Title: Fraud detection in financial statement: a study using Beneish algorithm

Authors: B.P. Bijay Sankar; Hemant Bhanawat

Addresses: Jatni College, Jatni, Odisha, India ' School of Commerce, NMIMS Deemed to be University, Chandigarh, India

Abstract: The current empirical research study was carried out to forecast earnings manipulation indications of businesses featured on the BSE 100 Index using the probabilistic Beneish M-score 8 variable model. To calculate the M-score, the period restricted from 2011 to 2016 time frame was adopted for the data on investigating financial statements. According to the study's findings, three ratios, namely total accruals to total assets (TATA), Daily Sales Receivable Index (DSRI), and Sales Growth Index (SGI), were used to identify financial manipulation by Indian corporations. The current effort contributes through publishing by identifying potential earnings manipulators of BSE 100 Index listed businesses that investors desire to invest in equities. This should serve as a wake-up call to regulators and legislators to impose strict checks, balances on the auditing of corporations' financial records and advises investors to rely on face validation rather than deception of the underlying worth of the company.

Keywords: earnings manipulation; Beneish M-score; data mining; fraud detection; Indian companies.

DOI: 10.1504/IJMFA.2024.141719

International Journal of Managerial and Financial Accounting, 2024 Vol.16 No.4, pp.380 - 394

Received: 13 Jul 2022
Accepted: 26 Apr 2023
Published online: 01 Oct 2024 *

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