Asset-Backed Loans for Compute: Turning GPUs into DeFi Yield | Conor Moore, USD.ai (#77)

Conor Moore breaks down USDAI’s GPU-backed, on-chain lending model—tokenized hardware loans, insurance-backed tranches, and a governance token to scale real-world compute finance.

Key Takeaways

USDAI tokenizes GPU asset titles (NFTs) and runs loans on-chain so investors mint tradable yield tokens that pool exposure across counterparties and jurisdictions.
Typical GPU loans run three years with 70–80% LTV and headline interest roughly 7–15%, targeting an effective protocol rate near 10% for many deals.
Risk stack uses ~20–30% equity first-loss, then Munich Re value insurance (~100–150 bps) to lower capital cost and convert nominal yields into stable risk‑adjusted returns.
Operational controls include SPV isolation, hardware telemetry, and visible deal terms—full transparency replaces opaque multi‑tranche permissionless products to attract lenders and borrowers.
Scaling thesis: massive GPU CapEx demand creates billions in addressable loans; a $1B loan book signals market credibility and enables rapid further capital inflows.
Governance token launching soon: it will set protocol parameters, take a percentage of interest income, initially route fees to the DAO, and materially affect investor valuation.

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