FINANCIAL STATEMENT FRAUD DETECTION TECHNIQUES AND PREVENTION MEASURES
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- NGN 3000
Abstract:
This study examines financial statement fraud detection techniques and prevention measures in Abuja, Nigeria. The objectives are to: (1) identify common financial statement fraud schemes, (2) assess the effectiveness of various detection techniques, and (3) evaluate preventive measures. A survey design was adopted to gather data from auditors and financial managers. The sample size, determined using Taro Yamane's formula, ensures statistical robustness. KPMG Nigeria was selected as the case study due to its expertise in forensic accounting. The reliability coefficient score of the survey was 0.89. Findings reveal that advanced analytical techniques, such as data mining and forensic accounting, are highly effective in detecting financial statement fraud. It is recommended that companies in Abuja invest in these techniques and implement stringent internal controls to prevent fraud.
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