Financial Data Engineering

Chapter 4. Financial Entity Systems

In the last chapter, you learned about financial identifiers and identification systems and their critical role in financial markets. Importantly, before a financial entity can be identified, it must first be extracted and ready for identification. However, in finance, it’s quite common for data to exist in an unstructured format, where entities are not immediately identifiable. In fact, analysts estimate that the vast majority of data in the world exists in unstructured formats, such as text, video, audio, and images. Moreover, it is quite frequent that different identifiers are used to reference the same financial entity across both structured and unstructured data. These factors collectively pose significant challenges when trying to extract value and insights from the data.

To this end, many financial institutions develop systems to extract, recognize, identify, and match financial entities within financial datasets. These systems, which I will call financial entity systems (FESs), constitute the main topic of this chapter. As a financial data engineer, understanding FESs and the challenges they entail is essential in navigating today’s complex financial data landscape.

In the first part of this chapter, I will clarify the notion of financial entities and provide an overview of their various types. Next, I will illustrate the problem of financial entity extraction and recognition using a popular FES called named entity recognition. After ...