The rapid evolution of cybercrime tactics poses significant challenges to financial systems worldwide, requiring innovative and adaptive solutions. Traditional cybersecurity measures, while effective against conventional threats, often struggle to mitigate sophisticated attacks such as identity theft, phishing, and account takeovers. Behavioural biometrics, which leverage unique patterns in human behaviour, offer a promising frontier for detecting and preventing cybercrime. Combined with machine learning (ML), these advanced systems enable dynamic threat detection by analysing user interactions, such as keystroke dynamics, mouse movements, and touchscreen gestures, in real-time. From a broader perspective, integrating behavioural biometrics into financial systems provides a continuous and non-intrusive method for authentication and fraud detection. Unlike static measures such as passwords, these systems dynamically adapt to individual user profiles, significantly enhancing security while preserving user experience. ML algorithms further amplify this capability by identifying subtle anomalies indicative of fraudulent behaviour, even in previously unseen attack patterns. Narrowing the focus, this approach has been particularly effective in combating emerging threats like synthetic identity fraud and deepfake-based impersonation. Financial institutions leveraging ML-driven behavioural biometrics have reported substantial reductions in fraud losses and improved operational efficiency. Case studies highlight their application in multi-layered security frameworks, combining biometrics with existing measures for a robust defense against cybercrime. Despite its potential, challenges such as data privacy, ethical concerns, and system scalability must be addressed to ensure widespread adoption. Collaborative efforts between financial institutions, regulatory bodies, and technology providers are essential to maximize the impact of these innovations. By integrating behavioural biometrics and machine learning, financial systems can proactively adapt to the ever-evolving cybercrime landscape, safeguarding assets and trust.