Comprehensive Risk Management Services Proposal by Chainrisk
1. Previous Work with Compound
Chainrisk conducted a comprehensive economic audit of Compound V3 on the Arbitrum One Chain as part of the Compound Grant Program (CGP) on April, 2024, with regular updates and active engagement on the grant forum. The audit focused on optimizing risk management and enhancing protocol stability through advanced simulations and stress tests within the USDC market, targeting collateral assets such as Wrapped Ether (WETH), Wrapped Bitcoin (WBTC), GMX, and Arbitrum (ARB). The final report, shared with the community, provides an in-depth overview of Chainriskâs risk methodology, offering valuable insights into how these recommendations enhance the protocolâs resilience and ensure its sustainable growth in the decentralized finance ecosystem.
Over the past few months, Chainrisk has been actively engaging during the biweekly community calls, provided market analysis on weETH and deUSD & sdeUSD, and parameter recommendations for new market deployments on Ronin and Sonic.
2. Executive Summary
Chainrisk proposes a state-of-the-art risk management solution for Compound Finance, designed to optimize protocol safety, capital efficiency, and sustainable growth. Our comprehensive approach leverages advanced quantitative methodologies, machine learning algorithms, and protocol-specific risk models to test Compound V3 (Comet) Modules and new protocol upgrades in various market scenarios.
Key Highlights:
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Chainrisk will serve as a secondary risk management provider alongside Gauntlet for all new and upcoming markets on Compound V3, with a special focus on longer-tail assets. We are committed to transparency by making our reports and analyses publicly accessible to enhance community engagement.
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Chainrisk will deliver comprehensive Quarterly and Annual Risk reports that will encompass our risk management framework, analyses of newly launched markets and added assets, and detailed assessments of high-risk events, including days with elevated liquidation risk, for the Compound protocol.
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Chainrisk will provide bi-weekly data-driven recommendations for dynamic risk parameters, including but not limited to:
- Collateral Factor
- Liquidation Factor
- Liquidation Penalty
- Supply Cap
- Target Reserves
- Storefront Price Factor
These recommendations will be based on rigorous quantitative analysis and market conditions to optimize protocol safety and efficiency.
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Chainrisk will deploy an advanced real-time monitoring and alerting system, providing critical risk insights to protocol stakeholders and facilitating timely responses to market dynamics.
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Chainrisk will actively support new initiatives like âCompound Sandboxâ and mechanism design of Compound V4 to foster innovation and enhance protocol utility. We will collaborate with the WOOF team on PID controller development while applying our risk management expertise to assess risks, propose mitigations, and establish best practices for seamless integration.
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A full-time team of 6 will be dedicated to Compound with experts in Security, Statistics, Cloud and Data Science, bringing valuable experience from prestigious institutions such as the Ethereum Foundation, NASA, JP Morgan, Deutsche Bank, Polygon, Nethermind, and EigenLayer.
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A robust knowledge transfer and community engagement program will be implemented to ensure comprehensive understanding and active participation within the Compound community.
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12-month engagement (April 1, 2025 - March 31, 2026): $400k base (in USDC, streamed linearly) will serve as the payment for this phase.
3. Company Overview
Chainrisk is an end-to-end economic security & risk management company building tools and services for all Defi protocols and L1, L2s to protect value at risk. Chainrisk specializes in economic security, offering a unified simulation platform designed for teams to efficiently test protocols, particularly in challenging market conditions. Our technology is anchored by a cloud-based simulation engine driven by agents and scenarios, enabling users to create tailored market situations for comprehensive risk assessment.
Key Differentiators:
- Focus on Capital Efficiency: We prioritize enhancing the top-line of DeFi protocols by exploring innovative avenues of capital efficiency for both protocols and its users.
- Commitment to Transparency: Risk management shouldnât be a black box. Thatâs why we strive to make our analyses as public as possible, fostering trust and clarity within the DeFi community.
- Advanced Simulation Engine: Our unique dual-pronged simulation engine combines the power of Rust-based off-chain computations with real-time on-chain data, enabling us to conduct precise risk assessments and fine-tune parameters effectively.
- Community Engagement: We value community input and actively involve users in our risk management proposals. By seeking feedback, we ensure our solutions align with the communityâs needs and insights.
- Agility and Speed: Our agile team is always ready to roll out new tools and strategies quickly, helping DeFi protocols understand and mitigate risks while opening up new opportunities for capital efficiency.
4. Scope of Work for Compound Finance
This proposal outlines a comprehensive approach to enhancing risk management, governance analysis, and user experience for Compound V3.
Deliverables -
A. Risk Management and Analysis
- Complementary Risk Management
- Serve as a secondary risk management provider alongside Gauntlet for all new and upcoming Compound V3 markets ( with no limit on the number of markets ).
- Expand asset offerings by introducing new collateral types for existing base assets, adding new base assets with corresponding collateral, and actively supporting new chain deployments with full coverage of associated base and collateral assets.
- Focus on longer-tail assets to ensure comprehensive coverage.
- Comprehensive Reporting
- Deliver Quarterly Risk Reports (4 per year).
- Provide an Annual Comprehensive Risk Report.
- Include:
- Risk management framework details
- Analyses of newly launched markets and added assets
- Assessments of high-risk events, particularly days with elevated liquidation risk
- Data-Driven Recommendations
- Provide bi-weekly recommendations for dynamic risk parameters:
- Collateral Factor
- Liquidation Factor
- Liquidation Penalty
- Supply Cap
- Target Reserves
- Storefront Price Factor
- Real-Time Monitoring & Alerts
- Implement an advanced real-time monitoring and alerting system.
- Provide critical risk insights to stakeholders.
- Supporting New DAO Initiatives
- Offer risk management/mechanism design support for new DAO initiatives, including recent proposals like the Compound Sandbox development by the WOOF team and Compound V4 as a whole.
B. Community Engagement and Knowledge Transfer
- Knowledge Transfer Program
- Implement a robust knowledge transfer initiative.
- Conduct regular community engagement sessions.
- Transparency
- Ensure all reports and analyses are publicly accessible.
- Provide clear documentation and resources for community understanding.
5. Detailed Service Offerings
5.1 Proposed Risk Management Framework for Longer Tail Assets
Long-tail assets in the cryptocurrency landscape refer to digital tokens characterized by low market capitalization and trading volume, positioning them at the periphery of the market compared to dominant cryptocurrencies like Bitcoin and Ethereum. Long-tail assets often attract speculative trading strategies, where traders aim to leverage short-term price movements in these less liquid markets.
Long-tail assets play a pivotal role in portfolio diversification, offering exposure to niche sectors within the cryptocurrency ecosystem. This category encompasses various tokens such as liquidity provision (LP) tokens, liquid restaking tokens (LRTs), liquid staking tokens (LSTs), real-world assets (RWAs), and vault tokens. While these assets hold the promise of high returns, their limited presence on mainstream decentralized finance (DeFi) platforms underscores the necessity for robust risk management strategies.
Read here for detailed analysis for onboarding long-tail assets.
5.2 Risk Monitoring and Alerting Dashboard
Chainrisk proposes to develop a comprehensive risk monitoring and alerting dashboard for Compound, focusing on real-time user positions, market dynamics and simulations. This powerful tool will provide valuable insights for both the protocol and its users, enabling them to make well-informed choices about their respective positions and strategies.
Key Features
Protocol Risk Analysis
The dashboard will offer in-depth protocol and market-specific risk analysis, including ( but not restricted to ) :
- Supply and borrow metrics per asset per market
- Asset-specific Utilization rates
- Asset distribution for supply and borrow
- Value at Risk (VaR) and Liquidations at Risk ( LaR ) calculations per market
- Protocol reserves distribution
- Identification of accounts at risk of liquidation
- Market Risk Alerts
User Analysis
To enhance user experience and decision-making, the dashboard will provide:
- Real-time user metrics
- User wallet breakdown and distribution
- Individual user health scores
- Simulations of user health based on asset price fluctuations
This comprehensive user analysis will enable Compound users to better understand and manage their positions.
6. Technical Implementation
The Chainrisk Simulation Engine is a sophisticated, modular testing environment designed to conduct high-fidelity simulations of DeFi market scenarios. It comprises two key components:-
- RiskEVM: A high-performance, Rust-based simulation engine optimized for computationally intensive tasks. RiskEVM models complex protocol interactions, including borrowing, lending, and liquidation events under various market conditions. This component enables a comprehensive assessment of protocol behaviour and stability, particularly during periods of market stress.
- On-Chain Simulation: This component executes backtests on forked mainnet networks, ensuring simulation accuracy and fidelity to real-world scenarios. By leveraging actual on-chain data, it evaluates protocol responses to diverse conditions, providing insights into resilience and potential vulnerabilities.
The integration of these components allows Chainrisk to identify potential risks and optimize parameters with a high degree of precision. This dual-pronged approach combines the efficiency of the Rust-based simulation engine with the accuracy of on-chain data, enabling robust risk assessment and parameter optimization for DeFi protocols.
Read here for detailed technical architecture of Chainrisk Simulator and Cloud Architecture.
7. Performance Metrics and KPIs
Financial Metrics
- Growth in Supply Volume: Monitor the increase in the total supply volume as a key indicator of market engagement and expansion.
- Revenue Growth: Track the increase in revenue due to introducing new markets.
- Community Adoption: Track the borrowing activity as a measure of market adoption and liquidity utilization.
Community Engagement and Satisfaction
- Community Net Promoter Score (NPS): Survey the community to gauge satisfaction with the Compound-Chainrisk relationship.
- Community Engagement Metrics: Track community participation in security-related discussions, forums, and educational initiatives.
8. Timelines
- For new Comet deployments on existing chains, risk recommendations will be delivered within one week.
- For new chain deployments on Compound, recommendations will be provided within two weeks from the date the proposal is listed on the forum.
9. Fee Structure
Compensation
- We will be utilizing the Compound Aera Vault and Llama Pay for the payment process. The payment stream will be executed on a per-second basis over a period of twelve months, from April 1, 2025 to March 31, 2026.
- A total of $400,000 USDC will be distributed during this period. Given the exact duration of 31,449,600 seconds, this results in a payout rate of approximately 0.01272 USDC per second.
- Early Termination Clause: Compound DAO can terminate the contract after 6 months (October 1, 2025) if unsatisfied with progress. In the event of early termination: Base compensation will be prorated for completed months
10. References to Previous & Upcoming Work
You can find in this section links to our work:
Research from the Team - Chainrisk Simulation Engine | Chainrisk VaR Methodology | DeFi Lending & Borrowing Risk Framework | Multi-Agent Influence Diagrams ( MAIDs ) for DeFi Governance | MAIDs Video
11. Conclusion and Next Steps
We would go ahead with a Temp Check proposal for comprehensive risk management services proposal on Compound, to understand the sentiment of the DAO. Please share your comments and suggestions below. Thank you for your active participation in our proposal.
Regards
Team Chainrisk