In recent years, the integration of machine learning (ML) and artificial intelligence (AI) technologies has revolutionized the landscape of digital banking. This review paper synthesizes the current state of research and practical implementations regarding the utilization of ML and AI in digital banking services. Leveraging a comprehensive review of scholarly articles, industry reports, and case studies, this paper examines key applications of ML and AI in enhancing various facets of digital banking, including fraud detection, customer service, risk assessment, personalization, and predictive analytics. Additionally, it explores the challenges and opportunities associated with the adoption of ML and AI in the banking sector, such as data privacy concerns, regulatory compliance, algorithmic biases, and the evolving role of human interaction. By critically analysing existing literature and real-world examples, this paper aims to provide insights into the transformative potential of ML and AI technologies in reshaping the future of digital banking, while also highlighting areas for further research and development.