TL;DR: Tokenized finance infrastructure does not have a single optimal blockchain, because financial institutions must trade off cost volatility, throughput, finality, contagion risk, illicit exposure, and governance, according to Chainalysis. The operational lesson is that chain selection is a control decision, not a branding exercise: settlement risk, compliance monitoring, and custody concentration all shape the right answer.
At a glance
What this is: NHI Mgmt Group's analysis, drawing on Chainalysis's research: Tokenized finance infrastructure must be chosen by asset and operating model, because different blockchains optimise for different trade-offs across cost, speed, finality, concentration, and compliance.
Why it matters: IAM, PAM, and broader governance teams should treat chain choice as part of the control plane for tokenized assets, because custody, monitoring, and settlement risk shift with the selected network.
By the numbers:
- Stablecoin volume is projected to reach $1.5 quadrillion by 2035, reframing infrastructure decisions as long-term governance choices.
Context
Tokenized finance does not fail because there is too much blockchain choice. It fails when organisations assume one network can serve every asset class, every settlement model, and every compliance requirement without trade-offs. For institutions, the real question is how to align chain properties with the controls that govern settlement, custody, monitoring, and operational resilience.
This article is strongest where it separates infrastructure characteristics that are often conflated: predictable cost versus low cost, throughput versus finality, and liquidity depth versus concentration risk. That distinction matters for governance because each property changes the control assumptions behind tokenised assets, especially when regulated institutions move from pilots to live deployments.
The identity and access angle is indirect but real: once tokenized assets move into production, custody concentration, delegated access, and monitoring scope become part of the security model, not just the product architecture.
Key questions
Q: What breaks when tokenized assets are placed on the wrong blockchain?
A: The main failure is control mismatch. A network can be technically functional but operationally wrong if its fee behaviour, settlement finality, or concentration profile does not fit the asset. That creates avoidable cost volatility, settlement uncertainty, and dependency risk that governance teams only see after deployment.
Q: Why does custody concentration increase risk in tokenized finance?
A: Custody concentration turns one participant’s failure into a system-wide event. If one exchange or custodian dominates holdings or liquidity on a network, a hack, run, or insolvency can propagate into the broader ecosystem. That is why concentration analysis belongs in infrastructure governance, not only in counterparty reviews.
Q: How can institutions tell whether a blockchain is suitable for regulated settlement?
A: They should test whether the network provides hard finality, predictable operating costs, and enough liquidity depth without excessive dependency on a single intermediary. If any of those controls are weak, the network may still be fine for some tokenization use cases but not for high-value regulated settlement.
Q: What should compliance teams do when tokenization spans multiple networks?
A: They should extend monitoring and wallet screening across every chain in scope, then define escalation thresholds for illicit exposure on each one. The goal is consistent visibility, not identical treatment, because every network has a different risk profile and different operational role.
Technical breakdown
Predictable fees matter more than headline low fees
Network cost for financial operations is not just about the average fee. Institutions care about tail risk, which is the chance that a normally cheap rail becomes suddenly expensive during congestion. A chain with low baseline costs but severe volatility can create operational exposure that looks invisible in procurement discussions but appears immediately in payment, minting, or settlement workflows. For tokenized assets, fee predictability is part of business continuity because repeated transactions and automated processes need stable execution economics, not occasional spikes.
Practical implication: model worst-case transaction cost, not average cost, before approving a network for live tokenized operations.
Throughput and finality are different controls
Raw throughput measures how many transactions a network can process per second, while time to finality measures when a transaction is truly irreversible. Those are not interchangeable, and regulated finance should not treat them as if they are. High-frequency systems may value throughput, but high-value settlement needs hard finality and a clear understanding of any L2-to-L1 dependency that delays irreversibility. In practice, the governance question is whether the network’s settlement guarantees match the asset’s risk tolerance and legal finality requirements.
Practical implication: map each tokenised use case to its required finality threshold before deciding whether an L2 or base layer is acceptable.
Custody concentration creates ecosystem-level contagion risk
A tokenized asset may sit on a network that is technically sound but operationally fragile because one exchange, custodian, or liquidity provider dominates access. That concentration turns a single entity’s failure into a broader market shock, much like a dependency chain in traditional finance. This is a governance problem, not just a market structure problem, because the network’s resilience depends on how many counterparties can absorb stress if one participant fails. Institutions need to distinguish healthy liquidity from dangerous dependency.
Practical implication: assess whether one custodian or exchange has become a single point of failure for the tokenized ecosystem.
Threat narrative
Attacker objective: The objective is to exploit structural concentration or operational weakness so that a single event produces disproportionate disruption across the tokenized ecosystem.
- Entry occurs through a network or custody model that concentrates activity in a small number of dominant entities, making the ecosystem sensitive to a single failure.
- Escalation happens when a hack, run, or insolvency at one dominant exchange or custodian spreads stress across the wider network.
- Impact is ecosystem-wide contagion, where withdrawal pressure, liquidity loss, or operational disruption affects otherwise unrelated participants.
NHI Mgmt Group analysis
Chain selection is becoming an access-control decision for digital assets: the article shows that network choice changes who can safely hold, move, and monitor tokenized value. Cost stability, settlement guarantees, and custody concentration all alter the effective control environment. For practitioners, the governing question is not which chain is popular, but which chain preserves the access model the asset requires.
Custody concentration is the hidden governance gap in tokenized finance: if one exchange or custodian dominates a network, the ecosystem inherits a single point of failure that looks like liquidity but behaves like dependency. That is structurally similar to standing privilege in identity systems, where apparent convenience masks systemic fragility. Practitioners should treat concentration risk as a board-level resilience issue.
Compliance scaling must track network reach, not just asset growth: the more networks a programme touches, the more its monitoring model must expand without losing visibility. This is where on-chain surveillance resembles identity governance, because control scope must follow the asset wherever it moves. The practical conclusion is that monitoring coverage should be designed as part of the asset architecture, not bolted on after launch.
Governance debt accumulates when technical architecture outruns operating controls: the article’s core warning is that attractive throughput or low fees can create hidden obligations in settlement policy, compliance tooling, and operational oversight. That debt shows up later as exceptions, manual workarounds, and risk exceptions. Practitioners should align deployment speed with the maturity of the control plane, not with market hype.
What this signals
Chain-specific governance will become the default operating model for tokenized finance: the article shows why infrastructure choice cannot be separated from control design. When settlement risk, fee volatility, and custody concentration differ by network, governance has to evaluate the chain itself as part of the asset lifecycle.
Tokenized finance will pressure programmes to treat monitoring as an architectural dependency: if compliance tooling does not expand with the number of chains in use, visibility degrades faster than deployment scales. That creates a familiar security pattern: control coverage lags the environment, and exception handling quietly becomes the real operating model.
Identity-style concentration risk is the clearest hidden pattern in the article: where one exchange or custodian dominates a network, the security problem shifts from transaction processing to dependency management. Practitioners should prepare for more board-level scrutiny of custody concentration, especially as live tokenized deployments move beyond pilots.
For practitioners
- Define chain selection criteria as governance requirements Score candidate networks against predictable fees, true finality, custody concentration, and illicit exposure before approving a tokenized asset design.
- Separate throughput from settlement finality Require the business owner to state whether the use case needs high transaction volume, hard settlement finality, or both, then match the network accordingly.
- Map concentration points in custody and liquidity Identify whether one exchange, custodian, or liquidity provider controls enough activity to create a systemic dependency for the asset programme.
- Scale on-chain monitoring with network expansion Extend transaction screening and wallet monitoring across every network the programme uses so compliance does not lag behind deployment scope.
Key takeaways
- Tokenized finance does not have a universal “best” blockchain, because each asset class imposes different demands on cost stability, finality, liquidity, and governance.
- The article’s strongest operational warning is that concentration risk can turn one exchange or custodian into a systemic dependency for the whole network.
- Practitioners should choose networks by control fit, then extend monitoring, custody oversight, and settlement policy to match the chain actually in use.
Standards & Framework Alignment
This section maps relevant standards and security frameworks to the operational risks and controls described in this guidance.
MITRE ATT&CK addresses the attack and risk surface, while NIST CSF 2.0, CIS Controls v8 and NIST SP 800-53 Rev 5 set the governance and control requirements practitioners need to meet.
| Framework | Control / Reference | Relevance |
|---|---|---|
| MITRE ATT&CK | TA0040 — Impact | The article focuses on ecosystem shock from concentration and failure cascades. |
| Recommendation — Map concentration-driven shock scenarios to TA0040 and test where one failure can disrupt the wider network. | ||
| NIST CSF 2.0 | GV.RM-01 — Risk Management Strategy | Chain selection is framed as a governance and risk decision for regulated institutions. |
| PR.AA-05 — Access Permissions, Entitlements and Authorizations | Custody concentration and monitoring scope are access-governance problems in tokenized finance. | |
| Recommendation — Embed chain selection into risk strategy so asset architecture reflects settlement, custody, and monitoring needs. Review custody and network access scopes to avoid hidden dependency on a single dominant intermediary. | ||
| CIS Controls v8 | CIS-5 — Account Management | The article’s governance concerns include who controls assets and how concentration is managed. |
| Recommendation — Apply account management discipline to custody and operational roles that concentrate control over tokenized assets. | ||
| NIST SP 800-53 Rev 5 | AC-6 — Least Privilege | The control logic behind custody concentration is closely aligned to limiting unnecessary control paths. |
| Recommendation — Use least privilege to reduce the number of parties who can directly influence tokenized asset operations. | ||
Key terms
- Tokenized Asset Platform: A tokenized asset platform is a system that represents a real-world asset or value right as a digital token that can be issued, transferred, or redeemed. These platforms need strong identity, compliance, and fraud controls because token ownership can affect access to financial value, custody, and redemption rights.
- Time To Finality: The point at which a blockchain transaction is considered irreversible and settled for operational purposes. It is different from confirmation speed or throughput, and for regulated finance it often matters more than raw transaction volume because legal and settlement certainty depend on it.
- Custody Concentration: Custody concentration occurs when too much asset control or liquidity depends on a small number of exchanges, custodians, or intermediaries. It is a governance risk because the failure of one trusted actor can cascade into broader market disruption, even if the underlying chain remains technically healthy.
- Fee Volatility: The degree to which transaction costs change unpredictably over time on a network. For institutional users, fee volatility can create tail risk even when average costs look low, because operational workflows need stable execution economics rather than occasional price spikes.
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Published by the NHIMG editorial team on July 10, 2026.
Updated on October 11, 2026.
NHI Mgmt Group, the independent authority on Non-Human Identity, IAM, and Agentic AI security. nhimg.org