IDENTIFYING FINANCIAL STATEMENT FRAUD INDICATORS IN NIGERIAN BANKS: EVIDENCE FROM RATIO-BASED BENEISH 8-M-SCORE DIAGNOSTICS

Abstract

This study investigates financial statement fraud (FSF) among BOFI firms listed in the Nigerian capital market using the Beneish M-score model over the study period. The objective is to detect the likelihood of earnings manipulation and identify the key financial indicators driving fraudulent reporting behavior. Secondary data from audited financial statements were analyzed using ratio-based diagnostics, including DSRI, GMI, AQI, SGI, DEPI, SGAI, LVGI, and TATA. The M-score results indicate that a significant proportion of firms exhibit potential manipulation tendencies, suggesting persistent risks of financial misreporting in the sector. Further statistical analysis reveals that DSRI, SGI, DEPI, LVGI, and TATA are significant predictors of FSF, while correlation and mean difference tests confirm structural differences between manipulators and non-manipulators. The findings highlight the importance of financial transparency, stronger regulatory oversight, and improved audit effectiveness in reducing earnings manipulation. The study recommends the integration of fraud detection models into regulatory surveillance systems.