The Integration of Artificial Intelligence and Machine Learning in Enhancing Risk Mitigation and Fraud Detection Mechanisms within Financial Trading Platforms

Abstract

The integration of Artificial Intelligence (AI) and Machine Learning (ML) within financial trading platforms has significantly enhanced risk mitigation and fraud detection capabilities. Traditional methods, based on rule-based systems and human oversight, have struggled to keep up with the growing complexity of financial markets and evolving threats. AI and ML technologies offer more dynamic and adaptive solutions, enabling real-time data analysis, predictive analytics, and the automation of key processes like Know Your Customer (KYC) and Anti-Money Laundering (AML). This paper explores the technical foundations and practical applications of AI and ML in financial trading, with a focus on their role in detecting fraud and mitigating risk. AI’s ability to process vast datasets and ML’s predictive models allow for the identification of patterns that may indicate fraudulent activities or market manipulation. Additionally, these technologies improve the accuracy of risk assessments through advanced predictive analytics and AI-driven stress testing. Despite these advancements, challenges such as model interpretability, regulatory compliance, and data security remain. The future of AI and ML in financial trading may involve further integration with blockchain technology and quantum computing, promising even more robust fraud detection and risk mitigation mechanisms.