This new tool aims to address risks in DeFi protocols

Despite offering revolutionary financial services, the decentralized finance (DeFi) sector has been plagued by a number of risks and exploits. According to IntoTheBlock, the DeFi ecosystem lost a staggering $58.78 billion from 2020 to 2023 due to exploits.

This alarming figure highlights the critical need for effective risk management strategies within the DeFi ecosystem.

Risk Management Challenges in DeFi Protocols

DeFi risks predominantly fall into two categories: technical and economic.

  • Technical risks involve potential vulnerabilities in the protocol code that malicious actors can exploit. This has been highlighted by incidents such as the DAO hack and the Ronin Network bridge exploit.
  • Economic risks are related to imbalances in the supply and demand dynamics of protocols, leading to losses for depositors. For example, the collapse of Earth and the FSO and oracle manipulation attacks.

In this context, IntoTheBlock introduced the DeFi Risk Radar, which presents intriguing development risk management. This tool aims to provide transparency by aggregating DeFi data and making it more accessible and understandable. It offers a real-time overview of assets and market conditions.

The platform includes risk dashboards with quantitative risk signals for individual DeFi protocols and markets, and programmable APIs for monitoring DeFi protocols. For example, in Automated Market Maker (AMM) protocols like Curve, users can find valuable signals such as slippage or active arbitrage position addresses. Similarly, in lending protocols, several signals identify conditions such as liquidations or the accumulation of bad debt in a lending market.

Considering the high stakes involved in deploying capital, the importance of such a tool in the DeFi ecosystem cannot be understated.

“Liquidations, slippages, depegging scenarios, temporary losses, and many others are responsible for hundreds of millions in losses in DeFi protocols every year. Investors, and particularly those deploying capital into DeFi at scale, need ways to model and manage these risks. For this reason, we expect risk management to become a key element in the next phase of DeFi,” IntoTheBlock head of research Lucas Outumuro told BeInCrypto.

However, it is essential to maintain a critical perspective on such developments. While the DeFi Risk Radar offers comprehensive insights, its effectiveness in real-world scenarios remains to be carefully evaluated.

How to detect risks in established ecosystems

To illustrate the effectiveness of IntoTheBlock’s DeFi Risk Radar, let’s consider the case of Avalanche. It is a major layer 1 blockchain that encountered a delicate situation in March 2023.

With a total value locked (TVL) close to $1 billion, Avalanche’s native token, AVAX, has found itself in a precarious position, featuring a market capitalization of $100 million and an estimated daily trading volume of 3 Millions of dollars.

The risk in the Avalanche ecosystem was particularly complex. For example, some protocols allowed borrowing sAVAX, a staked version of AVAX. This feature has inadvertently set the stage for potential economic attacks. Indeed, an attacker could exploit this situation by borrowing sAVAX, selling it on the open market, and simultaneously initiating a perpetual short hedge against it.

This strategy could trigger a domino effect, potentially leading to cascading liquidations of sAVAX and the decoupling of sAVAX from native AVAX. This is a particular scenario that has occurred before with notable price disparities.

Radar indicators of DeFi risk. Source: IntoTheBlock

IntoTheBlock’s DeFi Risk Radar could theoretically help identify and mitigate such complex risks. Indicators such as health factor distribution and high-risk loans are particularly relevant in this context. They could help investors monitor liquidable positions above a certain threshold, such as those with a health factor below 1.10, which could have a significant impact on protocol markets and trigger cascading liquidations.

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