Big Data and Data Analytics in Accounting: A New Era for the Detection and Prevention of Earnings Management -A case study ACS Holding-

Abstract

The integration of big data and advanced analytics has transformed the accounting profession, providing innovative solutions to the longstanding issue of earnings management. This study examines the potential of these technologies in enhancing financial transparency and safeguarding the integrity of financial reporting. A case study of this research focuses on the ACS Holding, which manages a heterogeneous portfolio of 32 companies across four (4) groups [GIPEC, ENAVA, ENAD, ENPC] and six (6) public enterprises [ENAP, TONIC INDUSTRIE, DIPROCHIM, SOCOTHYD, EN.DIMED, and 3R-SANTE], operating in the fields of chemistry and pharmaceuticals. Through detailed surveys of accounting professionals within these organizations, the study highlights the pivotal role of big data in detecting anomalies and reducing the risks of earnings manipulation. Machine learning algorithms are demonstrated to be highly effective in predicting and identifying fraudulent activities, empowering organizations with actionable insights. The findings emphasize the necessity of adopting these technological advancements and call for regulatory frameworks that ensure their ethical and responsible application. Collaborative efforts between financial experts and data scientists are critical to fully realizing the potential of these tools, paving the way for a new era of ethical, transparent, and accurate financial reporting.