Audit Siklus Piutang Berorientasi Risiko: Integrasi Analisis Data Dalam Mendeteksi Salah Saji Laporan Keuangan Perusahaan - Sitti Nur Syafika; Isma Dina; Masyhuri Masyhuri (CV SCRIPTA INTELEKTUAL MANDIRI, 2025)
This study aims to analyze how risk-oriented accounts receivable cycle audits integrated with data analysis can improve the effectiveness of detecting misstatements in company financial statements. The increased complexity of accounts receivable assessment due to post-2020 economic volatility and the implementation of PSAK 71 based on Expected Credit Loss (ECL) requires auditors to use a more adaptive and technology-based approach. With a qualitative-descriptive research design and Multi-Locus Case Study, this study explores the application of Risk-Based Audit (RBA), Audit Data Analytics (ADA), and continuous auditing in several public accounting firms and internal audit units. The results show that digital auditing significantly improves the accuracy of anomaly detection, speeds up analysis, and strengthens the quality of accounts receivable reconciliation. The integration of big data analytics, fraud score models, and computerized accounting information systems expands auditors' ability to identify material risks, including fraud in existence and valuation assertions. In addition, internal audits have proven to play a strategic role in strengthening credit control, collection, and the quality of a company's cash flow. This study confirms that audit digitization and risk-based approaches are important foundations for maintaining the reliability of financial statements and corporate resilience in the digital era.