Degree Type

Creative Component

Semester of Graduation

Spring 2021

Department

Information Systems and Business Analytics

First Major Professor

Anthony M. Townsend

Second Major Professor

Valentina Salotti

Degree(s)

Master of Science (MS)

Major(s)

Information Systems

Abstract

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.

Copyright Owner

Sheu, Yih-Shan

File Format

PDF

Embargo Period (admin only)

4-9-2021

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