A Data-Driven Model for Fraud Risk Assessment in Financial Statement Auditing: Empirical Evidence from Iraqi Commercial Banks

Abbas Hakim  Majhool; Ezatollah Abbasian; Islam  Fakher

Authors

Abbas Hakim Majhool Ph.D. student in Finance– Banking, Aras International Campus, University of Tehran, Jolfa, Iran, and Auditor at the Iraqi Federal Board of Supreme Audit, Iraq Author https://orcid.org/0009-0008-4671-542X
Ezatollah Abbasian Professor of Financial Economics, Department of Financial Engineering, Faculty of Management, University of Tehran, Tehran, Iran Author https://orcid.org/0000-0001-8364-6461
Islam Fakher Associate Professor, Department of Financial Management, Shahid Chamran University of Ahvaz, Ahvaz, Iran Author https://orcid.org/0000-0002-5240-2795

Keywords:

Fraud Risk Assessment, Financial Statement Auditing, Iraqi Commercial Banks, Data-Driven Auditing, Panel Data, Audit Quality

Abstract

This study aimed to develop and empirically validate a data-driven model for assessing financial statement fraud risk in Iraqi commercial banks by integrating financial reporting indicators, audit-related signals, and corporate governance characteristics within a longitudinal panel-data framework. A quantitative, applied, longitudinal design was employed using secondary panel data from 18 Iraqi commercial banks over the period 2015–2024, yielding 180 bank-year observations. Fraud risk was modeled using financial statement indicators including accrual intensity, earnings quality, asset growth, revenue growth, changes in receivables relative to revenue, leverage, liquidity, return on assets, and bank size, together with auditor change, modified audit opinion, board independence, and audit committee effectiveness. Pooled OLS, fixed-effects, and random-effects estimators were examined. Model selection was performed using the Hausman test, while multicollinearity, heteroscedasticity, serial correlation, and cross-sectional dependence were assessed through VIF, modified Wald, Wooldridge, and Pesaran CD tests. Robust fixed-effects estimation and temporal out-of-sample validation were applied. The Hausman test supported the fixed-effects specification, , . The final model was statistically significant, , , with a within- . Accrual intensity was the strongest positive predictor of fraud risk, , , followed by changes in receivables-to-revenue, , , modified audit opinion, , , leverage, , , asset growth, , , auditor change, , , and revenue growth, , . Earnings quality, liquidity, profitability, bank size, board independence, and audit committee effectiveness significantly reduced fraud risk. Validation produced an , accuracy of 77.8%, and AUC of .821. The proposed model demonstrated that financial statement fraud risk in Iraqi commercial banks can be effectively assessed through an integrated combination of accounting anomalies, financial pressure indicators, audit signals, and governance mechanisms.

References

Al-Khouri, R. (2021). Corporate Governance and Fraud Risk in Emerging Markets: Evidence from Middle Eastern Banks. Journal of Financial Crime, 28(4), 987-1005.

Al-Salem, F. (2023). Operational Efficiency and Internal Controls in Iraqi Commercial Banks: Implications for Financial Reporting Fraud. Iraqi Journal of Banking and Finance, 12(2), 45-68.

Anderson, E. W., & Fornell, C. (2000). Customer Satisfaction, Productivity, and Profitability: Differences between Goods and Services. Marketing Science, 19(2), 129-145. https://doi.org/10.1287/mksc.16.2.129

Anisykurlillah, A., Setyanto, S., & Wijaya, A. (2025). Audit Quality and Corporate Governance: Effects on Fraud Prevention in Banking Institutions. International Journal of Auditing, 29(1), 112-130.

Baltagi, B. H. (2021). Econometric Analysis of Panel Data (6th ed.). Springer. https://doi.org/10.1007/978-3-030-53953-5

Beasley, M. S. (1996). An Empirical Analysis of the Relation between the Board of Director Composition and Financial Statement Fraud. Accounting review, 71(4), 443-465. https://doi.org/10.2308/TAR-9611271988

Benyasrisawat, B., & Ounlert, N. (2026). Technological Adoption and Fraud Risk Reduction in Emerging Markets. Journal of Financial Innovation, 14(1), 77-95.

DeAngelo, L. E. (1981). Auditor Size and Audit Quality. Journal of Accounting and Economics, 3(3), 183-199. https://doi.org/10.1016/0165-4101(81)90002-1

Francis, J. R. (2004). What Do We Know about Audit Quality? The British Accounting Review, 36(4), 345-368. https://doi.org/10.1016/j.bar.2004.09.003

Kassem, R. (2024). Multi-Dimensional Approaches to Fraud Risk Assessment in Financial Institutions. International Journal of Auditing, 28(2), 99-123.

Kohli, A. K., & Jaworski, B. J. (1993). Market Orientation: The Construct, Research Propositions, and Managerial Implications. Journal of Marketing, 57(3), 1-18. https://doi.org/10.1177/002224299005400201

Kohli, A. K., & Jaworski, B. J. (2021). Revisiting Market Orientation and Its Role in Organizational Transparency and Fraud Prevention. Journal of Strategic Marketing, 29(6), 481-498.

Montgomery, D. C., Peck, E. A., & Vining, G. G. (2021). Introduction to Linear Regression Analysis (6th ed.). Wiley.

Narver, J. C., & Slater, S. F. (1990). The Effect of a Market Orientation on Business Profitability. Journal of Marketing, 54(4), 20-35. https://doi.org/10.1177/002224299005400403

Oliver, R. L. (1999). Whence Consumer Loyalty? Journal of Marketing, 63(Special Issue), 33-44. https://doi.org/10.2307/1252099

Rezaee, Z. (2005). Causes, Consequences, and Deterrence of Financial Statement Fraud. Critical Perspectives on Accounting, 16(3), 277-298. https://doi.org/10.1016/S1045-2354(03)00072-8