Since cryptocurrencies are highly volatile, they increase the risks of crypto trading but also make them significantly more profitable than conventional investments.
The market’s price fluctuates throughout the day, so traders can earn a stable income by calculating the fluctuations correctly. Artificial Intelligence and machine learning systems can assist in processing the vast amounts of information needed to calculate the patterns of a dynamic crypto market.
AI is widely used today in markets for stocks, bonds, and conventional assets worth billions of dollars. ML and Al systems were not commonly used earlier in fiat crypto investments, but nowadays the cryptocurrency space actively implements these highly advanced technologies with four different orientations.
Automated cryptocurrency market forecasting
As a decentralized platform, it can rely on the experience of network participants to create peer-to-peer prediction markets. Still, it is reasonably accurate at predicting cryptocurrencies. For instance, The Forecast Foundation, a nonprofit organization, developed a decentralized platform called Augur to give people access to AI-based forecasts.
Another platform, NeuroBot, is built on neural nets, not user experience. By using their input, the application makes cryptocurrency market predictions. Monitoring exchange rate fluctuations allows the system to compare them and predict changes the following day. It is claimed that NeuroBot can detect up to 90% of changes in data. Adding technical and fundamental analysis to the system will improve it.
Such platforms can be of tremendous assistance for novice crypto traders who do not yet have sufficient time to learn everything about the market. Even though predictive platforms cannot provide a comprehensive analysis of the market, they can provide the lion’s share of it with high levels of accuracy.
Al and machine learning for sentiment analysis
Analyzing various indicators is necessary for determining the sentiment of the cryptocurrency market. All articles, blogs, forums, and even comments under them are included in this category. For example, Senno is an Al-based platform that uses blockchain technology and artificial intelligence technologies to automate the analysis and produce the results automatically in a short period. Machine learning is also incorporated into the system.
CryptoScanner has also partnered with Senno as part of this partnership. Trading information is provided by the app, which uses artificial intelligence to forecast market sentiment and improve the strategies of traders.
Making deals with the right parties
The cryptocurrency market lacks liquidity, which is a major problem. The frequent fluctuations in exchange rates make digital currencies an unattractive payment method for businesses. Exchanges and banks typically charge high fees for the difference between supply and demand. Machine-learning platforms such as TradeConnect are being used to solve the problem. Customers can find the right broker and bank directly, pay minimal fees, and transact directly with this platform. Thanks to the side-matching protocol.
The cryptocurrency market is specifically served by companies that develop artificial intelligence platforms. Money Token created Amanda, an artificial intelligence assistant that lends to community members. A virtual assistant will be able to provide cryptocurrency-backed loans and handle loan applications through repayment.
Crypto bots security
Whenever you give someone API keys for your exchanges, you must be careful. Getting a good reputation is only for trusted services. A key identifies your account, which means you can trade through it and withdraw funds using it. The fact that a bot needs API access to the function does not indicate fraud.
Ensure you thoroughly examine each platform before using it. Find out how they secure the site. Set up two-factor authentication to prevent unauthorized access to your account.
Bottom line
With cryptocurrencies on the rise, artificial intelligence is becoming increasingly essential. Having this information is important for everyone. Even in investing, most things we do in our everyday lives are automated nowadays. By combining Al and no-code technology, Al can easily be accessible to non-technical users. An Al platform with no code provides users with an intuitive user interface where AI models can be developed and deployed without writing any code. Because no-code Al platforms require less setup time and consume fewer resources, financial services companies are changing their view of Al adoption. However, not all businesses are suited to use it. If there isn’t a strategy for using AI, it can be even riskier to implement it.
