An Evaluation of Big Data Use for Fraud Detection in Hotel Enterprises

Eskin İ., Adamış E.

in: Sustainability, Big Data, and Corporate Social Responsibility- Evidence from the Tourism Industry, Mohammed El Amine Abdelli,Nadia Mansour,Atilla Akbaba,Enric Serradell-Lopez, Editor, CRC, Ghent, Belgium , Florida, pp.1-278, 2022

  • Publication Type: Book Chapter / Chapter Research Book
  • Publication Date: 2022
  • Publisher: CRC, Ghent, Belgium 
  • City: Florida
  • Page Numbers: pp.1-278
  • Editors: Mohammed El Amine Abdelli,Nadia Mansour,Atilla Akbaba,Enric Serradell-Lopez, Editor
  • Bursa Uludag University Affiliated: Yes


The types of fraud encountered in enterprises are mainly classified into asset abuse, corruption, and financial statement fraud. The literature deals with the use of big data to detect these frauds from various sectors’ perspectives. The studies have stated that the data generated in the enterprise’s internal and external environments provides faster access than the database, reliable evidence is obtained by analyzing these data, and this evidence effectively detects fraud. In this study, big data in detecting fraud in hotel businesses is presented within the literature framework. The hotel industry has diverse data generated from management information systems, websites, social media, and blogs. Big data transforms these multiple source data into valuable, meaningful, and processable forms. When big data is interpreted with appropriate analysis techniques, it enables enterprises to manage fraud risks.