Slow Burn
The RWA Trust Rodeo
The importance of data availability and accessibility was perhaps most obviously illustrated by the 2008 financial crisis. Had credit default positions been visible, market participants and/or regulators would have detected leverage building and taken preventative action.
Now, crypto inherently promises transparency; however, accurately and securely translating real-world data to this digital environment has introduced one of the greatest challenges to the RWA ecosystem. This is, in short, the “oracle problem,” and the trust required by existing solutions renders them potential failure points with massive on-chain consequences. Resolving this complex and weighty issue will be analogous to training a wild horse for a toddler and, as any good RWA wrangler knows, many hands (+ good infrastructure) make light work.
Tools for taming this figurative horse are relatively new, and they each balance trust, performance, and scalability differently:
Single-Party Trust, employed by Slow’s sDAO and Maker/HVB, is effectively a lone wrangler with a lasso. An asset manager (e.g., an LLC managing member or other appointed steward) disseminates off-chain assets’ data at regular intervals. While incentives are aligned between the asset manager and owners, providing information is largely manual, and holders must accept single-counterparty risk. Because it lacks in both scalability and security, single-party trust is a minimally viable oracle.
Auditors, used by companies like Goldfinch, are a bevy of experienced wranglers. Though auditor frameworks can vary, they broadly use staked capital to incentivize diverse, capable observers to provide independent, reliable data; their responses are compared to ensure veracity. This model presents its own security risks (e.g., when off-chain benefits of bad-faith collusion outweigh on-chain slashing penalties), but it is inherently safer than single-party systems and is scalable across various asset classes (where large, asset-specific expert populations can perform analysis).
Data Streaming is a lunge line. As discussed in last week’s post, decentralized oracle services power “RWA-lite” synthetic products by tethering them to secure, scalable and readily available data pipelines. However, on-chain accuracy requires independent and redundant information sources to mitigate the “garbage in, garbage out” risk. Also, externally-derived data must be standardized for oracle platform consumption and, ultimately, inclusion in the RWA ecosystem at scale.
Refining these early instruments is integral to developing a robust RWA marketplace. The necessary experimentation with and evolution of oracles will be achieved through the continued efforts of RWA wranglers; asset managers, entrepreneurs, and officials across jurisdictions will grapple with building sufficiently secure data streams that will flow on-chain.
About Slow Burn
Weekly explorations into emerging crypto trends and how to navigate 2023 from the Slow Crypto Team, Sam Lessin, Clay Robbins, and Caroline Cline