AI-based Identity Fraud Detection: A Systematic Review

With the rapid development of digital services, personally identifiable information (PII) is increasingly exposed to identity fraud (IDF). The growing use of artificial intelligence (AI)-enabled deepfake technologies has further amplified this threat, enabling fraudsters to produce highly sophisticated counterfeit documents, photos, and videos. There is a pressing need to systematically review IDF detection methods, their limitations, and potential solutions. This paper presents a systematic literature review examining AI-based IDF detection and prevention methods. The review identifies two principal categories of detection approaches, consolidates findings into a taxonomy of AI-based IDF methods, and highlights key insights, open challenges, and emerging trends. This work provides a foundational knowledge base for researchers and practitioners advancing this critical area.