Tokenization's Next Bottleneck Is Economics, Not Technology

Institutional tokenization is entering a more demanding phase.

The technical question — whether financial assets, money and market processes can be represented and operated on shared digital infrastructure — has largely been answered. Banks have tested tokenized deposits. Asset managers have launched digital funds. Issuers have placed bonds on distributed ledgers. Market infrastructures are experimenting with new models for settlement, custody and asset servicing.

The economic question remains less settled.

Can these models reduce the total cost of operating financial markets? Do they generate new and defensible revenues? Can they release liquidity or collateral without introducing new risks elsewhere? What level of adoption is required before the investment becomes worthwhile? And, crucially, which participants capture the value?

These questions are becoming central as institutions move from isolated pilots toward decisions about production, integration and scale.

The Intelligence Economy Institute's research points to a market divided between a relatively small operating core and a much larger pilot economy. In the latest Global Institutional Tokenization Benchmark, 609 institutions were reviewed, but only 14.6% met the evidence threshold for controlled production or a more advanced stage.

The market is therefore no longer constrained mainly by the ability to tokenize an asset. It is constrained by the ability to demonstrate that the resulting operating model is economically superior, institutionally viable and capable of scaling across participants.

That is the rationale for the IEI Tokenization Economics Lab.

Moving beyond the promise of efficiency

Tokenization is frequently associated with faster settlement, fewer reconciliations, programmable compliance, broader distribution, improved collateral mobility and more efficient asset servicing.

These benefits are possible, but they are conditional.

A faster settlement process may reduce counterparty exposure while increasing the need for more immediate liquidity. Automation may remove manual steps while creating new requirements around identity, wallet management, cybersecurity and operational resilience. Digital distribution may broaden access while adding costs for onboarding, servicing and integration.

The economic outcome depends on the complete operating model — not simply on the performance of the ledger.

It also depends on whether existing infrastructure can be retired. A tokenized process operating alongside the conventional system may initially increase costs through duplicated technology, controls, reconciliations and staffing. The anticipated benefits may only emerge when adoption reaches sufficient scale and legacy processes can be reduced.

This is why tokenization cannot be evaluated only through transaction speed, asset value or technical functionality. Institutions need to examine costs, revenues, liquidity, capital, risk, adoption and value distribution together.

They also need to compare the proposed tokenized model with credible alternatives. If the same result could be achieved through better APIs, standardized data or conventional process automation, the benefit should not automatically be attributed to tokenization.

A common language for tokenization economics

The Tokenization Economics Lab is being designed as both a public knowledge resource and a member management tool.

Its public layer allows institutions, policymakers and market participants to explore the principal economic dimensions of tokenization. Visitors can understand how changes in issuance, settlement, custody, distribution, collateral and servicing affect different participants across the financial value chain.

The objective is to provide a structured language for questions that are currently addressed inconsistently across institutions.

What is included in implementation cost? How should liquidity benefits be understood? When does operational efficiency become a realized saving? How should new revenues be separated from revenues migrated from an existing channel? How should transition costs and continuing legacy expenses be treated?

A shared taxonomy can make these questions easier to discuss across strategy, product, operations, treasury, risk and technology teams.

The Lab also connects economic analysis with established financial-market concepts and standards. This allows institutions to relate the business case to the underlying financial instrument, lifecycle, participants and operating architecture without creating another isolated vocabulary.

From analytical framework to management tool

For IEI members, the Lab goes beyond exploration.

Institutions can create private assessments of tokenization initiatives, document their assumptions, compare alternative operating models and update results as projects move from design to pilot and production.

The focus is on decisions rather than abstract scoring.

An institution assessing a tokenized fund, for example, could examine the economics of issuance, investor onboarding, transfer controls, distribution, custody, administration and redemption. A bank considering tokenized deposits could investigate implementation costs, payment volumes, liquidity requirements, balance-sheet effects, client adoption and potential revenue models. A market infrastructure could study how a new settlement model affects its participants as well as its own economics.

The tool is intended to support several management questions:

• Should the institution continue investing in the initiative?
• What scale is required for the model to become economically viable?
• Which assumptions have the greatest influence on the outcome?
• What additional evidence is required before a production decision?
• Which costs disappear, which remain and which are newly introduced?
• Are the anticipated benefits being realized after launch?
• Should the project be scaled, redesigned, partnered, paused or stopped?

Members can follow the evolution of a business case rather than treating it as a one-time document. Forecasts can become operating targets, and targets can subsequently be compared with observed results.

This makes the Lab relevant not only to innovation teams but also to executives allocating capital, product owners managing profitability, operations teams measuring performance, and treasury and risk functions evaluating liquidity, capital and exposure.

Understanding value across the ecosystem

One of the most important challenges in tokenization is that value creation and value capture are not the same.

A new infrastructure may create benefits across the market while generating an insufficient return for the institution expected to finance it. Faster settlement may benefit investors and counterparties more than the platform operator. Reduced intermediation costs may improve issuer economics while weakening the revenue model of an incumbent service provider.

A commercially sustainable system therefore requires more than positive aggregate value. It requires an allocation of costs, benefits and incentives that supports participation by the institutions on which the model depends.

The Tokenization Economics Lab helps members explore these interdependencies.

Rather than reducing a project to a single headline return, it provides a view of who invests, who incurs ongoing costs, who assumes risk, who receives new revenue and who benefits from operational improvement.

This can support consortium formation, infrastructure procurement, partnership design and commercial discussions. It can also reveal when an otherwise attractive project is blocked by an unresolved distribution of value.

Building institutional benchmarks

As more members contribute evidence, the Lab will support confidential comparison with relevant peer groups.

The purpose is not to produce public league tables or expose individual institutional results. It is to help members understand whether their operating outcomes, transition costs, adoption patterns and realized benefits are broadly consistent with comparable initiatives.

A member may discover that its technology costs are competitive but that onboarding remains unusually expensive. Another may find that its operational performance is strong but that transaction volume remains below the level required to support the platform. A consortium may identify that the system creates value but concentrates the costs on participants with the weakest incentives to invest.

These comparisons can help institutions distinguish project-specific problems from wider market constraints.

They can also create a collective learning mechanism. As more initiatives move into production, the evidence can improve understanding of which operating models scale, where benefits tend to emerge and which obstacles continue to prevent adoption.

Member information remains protected through controlled participation, aggregation and governance. The public experience explains the framework and demonstrates its uses, while institution-specific data and peer intelligence remain within the member environment.

A different kind of tokenization intelligence

The Lab complements the IEI Tokenization Monitor and Global Institutional Tokenization Benchmark.

The Monitor examines what institutions are doing, how initiatives are evolving and where production can be verified. The Economics Lab addresses a different question: whether those initiatives create sustainable economic value relative to the available alternatives.

Together, they provide a more complete view of institutional tokenization.

External market evidence helps institutions understand maturity, architecture and peer activity. Internal economic analysis helps them decide where to invest, how to design the operating model and what results to measure.

The combination is intended to move tokenization intelligence from observation toward execution.

The shift from experimentation to accountability

The next phase of tokenization will be shaped by a different standard of evidence.

Institutions will increasingly need to demonstrate more than technical feasibility or a successful transaction. They will need to show recurring usage, credible unit economics, operational resilience and a path to recovering investment.

Some tokenization initiatives will prove economically compelling. Others may remain strategically useful even before they generate a direct return. Some will require a different commercial model or broader market coordination. Others should be stopped because the underlying economics do not justify continued investment.

A rigorous management framework should make all four outcomes possible.

The Tokenization Economics Lab is intended to help institutions replace generalized expectations with structured decisions: where tokenization creates value, under what conditions, for which participants and with what evidence.

The long-term opportunity is not simply to measure a new technology. It is to build a shared body of operating intelligence for the emerging tokenized economy.

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The framework, the full metric dictionary and a fully worked case are open to everyone. Institutions interested in contributing to the development of the framework, participating in the initial research and benchmarking cohorts, or accessing the Lab as IEI members can contact the Intelligence Economy Institute or request a membership walkthrough.