Fraud risk assessment a conceptual Framework for internal auditors to detect Financial statement fraud

Subject. This article assesses the propensity for material misstatement risk due to unfair actions of persons charged with the financial statements preparation, based on their behavioral traits. Objectives. The article aims to develop a scoring type methodology for identifying the propensity for material misstatement risk due to unfair actions of persons charged with the financial statements preparation. Methods. For the study, we used a multidimensional statistical method of discriminant analysis based on empirical data from an author-conducted survey of 515 employees charged with the financial statements preparation in companies. Results. The article presents a two-stage methodology that helps estimate whether a person has traits associated with a hyperpropensity for financial statements fraud risk. Conclusions and Relevance. The developed methodology for detecting the fraud risk is easy to use. It gives the result in binary form and does not violate the principles of audit ethics. The estimated material misstatement risk due to unfair actions makes it possible to justify the need for appropriate audit procedures when developing a strategy and audit plan.

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Financial Statement Fraud Detection: An Analysis of Statistical and Machine Learning Algorithms

Auditing A Journal of Practice & Theory ◽

10.2308/ajpt-50009 ◽

2011 ◽

Vol 30 (2) ◽

pp. 19-50 ◽

Cited By ~ 71

Author(s):

Johan Perols

Keyword(s):

Machine Learning ◽

Analyst Forecasts ◽

Machine Learning Algorithms ◽

Data Availability ◽

Financial Statement ◽

Support Vector ◽

Classification Algorithms ◽

Employee Productivity ◽

Financial Statement Fraud ◽

Fraud Risk

SUMMARY This study compares the performance of six popular statistical and machine learning models in detecting financial statement fraud under different assumptions of misclassification costs and ratios of fraud firms to nonfraud firms. The results show, somewhat surprisingly, that logistic regression and support vector machines perform well relative to an artificial neural network, bagging, C4.5, and stacking. The results also reveal some diversity in predictors used across the classification algorithms. Out of 42 predictors examined, only six are consistently selected and used by different classification algorithms: auditor turnover, total discretionary accruals, Big 4 auditor, accounts receivable, meeting or beating analyst forecasts, and unexpected employee productivity. These findings extend financial statement fraud research and can be used by practitioners and regulators to improve fraud risk models. Data Availability: A list of fraud companies used in this study is available from the author upon request. All other data sources are described in the text.

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Fraud Risk Factors of Fraud Triangle and the Likelihood of Fraud Occurrence: Evidence from Malaysia

Information Management and Business Review ◽

10.22610/imbr.v6i1.1095 ◽

2014 ◽

Vol 6 (1) ◽

pp. 1-7 ◽

Cited By ~ 9

Author(s):

Shabnam Fazli Aghghaleh ◽

Zakiah Muhammaddun Mohamed .

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Logistic Model ◽

Audit Committee ◽

Financial Statement ◽

Fraud Triangle ◽

Financial Statement Fraud ◽

Fraud Risk ◽

Available Information ◽

Binary Logistic Model

The current research studies the usefulness of Cresseyâ€™s fraud risk factor framework adopted from SAS No. 99 to prevent fraud from occurring. In accordance with Cresseyâ€™s theory, pressure, opportunity and rationalization are existing when fraud occurs. The study suggests variables as proxy measures for pressure and opportunity, and test these variables using publicly available information relating to a set of fraud firms and a sample of no-fraud firms. Two pressure proxies and two opportunity proxies are identified and suggested to be significantly related to financial statement fraud. We find that leverage and sale to account receivable are positively related to the likelihood of fraud. Audit committee size and board of directorsâ€™ size are also linked to decrease the level of financial statement fraud. A binary logistic model based on examples of fraud risk factors of fraud triangle model measures the likelihood of financial statement fraud and can assist experts.

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Financial Statement Fraud Risk Factors of Fraud Triangle: Evidence From Indonesia

International Journal of Financial Research ◽

10.5430/ijfr.v11n4p36 ◽

2020 ◽

Vol 11 (4) ◽

pp. 36

Author(s):

Hasni Yusrianti ◽

Imam Ghozali ◽

Etna Yuyetta ◽

Aryanto Aryanto ◽

Eka Meirawati

Keyword(s):

Risk Factors ◽

Financial Stability ◽

Stock Exchange ◽

Secondary Data ◽

Financial Statement ◽

Company Size ◽

Fraud Triangle ◽

Financial Statement Fraud ◽

Fraud Risk ◽

Industry Risk

The purpose of this study is to examine the risk factors that influencing financial statement fraud. Especially, it examines the influence of rationalization, pressure, and opportunity on the fraudulent financial statements and also examines the interaction effect of industry risk and company size on the relationship between rationalization, pressure, and opportunity on financial statement fraud. Secondary data were collected from Bloemberg Data Base, IDX and OJK RI. The population in this study is companies listed on the Indonesia Stock Exchange in the moving year from 2011 to 2017 and the sample was selected by companies that indicated financial statement fraud and those that did not indicate financial statement fraud. The company indicated by Fraud was collected from Bapepam and OJK RI. Data were tested using logistic regression analysis and different T-tests of 28 committed fraud companies and 28 companies that did not commit fraud. The results showed that only some variables had a significant effect on financial statement fraud, namely financial stability (ACHANGE), Financial Target (ROA), and the Nature of Industry (ARCHANGE). The results also show that company size and industry risk do not moderate the fraud factors on financial statement fraud. These results support the fraud triangle theory in explaining the phenomena of financial statement fraud.

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Dickinson Technologies, Inc.: Assessing Control Environment and Fraud Risk

Issues in Accounting Education ◽

10.2308/iace.2003.18.1.71 ◽

2003 ◽

Vol 18 (1) ◽

pp. 71-78 ◽

Cited By ~ 6

Author(s):

Christopher P. Agoglia ◽

Kevin F. Brown ◽

Dennis M. Hanno

Keyword(s):

Risk Assessment ◽

Internal Control ◽

Financial Statement ◽

Risk Assessments ◽

Background Information ◽

Control Environment ◽

Abstract Concepts ◽

Fraud Risk ◽

Financial Statement Audit ◽

Fraud Risk Assessments

This instructional case provides you an opportunity to perform realistic audit tasks using evidence obtained from an actual company. Through the use of engaging materials, the case helps you to develop an understanding of the control environment concepts presented in SAS No. 78 (AICPA 1995), Consideration of Internal Control in a Financial Statement Audit, and fraud risk assessment presented in SAS No. 99 (AICPA 2002), Consideration of Fraud in a Financial Statement Audit. This case involves making a series of fraud risk assessments based on company background information and a detailed and realistic control environment questionnaire, which provide you a context that makes the often abstract concepts relating to control environment and fraud risk assessment more concrete.

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Internal Audit Structure and Fraud Risk Assessment From a Regulatory Perspective

Organizational Auditing and Assurance in the Digital Age - Advances in Finance, Accounting, and Economics ◽

10.4018/978-1-5225-7356-2.ch015 ◽

2019 ◽

pp. 302-332

Author(s):

Lale Aslan

Keyword(s):

Risk Assessment ◽

Portfolio Management ◽

Internal Audit ◽

Internal Auditors ◽

Fraud Risk ◽

Critical Areas ◽

Regulatory Perspective ◽

Descriptive Approach ◽

Audit Standards

This chapter aims to depict the role of internal audit in Turkish capital markets by comparing the internal audit structure and its role in detecting fraud in financial institutions and developing a framework for assessing fraud risk in intermediary institutions. The newly constructed regulations concerning banks, intermediary institutions, and portfolio management companies are compared to a global benchmark by using a conceptual and descriptive approach. According to the results of this comparison, it is clear that Turkish legislation needs to be improved in critical areas. “Integrity” should be incorporated as a founding concept of the internal audit function. Certification of internal auditors needs to be encouraged, and internal audit standards need to be adapted. As a result, a fraud risk assessment template influenced by the new regulatory framework is developed for intermediary institutions.

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