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

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. 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 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. 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.