AI is already widely used in the financial sector as its features and qualities are well-suited for market analysis. This is especially noticeable in crypto trading, which has quickly accepted AI as a valuable tool. There are a few reasons why that’s the case, but there’s a feeling that both technologies are novel and still in their beginning stages.
In this article, we’ll go over a few use cases for AI in crypto trading that are already in place. All of these take advantage of AI’s ability to gather and process data in ways humans aren’t able to.
Real-Time Market Analysis
The value of a crypto asset changes in real-time based on countless outside factors. These include supply and demand, market sentiment, governmental actions, and the overall state of the blockchain network. AI bots are used to gather and analyze these data points in order to come up with market predictions.
The data is then used to help investors make decisions on which cryptos to buy or sell. This means that the trading process isn’t automated, and risky decisions are still left to the investors. They just have a broader base of information to work with when making financial decisions.
Portfolio Risk Management
Crypto portfolios are somewhat similar to traditional stock portfolios. Investors can easily learn how to buy Ethereum or other altcoins and incorporate them into their portfolio of crypto assets. A diverse portfolio hedges against the risks of investing. AI can help create a balance of assets made for growth and stability.
An AI trading bot can be used to assess the assets added to a portfolio and then suggest which to cut, add, or focus on. The investor and portfolio manager can still terms and goals of this assessment, allowing the AI to deal with calculations only.
Fraud Detection
Fraud is a real concern when it comes to digital assets. Even with security measures put in place, they are vulnerable to hacks, and those who have a lot of assets to track can often overlook issues with at least some of them. AI is, therefore, often used to search for patterns so it can spot activities that diverge from them.
AI bots monitor wallet addresses and flag behavior that’s out of the ordinary, such as large transactions or transactions made to unknown addresses. Bots can be used to stop these, alert the users about them, or simply flag them.
Sentiment Analysis
Many factors affect the value of a crypto asset. The most elusive of these is market sentiment, as it depends on assessing the overall feel of an asset. However, changes in the popular sentiment towards a cryptocurrency can be felt in the market.
AI can be used to quantify and analyze this elusive feeling. It does so by keeping track of the overall attitudes about an asset in the most important crypto publications, as well as the chatter found online. For a human analyst, the cacophony of these inputs is too much to follow, but AI bots can review countless such data points simultaneously.
Automated Compliance
The regulations regarding crypto trading are somewhat new, as the whole industry is new. At first, there were no regulations to speak of, but once cryptos became widely used, governments stepped up and introduced safety rules. These are now rapidly changing to accommodate a new approach to the industry, and they differ from one jurisdiction to another.
AI is now often used to automate the compliance process and align trading and investing activity with the most recent regulations. This is most noticeable in using AI to enforce Know Your Customer regulations, as well as Anti-Money-Laundering efforts.
Liquidity Risk Monitoring
For smaller altcoins, liquidity can be one of the most important metrics to follow. It refers to the ability to buy large quantities of a certain currency without affecting its overall price. Altcoins that aren’t liquid can lose value as large purchases are made.
AI systems track the order book depth, as well as other features such as trading volume, spread size, and transaction speeds. When put together, these features paint a picture of how liquid a currency is, providing the user with the data needed to inform decisions.
Stress Test Simulations
AI tools are commonly used to test a portfolio or an investing strategy. They run a simulation of how the portfolio will be done based on the existing information. This allows the investor to test out their ideas without any risk involved.
For example, AI can be used to simulate the effects of a few possible events on a portfolio. These include a major exchange experiencing an outage, a change in regulation, massive liquidation cascades in leveraged trading, and others.
To Sum Up
AI has been found to have many applications in the field of crypto investing. The ability to process large amounts of data and find patterns in it is key to crypto investing, and that’s where AI shines most of all. There’s also a feeling among investors that both crypto and AI are innovative technologies and that using them together is only natural.
At this point, AI is used to assess market sentiment, test out portfolios without risks, and automate compliance with regulations. It can also be used to notify investors of possible fraud and to analyze markets.
