Woofun AI reports that the Depository Trust & Clearing Corporation (DTCC) has initiated a tokenization trial involving approximately 40 major financial entities, including JPMorgan, Goldman Sachs, BlackRock, Vanguard, and the NYSE, to represent shares and Treasuries on-chain. This initiative underscores a fundamental structural challenge: these digital tokens only become viable collateral when lending markets can definitively answer who prices them and how valuations are maintained once the underlying venues go quiet. The core issue is not merely technical but relational, requiring a trusted mechanism to bridge traditional finance with decentralized protocols. As Fisher noted, the viability of this entire ecosystem hinges on the ability to price assets reliably during periods of market inactivity, a capability that remains largely unproven at scale.

Woofun AI data shows the disparity between asset availability and actual usage highlights a significant inefficiency in the current market structure. DefiLlama data indicates that the on-chain real-world asset (RWA) market capitalization has surpassed $51 billion, yet these assets generate only near $3.8 billion in active total value locked (TVL) within DeFi protocols. This results in a utilization rate of just 7.7%, suggesting that the vast majority of tokenized value remains idle or underutilized. Such a low engagement rate implies that while the supply side of tokenization is expanding rapidly, the demand side—specifically the lending and borrowing markets—is constrained by trust and pricing uncertainties. The gap suggests that institutions are hesitant to deploy capital into these assets without robust, verifiable pricing mechanisms that can withstand market volatility and downtime.

Structurally, a functional lending market requires more than just the presence of assets; it demands a reliable price feed, a set of venues from which that feed draws data, and explicit rules for handling scenarios where those venues cease operations. For assets such as tokenized stocks, bonds, and gold, the complexity increases because their primary markets operate on traditional schedules, leaving gaps in data continuity. Someone must select the oracle, verify its independence, cap exposure limits, and determine the precise conditions under which liquidations are triggered. For newly listed tokens, this infrastructure upgrade lags significantly, as liquidity has not yet concentrated in any single trusted venue. This fragmentation creates a vacuum where price discovery is ambiguous, increasing the risk of erroneous valuations and subsequent financial losses for participants.

To address these vulnerabilities, institutions are increasingly delegating the vetting process to professional curators rather than relying on decentralized consensus alone. Entities such as Steakhouse and Gauntlet act as vault operators, evaluating collateral quality, approving specific markets, and setting exposure limits on platforms like Morpho. Alternatively, some institutions partner with protocols like Aave, which build their own direct relationships with oracle providers to ensure data integrity. Fisher emphasized that institutions appreciate having "a professional kind of in the room" to manage these complex risk assessments.

This shift toward centralized curation reflects a pragmatic approach to mitigating the inherent uncertainties of decentralized pricing, where the cost of error is disproportionately high compared to the potential gains.

The liability framework surrounding these curated markets is equally critical, as it determines who absorbs the financial and reputational fallout when a market fails. Fisher explained that a single oracle manipulation within a market trusted by a curator can tarnish that curator’s entire track record, leading to a 'hard no' from investment committees regardless of performance in other areas. In this model, the curator owns the risk decision, while the depositor typically absorbs the direct financial loss. Pool-based models like Aave or isolated markets on Morpho often leave the underlying protocol with no direct liability, creating a misalignment of incentives. To close this gap, institutions are demanding mechanisms such as first-loss capital, mandatory insurance, fee clawbacks, and auditable exposure disclosures, ensuring that risk is properly allocated and transparently managed.

Looking ahead, the future of RWA tokenization will likely diverge into two distinct scenarios based on how these governance challenges are resolved. In the optimistic case, platforms will standardize off-hours pricing, implement circuit breakers, and enforce strict curator disclosures over the next several years, creating a robust infrastructure for tokenized equities, bonds, and commodities. Conversely, in the pessimistic scenario, tokenization will continue to expand in issuance terms without solving its governance layer, leading to an accumulation of tokenized assets on balance sheets that remain largely untouched by DeFi lending and composability.

Fisher noted that institutional sensitivity to oracle risks for traditional assets is higher than for crypto-native assets, given the closed nature of primary markets on weekends. Ultimately, institutions require a governance stack around their price feeds that is durable enough to survive rigorous investment committee scrutiny, along with a settled answer for who absorbs the loss when a feed fails.