AI-Driven Cybersecurity in Fintech: Leveraging Machine Learning for Threat Detection, Fraud Prevention, and Risk Mitigation

Abstract

intelligence (AI) together with machine learning (ML) functions as a transformative cybersecurity solution which defends against cyber threats and financial risks and fraud cases. The combination of AI and security solutions uses data analysis in real-time together with anomaly detection technology and predictive models to detect and stop threats which include malware, phishing attacks and insider threats. This research investigates how AI supports fintech cybersecurity by explaining its applications to detect threats along with protecting against fraud and minimizing risks. The analysis studies the hurdles that affect AI security systems through data privacy threats alongside AI based discrimination and the requirement for perpetual system maintenance. The paper examines how AI merges with blockchain and quantum computing technologies for setting future directions of cybersecurity practices in the fintech industry. Implementing AI technologies would allow financial institutions to achieve better security measures while improving regulatory compliance and developing stronger cybersecurity infrastructure.