Rate Mechanism

The JamFi rate mechanism defines how interest rates for borrowing and yields for liquidity providers are determined inside the protocol. Its primary goal is to keep supply and demand in balance, while maintaining predictable outcomes for both sides of the market. Instead of fixed percentages, JamFi relies on dynamic rates that adapt to market conditions such as pool utilization, collateral ratios, and asset volatility. This creates a system where borrowing remains affordable, liquidity remains attractive, and risks are minimized.

Core Components of Rate Formation

Rates in JamFi are determined through a combination of three elements: the base rate, utilization adjustments, and risk premiums. The base rate acts as a starting point and differs across asset types — stablecoins like USDT generally start lower (3–5% for borrowers, 10–15% APY for lenders), while volatile assets such as ETH are set higher to account for additional risk. On top of that, the utilization adjustment constantly recalculates rates depending on how much liquidity in the pool is in use. If demand is high and utilization climbs above the optimal 70%, borrowing becomes more expensive to attract new liquidity providers. Conversely, when utilization falls, rates are reduced to encourage borrowing activity.

The third layer is the risk premium, which is tied to collateralization levels and asset volatility. Assets with higher volatility or loans with lower collateral ratios incur additional rate increases, ensuring lenders are properly compensated for risk exposure. Combined, these three components make rates dynamic and responsive, preventing imbalances that could destabilize pools.

Calculation Logic

The formula used in JamFi is transparent and auditable on-chain:

Effective Rate = Base Rate × Utilization Multiplier × Risk Adjustment + Revenue Share Bonus

The utilization multiplier rises when pool demand exceeds targets and decreases when liquidity is underused. Risk adjustment scales with collateral quality and volatility indexes, applying higher premiums to unstable assets. Finally, the revenue share bonus rewards lenders by distributing part of protocol fees as extra yield, further aligning incentives. This approach ensures that every participant sees a clear link between market conditions and the rates they receive or pay.

Practical Scenarios

To illustrate, consider two examples. A borrower taking a USDT loan in a pool with 80% utilization and a 130% collateral ratio would face an effective borrowing rate of around 4.7% instead of the 4% base. This increase reflects healthy demand and a balanced collateral profile. Meanwhile, a lender contributing ETH liquidity into a pool with 90% utilization could see their yield climb from a base APY of 20% to above 40%, once risk and utilization adjustments are applied. These cases show how the mechanism flexibly rewards liquidity providers during periods of high demand while still keeping borrowing costs within reasonable limits.

Governance and Flexibility

JamFi’s rate mechanism is not static. All parameters — from base rates to utilization thresholds — are subject to adjustment through the DAO. This means the community can adapt the framework to shifting market environments without disrupting stability. Governance control ensures that rate policy remains transparent, accountable, and directly aligned with the interests of token holders.

Integration with the Ecosystem

Rates do not exist in isolation. Borrowers who hold or stake $JAMI benefit from reduced interest costs, while lenders see their APY boosted by additional multipliers tied to token holdings. Refinancing tools allow borrowers to restructure loans when market conditions change, and the analytics dashboard provides predictive models for rate movements. In this way, the rate mechanism becomes tightly interconnected with staking, governance, and the overall liquidity strategy of JamFi.

Risk Management

To safeguard the system, JamFi applies several protective measures. Borrowing rates have hard caps to prevent debt spirals in extreme conditions. Oracle data comes from multiple trusted sources to reduce manipulation risks. Liquidity providers are additionally protected through insurance pools that cover potential losses caused by abnormal volatility. Every formula and adjustment rule is coded into smart contracts and available for public audit, giving users full visibility into how rates are set and enforced.