Leveraging Text Mining and Analytical Technology to Enhance Financial Planning and Analysis

Thumbnail Image
Sheu, Yih-Shan
Major Professor
Anthony M. Townsend
Valentina Salotti
Committee Member
Journal Title
Journal ISSN
Volume Title
Research Projects
Organizational Units
Organizational Unit
Information Systems and Business Analytics
In today’s business landscape, information systems and business analytics are pivotal elements that drive success. Information systems form the digital foundation of modern enterprises, while business analytics involves the strategic analysis of data to extract meaningful insights. Information systems have the power to create and restructure industries, empower individuals and firms, and dramatically reduce costs. Business analytics empowers organizations to make precise, data-driven decisions that optimize operations, enhance strategies, and fuel overall growth. Explore these essential fields to understand how data and technology come together, providing the knowledge needed to make informed decisions and achieve remarkable outcomes.
Journal Issue
Is Version Of

Big data technologies have substantially affected various industries. Though data science has been the most valuable evolution in the age of technological innovation, the financial sector is lagging behind other sectors through leveraging data science to evolve quickly and emphasize competency in data analytics. Although big data technology used in financial services, such as FinTech and stock trending models, has grown immensely in the past few years, there is still little research in Corporate Finance. This paper focuses on the big-data technology application in corporate finance via text mining and algorithmic forecasting model. This study aims to answer the following two research questions: (i) How to handle unstructured information to gain an in-depth understanding of qualitative data that will impact the financial performance; (ii) How could machine learning help Corporate Finance acquire better market trend insights and achieve precise sales prediction as well as financial forecasting? In order to answer these questions, a qualitative analysis of literature is carried out comprehensively. Recent research and study indicate that such applications in corporate finance can significantly benefit the corporate decision-making process due to more timely, more relevant, and customer-oriented factors involving qualitative data sources. Finally, the paper briefly discusses the current challenges and limitations and points out the potential future scope of data technology in corporate finance.

Subject Categories
Fri Jan 01 00:00:00 UTC 2021