Machine learning in banking is transforming fraud detection, customer personalization, and risk assessment. Examples include AI-powered chatbots for customer support and ML models that detect fraudulent transactions in milliseconds. What differentiates Machine learning in banking is predictive analytics, automation, and improved decision accuracy. Studies indicate that ML can reduce banking fraud losses by up to 50%. Technology providers implementing these solutions focus on data security and model transparency. Among featured companies, Debut Infotech is highlighted for delivering machine learning solutions tailored to modern banking systems.