Thanks for the proposal, @monet-supply. As you mentioned, our data science team is conducting research into optimizing interest rate curves and will publish our methodology this month. We also mention in our post that our early research suggests we will be targeting stablecoin markets.
Our data science team is continuing to analyze, but one initial question I personally have is: are you concerned with the 90% optimal utilization? Although it may not have been a problem in the past, the risk is heavily dependent on dynamic factors, including user positions. If supply is heavily concentrated in several users, then (depending on size and collateralization ratio, etc), a 90% utilization may interfere with atomic liquidations should that utilization be reached.
Taking an initial look at Gauntlet’s Analytics Dashboard, there might be some concerns with large positions with all except the most developed assets. Of course, looking at individual positions can tell a different story.
In addition, can you provide a bit more color on how you decided the max borrow rates? The max rate would need to balance several factors, including:
- High enough to prevent utilization above the optimal utilization
- Not high enough as to push accounts toward liquidation (which can spiral into cascading liquidation)
- Balancing borrower UX (predictable borrow rates)
The revenue piece is important here because Aave’s safety module provides a potential backstop to insolvencies. As a result, reserves on Aave are not only a source of insolvency backstop but a source of protocol revenue as well.