The recent crypto market downturn (June 20–24, 2025) triggered widespread liquidations on DeFi lending platforms. Using zScore, Zeru’s onchain reputation system, we compared liquidation patterns and user behaviors on Aave and Morpho Blue between June 1–30, 2025, revealing critical insights:

• Risk Distribution: Most liquidated wallets on both platforms had zScores below 300, highlighting the predictive power of Zeru’s risk scoring.

• Behavioral Divergence: Aave users were notably active, often weakening their positions through collateral withdrawals pre-liquidation. Morpho users exhibited more passive behaviors, rarely withdrawing collateral before liquidation.

• Collateral Strategies: Over 90% of liquidated users borrowed stablecoins against volatile assets, amplifying liquidation risks during market downturns.

Score Dynamics: Scores dropped sharply post-liquidation, with Morpho users experiencing greater median declines, reflecting higher baseline risks.

• Distribution Peak: zScores mainly ranged from 100–400, with a small percentage of high-score outliers up to ~800.

• Pre-meditated Withdrawals(?): Active Aave users often withdrew collateral just prior to token value drawdowns, increasing their liquidation vulnerability.

• User Complexity: Aave features complex, multi-layered user strategies that increases risk and the need for monitoring, resulting in 9% of liquidated users experiencing repeated liquidations.

• Morpho Risk Skews Higher: Concentrated zScores between 200–250, with a sharp drop-off afterward, indicating uniformly higher-risk profiles.

• Passive Approach: Only 27% of wallets withdrew collateral pre-liquidation, demonstrating a predominantly passive user base.

• Simplicity Advantage: Fewer repeated liquidations (5%) reflect simpler, consolidated positions.

| Protocol | Positions Liquidated | Multiple Liquidations |
|:--------:|:----------------:|:---------------------|
| Aave     | 1522             | 187 wallets ( 12.28%) |
| Morpho   | 228              | 20 wallets ( 8.7%)    |

Morpho Blue saw 7 wallets experience more than two liquidation events in June, with one wallet reaching 6 liquidations in June alone. While the absolute number is small, the recurrence of liquidations within this group reveals a pattern of persistent risk exposure and limited adjustment. These wallets appear to have maintained vulnerable positions even after initial liquidations, displaying a lack of proactive intervention or system safeguards. The relatively uniform count of 3 liquidations across most cases suggests similar failure cycles, potentially due to static positions left exposed through the market downturn. Morpho’s more passive user base may lack the active monitoring or automation needed to prevent such repeated failures.

Aave exhibited 61 wallets with more than 2 liquidations in June, some reaching alarming levels—10, 16, even 28 liquidation events in a single month! This high concentration of repeated liquidations signals complex user behavior, where aggressive leveraging or automated strategies may have backfired during volatile conditions. Many wallets likely re-entered risky positions immediately after being liquidated, leading to cascading effects. This pattern reflects a more active and intervention-heavy user group, but also highlights the risks of recursive borrowing and minimal safety buffers. The sheer scale of repeated liquidation on Aave underscores the need for stronger circuit breakers, better real-time alerts, and smarter tooling to prevent compounding losses.

• Aave: 60% of wallets withdrew collateral, averaging ~26% of deposits. Proactive moves often increased liquidation risks, potentially with the intent to allow these positions to get liquidated.

• Morpho: Only 27% withdrew collateral prior to this downturn. Passive strategies suggest a lack of risk awareness or response capabilities.

• Over 90% of liquidations involved borrowing stablecoins against volatile assets on both platforms.

• Minimal stablecoin collateral setups highlight a structural vulnerability to market volatility.

| Risk Level | Score Range | % Liquidated (Aave) | % Liquidated (Morpho) |
|:----------:|:-----------:|:-------------------:|:---------------------:|
| Very High  | <200        | 26.48               | 33.33                 |
| High       | 200–300     | 26.68               | 28.51                 |
| Moderate   | 300–400     | 18.92               | 18.86                 |
| Lower Risk | 400+        | 27.92               | 19.30                 |

Morpho exhibited concentrated liquidations in high-risk categories (61% below 300), while Aave's broader spectrum affected users across various risk tiers.

| Protocol | Avg Pre-Liquidation Score | Median Pre-Liquidation Score | Avg Post-Liquidation Score | Median Post-Liquidation Score |
|:--------:|:-------------------------:|:----------------------------:|:--------------------------:|:-----------------------------:|
| Aave     | 314.6                     | 285.1                        | 289.96                     | 260.64                        |
| Morpho   | 284.17                    | 255.36                       | 294.42                     | 263.45                        |

Morpho’s lower pre-liquidation median score (255.36) indicates a generally riskier user base, but the increase to 263.45 post-liquidation suggests that some users took constructive actions—such as repaying or depositing—to improve their on-chain profiles after being liquidated.

Morpho showed expected high-risk liquidations. Users liquidated in June had heavily skewed zScore distributions (skewness: 0.993) with a low median score of 255.36. This means most liquidated users were already in high-risk categories where liquidation was predictable, with zScore’s risk model working as intended.

Aave revealed more concerning patterns. While also showing positively skewed distributions, Aave had less extreme skewness (0.637) and a higher median zScore (285.10) among liquidated users. This indicates that a significant number of users with moderate-to-good risk profiles still got liquidated, a more troubling finding.

The key difference: Morpho's liquidations were concentrated among users already flagged as high-risk, suggesting the zScore’s risk assessment was accurate. Aave's liquidations, however, extended into middle-tier users who should have been safer. This broader impact suggests that even users with decent pre-liquidation profiles faced systemic risks, possibly due to over-leveraging, delayed risk management responses, or complex trading strategies that weren't fully captured in their risk scores.

This leads to some recommendations for all DeFi protocols, not specifically Aave and Morpho.

• Real-Time Monitoring: Protocols should implement real-time risk flags and withdrawal warnings.

• Collateral Diversification: Encourage mixed collateral portfolios to mitigate market volatility risks.

Behavioral Education: Educate users on managing leverage and collateral, reducing preventable liquidations.

• Develop real-time volatility alerts and collateral withdrawal risk warnings.

• Offer targeted educational resources on leverage management and asset diversification.

• Strengthen user retention by rewarding responsible liquidity providers.

• Focus on converting passive users into active, risk-aware participants.

• Launch user engagement initiatives, such as guided borrowing and repayment challenges.

• Market its inherently simpler risk structure as a competitive advantage.

The June 2025 market downturn illuminated critical behavioral and structural differences between Aave and Morpho. By incorporating Zeru’s zScore, protocols can proactively manage risks, refine user education, and tailor incentive programs. Ultimately, reputation-based insights like these are key to building safer, more resilient DeFi ecosystems.