The rapid digitization of financial services has significantly expanded the scope and complexity of cybersecurity risks. With the rise in sophisticated cyberattacks targeting digital finance platforms, traditional risk assessment methods often fall short in detecting and mitigating threats effectively. Advanced machine learning (ML) algorithms offer a transformative approach to enhancing cybersecurity risk assessment by analysing vast amounts of data, identifying anomalies, and predicting potential vulnerabilities in real time. Machine learning enables dynamic risk assessment by leveraging supervised, unsupervised, and reinforcement learning techniques. Supervised learning models identify known threat patterns, while unsupervised learning detects emerging threats through anomaly detection. Reinforcement learning further optimizes risk mitigation strategies by adapting to evolving attack vectors. These algorithms provide financial institutions with proactive capabilities to assess vulnerabilities, prevent breaches, and safeguard sensitive information. The integration of advanced ML algorithms into cybersecurity frameworks enhances accuracy and scalability. By automating threat detection and response processes, ML minimizes human error and reduces response times, ensuring a robust defense against cyber threats. Additionally, ML-powered tools offer insights into risk trends, allowing organizations to strengthen security policies and infrastructure proactively. Despite its potential, the implementation of ML in cybersecurity risk assessment faces challenges, including the need for high-quality data, regulatory compliance, and algorithmic transparency. Addressing these requires collaboration between data scientists, cybersecurity experts, and policymakers. This article examines the application of advanced machine learning algorithms in cybersecurity risk assessment for digital finance. It explores key techniques, challenges, and case studies, providing actionable insights to strengthen resilience and enhance trust in the digital financial ecosystem.