Journal of Accounting Auditing and Business
Vol 4, No 2 (2021): July Edition

Detecting Fraudulent Financial Reporting Using Artificial Neural Network

Meutia Riany (Universitas Padjadjaran)
Citra Sukmadilaga (Universitas Padjadjaran)
Devianti Yunita (Universitas Padjadjaran)



Article Info

Publish Date
05 Aug 2021

Abstract

This research aims to examine whether Artificial Neural Network (ANN) method can detect fraudulent financial reporting and whether firms are indicated to commit fraudulent financial reporting. The population in this research are firms listed on the Indonesia Stock Exchange in 2019 and companies that are confirmed to have committed fraudulent financial reporting. In total, 506 data sets were obtained through the purposive sampling technique. The data used in this research were obtained from financial statements. ANN method is used as the data analysis method in this research. Ten variables were used as fraud risk indicators to detect fraudulent financial reporting using ANN. Findings indicate that the developed ANN model can detect fraudulent financial reporting in financial statements. The findings of this research contribute to the literature on methods of detecting indications of financial statement fraud and that it can also be used to assist the auditor's role in detecting material misstatements attributable to fraud

Copyrights © 2021






Journal Info

Abbrev

jaab

Publisher

Subject

Economics, Econometrics & Finance Social Sciences

Description

Journal of Accounting Auditing and Business (JAAB) is published by the Center of Accounting Development, Faculty of Economics and Business, Universitas Padjadjaran. JAAB provides opportunities for academicians, professionals, and university students to publish their papers. The publication covers ...