The relentless rise of financial frauds poses a significant challenge to the global economy, with perpetrators continuously adapting their tactics to exploit vulnerabilities within the financial sector. To counter this ever-evolving threat, the application of advanced technologies has become imperative. In particular, the fusion of Artificial Intelligence (AI) and Machine Learning techniques offers a promising avenue for financial institutions and organizations to fortify their defenses against fraudulent activities. Financial fraud manifests in various forms, including credit card fraud, mortgage fraud, money laundering, and securities manipulation. Perpetrators employ sophisticated techniques, necessitating a proactive and adaptable approach to detection. This paper investigates the pivotal role of AI and machine learning in mitigating financial fraud risks. In this paper, we conduct a comprehensive review of recent advancements in AI-driven financial fraud detection. We delve into high-cited papers from the past years, emphasizing benchmarking results achieved by prominent Machine Learning algorithms.