Automated Machine Learning and Federated Learning

Summary

Financial services firms still seem to be slow in adopting artificial intelligence (AI). There are three main reasons for this: shortage of data, lack of trust in AI, and shortage of qualified personnel. This chapter examines questions such as what can financial services firms do to accelerate their AI journeys and how can they build explainable models without relying on an army of data scientists, consultants or external vendors. It presents two recent AI innovations, automated machine learning and federated learning, which provide answers to the questions. Automated machine learning increases the productivity of data scientists by reducing the time spent on mundane tasks of model development. Federated learning has been used for text and image prediction on phones and tablets, where training data are privacy sensitive. In financial services, federated learning has been proposed for small business lending, anti‐money laundering transaction monitoring and fraud detection.