What are the economic risks of DeFi lending protocols? How are these monitoring risks?

Author: Pedro M. Negron, Medium; Compiler: Deng Tong, Golden Finance

Decentralized finance (DeFi) introduces financial protocols that allow direct lending on its platform, enabling users to Lending and borrowing assets without relying on traditional intermediaries.

These protocols primarily use smart contracts, which are self-executing agreements with contract terms encoded directly into them, thereby increasing transparency and security. Lenders provide their assets to liquidity pools and receive interest as compensation, while borrowers can obtain loans by providing collateral. The interest rate is usually determined by an algorithm that shows the supply and demand dynamics of the assets in the pool.

This article examines the economic risks associated with DeFi lending protocols, identifies their most vulnerable points, and discusses effective ways to monitor DeFi risks. In this article, we’ll look at indicators that highlight activity within the Aave protocol, the largest lending protocol in DeFi.

Lenders and Borrowers

The main financial risk of a deposit loan agreement is the possibility of failure to recover the assets Sex, which usually occurs when a borrower fails to repay a loan.

DeFi protocols currently operate on an over-collateralized basis, meaning borrowers must pre-post a certain percentage of collateral for the amount they borrow. If the value of borrowed funds falls below this threshold, a mechanism is activated to seize the borrower's collateral to protect the lender's assets.

Source: IntoTheBlock's Risk Radar

These two indicators are designed to monitor loan categories that are at risk of liquidation. The indicator "Health Factor Distribution" on the left displays the health factor of a loan position as an indicator that reflects the safety level of a borrower's position by calculating the ratio of collateral held to the amount borrowed. Users’ collateral is categorized based on their respective health factors. A health factor above 1.50 indicates a low risk level for the protocol. Monitoring the amount of collateral within each health factor category is useful for tracking purposes. Understanding a plan's exposure levels within each health factor range can help reduce risk if prices suddenly drop.

The indicator on the right shows the value of loans secured by volatile assets with liquidation thresholds within 5%. This information can help users understand the protocol and high-risk loans for a specific pool, and enable liquidators to predict future liquidations. If the value of the collateral falls or the price of the loaned asset rises, the chance of liquidation increases, so loans within just 5% of the liquidation threshold are considered high risk. By pinpointing loans with liquidation rates below 5%, investors and users can gain a clearer understanding of the associated risk levels, helping them make informed decisions about depositing or using the protocol.

Liquidator

In the Aave protocol and most lending protocols in DeFi, he is responsible for monitoring and ensuring The individual who repays the loan from the borrower is called the liquidator. A liquidator is responsible for liquidating a loan if the value of the collateral provided by the borrower for the loan falls below a predetermined threshold. Maintaining a strong and active group of liquidators within the protocol is critical to ensuring the viability of the protocol.

Source: IntoTheBlock's Risk Radar

Liquidation volume refers to forfeitures when a borrower fails to repay a loan and the total amount of funds sold. This metric provides insight into the level of risk within the system, with higher liquidations indicating that more borrowers are defaulting on their loans, thereby exposing the protocol to greater risk. Additionally, it demonstrates the value that a liquidator captures to protect the agreement from bad debts.

Whale Activity

The actions and trends of large holders (whales) are also important to the economic security of the protocol. Crucial. Their activity in the market can quickly affect various markets and change interest rates significantly.

If the incentives for liquidators are not sufficient to motivate them to process orders, then large-scale liquidation of whales may lead to bad debts on the protocol. Therefore, it is recommended to continuously monitor their activities and the markets they cover when participating in a protocol.

Source: IntoTheBlock's Risk Radar

These two indicators provide a comprehensive view of the current behavior of whales within the protocol Overview. From a borrower's perspective, analyzing liquidation history allows you to assess the risks associated with lending to a protocol. Additionally, by examining repayments and total debt, users can evaluate whales’ past interactions with the protocol and try to predict their typical behavior. Additionally, current loan shares enable liquidators and lenders to predict situations in which whales may be liquidated.

From the supply side, borrowers can monitor lenders’ share of supply and estimate liquidity withdrawals and their potential impact on lending rates. Users can also look at the largest depositors and analyze their borrowing capacity relative to their deposits, which can provide useful information when investigating lenders' leverage on protocol deposits.

Insight into the power of monitoring metrics

In summary, the DeFi ecosystem, especially lending protocols like Aave, runs on complex mechanisms involving borrowers, lenders, and Liquidators play a critical role in maintaining the health and safety of the system.

Monitoring metrics such as health factor distribution and liquidation volume can provide valuable insights into a protocol’s risk level and the efficiency of its liquidation process. The behavior of large depositors or “whales” can have a significant impact on market dynamics and the economic well-being of the protocol. Ongoing monitoring is required to mitigate risks associated with large-scale liquidations and interest rate fluctuations. Understanding the interactions between borrowers and lenders and analyzing the activities of the largest savers helps users assess borrowing risks and the potential impact of liquidity changes on the ecosystem.