Peer-to-Pool NFT Lending

The Loan-to-Value ratio is the fundamental risk parameter in peer-to-pool lending. It determines the maximum amount a user can borrow against their NFT collateral.

• Calculation: LTV = Loan Amount / NFT Collateral Value.
• Conservative Ratios: Typically range from 20% to 50% for most collections to account for NFT volatility.
• Dynamic Adjustment: Protocols may lower LTVs for less liquid collections or during market stress. A lower LTV provides a larger safety cushion against liquidation.

Liquidation is the automated process of selling a borrower's collateral to repay the pool when their position becomes undercollateralized. It protects liquidity providers. Common triggers and methods include:

• Health Factor Breach: Triggered when the collateral value falls too close to the loan value.
• Dutch Auctions: Starting price is set above market value and decreases over time (used by BendDAO).
• Fixed-Price Sales: Collateral is sold at a fixed discount (e.g., 10%) to the oracle price.
• Liquidation Penalty: A fee (e.g., 2-5%) is charged to the borrower and often distributed to the liquidator.

The core smart contract vault that aggregates lender capital. Unlike peer-to-peer models, lenders deposit fungible tokens (e.g., ETH, stablecoins) into a single pool to earn yield, creating a continuous source of liquidity for borrowers. The pool's utilization rate and supply/demand dynamics algorithmically determine interest rates.

Borrowers deposit an NFT as collateral to draw a loan. The protocol must determine the NFT's loan-to-value (LTV) ratio. This is typically done via:

• Oracle Pricing: Using price feeds from marketplaces like Blur or OpenSea.
• Collection-Wide Floor Price: Loans are issued as a percentage of the collection's floor.
• Risk Parameters: Each collection is assigned specific LTV caps and liquidation thresholds by governance.

Loans are non-recourse and have fixed parameters set by the protocol, not negotiated between individuals. Key terms include:

• Fixed Interest Rate: Often determined by pool utilization.
• Fixed Duration: A set repayment period (e.g., 30, 90 days).
• Automatic Renewal: Loans may be extended if the borrower pays the interest, preventing immediate liquidation.

A critical risk management process. If the value of the NFT collateral falls below the protocol's liquidation threshold (e.g., due to market drop or accrued interest), the position becomes eligible for liquidation. Liquidators can repay the outstanding debt to seize the collateral, often receiving a liquidation bonus as incentive. This process is fully automated by smart contracts.

A real-time, numerical metric that indicates the safety of a loan. It is calculated as (Collateral Value * LTV) / Loan Debt. A Health Factor below 1.0 triggers liquidation. Borrowers must monitor this factor and can add collateral or repay debt to improve it, making it the primary dashboard metric for loan risk.

Leading implementations of the peer-to-pool model, each with nuanced mechanisms:

• BendDAO: Early pioneer for blue-chip PFP collections, uses a shared ETH pool and community-governed parameters.
• JPEG'd: Focuses on lending against NFTfi vault tokens, introducing PUSd stablecoin and a dedicated pool.
• Arcade.xyz: Connects pooled lender capital with bundled or single NFT collateral through a wrapper contract.
• ParaSpace: Allows for cross-collateralization, enabling users to borrow against a portfolio of NFTs and ERC-20 tokens from a unified pool.

The integrity of the loan depends entirely on the oracle price feed for the NFT collateral. Manipulation of this price, either through wash trading on a marketplace or exploiting a flaw in the oracle's calculation (e.g., using outlier sales), can lead to undercollateralized loans and bad debt for the pool. Protocols mitigate this with time-weighted average prices (TWAPs), multiple oracle sources, and circuit breakers.

When an NFT loan becomes undercollateralized, liquidators must purchase the NFT from the pool at a discount. Key risks include:

• High slippage on low-liquidity NFTs, making liquidation unprofitable.
• Front-running of liquidation transactions.
• Gas wars during market volatility, eroding liquidation profits. Failed liquidations result in the pool holding an illiquid, depreciated asset.

The core risk is a vulnerability in the protocol's smart contracts, which could lead to the loss of pooled funds or collateral. This includes:

• Logic bugs in lending, borrowing, or liquidation functions.
• Upgradeability risks if the protocol uses proxy patterns; a malicious or faulty upgrade could compromise the system.
• Integration risks with external contracts like oracles or NFT marketplaces.

NFT collections are highly volatile and can experience floor price crashes. A pool overly concentrated in a single collection faces systemic risk. Protocols manage this through:

• Risk parameters: Setting different Loan-to-Value (LTV) ratios per collection based on volatility.
• Debt ceilings: Limiting total borrowing against a specific collection.
• Whitelisting: Only accepting established, liquid collections as collateral.

Providers depositing assets into the pool face several risks:

• Impermanent Loss: If the value of borrowed assets (e.g., ETH) rises sharply relative to the interest earned.
• Bad Debt: Losses from undercollateralized loans that cannot be liquidated are socialized across LPs.
• Capital Efficiency: Funds may sit idle if borrowing demand is low, yielding poor returns.

Borrowers risk losing their NFT collateral through liquidation if its value falls. The required overcollateralization (e.g., borrowing 30 ETH against a 100 ETH NFT) is a key safety feature but also a capital inefficiency. Borrowers must also monitor health factors and be aware of liquidation penalties and potential gas costs for managing their position.

A model where lenders and borrowers negotiate individual, discrete loan terms directly. This is the primary alternative to peer-to-pool systems.

• Mechanism: Lenders browse listed NFTs and make custom offers on specific assets.
• Key Feature: Enables bespoke terms (loan-to-value, duration, interest) but requires active management and counterparty discovery.
• Example Platforms: NFTfi, Arcade.

A smart contract containing pooled funds from many lenders, used to automatically underwrite loans according to predefined parameters. This is the core infrastructure of peer-to-pool lending.

• Function: Acts as the automated counterparty, providing instant liquidity to borrowers.
• Risk Management: Uses oracle prices and loan-to-value (LTV) ratios to determine borrowing limits and trigger liquidations.

A critical risk parameter representing the loan amount as a percentage of the NFT's collateral value.

• Calculation: (Loan Amount / NFT Collateral Value) * 100.
• Purpose: Protects the pool from insolvency; a lower maximum LTV (e.g., 30-50%) provides a larger safety cushion.
• Liquidation: If the NFT's value falls, pushing the LTV above a liquidation threshold, the collateral can be seized and sold.

A common peer-to-pool strategy where loans are issued based on the floor price (lowest ask) of an NFT collection, not individual trait value.

• Utility: Simplifies valuation, providing liquidity for "blue-chip" collections like Bored Ape Yacht Club.
• Limitation: Does not account for premium traits, capping borrowing power for rare NFTs.
• Oracle Dependency: Relies on decentralized oracles like Chainlink to provide real-time floor price feeds.

The process of seizing and selling an NFT collateral to repay a defaulted loan, protecting the liquidity pool.

• Trigger: Occurs when the health factor of a loan falls below 1 (e.g., collateral value drops or debt increases).
• Mechanism: Liquidators can purchase the NFT at a discount, repay the loan, and keep the difference as profit.
• Importance: Essential for maintaining pool solvency and enabling permissionless underwriting.

A pioneering peer-to-pool NFT lending and borrowing protocol, often cited as the canonical example.

• Model: Introduced the ETH liquidity pool model for blue-chip NFT collections.
• Mechanism: Uses a shared pool for all supported collections, with dynamic interest rates based on utilization.
• Historical Note: Its liquidity crisis in 2022 highlighted the systemic risks of high LTV ratios and oracle dependencies in pooled models.