Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.]
Fraud is an illegal activity that does not discriminate. It affects the global economy as well as all types of organizations. Surveys and reports by ACFE, Deloitte, KPMG and NFA confirmed that the public sector is more vulnerable to fraud compared to the private sector. Comments in the Auditor Gener...
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Universiti Teknologi MARA Cawangan Selangor
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Online Access: | http://ir.uitm.edu.my/id/eprint/31140/1/AJ_NOORASLINDA%20ABDUL%20ARIS%20MAR%20B%2017.pdf http://ir.uitm.edu.my/id/eprint/31140/ http://arionline.uitm.edu.my/ojs/index.php/MAR/article/view/666 |
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my.uitm.ir.311402020-06-17T01:50:59Z http://ir.uitm.edu.my/id/eprint/31140/ Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] Abdul Aris, Nooraslinda Othman, Rohana Mohd Bukhori, Muhamad Anas Mohd Arif, Siti Maznah Abdul, Mohamad Affendi HF Commerce Accounting. Bookkeeping Fraud is an illegal activity that does not discriminate. It affects the global economy as well as all types of organizations. Surveys and reports by ACFE, Deloitte, KPMG and NFA confirmed that the public sector is more vulnerable to fraud compared to the private sector. Comments in the Auditor General’s (AG) Report 2012 concluded the same findings. Thus, with respect to fraud, detection, investigation, and preventive measures are extremely important. While anomalies or red flags act as indicators for the auditor, management and other responsible parties to investigate whether there is real fraud, auditing and statistics remain the two primary strategies for detecting fraud. Taking this perspective, Benford’s Law is an advanced digital analysis useful in uncovering anomalies. This paper evaluates 500 accounting data from public sector agencies in Malaysia using theFirst-Digit, Second-Digit, First-Two Digit, First-Three Digit and Last-Two Digit tests. Results show that Benford’s analysis is a credible analytical tool in identifying and detecting suspicious accounts for further scrutiny of fraud incidences in the public sector. This study represents an initial effort to derive a tool to monitor and detect potential fraud incidences or trends, thereby enabling organizations to curb tendencies toward fraud and thus pilot an initiative towards an effective management of fraud risk exposure. Universiti Teknologi MARA Cawangan Selangor 2017-12 Article PeerReviewed text en http://ir.uitm.edu.my/id/eprint/31140/1/AJ_NOORASLINDA%20ABDUL%20ARIS%20MAR%20B%2017.pdf Abdul Aris, Nooraslinda and Othman, Rohana and Mohd Bukhori, Muhamad Anas and Mohd Arif, Siti Maznah and Abdul, Mohamad Affendi (2017) Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.]. Management & Accounting Review, 16 (2). pp. 1-32. ISSN 2550-1895 http://arionline.uitm.edu.my/ojs/index.php/MAR/article/view/666 |
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HF Commerce Accounting. Bookkeeping Abdul Aris, Nooraslinda Othman, Rohana Mohd Bukhori, Muhamad Anas Mohd Arif, Siti Maznah Abdul, Mohamad Affendi Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] |
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Fraud is an illegal activity that does not discriminate. It affects the global economy as well as all types of organizations. Surveys and reports by ACFE, Deloitte, KPMG and NFA confirmed that the public sector is more vulnerable to fraud compared to the private sector. Comments in the Auditor General’s (AG) Report 2012 concluded the same findings. Thus, with respect to fraud, detection, investigation, and preventive measures are extremely important. While anomalies or red flags act as indicators for the auditor, management and other responsible parties to investigate whether there is real fraud, auditing and statistics remain the two primary strategies for detecting fraud. Taking this perspective, Benford’s Law is an advanced digital analysis useful in uncovering anomalies. This paper evaluates 500 accounting data from public sector agencies in Malaysia using theFirst-Digit, Second-Digit, First-Two Digit, First-Three Digit and Last-Two Digit tests. Results show that Benford’s analysis is a credible analytical tool in identifying and detecting suspicious accounts for further scrutiny of fraud incidences in the public sector. This study represents an initial effort to derive a tool to monitor and detect potential fraud incidences or trends, thereby enabling organizations to curb tendencies toward fraud and thus pilot an initiative towards an effective management of fraud risk exposure. |
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Article |
author |
Abdul Aris, Nooraslinda Othman, Rohana Mohd Bukhori, Muhamad Anas Mohd Arif, Siti Maznah Abdul, Mohamad Affendi |
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Abdul Aris, Nooraslinda Othman, Rohana Mohd Bukhori, Muhamad Anas Mohd Arif, Siti Maznah Abdul, Mohamad Affendi |
author_sort |
Abdul Aris, Nooraslinda |
title |
Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] |
title_short |
Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] |
title_full |
Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] |
title_fullStr |
Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] |
title_full_unstemmed |
Detecting accounting anomalies using benford’s law : evidence from the Malaysian public sector / Nooraslinda Abdul Aris … [et al.] |
title_sort |
detecting accounting anomalies using benford’s law : evidence from the malaysian public sector / nooraslinda abdul aris … [et al.] |
publisher |
Universiti Teknologi MARA Cawangan Selangor |
publishDate |
2017 |
url |
http://ir.uitm.edu.my/id/eprint/31140/1/AJ_NOORASLINDA%20ABDUL%20ARIS%20MAR%20B%2017.pdf http://ir.uitm.edu.my/id/eprint/31140/ http://arionline.uitm.edu.my/ojs/index.php/MAR/article/view/666 |
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1685650750121705472 |
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13.211869 |