• Dr.Kasala Nageswar Rao

Modern technologies are required for real-time detection and mitigation due to the growing complexity and frequency of financial fraud and cyber threats. Artificial Intelligence (AI) has become a game-changing technology in cyber security and fraud detection, providing improved efficiency, accuracy, and agility in detecting illegal activity. This study investigates how AI-driven strategies, such as machine learning, deep learning, and anomaly detection methods, can be used to counteract cyber threats and fraudulent activity. The usefulness of several AI models, including supervised and unsupervised learning algorithms, neural networks, and natural language processing (NLP) for threat intelligence, in identifying fraud trends, stopping cyber attacks, and reducing false positives is assessed in this study. An adversarial assault, algorithmic biases, and data privacy issues are some of the difficulties that AI-enabled fraud detection presents. This study illustrates the benefits and drawbacks of artificial intelligence (AI) in cyber security and fraud prevention by doing a thorough analysis of the body of existing literature and case studies. The results show that AI improves fraud prevention strategies, automates security procedures, and strengthens real-time threat detection. In order to provide efficient fraud detection and threat mitigation, the study's conclusion offers insights into potential future routes for AI-driven cyber security, highlighting the necessity of strong AI models, improved data security, and ethical AI implementations.

AI fraud detection, cyber security, machine learning.

"ARTIFICIAL INTELLIGENCE IN FRAUD DETECTION AND CYBER SECURITY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.142-145, August-2025, Available :http://www.jetir.org/papers/JETIRHC06019.pdf

"ARTIFICIAL INTELLIGENCE IN FRAUD DETECTION AND CYBER SECURITY", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. pp142-145, August-2025, Available at : http://www.jetir.org/papers/JETIRHC06019.pdf