Harnessing the AI Potential in Crypto-Trading: Case Study of Datrics Solutions for Yanda

Background

Datrics is an end-to-end, low-code AI platform transforming business operations and user experiences by integrating smart ML solutions and achieving automated, data-driven decision-making. The ability of ML systems to analyze big data and provide accurate predictions has proven beneficial in many industries, including trading. With the help of intelligent trend analysis, ML algorithms applied in asset trading can spot the recurring trends, predict price fluctuations, and inform profitable decisions of traders.

Crypto trading is not an exception as this niche of asset trading is enjoying immense popularity among the public. Thus, the potential of using ML algorithms for price dynamics prediction and pattern identification is immense. Yanda, an innovative crypto trading platform, turned to Datrics with a request to automate trading tools and enrich the user experience with data-driven trading signals and analytics. The task set for Datrics was to empower traders without in-depth trading expertise to make data-driven decisions for reaping more profits.

Challenges

Working on the ML system's integration in Yanda, the AI engineering team faced the following challenges:

Inter-exchange price fluctuation. With dozens of crypto exchanges functioning globally, the prices for a particular cryptocurrency may fluctuate slightly, without a universally set rate established across platforms. Such variability of prices complicates ML analysis because of the dataset's heterogeneity.

Trade volume-dependent precision of analysis. The rule of thumb on any exchange says that the asset's price reacts dynamically to the volume of sale/purchase. Thus, the actual price of sale/purchase may differ from the one set by the ML algorithm in case large volumes of assets are traded at the moment.

Solutions

The Datrics team came up with two major solutions to the problems inherent in the trading industry.

Trends analytics

With huge masses of crypto assets traded across the globe every second, traders are often unable to capture the emerging trends and use them profitably. Datrics introduced an innovative ML algorithm for smart trends analysis at Yanda to give traders a better idea of the current state of the market, specific assets, and specific trading periods. With this data at their fingertips, Yanda clients can now detect and predict trends more accurately, generating more profit on data-driven trading activities.

Anomaly detection

The ML algorithm set by Datrics engineers performs real-time data analysis for the global crypto exchange to inform users about any detected anomalies sent via alerts. Anomalies in price dynamics, volumes of trade, or any other trade-related events are detected quickly to empower Yanda users for making decisions based on those market changes.

User Benefits from Smart Trading Tools by Datrics

Yanda was initially created with an overarching goal to make efficient trading more accessible for people, requiring no coding or in-depth tech knowledge. With the help of Datrics, a series of ML solutions were integrated in the platform to enable quicker, more accurate, and more profitable decision-making about trading strategies based on AI-powered data analysis.

Datrics offers competitively fast implementation, ML infrastructure out of the box, fast preparation date, and scheduling. Therefore, cases can be easily integrated as retrainable pipelines in the matter of days.

Before the introduction of predictive analytics and anomaly detection tools by Datrics, Yanda users could find it challenging to identify the right starting point for a deal. After acquiring access to AI analytics of crypto exchange trends and price dynamics, Yanda clients are better placed to make trading decisions.

  • Customized anomaly detection alerts (e.g., currency pairs, specified periods of time, etc.)
  • Signals about profitable starting points for sale/purchase of assets
  • Accurate predictive analytics with advanced ML algorithms
  • Ability to make automated, data-driven decisions with AI support.
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