Application of Big Data and Artificial Intelligence in Strengthening Fraud Analytics and Cybersecurity Resilience in Global Financial Markets

Abstract

The exponential growth of global financial markets has been accompanied by an equally significant increase in cyber threats and fraudulent activities. In this digitalized era, financial institutions face mounting challenges in detecting and mitigating fraud, as well as safeguarding their infrastructure against cyberattacks. Big Data and Artificial Intelligence (AI) have emerged as transformative technologies that enable robust fraud analytics and enhance cybersecurity resilience. By leveraging vast datasets and employing intelligent algorithms, financial institutions can detect sophisticated fraudulent patterns, respond proactively to cyber threats, and ensure regulatory compliance. This paper examines the synergistic application of Big Data and AI in global financial markets, focusing on the real-time detection of anomalies, predictive analytics for risk management, and the automation of fraud prevention mechanisms. Additionally, the discussion highlights how these technologies fortify cybersecurity frameworks by enabling advanced threat intelligence, adaptive security protocols, and continuous monitoring. Despite the potential benefits, the paper also addresses challenges such as ethical concerns, data privacy, and the growing sophistication of adversarial attacks. In conclusion, the integration of Big Data and AI is essential for securing global financial markets and sustaining trust in an increasingly interconnected and digitalized economic landscape.