Risk Monitoring

Status: Draft Last Updated: 2026-02-07

Purpose

Monitoring provides early warning, situational awareness, and accountability. This document defines the metric categories, stress testing approaches, anomaly detection, and escalation procedures that complement the quantitative risk framework.

For which beacons compute which metrics, see sentinel-integration.md. For sentinel formation architecture, see trading/sentinel-network.md.

Key Metrics

Solvency Metrics

System Collateral Ratio

Total Collateral Value / Total USDS Outstanding

Fundamental measure of system health. Must remain well above 100%.

Collateral Coverage by Tier Distribution across quality tiers. Higher Tier 1 concentration = more robust.

Surplus Buffer Accumulated surplus available to absorb losses before affecting USDS holders. The TMF targets Aggregate Backstop Capital at 1.5% of total USDS supply post-Genesis (see Appendix C). During the Genesis phase, the interim target is $125M.

Liquidity Metrics

USDS Liquidity Redeemability and tradability across venues.

Collateral Liquidity Depth and spread data for liquidation scenarios.

Redemption Capacity Maximum stress redemption before stability impact.

Concentration Metrics

Single Asset Exposure Maximum exposure to any single collateral asset. Governed by category caps (correlation-framework.md).

Counterparty Concentration Exposure to any single counterparty (custodian, issuer, protocol).

Correlated Asset Exposure Exposure to assets that move together. See correlation-framework.md.

Stress Metrics

Value at Risk (VaR) Loss at various confidence levels.

Liquidation Cascade Risk Probability of liquidations triggering further liquidations.

Oracle Failure Impact Consequences of price feed failure or manipulation.

Operational Metrics

Liquidator Activity Active, well-capitalized liquidators available.

Keeper Health Operational keepers performing their functions.

Oracle Freshness Price feeds current and accurate.

Monitoring Infrastructure

Stress Testing

Scenario Analysis

Test against specific scenarios:

• 50% price drop in major collateral
• Liquidity crisis (no buyers)
• Oracle failure or manipulation
• Mass redemption event
• Coordinated attack

Historical Stress Tests

Apply historical crisis conditions:

• March 2020 COVID crash
• May 2021 crypto crash
• Terra/Luna collapse
• FTX contagion

Monte Carlo Simulation

• Random price paths with varying correlations
• Tail event modeling
• Distribution of outcomes

Reverse Stress Testing

Work backwards from failure:

• What conditions cause insolvency?
• How likely are those conditions?
• What is the margin of safety?

Anomaly Detection

Not all risks surface as threshold breaches.

Escalation Procedures

Severity Levels

Escalation Path

1. Automated detection (lpla-checker, warden sentinels)
2. Sentinel formation review
3. Human operator notification (if needed)
4. Governance notification (if needed)
5. Emergency powers (if needed)

Continuous Improvement

Post-Event Analysis

After every significant event: what happened, what monitoring caught, what it missed, how to improve.

Metric Evolution

Add new metrics as risks evolve. Retire metrics that aren't useful. Refine thresholds based on experience.

Encumbrance Ratio Enforcement

[Future — governance proposal required]

The target encumbrance ratio is ≤90% (TRRC / TRC). Agents exceeding this threshold face restrictions until compliance is restored. The specific penalty schedule requires a governance proposal; likely mechanics include:

• Rate limit reduction — automatic scaling of PAU rate limits proportional to overshoot
• New deployment freeze — no new positions until ratio returns below threshold
• Mandatory deleveraging timeline — escalating timeline to restore compliance (e.g., 7 days for minor breach, 48 hours for severe)
• Governance notification — automatic escalation via lpla-checker alerts

The enforcement mechanism should be calibrated to avoid pro-cyclical forced selling while maintaining capital discipline.

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