Risks & Assumptions

Collateral Assumptions: PrimeFi assumes all loans are over-collateralized. Each asset has risk parameters (LTV, liquidation threshold, liquidation bonus) configured by governance or the team. The proper functioning of the algorithm depends on these parameters being set conservatively to account for volatility. If an asset’s value drops rapidly, the protocol relies on timely oracle updates and liquidators to stabilize the system. A key risk is oracle failure or delay – inaccurate prices could prevent or trigger wrongful liquidations. To mitigate this, PrimeFi likely uses robust oracles (Chainlink) and has an emergency admin who can pause markets if needed. Users are assumed to understand that borrowing carries liquidation risk and that maintaining a buffer above minimum collateral is prudent.

Interest Rate Model Limits: The two-slope interest model is designed to keep utilization below 100%, but in edge cases (e.g. sudden liquidity withdrawal or no liquidity for an asset), utilization could hit 100% and rates would max out. The algorithm assumes that such extreme rates will attract corrective action (either new deposits because of high APY or repayments because of expensive debt). There is a constraint that the model cannot exceed certain rates (and the smart contract uses Ray math with finite precision), so extremely high utilization should be temporary. The platform also sets a maximum stable borrow rate portion (in the LendingPool initialization, e.g. 25% of liquidity can be taken at stable rate by default) to ensure not all liquidity is locked at stable rates, maintaining some flexibility in the pool.

Reserve Factor and Treasury: A small portion of interest (governed by reserveFactor) is diverted as protocol revenue. This is assumed to be managed or re-distributed by PrimeFi (for example, it could fund the NFT profit sharing or other rewards). The reserve factor reduces lender APY slightly, but is important for the protocol’s sustainability. It’s assumed that this factor is set to a reasonable value (e.g. 10% or less) so that lender incentives remain strong. Changes to the reserve factor or interest model would require contract upgrades or governance actions.

Rewards Distribution Assumptions: The PRFI reward emission schedule and allocation points are set by PrimeFi and can be adjusted. The algorithm’s security assumes that the ChefIncentivesController is only operated by authorized accounts (it has owner and pool configurator restrictions). Users can trust that the reward parameters (emission rate, pool weights) won’t be arbitrarily changed without notice. However, inflationary rewards carry economic risk: the value of PRFI tokens could fluctuate, and high emissions could lead to fast token inflation. PrimeFi mitigates this by using time-based emission schedules (which can decrease over time or be adjusted) and by introducing locking mechanisms (the MultiFeeDistribution may encourage users to lock rewards for boosted yields, reducing immediate sell pressure).

Eligibility and Gaming Prevention: The presence of an eligibility check and disqualification system in the rewards controller indicates an assumption that some users might try to game the system (for example, Sybil addresses not holding required NFTs or attempting to farm rewards without “qualifying”). PrimeFi’s contracts assume that the off-chain or on-chain criteria (like NFT ownership, KYC, or other requirements managed by IEligibilityDataProvider) are correctly maintained and updated. If a user is disqualified, the system will stop their rewards – there is an implicit trust that the disqualification process is fair and that re-qualification is possible when criteria are met. A BountyManager may be in place to reward those who catch abuse or to handle the slashing of disqualified accounts, which suggests an additional assumption that community monitoring is part of security. Users should be aware that certain behaviors (like immediately selling all earned tokens or moving funds in a way that violates terms) might lead to loss of future rewards.

Smart Contract Risk: PrimeFi’s contracts are upgradeable (using proxy patterns as seen with the VersionedInitializable base). This allows improvements but also means users trust the PrimeFi team or governance not to introduce malicious changes. The algorithm described assumes the contracts behave as coded in the audited version (largely inherited from Aave for core functions, which is a positive sign). Any upgrades should be carefully reviewed by the community. There is also the general risk of smart contract bugs – e.g., a logic error in the interest calculation or reward distribution could cause fund misallocation. PrimeFi mitigates this by using battle-tested Aave code for lending and by presumably auditing the newer components (rewards, NFT integration). Nonetheless, users should only supply funds they can afford to lock and should keep an eye on platform announcements.

In summary, PrimeFi’s algorithm stands on the robust foundation of Aave’s money market design, enhanced with a multi-chain reward system. The design assumptions (reliable oracles, rational economic responses to rates, honest reward parameters) align with industry standards for DeFi protocols. Understanding these mechanics and risks – interest rate fluctuations, collateral requirements, and the nuances of the rewards system – is crucial for developers and advanced users to engage safely with PrimeFi’s platform. By adhering to these algorithmic rules and risk frameworks, PrimeFi aims to sustainably blend lending yields with incentive-driven growth, providing an innovative yet secure DeFi experience.