DeFi Lending & Borrowing Risk Framework

As DeFi continues to evolve, implementing a robust risk framework is crucial—particularly for lending & borrowing protocols. An effective framework not only mitigates default risks but also enhances operational efficiency and protocol resilience. This blog explores the technical foundations of risk frameworks in DeFi lending & borrowing protocols, examining how these frameworks optimize risk management strategies & enable more data-driven decision-making for improved stability & performance.

DeFi Lending & Borrowing

DeFi lending empowers users to engage as lenders or borrowers while retaining full custody of their assets in a permissionless manner. Lenders submit their tokens to a specific protocol, earning interest based on the prevailing supply annual percentage yield (APY).

These tokens are subsequently allocated to a smart contract, rendering them available for borrowing against collateral. When a borrower initiates a loan, the platform’s smart contracts retain custody of the collateral for the loan's duration. In return, the platform issues a receipt token that can be exchanged for the collateral along with accrued interest, determined by the borrow APY.

Common Functionalities of DeFi Lending

1. Collateral and Borrowing: Users must provide collateral to secure loans, which protects lenders from defaults. The collateral must exceed the loan amount based on predetermined ratios (e.g., Max LTV).
2. Interest Rate Curve: The interest rate curve is dynamic, adjusting based on supply and demand within the protocol. As borrowing demand increases, interest rates rise to maintain equilibrium between lenders and borrowers.
3. Liquidation Mechanism: If a borrower’s collateral value falls below a specified threshold, their position becomes eligible for liquidation. Liquidators are incentivized through bonuses to recover funds for lenders.

Risk Parameters of DeFi Lending

Risk parameters are pivotal metrics that delineate a protocol's exposure to various risks while shaping asset management and liquidation conditions. These parameters balance capital efficiency with risk management—essential for navigating market fluctuations effectively.

Max LTV (Loan-To-Value)

The Max LTV ratio establishes an upper limit on a user’s borrowing capacity relative to the value of their collateral. This parameter is vital for risk management as it ensures that borrowed assets remain within a safe threshold against provided collateral. A well-calibrated Max LTV protects both lenders and borrowers by preventing over-leveraging, which can lead to significant losses during market downturns.

Liquidation Threshold / Factor

The liquidation threshold is the percentage at which a borrower’s position becomes eligible for liquidation. If the value of a borrower’s collateral falls below this threshold, their position can be liquidated by keepers to restore it to a safe collateralization level. This acts as a safety measure to prevent potential defaults and maintain solvency within the protocol.

Repay Factor

This defines the minimum percentage of a liquidated position that must be repaid to avoid complete liquidation, allowing users facing liquidation to regain control over part of their collateral by meeting this minimum repayment requirement.

Liquidation Bonus

The liquidation bonus incentivizes users to participate in the liquidation process and helps maintain protocol solvency. When a borrower’s position becomes undercollateralized, this bonus provides additional rewards to liquidators on top of discounted collateral they acquire.

Interest Rate Curve

The Interest Rate Curve governs how borrowing costs escalate with increasing utilization rates within a lending protocol. As demand for borrowing rises, interest rates increase to incentivize lenders while deterring excessive borrowing. This dynamic promotes liquidity in the system and helps stabilize the market by adjusting costs based on real-time supply and demand conditions.

Supply & Borrow Caps

Supply Caps and Borrow Caps are mechanisms that limit maximum asset supply within protocols and restrict exposure to specific assets, respectively. These caps ensure sufficient liquidity for healthy liquidations while mitigating risks associated with overexposure to volatile assets. By controlling asset availability, these caps help maintain market equilibrium and prevent drastic price fluctuations during liquidation events.

Interrelationship of Risk Parameters in DeFi Lending

Understanding the interconnectedness of risk parameters is crucial for maintaining the integrity and stability of DeFi lending protocols. Each parameter does not operate in isolation; rather, they influence one another in significant ways, shaping the overall risk landscape. Here’s a closer look at how these parameters interact:

Impact of Supply & Borrow Caps in Protocol

By implementing borrow caps, protocols can dampen this procyclical behavior, thus stabilizing lending volumes during market booms and busts. This is crucial in preventing situations where a surge in borrowing leads to inadequate liquidity for covering potential liquidations, thereby mitigating liquidation impact and faulty liquidations. Supply caps can also promote diversification within the protocol by limiting excessive concentration in any single asset. This diversification reduces systemic risk across the ecosystem, as it prevents heavy reliance on a few volatile assets that could destabilize the entire protocol. 

Impact of Interest Rates on Liquidity

When interest rates rise, it can lead to liquidity withdrawals from the protocol. As borrowing costs increase, lenders may choose to withdraw their assets, which can subsequently affect collateralization ratios. This reduction in liquidity can trigger liquidations, as fewer funds are available to support borrowers whose collateral values are declining.

The Role of Liquidation Thresholds

A higher liquidation threshold effectively narrows the margin before collateral becomes undercollateralized. This adjustment minimizes the risk of bad debt by ensuring that positions are liquidated before they reach a critical state of insolvency. However, if set too high, it may also encourage risky borrowing behaviors, as users might leverage their positions more aggressively.

Relationship Between Max LTV & Liquidation Thresholds

An increased gap between the Max LTV ratio and the liquidation threshold can significantly lower average risk levels within the protocol. By maintaining a conservative Max LTV, protocols can minimize potential losses for both borrowers and lenders. This buffer ensures that even during market downturns, borrowers are less likely to face immediate liquidation, thereby enhancing overall market stability.

While DeFi lending mitigates many risks associated with centralized finance, it introduces its own set of challenges primarily revolving around smart contract vulnerabilities, market risks, counterparty risks, and other potential risks.

DeFi Lending & Borrowing Risk Framework

This section dissects the multifaceted risks inherent in decentralized finance (DeFi), focusing on oracles, smart contracts, composability, liquidity, volatility, and market dynamics. The objective is to establish a comprehensive risk assessment and management framework that enhances the stability and resilience of DeFi ecosystems.

Goals of a DeFi Lending/Borrowing Risk Framework

A robust risk framework is designed to optimize three pivotal metrics:

• Minimizing Insolvencies: Establish parameters that protect against borrower defaults, thereby preserving the health of the protocol.
• Optimizing Liquidations: Define criteria for timely liquidations to avert insolvencies while reducing unnecessary liquidation events that could harm both lenders and borrowers.
• Enhancing Borrow Usage: Foster an environment that incentivizes borrowing activity without jeopardizing the stability of the protocol.

Risks and Mitigation Techniques

1. Oracle Risks

Oracles serve as critical data providers, supplying external information to smart contracts. In DeFi lending and borrowing platforms, they are essential for fetching price data and determining collateral values.

Risks:

• Data Accuracy: Inaccurate data can lead to erroneous pricing and flawed execution of smart contracts.
• Data Availability: Downtime or failure to update can render dependent applications inoperative, causing potential user losses.
• Oracle Manipulation: Malicious actors may exploit or manipulate oracle data feeds, resulting in unintended consequences like liquidations or financial losses.

Mitigation Strategies:

• Implement real-time monitoring systems with anomaly detection algorithms to identify and address suspicious data points.
• Utilize multiple reputable oracle sources to cross-verify data integrity.
• Ensure robust integration protocols to reject stale or outdated price information.

2. Mechanism/Economic Risks

Mechanism or economic exploits of a DeFi protocol occur when an attacker is able to manipulate the economic incentives of the protocol to their advantage, resulting in a loss of funds for other participants. This can happen even when there are no smart contract bugs or other unintended logic errors.

Mitigation Strategies:

• Conduct comprehensive economic simulations and game-theory analyses to stress-test incentive structures.
• Implement monitoring systems for unusual activities such as price manipulation attempts.
• Regularly review and adjust risk parameters based on current market conditions.

3. DeFi Composability Risks

DeFi composability refers to the ability of different DeFi protocols and applications to work together seamlessly in endless combinations, allowing developers to create more complex financial transactions and applications. While composability offers many ben- efits, layering on protocols and applications on top of each other comes with additional risks. For instance, risks get compounded when multiple protocols are composed to- gether, as a vulnerability in one contract could impact others. The interconnectivity of DeFi protocols can amplify risks, turning isolated incidents into systemic threats.

Mitigation Strategies:

• Develop standardized communication protocols between DeFi applications to ensure secure interactions.
• Limit composability strictly to necessary interactions to reduce potential attack surfaces.
• Consider establishing insurance policies or reserves for potential losses from integrated protocol failures.

4. Loss of Stablecoin Peg

Stablecoins are tokens whose value is intended to be pegged or tied to that of another asset, which could be a currency, commodity, or financial instrument. There are many types of stablecoins, some of which are riskier than others depending on product design. For instance, some stablecoins are secured by real-world reserves while others are secured by other crypto assets or smart contract algorithms. Depegging occurs when a stablecoin loses its peg to the target asset.

Mitigation Strategies:

• Select stablecoins with strong collateralization and transparent governance structures.
• Develop warning systems that monitor depegging risks using both on-chain and off-chain data.
• Maintain adequate liquidity in stable pools and require overcollateralization for stablecoin deposits.

5. Liquidity Risks

Liquidity is vital in DeFi lending platforms; insufficient liquidity can result in substantial user losses during liquidation events. Primarily based on on-chain liquidity and trading volume, liquidity is critical for the liquidation process. Liquidation risks are mitigated via liquidation parameters (i.e., the lower the liquidity, the higher the liquidation incentives).

Mitigation Strategies:

• Ensure sufficient on-chain liquidity within protocols to absorb market shocks.
• Implement supply and borrow caps for assets to mitigate concentration risks.

6. Volatility Risks

Price volatility can negatively affect collateral value. Asset volatility is a crucial factor in determining its respective risk parameter configuration. The least volatile currencies are stablecoins followed by ETH and BTC. High volatility will yield low LTs and LTVs while low volatility will allow us to be more risk-on.

Mitigation Strategies:

• Set conservative loan-to-value (LTV) ratios for volatile assets.
• Monitor asset volatility in real-time, adjusting risk parameters as necessary.
• Encourage diversification of collateral types to mitigate concentration in high-volatility assets.

7. Counterparty Risks

Counterparty risks pertain to the governance of a given asset and degree of centralization. It is assessed based on factors such as the level of decentralization of the asset’s gover- nance, the number of parties that control the asset’s protocol, the number of holders of the asset, and the level of trust in the entity, project, community, or processes associated with the asset.

Mitigation Strategies:

• Limit exposure to assets with high counterparty risks associated with centralized governance.
• Establish protocols for rapid response if an asset’s risk profile deteriorates.

8. Market Risks

Market risks in the protocol are dynamic and impacted by the pool’s size and supply and demand oscillations. Constant assessments of average daily volume, volatility, and market capitalization aim to mitigate market risk.

Mitigation Strategies:

• Continuously monitor market conditions, adjusting risk parameters accordingly.
• Implement circuit breakers during extreme market volatility events.
• Regularly stress-test protocols under varying market scenarios.

Optimizing Risk Parameters

Effective optimization of risk parameters is essential for balancing user incentives with economic security. The innovative landscape of DeFi necessitates ongoing assessment and adjustment of these parameters in response to market dynamics and emerging threats.

Preventing Economic Exploits

Strategic optimization serves as a vital defense against economic exploits prevalent in DeFi ecosystems. By maintaining low maximum LTV ratios alongside wide liquidation thresholds, protocols can safeguard against both liquidation risks and price manipulation tactics employed by malicious actors. Establishing stringent controls on leverage while ensuring adequate collateralization will further mitigate vulnerabilities associated with economic attacks.

Conclusion

While DeFi has transformative potential as a standard mechanism for accessing financial services, inherent limitations within lending frameworks pose challenges to genuine innovation. Recognizing and managing risks within DeFi lending platforms is essential for fostering widespread adoption of their offerings. To effectively mitigate these risks, lending platforms must proactively establish well-defined risk frameworks equipped with appropriate tools.

At Chainrisk, we enhance risk assessment through advanced stress testing methodologies that leverage real-world data for comprehensive analysis. Our innovative approaches empower protocols to optimize their parameters for maximum resilience in an ever-evolving financial landscape, ultimately contributing to the long-term sustainability of DeFi lending practices.