Modeling of Overdue Receivables in the City Bank Using Factor-based Simulation (Northwestern Provinces of the Country)

Journal of System Management

مقاله 1، دوره 8، شماره 2 - شماره پیاپی 30، شهریور 2022، صفحه 1-18   

نوع مقاله: Research Paper

شناسه دیجیتال (DOI): 10.30495/jsm.2022.1943442.1560

نویسندگان

davoud norouzi¹؛ alireza bafandeh zendeh^{* 2}؛ morteza honarmand azimi³

¹PhD Student, Department of Management, Tabriz Branch ،Islamic Azad University, Tabriz، Iran

²Associate professor, department of management, Tabriz branch ،Islamic Azad University, Tabriz، Iran

³Assistant Professor, department of management, Tabriz branch ،Islamic Azad University, Tabriz، Iran

چکیده

The core goal of this study was to simulate the share and predict the current and non-current receivables in Shahr Bank using an agent-based approach. To this end, we employed the data related to the examined features in 11 bank branches aimed at determining the degree of importance of each of the factors affecting the repayment behavior of borrowers using the C5.0 algorithm, the decision tree method, and the simulation process in NetLogo software. We utilized the comparison of the repayment status of a sample of 100 customers over the past year (12 months ago) and at present aimed at assessing the simulated model. The estimation results of the simulation model, as well as the real findings, suggested that the number of type 1 customers (with active repayment status) has decreased during the last 12 months and the number of type 2 customers (with past due repayment status) has enhanced. If the economic recession conditions continue the same way, and considering the low effect of the recession conditions on the businesses of the bank''s customers in the next four years, then, the ratio of the bank''s current customers will decrease from about 89% to about 81%, while the ratio of the past-due customers of the bank will increase to more than double to about 13%. In the next step, we tried to simulate the future situation of the ratio and the share of the current bank customers'' claims in the next 4 years.

کلیدواژه‌ها

Deferred receivables؛ current and non-current receivables؛ foundation factor simulation

مراجع

Abolhassani, M. (2010). Evaluating the effect of banking sanctions and fluctuations in some economic variables on the volume of deferred foreign currency receivables of the Export Development Bank of Iran. Master Thesis, https://doi.org/10.1108/S1529-213420220000026006.

Akhoondi, B., & Mojarad Alaei, M. (2016). The impact of outstanding receivables on the resistance economy indicators in Iran. The First International Conference on Management Coherence and Economics in Urban Development, Tabriz, Osve University, University. Seyyed Shokri, Khashayar, Graossi, https://doi.org/10.1108/S2514-175920220000005007.

Asgharizadeh, Ezatullah. & Amin, Fereshteh. (2012). Increasing the productivity of banking services by prioritizing customers using quantitative techniques, Quarterly Journal of Economic Policies and Research, No. 36, pp. 5-31, https://doi.org/10.1108/S1746-979120160000012008.

Dermina, D., Shirdel, G., & Iranban, S. (2021). Illustration of the Position of Knowledge-Based Management in Iranian Organizations. Journal of System Management (JSM), Volume 7, Issue 3, Summer 2021, Pages 89-110, https://doi.org/ 10.30495/JSM.2021.1927569.1461.

Gholamian, M., Hakimpour, H., Kafashpour, A., & Mahmoudzadeh, M. (2021), Barriers to the Implementation and Use of Internet Banking in the Keshavarzi Bank. Journal of System Management (JSM), Volume 7, Issue 4, Autumn 2021, Pages 49-67, https://doi.org/10.30495/JSM.2021.1942650.1539.

Hakimipour, N. (2015). Assessing the process of banking factors impact on non-performing receivables of Iranian banks. Dynamic Panel Model Approach, Quarterly Journal of Financial Economics, Year 12, No. 42, pp. 99-119, https://doi.org/10.1108/S1876-066X20180000034003.

Hamdaoui, M., & Makyuf, S., (2019). Financial reforms and banking system vulnerability: The role of regulatory frameworks. Structural change and economic dynamics, Pp1-36, https://doi.org/10.1016/j.strueco.2019.10.007

Heidari, H., Zavvarian, Z., & Nourbakhsh, Iman. (2011). Examining the effect of macroeconomic indices on overdue receivables of banks, Money and Economy Quarterly, No. 4, pp. 191-219, https://doi.org/10.1108/S1745-886220210000015009.

Ibrahim, M., & Eskandar Shah, M. (2012), “Bank Lending, Macroeconomic Conditions and Financial Uncertainty: Evidence from Malaysia”. Review of Development Finance, Vol. 2, Pp.156-164, https://doi.org/10.1108/S1745-886220210000015009.

Kheirkhah, M., Barzegari Khaneghah, J., & Morovati Sharifabadi, A. (2016). Modeling the factors affecting banks'' deferred receivables using system dynamics approach, Quarterly Journal of Economic Research and Policies, Vol. 24, No. 79, pp. 29-54, https://doi.org/10.1108/S1535-120320200000013002.

Kian Mehr, Z., Hakimpour, H., Mahmoodzadeh V. M., & Mohammadi, M. (2021). Designing a Positioning Model for State Banks'' Services and its Validation from the Perspective of External Customers. Journal of System Management, Volume 7, Issue 4, Autumn 2021, Pages 163-182, https://doi.org/ 10.30495/JSM.2021.1942925.1543.

Kordbacheh, H. & Pordel Nooshabadi, L. (2011). Explaining the factors affecting overdue receivables in the Iranian banking industry. Iranian Economic Research Quarterly, Year 16, No. 49, pp. 117-150, https://doi.org/10.1108/S2514-175920220000005007.

Kordbacheh, H. (2011). Explaining the factors affecting overdue receivables in the Iranian banking industry. Iranian Economic Research Quarterly, Year 16, No. 49, pp. 117-149, https://doi.org/10.1108/S1746-979120160000012008.

Mehrabi, L. (2014). Evaluating the status of non-performing receivables in the Iranian banking system and comparing it with other countries with a review of the experiences of other Islamic countries. Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, pp. 1-23, https://doi.org/10.1108/S1529-213420220000026006.

Mehrabian, A., & Seifipour, R. (2016). The pathology of current receivables in the Iranian banking system. Financial Economics Quarterly Journal, Vol 10, No. 36, p. 73-85, https://doi.org/10.1108/S1474-787120150000026005.

Metawa, N. & Kabir, H. and Elhoseny, M. (2017), “Genetic Algorithm Based Model for Optimizing Bank Lending Decisions”, Expert Systems with Applications, Vol (80), Issue C, Pp.75-82, https://doi.org/10.1108/978-1-80117-864-820221002.

Mohammadkhani, M., Divandari, D., Talebi, M., & Amiri, M. (2020), A Systematic Review of Banking Business Models with an Approach to Sustainable Development. Journal of System Management (JSM), Volume 6, Issue 1, Spring 2020, Pages 1-18, https://doi.org/ 10.30495/JSM.2020.673642.

Moradi, Nader. (2014). A proper model for collecting bank receivables, Specialized Quarterly of Collection of Receivables, Volume 2, No. 3, pp. 12-42, https://doi.org/10.1108/S1876-066X20180000034003.

Mukoki, PG., & Mapfumo, A. (2015). The effects of dollarization on the growth of non-performing loans in Zimbabwe banking system: An Autoregressive Distributed Lag (ARDL) Bound Test Approach, Journal of Economics and Sustainable Development, vol. 6 (10), pp.83-90, https://doi.org/10.1108/S2051-231720170000005008.

Ouzis, D. L., Vouldis, A. T., & Metaxas, V. L. (2011). Macroeconomic and bank-specific determinants of non-performing loans in Greece: A comparative study of mortgage, business and customer loan portfolios. Journal of Banking & Finance 36, Pp 1012-1027, https://doi.org/10.1108/S1535-120320200000013002

Paidar, A., Shafiee, M., Avazzadeh, F., & Valipour. (2021). Predicting Banks'' Financial Distress by Data Envelopment Analysis Model and CAMELS Indicators. Journal of System Management (JSM), Volume 7, Issue 3, Summer 2021, Pages 213-240, https://doi.org/ 10.30495/JSM.2021.1935059.1499.

Rahmani, A., Gholamalipour, R., & Abdollahi, Z. (2017). Examining the effect of intra-bank variables on the growth of non-performing receivables in the Iranian banking system, Monetary-Banking Research Quarterly, Vol. 10, No. 31, pp. 57-69, https://doi.org/10.1108/978-1-80117-864-820221002.

Rasouli, S., & Majidi, M. (2015). An analysis of the reasons for the formation of bank arrears and forthcoming solutions. Scientific and Specialized Quarterly of Iran’s General Inspection Organization, Year 7, No. 25, pp. 5-21, https://doi.org/10.1108/S2051-231720170000005008.

Seyyed Shokri, K., & Garossi, S. (2015). Examining the factors affecting the increased non-performing receivables in Iran’s banking system. Quarterly Journal of Economic Sciences, Year 9, No. 31, pp. 95-120, https://doi.org/10.1108/978-1-78973-755-420201011.

Sontake, R. N., & Tiwari, Ch. (2013). Trend Analysis of None Performing Asset in Scheduled Commercial Banks in India. International Journal of Application or Innovation in Engineering & Management (IJAIEM), Vol. 3 (5), pp.2319-4847, https://doi.org/10.1108/978-1-78973-755-420201011.

Taghi Nataj, G. Hassan., & Najaf Pourkordi, H. R. (2014). Evaluation and analysis of reasons for the increase in overdue receivables of a sample bank and strategies for their prevention and reduction. Accounting and Auditing Studies, No. 17, https://doi.org/10.1108/S1474-78712015000002 6005.

Vithessonthi, C., Schwaninger, M., & Matthias O. M. (2016). Monetary policy: bank lending and corporate investment. International Review of Financial Analysis, Pp1-55, https://doi.org/10.1108/S0742-73012020000003 8 004.