Liquidation and How to Prevent It

No more CRE or Confidential Workflow fundamentals today — we jump straight into the new case study. But because it involves quite a few DeFi finance concepts, let’s spend some minutes getting them clear first.

Overcollateralized Lending: The Foundation of DeFi Borrowing

In DeFi lending protocols like Aave and Compound, borrowing works through overcollateralization:

You deposit $10,000 worth of ETH as collateral
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The protocol lets you borrow up to a certain ratio (say, $7,000 USDC)
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Your collateral must always "sufficiently cover" your debt

Why overcollateralization? Because the protocol has no identity information about you and no way to chase you for repayment — the collateral is the only guarantee.

Three Key Metrics

1. LTV (Loan-to-Value)

LTV = debt value / collateral value

Example:

• deposit $10,000 of ETH
• borrow $7,000 USDC
• LTV = $7,000 / $10,000 = 70%.

Each collateral asset has a maximum LTV (say, 75%) that determines how much you can borrow at most.

2. Liquidation Threshold

The liquidation threshold is a line slightly above the max LTV (say, 78%).

When your LTV crosses the liquidation threshold, the position is deemed undercollateralized, and anyone can liquidate it.

3. Health Factor (HF) ⭐

This is the most commonly used risk metric:

                     collateral value × liquidation threshold
Health Factor (HF) = ────────────────────────────────────────
                               debt value

Example:

• $10,000 of ETH collateral
• Liquidation threshold: 78%
• Loan $7,000 debt
• HF = 10000 × 0.78 / 7000 ≈ 1.11.

⚠️ HF moves with prices. ETH price drops → collateral value shrinks → HF falls → danger when it approaches 1.0. This is what drives “liquidation cascades” during periods of high crypto market volatility.

What Liquidation Costs You

When HF < 1, a liquidator can:

1. Repay part of your debt on your behalf (say, 50%)
2. Seize collateral worth the repaid amount plus a bonus (the liquidation bonus, typically 5%–10%) at a discount

For the borrower, liquidation means:

• 💸 Liquidation penalty: the collateral seized is worth more than the debt repaid
• 📉 Forced selling at the bottom: your collateral is sold during a market crash — precisely the worst price
• 🔒 Loss of the position: if the market rebounds afterward, you no longer have collateral to benefit

How to Prevent Liquidation

The core idea is one sentence:

raise your HF before it gets close to 1.

There are two broad approaches:

Approach 1: Increase collateral (grow the numerator)

Approach 2: Reduce debt (shrink the denominator)

Manual vs. Automated

The problem with manual defense: if liquidations happen at 3 AM, within minutes. When price crashes, going from HF 1.15 to liquidated can take just minutes — far too fast for a human to react.

So you need automation — a system that monitors risk signals 24/7 and executes defensive actions as danger approaches. That’s exactly where CRE shines.

Why the Defense Strategy Needs to Be “Confidential”

Automated liquidation protection has a subtle game-theoretic problem:

If your defense strategy is public, it can be exploited.

• If the market knows “this address adds collateral whenever HF drops below 1.25,” attackers can manipulate prices against you, anticipate your moves, and front-run them.
• If your reserve size and deployable capital caps are public, an adversary can calculate exactly “how much capital it takes to push you past the liquidation line”.
• Your exchange credentials and strategy parameters (target HF, deployment caps, sequencing preferences) are all high-value intelligence.

So a production-grade automated liquidation protection system needs:

1. Automation: 24/7 monitoring + automatic execution → CRE Workflow
2. Confidentiality: thresholds, strategy, and credentials hidden from node operators → Confidential Workflow

Key Takeaways

What’s Next

With the concepts clear, let’s look at Case Study 2: an Automated Liquidation Protection system built with a CRE Confidential Workflow.