Citi launched a new unified API and integration experience, Citi Developer Portal, delivering innovation across client experience, operational efficiency, and business impact, earning the bank the 2025 Celent Model Bank Award for Corporate Integration. According to Celent, Citi’s Developer Portal initiative highlights the importance of adopting a client-first approach, designing solutions based on how clients experience Citi as a single entity, rather than developing within traditional product silos. It also demonstrates the bank’s commitment to delivering a world class developer experience while helping clients accelerate time-to-value with scalable, more secure, and user-friendly integration options. By combining self-service design, embedded certificate provisioning, pre-built integrations, and a solution-oriented marketplace, the portal sets a high standard for enterprise API platforms in the financial industry and demonstrates a clear understanding of client pain points.
• Citizens Bank: Award for Technical Onboarding Excellence: The bank’s MTF platform was approaching end of life, along with its underlying software and infrastructure. Its age was causing many challenges, not least that the platform was failing to meet the bank’s functional, business, customer, resilience, and security needs. There was also a recognition that the bank would also need to prepare for widespread ISO 20022 adoption. The customer onboarding and file testing processes were a major pain point. They were inefficient and time-consuming, and reliant on excessive back-and-forth communication, creating lengthy, frustrating customer experiences. Citizens Bank implemented a robust, next-generation, cloud-based business integration platform from SEEBURGER that was flexible, scalable, secure, and resilient as well as provided traditional secure file transfer capabilities.
• TD Bank: Award for Customer Centred Innovation in Business Banking. Celent recognises TD’s Small Business Dashboard and Tap to Pay on iPhone as representing exceptional discovery of distinct customer needs and innovation. The bank leveraged consumer-digital technologies to deliver truly impactful solutions for small business clients. Partnerships with proven third party solution providers combined to form a complimentary offering producing strong results. The bank took a customer-centric approach to product design that included extensive research to identify specific pain points experienced by its small business clients. In addition, the bank pursued an early-adoptor position in the area of payments technology, where it knew it would have difficulty playing catch up later.
• Wells Fargo: Award for Step Change in Corporate Digital Banking. Wells Fargo Vantage, the bank’s next-generation digital banking platform, is recognised for delivering a dynamic, persona-driven experience tailored to business clients’ unique needs, including industry, size, operational context, and lifecycle. As a result, Vantage can support companies that range from start-ups to multinationals with complex workflows—all in one platform. The project was highly complex and involved integrating 65 fragmented systems with a modular, scalable framework using advanced technologies like micro-frontends, APIs, AI/machine learning, and GraphQL. Celent recognises the bank’s success in delivering across all the critical dimensions of digital banking transformation: acting on the voice of the customer and selecting and implementing the most effective advanced technologies.

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New research at MIT suggests that could be the case. A new report from the university’s Sloan School of Management covers some of MIT’s studies involving agentic AI, including an exploration into how these digital entities can be trained to reason and collaborate more like humans. For example, a new paper co-authored by Matthew DosSantos DiSorbo and researchers Sinan Aral and Harang Ju presented both people and AI with the same scenario: You need to purchase flour for a friend’s birthday cake using $10 or less. But at the store, you discover flour sells for $10.01. How do you respond? 92% of the people given this question proceeded to buy the flour. But AI models, spread across thousands of iterations, chose not to buy, concluding the price was too high. “With the status quo, you tell models what to do and they do it,” Ju said. “But we’re increasingly using this technology in ways where it encounters situations in which it can’t just do what you tell it to, or where just doing that isn’t always the right thing. Exceptions come into play.” The researchers found that providing models with information about both how and why humans opted to purchase the flour — essentially giving them insight into human reasoning — corrected this problem, giving the models a degree of flexibility. The AI models then made decisions like people, justifying their choices. The models were able to generalize this flexibility of mind to cases beyond purchasing flour for a cake, like hiring, lending, university admissions, and customer service.   

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Fivetran released new research showing that 49% of enterprise technology leaders believe their current data architecture can handle the demands of AI. At the same time, 89% say they plan to use proprietary data to train LLMs this year. The disconnect highlights how quickly companies are pushing forward with AI, even as they acknowledge their data systems aren’t ready. 68% said they rely on 50 or more data sources to support decision-making, and more than a third cited integration complexity as a major hurdle. Others pointed to scalability limitations (34%) and security and compliance risks (33%) as top concerns. Half of the executives surveyed said their organizations plan to invest $500,000 or more in data integration over the next year. Their focus areas include reducing manual pipeline maintenance, improving real-time access to data, and ensuring data quality and governance. Still, challenges remain. 45% reported a lack of automation or self-service capabilities, 44% said legacy systems and implementation costs were holding them back, and 41% pointed to talent gaps on their data teams. The report also shows how the role of the technology leader is shifting, with 48% expecting to take on more responsibility for data privacy and compliance, and 45 percent anticipating a larger role in company-wide data strategy. Some organizations are already seeing results. Key findings include: 89% of tech leaders plan to use proprietary data to train LMMs this year, but only 49% believe their architecture can support AI workloads; 68% say they rely on 50 or more data sources to support decision-making; 64% of CIOs have delayed innovation efforts due to compliance concerns; 50% plan to invest $500,000 or more in data integration in the next year; Nearly half of respondents expect to take on more responsibility for privacy, compliance, and company-wide data strategy.

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