In the evolving landscape of financial security, a new battlefront has emerged: synthetic identity fraud powered by Generative Artificial Intelligence (GAI). This paper examines the high-stakes digital duel between fraudsters wielding GAI and the adaptive defense mechanisms of financial institutions. The paper explores how GAI-created synthetic identities challenge traditional fraud detection paradigms with convincing backstories, digital footprints, and AI-generated images. These artificial personas’ unprecedented scale and sophistication threaten to overwhelm existing security infrastructures, potentially compromising the integrity of financial systems and identity verification frameworks. Our analysis reveals large-scale synthetic identity campaigns’ far-reaching economic implications and disruptive potential across multiple sectors. It also investigates cutting-edge countermeasures, including adversarial machine learning, real-time anomaly detection, and multi-modal data analysis techniques. As this technological arms race intensifies, the paper concludes by proposing future research directions and emphasizing the critical need for collaborative initiatives to stay ahead in this ever-evolving digital battlefield.
Keywords: Cybersecurity, Fraud Detection, generative AI, machine learning, synthetic identities
