Machine Learning in Digital Wealth Management

Summary

Artificial intelligence (AI) and its subset machine learning (ML) are becoming part of daily business in all business domains. This chapter looks at the application of ML in wealth management. Wealth management covers a large area of financial services processes and products. The process starts with the acquisition of clients through advising on investments to servicing clients by providing related banking and security services. Client experience can be greatly improved by anticipating client needs or providing personalized advice and service through virtual assistants. One of the key issues institutions might face in implementing ML is related to compliance with data privacy regulations. Regulations are complex and different depending on jurisdictions, making it even more difficult to find general purpose algorithms that can be applied across multiple entities, for example. But ML does not need to know the person behind the data, and using anonymous data sets can be enough to find and train good models.