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Liquidity Management and AI: How Machine Learning Technology Aids Asset Distribution and Accessibility in DeFi

Liquidity management is an integral part of the decentralized finance ecosystem. Knowing which protocols to contribute liquidity to is also crucial, as the right ones could fetch decent yields, and a bad investment could ruin your portfolio. Thankfully, AI tools can now help you distribute your funds in the right liquidity pools, enabling you to make the most of profitable tokens and avoid impermanent loss.

AI and Liquidity Management: How Machine Learning Technology Aids Asset Distribution and Accessibility in DeFi - Header Picture
Liquidity Management and AI: How Machine Learning Technology Aids Asset Distribution and Accessibility in DeFi – Header Picture

In this article, we’ll be covering AI in liquidity management and how you can use this technology to your advantage. But first, let’s explain what liquidity management means.

What is Liquidity Management in DeFi?

Liquidity management in DeFi is a complex process. It refers to ensuring assets are available and adequately distributed within DeFi protocols and platforms to ensure efficient trading, lending, borrowing, and other financial activities. 

Liquidity management is critical in decentralized markets because it operates differently from the centralized crypto market. Unlike centralized exchanges where entities like Coinbase and Binance have “unlimited liquidity,” the DeFi space requires liquidity pools to function. 

How Liquidity Pools Work - Screenshot by Techopedia
How Liquidity Pools Work – Screenshot by Techopedia

A liquidity pool is a collection of assets locked in a DeFi protocol. These funds facilitate trading, lending, borrowing, and other financial activities within the DeFi ecosystem. The more liquidity available in a liquidity pool, the better it is to trade with.

On a centralized exchange, you can trade as many units of a token as possible because it uses an order book that matches your trade with a suitable order. On the other hand, decentralized exchanges use an automated market maker that lets you buy and sell tokens directly from a liquidity pool.

Liquidity pools often involve liquidity providers (LPs) depositing funds in pairs. These liquidity providers are incentivized, earning yields or rewards from transactions that occur on liquidity pools they fund.

If a liquidity pool is designed for users who want to swap ETH for DAI, liquidity providers (LPs) will have to deposit an equal value of both cryptocurrencies. 

If the same protocol has another liquidity pool, say a USDT/DAI pool, LPs will deposit equal values of USDT and DAI into that pool. Having two pools like this where DAI is a constant means that there’ll be more liquidity for the DAI token. 

Most decentralized exchanges use automated market makers to adjust the differences in token value between one liquidity pool and another. For example, if DAI’s price is lower in the USDT/DAI pool than it is in the ETH/DAI pool, arbitrage traders will be matched with these pools, making them buy DAI from the lower-priced pool and sell it on the higher-priced one, balancing the prices between both pools.

While this system seems practical, it doesn’t come without challenges.

Challenges in DeFi Liquidity Management

Volatility-induced slippage, impermanent loss, price manipulation, and liquidity fragmentation are issues plaguing liquidity management in DeFi. Let’s discuss them briefly.


Slippage in DeFi refers to the difference between a trade’s expected price and the actual executed price due to market volatility or insufficient liquidity in the trading pool. 

An example of Slippage by Binance
An example of Slippage by Binance

One of the reasons slippage occurs is low liquidity. For instance, if an ETH/DAI liquidity pool has only $10,000 and someone just sold $1000 worth of DAI, it would negatively impact DAI’s price by 10 percent because the ratio between ETH and DAI would be imbalanced. So, if you wanted to swap 100 DAI for 1 ETH when the liquidity pool had $10,000, you’d be swapping that same amount now for a slightly higher amount of ETH than the pool only has $9000. 

Impermanent Loss

Impermanent loss is a concept that directly affects liquidity providers. It is the difference between an LP’s current value in the liquidity pool and the amount they would have if they just held their assets.

An example of Impermanent Loss by CoinBrain
An example of Impermanent Loss by CoinBrain

Take an ETH/DAI liquidity pool where 1 ETH is initially worth 1000 DAI, for instance. If ETH’s price increases, more ETH is withdrawn from the pool, leaving a higher proportion of DAI. Conversely, if ETH’s price decreases, traders would withdraw more DAI, leaving a higher proportion of ETH. 

As a liquidity provider, you would experience impermanent loss when the pool’s asset composition diverges from the initial ratio, resulting in a loss compared to simply holding the assets outside the pool.

Price manipulation

Low liquidity pools are very susceptible to price manipulation. This occurs when bad actors directly influence the price of a token through several means, such as washing, pumping-dumping, and whale collusion. 

When some malicious traders know that large orders can significantly affect the token’s value, they use it to their advantage, creating orders that artificially inflate and deflate the price of assets in a liquidity pool and profiting off it.

Liquidity Fragmentation

Liquidity fragmentation occurs when liquidity is dispersed across multiple decentralized finance (DeFi) platforms, protocols, or chains in such a way that it leads to reduced market depth, liquidity provision efficiency, and price discovery. 

Liquidity fragmentation is typically supposed to be a good thing in the DeFi space as it leads to more decentralization. But when there’s insufficient liquidity for each protocol, fragmentation worsens existing problems, leading to more market volatility.

How can AI Aid Liquidity Allocation and Distribution in DeFi?

AI DeFi protocols can aid better liquidity distribution in the DeFi space by utilizing advanced machine learning technology to identify optimal pools for investment and help market makers properly manage their liquidity pools.

By scanning the market for profitable projects and making AI-enabled estimates of how the projects will perform these AI protocols can enable liquidity providers to get the most out of their staked assets. They also reduce the risk of impermanent loss by continuously monitoring and optimizing the staked assets and readjusting positions when necessary for minimal loss and optimal yield.

Furthermore, these AI tools can provide solutions for market-making models, providing algorithmic strategies that enable proper asset management and distribution. They can help manage liquidity pools, maintain asset ratios, and reduce volatility for a small fee.

Examples of AI Solutions for Liquidity Management

There aren’t many publicly available AI solutions for liquidity management currently. However, Arrakis Finance and Parallax Finance are two great options we highly recommend.

Arrakis Finance

Arrakis Finance is an AI liquidity management tool based on the Uniswap V3 platform. It offers AI-powered asset distribution for liquidity providers, enabling them to maximize their staked liquidity. 

Screenshot of Arrakis Dashboard
Screenshot of Arrakis Dashboard

Arrakis Finance enables you to own multiple liquidity positions in a single pool and monitor your asset’s performance in real-time. It also adjusts your positions to reduce slippage and make the most yield from your deposits.

Parallax Finance

Parallax Finance is a liquidity management solution similar to Arrakis. It prides itself in being the first AI liquidity management algorithm, enabling LPs to yield the most from their liquidity. 

Screenshot of Parallax Finance Dashboard
Screenshot of Parallax Finance Dashboard

Like Arrakis, it is run on the Uniswap V3 platform. It helps liquidity providers extract maximum yield by providing strategies for maximum profitability in real-time market conditions using predictive analytics and dynamic adaption technology. 

Unlock Your Trading Potential: Enhance Your Strategy with AI-Driven Crypto Price Forecasts
Unlock Your Trading Potential: Enhance Your Strategy with AI-Driven Crypto Price Forecasts


Liquidity management is essential to the DeFi ecosystem as it controls asset flow. As expected, a few problems arise when liquidity is managed in a decentralized manner, ranging from slippage to fragmentation. Thankfully, we’ve discussed AI solutions you can leverage to protect your assets from these risks. Hopefully, you can leverage them to make the most yield from your staked liquidity.


How will AI influence DeFi?

AI will influence DeFi in several ways, ranging from prediction-enabled trading to improved liquidity management. AI tools for more efficient decentralized finance are being developed to mitigate the many risks that arise from the budding ecosystem.

How does DeFi provide liquidity?

DeFi provides liquidity through liquidity pools. More often than not, automated market makers manage these pools, ensuring that users’ orders are matched to the right liquidity pool. Furthermore, liquidity providers who stake assets in liquidity pools profit from yields and incentives based on their locked deposits. 

What is AI in liquidity management?

AI in liquidity management refers to using AI for efficient liquidity staking, distribution, and yield farming on decentralized protocols. Protocols like Arrakis Finance and Parallax Finance are examples of AI in liquidity management. 

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