Leveraging Enterprise Resource Planning, Data Mining, and Data Warehousing for Financial Statement Fraud Detection

Blasius Erik Sibarani (Universitas Media Nusantara Citra, Indonesia)
Rizki Oktavianto (Accounting Study Program, Sekolah Tinggi Ilmu Ekonomi Widya Wiwaha, Indonesia)

LIABILITIES (JURNAL PENDIDIKAN AKUNTANSI)

Financial statement fraud remains a significant concern for companies and stakeholders because it undermines the reliability of financial reporting and damages corporate reputation. Although fraudulent practices may provide short-term benefits, they ultimately erode investor confidence and reduce stakeholder trust. Therefore, effective mechanisms are required to assist auditors in detecting potential fraud in financial reports. Advances in digital information systems offer new opportunities to strengthen fraud detection in the auditing process. In particular, Enterprise Resource Planning (ERP) systems provide integrated organizational data that can help auditors trace transactions and identify irregularities during financial reporting. In addition, data mining techniques enable auditors to analyze large volumes of financial data to uncover hidden patterns, anomalies, and potential fraudulent activities. Data warehouses further support this process by consolidating and organizing data from multiple sources to facilitate comprehensive analysis. This article provides an overview of how ERP systems, data mining, and data warehousing can be utilized as technological tools to enhance the detection of fraudulent schemes in corporate financial reporting.