Evaluation and ranking of Iranian banks based on financial performance indicators using the BWM-RAPS approach

Authors

1 Department of Industrial Management, Performance Orientation, Karaj Azad University, Karaj, Iran.

2 Department of Research Center, Shiroud Municipality, Mazandaran, Iran.

Abstract
Purpose: This study aims to evaluate and rank the financial performance of banks listed on the Tehran Stock Exchange using a combined BWM–RAPS approach. Given the key role of banks in the capital market, this study is necessary to provide a scientific and reliable framework for decision-making by investors and analysts. This research seeks to provide the most appropriate method for ranking banks based on financial ratios.
Methodology: The present study employs a quantitative and descriptive–analytical approach and examines 5 criteria and 19 financial sub-criteria over the period from 2008 to 2021. The criteria were weighted using the BWM method based on the opinions of 10 expert specialists, and these weights were then applied to the TOPSIS, VIKOR, and RAPS techniques for ranking the banks. The data were calculated and analyzed based on the average financial ratios of the banks.
Findings: The results showed that profitability and efficiency were the most important criteria, with ROA, P/E, and the volume ratio being the most significant sub-criteria. In the final ranking, Parsian Bank ranked first in the TOPSIS and VIKOR methods, while Pasargad Bank ranked first in the RAPS method. Additionally, Shahr Bank exhibited the weakest financial performance across all three methods.
Originality/Value: By integrating BWM and RAPS and comparing them with TOPSIS and VIKOR, this study provides an innovative framework for evaluating bank financial performance. The use of 19 financial ratios and the combination of different MCDM methods distinguish this research from previous studies. Its results can serve as a basis for investor decision-making and for improving banking ranking models in the country.

Keywords

Subjects

 
[1]      Gohari, A., Ahmad, A. Bin, Balasbaneh, A. T., Gohari, A., Hasan, R., & Sholagberu, A. T. (2022). Significance of intermodal freight modal choice criteria: MCDM-based decision support models and SP-based modal shift policies. Transport policy, 121, 46–60. https://doi.org/10.1016/j.tranpol.2022.03.015
[2]      Moradi, M., Yazdifar, H., Eskandar, H., & Namazi, N. R. (2022). Institutional ownership and investment efficiency: Evidence from Iran. Journal of risk and financial management, 15(7), 290. https://doi.org/10.3390/jrfm15070290
[3]      Kolios, A., Mytilinou, V., Lozano-Minguez, E., & Salonitis, K. (2016). A comparative study of multiple-criteria decision-making methods under stochastic inputs. Energies, 9(7), 566. https://doi.org/10.3390/en9070566
[4]      Mareschal, B., & Mertens, D. (1992). Banks a multicriteria, PROMETHEE-based, decision support system for the evaluation of the international banking sector. Journal of decision systems, 1(2–3), 175–189. https://doi.org/10.1080/12460125.1992.10511524
[5]      Gómez-Navarro, T., Garcia-Melón, M., Guijarro, F., & Preuss, M. (2018). Methodology to assess the market value of companies according to their financial and social responsibility aspects: An AHP approach. Journal of the operational research society, 69(10), 1599–1608. https://doi.org/10.1057/s41274-017-0222-7
[6]      Rahiminezhad Galankashi, M., Mokhatab Rafiei, F., & Ghezelbash, M. (2020). Portfolio selection: A fuzzy-ANP approach. Financial innovation, 6(1), 17. https://doi.org/10.1186/s40854-020-00175-4%0A%0A
[7]      Touni, Z., Makui, A., Mohammadi, E., & others. (2019). A MCDM-based approach using UTA-STAR method to discover behavioral aspects in stock selection problem. International journal of industrial engineering and production research, 30(1), 93–103. https://doi.org/10.22068/ijiepr.30.1.93
[8]      Narang, M., Joshi, M. C., Bisht, K., & Pal, A. (2022). Stock portfolio selection using a new decision-making approach based on the integration of fuzzy CoCoSo with Heronian mean operator. Decision making: applications in management and engineering, 5(1), 90–112. https://doi.org/10.31181/dmame0310022022n
[9]      Kumaran, S. (2022). Financial performance index of IPO firms using VIKOR-CRITIC techniques. Finance research letters, 47, 102542. https://doi.org/10.1016/j.frl.2021.102542
[10]    Mohammadreza, M., Mohammadreza, S. M., & Mirseyed Mohammadhasan, I. (2019). Stock portfolio selection with the ELECTRE-TRI method: Review of capabilities, comparison of approaches, and sensitivity analysis, 7(25), 1-32 (In Persian). https://www.sid.ir/paper/388461/fa
[11]    Lombardi Netto, A., Salomon, V. A. P., & Ortiz Barrios, M. A. (2021). Multi-criteria analysis of green bonds: Hybrid multi-method applications. Sustainability, 13(19), 10512. https://doi.org/10.3390/su131910512
[12]    Lamata, M. T., Liern, V., & Pérez-Gladish, B. (2018). Doing good by doing well: A MCDM framework for evaluating corporate social responsibility attractiveness. Annals of operations research, 267(1), 249–266. https://doi.org/10.1007/s10479-016-2271-8%0A%0A
[13]    Petrillo, A., De Felice, F., Garcia-Melón, M., & Pérez-Gladish, B. (2016). Investing in socially responsible mutual funds: Proposal of non-financial ranking in Italian market. Research in international business and finance, 37, 541–555. https://doi.org/10.1016/j.ribaf.2016.01.027
[14]    Bilbao-Terol, A., Arenas-Parra, M., Cañal-Fernández, V., & Jiménez, M. (2016). A sequential goal programming model with fuzzy hierarchies to sustainable and responsible portfolio selection problem. Journal of the operational research society, 67(10), 1259–1273. https://doi.org/10.1057/jors.2016.33
[15]    Guo, S., & Qi, Z. (2021). A fuzzy best-worst multi-criteria group decision-making method. IEEE access, 9, 118941–118952. https://doi.org/10.1109/ACCESS.2021.3106296
[16]    Zhu, D., Hodgkinson, L., & Wang, Q. (2018). Academic performance and financial forecasting performance: A survey study. Journal of behavioral and experimental finance, 20, 45–51. https://doi.org/10.1016/j.jbef.2018.07.002
[17]    Vasant, D. (2005). The Indian financial system and financial market operation. Himalaya publishing house. https://himpub.com/product/the-indian-financial-system-and-financial-market-operation/?utm_source=chatgpt.com
[18] Albanese, R. (1981). Managing: Toward accountability for performance. Richard D. Irwin, Inc. https://cir.nii.ac.jp/crid/1970867909779300527
[19]    Kohler, E. L. (1975). A dictionary for accountants. Prentice-hall. https://books.google.nl/books/about/A_Dictionary_for_Accountants.html?id=H9QiAQAAIAAJ&redir_esc=y
[20]    Poudel, N. P. (1996). Financial statement analysis: An approach to evaluate bank’s performance [Thesis], Economic review. Kathmandu: Nepal rastra bank. https://elibrary.tucl.edu.np/JQ99OgQIizUxyjI9nB0on9OyLkqsGIf4/api/core/bitstreams/c35039c6-192e-4540-b8f5-e5ae09120fed/content
[21]    Mubashir, A., & Bin Tariq, D. Y. (2017). Application of financial ratios as a firm’s key performance and failure indicator: Literature review. Mubashir, afeera and bin tariq, yasir, application of financial ratios as a firm’s key performance and failure indicator: literature review, journal of global economics, management and business research, 8(1), 18–27. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2922992
[22]    Alzayed, N., Eskandari, R., & Yazdifar, H. (2023). Bank failure prediction: Corporate governance and financial indicators. Review of quantitative finance and accounting, 61(2), 601–631. https://doi.org/10.1007/s11156-023-01158-z%0A%0A
[23]    Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
[24]    Wu, Q., Liu, X., Zhou, L., Qin, J., & Rezaei, J. (2024). An analytical framework for the best--worst method. Omega, 123, 102974. https://doi.org/10.1016/j.omega.2023.102974
[25]    van de Kaa, G., Rezaei, J., Taebi, B., van de Poel, I., & Kizhakenath, A. (2020). How to weigh values in value sensitive design: A best worst method approach for the case of smart metering. Science and engineering ethics, 26(1), 475–494. https://doi.org/10.1007/s11948-019-00105-3%0A%0A
[26]    Peykani, P., Emrouznejad, A., & Nouri, M. (2025). Best-Worst multi-criteria decision-making method: A review of the literature. Socio-economic planning sciences, 102345. https://doi.org/10.1016/j.seps.2025.102345
[27]    Ishizaka, A., & Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert systems with applications, 38(11), 14336–14345. https://doi.org/10.1016/j.eswa.2011.04.143
[28]    Urosevic, K., Gligoric, Z., Miljanovic, I., Beljic, C., & Gligoric, M. (2021). Novel methods in multiple criteria decision-making process (MCRAT and RAPS) application in the mining industry. Mathematics, 9(16), 1980. https://doi.org/10.3390/math9161980
[29]    Opricovic, S., & Tzeng, G.-H. (2004). Compromise solution by MCDM methods: A comparative analysis of VIKOR and TOPSIS. European journal of operational research, 156(2), 445–455. https://doi.org/10.1016/S0377-2217(03)00020-1