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The Impact of Big Data on Accounting Practices: Empirical Evidence from Africa

In: Novel Financial Applications of Machine Learning and Deep Learning

Author

Listed:
  • Mandella Osei-Assibey Bonsu

    (Teesside University)

  • Naheed Roni

    (Teesside University)

  • Yongsheng Guo

    (Teesside University)

Abstract

Big data is much more than accounting and financial data. Big data including financial and non-accounting data have become accessible in immense volumes in distinct forms and in real time. The use of big data for accounting is immobile in initial periods. However, academics have predicted that having high-quality accessible and accelerated in real time might lead to more comprehensive financial reporting. Literature on big data is inconclusive, theoretical, and dearth empirical studies and models. This prompted us to explore the impacts of big data on accounting using accountants in an African emerging country, Nigeria. We use multiple regression for 151 responses. The samples were collected using a random sampling method. The results of the evidence show that big data has a positive and significant impact on financial reporting, performance management, corporate budgeting, audit evidence, risk management, and fraud management. Moreover, evidence indicates that while big data significantly impact accounting and auditing of accountants, utilizing the diversity of data volume, data variety, and data velocity significantly enhances it. The study can help accountants, prospective accountants, and accounting graduates hone their competencies in studying and producing big data analytics, which will benefit the industry. Moreover, business institutions of higher learning should create business curriculums that use big data in their offerings. Finally, policymakers can help by establishing governance models for big data to organize its usage and prevent its exploitation.

Suggested Citation

  • Mandella Osei-Assibey Bonsu & Naheed Roni & Yongsheng Guo, 2023. "The Impact of Big Data on Accounting Practices: Empirical Evidence from Africa," International Series in Operations Research & Management Science, in: Mohammad Zoynul Abedin & Petr Hajek (ed.), Novel Financial Applications of Machine Learning and Deep Learning, pages 47-71, Springer.
  • Handle: RePEc:spr:isochp:978-3-031-18552-6_4
    DOI: 10.1007/978-3-031-18552-6_4
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