Pengembangan Model Prediktif Pendeteksi Financial Fraud Berdasarkan Fraud Model Theory

Putri Andini - Program Studi Sarjana Akuntansi Bisnis, Sekolah Tinggi Manajemen PPM, DKI Jakarta
Anava Santoso - Program Studi Sarjana Akuntansi Bisnis, Sekolah Tinggi Manajemen PPM, DKI Jakarta
Kezia Yokbeth Danomira - Program Studi Sarjana Akuntansi Bisnis, Sekolah Tinggi Manajemen PPM, DKI Jakarta
Martdian Sari - PPM School of Management , & Program Studi Sarjana Akuntansi Bisnis, Sekolah Tinggi Manajemen PPM, DKI Jakarta , &
Noveri Maulana - Program Studi Sarjana Manajemen Bisnis, Sekolah Tinggi Manajemen PPM, DKI Jakarta

Abstract


Financial fraud is among the rarest forms, resulting in the greatest organizational losses. Financial and reputational crises are examples of the costs of financial manipulation. In detecting fraud, much research has been carried out regarding the factors driving fraud from the financial aspect. Therefore, this research fills the gap related to the lack of fraud detection by combining financial and non-financial aspects and the absence of a fraud detection model that effectively proves that fraud has occurred. This research uses a quantitative approach using company annual report data for 2018-2022. Analysis was carried out using multiple regression. The results of this research show that Return on Assets (ROA), Debt Equity Ratio (DER), Organizational Ownership (OSHIP), reduction in receivables, earnings growth, and e-procurement are capable of being factors in detecting organizations committing fraud. Based on the results of this research, organizations are expected to be able to implement good systems and controls to prevent fraud, such as maintaining stability, reducing dependence on debt, ensuring appropriate share ownership by insiders, limiting the amount of income from receivables, and implementing a good e-procurement system for reducing the risk of fraud. The results of this research can also help companies develop strategies to detect and prevent financial statement fraud. However, this research is limited to the same industry, namely the pharmaceutical industry.

Keywords


Fraudulent Financial Statement; Fraud Detection Factor; Fraud Detection Model

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DOI: https://doi.org/10.34149/jmbr.v20i3.583

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