The Impact of AI-Driven Algorithms on Trading Efficiency and Market Behavior: A Case Study of Binance Exchange in the Evolving Fintech Landscape
DOI:
https://doi.org/10.63056/Keywords:
Artificial intelligence, algorithmic trading, trading efficiency, market behavior, Binance, FinTechAbstract
One of the biggest uses of technology these days is artificial intelligence. AI took over many industries, one of them being the financial market. With the integration of AI technology in the automation of trading, the rate of trades being processed, and the execution of trades, the markets have become more volatile. This tech is quantifiable and analyzable, but so is the trade of crypto. This study uses the Binance Exchange in the FinTech arena for analyzing the effectiveness of AI. It also analyzes how execution, liquidity, volatility, and market entrants’ confidence is impacted. The method is considered cross-sectional, based on data collected from 350 members of the Binance Exchange. A unified questionnaire quantifying participation in trading, market response, and confidence levels charted the flow of the study. The data were evaluated using Cronbach alpha and SPSS. Surveyed Means were compiled using descriptive statistics and the relationships and influence of the measures were evaluated using Pearson correlation and multiple regression. This study demonstrated that utilization of the AI algorithm positively impacted the efficiency of crypto trading. More specifically their trades executed faster, cost less, and less errors were present in the trading activity. The results also show that AI trading increases liquidity and alters volatility on the Binance exchange, profoundly altering market behavior. The study showed that the use of AI does not directly influence behavior, but rather does so through mediating the effect of efficiency. This suggests that AI modifies behavior primarily through efficiency mechanisms. The conclusions state that AI improves performance, and consequently alters performance on exchanges. The study also cautions about the need of transparency, risk management, and regulation to control systemic risk. The literature on the intersection of AI, FinTech, and crypto market analysis is enriched by this research, allowing practical, actionable insights to a select audience of market participants, exchanges, and regulators.
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Copyright (c) 2025 Muhammad Zahid, Maria Yousaf, Muhammad Waqas Khan (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.







