NatWest, one of the leading banks in the UK, serves millions of customers and boasts a strong presence in business banking. With a dedicated team focused on machine learning, they have developed around 3,000 models in various stages of development and production. To ensure the successful deployment of machine learning models, NatWest follows a comprehensive process that includes data collection, configuration, verification, feature extraction, hosting, risk management, and monitoring.
Recognizing the importance of efficient machine learning operations (MLOps), NatWest embarked on their MLOps journey two years ago. They aimed to tackle challenges related to governance, data management, and the need for faster solution delivery. To achieve these goals, NatWest has implemented standardized templates and adopted tools like AWS Service Catalog, SageMaker Studio, and Triera. These technologies have facilitated automation and streamlined the entire machine learning lifecycle, encompassing environment setup, model development, tracking, monitoring, and even bias detection.
