Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms

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MOHAMMADI MAHMOOD; Yazdani Shoreh; KHANMOHAMMADI MOHAMMAD HAMED; MAHAM KEYHAN

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Paper Information

Journal: INTERNATIONAL JOURNAL OF FINANCE AND MANAGERIAL ACCOUNTING Year:2020 | Volume:4 | Issue:16 Page(s): 1-12

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Title

Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms

Author(s)

MOHAMMADI MAHMOOD | Yazdani Shoreh | KHANMOHAMMADI MOHAMMAD HAMED | MAHAM KEYHAN | Issue Writer Certificate

Keywords

financial reporting fraud

fraud detection

fraud predictors

classification algorithms

Abstract

In the last decade, high profile financial frauds committed by large companies in both developed and developing countries were discovered and reported. This study compares the performance of five popular statistical and machine learning models in detecting financial statement fraud. The research objects are companies which experienced both fraudulent and non-fraudulent financial statements between the years 2011 and 2016. The results show, that artificial neural network perform well relative to a Bayesian network, Discriminant Analysis, logistic regression and Support vector machine. The results also reveal some diversity in predictors used across the classification algorithms. Out of 19 predictors examined, only nine are consistently selected and used by different classification algorithms: Employee Productivity, Accounts Receivable to Sales, Debt-toEquity, Inventory to Sales, Sales to Total Assets, Return On Equity, Return on Sales, Liabilities to Interest Expenses, and Assets to Liabilities. These findings extend financial statement fraud research and can be used by practitioners and regulators to improve fraud risk models.

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APA: Copy

MOHAMMADI, MAHMOOD, Yazdani, Shoreh, KHANMOHAMMADI, MOHAMMAD HAMED, & MAHAM, KEYHAN. (2020). Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms. INTERNATIONAL JOURNAL OF FINANCE AND MANAGERIAL ACCOUNTING, 4(16), 1-12. SID. https://sid.ir/paper/662971/en

Vancouver: Copy

MOHAMMADI MAHMOOD, Yazdani Shoreh, KHANMOHAMMADI MOHAMMAD HAMED, MAHAM KEYHAN. Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms. INTERNATIONAL JOURNAL OF FINANCE AND MANAGERIAL ACCOUNTING[Internet]. 2020;4(16):1-12. Available from: https://sid.ir/paper/662971/en

IEEE: Copy

MAHMOOD MOHAMMADI, Shoreh Yazdani, MOHAMMAD HAMED KHANMOHAMMADI, and KEYHAN MAHAM, “Financial Reporting Fraud Detection: An Analysis of Data Mining Algorithms,” INTERNATIONAL JOURNAL OF FINANCE AND MANAGERIAL ACCOUNTING, vol. 4, no. 16, pp. 1–12, 2020, [Online]. Available: https://sid.ir/paper/662971/en

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