Machine Learning and Data Science Blueprints for Finance

Chapter 10. Natural Language Processing

Natural language processing (NLP) is a subfield of artificial intelligence used to aid computers in understanding natural human language. Most NLP techniques rely on machine learning to derive meaning from human languages. When text has been provided, the computer utilizes algorithms to extract meaning associated with every sentence and collect essential data from them. NLP manifests itself in different forms across many disciplines under various aliases, including (but not limited to) textual analysis, text mining, computational linguistics, and content analysis.

In the financial landscape, one of the earliest applications of NLP was implemented by the US Securities and Exchange Commission (SEC). The group used text mining and natural language processing to detect accounting fraud. The ability of NLP algorithms to scan and analyze legal and other documents at a high speed provides banks and other financial institutions with enormous efficiency gains to help them meet compliance regulations and combat fraud.

In the investment process, uncovering investment insights requires not only domain knowledge of finance but also a strong grasp of data science and machine learning principles. NLP tools may help detect, measure, predict, and anticipate important market characteristics and indicators, such as market volatility, liquidity risks, financial stress, housing prices, and unemployment.

News has always been a key factor in investment decisions. ...