Identification and Ranking of Barriers to the Expected Credit Loss (ECL) Model Implementation in Iranian Banks Using the FAHP and WASPAS Technique

Document Type : Research Paper


1 Ph.D., Department of Accounting, Central Tehran Branch, Islamic Azad University, Tehran, Iran.

2 Associate Prof., Department of Accounting, Central Tehran Branch, Islamic Azad University, Tehran, Iran

3 Associate Prof., Department of Accounting, Imam Hossein University, Tehran, Iran


Objective: The purpose of this research is to identify and quantify the challenges of implementing the expected credit loss (ECL) model in Iranian banks. This model can identify the effects of defaults in earlier periods, which would reduce the volume of banks bad debts.
Methods: The required data was collected mainly through library studies and interviews with those who are experts in the field using the fuzzy Delphi method and in appropriate cases through face-to-face interviews. Finally, the collected data were processed the Fuzzy Analytic Hierarchy Process (FAHP) to identify and rank barriers to implementing the ECL model. And by using the new WASPAS method, the best solutions to eliminate the obstacles to implementing the expected loss model in Iran's banks are proposed.
Results: Results showed that the globalization index of funding is the most important index for the need to implement international standards of financial reporting (IFRS) in Iranian banks. Index of the increased risk of bad debts and the provision for impairment bad debts of Iranian banks are the most important index of the status of existing infrastructure. Appropriate classification group of microfinance and timely provision for impairment bad debts were also identified as the most important consequences of using the credit loss model. Failure to monitor financial statements and other information during repayment is also the most important challenge in implementing this model. Access to reliable information for professional judgment has also been recognized as the most important solution to these challenges.
Conclusion: Banks are required to develop their risk management systems in order to implement the expected loss model, since most of the information needed, like the determination of default probabilities (PD) and internal customer ratings for determining Reserve, is provided by risk management units.


Ahmed, A. S., Takeda, C., & Thomas, S. (1999). Bank loan loss provisions: A reexamination of capital management, earnings management and signaling effects. Journal of Accounting and Economics, 28(1), 1–25.
Anvari Rostai, A.A., Rezaiat, E. (2007). Comparative evaluating of profitability of bank facilities of Islamic contracts by ABC and traditional costing: Export Development Bank of Iran. Journal of Accounting and Auditing Review, 14 (48), 23- 42.(in Persian)
Ball, R. (2006). International Financial Reporting Standards (IFRS): Pros and Cons for Investors. Working Paper, University of Chicago.
Beatty, A. L., & Liao, S. (2011). Do delays in expected loss recognition affect banks’ willingness to lend? Journal of Accounting and Economics, 52(1), 1-20.
Cantrell, B. W., McInnis, J. M., & Yust, C. G. (2014). Predicting Credit Losses: Loan Fair Values versus Historical Costs. The accounting review, 89(1), 147–176.
Cummings, J.R., Durrani, K.J. (2016). Effect of the Basel Accord capital requirements on the loan-loss provisioning practices of Australian banks. Journal of Banking & Finance, 67(2), 23-36.
Dadbeh, F. & Ahmadi, N . (2016). The rules of impairment International Financial Reporting Standard devaluation No. 9 (IFRS9) implementation challenges and potential solutions. a national conference on the role of strategic management accounting and information systems in the economy of resistance, Tehran, Iran. (in Persian)
Edwards, G. A. (2016). Supervisors’ Key Roles as Banks Implement Expected Credit Loss Provisioning. SEACEN Financial Stability Journal, 7, 1-25.
Ernst & Young. (2016). EY IFRS 9 impairment banking survey. /vwLUAssets/ey-ifrs-9-impairment-bankingsurveyseptember-2016/$FILE/ey-ifrs-9-impairment- banking-survey-september-2016.pdf European Banking Authority (EBA). (2016). Report on results from the EBA impact assessment.of.IFRS.9, documents/10180/ 1360107/EBA+Report+on+impact+assessment +of+IFRS9.
Frontczak, R. & Rostek, S. (2015). Modeling loss given default with stochastic collateral. Economic Modelling, 44, 162–170.
Han, C. & Jang, Y. (2013). Effects of debt collection practices on loss given default. Journal of Banking & Finance, 37(1), 21-31.
Huian, M. )2012(. Accounting for Financial Assets and Financial Liabilities According To IFRS9, Economic Sciences, 59 (1), 27-47.
IASB (2014). International Financial Reporting Standard 9 Financial Instruments, Available at:
Korzebar, Sh. (2017). The implementation of the expected credit loss model in banks; International Financial Reporting Standard No. 9, Auditorium Journal, 91, 44-49. (in Persian)
Linsmeier, T. J. (2011). Financial reporting and financial crises: The case for measuring financial instruments at fair value in the financial statements. Accounting Horizons, 25(2), 409–417.
Liong Tong, T. (2014). A Review of the Expected Credit Loss Model of IFRS 9 Financial Instruments. Available at:
Loterman, G., Brown, I., Martens, D., Mues, C. & Baesens, B. (2012). Benchmarking regression algorithms for loss given default modeling. International Journal of Forecasting, 28(1), 161–170.
Moghadasi Nikigeh, M., Hejazi, R., Akbari, M., Dehghan Dehnavi, M. A. (2017). The Effect of Estimating the Equity Value of the Portfolios of Bonding Facilities with the International Financial Reporting Standards Approach (Case Study: An Iranian Bank). Journal of Accounting and Auditing Review, 24 (4), 597-621.(in Persian)
Novoa, A., Scarlata, J., & Sole, J. (2009). Procyclicality and fair value accounting. Working paper, IMF, WP/09/39. Available at: 1/4 1366168.
Rahmani, A. & Taheri, M. (2017). The cost or fair value of the facility, which is more effective than the credit unions of the Iranian banking network? Monetary and Banking Research, 10 (33), 481-507.(in Persian)
Al Saaty, T. (1990). The Analytic Hierarchy Process in Conflict Management. International Journal of Conflict Management, 1(1), 47-68.
Schuermann, T. (2004). What do we know about loss given default? Wharton Financial Institutions Center, Working Paper, No. 04-01.
Seifloo, S. (2016). Designing a Model for Resistive Banking Case Study of Basic Needs Bank. Islamic Economics, 16 (64), 55-85.(in Persian)
Sultanoglu, B. (2018). Expected credit loss model by IFRS 9 and its possible early impacts on European and Turkish banking sector. World of Accounting Science, 20(3), 476-506.
Tschirhart, J., O’Brien, J., Moise, M., & Yang, E. (2007). Bank commercial loan fair value practices. Federal Reserve Board, Washington, DC. Available at: http://www. feds/2007/200729/200729pap.pdf, 2007.
Zavadskas, E.K.; Kalibatas, D.; Kalibatiene, D. (2016). A multi-attribute assessment using WASPAS for choosing an optimal indoor environment. Archives of Civil and Mechanical Engineering,16(1), 76–85.