Dynamic Loan-To-Value
The Loan to Value (LTV) ratio defines the maximum amount of currency that can be borrowed with a specific collateral. It’s expressed as a percentage: at LTV=30%, for every 1 ETH worth of NFT collateral, borrowers will be able to borrow 0.30 ETH worth of the corresponding currency.
With the latest update to our underlying model, users can now avail themselves of loans amounting to up to 75% of the actual value of their NFTs. This enhancement is coupled with our steadfast commitment to upholding the highest standards of financial security, positioning us as a leading NFT-backed protocol in terms of advanced safety measures.
Dynamic Loan-To-Value
Unlockd's Data Science team has developed a sophisticated Dynamic Loan-To-Value (LTV) model, expertly balancing user risk in an optimal way. This model, a testament to Unlockd's commitment to innovation and security, intelligently adapts to the intricacies of the NFT market.
The LTV model considers a range of factors, such as the volume of data available for asset valuation and the current market volatility. High-quality, abundant data coupled with low volatility leads to a higher LTV, reflecting the enhanced reliability of the valuation algorithm in stable market conditions.
As a result, two NFTs of similar value can have different LTVs under this model. This is due to the model's nuanced approach, which extends beyond mere appraisal value, incorporating data availability, recent market fluctuations, and other relevant elements into its calculation.
Adapting to Market Conditions
The model is designed to adjust LTVs in real-time, responding to changes in overall market volatility, specific collection volatility, and the volatility of individual assets.
For instance, if a certain NFT collection experiences increased market volatility, the model automatically recalibrates the LTVs for NFTs in that collection to better align with the new risk profile. These adjustments would aim to mitigate the increased uncertainty, resulting in reduced LTVs that align with the prevailing market conditions. This usually does not apply to RWA, as they are not part of collections.
Risk Mitigation Strategies
Proactive Safeguards: Beyond setting loan collateral ratios, the dynamic LTV model plays a crucial role in risk mitigation. It closely monitors reserve levels and the activities of other lending protocols to inform its decisions. An increase in reserves triggers a strategic response from the model, reducing the issuance of new collection-based loans, thereby managing selling pressure on the protocol.
Maintaining Stability: This proactive management of lending activities, based on reserve levels and market dynamics, is vital in sustaining the protocol's integrity and resilience. It effectively shields the protocol from potential adverse effects of market fluctuations, securing its long-term health and reliability.
The Dynamic Loan-To-Value model at Unlockd is not just a tool for determining loan terms; it's a comprehensive system designed to ensure stability, adaptability, and security within the ever-changing landscape of NFT-backed lending, particularly for RWAs.
You can learn about all the aspects of this model here:
spaceUnlockd Risk Framework
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