Document Type : Resear Paper (Islamic Public Finance)

Authors

• Ali Aghajani Khorasgani ^{1 ¶}
• Parastoo Mohammadi ²

¹ M. A. Student, Financial Engineering, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

² Faculty Member, Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran

Abstract

1. Introduction and Objective
The escalating issue of non-performing loans (NPLs) presents a significant challenge to the stability and efficiency of banking system in Iran. This paper introduces a novel, multi-faceted decision-making model specifically designed to optimize the process of rescheduling (known as "emhal" in Persian) bank receivables arising from non-performing facilities. The primary objective of this research is to provide Iranian banks and credit institutions with a structured, transparent, empirically informed, and practically applicable framework, meticulously aligned with the executive directive concerning the method of rescheduling receivables of credit institutions, ratified by the Monetary and Credit Council of the Central Bank of Iran on August 6, 2019. This framework aims to guide these institutions in making judicious and data-driven decisions regarding the rescheduling of their receivables portfolios, taking into comprehensive account a wide array of salient financial and operational criteria, with a particular emphasis on facilitating the potential rehabilitation and sustainable recovery of financially distressed borrowing entities, especially within the strategically important yet often economically vulnerable tile and ceramic manufacturing sector of the Iranian economy. The research also seeks to promote a more standardized and less ad-hoc approach to loan rescheduling within the Iranian banking system, thereby contributing to greater efficiency and reduced moral hazard.
2. Methods and Materials
The development of the proposed decision-making model was underpinned by a rigorous and systematically executed multi-stage research methodology. The initial phase involved a comprehensive review of domestic literature on NPL management and international best practices in loan restructuring. To ensure contextual relevance within the Iranian banking environment, the preliminary criteria were validated through a two-round Delphi technique and in-depth interviews with eight experienced banking experts (credit and legal specialists with NPL rescheduling experience and banking instructors). The identified criteria were categorized into three hierarchical groups: (a) initial eligibility criteria for entering the rescheduling process; (b) general financial and operational criteria for credit assessment and future profitability estimation; and (c) specific industry-related criteria tailored to the tile and ceramic sector. The final criteria are presented in Table 1 of the original paper.
The model features three sequential modules: (1) initial eligibility assessment; (2) decision on the rescheduling method (re-installment, extension, renewal, contract conversion) using weighted general criteria; and (3) selection of a new Islamic contract type (if conversion is chosen) using weighted industry-specific and further general criteria. A Likert scale questionnaire administered to the expert panel was used to assign weights to the criteria in Modules 2 and 3, with the reliability of the responses confirmed using Cronbach's alpha. Weighted scoring models were developed in Microsoft Excel, inspired by business failure prediction models like Altman's Z-Score and Ohlson's O-Score. Variables in Module 2 (A, B, C, D) represent the applicant's deviation from the industry average for operating profit margin, sales-to-assets ratio, long-term investment-to-assets ratio, and current installment amount (with a negative coefficient). Variables in Module 3 (M, N, P, R, Q) represent deviations for receivables collection period, export-to-total sales ratio, product quality/diversity, orders/prepayments, and cost of goods sold-to-sales ratio (with negative coefficients for the first and last). A case study involving financial data from listed tile and ceramic companies illustrated the model's practical application.
3. Research Findings
The research successfully developed a three-module decision-making model for bank receivables rescheduling. Module 1 effectively screens applicants based on initial eligibility criteria such as not being subject to Article 141, no prior rescheduling, and the overdue period. Module 2 utilizes the weighted scoring system based on general financial and operational criteria to recommend a rescheduling method. For instance, Table 6 of the paper showed contract extension as the top recommendation for Company X based on its financial performance relative to the industry average. If contract conversion is deemed necessary, Module 3 employs weighted industry-specific and operational criteria to prioritize and recommend the most suitable new Islamic contract type (e.g., Salaf was the highest-ranked in the example provided in the paper). The model provides a structured and data-driven approach for banks to evaluate rescheduling options, aiming to balance debt recovery with the potential rehabilitation of the borrowing entity within the specific context of the tile and ceramic industry.
4. Discussion and Conclusion
The developed decision-making model represents a novel domestic contribution specifically addressing the complex issue of NPL rescheduling within the Iranian banking system, with a targeted focus on the tile and ceramic manufacturing sector. This industry-specific focus enhances the relevance and granularity of the model's recommendations but also limits its direct applicability to other sectors without potential recalibration. The model's adherence to the Central Bank of Iran's directives ensures regulatory compliance while also imposing some constraints on incorporating all expert nuances. The expert-derived weights for financial ratios are integral to the model's calculations. The absence of a comprehensive historical database of rescheduling applicants necessitated a reliance on qualitative methods, specifically expert opinions validated statistically, which influenced the model's design. Future research should focus on developing more detailed recommendations for new contracts, integrating AI and machine learning techniques, designing dynamic policy options for banks, and extending the model's applicability to other industries facing NPL challenges.
 5. Acknowledgments
The authors sincerely thank the esteemed banking experts, particularly Mr. Asghar Pourmatin, for their valuable insights that enriched this research.
JEL Classification: G21, G33.

Keywords

• Decision-Making
• Non-Performing Loans
• Claims Postponement
• Receivables rescheduling
• Islamic Contracts
• Tile and Ceramic Industry

Main Subjects

• Resear Paper (Islamic Public Finance)