Data science transformation: Transforming a traditional wealth manager to a cutting-edge data-driven company

Charlotte Werger outlines the components necessary to transform a traditional wealth manager into a data-driven business. Charlotte first covers three key areas: customer focus (management, retention, and acquisition), asset management (investment and credit), and operations (risk, compliance, reporting, and technical infrastructure). The future desired state is conceived at this level, upon the foundations of data, driving both operations and decisions.

Charlotte then further partitions these business units to identify the subunits that benefit from automation and efficiency gains or improved performance due to better predictability (machine learning). You’ll participate in an interactive brainstorm to highlight the different kinds of data and techniques that will support their execution and implementation. You’ll also look for synergies across ideas and business units. Bringing this all together, Charlotte concludes with a discussion of feasibility, prioritization, components of execution, people, data, working with limited resources (data and good people are expensive), and infrastructure.