NFT-backed lending is one of the core innovations of the Treehouse Labs project, and its operational mechanism can be summarized in the following steps, combining the uniqueness of NFTs with the liquidity optimization logic of DeFi:
1. Collateral Submission and Assessment
Types of Collateral: Users can submit their held NFTs (such as digital art, gaming assets, virtual land, etc.) as collateral to the Treehouse protocol.
AI Risk Assessment: The protocol integrates AI models to dynamically assess the value and lending risk based on the historical transaction data, scarcity, creator reputation, and other dimensions of NFTs, determining the collateral ratio (e.g., NFT collateral ratio of 65%)
. This process reduces reliance on manual valuation and lowers the probability of default.
2. Lending Parameter Settings
Lending Limit: Based on the assessed value and collateral ratio of the collateral NFT, the system automatically calculates the amount of stablecoins or tokens the user can borrow. For example, if the assessed value of the NFT is $10,000 and the collateral ratio is 65%, the user can borrow up to $6,500.
Interest Rates and Terms: The borrowing interest rate is dynamically adjusted by algorithms to reflect market supply and demand and NFT liquidity risk; the term is usually flexible or fixed, and users must repay the principal and interest before maturity to redeem their NFTs.
3. Cross-Chain and Liquidity Aggregation
Multi-Chain Support: Treehouse is built on public chains like Ethereum, Solana, and Polygon, allowing users to submit NFT collateral on any chain and achieve seamless asset transfer through cross-chain bridging technologies (such as LayerZero).
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Liquidity Aggregation: The lending pool integrates multi-chain NFT collateral to attract DeFi users to provide stablecoin or token liquidity, creating a scale effect and reducing borrowing costs.
4. Risk Management and Liquidation Mechanism
Dynamic Monitoring: AI continuously tracks the market price fluctuations of collateralized NFTs; if the value falls below the liquidation threshold (e.g., collateral ratio below 50%), it triggers an automatic liquidation process.
Liquidation Method: The protocol repays debts through auction or direct sale of NFTs, with remaining value returned to the user; if NFT liquidity is insufficient, partial discounted liquidation may occur, but the AI assessment model can provide early warnings to reduce losses.
5. User Earnings and Ecosystem Closed Loop
Borrower's Earnings: Users can obtain funds without selling NFTs, meeting short-term liquidity needs while retaining potential appreciation benefits of the NFTs.
Lender's Earnings: DeFi users earn borrowing interest by providing liquidity, with 10-20% of the interest as protocol fees used for token buyback/burning (if issued), forming a deflationary value cycle.
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Ecosystem Expansion: Lending protocols combined with gaming, metaverse, and other scenarios support Play-to-Earn asset collateralization, promoting diversification of NFT application scenarios.
Operational Advantages
Addressing Liquidity Pain Points: Transforming non-standard NFTs into lendable assets to activate the existing market.
Technical Risk Reduction: AI assessment and cross-chain technology reduce the default rate and operational thresholds.
Ecosystem Synergy: Integrated with NFT markets like OpenSea and Blur, users can initiate lending directly on trading platforms, forming a closed loop of 'trade-collateral-reinvest'.
Summary: NFT-backed lending transforms low-liquidity NFTs into efficient financial instruments through AI valuation, cross-chain aggregation, and dynamic liquidation, providing funding flexibility for holders while injecting new assets into the DeFi market, promoting the transition of NFTs from collectibles to productive assets.