Bozyiğit F.Kılınç D.2023-03-222023-03-22202225097873https://doi.org/10.1007/978-981-16-8997-0_9https://hdl.handle.net/20.500.14034/848Natural language processing (NLP) is a subfield of artificial intelligence that focuses on extracting meaning from unstructured data. It has become widely used due to advances in information technology and so increasing textual data in recent years. Since a large portion of the available information in the finance domain is in textual form (e.g., reports, contracts, agreements), researchers have increased their scrutiny of using NLP that is necessary to obtain insight from such collections. This chapter synthesizes the recent literature using NLP methods in financial tasks to demonstrate the state of current knowledge and its implications for future studies. Accordingly, we examine the usage of NLP methods under two sections. In the first section, we focus on NLP analysis models to determine financial market dynamics using news and user comments in the digital platforms. In the second section, we discuss NLP methods to detect sensitive user data (e.g., identity number, credit card number, telephone number) in the financial documents. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.eninfo:eu-repo/semantics/closedAccessArtificial intelligenceFinance sectorFinancial market forecastingFinancial organizationLexical analysisNatural language processingPortfolio selectionSemantic analysisSyntactic analysisBook Chapter10.1007/978-981-16-8997-0_91571702-s2.0-85130813834N/A