Tokenized real-world assets will remain fragile collateral unless the markets around them can value, finance, hedge, sell and settle those assets through a disruption, according to Jesús Rodriguez, co-founder of Sentora. His analysis argues that issuing a token is only the first step: the harder task is designing on-chain market infrastructure that can handle a liquidation when blockchain-based loans operate continuously but the underlying assets and redemption systems do not.
That challenge becomes acute when tokenized bonds, private credit, equities or other off-chain claims are used to borrow stablecoins. A lending protocol can seize collateral within seconds after a borrower falls below a required threshold. Yet the issuer, custodian, bank, transfer agent or underlying market needed to convert that collateral into cash may be unavailable for days.
Rodriguez describes the resulting mismatch as a liquidation gap. In his example, a borrower breaches a threshold at 2 a.m. on Sunday. The smart contract can immediately transfer the token to a liquidator, but a traditional market may not open until Monday, while a redemption request might not be processed until Tuesday or later. The token has changed hands, but the mechanism for obtaining the settlement asset needed to close the loan remains delayed.
Fast liabilities can collide with slow asset exits
The analysis challenges a common assumption that low-volatility tokenized government debt is automatically safer collateral than crypto-native assets such as ETH. Government bond tokens may show stable prices because their reference values are updated infrequently or remain tied to stated net asset value, Rodriguez writes. ETH, by comparison, trades around the clock and can be sold in deep global markets even during weekends.
A smooth token price can therefore reflect stale valuation data rather than immediate liquidity. If a lending protocol relies on that stale price, it may permit more borrowing than the collateral could support in a stressed sale. If it applies a sudden correction later, the adjustment could trigger a wave of liquidations into thin secondary markets.
The issue is less about whether a token tracks an underlying asset under normal conditions than whether it can be converted into the required form of cash before a protocol’s liabilities come due. Rodriguez defines liquidity as the ability to sell or finance a position within a specific time window and at an acceptable discount. Total value locked, a visible trading pair and an issuer’s promise to redeem at net asset value do not meet that standard on their own.
An RWA token generally has three potential exit routes. A holder can sell to another market participant, redeem through the issuer, or borrow against the token to postpone a sale. Each route carries distinct limits. Secondary buyers can disappear or demand steep discounts; redemptions can be delayed, capped or restricted to eligible holders; and borrowing depends on available lending capacity and collateral rules.
Market makers can bridge some of that gap by committing balance sheet capital during periods when the underlying market is closed. Their willingness to do so should be treated as a risk variable, Rodriguez argues, rather than an assumed source of permanent liquidity. During stress, dealers may widen spreads, reduce inventory or withdraw from a market precisely when automated protocols need them most.
Collateral rules need to reflect legal and operational risks
Rodriguez’s framework calls for six elements before an off-chain asset can work reliably in decentralized finance: enforceable legal rights, dependable data feeds, clear transfer and redemption procedures, executable secondary-market liquidity, collateral settings that reflect real behavior, and a defined liquidation and loss-allocation process.
The final condition is often underdeveloped. Protocols can specify a loan-to-value ratio and an oracle price without establishing who absorbs losses when liquidation proceeds fail to cover outstanding debt. That gap can push losses to liquidity providers, stablecoin holders, protocol treasuries or other lenders, depending on a platform’s structure.
Collateral haircuts should account for more than historical price volatility, according to the analysis. They also need to reflect the enforceability of the holder’s claim, oracle update frequency, redemption timing, custody arrangements, issuer concentration, governance control, market-maker capacity and the relationship between collateral prices and the borrowed asset.
This approach could produce lower borrowing limits for tokenized Treasuries than for ETH under certain conditions. That conclusion runs against the usual intuition that U.S. government debt is inherently safer collateral, but it follows from the difference between underlying credit quality and the ability to liquidate a tokenized claim on a 24/7 schedule.
A token backed by short-term government securities may face little default risk from the securities themselves, while carrying material operational and timing risk at the token layer. For a lending protocol, those risks become relevant if it must convert collateral immediately.
Risk travels through a network of dependencies
Rodriguez proposes treating RWA risk as a relationship graph instead of compressing it into one score. The relevant nodes include cash flows, issuers, legal entities, custodians, oracles, exchanges or secondary venues, redemption mechanisms, stablecoin pools, lending protocols, governance keys and backstop capital.
Those links can transmit stress. A problem with a custodian can affect redemption; delayed redemption can weaken market-maker demand; thinner trading can make oracle prices less representative; and a price move can activate liquidations in a connected lending market. The token’s market price may be the last signal to move, rather than the first.
The analysis identifies redemption queues, market depth, position concentration, lending utilization, oracle deviations, reserve changes, deterioration in the underlying cash flows and market-maker activity as areas that require monitoring. Several of those signals develop off-chain, placing limits on systems that rely solely on blockchain data.
More complex assets raise the design burden
Tokenized Treasuries have become an early test case because they offer standardized assets and relatively familiar processes for custody, minting, compliance, pricing and redemption. Rodriguez presents them as a starting point, not a template that can be applied unchanged to more complicated asset classes.
Compute-related assets, for example, can involve GPU equipment, equipment leases, prepaid computing capacity, utilization-linked income and data-center revenue rights. Their economics combine equipment financing, operating performance, depreciation and shifts in technology demand. A token tied to such assets would need pricing and collateral rules that capture those variables rather than rely on a simple daily mark.
Energy-linked tokens present a similar problem of definition. A token could represent a physical asset, a power-purchase agreement, a megawatt-hour of generation, grid capacity, project revenue or an environmental credit. The legal claim, data source and liquidation procedure would differ across each structure.
Tokenized equities could provide an especially demanding test as platforms seek to connect global share exposure with crypto-native lending and derivatives. Direct share ownership, revenue rights, structured notes and synthetic trackers can follow similar price movements while carrying different rights to dividends, voting, corporate actions, redemption and bankruptcy recoveries.
Rodriguez sees perpetual futures as a possible complement to tokenized equity spot markets, providing leverage, short exposure, hedging and continuous price discovery. That combination also creates a feedback risk: tokenized shares used as stablecoin collateral could support a leveraged perpetual position, while a weekend decline in token prices triggers liquidations into a market with limited spot liquidity.
The safeguards he outlines include isolated margin systems, concentration limits, dynamic weekend haircuts, liquidity-aware oracles, circuit breakers, cross-market monitoring and explicitly funded backstops. Together, those measures would force protocols to price the costs of slow redemption and limited disposal capacity before leverage builds around an asset.
Tokenization can improve distribution, settlement and transparency, Rodriguez argues, but its usefulness in DeFi will depend on whether the surrounding market structure can absorb a stressed exit rather than merely record ownership on-chain.
Explore how DeFi markets truly support tokenized assets in stress scenarios in this RWA-focused guide for practical insight.
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