Base cases: Morpho, AAVE, Compound

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Overview

Current crypto lending needs humans to vote on every little change, like updating interest rates or changing liquidation thresholds. With Ritual, you can build lending systems where AI reacts to the market 24/7 and adjusts everything automatically. Replace slow moving manual processes with powerful, agentic governance that is supercharged with machine learning.

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Traditional System Failures

Current lending protocols rely heavily on governance processes and manual interventions for critical parameter adjustments. Liquidation thresholds, interest rates, and other key parameters require governance votes or manual updates, leading to a predominantly reactive rather than proactive approach to market changes. This dependency on manual processes creates significant operational friction and delays in parameter optimization. The complexity of managing collateral factors creates an ongoing challenge in balancing protocol safety with user experience, as these manual adjustment mechanisms struggle to keep pace with rapidly evolving market conditions. Risk assessment capabilities in these protocols remain rudimentary and inadequate for the complexity of today’s DeFi landscape. The systems demonstrate limited ability in evaluating diverse assets and consistently fall short in predicting volatility patterns. Their reactive nature leaves them vulnerable to market shifts, particularly when dealing with exotic assets. The protocols also struggle with accurately assessing correlations between different assets, leading to potential systemic risks that could remain undetected until crisis points. Liquidation mechanisms represent another critical weakness in traditional lending protocols. These systems are prone to devastating liquidation cascades, where one forced liquidation triggers a chain reaction of further liquidations. The problem is compounded by frequent liquidity shortages during critical moments and sub-optimal timing of liquidation events. Moreover, the transparent nature of these liquidations exposes them to MEV extraction, while the need for manual intervention in critical situations creates additional points of failure and inefficiency.

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Ritual Solutions

Ritual is uniquely positioned to solve many of these issues:
  • Heterogeneous Compute:
    • ML-driven parameter optimization
    • Correlation-based risk assessment
  • Scheduling:
    • Automated parameter updates
    • Regular risk reassessment
  • Privacy Primitives:
    • Protected parameter adjustment logic
    • Secure model execution