Machine learning in banking enhances risk assessment, fraud detection, customer segmentation, and personalized financial services. Banks use ML algorithms to reduce fraud losses, automate credit scoring, and optimize loan decisions with up to 90% accuracy. Machine Learning in Banking, including Debut Infotech, helps build advanced ML solutions like anomaly-detection engines, transaction-scoring models, and AI-powered advisory tools. Differentiators include real-time analytics, compliance-ready pipelines, and scalable cloud or on-premise architectures. Examples include predictive loan defaults, AML risk classification, chatbot banking assistants, and personalized product recommendations. With ML adoption accelerating globally, banks achieve improved security, operational efficiency, and customer experience while strengthening data-driven decision-making processes.