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ECB Moves To Build Unified European Market For Tokenised Assets

by News Editor

The European Central Bank is moving to build a unified European market for tokenised assets, warning that incompatible digital platforms could deepen fragmentation across Europe’s capital markets.

Speaking at a Deutsche Bundesbank symposium in Frankfurt, ECB Executive Board member Piero Cipollone said the central bank had moved from developing a vision for tokenised finance to implementation through its Pontes and Appia projects.

Tokenisation Could Reshape Financial Markets

Distributed ledger technology (DLT) could make financial markets more efficient by allowing assets to be represented as programmable digital records and transferred around the clock with greater automation.

Europe’s financial infrastructure remains fragmented, with 31 central securities depositories, 14 central counterparties and 323 trading venues. More than 95% of securities transactions by volume and value were settled between parties within the same central securities depository in 2023, according to Cipollone.

Tokenisation could bring issuance, trading, clearing, settlement, custody and asset servicing into a more integrated digital environment. Smart contracts could also automate processes such as coupon payments, collateral transfers and compliance checks.

Tokenised Finance Moves Toward Wider Adoption

Global adoption is beginning to accelerate. Tokenised traditional assets recorded on public blockchains increased roughly fivefold between March 2025 and March 2026, Cipollone said.

In the U.S., one private platform processed an average of $354 billion in tokenised repo transactions per day in March 2026, four times its average daily volume a year earlier. European institutions are also developing tokenised bonds, deposits, collateral and settlement solutions.

The Eurosystem began accepting marketable assets issued through DLT-based services as eligible collateral at European central securities depositories in March. Despite that progress, tokenised real-world assets remain small compared with global financial markets and continue to face limited liquidity and secondary-market activity.

ECB Wants Central Bank Money At The Core

Cipollone identified fragmentation, the loss of central bank money as a settlement anchor and excessive dependence on external infrastructure as three key risks for Europe.

More than 50 Eurosystem trials and experiments involving 64 market participants in 2024 showed that central bank money could be used to settle transactions on DLT platforms. The ECB said the work confirmed that access to central bank money is a key condition for tokenised finance to develop safely and at scale.

“Central bank money does not carry credit or liquidity risk. What’s more, it serves as the common settlement anchor across the financial system,” Cipollone said.

Pontes And Appia Set The Framework

Pontes is designed to connect market-based DLT platforms with the Eurosystem’s TARGET Services, allowing the cash leg of transactions to settle in central bank money. The ECB plans to launch the service in September 2026, with operating hours eventually expanding and a 24/7 service planned by mid-2028.

Appia focuses on the broader architecture and governance of a European tokenised financial ecosystem. Its roadmap covers interoperability standards, collateral management, cross-border transactions, tokenised central bank money and the legal and regulatory framework. The ECB aims to produce a blueprint for the ecosystem by 2028.

The two projects are designed to work together. Pontes provides the near-term settlement infrastructure, while Appia addresses the longer-term architecture, standards and governance needed for an integrated market.

Common Standards Will Determine Success

Cipollone said successful expansion will depend on common standards and interoperability, cooperation between public and private sectors, and an integrated legal framework.

“Competition should be in services, quality and price, not through incompatible standards or walled gardens,” he said.

Technology alone will not eliminate fragmentation. European rules also need greater clarity on ownership rights, settlement finality, liability, custody, asset servicing and the enforceability of smart-contract outcomes.

“Technical interoperability without legal compatibility will remain incomplete and fail to overcome fragmentation,” Cipollone said.

For the ECB, the objective extends beyond modernising settlement. Coordinated infrastructure, common standards and a compatible legal framework could help create a more integrated and competitive European capital market.

Google’s Gemini Has A Branding Problem As AI Apps Grow More Complicated

by News Editor

Google’s latest Gemini update highlights a broader problem in consumer AI: companies are increasingly turning internal tools and capabilities into separate products that users must learn to navigate.

In its announcement of new Gemini Live voice features, Google said users should not have to determine whether a task requires Spark, Daily Brief or a simple inbox search. Yet those are precisely the distinctions the Gemini app currently asks users to make.

Too Many Features, Too Many Names

Gemini users can switch between Chat, Spark and Daily Brief, each with its own icon and place in the app. Rather than simplifying the experience, the growing list of branded features risks making the underlying technology more visible than it needs to be.

Daily Brief illustrates the problem. Google describes it as a source of personalised, proactive updates based on information from services such as Gmail and Calendar. In practice, however, some of its suggestions can feel less like useful assistance and more like unsolicited reminders about previous searches or unfinished research.

Spark has almost the opposite problem. The feature can act as an AI agent capable of completing tasks on a user’s behalf, but packaging that capability under a separate brand forces users to understand when and where they should use it.

A simpler approach would be to let users describe what they need and allow Gemini to determine whether a standard response, an agent or another capability is appropriate.

Gemini Is Not Alone

Google’s approach reflects a wider trend across the AI industry, where companies increasingly expose the architecture of their products through separate modes and branded features.

Anthropic, for example, asks users to distinguish between Claude’s standard chat experience and Cowork. ChatGPT similarly separates Chat and Work. For consumers, these distinctions can turn what should be a simple interaction into a question about which product or mode to use.

That approach is largely driven by how AI systems are built, rather than by how people naturally think about using them.

Apple Takes A Different Approach

Apple’s strategy for Siri offers a contrasting model. Rather than requiring users to learn a new AI interface, the company is integrating AI capabilities into tools people already use, including Spotlight, Photos, the camera and voice requests.

That approach could prove more effective as AI becomes a mainstream consumer technology. Users do not necessarily need to understand which model, agent or feature is handling a request; they simply need the system to complete the task.

Text-Based AI Offers A Simpler Model

The popularity of text-based AI assistants points in the same direction. Services such as Poke, Ollie, Lindy, Orchid, Lucas, Folk, Tomo and Instinct largely reduce the interaction to a familiar interface: send a message and let the assistant determine what needs to happen next.

That simplicity removes an additional layer of decision-making. Users do not need to choose between Chat, an agent or a specialised feature before asking for help.

As a16z investment partner Justine Moore recently argued, consumers increasingly want an AI assistant to feel like a contact they can message rather than another application they must learn.

For Google and its competitors, the challenge may therefore be less about adding capabilities and more about hiding the complexity behind them. The AI that wins mainstream adoption may ultimately be the one that asks users to understand the least.

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