APPLICATIONS OF NATURAL LANGUAGE PROCESSING IN ECONOMICS AND FINANCE

Abstract

Natural Language Processing (NLP) is used to extract desired patterns from unstructured data and to convert the raw data into actionable insights. This capability serves as the foundation for all AI-human interactions in the financial sector. AI systems can gather, analyze, warn, and anticipate data thanks to NLP starting from customer care to risk prevention. This article represents some important applications of NLP in different fields of economics and finance. It is aimed to show how NLP can be beneficial for the industries. The following topics(issues) are discussed here: • how NLP can be helpful when predicting financial trends with stochastic time series, • why financial statements analysis is extremely helpful in accounting, • how to gain the general idea of the content without diving into much details and how it affects one’s decision making process (on the example of FED (Federal Reserve System)), • detection of language (style) change in financial reports (statements) on the example of FOMC (Federal Open Market Committee), • why words can be treated like triggers in finance and what the benefits are. The work is written by using scientific abstraction and a combined examination of different modern applications of the methodology. The level of reliability and validity of the sources through their comprehensive study have been verified. This article substantiates the fact that the limitations of the unstructured data can be overcome by using AI - NLP. Human and artificial intelligence, when skillfully mixed, can lead to better investment decisions and risk management and reducing human error is critical and can help expose the hidden intentions (here: trends, expectations, movements, etc.) of unstructured data.