Financial Data Engineering

Foreword

The common metaphor for data in financial services is that of oil, lifeblood, or more generally life-giving fuel. However, equally important is how firms use this fuel to the benefit of their business. Data is often raw material that needs to be processed, refined and blended before it can be used. How this material is then used in decision-making workflows is a critical differentiator. From strategy formulation, product development down to process implementation, operations and reporting to investors, customers and regulators, how firms manage information can be the difference between thriving, surviving or indeed declining.

The rapid changes in how data is captured, aggregated, distilled, consumed and distributed have led to faster cycle times, new insights and a much more close-knit integration of computer science into business operations. The wide variety of traditional as well as new data sets that often don’t fit the mold of traditional computer science, brings opportunities for business differentiation and provides the burgeoning field of financial data engineering with the raw materials it needs.

This variety has fostered rapid development of data governance and a better appreciation of the various aspects of data quality. Data pipelines do not exist in isolation but are shaped by the context of business goals, external reporting considerations as well as legal and commercial constraints. Cloud transition and the range of data sets, tools and data engineering ...