Expectations, competencies and domain knowledge in data- and machine-driven finance

Expectations about the economy and financial markets are often cast as figments of imaginaries of the future. While the sociology of finance have predominantly dealt with expectation formation in relation to calculative devices used in practices of valuation and prediction, this paper concerns the expectations finance professionals form about their work in data- and machine-driven finance. We examine how high-skilled professionals reflexively form expectations about their work and argue that techno-centric imaginaries of the future of finance tend to create an emphasis on domain-independent data science skills over financial domain knowledge. However, we show that such imaginaries do not necessarily perform the work-related expectations of financial professionals, but are instead challenged and nuanced in reflections about the value of practice-bound domain knowledge and expertise.

Automated summary

This paper examines the expectations finance professionals have about their work in data- and machine-driven finance, and argues that techno-centric imaginaries of the future tend to prioritize data science skills over financial domain knowledge. However, it shows that these imaginaries may not meet the work-related expectations of financial professionals, as they are challenged and nuanced in reflections about the value of practice-bound domain expertise.