This site uses cookies. Browsing the site, you agree to the use of cookies. If you need more information, please visit the Cookies Policy page

Русский

English

Enter / Registration

Cryptocurrencies: 9524 / Markets: 111839

Market Cap: $ 3 723 375 175 369 / 24h Vol: $ 245 515 881 392 / BTC Dominance: 58.355960987802%

Н News

A risk-first approach to DeFi

The following is a guest post and analysis from Vincent Maliepaard, Marketing Director at IntoTheBlock.

DeFi has matured into a complex web of lending markets, stablecoin ecosystems, and liquidity pools. While this growth comes with a broad range of opportunities, new forms of risk can emerge suddenly and require significant expertise to navigate effectively.

The Growing Complexity and Volatility of DeFi Markets

The DeFi market has grown significantly over the past years, and currently boasts around $88 billion in total value locked. However, the space is also fragmented, with hundreds of DeFi protocols across different chains, some with strong user bases and a good track record, and others with more novel designs. This complexity requires a well-thought out risk management framework that considers the most common economic risk in a variety of ways. To help put you in the right mindset, let’s consider a few major risk events that could occur.

Sudden Liquidity Crunches: In times of market stress, lenders often rush to withdraw funds, causing utilization in lending pools to skyrocket. For example, in March 2023 the DAI market on Aave reached near 100% utilization, forcing interest rates to spike sharply to entice repayments and new deposits – a mechanism that barely averted a liquidity crunch. Without such intervention, users remaining in the pool might have found themselves unable to withdraw as liquidity dried up.
Stablecoin Depegs: Stablecoins can lose their peg with little warning, sending shockwaves through markets. A notable case occurred on April 2, 2025, when First Digital USD (FDUSD) – normally fixed 1:1 to the dollar – plunged to $0.93 after allegations of insolvency against its issuer. Such depeg events not only erode trust but also threaten any protocols or liquidity pools relying on that stablecoin (e.g. causing imbalance in Curve pools and panic withdrawals).
Cascading Liquidations: A sharp price drop in a major asset can trigger chain-reaction liquidations across DeFi lending platforms. Falling prices force leveraged positions to unwind, which can depress prices further and liquidate even more loans in a vicious cycle. For instance, the “Black Thursday” crash of 2020 where a 50% single-day drop in ETH led to a wave of liquidations and even protocol insolvencies.

These examples show how quickly things can go wrong if you’re not on top of a wide range of risk metrics relevant to your positions. Sudden liquidity shortfalls, peg breaks, and mass liquidations highlight the need for continuous, in-depth risk monitoring. In fast-moving markets, timing is everything – by the time an average investor reacts to Twitter rumors or price charts, the damage might already be done.

Spotting Risk Early in Aave

Aave, one of DeFi’s largest money markets, is a key protocol to watch when determining potential risks in the market. If you’re an institutional investor in DeFi, chances are high you’ve deployed capital in the protocol. But even if you’re not deploying into Aave, the protocol’s strong position could be important when watching out for potential risk events in the broader market. Let’s take a practical example of how you’d watch for risk on Aave.

High-Risk Loan alerts on Aave

We can categorize each loan on Aave by a health factor (based on collateral vs. debt); when that health factor approaches 1.0 (the liquidation threshold), the loan is at high risk of being liquidated.

A sudden increase in high risk loans can be the result of extreme price movements, causing the collateral in the loans to drop. When this is significant enough, it can force liquidations and even create cascading liquidations as mentioned before. Continuously monitoring the amount of high risk loans is somewhat impractical, but nonetheless essential. Tools like IntoTheBlock’s risk Pulse can help spot these conditions automatically, as shown in the example below.

Watching Liquidity Flows

Another key signal on Aave is large movements of assets into or out of the protocol. Peaks in liquidity flows, specifically in outlfows, can indicate risk conditions. For instance, a large withdrawal of WETH from Aave may suggest that a whale is pulling collateral, perhaps out of concern over market volatility or to deploy elsewhere.

This sudden outflow can tighten the available liquidity on Aave. If a lot of WETH is taken out, there’s less WETH liquidity to borrow, and utilization for remaining WETH might shoot up, driving interest rates higher.

Conversely, a surge of WETH deposits could temporarily boost Aave’s liquidity and signal that big players are gearing up to lend or provide collateral for borrowing.

Watching Liquidity Flows

Conversely, a surge of WETH deposits could temporarily boost Aave’s liquidity and signal that big players are gearing up to lend or provide collateral for borrowing.

Source: Aave Risk Analytics

Both scenarios carry implications: a liquidity drop raises the risk of higher slippage or inability to withdraw for others, whereas a big influx might precede increased borrowing (and leverage in the system).

Curve: Depeg Alerts and Market Depth Changes for Stablecoin Pools

Another leading DeFi protocol is Curve. Curve is the backbone of stablecoin liquidity in DeFi, hosting pools where users trade and stake stablecoins and other pegged assets. By design, Curve pools are stable swap pools meant to hold assets at equal value, which makes any depeg event or imbalance immediately concerning. Risk monitoring on Curve focuses on peg stability and market depth: essentially, are the assets in the pool holding their expected value, and is there sufficient liquidity on each side of the pool?

Depeg Risks

When a token in a Curve pool drifts from its intended peg, LPs are often the first to feel the impact. A small price deviation can quickly spiral into a pool imbalance — the depegged asset floods the pool as others exit, leaving LPs holding the riskier side.

Recent events like FDUSD’s depeg on April 2, 2025, highlight the importance of rapid detection. As redemptions hit and rumors spread, FDUSD-heavy Curve pools skewed sharply. LPs caught unaware faced mounting impermanent loss and poor exit liquidity.

Source: Curve Risk Analytics

Early alerts flagging the initial drift (e.g., FDUSD < $0.98) would have given LPs time to exit or hedge.

And it’s not just fiat stables. Staked tokens like sdPENDLE have also shown dislocations in Curve. When these wrappers slip in price versus their underlying assets, their share in pools can balloon, a signal that LP risk is rising fast.

Source: Curve Risk Analytics

Liquidity Depth as a Signal

Curve risk isn’t only about price, it’s also about depth. When liquidity in a pool is thin, slippage worsens, and the ability to swap out becomes constrained. It’s therefore crucial to watch for sudden shifts in pool liquidity. There’s a couple of reasons why you might see a sudden shift in liquidity. The most obvious answer is that market events, like extreme price moves, cause uncertainty, which causes people to withdraw their liquidity.

An often less explored factor is that pool liquidity can consist of just a few large providers, meaning that just a few entities withdrawing can significantly alter market depth, exposing you to risk.

Source: Curve Risk Analytics

For funds managing liquidity on Curve, real-time alerts that combine large transactions with depth changes are critical. They offer a chance to exit, rebalance, or even deploy capital to stabilize the peg, before the rest of the market catches up.

Whale Concentration: Large Players that Move Markets

One recurring theme in the above discussions is the outsized influence of whale investors, entities or addresses that control very large positions. Whale behavior can move markets or distort liquidity precisely because of their scale.

On-chain analytics reveal these “whale concentration” risks by flagging pools where a few large lenders dominate. If three addresses supply half a pool’s liquidity, that pool is fragile: the first whale to exit could lock everyone else in until fresh capital arrives or high rates force borrowers to repay.

The post A risk-first approach to DeFi appeared first on CryptoSlate.

Source

Н News

A risk-first approach to DeFi

The Growing Complexity and Volatility of DeFi Markets