Document Type : Research Paper

Authors

1 Ph.D. Student in Public Administration, Islamic Azad University, Ghaemshahr Branch, Ghaemshahr, Iran

2 Assistant Professor, Department of Management, Islamic Azad University, Ghaemshahr Branch, Ghaemshahr, Iran

3 Associate Professor, Department of Management, Islamic Azad University, Ghaemshahr Branch, Ghaemshahr, Iran

4 Assistant Professor, Department of Economics, Islamic Azad University, Ghaemshahr Branch, Ghaemshahr, Iran

Abstract

The necessity to create stable and transparent economic conditions has made combating money laundering a universal policy on the agenda of parliaments and governments by all countries. This is currently the specific issue of the Iran monetary and banking system. In this regard, the infrastructural approach includes all effective dimensions of international anti-money laundering mechanisms such as Basel Committee indices and recommendations of the Financial Action Task Force, and the experiences of other countries show that applying factors of this approach can enhance Iran monetary and banking system internationally and decreases money laundering risk. In order to identify the challenges in this area and reach a model which includes a set of infrastructural factors in fighting money laundering, this study uses qualitative and quantitative parts; in qualitative part, the criteria raised by experts through face-to-face interviews and multi-stage coding, content analysis, and Fuzzy Delphi method, and in quantitative part, the criteria raised by questionnaire and factor analysis technique, and the RMSEA index have been used for fitting the model. Based on international guidelines, the proposed infrastructural model consists of functional, contextual, and structural dimensions and findings indicate that a systematic application of the proposed model improves the efficiency of anti-money laundering system and helps optimal management of anti-money laundering challenges of banks. In this regard, the relative weights of legal, political, geopolitical, and risk-taking components of the structural dimension highlight the importance and necessity of focusing on this dimension and its components of the Iran banking system.

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Main Subjects

Abolhassani Hastiani, A. , & Daniali, Gh. (2018). Development of a strategic model for preventing money laundering in the country's banking structure. Management of Government Organizations, 6 (4), 11-24. [In Persian]
Arjomand Nejad, A. , Zare Qajari, Fe. & Ghaem Maghami, A. (2017A). Specialized culture of money laundering and terrorist financing. (2nd ed.). Tehran: Tash. [In Persian]
Arjmand Nejad, A. , Zare Qajari, F. , & Ghaem Maghami, A. (2013B). International Standards on Combating Money Laundering and Terrorist Financing (FATF Financial Action Task Force 40 Recommendations). (1nd ed.). Tehran: Tash. [In Persian]
Asadi, B. (2018). Legal investigation of money laundering in the country's banking system. New Banking Studies, 1 (1), 170-151. [In Persian]
Bagheri, F. (2015). Comparative study of money laundering prevention strategies in the Anti-Money Laundering Law and the Merida Convention. Detective, 8 (31), 86-66. [In Persian]
Basel AML Index (2020), (9nd ed.). ranking money laundering and terrorist financing risks around the word, BASEL Institute Governance.
Basel AML index (2018) report, Basel institute on Governance. Homepage, https://baselgovernance.org/
Byrne, B.M. (1994). Structural equation modeling with EQS and EQS/Windows: Basic concepts, applications, and programming. Sage.‏
Choua, S. W., & Chen, P. Y. (2009). The influence of individual differences on continuance intentions of enterprise resource planning (ERP). Int. J. Human.
 Computer Studies, 67 (6), 484–496.
Davari, A. , & Rezazadeh, A. (2013). Structural equation modeling with PLS software. (1nd ed.). Tehran: University Jihad. [In Persian]
Fallahnejad, F. (2017). Money laundering in international documents and Iranian criminal law. Annual Conference on Legal and Judicial Research, September. [In Persian]
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-Graph: Tutorial and annotated example. Communications of the Association for Information systems, 16(1), 5-6.
Ghazavi, H., & Kianizadeh, H. (2015). Investigating the consequences of money laundering and its effects on Iran's economic security. Economic Journal of the Ministry of Economic Affairs and Finance, 6 (55, 56), 103-77. [In Persian]
Gholami, A., & Pourbakhsh, S. (2011). Combating Money Laundering in Iranian Laws and International Documents. Islamic Economics Studies, 4(1), 120-93. [In Persian]
Goldkuhl, G., & Cronholm, S. (2010). Adding theoretical grounding to grounded theory: Toward multi-grounded theory. International journal of qualitative methods, 9(2), 187-205.
Gujarati, D. (1995). Fundamentals of Econometrics, translated by Hamid Abrishami (2004). (1nd ed.). Tehran: University of Tehran. [In Persian]
Klein, K., Becker, J. M., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM: guidelines for using reflective-formative type models. Long range planning, 45(5-6), 359-394.‏
Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In New challenges to international marketing. Emerald Group Publishing Limited.
Hossein Pouri, D. , Madani, J. , Sharifzadeh, F., & Mohagheghnia, M. (2018). Develop an interactive policy framework to combat money laundering in the banking system of the Islamic Republic of Iran. Public Policy, 4(2), 32-9. [In Persian]
Jafarzadeh, S. , & Ghasemi, A. (2019). Evaluation and prioritization of money laundering risk indicators (Case study: Welfare Bank). Investment Knowledge, 8(31), 224-209. [In Persian]
Jayasree, V., & Balan, R. S. (2017). Money laundering regulatory risk evaluation using Bitmap Index-based Decision Tree. Journal of the Association of Arab Universities for Basic and Applied Sciences, (23), 96-102.
Jazayeri, M. (2004). A look at money laundering and related international documents. Trend, Central Bank of the Islamic Republic of Iran 42(43), 215-169. [In Persian]
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling. Psychological methods, 1(2), 130-149.
Madah, M., & Sinaian, M. (2020). Experimental Analysis of Money Laundering Process in Iran (Approach to Structural Equation Methods Based on Minor Squares), Economic Modeling Research, 10(40), 99-122. [In Persian]
Mahjoorian Qomi, F. & Arjmandnejad, A. (2015). Methodology for evaluating technical compliance with the recommendations of the Financial Action Task Force and the effectiveness of the anti-money laundering system. (1nd ed.). Tehran: Central Bank of the Islamic Republic of Iran General management of regulations, bank licenses and anti-money laundering. [In Persian]
McCarthy, K. J., van Santen, P., & Fiedler, I. (2015). Modeling the money launderer: Microtheoretical arguments on anti-money laundering policy. International Review of Law and Economics, (43), 148-155.
Mobini Dehkordi, A. , & Keshtkar Haranki, M. (2014). Investigating the effect of the three-pronged model on social innovation. Innovation Management, 3 (4) ,75-57. [In Persian]
Niknam, M. , & Bidkhori, N. (2017). Legal bases of money laundering in the Iranian banking system. The Second International Congress of Islamic Sciences, Humanities, Tehran, December 1996. [In Persian]
Parvizian, K. , Ghasemi A. (2017). Unreal image of Iran in the mirror of Basel. World Economy, (4063). [In Persian]
Rahbar, F. (2003). Money Laundering and Its effects and consequences, Economic Research, (Special Issue), ( 63), 33-55. [In Persian]
Rahimi, A., Khoeini, Gh. (2015). Combating money laundering in the Islamic Republic of Iran with emphasis on the role of the Court of Audit. Auditing Knowledge, 15(60), 24-5. [In Persian]
Tajali, S. (2011). Combating Money Laundering and Terrorist Financing in Banks, (1nd ed.). Tehran: Arad. [In Persian]
Saamati, M., Shahnazi, R. , & Dehghan Shabani, Z. (2006). Investigating the effect of economic freedom on corruption (Case study with Panel Data approach). Iranian Economic Research, 8(28), 105-87. [In Persian]
Samanipour, H. , Mohammadi, T., Shakeri, A. , & Taghavi, Mehdi (2020). Macro-prudential supervision requirements and its impact on the stability of the Iranian banking system. Financial Economics, 14(52), 26-1. [In Persian]
Selden, L. (2005). On Grounded Theory‐with some malice. Journal of Documentation, 61(1), 114-129.
Sidi, S. (2014). Combating money laundering by focusing on the role of banks and credit institutions. (2nd ed.). Tehran: Eyelid. [In Persian]
Shamloo, B. , Khalili Pachi, A. (2020). Risk-oriented approach of criminal policy against money laundering. Journal of Criminal Law, University of Guilan, 11(23), 152-127. [In Persian]
Tazhibi, F. (2017). Money laundering and methods to combat it. (4nd ed.). Tehran: Jangal. [In Persian]
Timm, F., Zasada, A., & Thiede, F. (2016). Building a reference model for anti-money laundering in the financial sector. In CEUR Workshop Proceedings, (1670), 111-120.
Website of the Financial Information and Anti-Money Laundering Center, Supreme Council for Combating Money Laundering, Ministry of Economic Affairs and Finance, Bita. Available at http://araku.ac.ir . [In Persian]
Website of the Central Bank of the Islamic Republic of Iran, Department for Combating Money Laundering and Terrorist Financing, Bita. Translation of anti-money laundering documents. Available at https://www.cbi.ir/simplelist/8118.aspx . [In Persian]‏